SLGD WORK PLAN
April 2013
Final (Approved)
Revised June 2018
This document was prepared for the United States Agency for International Development. 
It was prepared by The Mitchell Group, Inc. (TMG)
SAHEL RESILIENCE LEARNING 
(SAREL)
RISE Midline Quantitative 
Survey Report
This document was prepared for the United States Agency for International Development, 
Contract No. AID-625-C-14-00002 Sahel Resilience Learning (SAREL) Project.
Prepared by: 
The Mitchell Group, Inc. with the support of the Centre d’Etudes Economiques et Sociales de 
l’Afrique de l’Ouest (CESAO)
Principal contacts:
Steve Reid, Chief of Party, SAREL, Niamey, Niger, sreid@sarelproject.com
Jenkins Cooper, Vice President Operations, TMG, Inc., Washington, DC, jenkinsc@the￾mitchellgroup.com
Implemented by:
The Mitchell Group, Inc.
1816 11th Street, NW
Washington, DC 20001
Tel: 202-745-1919
The Mitchell Group, Inc.
SAREL Project
behind ORTN
Quartier Issa Béri
Niamey, Niger
SAHEL RESILIENCE LEARNING 
PROJECT (SAREL)
RISE Midline Quantitative Survey Report
Final (Approved)
Revised June 2018
DISCLAIMER
The author’s views expressed in this publication do not necessarily reflect the views of the United 
States Agency for International Development or the United States Government
Sahel Resilience Learning (SAREL)—RISE Midline Quantitative Survey Report
Revised June 2018 i
Table of Contents
Table of Contents __________________________________________________________ i
List of Tables ______________________________________________________________iv
List of Figures_____________________________________________________________ vii
List of Acronyms ___________________________________________________________ x
Executive Summary_________________________________________________________ xii
1. Introduction___________________________________________________________ 1
1.1. Overview of the RISE Program ______________________________________________ 3
1.1.1. Specific RISE Objectives __________________________________________________ 4
1.1.2. Coverage and Target Groups ______________________________________________ 6
1.2. Overview of the Midline Study ______________________________________________ 7
2. Methodology __________________________________________________________ 9
2.1. Data Collection _________________________________________________________ 9
2.1.1. Data Collection Objectives _______________________________________________ 9
2.1.2. Questionnaire Description_______________________________________________ 10
2.1.3. Sampling ____________________________________________________________ 11
2.1.4. Enumerator Training ___________________________________________________ 13
2.1.5. Number of Households Covered __________________________________________ 14
2.1.6. Sampling Weights _____________________________________________________ 15
2.1.7. Difficulties Encountered during Data Collection _______________________________ 15
2.2. Exploitation of the Data Collected __________________________________________ 16
2.2.1. Data Processing_______________________________________________________ 16
2.2.2. Analytical Methodology for Statistical Analyses ________________________________ 17
2.2.3. Report Preparation ____________________________________________________ 20
2.3. Methodological Notes and Limitations________________________________________ 20
2.3.1. Original Baseline Results vs. Recalculated Baseline Results ________________________ 20
2.3.2. Limitations to the Evaluation Methodology ___________________________________ 22
2.3.3. Limitations to the RISE Study Design _______________________________________ 23
3. Household and Village Descriptions _________________________________________ 24
3.1. Demographic Characteristics of Respondents __________________________________ 24
3.1.1. Structure of Respondents by Sex __________________________________________ 24
3.1.2. Population Age Trends__________________________________________________ 24
3.1.3. Population Age Structure (Women/Men) ____________________________________ 25
3.1.4. Relationship to Head of Household ________________________________________ 25
3.1.5. Marital Status of Population Aged 12 or Over _________________________________ 26
Sahel Resilience Learning (SAREL)—RISE Midline Quantitative Survey Report
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3.2. Household Characteristics ________________________________________________ 26
3.2.1. Size and Composition of Households _______________________________________ 26
3.2.2. Characteristics of Heads of Household ______________________________________ 27
3.2.3. Literacy by Language ___________________________________________________ 28
3.2.4. Education Levels ______________________________________________________ 29
3.3. Home Features and Construction ___________________________________________ 29
3.3.1. Main Housing Characteristics _____________________________________________ 29
3.3.2. Building Materials for Dwelling Structures ____________________________________ 30
3.3.3. Main Housing Flooring Type______________________________________________ 31
3.4. Drinking Water Supply___________________________________________________ 31
3.5. Types of Toilets Used by Households ________________________________________ 33
3.6. Livestock Headcount ____________________________________________________ 33
3.7. Farmlands ____________________________________________________________ 33
3.8. Sources of Household Revenue_____________________________________________ 34
3.9. Exposure to Shocks _____________________________________________________ 35
3.9.1. Exposure to Shocks over the Previous Twelve Months __________________________ 36
3.9.2. Types of Shocks Experienced over the Previous Twelve Months ___________________ 36
3.9.3. Perceived Impact of Shocks ______________________________________________ 38
3.9.4. Shock Recovery and Coping______________________________________________ 38
4. Economic Well-Being / Livelihoods _________________________________________ 42
4.1 Prevalence of Poverty (Indicator 4) __________________________________________ 43
4.2. Depth of Poverty (Indicator 1) _____________________________________________ 45
4.3. Average Value of Household Assets (Indicator 3.a)_______________________________ 49
4.4. Asset Ownership (Indicator 3.b) ____________________________________________ 51
4.5. Non-Agricultural Sources of Household Income (Indicator 6) ________________________ 52
4.6. Propensity score matching for Livelihoods indicator________________________________ 57
5. Governance __________________________________________________________ 58
5.1. Communities with Evidence of Good Governance (Indicator 7) _______________________ 59
5.2. Communities with Adequate Capacity to Manage Climate Shocks (Indicator 8) ___________ 62
5.3. Individual Engagement with Local Power Structures (Indicator 9) _______________________ 64
6. Health and Nutrition____________________________________________________ 67
6.1. Prevalence of Moderate or Severe Hunger(Indicator 2) ____________________________ 69
6.2. Global Acute Malnutrition (GAM) Rate (Indicator 10) ____________________________ 70
6.3. Stunting Among Children Under 5 Years of Age (Indicator11) ______________________ 74
6.4. Underweight among children under 5 (Indicator 12) _______________________________ 78
6.5. Improveddrinkingwatersources(Indicator 13) __________________________________ 80
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6.6. Soap-and-waterhandwashingstations(Indicator14)_______________________________ 81
6.7. Improved sanitation systems(Indicator 15) _____________________________________ 83
6.8. Household dietary diversity (Indicator 16) ______________________________________ 87
6.9. Minimumacceptablediet(MAD)amongchildren6-23months of age (Indicator 17)__________ 91
6.10. Exclusive breastfeeding of children under 6 months of age (Indicator 18) _______________ 93
6.11. Propensity score matching for health and nutrition indicators _______________________ 95
7. Cross-Cutting Components_______________________________________________ 96
7.1. Women’s empowerment in agriculture index (Indicator 5) _________________________ 97
7.2. Supportfor equal accessformales and females(Indicator 19) _________________________ 98
7.3. Women reporting effective participation (Indicator 20)_____________________________ 100
8. Summary of Demographic Correlates: Gender, Literacy, and Ethnicity of Household Heads 106
9. Complementary Analysis Regarding Family Planning in the RISE Zone________________ 108
10. Lessons Learned and Recommendations_____________________________________ 113
10.1. Technical Lessons and Recommendations________________________________________ 113
10.2. Technical Lessons Learned _________________________________________________ 113
10.3. Recommendations Regarding the Technical Aspects _________________________________ 114
10.4. Administrative Lessons and Recommendations ____________________________________ 115
10.5. Administrative Lessons Learned ______________________________________________ 115
10.6. Recommendations Regarding Administrative Aspects ________________________________ 116
11. Conclusion__________________________________________________________ 118
Appendix A. SAREL Methodological Guidelines for Measuring RISE Indicators _____________ 119
Appendix B. WHO Height and Weight Standards __________________________________ 164
Appendix C. Baseline Survey Questionnaires _____________________________________ 183
C1. Household Questionnaire ________________________________________________ 184
C.2: Gender Questionnaire__________________________________________________ 253
C.3: Household Food Consumption Survey & Child Anthropometry Questionnaire _________ 267
C.4: Village Questionnaire___________________________________________________ 299
Appendix D. Midline Sample Villages ___________________________________________ 334
Appendix E1. Scope of Work – Data Collection ___________________________________ 341
Appendix E2. Scope of Work Data Analysis ______________________________________ 352
Sahel Resilience Learning (SAREL)—RISE Midline Quantitative Survey Report
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List of Tables
Table 2-1: Sampling Weights for Households and Villages in the RISE Zone ________________ 12
Table 3-1: Population Distribution by Sex_________________________________________ 24
Table 3-2: Average and Median Age by Sex________________________________________ 24
Table 3-3: Relationship to Head of Household _____________________________________ 25
Table 3-4: Marital Status of the Population ________________________________________ 26
Table 3-5: Household Size____________________________________________________ 26
Table 3-6: Distribution of Heads of Households by Selected Characteristics and Sex__________ 27
Table 3-7: Local Language Literacy______________________________________________ 28
Table 3-8: Foreign Language Literacy ____________________________________________ 29
Table 3-9: Number of Rooms and the Overcrowding Rate ____________________________ 30
Table 3-10: Wall-Building Materials for Dwelling Structures____________________________ 30
Table 3-11: Roof-Building Materials for the Main Housing _____________________________ 31
Table 3-12: Flooring Materials in Dwelling Structures ________________________________ 31
Table 3-13: Main Source of Households’ Drinking Water Supply ________________________ 32
Table 3-14: Average Water Collection Time in Minutes ______________________________ 32
Table 3-15: Average Number of Livestock Owned by Households _______________________ 33
Table 3-16: Breakout of farmlands by type ________________________________________ 33
Table 3-17: Average Area of Land Owned by Households _____________________________ 34
Table 3-18: Main Activities by Age Group_________________________________________ 35
Table 3-19: Shock Distribution over the Previous Twelve Months (%) ____________________ 36
Table 3-20: Shocks sustained over the previous 12 months in RISE zone (percentage) _________ 37
Table 3-21: Perceived Impact by Type of Shock (%)__________________________________ 38
Table 3-22: Recovery by Type of Shock __________________________________________ 38
Table 3-23: Strategies employed by surveyed households to cope with shocks in previous 12 months 
(as percentage of all strategies listed) ________________________________________ 39
Table 4-1: T-test comparison between baseline and midline results by stratum for prevalence of 
poverty _____________________________________________________________ 44
Table 4-2: Depth of poverty by stratum __________________________________________ 45
Table 4-3: T-test comparison between baseline and midline results by stratum for poverty depth_ 49
Table 4-4: Average value of household assets by stratum______________________________ 50
Table 4-5: T-test comparison between baseline and midline results by stratum ______________ 50
Table 4-6: T-test comparison between baseline and midline results by stratum for number of 
household assets_______________________________________________________ 51
Sahel Resilience Learning (SAREL)—RISE Midline Quantitative Survey Report
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Table 4-7: Proportion of households with income from non-agricultural sources by type and stratum
53
Table 4-8: T-test comparison between baseline and midline results by stratum for household income 
sources _____________________________________________________________ 56
Table 5-1: T-test comparison between baseline and midline results by stratum for evidence of good 
governance___________________________________________________________ 61
Table 5-2: T-test comparison between baseline and midline results by stratum for adequate climate 
shock and risk management capacity ________________________________________ 63
Table 5-3: T-test comparison between baseline and midline results by stratum ______________ 65
Table 6-1: T-test comparison between the baseline and midline results by stratum for moderate/severe 
hunger ______________________________________________________________ 69
Table 6-2: T-test comparison between the baseline and midline results by stratum for GAM ____ 73
Table 6-3: T-test comparison between the baseline and midline results by stratum for stunting __ 77
Table 6-4: T-test comparison between the baseline and midline results by stratum for underweight79
Table 6-5: T-test comparison between the baseline and midline results by stratum for improved 
drinking water sources __________________________________________________ 81
Table 6-6: T-test comparison between the baseline and midline results by stratum for hand washing 
station ______________________________________________________________ 82
Table 6-7: T-test comparison between the baseline and midline results by stratum for improved 
sanitation system ______________________________________________________ 87
Table 6-8: Average household dietary diversity score by stratum ________________________ 88
Table 6-9: T-test comparison between the baseline and midline results by stratum dietary diversity90
Table 6-10: T-test comparison between the baseline and midline results by stratum for MAD ___ 92
Table 6-11: T-test comparison between the baseline and midline results by stratum for exclusive 
breastfeeding _________________________________________________________ 95
Table 6-12: Propensity score matching for the GAM, prevalence of stunting and prevalence of 
breastfeeding. _________________________________________________________ 95
Table 7-1: Average village level WEAI score by stratum and RISE zone of each country________ 98
Table 7-2: T-test comparison between baseline and midline results by stratum for WEAI ______ 98
Table 7-3: Proportion of households that agree that males and females should have equal access to 
social, political, and economic opportunities by household type _____________________ 99
Table 7-4: T-test comparison between baseline and midline results by stratum for equal access _ 100
Table 7-5: Proportion of women with effective decision-making power, by activity type_______ 102
Table 7-6: Proportion of women with effective decision-making power, by Strata and by Country 
related to Food production: crops primarily grown for household consumption ________ 103
Table 7-7: Proportion of women with effective decision-making power, by Strata and by Country 
related to Cash crops: crops primarily grown for sale in markets ___________________ 103
Sahel Resilience Learning (SAREL)—RISE Midline Quantitative Survey Report
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Table 7-8: Proportion of women with effective decision-making power, by Strata and by Country 
related to Livestock ___________________________________________________ 103
Table 7-9: Proportion of women with effective decision-making power, by Strata and by Country 
related to Non-agricultural economic activities: small business, self-employment, purchase and 
sale _______________________________________________________________ 103
Table 7-10: Proportion of women with effective decision-making power, by Strata and by Country 
related to salaried employment: work in kind or monetary in agriculture and other paid work
104
Table 7-11 : Proportion of women with effective decision-making power, by Strata and by Country 
related to fishing and fish ponds___________________________________________ 104
Table 7-12: T-test comparison between baseline and midline results by stratum ____________ 104
Table 9-1: Women’s awareness of methods a couple may use to delay or avoid pregnancy ____ 108
Table 9-2: Women’s awareness of methods a couple may use to delay or avoid pregnancy ____ 109
Table 9-3: Percentage of women taking actions/using methods to delay or avoid pregnancy ____ 110
Table 9-4: Percentage of women taking actions/using methods to delay or avoid pregnancy ____ 111
Sahel Resilience Learning (SAREL)—RISE Midline Quantitative Survey Report
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List of Figures
Figure 1-1: Map of the RISE Study Area __________________________________________ 6
Figure 2-1: Sample of Villages included in RISE Midline Survey by Stratum __________________ 12
Figure 2-2: Hypothetical changes in a Difference-in-Difference Analysis ___________________ 18
Figure 2-3: Hypothetical Difference-in-Differences Analysis ____________________________ 19
Figure 3-1: Population Age Structure ____________________________________________ 25
Figure 3-2: Heads of Household by Marital Status and Sex _____________________________ 28
Figure 3-3: Population's Educational Attainment by Sex _______________________________ 29
Figure 3-4: Structure of the Population Aged 12 and older by Main Activity ________________ 34
Figure 3-5: Main Activities by Age Group _________________________________________ 35
Figure 4-1: Change in the prevalence of poverty from baseline to midline by stratum _________ 45
Figure 4-2: Depth of poverty by RISE zone of each country ____________________________ 46
Figure 4-3: Depth of Poverty: Sex of Head of Household______________________________ 47
Figure 4-4: Depth of Poverty: Marital Status of Head of Household ______________________ 47
Figure 4-5: Depth of Poverty: Literacy Status of Head of Household______________________ 48
Figure 4-6: Depth of Poverty: Ethnicity of Head of Household __________________________ 48
Figure 4-7: Change in the depth of poverty from baseline to midline by stratum _____________ 49
Figure 4-8: Average value of household assets by RISE zone of each country________________ 50
Figure 4-9: Change in the average value of household assets from baseline to midline by stratum _ 51
Figure 4-10: Change in the number of household assets from baseline to midline by stratum ____ 52
Figure 4-11: Proportion of households with income from non-agricultural sources by RISE zone of 
each country _________________________________________________________ 54
Figure 4-12: Income from non-agricultural Sources: Sex of Head of Household ______________ 54
Figure 4-13: Income from non-agricultural Sources: Marital Status of Head of Household ______ 55
Figure 4-14: Income from non-agricultural Sources: Literacy Status of Head of Household______ 55
Figure 4-15: Income from non-agricultural Sources: Ethnicity of Head of Household __________ 56
Figure 4-16: Change in the non-agricultural sources of household income from baseline to midline by 
stratum _____________________________________________________________ 57
Figure 5-1: Proportion of villages with evidence of good governance by stratum _____________ 60
Figure 5-2: Proportion of villages with evidence of good governance by RISE zones in each country61
Figure 5-3: Proportion of villages with evidence of good governance by stratum _____________ 62
Figure 5-4: Proportion of villages with adequate capacity to manage climate shocks and risks by stratum
62
Figure 5-5: Proportion of villages with adequate capacity to manage climate shocks and risks by RISE 
Sahel Resilience Learning (SAREL)—RISE Midline Quantitative Survey Report
Revised June 2018 viii
zone in each country____________________________________________________ 63
Figure 5-6: Proportion of villages with adequate capacity to manage climate shocks and risks by stratum 
from baseline to midline _________________________________________________ 64
Figure 5-7: Proportion of individuals who engage with a local power structure by RISE zone in each 
country _____________________________________________________________ 64
Figure 5-8: Proportion of individuals who engage with local power structures by stratum ______ 65
Figure 6-1: Prevalence of moderate or severe hunger from baseline to midline by stratum______ 70
Figure 6-2: Proportion of acutely malnourished children under 5 by RISE zone of each country __ 71
Figure 6-3: Proportion of acutely malnourished Children under 5: Sex of the Child ___________ 71
Figure 6-4: Proportion of acutely malnourished Children under 5: Ethnicity of the Child _______ 72
Figure 6-5: Proportion of acutely malnourished Children under 5: Marital Status of Head of Household
72
Figure 6-6: Proportion of acutely malnourished Children under 5: Literacy Status of Head of Household
73
Figure 6-7: Proportion of acutely malnourished children under 5 by stratum________________ 74
Figure 6-8: Proportion of stunted children under 5 years of age by RISE zone of each country ___ 75
Figure 6-9: Proportion of Stunted Children under 5 Years of Age: Sex of the Child ___________ 75
Figure 6-10: Proportion of Stunted Children under 5 Years of Age: Ethnicity of the Child ______ 76
Figure 6-11: Proportion of Stunted Children under 5 Years of Age: Marital Status of Head of Household
76
Figure 6-12: Proportion of Stunted Children under 5 Years of Age: Literacy Status of Head of 
Household ___________________________________________________________ 77
Figure 6-13: Proportion of stunted children under 5 years of age by stratum________________ 78
Figure 6-14: Proportion of underweight children under 5 years of age by RISE zone of each country
79
Figure 6-15: Proportion of underweight children under 5 years of age by stratum ____________ 80
Figure 6-16: Proportion of Households Using improved Drinking Water Sources by Stratum and by 
RISE Zone of each Country’s Dimensions_____________________________________ 80
Figure 6-17: Proportion of households using improved drinking water sources by stratum______ 81
Figure 6-18: Proportion of Households Using Soap and Water Hand Washing Station by Stratum and 
by RISE Zone of Each Country’s Dimensions __________________________________ 82
Figure 6-19: Proportion of households using soap and water hand washing station by stratum ___ 83
Figure 6-20: Proportion of households using an improved sanitation system by stratum and RISE zone 
of each country _______________________________________________________ 84
Figure 6-21: Proportion of Households Using an Improved Sanitation System: Sex of Head of 
Household ___________________________________________________________ 85
Figure 6-22: Proportion of Households Using an Improved Sanitation System: Marital Status of Head 
Sahel Resilience Learning (SAREL)—RISE Midline Quantitative Survey Report
Revised June 2018 ix
of Household _________________________________________________________ 85
Figure 6-23: Proportion of Households Using an Improved Sanitation System: Literary Status of Head 
of Household _________________________________________________________ 86
Figure 6-24: Proportion of Households Using an Improved Sanitation System: Ethnicity of Head of 
Household ___________________________________________________________ 86
Figure 6-25: Proportion of households using an improved sanitation system by stratum________ 87
Figure 6-26: Average Household Dietary Diversity Score: Sex of Head of Household _________ 89
Figure 6-27: Average Household Dietary Diversity Score: Marital Status of Head of Household __ 89
Figure 6-28: Average Household Dietary Diversity Score: Literacy Status of Head of Household _ 90
Figure 6-29: Average Household Dietary Diversity Score: Ethnicity of Head of Household______ 90
Figure 6-30: Average household dietary diversity score from baseline to midline by stratum ____ 91
Figure 6-31: Proportion of children receiving a minimum acceptable diet (MAD) by RISE zone of each 
country _____________________________________________________________ 92
Figure 6-32: Proportion of children receiving a minimum acceptable diet (MAD) by stratum ____ 93
Figure 6-33: Exclusive breastfeeding: count and proportion by stratum____________________ 94
Figure 6-34: Proportion of children receiving exclusive breastfeeding by RISE zone of each country94
Figure 6-35: Proportion of children receiving exclusive breastfeeding by stratum_____________ 95
Figure 7-1: Average village level WEAI score by stratum ______________________________ 98
Figure 7-2: Proportion of households that agree that males and females should have equal access to 
social, political, and economic opportunities by stratum__________________________ 100
Figure 7-3: Proportion of women reporting effective participation in decision making by stratum 101
Figure 7-4: Proportion of women reporting effective participation in decisions by RISE zone in each 
country ____________________________________________________________ 101
Figure 7-5: Proportion of women reporting effective participation in decisions by stratum _____ 105
Figure 9-1: Women’s awareness of methods a couple may use to delay or avoid pregnancy (by strata)
109
Figure 9-2: Women’s awareness of methods a couple may use to delay or avoid pregnancy (by country)
110
Figure 9-3: Percentage of women taking actions/using methods to delay or avoid pregnancy (by strata)
111
Figure 9-4: Percentage of women taking actions/using methods to delay or avoid pregnancy (by 
country)____________________________________________________________ 112
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List of Acronyms
CBSP Community-Based Solution Provider
CESAO West African Center for Social and Economic Research
CFW Cash for Work
CPI Consumer Price Index
DEFF Design Effects
DFAP Development Food Assistance Program
EICVM Integrated Survey on Household Living Conditions
FCFA Franc de la Communauté Française d’Afrique 
FFP Food for Peace
FFW Food for Work
FMNR Farmer-Managed Natural Regeneration
FY Fiscal Year
GAM Global Acute Malnutrition
GPI Gender Parity Index 
Ha Hectare
HH Household
HHH Household Head
HHS Household Hunger Scale
IMF International Monetary Fund
INSD Burkina Faso National Statistics and Demographic Institute
LCUs Local Currency Units
IPs Implementing Partners
Km Kilometer 
LCU Local Currency Unit
MAD Minimum Acceptable Diet
NGO Non-Governmental Organization 
OLS Ordinary Least Squares
PGI Poverty Gap Index
PPP Purchasing Power Parity
PPS Probability Proportional to Size
PMP Performance Monitoring Plan
PRIME Pastoralist Areas Resilience Improvement and Market Expansion
PS/NFSC Permanent Secretariat for the National Food Security Council in Burkina Faso
PSUs Primary Sampling Units
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REGIS-AG Resilience and Economic Growth in the Sahel - Accelerated Growth
REGIS-ER Resilience and Economic Growth in the Sahel – Enhanced Resilience
RISE Resilience in the Sahel Enhanced
SAREL Sahel Resilience Learning Project
TLU Total Livestock Unit 
TMG The Mitchell Group, Inc.
USAID United States Agency for International Development
USG United States Government
WEAI Women’s Empowerment in Agriculture Index
WHO World Health Organization
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Executive Summary
The Resilience in the Sahel Enhanced (RISE) program aims to increase the resilience of 
chronically vulnerable people, households, villages, and systems in targeted agro-pastoral and 
marginal agriculture livelihood zones of Burkina Faso and Niger. The program has a duration 
of five years, from 2014 to 2019. This report describes the results of a quantitative midline 
survey conducted in 2017, using a probabilistic sampling methodology of approximately 2,500 
households across 100 villages in three regions of Burkina Faso (Est, Centre Nord, and Sahel) 
and three regions of Niger (Zinder, Maradi, and Tillabery). The survey was funded by the 
United States Agency for International Development (USAID), commissioned by The Mitchell 
Group (TMG), and overseen by the SAREL project team. The Centre d’Etudes Economiques et 
Sociales de l’Afrique de l’Ouest (CESAO)—an African international association based in Burkina 
Faso that SAREL has worked with since 2014 to build its capacity to provide monitoring, 
evaluation, learning, and collaboration support services to resilience actors after the SAREL 
project ends—conducted the data collection and processing. SAREL carried out the survey 
and analysis in close coordination with TANGO International, which is tasked by USAID with 
conducting the complementary qualitative evaluations of RISE. 
The RISE program includes Food for Peace (FFP) projects implemented by Catholic Relief 
Services, Mercy Corps, Save the Children, and ACDI/VOCA. It also includes the Resilience 
and Economic Growth in the Sahel – Enhanced Resilience (REGIS-ER) project, whose overall 
objective is to increase the resilience of chronically vulnerable populations in the agro-pastoral 
and marginal agricultural areas of Burkina Faso and Niger, and the Resilience and Economic 
Growth in the Sahel - Accelerated Growth (REGIS-AG) project, launched in FY 2014 and 
2015, respectively. 
The midline survey serves two purposes. First, it is intended to provide up-to-date 
population-based information for the RISE zone. Second, it allows for a comparison of 
outcomes from the baseline to the current midline point. Insofar as the same set of measures 
were used at baseline and midline, that comparison constitutes an estimation of the impact of 
RISE interventions to date, taking into account other possible changes, unrelated to RISE, that 
may have occurred over the same time period. The impact of RISE will not be fully apparent 
until at least the point of the final round of data collection; this midline survey should thus be 
seen as addressing the first purpose and providing preliminary evidence with respect to the 
impact of RISE. 
In order to evaluate the impact of the RISE initiative, villages included in the data collection 
process were stratified into two zones: the High exposure zone constitutes villages that have 
received support from any of the FFP projects (PASAM-TAI, LAHIA, and Sawki in Niger, and 
Faso and ViM in Burkina Faso), or the REGIS projects. The Low exposure zone is the set of 
comparable villages from which data are collected but which are not receiving any of the 
above-listed RISE interventions. This constitutes a quasi-control set against which the impact 
of the RISE interventions in the High exposure zones can be compared. Difference-in￾Differences analysis served as the principal methodological approach for evaluating the change 
Sahel Resilience Learning (SAREL)—RISE Midline Quantitative Survey Report
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across Low and High exposure villages from the baseline to the midline period. The data 
structure also allows for complementary analyses using Propensity Score Matching, and, for 
the village-level data, panel analyses with country- or region-level fixed effects.1 We intend to 
conduct matching analyses at the endline stage for those indicators with significant, or close 
to significant, difference-in-differences.
To collect the midline data, enumerators, controllers and supervisors were selected and 
trained. Enumeration teams worked across regions in the RISE area, simultaneously collecting 
data from Niger and Burkina Faso in a total of 37 High exposure villages and 63 Low exposure 
villages. Following the data collection, SAREL undertook data cleaning, coding, and analysis.
This report describes the data collection process, the midline results obtained through this 
phase of data collection, and the comparative analyses from baseline to midline. 
The report organizes outcomes around the three core components of the RISE program: 
Livelihoods, Governance, and Health and Nutrition. Under each component, specific impact 
indicators derived from the RISE Performance Management Plan (PMP) are included. In total, 
the report documents progress on a list of 21 performance measurement indicators. The 
report also includes Household and Village information, such as demographic data and 
exposure to shocks, as well as data and indicators relevant to the RISE program’s cross-cutting 
objective of Gender Equality. 
Data from the midline surveys indicate the following key results: 
Living Conditions and Exposure to Shocks
The population under study is largely young, rural, and agricultural with low levels of 
education: the average age is 19; nearly 80 percent of surveyed households rely on agriculture 
as their principal livelihood; and approximately 90 percent of heads of households cannot 
read. On average, households spend 73 minutes per day fetching water, and nearly 80 percent 
have floors of dirt, clay, or sand. The RISE study area is also highly susceptible to shocks. 
Overall, 96 percent of households report experiencing a shock over the past twelve months, 
due to factors such as conflict, natural disaster, or a death.2 Households in the region employ 
a number of different strategies to cope with those shocks: they sell animals, receive help or 
borrow from friends, reduce their food consumption, and deplete their savings, among other 
measures. However, almost half were unable to recover from those shocks to their pre-shock 
status.
Livelihoods
Close to two-thirds of respondents in the RISE zone live on less than $1.90 per day. The 
 1 At this midline stage, matching was not employed given the infrequent occurrence of statistically significant 
findings from the DiD analyses. We note this because we expect that such complementary analyses may be 
fruitful at the endline stage. Panel data is not available at the individual or household levels, but the inclusion of 
the same 100 communes makes such analyses possible for the village-level data.
2 Categories of shock include natural disaster, socioeconomic, anthropogenic, psychosocial, and other. See 
Section 3 for more details.
Sahel Resilience Learning (SAREL)—RISE Midline Quantitative Survey Report
Revised June 2018 xiv
depth of poverty increased slightly in the Low exposure zone but remained steady or perhaps 
improved slightly in the High exposure zone, but the difference-in-differences is not 
statistically significant. There has been no improvement in the prevalence of poverty to this 
point. Overall, poverty is notably worse in the Niger sample compared to the Burkina Faso 
sample. Asset ownership also trended slightly in the desired direction in the High exposure 
zone relative to the Low exposure zone, but the difference is not statistically significant. With 
respect to the diversification of livelihoods in the study region, nearly three-quarters of 
households (73.3%) earn some income from non-agricultural sources, and even greater 
proportions do in Niger. From baseline to midline, there has been a statistically significant 
improvement in livelihood diversification in the High exposure zone compared to the Low 
exposure zone. 
Governance
In the Governance category, we measured the share of villages with effective governance, the 
share with adequate capacity to manage climate risks, and the proportion of individuals who 
engage with local power structures. Two findings are worth underscoring. First, the 
percentage of communities with evidence of good governance improved significantly in the 
High exposure areas from baseline to midline (47% to 81%, p=.02). The difference-in￾differences comparing the relative change in the High exposure zone versus the Low exposure 
zone, furthermore, is positive and approaches conventional levels of statistical significance 
(p=.08). Second, the share of communities with adequate capacity to manage climate shocks 
improved significantly from baseline to midline, but a comparable change occurred in both the 
High and Low exposure areas, so the improvement cannot be attributed to RISE interventions. 
The proportion of respondents engaging with local authorities remained in the range of 13% 
in both the High and Low exposure zones from baseline to midline. There was no statistically 
significant change.
Health, Nutrition and Sanitation
Rates of moderate and severe hunger are lower in the High exposure zone, but that difference 
existed already at baseline, likely for unobserved confounding reasons since the assignment of 
communes to low and high exposure was randomized, and no improvement was observed. 
Global acute malnutrition rates actually decreased in the Low exposure zone but not in the 
High exposure zone; this could be a function of other donor activities overlapping with the 
RISE Low exposure area, climate and food variability that happened to affect the High and 
Low exposure zones in systematic ways, or other confounding factors. The share of children 
with stunted growth decreased in the High exposure zone from 50% down to 46%; no 
significant change occurred in the Low exposure zone, but the difference-in-differences is not 
statistically significant. Regarding clean drinking water, overall access improved slightly from 
66% to 69%, though most of the gains occurred in the Low exposure zone and the change is 
not statistically significant. Households in the High exposure area are significantly more likely 
to have a soap-and-water handwashing station at the midline stage (7.8% vs. 1.8%), but there 
has been a drop overall since the baseline, and especially in the Low exposure area. Niger lags 
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far behind Burkina Faso in terms of improved sanitation, as only 11 percent of surveyed 
Nigerien households had an improved sanitation system. Household diets have not improved 
during the first two years of the RISE program, and while the proportion of children 
exclusively breastfed jumped from 36 percent to 45 percent in the High exposure zone, the 
change is not statistically significant.
Gender Equality
The RISE survey includes measures for a modified version of the Women’s Empowerment in 
Agriculture Index (WEAI), addressing the domains of Production and Resources. From 
baseline to midline, we do not observe a notable improvement in this measure – the 
empowerment score is approximately 70 across the RISE zone (and is significantly higher in 
Niger than in Burkina Faso), but no statistically significant difference-in-differences is observed. 
Regarding attitudes about equal access for women to social, political, and economic 
opportunities, not quite half of the overall sample supports such equality (52% of women and 
44% of men). There has actually been a statistically significant drop of approximately five 
percentage points in the WEAI score in both the High and Low exposure zones. The share 
of women who state that they participate effectively in decisions did not change in any 
statistically significant way from baseline to midline. We note that women in Niger in general 
have higher effective decision-making power, and in particular in the domain of livestock. 
Women in Burkina Faso have higher rates of effective decision-making regarding non￾agricultural sources of income. We also include a complementary section on family planning 
(Section 9). The analyses suggest that familiarity with family planning methods is on the rise, 
but that behavioral changes lag behind.
Additional Factors that Correlate with Key Outcomes
We disaggregated outcomes according to a number of sociodemographic household-level 
factors to explore additional correlations. Female-headed households tend to be poorer and 
to have worse sanitation practices. They tend to have better health measures for their 
children (such as stunting and being underweight), despite the fact that they more often face 
moderate to severe hunger and lack dietary diversity to a greater degree. Households with 
a literate head of household are on average wealthier, more engaged with local power 
structures, and more sanitary. They also face less hunger and have more diverse diets. 
Outcomes frequently differ by the ethnicity of households, though with little in the way of 
systematic patterns. Mossi households tend to be better off and healthier, and Hausa 
households tend to be worse off. Fulani/Peul households are more likely to suffer from 
malnutrition. In terms of the marital status of household heads, monogamous and polygamous 
households do not differ in systematic ways. These sociodemographic features are discussed 
throughout the report and are summarized in Section 8.
Limitations and Challenges
Overall, the RISE program seems to be contributing to some modest improvements in the 
High versus Low exposure zones over the first two years of the program. Some challenges 
limit the program’s effectiveness in other ways. First, the increase in violent extremist 
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activities and rhetoric in the region, which corresponds timewise almost exactly with the 
introduction of the RISE program, may undermine some of the enthusiasm for and 
effectiveness of the RISE activities, though measuring that impact is beyond the scope of this 
study. Further, activities organized by other donors may reinforce some of the larger 
objectives of the RISE program, but may also complicate the ability to determine precise 
estimates of the RISE program effects. Finally, climate change and population growth continue 
at a rapid pace in the Sahel, so the RISE activities are working against a rising tide of natural 
challenges. Climate and precipitation variability constitutes a particular challenge, as 
communities can be affected alternately by high and low levels of rainfall. This makes the RISE 
program doubly important, though it also becomes increasingly difficult to realize notable 
improvements in a difference-in-differences design since the entire RISE zone may be affected 
by important natural changes.
USAID has already begun responding to some of these challenges in the RISE zone with 
significant new investments in programs to promote family planning and combat violent 
extremism. RISE and Food for Peace performance evaluations have confirmed the importance 
of ensuring better integration of program interventions into national strategies and plans, 
building the capacity of decentralized local collectivities (regions and communes) to lead and 
coordinate development efforts, and strengthening inter-donor collaboration to address 
problems such as climate change whose dimensions exceed the resources and capacities of 
individual partners. 
Regarding the midline survey itself, two important limitations are worth noting. First, to 
adequately track changes over time across a number of dimensions (such as program stratum, 
country, and gender), larger sample sizes are needed. As a result, improvement may have 
occurred on certain indicators but the results are not strong enough to attain statistical 
significance given the sample size. Second, the High and Low exposure zones were not 
stratified by country or region within countries, so some power is lost in conducting 
disaggregated analyses. 
Lessons Applied, New Lessons Learned, and Recommendations
A number of lessons learned during the 2015 baseline study were addressed during the 
implementation of the midline survey with positive effects. These included:
• Begin the processes of administrative authorization and village awareness as early as 
possible.
• Select and train controllers separately from survey enumerators.
• Develop a guidebook and checklist for quality control personnel to ensure consistent 
data collection across locations.
New lessons were learned during the course of the midline survey, leading to a number of 
recommendations for subsequent data collection. Some of those recommendations are to:
• Revise the questionnaire to reduce its length and add clarity.
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• Engage highly-skilled data consultants early and devote adequate time to data 
preparation prior to the planned analysis period.
• Involve the local data collection/processing partner in data analysis as part of capacity￾building strategy for Sahelian institutions.
• Develop systematic methodologies for addressing missing and anomalous values.
• Consider the use of tablets during the next round of data collection, perhaps as a pilot 
and capacity building exercise.
• Consider engaging local security personnel to ensure safe movement and data 
collection by the enumeration team.
• Regarding Women’s Empowerment and the WEAI score, consider calculating the 
scores by individual in the High versus Low exposure zones, as aggregations at the 
village level may mask some trends. Furthermore, consider coupling the WEAI score 
with analyses by sector, as women engaged in livestock raising and agriculture seem 
to have different levels of decision-making power.
Next Steps
The RISE program is designed to strengthen resilience among chronically vulnerable 
populations in the marginalized area that spans Burkina Faso and Niger. The midline survey 
provides empirical data that allows for an evaluation of improvements attributable to the RISE 
program (in High versus Low exposure zones) from the baseline period to the present, in the 
context of other unobserved factors that may affect the outcomes of interest. TANGO will 
exploit the quantitative survey results and also conduct a more in-depth, exploratory and 
open-ended community qualitative survey in a sub-set of the 100 villages selected for inclusion 
in the household and village quantitative survey. We anticipate that program activities will 
begin reaching a more mature status and will become more widely known by villages and 
households in the RISE zone over the remaining two years of the program. Next steps include 
the exploration of additional hypotheses that could shed important light on the effects of RISE 
beyond the listed indicators of interest. Furthermore, we anticipate transferring more capacity 
to SAREL’s partner CESAO in advance of the endline survey and will work closely with 
CESAO to ensure a strong data collection plan to evaluate progress from midline to endline.
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Summary of Midline RISE Indicator Outcomes
The following table summarizes the findings by indicator. Dark green indicates a statistically 
significant finding (p<.05). Light green indicates a trend in the desired direction that 
approaches conventional levels of statistical significance (p-values between .05 and .15). 
Dark red indicates a statistically significant finding in the wrong direction, while light red 
indicates a trend in the wrong direction that approaches statistical significance.
Indicator
Baseline Midline P￾value
DiD P￾value
Weighted 
estimates
Weighted 
estimates
Confidence Interval 
(95%)
Lower 
bound
Upper 
bound
Indicator 1: Depth of 
Poverty (%)
Overall Mean 25.4 26.1 22.8 29.4 0.72
 High Exposure Zone 27.8 25.9 20.9 30.9 0.48 0.14
 Low Exposure Zone 23.0 26.2 22.0 30.5 0.15
Indicator 2: HH with 
Moderate/Severe Hunger 
(%)
No Hunger, Mean 87.0 85.6 82.9 88.3
 High Exposure Zone 91.2 88.7 85.3 92.1
 Low Exposure Zone 82.1 82.4 78.4 86.5
Moderate Hunger, Mean 10.5 12.4 9.9 14.9
 High Exposure Zone 7.9 9.8 6.7 12.9
 Low Exposure Zone 13.1 15.0 11.2 18.7
Severe Hunger, Mean 2.5 2.0 1.4 2.7
 High Exposure Zone 0.6 1.5 0.7 2.2
 Low Exposure Zone 4.4 2.6 1.6 3.6
Moderate/Severe Hunger, 
Mean (combined)
12.9 14.4 0.39
 High Exposure Zone 8.5 11.3 0.18 0.42
 Low Exposure Zone 17.5 17.6 0.97
Indicator 3a: Average 
Value of HH Assets (in 
FCFA)
Overall mean 786,207 836,192 642,584 1,029,800 0.37
 High Exposure Zone 650,066 758,749 454,425 1,063,073 0.27 0.28
 Low Exposure Zone 928,394 915,619 680,911 1,150,327 0.81
Indicator 3b: Asset 
Ownership (items)
Overall Mean 49.7 49.0 42.7 55.2 0.81
 High Exposure Zone 44.5 46.5 36.6 56.3 0.51 0.28
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Indicator
Baseline Midline P￾value
DiD P￾value
Weighted 
estimates
Weighted 
estimates
Confidence Interval 
(95%)
Lower 
bound
Upper 
bound
 Low Exposure Zone 54.9 51.6 44.1 59.1 0.49
Indicator 4: Prevalence 
of Poverty (%)
Overall Mean 61.8 63.8 58.5 69.1 0.43
 High Exposure Zone 65.4 65.5 57.1 73.8 0.98 0.44
 Low Exposure Zone 58.2 62.1 55.6 68.6 0.25
Indicator 5: Women’s 
Empowerment in 
Agriculture Index (Index 
score, out of 100)
Overall Mean 66.9 70.6 66.2 75.1 0.05
 High Exposure Zone 69.4 69.7 63.5 75.9 0.91 0.12
 Low Exposure Zone 65.1 71.3 65.2 77.4 0.02
Indicator 6: HH with 
Income from Non￾Agricultural Sources (%)
Overall Mean 72.2 73.3 68.0 78.5 0.55
 High Exposure Zone 72.6 77.3 68.9 85.7 0.08 0.03
 Low Exposure Zone 71.8 69.1 63.3 75.0 0.23
Indicator 7: 
Communities with 
Evidence of Good 
Governance (%)
Overall Mean 55.9 69.1 56.2 81.9 0.21
 High Exposure Zone 46.8 80.7 67.0 94.4 0.02 0.08
 Low Exposure Zone 61.7 61.6 42.4 80.8 0.99
Indicator 8: 
Communities with 
Adequate Capacity to 
Manage Climate Shocks 
(%) 
Overall Mean 25.6 55.1 40.1 70.1 0.01
 High Exposure Zone 41.7 72.8 55.7 90.0 0.04 0.90
 Low Exposure Zone 15.2 43.7 21.2 66.2 0.05
Indicator 9: Share of 
Individuals Engaging 
with Local Power 
Structures (%)
Overall Mean 12.9 12.3 9.0 15.6 0.76
 High Exposure Zone 12.3 12.6 7.4 17.8 0.93 0.67
 Low Exposure Zone 13.5 12.0 8.1 16.0 0.62
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Indicator
Baseline Midline P￾value
DiD P￾value
Weighted 
estimates
Weighted 
estimates
Confidence Interval 
(95%)
Lower 
bound
Upper 
bound
Indicator 10: Global 
Acute Malnutrition Rate 
(%)
Overall Mean 17.4 15.9 14.1 17.6 0.16
 High Exposure Zone 15.7 15.7 13.1 18.4 1.00 0.15
 Low Exposure Zone 19.1 16.0 13.8 18.3 0.05
Indicator 11: Prevalence 
of Stunted Children 
Under 5 (%)
Overall Mean 49.8 46.8 42.6 51.0 0.07
 High Exposure Zone 50.2 46.0 39.1 52.9 0.13 0.45
 Low Exposure Zone 49.3 47.6 43.1 52.2 0.36
Indicator 12: Prevalence 
of Underweight Children 
Under 5 (%)
Overall Mean 39.2 36.0 32.8 39.2 0.02
 High Exposure Zone 37.4 35.9 30.7 41.0 0.49 0.23
 Low Exposure Zone 41.0 36.1 32.4 39.9 0.01
Indicator 13: Share of 
HH Using Improved 
Drinking Water Source 
(%)
Overall Mean 66.4 68.9 61.2 76.6 0.23
 High Exposure Zone 67.8 68.2 54.9 81.5 0.89 0.31
 Low Exposure Zone 64.9 69.6 62.1 77.2 0.10
Indictor 14: Share of HH 
with Soap-and-Water 
Hand Washing Station 
(%)
Overall Mean 7.0 4.8 2.4 7.2 0.15
 High Exposure Zone 9.6 7.8 3.0 12.6 0.54 0.79
 Low Exposure Zone 4.4 1.8 0.5 3.2 0.04
Indicator 15: Share of 
HH Using Improved 
Sanitation System (%)
Overall Mean 18.9 19.4 12.9 26.0 0.78
 High Exposure Zone 21.6 24.3 12.7 35.9 0.42 0.79
 Low Exposure Zone 16.2 14.5 9.5 19.4 0.31
Indicator 16: Household 
Dietary Diversity (Score 
from 0-12)
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Indicator
Baseline Midline P￾value
DiD P￾value
Weighted 
estimates
Weighted 
estimates
Confidence Interval 
(95%)
Lower 
bound
Upper 
bound
Overall Mean 5.1 5.0 4.7 5.3 0.60
 High Exposure Zone 5.1 4.9 4.5 5.4 0.26 0.42
 Low Exposure Zone 5.1 5.1 4.8 5.4 0.86
Indicator 17: Share of 
Children Receiving 
Minimum Acceptable 
Diet (%)
Overall Mean 6.3 5.7 2.9 8.4 0.78
 High Exposure Zone 7.2 6.2 1.6 10.8 0.80 0.87
 Low Exposure Zone 5.3 5.0 2.4 7.7 0.86
Indicator 18: Prevalence 
of Exclusive 
Breastfeeding Under 6 
Months Old (%)
Overall Mean 34.5 39.8 32.0 47.6 0.26
 High Exposure Zone 36.7 46.1 34.7 57.6 0.16 0.29
 Low Exposure Zone 31.7 31.7 22.5 40.8 0.99
Indicator 19: Proportion 
Supporting Equal 
Access for Males and 
Females (%)
Overall Mean 51.7 44.8 37.7 51.9 0.00
 High Exposure Zone 52.7 46.5 33.7 59.3 0.04 0.74
 Low Exposure Zone 50.6 43.1 37.6 48.6 0.02
Indicator 20: Share of 
Women Reporting 
Effective Participation 
(%)
Overall Mean 75.0 72.8 68.7 77.0 0.42
 High Exposure Zone 78.6 74.6 68.7 80.5 0.24 0.47
 Low Exposure Zone 71.1 71.0 65.2 76.7 0.97
Overall, we find few statistically significant impacts from the RISE interventions at this 
midpoint of the program. Of course, only two years have passed since the baseline, and the 
context is a complex one with numerous factors that could undermine or confound RISE 
effects. In presenting these results in the report, we share analyses for all indicators, whether 
or not the differences reach conventional levels of statistical significance. We do this for three 
reasons. First, doing so serves a broader interest in accumulating knowledge about the 
program effects, whether they be positive, negative, or negligible at the midpoint. Second, if 
we did not report information about indicators for which there is no statistically significant 
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finding, readers who specialize in particular omitted domains would learn nothing about the 
status of those areas. Third, we prefer to allow readers to evaluate the importance of program 
effects by considering both the substantive impact and the statistical significance of findings 
and making their own judgments. If we imposed conventional but arbitrary p-value cutoffs 
(such as .05) in determining what we report, readers would not have the opportunity to judge 
the substantive and statistical effects, and we would be unable to highlight circumstances in 
which a bigger sample size would likely shift statistical conclusions. The report is longer as a 
result, but also more thorough in a manner that should pay dividends upon the final evaluation 
of RISE. We do make an effort to streamline the presentation of results where the differences 
are not significant and where further analyses or figures would not provide fruitful 
information.
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1. Introduction
Resilience in the Sahel Enhanced (RISE) is a USAID-funded program aimed at increasing the 
resilience of chronically vulnerable people, households, communities and systems in targeted 
agro-pastoral and marginal agriculture livelihood zones of Burkina Faso and Niger. RISE has a 
duration of five years, from 2014 to 2019. To track the ongoing impact of the RISE program, 
USAID funded a midline quantitative survey of approximately 2,500 households across 100 
villages in 2017, which followed an initial baseline survey conducted in 2015. The midline 
survey was commissioned by The Mitchell Group (TMG) and overseen by the SAREL project 
team. The Centre d’Etudes Economiques et Sociales de l’Afrique de l’Ouest (CESAO), an 
African international association based in Burkina Faso that is slated to continue providing 
monitoring, evaluation, learning and collaboration support services to resilience actors after 
the SAREL project ends, conducted the survey, which covered three regions in Burkina Faso 
(Est, Centre Nord, and Sahel) and three in Niger (Zinder, Maradi, and Tillabery). SAREL 
carried out the baseline and midline surveys and analysis in close coordination with TANGO 
International, a firm with specialized expertise in resilience that has been tasked by USAID 
with conducting the complementary qualitative evaluations of RISE.
The activities that USAID supports to impact resilience in the region include Food for Peace 
projects implemented by Catholic Relief Services, Mercy Corps, Save the Children, and 
ACDI/VOCA. The program also includes the Resilience and Economic Growth in the Sahel –
Enhanced Resilience (REGIS-ER) project, a facilitation-oriented project that aims to increase 
resilience through key livelihood, health, and local governance activities, and the Resilience 
and Economic Growth in the Sahel - Accelerated Growth (REGIS-AG) project, an export￾oriented project that prioritizes value chain improvements. REGIS-ER and REGIS-AG were 
launched in FY 2014 and 2015, respectively, while Food for Peace activities were already 
underway at the start of RISE and were subsequently incorporated. 
The aim of the study is to begin evaluating the impact of the RISE initiative over time by 
comparing survey results at the midline of the initiative to the results reported in the initial 
baseline survey. In order to properly catalog the impact of RISE while accounting for other 
potential factors that might affect resilience in the region, villages included in the data 
collection area were selected and stratified into two zones: the High exposure zone 
constitutes villages that receive support from any of the FFP projects (PASAM-TAI, LAHIA, 
and Sawki in Niger, and FASO and ViM in Burkina Faso), or the REGIS-ER and -AG projects. 
The Low exposure zone is the set of comparable villages from which data are collected but 
which are not receiving any of the above-listed RISE interventions. This constitutes what, in 
experimental language, would be referred to as a quasi “control” set against which the impact 
of the RISE initiative in the High exposure zone can be compared over time. Thus, at the 
midline, a difference-in-differences (DiD) analysis can be undertaken: the change over time in 
the High exposure villages can be compared to the change over time in Low exposure villages, 
and any systematic differences in the High vs. Low changes may be attributed to the RISE 
activities. In addition to testing a set of 21 key indicators related to the RISE objectives, the 
midline survey also provides data useful for tracking demographic and village characteristics, 
Sahel Resilience Learning (SAREL)—RISE Midline Quantitative Survey Report
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reporting exposure to shocks, and testing additional causal hypotheses of interest. 
To collect the RISE quantitative baseline data in 2015, SAREL contracted a Burkina Faso-based 
firm, IMC, which recruited and trained enumerators from the pool that exists in both Burkina 
Faso and Niger of persons who have acquired experience and skills conducting surveys for 
the national statistics services and diverse donor institutions. To lead data collection and 
processing for the midline evaluation SAREL tapped its principal Sahelian institutional partner, 
the West African Center for Social and Economic Studies (CESAO). CESAO carried out an 
extensive competitive recruitment process in Niger and Burkina Faso. Controllers and 
enumerators who had participated in the 2015 RISE baseline study and performed well were 
given priority, but all application dossiers were screened before candidates were invited to 
training. Controller candidates were interviewed by a panel in each country that included a 
representative of SAREL. Controllers completed a special five-day training, and those who 
were selected then assisted CESAO in conducting the full ten-day training program organized 
for enumerators. The latter were evaluated and selected based on their performance during 
the training, on a final written exam, and during a simulated data collection exercise in a local 
village. (Note that separate reports were submitted to USAID detailing all phases of the 
preparation and implementation of the RISE midline evaluation, including recruitment and 
training of survey personnel).
Enumeration teams worked across regions in the RISE area, simultaneously collecting data 
from Niger and Burkina Faso. Following the data collection, data cleaning, coding, and analysis 
were conducted. This report describes the data collection process, the midline results, and 
the impact of the RISE initiative at its midline.
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1.1. Overview of the RISE Program
As noted, the objective of the RISE program is to enhance resilience among vulnerable 
populations in the Sahel region of Burkina Faso and Niger. USAID defines resilience as the 
capacity of affected people, households, communities, countries and systems to mitigate, adapt 
to, and recover from shocks and stresses in a manner that reduces chronic vulnerability and 
facilitates inclusive growth. The reasons behind USAID’s decision to invest in resilience 
enhancement in the Sahel include:
• The high human and financial costs of chronic humanitarian assistance
• The impediments that chronic vulnerability pose to economic growth 
• The cyclical impact of weak economic growth on the capacity of individuals, 
households, communities and systems to mitigate, adapt to, and overcome shocks and 
stresses
• Evidence suggesting that investments in resilience can result in significant savings in 
humanitarian outlays, which typically are able to address only the effects of crisis 
instead of addressing their underlying causes in a preventative manner. 
According to the theory of change that underpins USAID’s RISE initiative, resilience in the 
Sahel can be better strengthened by sequencing, layering, and integrating humanitarian and 
development interventions, rather than employing humanitarian and development 
interventions in isolation. The assumption of this theory of change is that development 
interventions can reduce risks so as to offset the adverse impacts of humanitarian crises due 
to shocks and stresses. As households and communities become more adept at absorbing 
those shocks and stresses, adapting new livelihood approaches in response, and then 
transforming their livelihood options, they will develop resilience to withstand setbacks and 
to promote inclusive economic growth in the targeted Sahel zone.
The RISE zone was demarcated based on both quantitative and qualitative criteria, taking into 
account vulnerability, natural resource endowments, irrigation and horticultural land potential 
(i.e. gardening, arboriculture), accessibility, and human and property security (see map below). 
Communes and villages within the RISE zone were then selected with attention to those same 
factors, with beneficiary (High exposure) villages paired with similar non-beneficiary (Low 
exposure) villages in order to build evaluation concerns directly into the initial program design. 
The same set of 37 High exposure villages and 63 Low exposure villages were surveyed for the 
2015 baseline and the 2017 midline evaluation.3
 For household selection, however, a new 
sample of 25 households was drawn in each village for the midline survey using the same 
systematic approach applied during the baseline that gave each household an equal 
probability of being selected. 
 3 One Low exposure village in Niger’s Tillabery region had to be replaced for the midline survey because of 
security concerns.
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1.1.1. Specific RISE Objectives
In order to achieve the goal of increasing resilience among vulnerable populations in this part 
of the Sahel, several desired outcomes were identified and then grouped around three specific 
objectives or components:
Objective 1: Increased and Sustainable Economic Well-Being (Income, food access, 
assets, adaptive capacity)
To meet this objective, the RISE initiative seeks the following intermediate results among 
households and villages in the region:
• Diversified economic opportunities
• Intensified production and marketing
• Improved access to financial services
• Increase of market infrastructures
Objective 2: Strengthened Institutions and Governance
To promote stronger institutions and governance in such a way as to build resilience, RISE 
identified a number of intermediate results for local villages to achieve:
• Improved natural resource management
• Disaster risk management
• Strengthened conflict management systems
• Strengthened government and regional capacity and coordination
Objective 3: Improved Health and Nutrition Status 
Improved health and nutrition supports resilience in numerous ways, for example, by 
minimizing medical expenses, enhancing prospects for educational success, and improving 
productivity. To attain this objective, the RISE initiative identified the following major 
intermediate results:
• Increased access to potable water
• Improved health and nutrition practices, particularly for mothers and children
• Improved family planning 
• Better sanitation practices
RISE has set a number of expected results to be achieved over the course of the five years of 
interventions. Among them are that:
● 375,000 fewer people will require humanitarian assistance during a drought of 2011 
magnitude.
● Global acute malnutrition (GAM) rates will be reduced from near 15% to below 10% 
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in targeted communes.
● Depth of poverty amongst poor households will be reduced by 20% in targeted 
communes (thus from approximately 22% to less than 17.5%).
● Prevalence of severely/moderately hungry households will be reduced by 20% in 
targeted communes (thus moving from approximately 28% to less than 22.5%).
● 237,500 vulnerable households will benefit directly from USG interventions (8 persons 
per household in average).
At the midline of the initiative, there are no set targets regarding intermediate impact. Instead, 
the purpose of the data collection and analysis is to determine the scope of change since the 
inception of the RISE program, which will enable USAID and its implementing partners to 
consider changes that may serve the broader five-year objectives.
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1.1.2. Coverage and Target Groups
The map below provides an illustration of the RISE study area, which stretches across the 
southern part of Niger and the northern portion of Burkina Faso. The RISE zone includes 
three regions in Niger (Zinder, Maradi, and Tillabery) and three in Burkina Faso (Est, Centre￾Nord, and Sahel). An obvious challenge in undertaking development and humanitarian 
activities in this region is that, by virtue of the high degree of vulnerability that households 
and villages face, numerous other donor activities may also be operating in the same area. The 
RISE design, which randomly assigns villages to Low or High exposure, mitigates this concern 
to some degree, since it would be unlikely that other programs assign their interventions and 
controls in the same localities. Nevertheless, this challenge persists across the Sahel and will 
only be overcome with full collaboration among donors. 
Figure 1-1: Map of the RISE Study Area
At the inception of RISE, it was determined that the assignment of interventions would be 
made across the entire zone rather than stratifying High and Low exposure zones by country 
or region.
Overview of the SAREL Project
Evaluating the impact of a complex, multi-country initiative with numerous implementing 
partners, activities, and objectives requires a dedicated project. The Sahel Resilience Learning 
(SAREL) Project was established for this purpose. SAREL is a five-year (2014-2019) project
funded by USAID and implemented by The Mitchell Group (TMG), a US-based development 
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consulting firm, in collaboration with a consortium of partners.
The objective of the SAREL project is to provide monitoring, evaluation, collaboration and 
learning support to USAID’s RISE Initiative. The SAREL Project is not a standalone 
intervention, but instead builds on and responds to the different resilience projects funded by 
USAID in the regions mentioned above.
The expected results of SAREL are: 1) to test, extend, and accelerate the adoption of proven 
technologies to build resilience and innovations already underway; 2) to develop, test, and 
catalyze widespread adoption of new models integrating humanitarian and development 
assistance; 3) to promote ownership, build the capacity of national and regional institutions, 
and coordinate humanitarian development interventions in the areas of influence; 4) to 
address gender issues critical to resilience and growth; and 5) to create a knowledge 
management database that will house the baseline assessment, routine monitoring data and 
impact assessments for REGIS-ER and REGIS-AG. The midline data and this report constitute 
two of the key contributions of SAREL to the evaluation of RISE and the resilience learning it 
aims to promote.
1.2. Overview of the Midline Study
The midline survey is a probabilistic household survey of approximately 2,500 households 
across 100 villages in the RISE zone. It includes four components: household data, village data, 
gender/women’s data, and child anthropometric data, all of which are gathered at the 
individual level save the village data, which are collected from village representatives. Coming 
two years after the baseline survey, the intention of the midline survey is to provide village-, 
household, and individual-level data that determine the progress made by the RISE initiative 
to this point. These data will serve as a reflection point once the initiative is completed and 
the final data are collected, but they also allow SAREL to test hypotheses and evaluate impact 
at an intermediate stage, and they provide an opportunity for suggesting changes to RISE 
activities. The data collection focuses on a set of core results and impact indicators derived 
from the RISE Performance Management Plan (PMP) and supplemented by more specific 
indicators from the REGIS-ER Performance Management Plan. In total, 21 performance 
measurement indicators are featured in the midline survey report, which tracks changes on 
each since the baseline. The report also includes supplementary analyses of additional 
hypotheses tested using the midline data. 
The key methodological design aspects of this population-based survey – including 
stratification procedures, sample size determination, and sampling protocols – were 
developed in close consultation with USAID and with the technical support of the Institut 
Supérieur des Sciences de la Population (Université de Ouagadougou) in November–December 
2014. The same protocols employed for the baseline survey were maintained for the midline, 
in order to ensure consistency. Whereas data were drawn from the same villages, the data 
set does not constitute a panel since the same households were not re-surveyed from baseline 
to midline. That decision was based on the difficulty of ensuring participation from the same 
individuals and households two years later, given patterns of migration and other challenges 
common in the region. Only the village-level data can be treated as a panel.
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Corresponding to the components of the survey noted above, the survey instruments include 
a household questionnaire and a village questionnaire. For practical purposes of organization 
and administration, the household questionnaire was divided into three “sub-questionnaires 
(household, gender, and food consumption and child anthropometry). The development of 
the RISE survey instruments drew extensively from questionnaires used in the USAID Ethiopia 
PRIME baseline study, though SAREL made numerous changes to reflect a different context. 
Minor changes were made for the midline survey in consultation with USAID, but the 
questionnaires otherwise remained identical in order to ensure comparability across survey
waves.
USAID’s other RISE evaluation contractor, TANGO International, uses the quantitative 
household and village data collected and analyzed by SAREL, as well as the results of in-depth, 
exploratory and open-ended qualitative surveys that it conducts itself in a subset of sample 
villages, in providing analysis to USAID. Using data analysis methods to calculate household 
and village resilience capacities, TANGO has been able to identify factors that contribute 
substantially to building those capacities; explore linkages between resilience capacities, ability 
to recover from shocks, and household food security; and to begin to assess differences across 
intervention groups. 
SAREL and TANGO coordinated in determining dates for conducting the midline quantitative 
and qualitative studies and in obtaining authorizations from relevant administrative authorities 
in Niger and Burkina Faso. Both TMG and TANGO used the same local organization, CESAO, 
for assistance in data collection, which provided advantages to TANGO (local contractor and 
personnel already intimately familiar with RISE, the evaluation process, and the sample 
communities) and to CESAO (capacity-building in qualitative survey processes).
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2. Methodology
This section describes the methodology used for the midline data collection.
2.1. Data Collection
Data were collected concurrently in Burkina Faso and Niger from April 6 to May 4, 2017. 
Data were drawn from 100 villages, with a sample of 25 households per village, for a total of 
2,500 households. The timing of the data collection mirrored the timing of the baseline survey 
in order to avoid seasonal changes that could affect the data.
SAREL and CESAO jointly managed the preparations for data collection. Data collection teams 
consisted of one controller and two man/woman pairs of investigators. One area supervisor 
was responsible for each region, thus amounting to a total of six area supervisors; each of 
them oversaw the work of four enumeration teams. Area supervisors themselves were under 
the responsibility of two general supervisors, one in each country. The entire field data 
collection team fell under the supervision of a project coordinator. Regular and sustained 
coordination, supervision, collaboration, and quality control efforts undertaken by SAREL and 
CESAO allowed for minor adjustments and corrections during the course of the data 
collection. 
Apart from organizing enumeration teams, a series of steps were taken to facilitate data 
collection. Teams received logistical and financial resources for the operation kick-off, as well 
as questionnaire packets (for household, gender, food consumption/child anthropometry, and 
village questionnaires), manuals, enumeration sheets and sample selection sheets. Office 
supplies and other equipment such as scales, length boards, and flashlights were made available 
to the enumeration teams via their area supervisors. Building on lessons learned during the 
baseline survey, controllers and supervisors were trained ahead of the enumerators, so that 
they could participate themselves in the enumerator training.
One successful aspect of the baseline study was the commitment from local administrative 
authorities in ensuring robust participation. SAREL built on that experience by again 
dispatching CESAO, several weeks in advance of the data collection, to provide information 
to governors, prefects, mayors, and customary leaders (cantons and village chiefs). Those 
missions also had the responsibility of raising awareness in the villages regarding the survey 
topics. This process helped to gain buy-in for the midline survey and created some initial 
contact with village members that facilitated the data collection activities. Because CESAO 
has regional offices in both Burkina Faso and Niger, they have a familiarity with the terrain 
and key stakeholders that further helped prepare the groundwork for the surveys.
2.1.1. Data Collection Objectives
The objective of the data collection was to obtain quantitative data necessary for drawing 
rigorous comparisons over time since the conduct of the baseline survey in 2015 and across 
High and Low exposure zones. Those data reveal the impact of the RISE initiative at the 
midline, focusing primarily on measures related to the RISE performance measurement 
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indicators.
2.1.2. Questionnaire Description
Household Questionnaire
The Household Questionnaire, administered with the head of household or his/her household 
representative, was used to record data on all household members along with their 
demographic and socioeconomic characteristics: age, sex, relationship to the head of 
household, ethnicity, highest educational attainment, marital status, primary occupation, etc. 
The questionnaire also included measures of housing characteristics, shocks sustained by the 
household, assets, livestock, access to land and information, production, household 
expenditures and much more. The purpose of the Household Questionnaire was to capture 
household-level data relevant to the key indicators and related issues (such as shock 
exposure). In addition, this survey instrument provided the framework for identifying children 
under five years of age—from whom enumerators collected additional anthropometric data—
and to identify women who would answer the Gender Questionnaire. The questionnaire 
remained almost identical to the baseline household questionnaire; one small change was an 
adjustment to the series of questions regarding the value of household assets, since the 
baseline formulation did not include a mechanism for valuing older assets.
Food Consumption and Child Anthropometry Questionnaire
This survey instrument was used to gather information on children under five years of age. 
Data on consumption and dietary diversity, hunger in households, anthropometry (i.e. child 
height and weight), nutritional status, and dietary practices were collected. It is important to 
note that the survey was conducted at the same time of year as the baseline, which controls 
for any potential seasonal differences in food consumption.
Gender Questionnaire
This questionnaire was used to measure the inclusion of women in agricultural sector growth 
and in household decision making. It was administered to the wives of the heads of 
households, presumed to be centrally involved in life of the household. In the event of a 
female-headed household, the head of household herself was surveyed. The survey instrument 
focused on women's participation in decision making, especially regarding production and 
income-generating activities. The questionnaire included measures used to evaluate the 
modified Women’s Empowerment in Agriculture Index (WEAI) requested by USAID. This 
modified version of the WEAI includes two of the five standard dimensions (Production and 
Resources) and adjusts the shares that each contribute to the WEAI score as a result (see 
Annex). The survey also included a module on reproductive choices and family planning; while
the key indicators do not focus on these issues, SAREL decided to maintain this module as a 
potentially valuable source of data for future analyses.
Village Questionnaire
This questionnaire served as framework for gathering data on the 100 villages where the 
household-level data collection took place. Village characteristics, village infrastructure and 
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services, village organization types, various governmental and NGO programs, shocks, climate 
shock management, land management, and village governance structures are among the 
categories of data captured through this instrument. Responses were obtained from small 
groups of village representatives and leaders. Because the data are village-level and the same 
villages were included in the baseline and the midline surveys, the village data can be 
considered a true panel (with observations from the same units in time 1 and time 2), despite 
the fact that the group of representatives providing answers in each village may have changed 
somewhat from the baseline to the midline.
2.1.3. Sampling 
In order to effectively measure the impact of the RISE program interventions, the research 
design for the study included a satisfactory counterfactual, established at baseline. That is, 
intervention areas were compared to plausibly comparable areas that did not receive those 
interventions. To establish a counterfactual, SAREL used a quasi-experimental research 
method that matched intervention villages with similar control villages. Thus, as noted above, 
two strata were defined based on the degree of exposure (“High” or “Low”) to RISE 
interventions in Burkina Faso and Niger. Following USAID’s inclusion of FFP activities in RISE 
programming, SAREL and USAID made the determination to delineate the High exposure 
zone as all villages where (1) the REGIS-ER Project intervenes alone; (2) the REGIS-ER and 
FFP Projects jointly intervene; or (3) FFP intervenes alone. It should be noted that at the time 
the sample frame was defined (November 2014), REGIS-AG had not yet been launched. Since 
REGIS-AG initiated field activities in the second quarter of 2015, however, its approach has 
been to work with producer groups in villages where REGIS-ER (or one of the DFAP projects) 
already intervenes. The Low exposure zone consists of villages in the RISE intervention area 
which do not benefit from REGIS-ER or FFP interventions and will not do so over the five￾year RISE implementation period (2014–2019). This stratum therefore serves as an implicit 
control area from which a sample of villages resembling the intervention villages as closely as 
possible in terms of socio-cultural, economic, and environmental characteristics was drawn. 
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Figure 2-1: Sample of Villages included in RISE Midline Survey by Stratum
As mentioned above, the Midline survey employed a two-stage cluster design. At the first 
stage, a sample of villages was selected using a probability proportional to size (PPS) 
method. The frame of primary sampling units (PSUs) was composed of all the villages 
located in the RISE area across Burkina Faso and Niger. In this text, we will interchangeably 
use village and PSU. The estimated number of households was used as the estimated 
measure of size to calculate the probabilities of inclusion. The PSU frame was stratified 
following the distinction High versus Low as discussed previously. The total sample size of 
100 PSUs was split into 63 PSUs for the High stratum and 37 for the Low stratum.
Table 2-1: Sampling Weights for Households and Villages in the RISE Zone
Strata Population Sample (Baseline) Sample (Midline)
Nb. Villages Nb. of HHs Nb. Villages Nb. of HHs Nb. of HHs
High 1,702 263,903 37 924 925
Low 2,658 276,441 63 1,569 1,567
Total 4,360 540,344 100 2,493 2,492
The selection of surveyed households was conducted by the field team. To achieve the desired 
sample size of 25 households per village, 28 were drawn from a list of households in each 
village, using systematic simple random selection (SRS) and allowing for three reserves, in the 
event that replacement was necessary. Using the replacements, it was possible to achieve 25 
responding households in all communities but two. In those two communities, all available 
households—19 and 23, respectively—were surveyed. Note that the survey sample within 
High exposure areas was randomly selected; it did not intentionally target known household 
beneficiaries. The effect is that the estimates of impact should be conservative ones. As the 
approach taken did not allow for traditional calculation of response rates, non-responding 
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households were replaced using a backup sample. For the endline, replacement of households 
should be avoided. The original sample should be inflated to account for attrition due to non￾response.
The selection of surveyed households took place in the field, based on the list of households 
in each surveyed village, after all households in the village were identified (using updated print 
lists). Since this is a population-based survey, not all households in RISE villages will have 
benefited directly from RISE programs, thus the need to randomly select from households in 
the villages. This being said, we assume that households that may not have directly benefited 
from RISE programs are likely to have indirectly benefited by virtue of proximity to their 
benefiting neighbors.
2.1.4. Enumerator Training 
The preparation for midline data collection was conducted largely in keeping with the 
protocols used for the baseline. CESAO first shortlisted candidates in both countries for 
enumerator positions, based on a number of criteria defined in the methodology note, 
including the need for male-female pairs to administer questionnaires. A training phase 
followed from March 20 to 30, 2017, simultaneously in Niamey and Ouagadougou. In a 
departure from the baseline process, the controllers were trained prior to the enumerators, 
which gave them (as well as the six supervisors) an opportunity to build capacity and then 
assist with the training of the enumerators. CESAO assembled an experienced team of survey 
experts to lead the data collection effort. They served as the primary training facilitators in 
each country and were assisted by SAREL’s M&E specialists. The training focused on 
participants’ understanding and mastery not only of the data collection tools (questionnaires, 
manuals, and glossaries) but also of household sampling procedures and identification of other 
survey targets (for example, children under five years of age for the anthropometry modules). 
CESAO mobilized specialists to provide training on specific subjects, notably on taking 
anthropometric measurements and GPS readings, and on the use of “event calendars” as an 
aid in determining children’s age. 
Trainers in Burkina Faso and Niger remained in regular contact throughout the training to 
exchange information and share observations and amendments. Typically, this exchange took 
place via internet or telephone, allowing for real time decisions on new instructions. Survey 
instruments and other necessary documents and tools were finalized through the process of 
training and collaboration, and enumerators were tested on sampling procedures and 
questionnaire comprehension prior to leaving the training.
Pilot Survey 
Consistent with the pre-survey protocols used for the baseline data collection, a one-day pilot 
survey was conducted on March 29, 2017 in localities close to the capital cities of 
Ouagadougou, Burkina Faso and Niamey, Niger. Three villages were included in the pilot 
survey in Burkina Faso, selected to ensure the inclusion of villages where the three principal 
languages of the region (Mooré, Fulfuldé, and Gulmantchéma) are spoken. In Niger, the pilot 
survey was conducted in two villages, one Hausa-speaking and one Zarma-speaking. 
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Administrative officials of the villages selected for this exercise—including both mayors and 
traditional leaders—were first consulted to obtain their consent before the pilot survey took 
place. To ease the administrative burden of the pilot survey, enumerator candidates were 
divided based on their command of languages spoken by the villagers and were organized in 
pairs that included a male enumerator to administer the Household Questionnaire and a 
female enumerator to administer the Gender Questionnaire, on the understanding that both 
would ensure all anthropometric measurements.
Representatives of CESAO and the SAREL technical team provided supervision in both 
countries. All enumerator candidates had the opportunity to practice handling different data 
collection tools and survey instruments. At the end of the pilot survey, a debriefing session 
was held in each country to discuss lessons learned and strategies for effectively obtaining the 
survey data.
Final Selection of Field Staff
Shortlisted candidates took a written test after the training session and the pilot survey and a 
final list of selected enumerators was published. Thirty-six (36) candidates were selected to 
conduct the surveys in Burkina Faso, with an additional 16 kept on a list of alternates. In Niger, 
a team of 28 agents was assembled, with 5 alternates. In each country, the alternates served 
as a provision for potential replacements in case of staff withdrawals.
Six regional supervisors oversaw the data collection, each in one of the six regions of Burkina 
Faso or Niger. Below the level of supervisors, 16 controllers each supervised the work of 
two pairs of enumerators. Enumerators were divided into teams and then mixed-gender pairs
based on the survey demands for different regions, as well as their knowledge of local
languages and specific targeted areas. All staff reported to one of two Assistant Coordinators, 
one per country. Both Assistant Coordinators reported to the General Survey Coordinator.
In addition to the sampling and questionnaire training that the enumerators received, 
controllers and supervisors were trained in the management of field teams. They also 
undertook added instruction for the administration of the Village Questionnaire since that 
instrument involved data collection from village stakeholders rather than households.
Prior to the departure date of April 4, 2017, all survey personnel (supervisors, controllers, 
and enumerators) received the deployment plan detailing the villages to be surveyed and 
timetable. The roles, responsibilities and tasks for each team member were defined in 
instruction manuals that they received during training and used as references during data 
collection.
2.1.5. Number of Households Covered 
2,492 out of the 2,500 sampled households responded to the survey, constituting a success
rate of 99.7%. Missing observations are generally explained by the fact that in some villages, 
the number of listed households amounted to fewer than the predetermined sample size of 
25 households per village. In other cases, enumerators identified randomly selected 
households and replacements (totaling 28) without reaching the desired number of 25 
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households. A second round of data collection to supplement missing data or rectify 
identification errors was necessary in some villages, particularly in Niger. The response rate 
was much higher than is often the case for household surveys largely due to the advance work 
of the CESAO information campaign teams. By establishing a relationship with local 
stakeholders, government actors, and community members, CESAO and SAREL were able to 
enlist the help of village leaders in publicizing the surveys, encouraging participation, and 
underscoring the importance of village members’ input.
2.1.6. Sampling Weights
Sampling weights were calculated for each respondent and used in the statistical analysis to 
ensure that the results obtained from the sample “represented” the target population, i.e. the 
results were generalizable to the target population. It also allowed the calculation of correct 
measures of precision such as standard errors and confidence intervals.
For each respondent, the sampling weight was calculated to quantify the relative share of the 
population represented by the respondent. It allowed the extrapolation of the sample results 
to the target population. The sampling weights were calculated in steps. At the first step, the 
base weight was obtained as the inverse of the probability of selection. The subsequent steps 
in the sampling weight calculation were usually adjustments made to the base weights to 
ensure that the responding units were representative of the target population. One common 
adjustment was to correct for non-respondents. When some of the selected units do not 
participate in the survey, the remaining units may not represent the full target population 
unless their sampling weight is adjusted (usually inflated) to compensate for the loss of sample. 
When the non-response rate is high, efforts need to be taken to adjust the sampling weights 
so as to compensate for any response bias. For the RISE Midline survey, the response rate 
(after replacement) was very high; hence a simple rescaling of the base weights within the 
administrative division called “commune”. This is the non-response adjustment. It is necessary 
to redistribute the sampling weights of the households that did not respond to the 
participating households. Otherwise, there will be an under-representation of the target 
population. The adjustment should be done within a group (e.g. by village, or by commune, or 
by province, etc.). We chose commune to preserve the stability of the weights, to avoid given 
too much extra weight to few households. The adjustment procedure consisted in computing 
the adjustment factor within “commune” as the ratio of the sum of the sampling weights of 
all selected units and the sum of the sampling weights of the respondent units. At the second 
step, the sampling weights of the respondents were inflated by the adjustment factor.
2.1.7. Difficulties Encountered during Data Collection
Lessons learned during the baseline data collection greatly facilitated the process for the 
midline survey. Nevertheless, some difficulties persisted, and some new ones arose. While 
the enumeration teams were able to successfully carry out their duties and successfully collect 
the desired data, it is worth noting the challenges they encountered. They include: 
• Difficulties, in isolated cases, of village leaders being reticent to offer administrative 
support or full cooperation. This was especially true in Forgui and Konkoara-Yarce in 
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the Centre-Nord region of Burkina Faso. In most instances, collaboration was ensured 
by municipal advisors who accompanied the survey teams.
• Difficulties getting to survey locations. Vehicle availability and breakdowns hampered 
the survey efforts in some cases. The teams overcame this challenge by walking long 
distances when necessary or using motorbikes.
• Difficulties remaining in regular communication with the team. Some enumerators
found that the resources made available for calls were insufficient, and the networks 
were often unreliable. The team remedied this concern by providing phone allowances 
frequently and with minimal delay.
• Difficulties with equipment, such as GPS devices and scales. The number of 
questionnaires was never a problem, but if anything went wrong with a piece of 
equipment, this often slowed the work of the team. To address this concern, teams 
were encouraged to share equipment as necessary.
• Difficulties identifying households. Migration, the death of a household head, differently 
reported names, and errors in the establishment of household lists often led to 
difficulties in the sampling process.
• Difficulty of enumerators and survey participants understanding survey questions in a 
consistent manner. The problem did not arise for many questions, but there are always 
some questions that prove more complex in the field that even a pilot survey cannot
reveal. This was especially true for questions regarding obtaining a loan (Q306), 
agricultural production of the household (Q705b), and livelihood activities (Q1206 to 
1211). Gauging exposure to shocks was also more complicated and variable than 
anticipated. One issue, for example, concerned the determination of degrees of shock 
severity experienced by households. The questionnaire provided a scale to assess 
severity (None; Low impact; Moderate impact; High impact; Worst impact of all time), 
but it proved difficult to use because of challenges translating terms consistently across 
multiple local languages. To address different challenges that arose, the Assistant 
Coordinators undertook regular Skype calls to share information on how difficult 
questions were interpreted and to generate consistency in interpretations across the 
survey sites.
2.2. Exploitation of the Data Collected
Following the data collection phase in the field, the collected data was analyzed using a two￾step process consisting of data processing and report writing.
2.2.1. Data Processing
Processing of data consisted of four principal components: a systematic, manual check of all 
completed questionnaires; data entry; quality control of data entered; and file cleaning.
Checking and Coding Completed Questionnaires 
When questionnaires were brought back from the field, a team of enumerators and 
supervisors was established by CESAO to check the data. The goal was to prepare all 
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questionnaires for a systematic data entry process. During this work, the staff also coded 
some open-ended questions that could not be coded directly in the field. This allowed for a 
straightforward and efficient data entry process.
Data Entry and Quality Control
Data entry was carried out by approximately 20 staff members trained in the survey 
instruments, the input templates, and data entry protocols. Two Input Controllers, recruited 
and trained specifically for the task, supervised the organization and technical monitoring of 
the staff members’ work. They were responsible for verifying the accuracy and completeness 
of the recorded data. Controllers brought the staff’s attention to any entry errors they 
spotted so that corrections could be made efficiently before continuing the work. The Input 
Controllers themselves were supervised by CESAO’s data processing specialist. The CESAO
technical team ensured overall monitoring of the activity to meet the deadlines and guarantee 
proper functioning of logistics. 
File Cleaning
Consistent with protocols employed for the baseline data entry, SAREL and CESAO again 
opted to conduct double manual entry of all data, meaning that the data from each 
questionnaire were entered twice, by two different data entry staff members. CESAO met 
this requirement, and in doing so was able to perform necessary minor data corrections at 
the entry stage; this can be considered a first level of file cleaning. While adding to the time 
and cost of data entry, the double entry process made the overall data cleaning task
significantly easier.
Indicator and Difference-in-Difference Calculations
Once the cleaned data files were made available, CESAO and a team of statistical analysis 
experts calculated means for demographic variables, the desired indicators values, and the 
difference-in-differences from the baseline to midline across the High and Low exposure 
zones. In addition, the analysis team conducted a number of secondary analyses to explore 
hypotheses of potential interest to SAREL and USAID. It should be noted that the calculation 
of difference-in-differences required that the data files be identically formatted across the 
midline and baseline surveys. This required extensive effort, since minor differences in coding 
decisions would undermine the rigor of the Difference-in-Differences (DiD) analysis. 
2.2.2. Analytical Methodology for Statistical Analyses
The principal statistical task of study was to analyze the SAREL midline sample in relation to 
the baseline sample. That included first developing a descriptive analysis and then conducting 
analyses that allow for comparisons over time and across zones while accounting for potential 
confounding factors. We relied primarily on Difference-in-Differences analyses.
Descriptive Analysis 
The first set of analyses consisted of computing means with associated levels of precision. 
These statistics are disaggregated by stratum (High versus Low) and by RISE zone of each 
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country (Burkina Faso versus Niger). 
While the descriptive statistics do not constitute an evaluation of RISE impact over time, they 
nevertheless provide insights into potential differences at the time of the midline study.
Difference-in-Differences (DiD)
Simple differences as discussed in the previous section show the cross-sectional situation at 
Midline. The changes over time are not reflected in these simple differences. To incorporate 
the time factor, the midline estimates were compared to the baseline results. The DiD 
methodology isolates the intervention effect over time by comparing the change from baseline 
to midline in the High exposure zone to the change over time in the Low exposure zone.
The two graphs in Figure 2-2 below illustrate two situations. On the left, Figure 2-2A
illustrates a hypothetical situation in which both the intervention or High zone (blue line) and 
the non-intervention or Low zone (red line) progress in a similar way between Baseline (2015) 
and Midline (2017). This suggests that there was no significant effect of the intervention even 
if progress was observed during the study period. In contrast, Figure 2-2B on the right shows 
a clearly sharper increase for the intervention zone (blue line) compared to the non￾intervention zone (red line).
Figure 2-2: Hypothetical changes in a Difference-in-Difference Analysis
The DiD approach consists of subtracting the change in the Low zone (where no interventions 
took place) from the change in the High (intervention) zone in order to isolate the effects of 
the RISE activities after accounting for other potential reasons for change over time that 
would affect both the High and Low zones. An example follows in Figure 2-3.
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Figure 2-3: Hypothetical Difference-in-Differences Analysis
In the simple illustration above, the DiD estimated effect would be 14 points i.e. 18-4. Note 
that the difference between the Midline gap (57-38=19) and the Baseline gap (39-34=5) of 19 
minus 5 also leads to the DiD estimate of 14 points. 
In formal terms, the DiD is calculated in the following manner. Consider a variable of interest 
𝑦𝑦. We can write conduct DiD calculations using the following model
𝑦𝑦 = 𝛽𝛽0 + 𝛽𝛽1𝐼𝐼(𝐼𝐼𝐼𝐼𝐼𝐼) + 𝛽𝛽2𝐼𝐼(𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀 𝑀𝑀) + 𝛽𝛽12𝐼𝐼(𝐼𝐼𝐼𝐼𝐼𝐼)𝐼𝐼(𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀 𝑀𝑀),
where 𝐼𝐼(𝐼𝐼𝐼𝐼𝐼𝐼) is an indicator of the intervention zone (coded 1 for High) and 𝐼𝐼(𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀 𝑀𝑀) is 
an indicator of the survey wave (coded 1 for the midline survey and 0 for the baseline). The 
coefficients on those terms thus convey the impact solely of the zone and the survey wave, 
respectively. The interaction term conveys the DiD; under this model, the DiD estimate is 
𝛽𝛽̂
12 = �𝑦𝑦�𝐼𝐼𝐼𝐼𝐼𝐼,𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀 𝑀𝑀 − 𝑦𝑦�𝐼𝐼𝐼𝐼𝐼𝐼,𝐵𝐵𝐵𝐵𝐵𝐵 � − �𝑦𝑦�𝑁𝑁𝑁𝑁− ,𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀 𝑀𝑀 − 𝑦𝑦�𝑁𝑁𝑁𝑁− ,𝐵𝐵𝐵𝐵𝐵𝐵 �
where 𝑦𝑦�𝐼𝐼𝐼𝐼𝐼𝐼,𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀 𝑀𝑀 is the average of the variable of interest in the High exposure zone at the 
midline, and similarly for 𝑦𝑦�𝐼𝐼𝐼𝐼𝐼𝐼,𝐵𝐵𝐵𝐵𝐵𝐵 (mean for the High zone at the baseline), 𝑦𝑦�𝑁𝑁𝑁𝑁− ,𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀 𝑀𝑀
(mean for the Low zone at the midline), and 𝑦𝑦�𝑁𝑁𝑁𝑁− ,𝐵𝐵𝐵𝐵𝐵𝐵 (mean for the Low zone at the 
baseline).
Propensity score matching 
The DiD methodology described above identifies significant differences between the Low and 
High strata from baseline to midline. Unfortunately, because the survey is not a rigorous 
randomized control study, the DiD is not sufficient to attribute the identified changes to the 
RISE interventions. The propensity score matching (PSM) is a technique used in quasi￾experimental studies such as the RISE survey. In quasi-experimental studies the treatment and 
control groups are not always comparable. The PSM is then used to correct the lack of 
comparability between the treatment and control groups before applying the comparison test. 
Sahel Resilience Learning (SAREL)—RISE Midline Quantitative Survey Report
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One important aspect of the PSM methodology is the metric for deciding the similarity 
between the control and treatment samples. For the SAREL study, the nearest neighbor 
metric was used to match the High sample to the Low sample using a logistic regression. The 
person and household level characteristics used as predictors for the logistic regression were 
age, sex, marital status, literacy, and ethnicity of the head of the household. Note that age and 
sex apply to the child for the child-level indicators and to the head of household for the 
household-level indicators. Using the logistic regression model, a propensity score was 
calculated. Each element from the High sample was then matched to the nearest unit from 
the Low sample, i.e. the pair with the smallest propensity scores difference. 
The matching methodology described in the previous paragraph was applied independently to 
the baseline and midline samples. The two matched samples (i.e. baseline and midline) were 
then combined and analyzed for detecting differences using the DiD technique. 
As mentioned above, the PSM is a tool to help attribute possible differences to the RISE 
program. Unfortunately, very few indicators were significant. Hence, the PSM method was 
also applied to non-statistically significant differences with p-values up to about 0.30. The 
community-level indicators were not considered for the PSM analysis due to the sample size 
(i.e. only 100 villages in the study). Also, there were very few community-level characteristics 
to use for developing the logistic regression model. 
2.2.3. Report Preparation
This Midline Study Report was developed through a series of steps. Initially, SAREL’s data 
analysis experts developed an analysis plan. CESAO then submitted the data to SAREL and 
the data analysis experts calculated the relevant statistics and differences. SAREL transmitted 
findings to USAID concerning the 21 key indicators and developed the text for the present, 
full draft report. 
2.3. Methodological Notes and Limitations
2.3.1. Original Baseline Results vs. Recalculated Baseline Results
In attempting to reproduce the results reported for the baseline (see the September 2016 
report), we were unable to replicate 10 of the 21 indicators with exact precision. 
Several differences were observed, which required the following corrections and 
recalculations:
• The sampling weights were corrected for one village. The village had a total of 20 
households and they were all included in the survey. The sampling weights in that 
village did not account for this special circumstance and were corrected. It was not 
always clear how to treat the missing values, and the algorithms for the key indicators
did not in all cases provide guidelines on the treatment of missing values. For example, 
WEAI has many components (decision, autonomy, ownership, purchases, and credit), 
and all of the components should be combined to compute the composite index. It 
was not clear what decision should be taken when some component values of the 
modified WEAI are missing and the combined available component value falls below 
Sahel Resilience Learning (SAREL)—RISE Midline Quantitative Survey Report
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the threshold. If the missing component values had been known, then the WEAI might 
have increased.
• The weights associated with the gender file were corrected for several women. When 
a head of household had more than one spouse, a Kish grid was used to randomly 
select one woman. Therefore, in those situations, an adjustment had to be made to 
the weighting for women in polygamous households to account for their selection. 
This was not done during the baseline analysis, so a recalculation of baseline sampling 
weights was done for the midline report to ensure comparability.
• The gender questionnaire should be applied only to women who are heads of 
household or to women married to the head of household. In 22 cases, women who 
did not fit these categories responded to the baseline gender questionnaire. These 
women should have been excluded when calculating the gender baseline results.
• Similarly, some children initially identified in the household survey were not available 
during the anthropometry measurements phase, but they were kept in the analysis file 
used at baseline. Given their significant number (211 children), they were removed 
from the analysis file and the weights of the remaining children adjusted to compensate 
for the removal of those 211 children (non-response adjustment).
The differences observed between the baseline indicator results and the recalculated values 
are provided below:
1. Minor differences in calculation were observed for the following indicators: indicator 
3a - Average Value of HH Assets (FCFA (788,650 vs. 786,207 CFA); indicator 3b Asset 
Ownership (50.6 vs. 49.7 items); indicator 19 Proportion Supporting Equal Access for Males 
and Females (51.0% vs. 51.7%); and indicator 20 Share of Women Reporting Effective 
Participation (75.2% vs. 75.0%).
2. The women’s empowerment in agriculture index (WEAI) changed from 68.0 (baseline 
report) to the recalculated value of 66.9. The sampling weights associated to some 
women in the baseline needed adjustment. In the case of multiple eligible women, a 
Kish grid was used to select one woman. In the baseline, the women sampling weight 
calculation did not reflect this fact and thus needed adjustment.
3. Evidence of good governance (indicator 7) changed: 62.1% (baseline report) vs 55.9% 
(recalculated). This is a village level indicator, and for the baseline report, the village 
weights were not included in the calculation of the indicator. Therefore, an unweighted 
proportion was presented while the recalculated value is weighted.
4. Villages with adequate capacities to manage climate shocks changed: 30.5% (baseline 
report) vs. 25.6% (recalculated). The reason for the discrepancy is exactly the same as 
for the previously discussed indicator 7, Communities with Evidence of Good Governance; 
that is, unweighted results were presented in the baseline report.
5. Stunting and underweight prevalence rates were changed: 42.5% and 33.5% (baseline 
report) vs. 49.8% and 39.2% (recalculated), respectively. There are two reasons for 
the changes: first, the adjustment of the sampling weights due to the missing and sick 
children and second, the age shift between the WHO heights/weights standards and 
Sahel Resilience Learning (SAREL)—RISE Midline Quantitative Survey Report
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the SAREL coded child’s age in months. The problem was that the WHO labels the 
first 30 days as one month old while the RISE survey coded it as 0 months of age. 
Unfortunately, this shift in the coding of the age was not immediately detected at the 
time of the baseline report. Note that these two issues were identified and resolved 
only after the preliminary midline results were communicated to USAID in August 
2017. Hence, the results in this report are different from the ones provided to USAID 
earlier (In the August 2017 results, the recalculated results were equal to the baseline 
report results).
6. The minimum acceptable diet (MAD) also changed because of the missing and sick 
children mentioned in the previous point. The indicator changed from 5.7% (baseline 
report) to 6.3% (recalculated). Furthermore, for the same reason noted above, the 
value of MAD provided in August 2017 is different from the current recalculated value.
2.3.2. Limitations to the Evaluation Methodology
In employing a difference-in-differences approach, the evaluation team took considerable steps 
to account for the bias that often bedevils conventional observational studies, such as a secular 
change over time across the entire region or external interventions that overlap with the RISE 
activities. Nevertheless, the design of High and Low exposure zones coupled with DiD 
analyses is still only quasi-experimental, so it is worth noting some potential limitations. First, 
the differences over time in High and Low exposure zones can only capture changes since the 
baseline data were collected; if activities were already underway in the High zones, that could 
mask some of the impact of the activities (by reducing the difference in those zones between 
baseline and midline). Further, as noted earlier, interventions by other donors constitute a 
frequent concern in program evaluations in the Sahel. That problem is less severe if the 
assignment of interventions by other projects reaches some of the RISE High exposure zones 
and some of the Low exposure zones (which is likely the case). However, if a program covers 
a wide swath of the RISE zone, thus affecting most of both the High and Low areas, or if the 
external intervention happens to overlap largely with the RISE treatment and control zones, 
those external activities will again introduce bias and mask the true effects of the RISE 
initiative. Propensity Score Matching analyses of households in Low and High exposure zones 
on key observable characteristics may help to address these concerns upon collection of the 
endline data (though, in the absence of statistically significant differences in DiD analyses, 
matching exercises are unlikely to add new insights and were thus not employed at this midline 
stage). Finally, calculations of some indicators, such as household assets and the value of those
assets (which also affect other poverty indicators) are subject to the recall of household 
respondents, which could vary non-randomly if, for example, respondents suspect greater 
assistance by reporting lower values. Such a pattern would likely be consistent across the High 
and Low exposure zones and thus not bias the impact analysis, but it would result in imprecise 
measurements. We do not otherwise have reason to suspect a strong presence of social 
desirability bias; while campaigns were conducted to encourage participation, any effects on 
social desirability bias in responses would be equal in expectation across the High and Low 
exposure zones.
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2.3.3. Limitations to the RISE Study Design
The study had some limitations that can be addressed for the endline or for a redesign of the 
RISE study, if applicable. Some of the limitations are:
● The RISE survey was not optimally designed (e.g. in terms of sample size, going back 
to the same villages, allocating the same number of households per village, treating this 
as a quasi-RCT, designating the High vs Low areas, etc.) to detect differences over 
time. Principally, the large design effects (DEFF) for many key indicators demonstrate 
the low efficiency of the sample design. Further, the point estimates for many of the 
indicators have large uncertainties, as some indicators (e.g. depth of poverty) require 
much larger sample sizes in order to achieve a confidence interval of +/-5%, as shown 
in the statistical tables. In general, this suggests sample sizes not sufficiently large to 
ensure appropriate comparisons over time. The poverty indicators are especially 
complex and generally require a much larger sample to achieve equivalent precision. 
These challenging indicators, in terms of precision, should be kept in mind when 
redesigning the RISE study.
● Disaggregation is barely feasible when the factor has more than two levels, yet many 
of the key findings call for disaggregation not only by stratum but also by country, 
gender, etc. Sample sizes, in particular in the High stratum, should be increased.
● We only have 100 villages with which to evaluate village level indicators. Given the 
high variability in the village weights (a consequence of the PPS method), it would be 
helpful to increase the number of villages selected and/or to use a different method 
for selecting villages in order to obtain more precise primary sampling unit (PSU) 
weights. At the village level the probability of selection is proportional to the size of 
the village (PPS method). Since the size of the villages were different, the resulting 
weights using PPS were also different. When sampling weights are widely variable it 
negatively affects the precision of the associated estimates. Unfortunately, pursuing 
PSU-level and Household-level analyses will result in conflicting sampling design
optimization. Hence, some balance and prioritization will be necessary between the 
two objectives.
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3. Household and Village Descriptions
This chapter details some key household sociodemographic and economic characteristics that 
together create an overview of the living conditions of residents in the RISE study area. They 
are largely consistent with findings from the baseline survey, and with conventional wisdom 
of life in the Sahel: extreme poverty, large families, and very modest accommodations. Here, 
we present household sociodemographic and economic information, and we also provide data 
on the exposure to shocks that residents of the region face. In the course of addressing the 
results for each indicator later in the report, we also disaggregate the findings according to 
some of these sociodemographic characteristics, namely the sex of household heads, the 
marital status of household heads (monogamous, polygamous, etc.), the literacy of household 
heads, and the ethnicity of the household. After presenting data on all of the indicators, we 
summarize the correlations between these characteristics and the outcomes of interest.
3.1. Demographic Characteristics of Respondents
The demographic characteristics analyzed in this section include gender, age, marital status 
etc.
3.1.1. Structure of Respondents by Sex
Among the approximately 2,500 households included in the baseline survey were nearly 
19,000 individuals. Consistent with expectations, Table 3-1 indicates that just over half are 
female. Females, it should be noted, are the predominant target population for several of the 
RISE interventions.
Table 3-1: Population Distribution by Sex
Headcount Percentage (%)
Male 9,051 48.3
Female 9,688 51.7
Total 18,739 100.0
3.1.2. Population Age Trends
Overall, the average age of respondents was 19.8 and the median age was 13.5. This figure 
does not differ significantly across males and females (see Table 3-2). We note as we did in 
the baseline report that far over half of the population in the RISE study area has the status 
of minor, leaving responsibility for many people in the hands of heads of households, parents, 
and other adults.
Table 3-2: Average and Median Age by Sex
Sex
Age
Average Median
Male 19.6 13
Female 20.0 14
Together 19.8 13.5
Sahel Resilience Learning (SAREL)—RISE Midline Quantitative Survey Report
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3.1.3. Population Age Structure (Women/Men)
The age pyramid in Figure 3-1 provides additional information on the population by age 
and sex. It shows that, taken together, the bottom three age groups (0–5, 6–10, and 11–15 
years-old) comprise fully 60% of the surveyed population.
Figure 3-1: Population Age Structure
3.1.4. Relationship to Head of Household
Households consist of many types of people who maintain various relationships to the head 
of household. The sons and daughters of the heads of households account for about 52.4% of 
respondents, and spouses 16.0% (see Table 3-3).
Table 3-3: Relationship to Head of Household
Relationship to Head of Household Percentage (%)
Household Head 13.4
Spouse (wife/husband) 16.0
Own son/daughter 52.4
Child from spouse's other marriage 0.2
Step-son/step-daughter 2.2
Grandson/granddaughter 7.0
Brother/sister 2.1
(Biological) parent father/mother 1.7
Step-father/step-mother 0.1
30 20 10 0 10 20 30
0;5
6;10
11;15
16;20
21;25
26;30
31;35
36;40
41;45
46;50
51;55
56;60
61;65
66;70
71;75
76;80
Percentage
Age Strata
MALE FEMALE
Sahel Resilience Learning (SAREL)—RISE Midline Quantitative Survey Report
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Relationship to Head of Household Percentage (%)
Niece/nephew 3.0
Co-wife 0.1
House Help 0.0
Another household member 2.0
Total 100.0
3.1.5. Marital Status of Population Aged 12 or Over
As Table 3-4 illustrates, the population aged 12 and over consists predominantly of married 
persons--62.0%, including 38.9% monogamous and 23.1% polygamous. 32.6% have never been 
married.
Table 3-4: Marital Status of the Population
Marital Status Percentage (%)
Never got married 32.6
Married, monogamous 38.9
Married, polygamous 23.1
Cohabitation 0.1
Divorced/separated 1.1
Widow(er) 4.2
Total 100
3.2. Household Characteristics
3.2.1. Size and Composition of Households
Household sizes—measured as the number of people living under one budget and sharing the 
same meals who have been present for at least three months—are large in both countries. In 
Burkina Faso, households of 7-10 people are the most common, accounting for 32.6% of all 
households in the Burkina study region, followed by households with 4-6 people (25.1%). 
Those with over 10 people constitute 20.4% of households in Burkina Faso. In Niger, 33% of 
households have between 7 and 10 members, and an additional 16.6% have more than 10 
members. 
In the RISE area, more than half (59.4%) of all households have at least six people (see Table 
3-5). It should be noted that household size does not differ by the sex of the head of 
household.
Table 3-5: Household Size
Indicator Total
Country
Burkina Faso Niger
Household Size % % %
Less than 4 persons 23.4 21.9 25.3
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4–6 persons 25.1 25.1 25.1
7–10 persons 32.8 32.6 33.1
More than 10 persons 18.7 20.4 16.6
3.2.2. Characteristics of Heads of Household
55.6% of household heads are aged between 25 and 49, whereas 41.2% are over 50. Heads of 
households aged under 25 account for less than 5% of all households in the study area. By 
sex, the proportion of heads of households aged under 25 is 2.8% for men and 6.1% for 
women. Furthermore, the results show a significant proportion of female heads of household 
aged 50 and older. They account for 58.3% of female heads of households, compared to 39.3% 
of male heads of household in this age group (see Table 3-6). The difference owes to a 
greater relative number of widows than widowers.
Throughout the RISE area, male heads of household were the most numerous (26.1%) in the 
Hausa ethnic group while female heads of household were most common among the Mossi 
ethnic group (32.2%). Regarding ethnicity more generally, Table 3-6 indicates that Hausa 
households are the most numerous (25.6%) in the study area, followed by the Mossi (23.8%) 
and Fulani/Peul (19.6%).
The table also shows that a significant share of heads of household practice agriculture as their 
primary activity. Indeed, 77.2% of all respondents primarily practiced agriculture at the time 
of the survey. Trade (5.1%) and livestock (4.4%) are other common primary activities for 
heads of households. Based on the sex of the head of household, men outnumber women in 
agriculture (79.8% vs. 54.4%). It is also worth noting that female heads of household are more 
involved in trade compared to men.
Table 3-6: Distribution of Heads of Households by Selected Characteristics and Sex
Characteristics HH Head 
Total
Sex of the Head of Household
Male Female
Age
<25 years old 3.2 2.8 6.1
25-49 years old 55.6 57.9 35.6
50 and older 41.2 39.3 58.3
Ethnic Group
Mossi 23.9 22.9 32.2
Fulfuldé/Peul 19.6 20.0 15.8
Gourmantché 9.6 10.1 5.3
Songhaï/Sonraï 7.0 6.4 11.9
Touareg 1.3 1.4 0.7
Bella 7.6 7.4 10.0
Other ethnic groups 1.7 1.9 0.6
Haoussa 25.6 26.2 21.0
Djerma 3.6 3.7 2.6
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Characteristics HH Head 
Total
Sex of the Head of Household
Male Female
Main Activity
Agriculture 77.2 79.8 54.4
Livestock 4.4 4.6 2.4
Trade 5.1 4.5 10.4
N/A 4.5 2.5 22.1
Other activities 8.5 8.3 10.3
Unaccounted for 0.3 0.4 0.2
Overall, six in 10 heads of household are involved in monogamous unions, while 29.2% are in 
polygamous ones and 1.1% are single (never married). Divorced or separated females account 
for 5.1% of heads of household while the widowed female head of house represents 56.6%. It 
is exceedingly uncommon in the region to find households led by a partnered but non-married 
person. Figure 3.2 details the marital status of heads of household by gender.
Figure 3-2: Heads of Household by Marital Status and Sex
3.2.3. Literacy by Language
Approximately 85% of the sampled population never attended school. Similarly, a very large 
share of the population surveyed (87.9%) is not literate in the local language (See Table 3-7).
Table 3-7: Local Language Literacy
Local Language Literate Percentage (%)
Yes 7.1
No 92.9
Total 100.0
0
10
20
30
40
50
60
70
Never married Monogamous marriagePolygamous marriage Partnered Divorced/separated Widowed
1.2
66.4
30.7
0.7 0.1 0.5 1.1
21.6
16.0
0.0
5.1
56.6
1.1
61.8
29.2
0.1 1.0
6.7
Male
Female
TOTAL
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Regarding other languages, only French (8.6%) registered close to the rate of local language 
literacy. As Table 3-8 illustrates, English and Arabic are read only marginally in the study 
region.
Table 3-8: Foreign Language Literacy
Foreign Language Literate Percentage (%)
French 8.6
English 1.2
Arabic 5.2
Other 0.1
None 84.9
Total 100
3.2.4. Education Levels 
Overall, 73.7% of individuals in the surveyed households never attended school. This rate is 
notably higher for females (78%) than for males (69%) (See Figure 3-3).
Figure 3-3: Population's Educational Attainment by Sex
3.3. Home Features and Construction
3.3.1. Main Housing Characteristics
A housing room is understood as an enclosed space in a home which is finished and habitable 
all year round. 
The survey results show that surveyed households have 3.5 rooms on average. The size of 
homes varies according to the disaggregation factors outlined in Table 3-9.
Space is critical to the growth and health of an individual. Close physical proximity between 
individuals in a household is therefore not conducive to development and maintaining 
69.0
23.0
6.5
1.2
0.2
78.1
17.4
4.1
0.4
0.1
73.7
20.1
5.3
0.8
0.1
0 10 20 30 40 50 60 70 80 90
No Schooling
Primary School
1st Cycle, Secondary
2nd Cycle, Secondary
Professional School
TOTAL
Female
Male
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cleanliness. 
To measure this, the overload rate, i.e., the percentage of households with more than three 
people per room, was calculated. Across the sampled population, 60% of individuals live in an 
overload situation. 
Table 3-9: Number of Rooms and the Overcrowding Rate
Number of Housing Rooms Overcrowding Rate
Min Max Average
Country
Burkina Faso 1 8 3.3 0.6
Niger 1 8 3.8 0.7
Whole Area 1 8 3.5 0.6
Stratum
High 1 8 3.6 0.7
Low 1 8 3.4 0.6
Sex of the Head of Household
Male 1 8 3.5 0.6
Female 1 8 3.3 1.0
Marital Status of Household Head
Never got married 1 7 3.2 1.4
Married, monogamous 1 8 3.6 0.7
Married, polygamous 1 8 3.4 0.4
Cohabitation 1 3 3.0 0.5
Divorced/separated 1 7 3.8 1.7
Widow(er) 1 8 3.2 0.9
3.3.2. Building Materials for Dwelling Structures 
Living in insecure housing may have adverse effects on the health and productive capacity of 
individuals living in RISE area households. One way to measure the precariousness of dwelling 
structures is to account for the type of materials used in household construction.
The survey data indicates that approximately 80% of households surveyed have walls built of 
clay or mud brick. 11% have walls built of straw, and a very small percentage are constructed 
with sustainable and good quality materials (3% used cement/concrete and less than 1% used 
baked bricks). In Table 3-10, these figures are disaggregated by country.
Table 3-10: Wall-Building Materials for Dwelling Structures
Wall-Building 
Material
% of All 
Household 
Walls
RISE Zone 
of Burkina 
Faso
RISE Zone 
of Niger
Cement 3.3 5.5 0.7
Fired Brick 0.5 0.5 0.4
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Clay/Mud Brick 79.9 83.4 75.5
Wood/Bamboo 3 0.9 5.6
Stone 0 0 0
Sheet Metal 0 0 0
Straw 11.3 8 15.4
Other 2 1.7 2.4
Total 100 100 100
As far as roof-building materials go, Table 3-11 indicates that wood and earth (34%), straw 
(32.9%), and sheet metal (32.7%) are the most common forms of roofing in the RISE region.
Most of the sheet metal roofs are found in Burkina Faso, whereas wood/earth and straw roofs 
are more common in Niger. 
Table 3-11: Roof-Building Materials for the Main Housing
Roof-Building 
Material
% of All Household 
Roofs
RISE Zone of 
Burkina Faso
RISE Zone of Niger
Sheet Metal 32.7 54 6.3
Cement 0.2 0.3 0.2
Straw or Thatch 32.9 32.8 33
Wood and Earth 34 12.6 60.5
Total 100 100 100
3.3.3. Main Housing Flooring Type
Dirt floors with no quality material such as cement or tiling as a cover exacerbate the spread 
of germs and disease. The survey results show that only about one-fifth of households (22%) 
covered the floor of their dwelling with concrete/cement, and that almost all others use either 
clay (37%) or sand (40%). See Table 3-12.
Table 3-12: Flooring Materials in Dwelling Structures
Flooring Material % of All Household 
Floors
RISE Zone of 
Burkina Faso
RISE Zone of Niger
Dirt/Clay 37.1 48.6 22.9
Cow Dung 0.3 0.5 0
Concrete/Cement 22.1 36.2 4.7
Sand 39.9 13.7 72.2
Other 0.6 1 0.2
Total 100 100 100
3.4. Drinking Water Supply
The importance of drinking water for the health and productivity of individuals is well 
established, and access to adequate supplies of clean water is of paramount importance to 
humans. The Household Questionnaire included questions regarding households' main source 
of water. 
Sahel Resilience Learning (SAREL)—RISE Midline Quantitative Survey Report
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The survey results show that half of the surveyed households (48.8%) use boreholes/piped 
wells for their supply of drinking water, whereas only a small percentage use public or private 
taps. Results based on disaggregation variables are shown in Table 3-13.
Table 3-13: Main Source of Households’ Drinking Water Supply
Source of Drinking Water % of All Households
Surface Water 1.3
Protected Well 4.3
Uncovered Well with Drains 12.9
Traditional Well 16.9
Borehole/Tube Well 48.8
Public Tap 12.8
Own Indoor Tap 2.1
Shared Outdoor Tap 0.9
Bottled Water 0.1
Reducing distances and waiting time for fetching water reduce the workloads of household 
members (particularly women) and allow them to devote more time and energy to other 
important activities including childcare, education, and food production. From a question on 
the Household Questionnaire, the data indicates that, on average, households in the RISE 
zone spend 73 minutes per day to get the water they require. Note that this represents a 
decrease from the 82-minute average reported during the baseline survey. Water collection 
time in minutes are disaggregated by various factors in Table 3-14.
Table 3-14: Average Water Collection Time in Minutes
Household Characteristics Average Water Collection Time (min)
Country 
Burkina Faso 84
Niger 60
Whole Area 73
Stratum 
High 65
Low 81
Sex of the Head of Household
Male 71
Female 89
Marital Status of Household Head
Never got married 42
Married, monogamous 72
Married, polygamous 76
Cohabitation 120
Divorced/separated 59
Sahel Resilience Learning (SAREL)—RISE Midline Quantitative Survey Report
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Household Characteristics Average Water Collection Time (min)
Widow(er) 80
3.5. Types of Toilets Used by Households
The vast majority of households surveyed (about 80%) go to the toilet in non-improved 
sanitation facilities (typically either in the open or using latrines with no covers). Most others 
use slab-covered pit latrines, while less than 2% use other types of toilets.
3.6. Livestock Headcount 
The most common animals kept as livestock in the RISE zone are cattle, sheep, goats and 
poultry. The average number of livestock per household in Burkina Faso is notably higher than 
in Niger: households in Burkina Faso reported owning an average of six cattle, six sheep, and 
five goats, compared to one head of cattle, two sheep, and three goats in Niger. Table 3-15
shows livestock holdings in the RISE zone disaggregated by country and by High/Low strata.
Table 3-15: Average Number of Livestock Owned by Households
Together Country Stratum
Burkina Faso Niger Low High
Cattle 3 5 1 3 3
Sheep 4 5 2 4 4
Goats 5 6 3 5 5
Donkeys 1 1 0 1 0
Horses 0 0 0 0 0
Pigs 0 0 0 0 0
Camels-dromedaries 0 0 0 0 0
Rabbits 0 0 0 0 0
Hens 6 8 4 6 6
Guinea fowls 2 3 1 2 2
Turkeys 0 0 0 0 0
Ducks 0 0 0 0 0
Pigeons 1 1 1 1 1
3.7. Farmlands
Households have a range of possible uses for farmland (rain-fed agriculture, off-season farms, 
gardens, etc.) but rain-fed fields are by far the most common type of farmland across the RISE 
zone (97.4% in Burkina Faso, and 95% in Niger). See Table 3-16.
Table 3-16: Breakout of farmlands by type
Farm Types Country Total
Burkina Faso Niger
Rain-fed farm 97.4 95 96.1
Off-season 1.0 2.9 2.0
Orchard 0.2 0.1 0.2
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Hydro-agricultural 
Development
0.0 1.3 0.7
Garden 0.7 0.0 0.3
Rain-fed + off-season 0.6 0.6 0.6
The most common field size is 1-3 hectares, which 43% of households exploit. Approximately 
46% of households possess between 3 and 10 hectares. Only 5% of households have more 
than 10 hectares, and 5% have one hectare or less. See Table 3-17.
Table 3-17: Average Area of Land Owned by Households
Field Size Country Total
Burkina Faso Niger
0-1ha 4.5 6.1 5.2
1-3ha 46.4 38.2 42.7
3-5ha 26.6 24.5 25.7
5-10ha 18.0 24.2 20.8
10+ ha 4.4 7.0 5.6
3.8. Sources of Household Revenue
We noted earlier that a vast majority of heads of households rely on agriculture as their 
primary activity. Among all individuals above the age of 12 in the surveyed households, 59% 
do so. The majority of both men (67.8%) and women (50.4%) are farmers in the RISE zone.
Figure 3-4: Structure of the Population Aged 12 and older by Main Activity
0.0
10.0
20.0
30.0
40.0
50.0
60.0
70.0
Agriculture Livestock Trade No Activity Other
Males 67.8 5.2 3.4 16.9 6.7
Females 50.4 2.9 4.3 35.3 7.1
Total 58.6 4.0 3.9 26.7 6.9
%
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Breakout of Main Activities by Age Groups
Figure 3-5 and Table 3-18 below disaggregate the main activities of RISE survey household 
members in both strata according to six age groups. Agriculture is the dominant occupation 
among all age groups between 19 and 65 years of age, averaging approximately 67% for groups 
between 28 and 65 years, and slightly less (60%) for the 19–27-year-old group.
Figure 3-5: Main Activities by Age Group
Approximately half of household members in the 12-18-year-old group are economically 
active, most of them in agriculture (42%). “Inactive” members of this age cohort include 
children enrolled in school. Not surprisingly, economic activity drops sharply in the group 
aged 66 and older with slightly less than 20 percent still engaged in some activity, mainly 
agriculture (about 45%) and some livestock raising (2.2%) and trade (2.9%). 
Table 3-18: Main Activities by Age Group
Main Activity
Age group
Total 12-18 
yrs.
19-27 yrs. 28-35 yrs. 36-50 
yrs.
51-65 
yrs. 66+ yrs.
Agriculture 42 59.4 67.7 69.3 66.5 44.9 58.6
Livestock 4.0 4.0 4.2 4.1 4.1 2.2 4.0
Trade 1.3 3.4 5.5 5.3 5.8 2.9 3.9
No Activity 48.7 24.9 14.2 13.2 16.9 44.2 26.7
Other 4.2 8.3 8.4 8.0 6.7 5.8 6.9
Total 100 100 100 100 100 100 100
3.9. Exposure to Shocks
In this section, we provide information on shocks sustained by households in the RISE zone 
over the twelve months prior to the midline study, and we offer some comparative insights 
regarding exposure to shocks at this midline point compared to the baseline study.
0 10 20 30 40 50 60 70 80 90 100
12-18 yrs.
19-27 yrs.
28-35 yrs.
36-50 yrs.
51-65 yrs.
66+ yrs.
Total
% Main Activity
Agriculture
Livestock
Trade
No Activity
Other
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3.9.1. Exposure to Shocks over the Previous Twelve Months
Nearly every household in the study reported experiencing shocks over the twelve months 
prior to the midline survey: 96% overall, including 94% of households in Burkina Faso and 
98.4% of households in Niger, noted that they had been exposed to a shock during that period 
(see Table 3-19). 
This is a particularly noteworthy finding, particularly because only about 65% of respondents 
had reported experiencing a shock during the twelve months prior to the baseline survey in 
2015. The sharp uptick in shock exposure could be a function of a number of different factors. 
First is the possibility that the region simply faced more shocks than it had during the previous 
study period, perhaps due to worsening climate effects, perhaps due to the uptick in violent 
extremism in the region, or due to other factors. Second, it may be the case that residents of 
the region are increasingly cognizant of the concept of shocks and are more attuned to the 
impact of shocks on their own household conditions. This could be taken as a positive trend 
in reporting, perhaps as a function of RISE activities and others like them, rather than an 
adverse trend in actual shocks occurring in the region. Third, it may be that the survey 
enumerators themselves have a more refined understanding of shocks and thus posed the 
question in a slightly different way. The data we collected on types of shocks (see below) does 
not suggest that the period preceding the midline survey was particularly noteworthy in terms 
of shocks, (i.e. there was no striking jump in the share of households exposed to an insect 
invasion, drought or other major event), so our suspicion is that the latter two explanations 
may be contributing to this increase in shock exposure.
As Table 3-19 also shows, there has not been an improvement in the High exposure zone 
versus the Low exposure zone in terms of exposure to shocks. In both strata, approximately 
96 percent of households reported exposure to a shock during the previous twelve months.
Table 3-19: Shock Distribution over the Previous Twelve Months (%)
Country
Stratum* Burkina Faso Niger Total
Low 95.6 97.3 96.3
High 92.2 99.4 95.7
Together 94.0 98.4 96.0
3.9.2. Types of Shocks Experienced over the Previous Twelve 
Months
Regarding types of shocks that households experience in the region, the most common form 
of shock was drought or too little rain, which has direct and immediate consequences for the 
many residents of the region who rely primarily on agriculture for their livelihood. About one￾fifth of households reported this experience during the prior twelve months. Other common 
forms of shock experienced by households in the region were sharp increases in food prices 
(16.9% of households), disease and health expenses (10%), animal diseases (10%), insect 
invasions (9%), and excessive rains (6%). An additional 9% of households faced psychological 
shocks due to a death, emigration, or illness in the family. See Table 3-20 for details. Note 
Sahel Resilience Learning (SAREL)—RISE Midline Quantitative Survey Report
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that the figures report the distribution of shocks by type as reported by households, but many 
households could have experienced more than one type of shock. It is also important to note 
that most shocks are related to weather events either directly or indirectly (through the 
impact on prices, animals, etc.), which may have implications for the importance of RISE 
interventions that explicitly aim to offset adverse consequences due to weather.
Table 3-20: Shocks sustained over the previous 12 months in RISE zone (percentage)
Type of Shocks High 
Exposure 
(%)
Low 
Exposure
(%)
Total
(%)
Natural disasters
Excessive rains 5.3 6.5 5.9
Too little rain/drought 18.9 21.4 20.1
Massive insect invasion 8.7 9.0 8.8
Epizootic (animal disease outbreak) 9.9 9.3 9.6
Bush fires 0.2 0.2 0.2
Conflict-related shocks 0.4 0.7 0.6
Land conflicts 0.5 0.5 0.5
Conflicts between farmers and herders 0.0 0.2 0.1
Theft of assets/holdups (animals. crops. etc.) 3.7 3.3 3.5
Socioeconomic shocks 
Sharp food price increase 15.9 18.1 16.9
Unavailability of agricultural or livestock inputs 3.8 2.9 3.4
Drop in agricultural or livestock product demand 0.8 1.2 1.0
Disease/exceptional health-related expense 10.7 9.9 10.3
Debt repayment 3.4 2.4 2.9
Increase in price of agricultural or livestock inputs 3.3 2.1 2.7
Drop in price of agricultural or livestock products 0.5 1.6 1.0
Job loss by household member 0.2 0.5 0.4
Long-term unemployment 0.2 0.6 0.4
Abrupt end of assistance/regular support from outside the 
household 0.8 0.4 0.6
Sudden increase in household size (including birth: triplets 
etc.) 1.0 1.0 1.0
Anthropogenic Shocks 
Fire (house. fields) 0.7 0.4 0.5
Psychosocial Shocks 
Death of household member 4.2 3.2 3.8
Emigration of household member 1.2 1.3 1.2
Serious illness of household member 5.2 2.9 4.1
Other Shocks 
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Type of Shocks High 
Exposure 
(%)
Low 
Exposure
(%)
Total
(%)
Forced repatriation 0.3 0.2 0.2
Household dislocation 0.2 0.2 0.2
3.9.3. Perceived Impact of Shocks
Whereas climate and other natural shocks appear to be most ubiquitous, Table 3-21 below 
indicates that some of the hardest felt shocks are actually anthropogenic (such as fires) and 
psychosocial (related to absence, loss, or illness of a household member). One-third of those 
who experienced an anthropogenic shock called this shock the worst of any they experienced. 
Further, approximately two-thirds of households called the psychosocial shocks they 
experienced either strong or the worst that they experienced.
Table 3-21: Perceived Impact by Type of Shock (%)
Shock Structure None Slight 
impact
Medium 
impact
Strong 
impact
Worst 
impact Total
Natural Disaster 0.6 12.4 24.9 60.3 1.8 100
Conflicts 2.1 22.5 13.9 59.6 2.0 100
Socioeconomic 1.9 9.6 23.4 59.9 5.2 100
Anthropogenic 2.7 9.1 15.3 39.7 33.1 100
Psychosocial 3.9 10.8 17.8 61.7 5.8 100
Other 0.0 20.0 17.8 49.9 12.3 100
Total 1.5 11.3 23.4 60.1 3.8 100
3.9.4. Shock Recovery and Coping
The midline data suggest that shocks represent a serious setback for households, and that 
recovery varies greatly across shock type and household. As Table 3-22 indicates, 
approximately half of all shocks (49.1%) leave households unable to recover. Worst are the 
anthropogenic shocks, but socioeconomic, natural, and psychosocial all leave at least half of 
households who experience them unable to recover. Just 19.8% of households reported that 
they recovered to the same level or better, which is a drop from the 23.3% of households 
reporting the same recovery in the baseline survey from 2015. Approximately one-third of 
households (31.1%) reported recovering somewhat but still being left worse off.
Table 3-22: Recovery by Type of Shock
Shock Type Did not 
recover
Recovered 
some. but 
worse off
Recovered 
to same 
level
Recovered 
and better 
off
Unaffected
Natural Disaster 43.3 36.7 15.9 3.5 0.6
Conflicts 38.2 36.7 12.2 11.2 1.7
Socioeconomic 54.5 27.6 11.4 5.1 1.4
Anthropogenic 70.2 10.6 16.5 0.0 2.7
Psychosocial 50.8 18.3 17.8 9.1 4.0
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Other 63.1 28.3 6.1 2.5 0.0
Total 49.0 31.1 13.8 4.8 1.2
Regarding strategies for coping in the face of shock, households in the Sahel have developed 
a number of mechanisms. As Table 3-23 indicates, the most common coping strategy 
employed during the prior twelve months is to sell off animals; 81.2% of households in Burkina 
Faso and 66.9% of households in Niger adopted this approach. Other common coping 
strategies included reducing food rations—used by between one-quarter and one-third of 
households—and taking a loan with a friend. In fact, in Niger, 60% of households facing a shock 
sought a loan from a friend, whereas 25% did so in Burkina. Temporary migration is another 
common response to shock in Niger, where about one-third of households had members 
who chose this strategy. Migration is less common among Burkinabé (6.1%).
Some notable differences stand out across the High and Low exposure zones. Households in 
the High exposure zone are notably more likely to use their savings in response to shocks, 
especially in Burkina Faso (41.7% in the High zone versus 15.2% in the Low zone). Further, 
those in the High zone are less likely to sell off animals or take cattle in search of pasture in 
Burkina Faso. Those in the High exposure zones in both countries are less likely to obtain 
remittances from relatives in migration. 
Table 3-23: Strategies employed by surveyed households to cope with shocks in previous 12 months (as percentage of all 
strategies listed)
Strategies Burkina Faso (%) Niger (%)
High Low Total High Low Total
Take cattle in search of 
pasture
2.1 12.5 7.7 2.4 0.6 1.6
Sell animals 77.6 84.2 81.2 67.8 65.8 66.9
Slaughter cattle 2.3 4.2 3.3 2.4 1.0 1.8
Rent land 0.3 0.4 0.3 10.7 7.7 9.3
Migrate with several family 
members
2.1 9.6 6.1 34.1 34.8 34.4
Migrate with entire family 0.0 0.3 0.2 0.2 0.3 0.2
Send children to live with 
relatives
2.3 0.5 1.3 10.4 2.1 6.6
Withdraw children from 
school
1.6 0.8 1.2 1.0 0.1 0.7
Move into less expensive 
lodgings
0.0 0.0 0.0 0.3 0.0 0.2
Reduce food rations served 10.9 35.9 24.2 36.7 25.3 31.6
Take new. salaried work 6.6 2.1 4.2 2.7 2.3 2.5
Sell household goods 0.5 .7 0.6 21.6 8.3 15.6
Sell productive assets 0.0 0.1 0.4 1.8 1.7 1.8
Contract loan with NGO 0.6 0.4 0.5 2.4 2.0 2.2
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Strategies Burkina Faso (%) Niger (%)
High Low Total High Low Total
Contract bank loan 1.1 1.5 1.3 0.2 0.0 0.1
Contract loan with 
moneylender
5.6 14.2 10.1 3.0 5.9 4.3
Contract loan with friend 19.1 29.4 24.6 62.3 58.0 60.4
Send child to work to earn 
money
0.5 0.5 0.5 4.6 4.8 4.7
Receive money or food 
from a family member
25.2 22.1 23.6 25.1 28.8 26.8
Receive government food 
aid
0.4 4.6 2.6 1.2 1.8 1.5
Receive NGO food aid 2.0 2.0 2.0 6.6 1.0 4.1
Participate in CFW/FFW 2.8 0.5 1.6 8.4 0.7 4.9
Use savings 41.7 15.2 27.6 16.1 11.5 14.0
Obtain remittance from 
relative in migration
2.9 8.5 5.9 8.1 17.5 12.3
Consume a hardship 
product
0.4 2.1 1.3 5.4 2.3 4.0
Dig up termite hill for grain 0.0 0.0 0.1 0.2 0.1 0.2
Hunt. gather food products 0.4 2.3 1.5 4.3 13.2 8.4
Consume food reserves 2.6 6.0 4.4 28.3 16.4 22.9
Reduce number of meals 6.6 27.1 17.5 23.0 35.0 34.1
Other 5.0 10.7 8.1 28.5 25.3 27.1
We do not have information from respondents regarding distinct coping strategies that they 
use in response to particular types of shocks (i.e. what coping strategies they use in response 
to psychosocial shocks as opposed to socioeconomic shocks, for example). Because 
households frequently confront multiple, overlapping shocks, it may be difficult for them to 
parse their coping strategies in this way. Nevertheless, the data on responses to shock offers 
some interesting insights. First, shocks in precipitation, animal disease, insect invasions, and 
higher food prices are all integrally related and of serious consequence to households in the 
RISE zone. We also know from the data that selling animals is one of the most common 
coping strategies in the face of shocks. Doing so provides a number of immediate benefits for 
households, even if it entails longer-term costs: they gain some financial flexibility from the 
sales, they avert further losses if their animals are susceptible to disease or cannot acquire 
adequate food themselves, and they reduce their household labor costs at a time when their 
efforts may be needed in other areas. Thus, the fact that those weather-related shocks are 
high and that the selling of animals is a common shock response may well be related. The 
implications for programming are that, in the face of weather-related shocks, households need 
short-term financial flexibility, monitoring and protection of their animals’ health, and 
Sahel Resilience Learning (SAREL)—RISE Midline Quantitative Survey Report
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strategies to conserve their labor output for critical needs.
Other common responses to shock are reducing food intake, receiving aid from a friend, 
taking on a loan from a friend, and using savings. Given social norms that we observed during
the course of the field study portion of the midline performance study—noting, for example, 
that families receiving cash transfers often shared those transfers with community members 
as a form of investment in informal insurance—it is likely that psychosocial and anthropogenic 
shocks would be more likely addressed through aid from others and perhaps personal 
restraint. Contracting loans with friends may be more common in the face of socioeconomic 
shocks, though we note again that these shocks are often related and overlapping.
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4. Economic Well-Being / Livelihoods
To improve resilience in the Sahel, the RISE program is constructed around three central 
components, as well as a set of cross-cutting measures. The first component aims to achieve 
increased and sustainable well-being by improving incomes, food access, assets, and the 
capacity to adapt to changing conditions. To address this component, RISE seeks several 
intermediate results:
• Diversified economic opportunities
• Intensified production and marketing
• Improved access to financial services
• Increase of market infrastructures
One rationale for these intermediate results is that households and communities facing regular 
stresses and repeated shocks remain vulnerable if their revenue streams are tied solely to one 
endeavor, particularly a climate-dependent one, such as small-scale farming. Thus, generating 
new income streams serves as a form of risk protection. Further, intensifying production and 
marketing can increase income streams in most residents’ principal livelihood domain, so that 
more resources can be set aside to address crises. Next, access to financial services gives 
households and communities a mechanism both for securing their savings and for obtaining 
loans; these two services both reduce risk and create new economic opportunities. Finally, as 
residents of the RISE zone develop strategies for reducing risk and raising revenues, an 
improved market infrastructure can provide trade opportunities so that households and 
communities can envision livelihood strategies that take them beyond subsistence. If these 
intermediate results are achieved, households and communities in the RISE zone should 
realize improved and sustainable wellbeing, which in turn should limit the need for repeated 
humanitarian assistance.
The main livelihood activities of the target population include the following: farming, livestock 
raising, gardening, small-scale trade, artisan-repair, etc. Because most of these livelihoods 
depend critically on adequate rain and soils, vulnerabilities due to climate or other 
catastrophic events are particularly high.
To address those vulnerabilities, improve livelihoods, and reduce the need for humanitarian 
assistance, the RISE Implementing Partners (IPs) are conducting a number of specific 
livelihood-related activities. They include: conservation agriculture and farmer managed 
natural regeneration (FMNR), market and home gardening, village based savings and loan 
programs, poultry and small ruminant rearing for nutrition and cash, training community-based 
solution providers (CBSP) who can provide services and inputs to producers and production 
groups, habbanayé (women receiving and raising small ruminants who, after 18 months, keep 
the offspring and pass the animals on to other vulnerable women), and access to credit in 
association with small enterprises and savings programs at the village level. In addition, some 
activities aim to address the livelihood and health components simultaneously, such as the 
promotion of bio-fortified seed in market gardens. Other interventions, such as bio-
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reclamation of degraded lands/cash for assets development and securing of women’s tenure 
rights for gardening, aim to address both the livelihood and governance components.
Specific indicators measured through the baseline and midline surveys that track progress 
toward the livelihood objectives include the following:
• Indicator 1: Depth of Poverty
• Indicator 3a: Average Value of Household Assets
• Indicator 3b: Asset Ownership
• Indicator 4: Prevalence of Poverty
• Indicator 6: Number of Households with Income from Non-Agricultural Sources
A few challenges arise in determining progress toward the livelihood goals from the baseline 
stage to the midline. First, the evaluation team discovered fairly notable cross-country 
differences in poverty in the Burkina Faso and Niger samples; far more households were 
categorized as extremely poor (as defined by the $1.90 standard threshold) in Niger than in 
Burkina Faso. This poses a challenge in the sense that the RISE interventions were not 
stratified by country or region, so we have less leverage than may be necessary to evaluate 
how the intervention effects relate to this cross-border difference. Second, the value of assets 
proved particularly difficult to measure; respondents were not asked the value of older assets 
at baseline, and whereas the midline survey corrects for that, the measure depends on 
respondents to determine a current value for those older assets. Finally, the status of 
household migrants can obscure revenue and wealth measures, despite the efforts of 
enumerators to extract complete information on household livelihoods.
Overview of results: in the Livelihoods category of indicators, two are statistically significant 
or approach statistical significance. First, depth of poverty decreased somewhat in the High 
exposure areas (from 27.8% to 25.9%), while it increased slightly in the Low exposure areas 
(from 23.0 to 26.2%). The difference-in-differences of approximately 5 percentage points 
approaches statistical significance, though it is short of conventional levels (p=0.14). Second, 
households with revenue from non-agricultural resources improved from 72.6% at baseline 
to 77.3% at midline in the High exposure areas, while dropping slightly in the Low exposure 
areas (from 71.8% to 69.1%). The improvement in the High exposure areas is close to 
conventional levels of statistical significance (0.08), and the difference-in-differences across the 
High and Low exposure areas is statistically significant at the 97% confidence level. In the 
results that follow, we place greater emphasis on these two findings, though we include results 
for each of the indicators.
4.1 Prevalence of Poverty (Indicator 4)
The prevalence of poverty indicates the proportion of individuals living under the poverty line. 
The poverty line used in this report is $1.90 which reflects the current standard used by the 
World Bank since October 2015. For the baseline report, the poverty line used was $1.25 to 
reflect the World Bank standards at the time. However, in light of the new standards, the 
Sahel Resilience Learning (SAREL)—RISE Midline Quantitative Survey Report
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baseline poverty related indicators (prevalence and depth) are recalculated in this report to 
allow the comparison with the midline results.
The prevalence of poverty is calculated using the consumption expenditures rather than 
reported income. The consumption expenditures include food, non-food, and durable goods 
expenditures, excluding investments and using imputed rent values. Lodging expenditures 
information was not collected by the RISE baseline or midline survey given the infrequency of 
housing rentals and sales in the rural areas concerned. In order to determine an appropriate 
value for lodging expenditures, auxiliary information from the 2009-2010 Integrated Survey 
on Household Living Conditions (EICVM) conducted by Institut National de la Statistique et de 
Démographie (INSD) du Burkina Faso was used to estimate imputed rent of households, then 
the value was adjusted using the consumer price index (CPI). The resulting poverty line was 
adjusted using the World Bank’s purchasing power parity (PPP) rates to convert the amount 
to the local currency, i.e. Franc CFA. More details on the determination of the poverty line 
and the related indicators can be found in Appendix A.
Using the World Bank poverty line of $1.90, close to two-thirds or 63.8% of the RISE program 
area inhabitants live in poverty – that is, with less than 451.6 FCFA a day in Burkina Faso and 
less than 460.1 FCFA a day in Niger. There is no statistically significant difference in the 
prevalence of poverty between the High and Low exposure strata.
Comparison of Baseline and Midline
Table 4-1 shows no significant change between baseline and midline results in the RISE 
program zone. Similarly, there is no significant change within the strata. The prevalence of 
poverty remained unchanged in the High and Low zones. If the trend continues, however, the 
endline may show a significant increase of prevalence of poverty in the Low zone.
Table 4-1: T-test comparison between baseline and midline results by stratum for prevalence of poverty
Stratum Baseline Est. (%) Midline Est. (%) Difference (%) P-Value
High 65.4 65.5 0.1 0.98
Low 58.2 62.1 3.9 0.25
Total 61.8 63.8 2.0 0.43
Figure 4-1 is an illustration of the differences in the change of the prevalence of poverty 
between baseline and midline (even if it was not significant). One might ask if the rate of 
change is significantly different between the High zone and the Low zone. The p-value of the 
DiD statistics is 0.44 showing no difference in the rate of change for the midline compared to 
the baseline.
Sahel Resilience Learning (SAREL)—RISE Midline Quantitative Survey Report
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Figure 4-1: Change in the prevalence of poverty from baseline to midline by stratum
4.2. Depth of Poverty (Indicator 1)
The depth of poverty was calculated using $1.90 as the poverty line. Also called the poverty 
gap, it is a measure of the intensity of poverty. This indicator is the average gap between the 
population’s wealth and the poverty line. Hence, it gives an idea how far below the poverty 
line the population is. For instance, if two populations are compared, they may have the same 
proportion of people below the poverty line (same prevalence of poverty), but one population 
may show much lower average wealth compared to the other population. In such situation, 
the former population will have a greater depth of poverty.
The results suggest that, while there is change in the right direction, the RISE program has 
not, to this point, affected the depth of poverty in a statistically significant manner. The 
outcomes for the Low and High exposure areas at midline are very similar. The depth of 
poverty decreased slightly in the High exposure area while increasing somewhat in the Low 
exposure area, though the difference-in-difference of approximately 5 percentage points does 
not reach conventional levels of statistical significance (p=0.14).
Midline Findings
Table 4-2 shows very similar depth of poverty in the two strata. On average, the population’s 
wealth is about 26% below the poverty line. In Burkina Faso, it is 21.8% (or about $1.50 per 
day) and In Niger it is 31.7% (or about $1.30 per day). Hence, there was no significant 
difference between the two strata in the depth of poverty.
Table 4-2: Depth of poverty by stratum
Stratum Estimate StdErr LCI (95%) UCI (95%) DEFF
High 25.9 2.56 20.9 30.9 70.7
Low 26.2 2.18 22.0 30.5 76.6
Total 26.1 1.69 22.8 29.4 77.6
80
70
60
50
Baseline
High, 65.4
Total, 61.8
Low, 58.2
Midline
High, 65.5
Total, 63.8
Low, 62.1
Percentage
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Key Socio-Demographic Disaggregation
The RISE zone of Niger shows much greater depth of poverty at 31.7% compared to 21.8% 
in the RISE zone of Burkina Faso. This difference of nearly 10% was highly significant with a p￾value of 0.002. Combined with the previous results of the prevalence of poverty, the RISE 
zone of Niger is not only the area with the highest prevalence of poverty, but it also exhibits 
greater depth of poverty. The Niger poverty line adjusted for the World Bank’s PPP was 
slightly higher, by 8.5 FCFA, than the equivalent poverty line in Burkina Faso. This higher 
prevalence and depth of poverty in Niger may be related to: 1) the lower availability of critical 
natural resources (i.e. rainfall, soil-fertility, water access) essential for traditional livelihoods 
in Niger, 2) Lower measures of human capital (i.e. lower educational and health outcomes) in 
Niger, and 3) stronger and more frequent climate shocks (i.e. droughts, higher rainfall 
variability) in Niger.
Figure 4-2: Depth of poverty by RISE zone of each country
Figures 4-3 to 4-6 show the depth of poverty disaggregated along several socio-demographic 
dimensions. There is not much difference between the households headed by a male versus 
those headed by a female (Figure 4-3). 
Figure 4-4 shows that polygamous households have the greatest depth of poverty with 
30.8%. The category “Other” has the lowest depth, but given its very small sample size (only 
57 households), the estimates are not very reliable. The monogamous households have a 
depth of poverty of 22.6%.
Figure 4-5 reveals that when the head of household is not capable of reading or writing in 
any languages, national or foreign, then the household has higher chance of living in deeper 
poverty. The depth of poverty among households with a non-literate head of household is 
significantly higher with 27.6% – more than 7% greater than the literate category.
The Mossi ethnic group has the lowest depth of poverty with 18.4%; the Mossi ethnic group 
is also the one with the lowest prevalence of poverty. The highest depth of poverty is 
observed with the Songhai ethnic group with 35.1%. The following charts demonstrate the 
depth of poverty by several key socio-demographic dimensions.
Sahel Resilience Learning (SAREL)—RISE Midline Quantitative Survey Report
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Figure 4-3: Depth of Poverty: Sex of Head of Household
Figure 4-4: Depth of Poverty: Marital Status of Head of Household
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Figure 4-5: Depth of Poverty: Literacy Status of Head of Household
Figure 4-6: Depth of Poverty: Ethnicity of Head of Household
Table 4-3 shows no significant change between baseline and midline results in the RISE 
program zone. Similarly, there is no significant change within the strata. The results are 
trending in the desired direction, but acceleration and prioritization of the appropriate 
interventions to reduce poverty are needed in the High zone in order to see significant 
reduction of the depth of poverty by the endline impact evaluation.
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Table 4-3: T-test comparison between baseline and midline results by stratum for poverty depth
Stratum Baseline Est. (%) Midline Est. (%) Difference (%) P-Value
High 27.8 25.9 -1.9 0.48
Low 23.0 26.2 3.2 0.15
Total 25.4 26.1 0.6 0.72
Figure 4-7 below is an illustration of the differences in the change of the depth of poverty 
between baseline and midline (even if it was not significant). Given that the depth of poverty 
is decreasing in the High stratum while increasing at the same time in the Low stratum (even 
if these changes are not significant), we may wonder if the High stratum is improving in depth 
of poverty due to the RISE initiatives. Unfortunately, the DiD shows a p-value of 0.14 which 
does not support the hypothesis of the High stratum doing better than the Low stratum in 
statistically significant terms. Nevertheless, the p-value is close to 10%. A more efficient 
sampling design (e.g. larger sample size, better allocation of the household sample across 
villages (i.e. not the same number of households per village)) would likely shed more light on 
whether a significant difference may exist or not.
Figure 4-7: Change in the depth of poverty from baseline to midline by stratum
4.3. Average Value of Household Assets (Indicator 3.a)
The average value of household assets is the average value of all the consumptive, productive 
and livestock assets held by a household. The value of the assets is determined by purchasing 
price or by market value evaluation from the owner when the asset was obtained outside a 
monetary transaction. The values in this section are presented in Franc CFA (FCFA).
To summarize the findings, the average value of household assets was lower to begin with in 
the High exposure villages compared to the Low exposure villages. Substantively, the results 
from baseline to midline trend in the desired direction, but the difference-in-differences is not 
statistically significant.
30
25
20
Percentage
Baseline
High, 27.8
Total, 25.4
Low, 23
Midline
Total, 26.1
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Midline Findings
As shown in Table 4-4, households in the Low stratum reported higher household assets 
value with an average of 915,619 FCFA compared to 758,749 FCFA. However, given the large 
confidence intervals, the difference is not statistically significant.
Table 4-4: Average value of household assets by stratum
Stratum Estimate StdErr LCI (95%) UCI (95%) DEFF
High 758,749 155,270 454,425 1,063,073 6.5
Low 915,619 119,751 680,911 1,150,327 4.3
Total 836,192 98,781 642,584 1,029,800 5.6
Key Socio-Demographic Disaggregation
The average household assets value is much higher in the RISE zone of Burkina Faso. With an 
average value of about 1.27 million FCFA, the average value of household assets in the RISE 
zone of Burkina Faso is about 4 times higher than in the RISE zone of Niger.
Figure 4-8: Average value of household assets by RISE zone of each country
Comparison of Baseline and Midline
Table 4-5 shows that none of the changes by stratum is statistically significant. 
Table 4-5: T-test comparison between baseline and midline results by stratum
Stratum Baseline Est. (FCFA) Midline Est. (FCFA) Difference (FCFA) P-Value
High 650,066 758,749 108,684 0.27
Low 928,394 915,619 -12,775 0.81
Total 786,207 836,192 49,984 0.37
The DiD p-value associated with the figure below is 0.28, which confirms the observation 
from the previous table. That is, the positive trend in the High stratum and the negative or 
stagnating trend in the Low stratum, are not large enough to attribute any statistically 
significant effect to the interventions in the High stratum, despite movement in the desired 
Sahel Resilience Learning (SAREL)—RISE Midline Quantitative Survey Report
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direction. The interventions have thus, to this point, not produced a statistically significant 
change.
Figure 4-9: Change in the average value of household assets from baseline to midline by stratum
4.4. Asset Ownership (Indicator 3.b)
Asset ownership is the average number of assets owned by the household, related to 
consumption, production, and livestock. Counting assets can be problematic in the sense that 
one household may have fewer, but more valuable assets compared to another household. 
The indicator’s usefulness comes in allowing us to track increases in the economic well-being 
of program beneficiaries through their acquisition of new assets. Unless families shift the type 
of assets they own, for example from more assets of little value to fewer assets of larger value, 
measuring the acquisition of new assets can reveal important information about the wellbeing 
of households. Some households, of course, may adopt exactly that approach as a form of 
building resilience. Thus, this indicator may be more informative when considered along with 
the average value of household assets (both of which USAID proposed). 
At the midline point, though the results are trending in the desired direction, we find no 
statistically significant change in asset ownership in the High exposure areas compared to the 
Low exposure areas.
Comparison of Baseline and Midline
Table 4-6 shows that none of the changes by stratum is statistically significant.
Table 4-6: T-test comparison between baseline and midline results by stratum for number of household assets
Stratum Baseline Est. Midline Est. Difference P-Value
High 44.5 46.5 1.9 0.51
Low 54.9 51.6 -3.3 0.49
Total 49.7 49.0 -0.7 0.81
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The DiD p-value associated with the figure below is 0.28 which confirms the observation from 
the previous table. That is, the positive trend in the High stratum and the negative or 
stagnating trend in the Low stratum are not large enough to attribute any statistically 
significant effect to the interventions in the High stratum.
Figure 4-10: Change in the number of household assets from baseline to midline by stratum
4.5. Non-Agricultural Sources of Household Income (Indicator 6)
In the RISE zone, 77.3% of the heads of households are estimated to work primarily in 
agriculture. Therefore, agriculture is typically one of the main sources of revenue for those 
households. In that context, household income from non-agricultural sources may constitute 
a protection against economic shocks due to poor crop seasons, climate-related events, and 
swings in crop prices. The indicator in this section provides the share of households’ income 
derived from non-agriculture sources. Three categories of sources are defined. In households 
with 10 percent or more of their overall income earned from non-agricultural sources, those 
sources are considered to constitute an important source of revenue for the household. If 
the household reports relying on any non- agricultural sources of income during times of 
stress, those non-agricultural sources of income are considered a critical source of revenue 
for the household. And lastly, if a household’s non-agricultural income is derived from 
activities that take place only during the dry season or only during the wet season, the non￾agricultural activities are considered a temporary source of revenue for the household.
Regarding revenue from non-agricultural sources, we find statistically significant 
improvements both from baseline to midline in the High exposure villages, and also in the 
difference-in-differences comparing the High exposure areas to the Low exposure areas.
Midline Findings
The majority of the households, that is 73.3%, earn income from non-agricultural sources. 
The difference of 8.1% between the High and Low strata is not significant.
60
50
40
Value in FC
FA
Baseline
Low, 55
Total, 50
High, 45
Midline
Low, 52
Total, 49
High, 46
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Table 4-7: Proportion of households with income from non-agricultural sources by type and stratum
Stratum Estimate (%) StdErr (%) LCI (95%) UCI (95%) DEFF
Any type
High 77.3 4.28 68.9 85.7 9.7
Low 69.1 3.00 63.3 75.0 6.6
Total 73.3 2.69 68.0 78.5 9.2
Important
High 76.7 4.38 68.1 85.3 9.9
Low 68.0 3.02 62.1 73.9 6.6
Total 72.4 2.74 67.0 77.8 9.4
Critical
High 45.6 5.34 35.2 56.1 10.6
Low 29.7 2.74 24.3 35.0 5.7
Total 37.8 3.12 31.7 43.9 10.4
Temporary
High 29.1 3.80 21.7 36.6 6.5
Low 34.9 2.87 29.3 40.5 5.7
Total 32.0 2.41 27.2 36.7 6.7
The income from non-agricultural sources is important for almost all the households with 
non- agricultural sources in the sense that it constitutes more than 10% of their overall 
income. In the RISE zone, 37.8% of the households earn critical income from non-agricultural 
sources. That proportion is much higher in the High stratum with 45.6% of the households 
while it is only 29.7% in the Low stratum. This difference of 16.0% is statistically significant 
with a p-value smaller than 0.001. Temporary income from non-agricultural sources is 
reported by 32.0% of the households and there is not significant difference between the High 
and Low strata.
Key Socio-Demographic Disaggregation
The proportion of households with income from non-agricultural sources is higher in the RISE 
zone of Niger (83.3%) compared to the RISE zone of Burkina Faso (65.2%). The difference of 
18.1% is significant with a p-value smaller than 0.001.
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Figure 4-11: Proportion of households with income from non-agricultural sources by RISE zone of each country
Figures 4-12 to 4-15 show the proportion of households with income from non-agricultural 
sources by some key demographics. There is no significant difference when the indicator is 
disaggregated by sex or marital status or literacy of the head of household. However, the 
ethnicity disaggregation shows significant differences. The Gourmantché group has the lowest 
proportion of households with income from non-agricultural sources, while the Hausa group 
has the highest proportion with 88.4%.
Figure 4-12: Proportion with income from non-agricultural Sources: Sex of Head of Household
80
60
40
20
0
Burkina Faso Niger Total
Burkina Faso 
Niger
Total Percentage
83.3
73.3
65.2
77.1
72.8 73.3
0
10
20
30
40
50
60
70
80
Percentage
Sex of Head of Household
Female Male Total
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Figure 4-13: Proportion with income from non-agricultural Sources: Marital Status of Head of Household
Figure 4-14: Proportion with income from non-agricultural Sources: Literacy Status of Head of Household
75.3
68
75.8
78.4
73.3
62
64
66
68
70
72
74
76
78
80
Percentage
Marital Status of Head of Household
Monogamous Polygamous Widow Other Total
78.1
72
73.3
68
69
70
71
72
73
74
75
76
77
78
79
Percentage
Literacy Status of Head of Household
Yes No Total
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Figure 4-15: Proportion with income from non-agricultural Sources: Ethnicity of Head of Household
Comparison of Baseline and Midline
Table 4-8 (below) shows that none of the differences at the RISE zone and by stratum is 
statistically significant. However, the increase observed in the High zone is marginally 
significant, and a larger sample size might have shown a significant increase.
Table 4-8: T-test comparison between baseline and midline results by stratum for household income sources
Stratum Baseline Est. (%) Midline Est. (%) Difference (%) P-Value
High 72.6 77.3 4.6 0.08
Low 71.8 69.1 -2.7 0.23
Total 72.2 73.3 1.0 0.55
The DiD p-value associated with the figure below is 0.03, hence the increase in the High 
stratum is significantly different from the decrease in the Low stratum. The DiD suggests that 
the trend of the proportion of households with income from non-agricultural sources is 
different between the two strata. It is possible that the RISE programs are helping to diversify 
sources of income.
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Figure 4-16: Change in the percentage of households obtaining income from non-agricultural sources from baseline to 
midline by stratum
4.6. Propensity score matching for Livelihoods indicator
Only four indicators i.e. depth of poverty, average value of household assets, asset ownership, 
and household with income from non-agricultural sources, were retained for the PSM analysis 
because their p-values were under 0.30. Each of the households in the High stratum with non￾missing values (i.e. 923 for baseline and 924 for midline) for the predictors (i.e. age, sex, marital 
status, literacy, and ethnicity of the head of the household) was matched to the nearest 
household in the Low stratum. This procedure was conducted for both the baseline and 
midline samples. The DiD test was applied to the resulting combined sample. 
Table 4-9 shows that the p-value of the test of difference increased for depth of poverty, 
average value of household assets and asset ownership while it diminished for income from 
non-agricultural sources. Based on the threshold of 0.05, the PSM analysis suggests that the 
RISE program was instrumental in increasing the proportion of households with non￾agricultural sources of income. 
Table 4-9: Propensity score matching for the depth of poverty, average value of household assets, asset ownership and 
income from non-agricultural sources
90
80
70
60
Percentage
Baseline Midline
High, 77.3
Total, 72.2 Total, 73.3
Low, 69.1
Indicator DiD p-value DiD p-value after PSM
Poverty depth 0.14 0.40
Average value of household assets 0.28 0.66
Asset ownership 0.28 0.60
Income from non-agricultural sources 0.03 0.01
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5. Governance
The second RISE component aims to achieve Strengthened Institutions and Governance. In 
order to promote stronger institutions and governance in a manner that helps communities 
to build resilience, RISE has outlined a number of intermediate results:
● Improved natural resource management
● Disaster risk management
● Strengthened conflict management systems
● Strengthened government and regional capacity and coordination
The rationale for these intermediate results is that villages will first be able to make best use 
of the natural resources at their disposal, which should help to promote sustainability and 
offset some of the risks from climate and other type of catastrophic shocks. Next, as villages 
develop improved strategies for managing risk, households and key village stakeholders should 
have plans in place so that at least some aspects of crisis and disaster can be anticipated and 
their impact mitigated through timely early response actions. Since social conflict can 
compound the effects of climate and other forms of shock and stress, villages that are able to 
minimize and manage such tensions can maintain greater focus on averting natural crises. 
Finally, all of these aspects of village management—from natural resources to disaster to 
conflict—involve higher levels of government in one form or another. To avoid predation, 
miscommunication, or competing objectives, coordination and capacity building are critical at 
different levels of government.
Governance and natural resource management activities involve a number of different levels 
of government. At the national level, annual meetings occur with government agencies, such 
as 3N in Niger and the Permanent Secretariat for the National Food Security Council 
(PS/NFSC) in Burkina Faso, to ensure alignment with their respective policies and priorities. 
Ministries of Agriculture, Health, and Water are also involved in agreements. At the regional 
and departmental or provincial levels, RISE partners coordinate with administrative authorities 
and technical services in both countries. Prefects must approve commune-level land use plans, 
and district meetings are regularly attended by RISE staff and government health agents who 
support many project activities. Several RISE projects coordinate with departmental services 
to ensure that disaster planning at the commune level is consistent with the national disaster 
planning system. Finally, the commune level is the entry point for most RISE activities. 
Commune authorities orient IP staff to priority zones for intervention and help resolve 
questions about conflicts, resource use, NGOs or projects already working in the area, and 
security issues. Local technical services participate in RISE training sessions and sometimes 
supervise cascade training.
Specific activities related to improved governance include the following: developing commune￾level and village-level natural resource plans to avoid conflict and bring more control to local 
groups; forming committees that can respond to disasters such as flood and drought; 
establishing conflict resolution committees; enabling women to gain access and secure rights 
Sahel Resilience Learning (SAREL)—RISE Midline Quantitative Survey Report
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to land; increasing understanding of the causes and impacts of climate change and actions that 
can be taken to adapt to it. Some other activities jointly address both the governance and 
livelihood components. For example, conservation farming combined with natural 
regeneration of wide swaths of land farmed by groups or individuals targets both revenue 
generation and resource management. Sensitization of farmers on agricultural risks due to 
climate change aims to improve their adaptive capacity while also fortifying climate-related 
governance and management.
Specific indicators drawn from the baseline and midline surveys to track improvements in 
governance include the following, the details of which are described in the subsequent sub￾sections:
● Indicator 7: Percentage of targeted communities with evidence of improved 
governance
● Indicator 8: Percentage of targeted communities with evidence of improved capacity 
to manage climate shocks and risks
● Indicator 9: Percentage of individuals who engage with local power structures to effect 
change
Two key challenges arise in the effort to improve governance and natural resource 
management in targeted RISE villages. First, collaboration imposes demands (or at least 
expectations) on government staff and agencies. Second, effective community management 
and governance requires that stakeholders and government actors involve other community 
members, delegate responsibility to them, and respond to their feedback.
Overview of Results: In the Governance category, two findings are worth underscoring up 
front. First, villages with evidence of good governance improved significantly in the High 
exposure areas from baseline to midline (47% to 81%, p=.02). The difference-in-differences 
is positive and approaches conventional levels of statistical significance (p=.08). Second, the 
share of villages with adequate capacity to manage climate shocks improved significantly from 
baseline to midline, but a comparable change occurred in both the High and Low exposure 
areas, so the improvement cannot be attributed to RISE interventions. There was no 
significant change in the share of individuals engaging with local power structures.
5.1. Communities with Evidence of Good Governance (Indicator 7)
Good governance at the village level includes the following components: natural resource 
management plans, conflict management systems, successful dispute mediation, and 
development plans (typically as part of a commune-level development plan). Villages that 
develop good governance in these domains are better prepared to navigate sudden changes 
that result from climate shocks.
In this section, a village is considered to have evidence of good governance when it has two 
of the following four elements: 1) natural resource management plans, 2) conflict management 
systems, 3) successful dispute mediation (meaning that at least half of the village-level disputes 
were resolved), and 4) a community development plans. Putting in place plans and mechanisms 
Sahel Resilience Learning (SAREL)—RISE Midline Quantitative Survey Report
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is an important step, but successful application and use is more challenging. It should be noted 
that the indicator includes a measure of application of only one of the three plans/mechanisms 
- the one concerning conflict management. 
Midline Findings
The total number of villages in the RISE zone is 4,360 as determined during the establishment 
of the sampling frame in 2014. The total number of villages in the High stratum is 1,702 while 
the corresponding number is 2,658 villages in the Low stratum. Therefore, 61.0% of the 
villages of the RISE zone are situated in the Low stratum.
The graph on the left side of Figure 5-1 shows that an estimated 1,374 villages in the High 
stratum showed evidence of good governance while the corresponding estimate is 1,637 in 
the Low stratum.
The graph on the right side of Figure 5-1 shows the distribution of villages according to their 
evidence of good governance status. The exterior ring represents the Low stratum while the 
interior ring shows data from the High stratum. The graph shows that 80.7% of the villages in 
the High stratum showed evidence of good governance compared to only 61.6% in the Low 
stratum. The difference of 19.1% is marginally significant with a p-value of 0.11. It is made 
much stronger by considering the status of High and Low exposure communes at the baseline 
stage, which we do below.
Figure 5-1: Proportion of villages with evidence of good governance by stratum
The total number of villages in the RISE zone of Burkina Faso is 1,232 while the corresponding 
number in the RISE zone Niger is 3,128 villages. Therefore, close to 72% of the villages of the 
RISE zone are situated in Niger.
The graph on the left side of Figure 5-2 shows that an estimated 871 villages in the RISE 
zone of Burkina Faso showed evidence of good governance while the corresponding estimate 
is more than twice as large at 2,140 in the RISE zone of Niger.
The graph on the right side of Figure 5-2 shows the distribution of villages according to their 
evidence of good governance status. The exterior ring represents the RISE zone of Niger 
while the interior ring shows data from the RISE zone of Burkina Faso. The graph shows that 
the proportion of villages with evidence of good governance is very similar in the two parts 
Sahel Resilience Learning (SAREL)—RISE Midline Quantitative Survey Report
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of the RISE zones- Burkina Faso and Niger - at 70.7% and 68.4%, respectively. The difference 
is not statistically significant with a p-value of 0.85.
Figure 5-2: Proportion of villages with evidence of good governance by RISE zones in each country
Comparison of the Baseline and Midline
Table 5-1 shows that there was essentially no change in the Low stratum between the 
baseline and midline at about 62%. At the same time, a significant increase was observed in 
the High stratum going from 46.8% during the baseline to 80.7% for the midline. The p-value 
in the High stratum was 0.02.
Table 5-1: T-test comparison between baseline and midline results by stratum for evidence of good governance
Stratum Baseline Est. (%) Midline Est. (%) Difference (%) P-Value
High 46.8 80.7 34.0 0.02
Low 61.7 61.6 -0.1 0.99
Total 55.9 69.1 13.2 0.21
The figure below shows different change patterns in the High stratum compared to the Low 
stratum between the baseline and midline. The difference in trends is statistically significant 
under the current sampling design at a DiD confidence level of 0.08. This marginally statistically 
significant result is noteworthy given the sample size of just 100 communes, and a larger 
sample size could have shown more significant effects attributable to the RISE program.
80
60
40
Baseline
Low, 61.7
Total, 55.9
High, 46.8
Midline
High, 80.7
Total, 69.1
Low, 61.6 Percentage
Sahel Resilience Learning (SAREL)—RISE Midline Quantitative Survey Report
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Figure 5-3: Proportion of villages with evidence of good governance by stratum
5.2. Communities with Adequate Capacity to Manage Climate Shocks 
(Indicator 8)
The capacity to manage climate shocks and risks helps villages to adapt to them with minimal 
disruption. Improved management capability with regard to climate shocks also refers to the 
ability of villages to take advantage of positive opportunities that may arise from climate 
change. Two criteria serve as the primary basis for the indicator: 1) level of village members’ 
application of new techniques or practices for adapting to climate change, and 2) village 
members’ own assessment of the efficacy of the adaptations.
Midline Findings
As determined during the establishment of the sampling frame in 2014, the total number of 
villages in the RISE zone is 4,360. One thousand seven hundred and two (1,702) of these 
villages are in the High stratum, while the corresponding number in the Low stratum is 2,658 
villages, representing 61.0% of the total number of RISE zone villages.
The graph on the left side of Figure 5-4 reveals that an estimated 1,240 villages in the High 
stratum showed evidence of adequate capacity to manage climate shocks while the equivalent 
estimate in the Low stratum is 1,162.
The graph on the right side of Figure 5-4 shows the distribution of villages according to their 
capacity to manage climate shocks. The exterior ring represents the Low stratum while the 
interior ring shows data from the High stratum. The graph reveals that 72.8% of the villages 
in the High stratum have adequate capacities to manage climate shocks compared to only 
43.7% in the Low stratum. The difference of 29.1% is statistically significant with a p-value of 
0.046. This should not be interpreted as a success of RISE programming since this proportional 
difference between the High and Low stratum zones has existed since baseline. The DiD p￾value of 0.90 is clearly not significant.
Figure 5-4: Proportion of villages with adequate capacity to manage climate shocks and risks by stratum
The total number of villages in the RISE zone of Burkina Faso is 1,232 while the corresponding 
number in the RISE zone of Niger is 3,128 villages. Therefore, close to 72% of the villages of 
the RISE zone are situated in Niger.
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The graph on the left side of Figure 5-5 reveals that an estimated 547 villages in the RISE 
zone of Burkina Faso showed evidence of adequate capacity to manage climate shocks and 
risks while the equivalent estimate in the RISE zone of Niger is more than three times as large 
at 1,854.
The graph on the right side of Figure 5-5 shows the distribution of villages according to their 
evidence status on adequate capacity to manage climate shocks and risks. The exterior ring 
represents the RISE zone of Niger while the interior ring shows data from the RISE zone of 
Burkina Faso. The graph shows the proportion of villages with adequate climate shock and 
risk management capability in the two parts of the RISE zones - Burkina Faso and Niger - at 
44.4% and 59.3%, respectively. The difference of 14.9% is not statistically significant with a p￾value of 0.27.
Figure 5-5: Proportion of villages with adequate capacity to manage climate shocks and risks by RISE zone in each 
country
Comparison of the Baseline and Midline
Table 5-2 shows that the increases in the High stratum and at the overall RISE zone are 
significant.
The increase in the Low stratum (0.05) is marginally significant. .
Table 5-2: T-test comparison between baseline and midline results by stratum for adequate climate shock and risk 
management capacity
Stratum Baseline Est. (%) Midline Est. (%) Difference (%) P-Value
High 41.7 72.8 31.1 0.04
Low 15.2 43.7 28.5 0.05
Total 25.6 55.1 29.5 0.01
The figure below clearly reveals similar change patterns in the High stratum compared to the 
Low stratum, between the baseline and midline, which is confirmed by the DiD test p-value 
of 0.90 which means that any change is unlikely attributable to RISE interventions.
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Figure 5-6: Proportion of villages with adequate capacity to manage climate shocks and risks by stratum from baseline to 
midline
5.3. Individual Engagement with Local Power Structures (Indicator 9)
When individuals engage with local power structures, their needs are more likely to take 
precedent over less critical government decisions. This helps to strengthen households’ 
capacity for resilience, as government becomes aware of and thus more likely to address 
those household needs. This indicator measures the proportion of household heads who 
report engaging with local power structures during the past year.
The midline findings indicate a prevalence of individual engagement with local power 
structures at 12.3% in the RISE zone. The prevalence in the Low stratum and the High stratum 
is similar at 12.0% and 12.6%, respectively.
Key Socio-Demographic Disaggregation at Midline
The RISE zone of Niger has a higher proportion of individuals who engaged with a local power 
structure at 15.6% compared to 9.6% in the RISE zone of Burkina Faso. The difference of 6.0% 
was not statistically significant, barely missing the threshold, with a p-value of 0.06.
Figure 5-7: Proportion of individuals who engage with a local power structure by RISE zone in each country
75
50
25
Percentage
Baseline
High, 41.7
Total, 25.6
Low, 15.2
Midline
High, 72.8
Total, 55.1
Low, 43.7
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Figure 5-7 shows the proportion of individuals who engaged with a local power structure 
along several socio-demographic dimensions. The households headed by a male have a much 
greater proportion of individuals who engaged with a local power structure at 13.2%, while
the households headed by a female were at 4.3%. The difference of 8.9% is highly significant 
with a p-value smaller than 0.001.
Polygamous households have the highest proportion of individuals who engaged with local 
power structures at 14.3%. The category widow has the lowest proportion at 5.7%. 
Monogamous households have a proportion close to that of the overall RISE zone at 12.1%.
Households headed by a literate person have a higher proportion of individuals who engaged 
with a local power structure with 20.6%. The difference of 10.5% with households headed by 
a non-literate person is significant; the p-value is 0.001.
The Mossi ethnic group shows the lowest proportion of individuals who engaged with a local 
power structure at 2.9%; the second lowest group is the Songhai at 5.6%. The Gourmantché 
and Hausa have the highest proportions at 22.9% and 18.9%, respectively.
Comparison of the Baseline and Midline
Table 5-3 shows that none of the changes within strata or at the level of the overall RISE 
zone were significant.
Table 5-3: T-test comparison between baseline and midline results by stratum
Stratum Baseline Est. (%) Midline Est. (%) Difference (%) P-Value
High 12.3 12.6 0.2 0.93
Low 13.5 12.0 -1.5 0.62
Total 12.9 12.3 -0.6 0.76
The figure below shows that the different trends in the High stratum and in the Low stratum.
The intensity of the increase in the High stratum is not large enough, however, to confirm a 
trend different from the one in the Low stratum. The p-value of the DiD test is 0.67.
Figure 5-8: Proportion of individuals who engage with local power structures by stratum
To summarize the findings on Governance, we relied on three key indicators: evidence of 
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good governance, capacity to manage climate shocks, and engagement with local power 
structures. Regarding evidence for good governance, the findings suggest that progress 
attributable to RISE has occurred. 80.7 percent of High exposure villages versus just over 60 
percent of Low exposure villages meet the requisite standards, whereas only 46 percent of 
High exposure villages did so at the baseline stage (again compared to approximately 60 
percent in the Low exposure areas). The difference-in-differences approaches statistical 
significance at p=.08, and it should be noted that the sample size of 100 is small. We did not 
detect a significant difference in Burkina Faso compared to Niger. Regarding capacity to 
manage climate shocks, no change can be attributed to RISE at this point: the share of villages 
meeting the standard increased by approximately 30 percentage points in the High exposure 
areas (41.7% to 72.8%), but the same magnitude of change was observed in the Low exposure 
areas. Again, we did not detect a significant difference across the two countries. Finally, in 
terms of engaging with local power structures, we observed neither a change from baseline 
to midline nor a change in High exposure villages compared to Low exposure villages. The 
tendency to engage with local authorities is higher in Niger (15%) than Burkina Faso (9%), but 
not in a manner attributable to the RISE interventions, as the differences do not break along 
High and Low exposure lines.
The evidence indicates that work with community stakeholders to establish improved 
governing norms can generate positive results. The small sample size of villages limits the 
analytical strength for attributing statistical significance, but the results for evidence of good 
governance are encouraging.
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6. Health and Nutrition
The third component of RISE aims to achieve Improved Health and Nutrition Status, and 
includes the following intermediate results:
● Increased access to potable water
● Improved health and nutrition practices, particularly for mothers and children
● Improved family planning
● Better sanitation practices
The rationale for these intermediate goals is first that clean, drinkable water is the starting 
point for good health, avoiding water-borne illness, and ensuring properly cleaned foods. 
Beyond access to potable water, households must have the information that allows them to 
develop good health and nutrition practices that they can sustain beyond the life of the RISE 
initiative. Next, sound family planning practices serves the health not just of mothers but also 
of the children they bear and raise. Finally, improved health and nutrition practices can be 
undermined by a lack of sanitation, so the RISE initiative seeks to couple sanitation 
improvements with health and nutrition learning.
The RISE initiative includes numerous activities aimed at improving health and nutrition in 
targeted villages and households. Family planning, health, and nutrition education activities are 
provided for both men and women. Training is provided on handwashing and sanitation. IPs 
promote awareness of the importance dietary diversity and enrichment. Through “safe 
spaces” activities, IPs raise the awareness of adolescent girls concerning health and nutritional 
issues. The REGIS-ER project also includes health-related “early response” actions and other 
crisis modifier activities that can be undertaken to mitigate impacts of shocks and the onset 
of humanitarian emergencies, as needed. Other activities link the health and livelihoods 
components: cultivation of moringa and fruit trees, for example, in women’s “oasis gardens” 
or in family fields can improve livelihoods while also addressing nutritional concerns. Other 
specific activities include the following:
● Mother-to-Mother groups
● Women’s home gardens
● Community-led total sanitation initiatives
● Village water supply development and rehabilitation
● Husband schools to promote family planning, increased consultation of health services 
for pre- and ante-natal care and childbirth, gender equality, etc.
● Safe spaces activities for adolescents to raise awareness of problems associated with 
early marriage and childbearing
● Production and use of community videos and radio programs to promote awareness 
and behavior change on health, nutrition, and sanitation practices
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● Cooking demonstrations on use of locally-available products to enrich meals
Indicators measured using data from the baseline and midline surveys that track changes in 
health, nutrition, and sanitation include the following:
● Indicator 2: Prevalence of households with moderate or severe hunger
● Indicator 10: Global acute malnutrition (GAM)
● Indicator 11: Prevalence of stunted children under 5
● Indicator 12: Prevalence of underweight children under 5
● Indicator 13: Percentage of households using an improved drinking water source
● Indicator 14: Percentage of households with a dedicated soap-and-water handwashing 
station
● Indicator 15: Percentage of households using an improved sanitation facility
● Indicator 16: Dietary diversity score
● Indicator 17: Prevalence of children 6-23 months receiving a minimum acceptable diet 
(MAD)
● Indicator 18: Prevalence of exclusive breastfeeding of children under 6 months
The qualitative RISE midline performance assessment that SAREL conducted in February￾March 2017 indicated that several health and nutrition activities, such as husband schools for 
men and safe spaces activities for adolescent girls were particularly effective from an anecdotal 
standpoint. A challenge in evaluating the impact of the health- and nutrition-related indicators, 
like many of the other indicators, is that progress may well take more than two years to 
develop. Furthermore, residents of the Sahel—particularly women— have been exposed to 
numerous initiatives and have received extensive information from many different donor 
activities dating back to the development of the United Nations’ Millennium Development 
Goals in the 1990s. As a result, gradual improvements across the region may mask some of 
the effect of the RISE activities. Nevertheless, continued efforts remain critical, and the quasi￾experimental design of the RISE evaluation hopefully provides an opportunity to gauge the 
specific, added impact of RISE.
Overview of Results: At the midline stage, we find very little in terms of progress that can be 
attributed to the RISE interventions. Of the ten indicators associated with Health and 
Nutrition, none of the difference-in-differences are statistically significant. Global Acute 
Malnutrition actually trends in the wrong direction, as the rate remained stable in the High 
exposure areas while falling significantly in the Low exposure areas. The prevalence of stunted 
children under 5 trended in the desired direction in the High exposure areas, but the change 
did not reach conventional levels of statistical significance (p=.13), and the difference-in￾differences showed no relative improvement. No other indicators approached statistically 
significant outcomes in the desired direction.
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6.1. Prevalence of Moderate or Severe Hunger (Indicator 2)
This indicator measures the prevalence of households with hunger. Hunger is determined by 
asking household heads about the frequency of three events experienced by household 
members. Respondents are asked if in the last four weeks, there were days during which 1) 
there was no food at all in the house, 2) any member of the household went to bed hungry, 
or 3) any member of the household went all day and night without eating. Scores are ascribed 
to each answer based on the intensity of the event. The scores of the three questions are 
summed to produce the hunger score ranging from 0 to 6. More details on the calculation of 
the hunger score are provided in Appendix A.
The hunger scores are then categorized as no hunger for a score of 0 or 1, moderate for a 
score of 2 or 3, and severe for a score greater than 3. In the midline sample, only 52 
households, representing 2% of the population, were classified as suffering from severe 
hunger. Therefore, in the analysis, the moderate and severe hunger categories are combined 
to form a moderate/severe category which allows disaggregation.
Midline Findings
The midline results indicate a prevalence of moderate/severe hunger at 14.4% in the RISE 
zone. The prevalence is higher in the Low stratum at 17.6% than it is in the High stratum with 
a prevalence of 11.3%. The resulting difference of 6.3% is statistically significant with a p-value 
of 0.02. The RISE zone of Burkina Faso and the RISE zone of Niger have very similar estimated 
prevalence of moderate/severe hunger with 14.6% and 14.2%, respectively.
Comparison of Baseline and Midline
Table 6-1 does not show a significant increase in the prevalence of moderate/severe hunger
in either the High or Low strata between the baseline and the midline. 
Table 6-1: T-test comparison between the baseline and midline results by stratum for moderate/severe hunger
Stratum Baseline Est. (%) Midline Est. (%) Difference (%) P-Value
High 8.5 11.3 2.8 0.18
Low 17.5 17.6 0.1 0.97
Total 12.9 14.4 1.4 0.39
Figure 6-1 shows the higher increase in moderate or severe hunger in the High stratum 
compared to the Low stratum and to the overall RISE zone. Nevertheless, the intensity of the 
change in the High stratum is not large enough to confirm a trend different than that observed 
in the Low stratum. The p-value of the DiD test is 0.42.
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Figure 6-1: Prevalence of moderate or severe hunger from baseline to midline by stratum
6.2. Global Acute Malnutrition (GAM) Rate (Indicator 10)
This indicator measures the proportion of children under 5 years of age who are acutely 
malnourished based on a comparison of a child’s weight to his/her height. The global acute 
malnutrition (GAM) indicator is a standard measure used globally to assess children’s well￾being. Both inadequate dietary intake and disease are the immediate causes of acute 
malnutrition.
In total, the estimated number of children under 5 in the RISE zone is 853,957. The population 
of children under 5 in the High stratum is estimated at 442,662 while the same population is 
estimated at 410,095 children in the Low stratum. Therefore, it is estimated that 51.8% of the 
children under 5 live in the High stratum.
The data used to derive the GAM indicator were not complete or reliable for 22 children. 
Hence, the information of those 22 children was not incorporated in the GAM analysis of this 
section.
Key Socio-Demographic Disaggregation
The proportion of acutely malnourished children under 5 years of age is greater in the RISE 
zone of Burkina Faso at 17.5% compared to 14% in the RISE zone of Niger. This difference of 
3.5% is significant with a p-value of 0.049.
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Figure 6-2: Proportion of acutely malnourished children under 5 by RISE zone of each country
Figures 6-3 to 6-6 show the proportion of acutely malnourished children under 5 years of 
age by some key demographics, notably the sex and ethnicity of the child as well as marital 
status and literacy status of the head of the household.
The prevalence of GAM is higher among boys with 18.2% compared to 13.7% for the girls. 
The difference of 4.5% is significant with a p-value smaller than 0.001. The children from the 
Songhai ethnic group have the lowest prevalence of GAM at 8.9% while the children belonging 
to the Peul ethnic group have the highest average rate of acute malnutrition at 22.8%. The 
other ethnic groups are somewhat similar at around 15% prevalence of GAM with the 
Gourmantché being a little higher at 17.5%. In terms of the marital status of the head of 
household, the three groups (i.e. monogamous, polygamous and widow) are not too different 
with GAM prevalence rates ranging from 13.2% to 16.8%. There is no significant difference of 
the prevalence of GAM by the literacy status of the head of household.
Figure 6-3: Proportion of acutely malnourished children under 5: Sex of the child
13.7
18.2
15.9
0
2
4
6
8
10
12
14
16
18
20
Percentage
Sex of the Child
Female Male Total
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Figure 6-4: Proportion of acutely malnourished children under 5: Ethnicity of the child
Figure 6-5: Proportion of acutely malnourished children under 5: Marital status of head of household
15
16.8
13.2
32.1
15.9
0
5
10
15
20
25
30
35
Percentage
Marital Status of Head of Household
Monogamous Polygamous Widow Other Total
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Figure 6-6: Proportion of acutely malnourished children under 5: Literacy status of head of household
Comparison of Baseline and Midline
Table 6-2 shows clearly that the reduction of the prevalence of GAM in the Low stratum 
was significant. However, there was essentially no change in the High stratum. The overall 
change in the RISE zone was not significant.
Table 6-2: T-test comparison between the baseline and midline results by stratum for GAM
Stratum Baseline Est. (%) Midline Est. (%) Difference (%) P-Value
High 15.7 15.7 0.0 1.00
Low 19.1 16.0 -3.1 0.05
Total 17.4 15.9 -1.5 0.16
Figure 6-7 shows the changes in each stratum and for the RISE zone between the baseline 
and midline. The reductions were only statistically significant in the Low stratum. While the 
changes were different between the two strata, they were not large enough to confidently 
attribute a stratum effect. Indeed, the DiD test resulted in a p-value of 0.15.
17.3
15.5
15.9
14.5
15
15.5
16
16.5
17
17.5
Percentage
Literacy Status of Head of Household
Yes No Total
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Figure 6-7: Proportion of acutely malnourished children under 5 from baseline to midline by stratum
6.3. Stunting Among Children Under 5 Years of Age (Indicator11)
Stunted growth refers to low height-for-age, when a child is short for his/her age but not 
necessarily thin. The indicator measures the proportion of children under 5 years of age in 
the RISE study zone who are categorized as moderately or severely stunted.
In total, the estimated number of children under 5 in the RISE zone is 853,957. The population 
of children under 5 in the High stratum is estimated at 442,662 while the same population is 
estimated at 410,095 children in the Low stratum. Therefore, it is estimated that 51.8% of the 
children under 5 live in the High stratum.
The data used to derive the stunting indicator were not complete or reliable for 5 children. 
Hence, the information of those 5 children was not incorporated in the stunting analysis of 
this section. 
Key Socio-Demographic Disaggregation
The proportion of stunted children under 5 years of age is much higher in the RISE zone of 
Niger at 59.7%. There is a 24.1% difference in the proportion of stunted children between the 
RISE zone of Niger and the RISE zone of Burkina Faso. That difference is strongly significant 
with a p-value smaller than 0.001.
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Figure 6-8: Proportion of stunted children under 5 years of age by RISE zone of each country
Figure 6-8 shows the proportion of stunted children under 5 years of age by some key 
demographics. The key demographics considered are sex and ethnicity of the child as well as 
marital status and literacy status of the head of the household.
The prevalence of stunting is higher among boys at 52.1%, compared to girls at 41.7%. The 
difference of 10.4% is highly significant with a p-value smaller than 0.001. The children from 
the Mossi ethnic group have the lowest prevalence of stunting at 25.7% while the Hausa 
children are stunted at the highest average of 63.9%. In terms of the marital status of the head 
of household, the three groups (i.e. monogamous, polygamous and widow) have somewhat 
similar prevalence of stunting ranging from 41% to 48.3% among their children under 5 years 
of age. There is no difference in the prevalence of stunting by the literacy status of the head 
of household.
Figure 6-9: Proportion of Stunted Children under 5 Years of Age: Sex of the Child
41.7
52.1
46.8
0
10
20
30
40
50
60
Percentage
Sex of the Child
Female Male Total
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Figure 6-10: Proportion of Stunted Children under 5 Years of Age: Ethnicity of the Child
Figure 6-11: Proportion of Stunted Children under 5 Years of Age: Marital Status of Head of Household
45.4
48.3
41
74.3
46.8
0
10
20
30
40
50
60
70
80
Percentage
Marital Status of Head of Household
Monogamous Polygamous Widow Other Total
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Figure 6-12: Proportion of Stunted Children under 5 Years of Age: Literacy Status of Head of Household
Comparison of Baseline and Midline
Table 6-3 shows that although, the overall RISE zone’s decrease in stunting was marginally 
significant (p-value 0.07), none of the differences observed at the level of the RISE zone or by 
stratum are statistically significant. Nonetheless, it can be noticed that the reduction in the 
High stratum is much larger at 4.2% compared to the reduction of 1.7% in the Low stratum.
Table 6-3: T-test comparison between the baseline and midline results by stratum for stunting
Stratum Baseline Est. (%) Midline Est. (%) Difference (%) P-Value
High 50.2 46.0 -4.2 0.13
Low 49.3 47.6 -1.7 0.36
Total 49.8 46.8 -3.0 0.07
Figure 6-13 shows similar change patterns in the High and Low strata between the baseline 
and midline, however the scale was somewhat larger in the High stratum. The DiD test p￾value at 0.45 supports the conclusion of similar trends in the High and Low strata. Larger
sample sizes in particular in the High stratum could have produced different DiD test results.
45.7
47.1
46.8
45
45.5
46
46.5
47
47.5
Percentage
Literacy Status of Head of Household
Yes No Total
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Figure 6-13: Proportion of stunted children under 5 years of age from baseline to midline by stratum
6.4. Underweight among children under 5 (Indicator 12)
Underweight status indicates that a child does not weigh as much as he/she should, based on 
age. The indicator measures the proportion of children under 5 years of age in the RISE study 
zone who fall significantly below the global average of the weight standardized score.
In total, the estimated number of children under 5 in the RISE zone is 853,957. The population 
of children under 5 in the High stratum is estimated at 442,662 while the same population is 
estimated at 410,095 children in the Low stratum. Therefore, it is estimated that 51.8% of the 
children under 5 live in the High stratum.
At the midline, there is no meaningful difference in the distribution of underweight children 
in the High stratum compared to the Low stratum at about 36% of underweight children.
Key Socio-Demographic Disaggregation
The proportion of underweight children under 5 years of age is much higher in the RISE zone 
of Niger at 43.4%. There is a 13.9% difference in the proportion of underweight children 
between the RISE zone of Niger and the RISE zone of Burkina Faso. That difference is strongly 
significant with a p-value smaller than 0.001.
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Figure 6-14: Proportion of underweight children under 5 years of age by RISE zone of each country
We also report the proportion of underweight children by some key demographics. The key 
demographics considered are sex and ethnicity of the child as well as marital status and literacy 
status of the head of the household.
The prevalence of underweight children is higher among boys with 39%. The difference of 
5.9% is significant with a p-value of 0.01. The children from the Mossi ethnic group have the 
lowest prevalence of underweight at 22.2% while the Hausa children are underweight at the 
highest average of 45.5%. The Bella and Peul have very similar prevalence rates of underweight 
at 44.2% and 41.4%, respectively. In terms of the marital status of the head of household, the 
three groups (i.e. monogamous, polygamous and widow) have similar prevalence of 
underweight around 36%. There is no difference in the prevalence of underweight children 
according to the literacy status of the head of household.
Comparison of Baseline and Midline
Table 6-4 shows that the change in the proportion of underweight children under 5 is 
statistically significant in the Low stratum but not in the High stratum. The total change in the 
RISE zone (reduction of 3.1%) suggests overall improvement, with a p-value of 0.02, though 
the improvement is driven largely by the Low exposure areas where RISE activities are not 
operating.
Table 6-4: T-test comparison between the baseline and midline results by stratum for underweight
Stratum Baseline Est. (%) Midline Est. (%) Difference (%) P-Value
High 37.4 35.9 -1.5 0.49
Low 41.0 36.1 -4.8 0.01
Total 39.2 36.0 -3.1 0.02
Figure 6-15 shows the change in the Low stratum and the stagnation in the High stratum 
between the baseline and midline. The DiD test is not significant with a p-value of 0.23 
suggesting that the difference in behavior of the indicator in the High stratum compared to
the Low stratum was not large enough to confidently conclude that the Low stratum did 
better than the High stratum.
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Figure 6-15: Proportion of underweight children under 5 years of age from baseline to midline by stratum
6.5. Improved drinking water sources (Indicator 13)
This indicator measures the share of households that use an improved source of drinking 
water. Improved sources include: protected well, borehole/tube well, public fountain/tap, own 
indoor tap, shared outdoor tap, and bottled water. These sources are protected from outside 
contamination, especially fecal matter.
The graph on the left side of Figure 6-16 shows the distribution of the households according 
to presence of improved drinking water sources. The exterior ring represents the Low 
stratum while the interior ring shows data from the High stratum. The graph shows that there 
is not much difference in the proportion of households using improved drinking water sources 
in the High stratum compared to the Low stratum at 68.2% and 69.6%, respectively. The 
difference is not statistically different.
The graph on the right side of Figure 6-16 shows that the RISE zone of Burkina Faso has a 
much higher prevalence of improved drinking water sources at 84% which is almost 34% 
higher than the RISE zone of Niger. This difference is strongly significant with a p-value smaller 
than 0.001.
Figure 6-16: Proportion of Households Using improved Drinking Water Sources by Stratum and by RISE Zone of each 
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Country’s Dimensions
Comparison of Baseline and Midline
Table 6-5 shows that neither the increases within stratum nor the increase at the RISE zone 
level are statistically significant.
Table 6-5: T-test comparison between the baseline and midline results by stratum for improved drinking water sources
Stratum Baseline Est. (%) Midline Est. (%) Difference (%) P-Value
High 67.8 68.2 0.4 0.89
Low 64.9 69.6 4.7 0.10
Total 66.4 68.9 2.5 0.23
Figure 6-17 shows the changes in each stratum and for the RISE zone between the baseline 
and midline. The changes were not significant and similarly the DiD test is not significant with 
a p-value of 0.31.
Figure 6-17: Proportion of households using improved drinking water sources from baseline to midline by stratum
6.6. Soap-and-water handwashingstations (Indicator 14)
This indicator measures the share of households using a hand-washing station with soap and 
water. A hand-washing station with soap and water is a critical tool for minimizing 
contamination of foods. Avoiding subsequent illnesses from contamination constitutes an 
important step in building resilience at the household level.
The graph on the left side of Figure 6-18 shows the distribution of households according to 
presence of hand-washing stations with soap and water. The exterior ring represents the Low 
stratum while the interior ring shows data from the High stratum. The graph shows that the 
proportion of households using a hand-washing station with soap and water is much smaller 
in the Low stratum at 1.8% compared to a proportion of 7.8% in the High stratum. The 
difference of 6% is statistically significant at 0.02.
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The graph on the right side of Figure 6-18 shows that the RISE zone of Burkina Faso has a 
much lower proportion of households using a hand-washing station with soap and water at 
0.6%. Note that the proportion of 0.6% corresponds to only 11 households in the sample. In 
the RISE zone of Niger, about 10.2% of the households have a hand-washing station with soap 
and water. The difference between the two RISE zone is highly statistically significant with a 
p-value smaller than 0.001.
Figure 6-18: Proportion of Households Using Soap and Water Hand Washing Station by Stratum and by RISE Zone of 
Each Country’s Dimensions
Comparison of Baseline and Midline
Table 6-6 shows that the reduction in the High stratum was not significant while the 
reduction in the Low stratum was significant.
Table 6-6: T-test comparison between the baseline and midline results by stratum for hand washing station
Stratum Baseline Est. (%) Midline Est. (%) Difference (%) P-Value
High 9.6 7.8 -1.8 0.54
Low 4.4 1.8 -2.6 0.04
Total 7.0 4.8 -2.3 0.15
The figure below shows the changes in each stratum and for the RISE zone between the 
baseline and midline. 
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Figure 6-19: Proportion of households using soap and water hand washing station from baseline to midline by stratum
6.7. Improved sanitation systems (Indicator 15)
This indicator measures the share of households using an improved sanitation system. The 
presence of a sanitary facility for human waste dramatically reduces contamination and 
exposure to illness, thereby helping to avert unnecessary expenditures and reduced 
productivity at the household level. In these ways, improved sanitation systems strengthen 
resilience.
The graph on the left side of Figure 6-20 shows the distribution of the households according 
to presence of an improved sanitation system. The exterior ring represents the Low stratum 
while the interior ring shows data from the High stratum. The graph shows that the 
proportion of households using an improved sanitation system is much smaller in the Low 
stratum at 14.5% compared to a proportion of 24.3% in the High stratum. The difference of 
9.8% is not statistically significant (p=0.13).
The graph on the right side of Figure 6-20 shows that the RISE zone of Burkina Faso has a 
much higher proportion of households using an improved sanitation system at 26.5%. In the 
RISE zone of Niger, about 10.8% of the households have an improved sanitation system. The 
difference between the two parts of the RISE zone is statistically significant with a p-value of 
0.01.
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Figure 6-20: Proportion of households using an improved sanitation system by stratum and RISE zone of each country
Key Socio-Demographic Disaggregation
Figure 6-21 shows the proportion of households using an improved sanitation system by 
some key demographics. The difference of 7.0% observed between the households headed by 
a male and those headed by a female is not statistically significant with a p-value of 0.06.
The three main categories of marital status, i.e. monogamous, polygamous, and widow, have 
similar proportion of households using an improved sanitation system. The values are not 
significantly different and are close to the overall RISE zone proportion of 19.4%.
The average proportion of households headed by a literate person using an improved 
sanitation system is at 29.7% and is higher than the average proportion in the remaining 
households. The difference is about 13.0% and is statistically significant with a p-value smaller 
than 0.001.
The Mossi ethnic group has the highest average proportion at 36.9% followed by the 
Gourmantché at 29.1%. The Bella group has the lowest proportion at 5.4%.
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Figure 6-21: Proportion of households using an improved sanitation system: Sex of head of household
Figure 6-22: Proportion of households using an improved sanitation system: Marital status of head of household
13.2
20.2 19.4
0
5
10
15
20
25
Percentage
Sex of Head of Household
Female Male Total
18.1
21.8
19
25.9
19.4
0
5
10
15
20
25
30
Percentage
Marital Status of Head of Household
Monogamous Polygamous Widow Other Total
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Figure 6-23: Proportion of households using an improved sanitation system: Literary status of head of household
Figure 6-24: Proportion of households using an improved sanitation system: Ethnicity of head of household
Comparison of Baseline and Midline
Table 6-7 shows that neither the increase noted in the High stratum, nor the reduction 
observed in the Low stratum were not significant.
29.7
16.7
19.4
0
5
10
15
20
25
30
35
Percentage
Literary Status of Head of Household
Yes No Total
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Table 6-7: T-test comparison between the baseline and midline results by stratum for improved sanitation system
Stratum Baseline Est. (%) Midline Est. (%) Difference (%) P-Value
High 21.6 24.3 2.7 0.42
Low 16.2 14.5 -1.7 0.31
Total 18.9 19.4 0.5 0.78
The figure below shows the changes in each stratum and for the RISE zone between the 
baseline and midline. One question that could be asked is whether the difference in trend 
between the High and Low strata are different enough to attribute some of the progress in 
the High stratum to the RISE interventions. Unfortunately, the DiD test was not significant 
with a p-value of 0.79, and therefore does not support that the change is attributable to RISE 
interventions.
Figure 6-25: Proportion of households using an improved sanitation system by stratum
6.8. Household dietary diversity (Indicator 16)
Household dietary diversity is a score that indicates the extent to which members of the 
household consume food from a variety of critical food groups.
It accounts for consumption in the previous 24 hours of 12 different food categories, by any 
member of the household. The food categories include: cereals, roots and tubers, vegetables, 
fruits, meat and poultry, eggs, fish and seafood, legumes and nuts, milk, oil, sugar, and 
miscellaneous (condiments, spices. etc.). The guidelines are based on the definition for dietary 
diversity developed by the Food and Agriculture Organization of the United Nations.
NB: The household dietary diversity score ranges from 0 to 12 and is discrete. In this analysis, 
it is largely treated as a continuous variable, for instance by computing average values that 
may fall between discrete points. Also, applying statistical methods such as t-test that assume 
normal or t distributions for the variable of interest may not be fully applicable. Indeed, the 
score only takes 12 discrete values which is hardly generalizable to a normal distribution.
Midline Findings
Table 6-8 shows very similar average household dietary diversity scores for the High and 
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Low strata at 4.9 and 5.1, respectively. The difference between the two strata is not significant 
with a p-value of 0.52.
Table 6-8: Average household dietary diversity score by stratum
Stratum Estimate StdErr LCI (95%) UCI (95%) DEFF
High 4.9 0.23 4.5 5.4 10.6
Low 5.1 0.14 4.8 5.4 5.6
Total 5.0 0.14 4.7 5.3 9.1
Key Socio-Demographic Disaggregation
The RISE zone of Burkina Faso has a higher average household dietary diversity score at 5.4 
compared to 4.5 in the RISE zone of Niger. The difference was significant with a p-value 
smaller than 0.001.
Figure 6-26 shows the average household dietary diversity score along several socio￾demographic dimensions. The average score in households headed by a female was 4.5, while 
for the households headed by a male it was 5.1. The difference of 8.8% is strongly significant 
with a p-value of 0.002.
The three main categories of marital status, i.e. monogamous, polygamous, and widow, have 
similar average household dietary diversity scores of about 5.
The households headed by a person who cannot read and write have a smaller average dietary 
diversity score of 4.8 compared to 5.6 for the households headed by a literate person. The
difference of 0.8 is strongly significant with a p-value smaller than 0.001.
The Bella and the Hausa ethnic groups have the lowest average score at 4.6 and 4.7, 
respectively. The Mossi ethnic group has the higher score at 5.4 followed by the Gourmantché 
and the Songhai at 5.2. 
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Figure 6-26: Average Household Dietary Diversity Score: Sex of Head of Household
Figure 6-27: Average Household Dietary Diversity Score: Marital Status of Head of Household
4.5
5.1
5
4.2
4.3
4.4
4.5
4.6
4.7
4.8
4.9
5
5.1
5.2
Score (range 1 to 12)
Axis Title
Sex of Head of Household
Female Male Total
5.1
5
4.7
5.3
5
4.4
4.5
4.6
4.7
4.8
4.9
5
5.1
5.2
5.3
5.4
Score (range 1 to12)
Marital Status of Head of Household
Monogamous Polygamous Widow Other Total
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Figure 6-28: Average Household Dietary Diversity Score: Literacy Status of Head of Household
Figure 6-29: Average Household Dietary Diversity Score: Ethnicity of Head of Household
Comparison of Baseline and Midline
Table 6-9 shows that none of the changes within stratum and at the RISE zone were 
significant. 
Table 6-9: T-test comparison between the baseline and midline results by stratum dietary diversity
Stratum Baseline Est. Midline Est. Difference P-Value
5.6
4.8
5
4.4
4.6
4.8
5
5.2
5.4
5.6
5.8
Score (range 1 to 12)
Literacy Status of Head of Household
Yes No Total
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High 5.1 4.9 -0.2 0.26
Low 5.1 5.1 0.0 0.86
Total 5.1 5.0 -0.1 0.60
The table shows different trends between the High and Low strata. However, the DiD test 
p-value is 0.60, meaning the difference in trends is not significant.
Figure 6-30: Average household dietary diversity score from baseline to midline by stratum
6.9. Minimum acceptable diet (MAD) among children 6-23 months of age 
(Indicator 17)
The Minimum acceptable diet (MAD) is a global dietary standard for children aged 6-23 
months. It addresses two principles: the frequency of feedings and the diversity of diet. 
Frequency generally requires that children eat at least two meals per day, three for those over 
six months of age. Diversity requires at least four food groups. Breastfeeding is also taken 
into account.
In total, the estimated number of children 6-23 months of age in the RISE zone is 267,111. 
The population of children 6-23 months in the High stratum is estimated at 145,337 while the 
same population is estimated at 121,774 children in the Low stratum. Therefore, it is 
estimated that 54.4% of the children 6-23 months of age live in the High stratum. The 
difference between these two estimated numbers is not statistically significant.
Key Socio-Demographic Disaggregation
The prevalence of minimum acceptable diet (MAD) among children 6-23 months of age is 
much higher in the RISE zone of Niger at 8.7%. There is a 5.6% difference in the prevalence 
of MAD between the RISE zone of Niger and the RISE zone of Burkina Faso (see Figure 6-
31). That difference is significant, however, with a p-value of 0.04.
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Figure 6-31: Proportion of children receiving a minimum acceptable diet (MAD) by RISE zone of each country
Given the small sample size of children receiving a minimum acceptable diet, it is not 
statistically justified to disaggregate the estimates by demographic variables with a large 
number of categories such as ethnicity. The disaggregation by sex of the child and literacy 
status of the head of household did not reveal any significant differences in the prevalence of 
MAD.
Comparison of Baseline and Midline
Table 6-10 shows that the change is not significant for either stratum or for the overall RISE 
zone.
Table 6-10: T-test comparison between the baseline and midline results by stratum for MAD
Stratum Baseline Est. (%) Midline Est. (%) Difference (%) P-Value
High 7.2 6.2 -1.1 0.80
Low 5.3 5.0 -0.3 0.86
Total 6.3 5.7 -0.7 0.78
Figure 6-32 shows the change in the High stratum and the stagnation in the Low stratum 
between the baseline and midline. The DiD test is not significant with a p-value of 0.87.
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Figure 6-32: Proportion of children receiving a minimum acceptable diet (MAD) from baseline to midline by stratum
6.10. Exclusive breastfeeding of children under 6 months of age (Indicator
18)
Exclusive breastfeeding in the first months of life has proven important for the long-term 
health of children. This indicator measures the proportion of children under 6 months of age 
who are exclusively breastfed. Note that in the midline sample, there were only 307 
respondent children under 6 months; among them 116 were exclusively breastfed. Given the 
small sample sizes, disaggregation must be considered carefully.
In total, the estimated number of children under 6 months of age living in the RISE zone is 
73,938. The population of children under 6 months in the High stratum is estimated at 43,071 
while the same population is estimated at 33,867 children in the Low stratum. Therefore, it 
is estimated that 56.0% of the children under 6 months of age live in the High stratum.
The data used to derive the exclusive breastfeeding indicator were not complete or reliable 
for one child. Hence, the information of that child was not incorporated in the exclusive 
breastfeeding analysis of this section.
The graph on the left side of Figure 6-33 shows the estimated number of children receiving 
exclusive breastfeeding by stratum. In the High stratum the estimated number of children 
receiving exclusive breastfeeding is 19,803 while the corresponding number in the Low 
stratum is 10,724.
The graph on the right side of Figure 6-33 shows the distribution of children under 6 months 
of age according to their exclusive breastfeeding status. The exterior ring represents the Low 
stratum while the interior ring shows data from the High stratum. The graph shows that there 
is a difference of 14.4% in the prevalence of exclusive breastfeeding between the two strata 
(i.e. 31.7% in the Low stratum versus 46.1% in the High stratum). That difference was 
marginally significant with a p-value of 0.056. A bigger sample size would probably show a 
significant difference.
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Figure 6-33: Exclusive breastfeeding: count and proportion by stratum
Key Socio-Demographic Disaggregation
As shown in Figure 6-34, the prevalence of exclusive breastfeeding among children under 6 
months of age is lower in the RISE zone of Niger at 34.0% compared to 46.2% in the RISE 
zone of Burkina Faso. The difference of 12.2% is not statistically significant, however, given 
the low precision associated with the small sample sizes (i.e. 161 children under 6 months in 
the RISE zone of Burkina Faso sample and 143 in the RISE zone of Niger sample).
The small sample size of children under 6 months of age is inadequate to allow disaggregation 
the estimates by demographic variables with a large number of categories such as ethnicity. 
The disaggregation by sex of the child and literacy status of the head of household did not 
show any significant differences in the prevalence of exclusive breastfeeding.
Figure 6-34: Proportion of children receiving exclusive breastfeeding by RISE zone of each country
Comparison of Baseline and Midline
Table 6-11 shows that the changes are not significant for either of the strata, nor for the 
overall RISE zone.
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Table 6-11: T-test comparison between the baseline and midline results by stratum for exclusive breastfeeding
Stratum Baseline Est. (%) Midline Est. (%) Difference (%) P-Value
High 36.7 46.1 9.5 0.16
Low 31.7 31.7 -0.1 0.99
Total 34.5 39.8 5.2 0.26
Figure 6-35 shows the change in the High stratum and the stagnation in the Low stratum 
between the baseline and midline. The DiD test shows that the results trend in the desired 
direction, but that the change is not statistically significant, with a p-value of 0.29.
Figure 6-35: Proportion of children receiving exclusive breastfeeding from baseline to midline by stratum
6.11. Propensity score matching for health and nutrition indicators
Only three indicators i.e. GAM, underweight and exclusive breastfeeding were retained for 
the PSM analysis because their p-values were under 0.30. Each of the children in the High 
stratum with non-missing values (i.e. 1,294 for baseline and 1,284 for midline) for the 
predictors (i.e. sex of the child, marital status, literacy, and ethnicity of the head of the 
household) was matched to the nearest children in the Low stratum. This procedure was 
conducted for both the baseline and midline samples. The DiD test was applied to the resulting 
combined sample. 
Table 6-12 shows that the p-value of the test of difference increased for GAM and stunting 
while stable for exclusive breastfeeding. Based on the threshold of 0.05, none of these tests 
were significant from the beginning. Hence, the tests shown below are provided for 
information only. 
Table 6-12: Propensity score matching for the GAM, prevalence of stunting and prevalence of breastfeeding.
Indicator DiD p-value DiD p-value after PSM
GAM 0.15 0.40
Stunting 0.23 0.41
Exclusive breastfeeding 0.29 0.29
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7. Cross-Cutting Components
In addition to the goals related to Livelihoods, Governance, and Health and Nutrition, RISE’s 
resilience enhancement efforts call for attention to a number of cross-cutting issues. These 
issues arise across different sectors of development and humanitarian assistance. Addressing 
them helps to reinforce collaborative learning and shared responsibility for resilience building. 
One of the key cross-cutting issues is Gender. Existing gender disparities in access to and 
control of assets (physical, financial, human, social and natural), decision making, and time use 
reduce the ability of individuals, households, villages and systems in targeted agro-pastoralist 
and marginal agriculture livelihood zones to mitigate, adapt to and recover from shocks and 
stresses. Targeted efforts that engage both men and women to reduce these disparities and 
shift socio-political and socio-cultural norms that disempower girls and women are essential 
not only for gender equity, but also for the achievement of the program’s resilience aims.
Thus, the specific indicators used to track improvements in cross-cutting issues through the 
baseline and midline surveys focus on gender. The three indicators are:
● Indicator 5: Women’s empowerment in agriculture index (subset: Production and 
Resources)
● Indicator 19: Proportion of the target population reporting increased agreement that 
males and females should have equal access to social, economic, and political 
opportunities
● Indicator 20: Percentage of women reporting effective participation in household 
decision making around production and income generation
The Women’s empowerment in agriculture index (WEAI) is a standard measure developed 
by USAID FTF, IFPRI, and the Oxford Poverty and Human Development Initiative using five 
domains of empowerment (5DE); it is used by numerous international organizations to track 
women’s empowerment. In this case, RISE uses a modified WEAI, at USAID’s request, which 
focuses on a subset of the broader measure: two domains, Production and Resources, are 
used instead of the standard five, and the shares that each of those domains contributes to 
the WEAI score are adjusted accordingly.
● One challenge that arises in tracking improvements related to gender roles and 
equality is the potential for social desirability bias. A normative preference among 
donors for gender equality is increasingly well understood in the region (see the RISE 
Midterm Performance Assessment Phase II Qualitative Report), so respondents (both
men and women) may become more adept at expressing preferences for gender 
equality that do not match their true beliefs or behaviors. To address this challenge, 
the survey includes a number of different survey questions that might tap into the issue 
in diverse ways.
Overview of Results: In the Cross-cutting Gender Equality category, we did not find any 
evidence that the RISE activities have had a positive effect to this point. The Women’s 
Empowerment in Agriculture Index improved more in the Low exposure areas than in the 
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High exposure areas, and the proportion of respondents supporting equal access for females 
and male declined significantly in both the High and Low exposure areas.
7.1. Women’s empowerment in agriculture index (Indicator 5)
This indicator is an adaptation of a common tool that measures the opportunities for women 
to gain control over their own lives through empowerment in the agricultural sector. The 
modified WEAI measure used for this evaluation counts women as empowered if they achieve 
a threshold of autonomy and decision-making power in Production and Resources, and it also 
accounts for the activities that other women achieve even if they do not reach the threshold 
of empowerment.
The weights assigned to the Production and Resources domains using the standard WEAI are 
each 20 percent of the total. Because they are weighted equally, we maintain those relative 
weights, thus assigning new weights of 50 percent to each of these domains (since they are 
the only two dimensions included in this modified version of WEAI). The sub-components 
within each domain are weighted equally, which means that Decision Making and Autonomy—
the two sub-components of Production—are each worth 25 percent, and the three Resources 
sub-dimensions (Ownership, Purchases, and Credit Access) are each worth 16.7 percent.
The standard WEAI protocols indicate that a woman is empowered if she reaches 
achievement on 80 percent of the weighted indicators. Because this modified version has 
fewer indicators and thus constitutes a blunter measure, we use a threshold of 75 percent. 
Thus, a surveyed woman must reach achievement on some of the five sub-components, such 
that the weights assigned to those sub-components in which she is successful account for 75 
percent of the weighting. The modified WEAI score, like the standard WEAI, captures the 
share of women who reach this empowerment threshold, plus the average level of 
achievement on the five sub-components for the women who do not reach the threshold. 
Finally, the modified WEAI used here does not include a contribution from the Global Parity 
Index, since the relevant questions were not posed to both men and women; 100 percent of 
the modified WEAI comes from the empowerment dimensions. See the annex for more 
information.
Note that in comparing the baseline to midline results, we calculated the WEAI scores at the 
village level, so the analyses that follow use village-level aggregations of the index. We can also 
report that the point estimates for the WEAI score aggregated from individual-level 
empowerment to the entire High and Low exposure areas at the midline are 66.4 and 62.7, 
respectively. At the endline stage, we will be in position to analyze the index in High vs. Low 
strata or by any alternative disaggregation.
Midline Findings
Table 7-1 shows that the average village level WEAI score is 70.6 for the overall RISE zone. 
The WEAI score is 71.3 in the Low stratum compared to 69.7 in the High stratum. The 
difference of 1.6 is not statistically significant with a p-value of 0.72. The average village level 
WEAI is higher in the RISE zone of Niger at 78.7 compared to 54.9 in the RISE zone of Burkina 
Faso. The difference of 23.8 is highly significant with a p-value less than 0.001.
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Table 7-1: Average village level WEAI score by stratum and RISE zone of each country
Comparison of the Baseline and Midline
Table 7-2 shows that the change in the High stratum was not statistically significant. 
However, the changes in the Low strata and at the overall RISE zone were significant.
Table 7-2: T-test comparison between baseline and midline results by stratum for WEAI
Stratum Baseline Est. (%) Midline Est. (%) Difference (%) P-Value
High 69.4 69.7 0.3 0.91
Low 65.1 71.3 6.2 0.02
Total 66.9 70.6 3.8 0.05
Figure 7-1 shows a larger increase in the Low stratum. However, the increase in the Low 
stratum was not sufficiently higher compared to the High stratum to support a statistically 
significant change in trend. The p-value of the DiD test was 0.12.
Figure 7-1: Average village level WEAI score from baseline to midline by stratum
7.2. Support for equal access for males and females (Indicator 19)
This indicator measures the degree to which households agree that males and females should 
have equal access to social, political, and economic opportunities.
NB: The question m1410 used to derive this indicator was collected from the household 
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questionnaire. Because, the respondent was not randomly selected from the list of people in 
the household, this indicator cannot be treated as person level variable. Instead, the indicator 
19 will be treated as a household level indicator and interpreted as the best proxy available 
of what the household thinks about equal access for males and females to social, political, and 
economic opportunities.
Midline Findings
We analyzed the distribution of households according to their acceptance of equal access of 
males and females to social, political, and economic opportunities at the midline stage. The
results indicate that 46.5% of the households in the High stratum believed in equal access for 
males and females compared to 43.1% in the Low stratum. The difference of 3.4% is not 
statistically significant with a p-value of 0.63. In terms of country-level differences, 54.8% of 
the households in the RISE zone of Burkina Faso believed in equal access for males and females 
compared to 32.5% in the RISE zone of Niger. The difference of 22.3% is statistically significant 
with a p-value less than 0.001. 
Table 7-3 shows that the households headed by a female were more likely to agree that 
males and females should have equal access to social, political, and economic opportunities at 
52.1% compared to 44.0% for the households headed by a male. However, this difference of 
8.1% was not statistically significant.
Monogamous households agree at the lowest proportion (43.1%) that males and females 
should have equal access, followed by polygamous households at 46.3%. The difference is not 
statistically significant.
Table 7-3: Proportion of households that agree that males and females should have equal access to social, political, and 
economic opportunities by household type
Domain Estimate (%) StdErr LCI (95%) UCI (95%)
 RISE zone
Total 44.8 3.63 37.7 51.9
Sex of the head of household
Male 44.0 3.79 36.6 51.4
Female 52.1 5.27 41.8 62.5
Marital status of the head of the household
Monogamous 43.1 3.88 35.5 50.7
Polygamous 46.3 4.47 37.6 55.1
Widow 52.2 6.03 40.4 64.0
Other 50.7 7.76 35.5 65.9
Comparison of the Baseline and Midline
Table 7-4 shows that the changes within each stratum and at the level of the overall RISE 
zone were statistically significant, but in a negative direction (opposite the desired effect).
SAREL has a few hypotheses that could explain the growth in negative perceptions towards 
equal opportunities, including: 1) a growing conservative ideological trend (particularly rooted 
in the Zinder region of Niger), 2) backlash and psychological reactance from social changes 
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perceived to be imposed by foreign stakeholders, and 3) other yet to be identified contextual 
changes that may have influenced the perceptions change. To understand these results, SAREL 
will be compiling any relevant opensource data available relating to changing gender 
perceptions in Niger and Burkina Faso over time. SAREL will also be disaggregating the raw 
survey data relating to this question in order to better understand the underlying dynamics 
that may be at play. After all existing data is fully leveraged, a few qualitative questions will be 
developed to test all hypotheses, and other possible explanations, and a short field survey will 
be conducted. Once completed, the data will be analyzed, and a final conclusion will be 
reported.
Table 7-4: T-test comparison between baseline and midline results by stratum for equal access
Stratum Baseline Est. (%) Midline Est. (%) Difference (%) P-Value
High 52.7 46.5 -6.1 0.04
Low 50.6 43.1 -7.5 0.02
Total 51.7 44.8 -6.8 0.00
Figure 7-2 shows that there was no difference in trend between the High and Low strata, 
which is confirmed by the DiD test of 0.74.
Figure 7-2: Proportion of households that agree that males and females should have equal access to social, political, and 
economic opportunities from baseline to midline by stratum
7.3. Women reporting effective participation (Indicator 20)
This indicator captures the degree to which women feel that they have opportunities to 
participate meaningfully in household decisions regarding production and income generation. 
Relative improvements over time in the High exposure zone would serve as evidence that 
women are gaining more autonomy and input as a result of the RISE programs. Women are 
interviewed about their participation in five categories of household decisions: cash crops, 
livestock, non-agricultural activities, employment, and fishing. If a respondent states that she 
participates to a medium or high degree in both the production decisions and the revenue 
decisions for at least one of the five categories, she is treated as participating effectively in 
household decisions.
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Midline Findings
The graph on the left side of Figure 7-3 shows that there are an estimated 285,000 women 
in the High stratum who showed evidence of effective participation while the corresponding 
estimate is about 250,000 in the Low stratum.
The graph on the right side of Figure 7-3 shows the distribution of women according to 
their effective participation on decision making. The exterior ring represents the Low stratum 
while the interior ring shows data from the High stratum. The graph shows that 74.6% of 
women in the High stratum showed effective participation in decision making compared to 
71.0% in the Low stratum. The difference of 3.6% is not statistically significant with a p-value 
of 0.39.
Figure 7-3: Proportion of women reporting effective participation in decision making by stratum
The graph on the left side of Figure 7-4 shows that an estimate of more than 253,000 women 
in the RISE zone of Burkina Faso effectively participated in decision making while the 
corresponding estimate is about 280,000 in the RISE zone of Niger.
Figure 7-4: Proportion of women reporting effective participation in decisions by RISE zone in each country
The graph on the right side of Figure 7-4 shows the distribution of women according to 
their effective participation in decision making. The exterior ring represents the RISE zone of 
Niger while the interior ring shows data from the RISE zone of Burkina Faso. The graph shows 
that the proportion of women with effective participation in decision making is significantly 
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higher in the RISE zone of Niger at 85.7% compared to 62.5% in the RISE zone of Burkina 
Faso. The difference of about 23% is highly significant with a p-value of less than 0.001.
The patterns of the decision making regarding production and revenue are very similar to the 
combined decision making reviewed in the previous paragraphs. That is, there is no significant 
differences between strata, but the proportion of women who made effective decisions, both 
for production and income generation, was significantly higher in the RISE zone of Niger. The 
difference was about 24% for decision making regarding both production and income 
generation; and in both cases it was statistically significant.
Table 7-5: Proportion of women with effective decision-making power, by activity type
The review of the data concerning women with effective decision-making power revealed 
some difference across activities, countries and strata.
Overall, the percentage of women with effective decision-making power is higher among those 
engaged in the non-agricultural economic activities (62%), livestock (57%) and cash crops 
(54%). In contrast, among women involved in fishing and salaried employment, the percentage 
responding that they have effective decision-making is very low at 8% and 28%, respectively, 
although it is important to note that the number of households practicing the latter two 
activities is extremely small. 
Regarding country level differences, the results revealed that the percentage of women with 
decision-making power is higher in Niger than in Burkina Faso for all the categories of activities 
except for non-agricultural economic activities.
Related to the strata, the results showed that the percentage of women with effective 
decision-making power is more important in the High Strata than in Low Strata for only 
livestock and the salaried employment categories.
The details on the results are presented in the tables below.
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Table 7-6: Proportion of women with effective decision-making power, by strata and by country related to food 
production: crops primarily grown for household consumption
Types of 
responses 
Stratum (%) Countries (%)
High Low Total Niger Burkina Total
Yes
41.99 42.74 42.46 51.93 35.24 42.46
No
58.01 57.26 57.54 48.07 64.76 57.54
Total 100 100 100 100 100 100
Table 7-7: Proportion of women with effective decision-making power, by strata and by country related to cash crops: 
crops primarily grown for sale in markets
Types of 
responses 
Stratum (%) Countries (%)
High Low Total Niger Burkina Total
Yes
47.94 58.94 54.18 61.41 49.45 54.18
No
52.06 41.06 45.82 38.59 50.55 45.82
Total 100 100 100 100 100 100
Table 7-8: Proportion of women with effective decision-making power, by strata and by country related to livestock
Types of 
responses 
Stratum (%) Countries (%)
High Low Total Niger Burkina Total
Yes
59.27 55.49 56.93 76.85 42.60 56.93
No
40.73 44.51 43.07 23.15 57.40 43.07
Total 100 100 100 100 100 100
Table 7-9: Proportion of women with effective decision-making power, by strata and by country related to non￾agricultural economic activities: small business, self-employment, purchase and sale
Types of 
responses 
Stratum (%) Countries (%)
High Low Total Niger Burkina Total
Yes
59.24 63.46 61.68 54.91 67.90 61.68
No
40.76 36.54 38.32 45.09 32.10 38.32
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Total 100 100 100 100 100 100
Table 7-10: Proportion of women with effective decision-making power, by strata and by country related to salaried 
employment: work in kind or monetary in agriculture and other paid work
Types of 
responses 
Stratum (%) Countries (%)
High Low Total Niger Burkina Total
Yes
31.28 24.60 28.14 32.45 14.58 28.14
No
68.72 75.40 71.86 67.55 85.42 71.86
Total 100 100 100 100 100 100
Table 7-11 : Proportion of women with effective decision-making power, by strata and by country related to fishing and 
fish ponds
Types of 
responses 
Stratum (%) Countries (%)
High Low Total Niger Burkina Total
Yes
0.00 11.11 8.33 25.00 0.00 8.33
No
100.00 88.89 91.67 75.00 100.00 91.67
Total 100 100 100 100 100 100
Comparison of the Baseline and Midline
Table 7-12 shows that none of the changes within strata or at the level of the overall RISE 
zone were significant.
Table 7-12: T-test comparison between baseline and midline results by stratum
Stratum Baseline Est. (%) Midline Est. (%) Difference (%) P-Value
High 78.6 74.6 -4.0 0.24
Low 71.1 71.0 -0.1 0.97
Total 75.0 72.8 -2.2 0.42
Figure 7-5 shows that the decrease was sharper in the High stratum, but the difference in 
trend was not significant. The DiD test p-value confirms that with a value of 0.47.
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Figure 7-5: Proportion of women reporting effective participation in decisions from baseline to midline by stratum
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8. Summary of Demographic Correlates: Gender, 
Literacy, and Ethnicity of Household Heads
The principal objective of the study was to characterize the RISE zone according to key 
measures of resilience and to draw comparisons from baseline to midline in the High exposure 
versus Low exposure areas. In doing so, however, we also tracked patterns according to a 
number of sociodemographic features of households that could potentially have a bearing on 
the outcomes. Throughout the report, we disaggregated the results for indicators according 
to a number of those features: the gender of heads of households, the marital status of 
household heads, whether or not household heads are literate, and the ethnicity of 
households. Though the study was not designed to test these factors as causal determinants 
of variation in resilience, there are nevertheless some correlations that are worth noting. 
First, the sex of the head of household correlates with a number of outcomes. In general, 
households headed by women were significantly poorer than their male-headed counterparts. 
Women-headed households also scored worse on measures of sanitation, including having a 
soap-and-water handwashing station and an improved sanitation system. Interestingly, female￾headed households correlated with better health outcomes for children living in those 
households, in terms of stunting, being underweight, and being malnourished, even though 
they face greater hunger and worse dietary diversity at the household level.
Second, a literate head of household correlated very strongly with a number of important 
resilience outcomes, all in the expected direction. Households with a head-of-household who 
can read were notably wealthier. They were also more likely to be engaged with the 
community and local leaders, in terms of reaching out to local power structures. Literate 
heads of households likewise correlated with the members of those households having greater 
dietary diversity and facing hunger less often. Finally, households with a literate head had much 
better sanitation practices: they were more likely to use improved sources of drinking water, 
they were more likely to have dedicated soap-and-water handwashing stations, and they 
tended to have improved sanitation systems at a greater rate than their counterparts.
Third, differences in indicator outcomes were notable across ethnic groups. The Hausa had 
a higher rate of poverty, and fewer and less valuable household assets; the Mossi tended to 
be the opposite on these livelihood indicators. Mossi children also tended to be healthier 
than children of other ethnic groups: they had low rates of both stunting and being 
underweight. The Peul/Fulani were particularly likely to suffer from malnutrition. The 
Gourmanchema were more likely than other ethnic groups to have improved drinking water 
and sanitation systems, whereas the Hausa were much more likely than other ethnic groups 
to have soap-and-water handwashing stations. These correlations summarized here constitute 
statistically significant differences, though we reported only comparative means to maintain 
the focus on the intervention effects. We did not find systematic differences in outcomes 
across monogamous and polygamous households, though a few isolated differences were 
apparent and were noted in the text under the sections for those indicators.
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We should underscore two points about these sociodemographic factors and their analysis. 
First, these observed correlations were not tested in a manner that would allow for causal 
inferences. We cannot be sure, for example, if literacy contributes in an important way to 
livelihoods, governance, and health and nutrition, or if some (unobserved) factors that led 
those household heads to become literate also led their households to be wealthier, healthier, 
and more engaged. These correlations are nevertheless important to note, especially because 
RISE activities explicitly target women (which could address some of the challenges that 
female-headed households face) and aim to improve literacy. They may thus contribute in a 
causal manner to differences in low and high exposure areas over time, even though their 
isolated causal effects cannot be measured under the current implementation strategy.
Second, the midline survey upon which this report is based was not designed to explore why
these various sociodemographic correlations exist. However, in complement to this 
quantitative data collection effort, TANGO International will be conducting a qualitative 
evaluation. That more in-depth examination of households and communities should shed 
important light on the nature of some of the correlations noted here.
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9. Complementary Analysis Regarding Family 
Planning in the RISE Zone
During the development of the RISE baseline questionnaires in 2014, USAID requested that 
SAREL add a module that could be used to capture information on trends in the use of family 
planning practices and techniques in the RISE zone. None of the 21 key RISE indicators that 
constitute the main focus of the baseline, midline, and endline evaluations, and that are 
analyzed in the preceding chapters, specifically concern family planning. It is well known, 
however, that family planning is one of the keys and main challenges to achieving reinforced 
household resilience in the Sahel. RISE partners are implementing a number of activities aimed 
at promoting improved access to family planning services for improved maternal and child 
health, as well as addressing social, cultural, and other barriers to the adoption of family 
planning. These activities target women, men, and couples. Given the growing importance of 
family planning as an integral part of USAID’s overall resilience strengthening strategy, we 
report below some of the results gathered on this subject during the baseline and midline 
surveys. 
To gather information related to family planning, SAREL added a module on this subject to 
the RISE Gender questionnaire. Key questions included: 
● Whether the women had heard of methods that a couple may use to delay or avoid 
pregnancy;
● Whether the women and their husbands/partners are doing anything or are currently 
using any method to delay or avoid pregnancy. 
Respondents’ answers to the above questions during the baseline and midline surveys are 
summarized in the tables and graphs below, by strata and by RISE zone of each country.
Table 9-1 and Figure 9-1 reveal a notable increase between the baseline and the midline in 
the percentage of women (in both the High and Low strata) reporting that they have heard 
about methods that a couple may use to delay or to avoid pregnancy. Importantly, there is a 
significant improvement not only across the RISE zone over time, which suggests a general 
increase in awareness, but also in the High stratum relative to the Low stratum. This indicates 
that, above and beyond the broader progress in the study zone, the RISE activities seem to 
have had a notable impact on awareness regarding contraception.
Table 9-1: Women’s awareness of methods a couple may use to delay or avoid pregnancy (by strata)
Types of 
responses 
Baseline (%) Midline (%)
High Low Total High Low Total
Yes 84.9 72.5 78.7 90.3 80.3 85.4
No 15.1 26 20.6 9.7 19.5 14.5
Don't know 0 0.4 0.2 0 0 0
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No answer 0 1.1 0.5 0 0.1 0.1
Total 100 100 100 100 99.9 100
Figure 9-1: Women’s awareness of methods a couple may use to delay or avoid pregnancy (by strata)
The analysis of trends by country show (see Table 9-2 and Figure 9-2) show no significant 
change in awareness of contraceptive methods in the RISE zone of Burkina Faso between the 
baseline and the midline, but the percentage of women in the RISE zone of Niger reporting 
that they have heard about methods that a couple may use to delay or to avoid pregnancy 
increased perceptibly (from 67.6% at the baseline to 84.8% at the midline). The share of 
women in Burkina Faso familiar with contraceptive methods was already quite high at baseline, 
so ceiling effects likely prevented similar improvements there.
Table 9-2: Women’s awareness of methods a couple may use to delay or avoid pregnancy (by country)
Type of 
responses
Baseline (%) Midline (%)
Burkina 
Faso Niger Total
Burkina 
Faso Niger Total
Yes 88.4 67.6 78.7 86 84.8 85.4
No 11.5 30.9 20.6 14 15.1 14.5
Don't know 0.1 0.3 0.2 0 0 0
No answer 0 1.2 0.5 0 0.1 0.1
Total 100 100 100 100 100 100
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Figure 9-2: Women’s awareness of methods a couple may use to delay or avoid pregnancy (by country)
With regard to the question of whether women are actually taking action and using some 
method to delay or avoid pregnancy, Table 9-3 and Figure 9-3 show a modest increase in 
the percentage of women responding affirmatively. Again, there is a slight improvement across 
both the High and Low strata.
Table 9-3: Percentage of women taking actions/using methods to delay or avoid pregnancy (by strata)
Types of 
responses 
Baseline (%) Midline (%)
High Low Total High Low Total
Yes 24.2 20.6 22.5 25.8 22.9 24.4
No 66.7 68.4 67.5 63.1 65.8 64.4
N/A 9.1 10.9 9.9 11.1 11.3 11.2
Don't know 0 0.1 0 0 0 0
No answer 0 0 0 0 0 0
Total 100 100 99.9 100 100 100
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Figure 9-3: Percentage of women taking actions/using methods to delay or avoid pregnancy (by strata)
Table 9-4 and Figure 9-4 reveal important differences, however, in trends in the Burkina 
and Niger parts of the RISE zone. While the percentage of women in the RISE zone of Burkina 
Faso reporting that they were taking action to delay or avoid pregnancy increased notably
from 22% to 31%, in the RISE zone of Niger, the percentage declined during the period from 
22.8% to 16.1%. The sample was small, however, and further analysis will be done to 
determine the significance of that result.
Table 9-4: Percentage of women taking actions/using methods to delay or avoid pregnancy (by country)
Types of 
responses 
Baseline (%) Midline (%)
Burkina Faso Niger Total Burkina Faso Niger Total
Yes 22.3 22.8 22.5 31.3 16.1 24.4
No 66.7 68.7 67.5 58.8 71.1 64.4
N/A 10.9 8.5 9.9 9.9 12.8 11.2
Don't know 0.1 0 0 0 0 0
Not answer 0 0 0 0 0 0
Total 100 100 99.9 100 100 100
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Figure 9-4: Percentage of women taking actions/using methods to delay or avoid pregnancy (by country)
These complementary analyses regarding family planning underscore two important trends at 
the midline point of the RISE program. First, there seems to be notable progress in terms of 
familiarity and understanding of family planning methods among women in the RISE zone. This 
is an important first step in building adaptive and transformative capacities at the household 
level. Second, change in behaviors seem to lag behind changes in awareness, particularly in 
Niger. The trend itself should not be surprising, as behavioral change typically takes longer to 
occur. Attention to these patterns between the midline and the endline surveys will shed 
more light on the adoption of family planning practices.
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10. Lessons Learned and Recommendations
The RISE midline survey resulted in a number of new lessons learned, beyond those learned 
following the baseline study. We have also generated a number of recommendations that can 
serve the continuation of the RISE program, the endline survey of impact, and a potential 
second iteration of the RISE program. We begin this section by outlining lessons learned from 
a technical standpoint, followed by technical recommendations. We then present 
administrative lessons learned and corresponding recommendations. 
10.1. Technical Lessons and Recommendations 
Extensive data collection and analyses always result in new lessons learned from a technical 
standpoint; that was as true of the midline study as it was the baseline. We present the 
technical lessons learned and recommendations from the midline survey here.
10.2. Technical Lessons Learned
The time to administer the questionnaire in each household remains long (2 to 3 hours). This 
creates a hardship for the interviewees as well as those administering the questionnaire. We 
considered stripping out some modules this year that were not directly related to any of the 
21 key indicators, but we backed away from this proposition because: 1) it was still early in 
the implementation of RISE, and we were loath to remove items that we might potentially 
need later in order to have a more complete picture and to help explain certain trends noted 
with the 21 main indicators, and 2) we were concerned that the removal of questionnaire 
items could complicate the comparison of the two data sets, and then the analysis. This 
question can be revisited in consultation with USAID after the completion of the midline 
report.
1. Despite the fact that the enumerators received a thorough and complete training, 
including 10 days of theoretical and practical training, some modules remained difficult 
to administer. This was particularly true of Module 5, concerning Household Assets. 
Measuring the currently value of old household items is exceedingly complex in any 
conditions, and the enumerators had to rely on interviewee recall and had to inquire 
about a large number of items. 
2. Before the analysis of data can take place, the period of data cleaning, coding, and 
preparation is critical for ensuring high quality results from the analysis. We learned 
during the course of the midline analyses that several measures from the baseline data 
had to be recalculated before comparative analyses could be conducted. For example, 
211 children initially identified as belonging to households during the course of the 
survey were not available for the anthropometric measurements, but they 
nevertheless remained in the data set, thus skewing the means. Further, 22 women 
who were not heads of households or the spouse of the household head responded 
to the gender survey, which should not have been the case, so those data needed to 
be removed. These and other data challenges were appropriately addressed when 
SAREL added a high-level statistical expert who could work directly with the data. 
With a data set of the size and complexity of the midline survey, along with the 
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requirement to ensure that the baseline and midline data sets correspond perfectly, it 
is critical to engage higher-level expertise right from the data cleaning stage. In the 
case of the midline survey, the decision to seek a coordinator accredited by the 
American Statistical Association (ASA) to help us better contend with the 
methodological complexities of a survey of this kind was beneficial, because without 
his rigorous recalculation of the baseline values, there are errors that would not have 
been detected and methodological refinements that we would not have made. In 
addition, time needs to be set aside for an expert data analyst to ensure the quality of 
the data before analyses can begin. 
3. In terms of data analysis, the treatment of missing data and exaggerated values remains 
a challenge. For example, there is often little guide for how much an item does or 
should cost in the RISE study zone, particularly in very rural areas where goods may 
come to families through informal means, so it is difficult to rectify wildly different 
reported values. Who exactly counts in a household seems straightforward, but that 
too can be complicated by patterns of seasonal migration and can add to the difficulty 
of data collection.
4. The availability of highly competent and qualified consultants to conduct the kinds of 
rigorous data analyses and statistical reporting required for a report such as this one 
is never guaranteed. Even if they are available and recruited to join the effort, they are 
often working on several commitments simultaneously. Thus, their time is spread over 
longer periods, making it more difficult to provide results of the analyses in a timely 
manner.
10.3. Recommendations Regarding the Technical Aspects
1. The questionnaire needs to be revised. This revision should a) reduce the time of the 
actual administering of the questionnaire by eliminating the modules that are not 
directly relevant to the RISE indicators (such as module 7), and ii) include a clear and 
straightforward process for measuring aspects related to key indicators, such as 
household assets. 
2. To improve the quality of data, more time should be devoted to data cleaning before 
the schedule for analysis begins. This is doubly important as multiple rounds of data 
must be synchronized. 
3. The length of time devoted to data collection is significant, and the data entry, coding, 
cleaning, and analysis took more time than anticipated, despite the best efforts of 
CESAO and the data processing experts. For the final quantitative evaluation, the use 
of tablets could help to ensure faster, high quality data entry and the delivery of clean 
data sets to the data experts in a relatively shorter period of time. We are also aware 
of the risks and challenges inherent in the use of tablets for data collection. The endline 
survey may provide an opportunity for SAREL and CESAO to at least pilot the use of 
tablets among a subset of respondents, which may add some efficiency and would also 
contribute to capacity building. Above all, it remains critical that highly competent data 
experts be brought in early enough to detect potential problems and ensure 
compatibility between different rounds of data before the analysis begin. 
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4. The treatment of missing data and other exaggerated values should be a point of 
emphasis both prior to and during data analysis. Calculation methodologies might be 
developed to provide ranges for values and guidelines for dealing with missing values 
in a systematic manner across all measures. 
5. Data analyst consultants must be recruited early, and time must be set aside to assure 
compatibility in data sets before any analyses can begin. Measures must then be taken 
to avoid time conflicts and other inconveniences that might result in the late 
submission of deliverables. 
10.4. Administrative Lessons and Recommendations
Administration of the survey, analysis, and report improved significantly from baseline to 
midline, especially with the fuller incorporation of CESAO. Nevertheless, a number of lessons 
were learned.
10.5. Administrative Lessons Learned
1. In both Niger and Burkina Faso, we learned that it is critical to begin the institutional 
arrangements at the earliest possible stage, especially with respect to obtaining the 
legal authorization at the Ministry of Territorial Administration in Burkina Faso and 
the Ministry of Interior in Niger. Advanced planning and initiative is also necessary to 
ensure a favorable decision from the institutional review board (IRB), prior to 
collecting the data. 
2. Data collection at the midline stage went much more successfully than at the baseline 
stage, in large part due to the effort to implicate local authorities at every level and to 
engage the sample villages in an extensive awareness campaign. 
3. Based on advice from local authorities, one Low exposure village in Niger had to be 
replaced due to security issues. In some villages in Burkina Faso, team surveyors 
received lodging, support, and advice related to security issues when moving from one 
village to another. In many cases, local authorities served as guides and facilitated the 
identification of households and administration of questionnaires in both countries. 
Though one case of an attack was reported during the course of data collection, 
overall, the data collection was well implemented in the planned timeframe. 
Collaboration with local authorities and populations contributed importantly to 
achieving the objective.
4. The decision to confer the data collection and processing to CESAO worked out very 
well in general, allowing SAREL (and USAID) to obtain good quality data, while also 
allowing SAREL’s partner to substantially strengthen its capacity and experience in 
conducting a large-scale survey.
5. One deliberate change made for the preparation of the midline data collection is that 
Controllers were recruited separately from enumerators (based on more rigorous 
qualifications established for the position), and they completed a training (with 
supervisors), in advance of the training organized for the enumerator candidates. This 
enabled SAREL and CESAO to obtain more experienced persons for the control 
function, and to prepare them better to fulfill their role. By contrast, during the 
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baseline survey, controllers were selected from among the best enumerator 
candidates at the end of surveyor training. They had only cursory additional 
orientation to the specific responsibilities of controllers and the standards to apply.
6. For the midline survey, SAREL developed a guide and checklist to be used by the four 
quality control persons (two M&E consultants, two SAREL M&E specialists) mobilized 
to ensure the correct implementation of field data collection. The application of the 
guide helped to standardize the procedures for conducting the control missions and 
facilitated both the efficient exchange of notes from the field and the application of 
agreed remedial measures. 
7. Logistical decisions in the field depend crucially on the context, and not every decision 
is right for every location. In working closely with CESAO, SAREL learned that it is 
important for data collection partners to have a strong understanding of local 
contextual factors and idiosyncrasies.
8. Security proved to be a challenging issue in the current climate.
9. Despite relying on an enumeration of households conducted in 2015 in order to draw 
the sample, many households had changed or moved. Given the high degree of 
seasonal migration and livelihood challenges in the region, SAREL learned that 
household enumeration lists must be updated regularly.
10.6. Recommendations Regarding Administrative Aspects
1. The institutional arrangements required for obtaining authorizations to conduct the 
survey must be maintained as they have been conducted for the baseline and midline; 
it is important that the process start as early as possible.
2. Given the important improvements in the data collection process resulting from an 
effective awareness campaign in the sample villages, we recommend that this part of 
the process be treated as a formal and important step in the process. It is also 
important that collaboration begin early between surveys, the local authorities, and 
the populations under study. 
3. The local partner organization, in this case CESAO, should take on increasing 
responsibilities over the course of multiple rounds of data collection, working in a 
close collaborative relationship with the monitoring and evaluation project.
4. Controllers must be recruited and trained separately from survey enumerators. They 
should then be implicated in the training of those enumerators as a means of 
reinforcing capacities, fortifying chains of command, and increasing exposure to 
potential challenges in the administration of questionnaires.
5. A guide and checklist should be utilized by quality control personnel in subsequent 
data collection exercises as a means of maintaining standards and ensuring effective 
communication.
6. It is recommended to continue working with data collection partner(s) who have 
regional offices in the countries in question as well as staff familiar with the different 
regions. Further, adequate time must be given to the data collection team to carry out 
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an extensive awareness campaign prior to the actual data collection.
7. It may be necessary to involve local security in the data collection processes, and to 
ensure that survey teams have access to means of transportation that allow them to 
remain as mobile as possible. 
8. With regard to the mobility of populations and the shortcomings of household 
enumeration in 2015, a new enumeration of households in the survey villages should 
be conducted in order to update the sampling frame prior to the next survey.
These recommendations should be given careful consideration in order to continue improving 
upon the data collection processes that began in 2015. The midline process improved 
significantly upon the baseline data collection and analysis in terms of efficiency, accuracy, and 
anticipation of challenges. We believe that additional gains can be realized for the endline 
survey, and the same recommendations may be useful in developing plans for subsequent 
RISE-related programs.
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11. Conclusion
Substantively, the analyses indicate some areas of promise after two years of program 
activities. In particular, livelihood diversification seems to be improving, more villages are 
showing evidence of good governance and preparedness, and the shares of stunted and 
underweight children show signs of decreasing in the areas where RISE activities were 
implemented. Household diets do not seem to have improved, however, and practices that 
would improve sanitation are also not gaining in popularity. Finally, efforts to improve gender 
equality, a key cross-cutting initiative within the RISE program, have not yet resulted in 
measurable improvements.
The administration of the midline survey and the analysis of data improved upon the work 
undertaken for the baseline study. Some methodological challenges were addressed, and 
shortcomings in the original baseline data set were corrected in order to ensure complete 
compatibility with the midline data. SAREL relied on difference-in-differences analysis to 
compare changes in the High exposure zone versus the Low exposure zone over time, so 
consistency across the two rounds of data collection was critical.
To close, we note that the findings at this midline point should still be treated with some 
caution. Many program activities took longer than anticipated to fully implement, and a 
number of exogenous factors—including climate and population change, the rise of violent 
extremism, and activities supported by other donor agencies—can play an outsized role in 
influencing outcomes over a fairly short period of program implementation. Analyses at the 
endline will provide a more robust picture of the effectiveness of RISE activities in 
strengthening the resilience of vulnerable households and villages in the Sahel. The hope is 
that more gains will be observed and that those gains will be sustained beyond the life of the 
RISE program.
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Appendix A. SAREL Methodological Guidelines for 
Measuring RISE Indicators
USAID’s Resilience in the Sahel Enhanced (RISE) initiative aims to strengthen resilience by 
achieving reductions in a set of four topline indicators: shock-related needs, depth of poverty, 
severe hunger, and global acute malnutrition. SAREL is charged with conducting population￾based surveys in Burkina Faso and Niger that provide baseline, midline, and final quantitative 
data related to the latter three of these broad goals.
Twenty-one specific RISE Indicators are used to track progress on the topline goals for which 
SAREL is responsible. This report presents guidelines for measuring those 21 RISE Indicators.
Drawing from the REGIS-ER Monitoring and Evaluation Plan 2013 – 2018, the Ethiopia PRIME 
Impact Evaluation Report, the Niger Food for Peace (FFP) baseline analysis, and other USAID 
sources, the measurement strategies presented here are consistent with USAID methods 
employed elsewhere, which facilitates comparisons. The general approach is to link specific 
survey modules and questions—from the Village, Household, Gender, and Food Consumption 
questionnaires that were administered to participants in the field—to the Performance 
Indicator Reference Sheet (PIRS) for each RISE Indicator. The measurement and aggregation 
methods necessary for making those links differ for each indicator, and the measurement 
guidelines must in some cases be adapted to account for limitations in the data actually 
collected.
Below, the report provides detailed information to facilitate the measurement of each RISE 
Indicator. Under each indicator, definitions and clarifications are provided to the extent 
necessary. The report then describes the specific survey questions used to address the 
indicator, and the coding strategy to be used to account for whether or not for respondents 
or households meet the criterion in question, based on the data obtained from them through 
survey questions. Next, it provides instructions on how to aggregate and analyze the data 
from individual households in order to measure attainment of the RISE Indicator goals and to 
conduct the appropriate comparisons across countries, villages, and eventually high vs. low 
exposure areas. Those data will allow SAREL to develop a comprehensive set of descriptive 
baseline statistics for USAID. Finally, for each indicator, the report provides instructions for 
conducting multivariate analysis. This step will eventually be useful for determining the factors 
related to key outcomes of interest; it also highlights the control variables that will ultimately 
serve as matching factors for the propensity score matching of responses from high and low 
exposure villages. Notes on measurement innovations that result from data constraints are 
also reported.
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Depth of Poverty measures the extent to which individuals are below the poverty line, if they 
are. It is calculated as the average difference between an individual’s income and the poverty 
line of $1.90/day, adjusted for Purchasing Power Parity (PPP) and inflation. Income is reported 
in Local Currency Units (LCUs), in this case FCFA, and is calculated based on household 
expenditures (see Indicator 4). Therefore, it may be easiest to calculate Indicator 4 prior to 
Indicator 1. Individuals whose income is above the poverty line should be given a value of 
zero.
Mathematically, depth of poverty is calculated based on the Poverty Gap Index (PGI), which 
is given by the formula:
𝑃𝑃𝑃𝑃 = (
1
𝑁𝑁 ∑ (
𝑧𝑧−𝑦𝑦𝑖𝑖
𝑧𝑧
𝑁𝑁
=1 )) X 100
Where N is the total number of individuals in the RISE zone, z is the country’s poverty line 
in LCUs, and yi is the daily per capita expenditures of individual i.
To calculate the Depth of Poverty at the national level, use the following steps:
1) For each individual listed in the table from A.11 above (under Prevalence of Poverty), 
subtract the individual’s daily expenditures (yi
) from the country’s poverty line.
a. For Burkina Faso: 451.587 - (yi
)
b. For Niger: 460.058 - (yi
)
2) For each individual, divide the figure from (1) above by the country’s poverty line. This 
calculation generates the difference between each individual’s income and the respective 
country’s poverty line.
a. So, for Burkina Faso: (481.587 - (yi
))/451.587
b. So, for Niger: (460.058 - (yi
))/460.058
3) For all individuals for whom the calculation in (2) results in a negative number, indicating 
per capita expenditures that are greater than the country’s poverty line, replace the figure 
from (2) with zero. If the calculation from (2) results in a positive number, leave those 
figures unchanged.
4) The estimated depth of poverty is the weighted average of the values calculated in (3) 
over all the individuals in the sample.
Descriptive Statistics to Calculate:
• Calculate separate values for each country.
• Disaggregate by Sex of the head of household.
• Disaggregate by the matrimonial situation of the head of household.
• After High and Low Exposure programs have been fully implemented in the field, we 
will eventually calculate depth of poverty based on High and Low Exposure zones. 
Indicator 1: Depth of Poverty
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This indicator is based on the Household Hunger Scale (HHS). Respondents are asked about 
the frequency with which three events were experienced by household members in the last 
four weeks: 1) no food at all in the house; 2) went to bed hungry; and 3) went all day and 
night without eating. For each question, four responses are possible—never, rarely, 
sometimes, or often—which are then collapsed into the follow three responses: never 
(value=0), rarely or sometimes (value=1), and often (value=2). Values for the three questions 
are summed for each household, producing a HHS score ranging from 0 to 6.
The threshold for moderate or severe hunger is a score of 2 or more on the HHS. We do 
not make a further distinction between moderate and severe levels.
The indicator is calculated as follows:
1) First give a score for the first event: “No Food in Household.” Refer to Question 1607 
on the Food Consumption Questionnaire. If the response is coded 2, give the respondent 
0 points for this event. If the response is coded 8 or 9, mark the outcome as missing data.
If the response to Q1607 is coded 1, proceed to Q1607a.
2) From Q1607a, if the response is coded 1 or 2, give the respondent 1 point for this event.
If the response in Q1607a is coded 3, give the respondent 2 points for this event.
3) Then give a score for the second event: “Went to Bed Hungry.” Refer to Question 1608 
on the Food Consumption Questionnaire. If the response is coded 2, give the respondent 
0 points for this event. If the response is coded 8 or 9, mark the outcome as missing data.
If the response to Q1608 is coded 1, proceed to Q1608a.
4) From Q1608a, if the response is coded 1 or 2, give the respondent 1 point for this event.
If the response in Q1608a is coded 3, give the respondent 2 points for this event.
5) Finally, give a score for the third event: “Went All Day and Night Without Food.” Refer 
to Question 1609 on the Food Consumption Questionnaire. If the response is coded 2, 
give the respondent 0 points for this event. If the response is coded 8 or 9, mark the 
outcome as missing data. If the response to Q1609 is coded 1, proceed to Q1609a.
6) From Q1609a, if the response is coded 1 or 2, give the respondent 1 point for this event.
If the response in Q1609a is coded 3, give the respondent 2 points for this event.
7) For each respondent, sum the points for the three events. If the total is equal to or greater 
than 2 points, code the household 1 for Moderate or Severe Hunger. If the total is less 
than 2, code the household 0 for this outcome.
8) The numerator is the weighted total number of households with a score of 2 points or
more. So, divide the weighted number of households coded 1 in (7) by the weighted total 
number of households in the sample for which HHS data was collected. This quotient is 
the estimated prevalence of households with moderate or severe hunger.
Indicator 2: Prevalence of Households with Moderate or Severe Hunger
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Descriptive Statistics to Calculate:
• The indicator can be disaggregated by country. Separate the totals from (7) by country, 
and divide those figures by the total number of households in each country’s sample 
(for which HHS data was collected).
• After the implementation of High and Low Exposure programs, the data can also be 
disaggregated by exposure type.
• Disaggregate by sex of the head of household.
Multivariate Analysis:
As a next step, multivariate regressions can be conducted to determine the factors that 
predict moderate to severe hunger at the household level.
a) Methodological approach: Logit regression – likelihood that a household suffers from 
moderate to severe hunger.
b) Dependent variable: Binary dependent variable coded 1 if the household suffers 
moderate or severe hunger, 0 otherwise.
c) Unit of analysis: the household. Therefore, the number of observations should equate 
to the number of households in the sample, minus any missing data.
d) Possible Independent variables:
i. Country (Q100) – a 1/0 variable
ii. High/Low Exposure (later) – a 1/0 variable
iii. Size of household (Q201)
iv. Ethnicity of HH head (Q205) – 1/0 variables for each group, with one 
omitted
v. Distance from the chef-lieu (Q205 on the Village Questionnaire)
vi. Education level of the head of household (Q206)
vii. Education level of the wife of head of household, if different (Q206)
viii. Daily Household Income (based on expenditures, from Indicator 4, No. 8).
ix. Principal activity of the head of household: 1/0 variables for Agriculture and 
Commerce (all other responses serve as the omitted category).
x. Village fixed effects (1/0 variables for each village, omitting one).
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This measure captures the value of Consumptive, Productive, and Livestock assets in each 
household’s possession, and averages the values across all households. The indicator can be 
reported in either LCU, in this case FCFA, or in US dollars.
We are unable to measure the value of assets in each household’s possession with 
precision. For the Consumptive and Productive Assets, we have data on the number of 
items the household owns currently (Q501), the number it possessed one year ago (Q502), 
the number it possessed two years ago (Q503), whether or not one of the items was 
purchased during the last twelve months (Q504), and how much the household paid for all 
of those items purchased in the last twelve months (Q505). However, because we do not 
have information on how many of the items were purchased during the last twelve months, 
we cannot determine the precise average cost of the recently purchased items. We also do 
not have a baseline from which to assign monetary values to older assets, and we have no 
other data on their cost or how many were lost. The key shortcoming is that we do not 
have a precise way of determining the number of recently purchased items that contribute 
to the total spent on the items in Q505.
As an alternative, we simply add the total amounts spent on items during the last 12 months 
in each household. Thus, the value of assets per household will include only items purchased 
during the last 12 months, along with the value of livestock, for which we do have quantities 
currently owned and average price. 
1) For Consumptive Assets: Sum the values listed in Question 505 (101 – 132) for each 
household. This figure represents the total amount spent by the household during the last 
12 months.
2) For the Productive Assets: follow the same procedure. Sum the values listed in 505 (201 
– 220), which represents the value of all productive assets purchased during the last 12 
months.
3) For the Livestock Assets: sum the values listed in question 603 (01 – 13). This figure 
represents the value of all livestock assets.
4) For each household, sum (1) + (2) + (43). This represents the total value of assets for the 
household (using only purchases from the last 12 months) in FCFA.
5) To obtain the total value of assets for the households in 2010 US dollar Purchasing Power 
Parity (PPP), divide the values reported in (8) by the 2010 PPP conversion rate to US 
dollars.
a. For Burkina Faso: 223.10 FCFA
b. For Niger: 229.23 FCFA
6) Calculate the weighted average of the values in (4) to obtain the estimated average value 
of household assets in FCFA. The same calculation using (5) will provide the estimated 
average value of household assets in US dollar PPP terms.
Indicator 3a. Average Value of Household Assets
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Notes:
1) Agricultural production can also be included. To include the current stock of agricultural 
products, sum the values listed in Q706b (01-26) for each household. Add that amount to 
the sum calculated in (5) above to obtain the total value of assets including agriculture for 
each household. Then continue with step (6): sum the outcomes across all households 
and divide by the total number of households in the sample.
2) Despite the lack of precision in the household assets data, the measure will still be useful 
for tracking changes in purchases and asset ownership over time and in High and Low 
Exposure zones. 
Descriptive Statistics to Calculate:
• The indicator should be disaggregated by country, particularly if the conversion to US 
dollars in PPP terms is made.
• Eventually we will disaggregate the data by High and Low Exposure zones.
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This indicator measures the assets owned by the household, related to consumption, 
production, and livestock. Because Indicator 3a focuses on the average value of such assets, 
here we focus on the accumulation of assets themselves. With the implementation of High 
and Low Exposure programs and subsequent data collection, the indicator will allow us to 
track increases in the economic well-being of program beneficiaries through their acquisition 
of new assets. From this baseline study, we can also calculate the change in asset ownership 
over the past year, to track the economic trajectory of households.
The approach we employ here includes consumptive assets, productive assets, and Total 
Livestock Units (TLUs). It does not include land, nor does it include the agricultural output 
from production. It focuses on the durable (and livestock) assets that households possess.
1) For Consumptive assets: From Question 501, sum the values in the column from 
Q501.101 to Q501.132 for each household. The outcome is the number of Total 
Consumptive Assets that the household currently owns.
2) From Question 502, sum the values in the column from Q502.101 to Q502.132. Subtract 
the Q502 total from the Q501 total for each household. This is the household’s Annual 
Change in Consumptive Assets.
3) For Productive assets: From Question 501, sum the values in the column from Q501.201 
to Q501.220 for each household. The outcome is the number of Total Productive Assets 
that the household currently owns.
4) From Question 502, sum the values in the column from Q502.201 to Q502.220. Subtract 
the Q502 total from the Q501 total for each household. This is the household’s Annual 
Change in Productive Assets.
5) For Total Livestock Units (TLU): From Question 602, sum the values in the column from 
Q602.01 to Q602.13 for each household. The outcome is the number of TLUs that the 
household currently owns.
6) From Question 601, sum the values in the column from Q601.01 to Q601.13. Subtract 
the Q601 total from the Q602 total for each household. This is the household’s Annual 
Change in TLU assets.
7) To determine total asset ownership for the household, calculate the weighted sum of the 
outcomes from (1), (3), and (5) above; these are the current asset totals for each of the 
three types of assets. This figure represents asset ownership at the household level.
8) To determine annual asset change for the household, calculate the weighted sum of
outcomes from (2), (4), and (6) above; these figures represent the change in each type of 
asset ownership over the past year. Outcomes may be negative for each type or for the 
total annual change in assets. This figure represents the estimated annual change in 
asset ownership at the household level.
Indicator 3b: Asset Ownership
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Descriptive Statistics to Calculate:
• The average number of assets owned per household can be calculated by summing the 
total across households and dividing by the number of households in the sample.
• Average ownership of each type of asset can then be determined by disaggregating the 
overall average into Consumptive, Productive, and Livestock categories.
• Average number of assets and annual changes in asset ownership can also be 
disaggregated by country.
• Eventually, we will disaggregate the data by High and Low Exposure zones.
• Because the data is collected at the household level, we are unable to disaggregate the 
outcomes based on the gender of the owner, or on any other individual-level 
characteristics.
Multivariate Analysis:
As a next step, multivariate regressions can be conducted to determine the factors that 
predict asset ownership at the household level.
a) Methodological approach: OLS regression 
b) Dependent variable: the number of assets owned by a household.
a) Unit of analysis: the household. Therefore, the number of observations should equate 
to the number of households in the sample, minus any missing data.
b) Possible Independent variables:
a. Country (Q100) – a 1/0 variable
b. High/Low Exposure (later) – a 1/0 variable
c. Size of household (Q201)
d. Ethnicity of HH head (Q205) – 1/0 variables for each group, with one omitted
e. Distance from the chef-lieu (Q205 on the Village Questionnaire)
f. Education level of the head of household (Q206)
g. Education level of the wife of head of household, if different (Q206)
h. Daily Household Income (based on expenditures, from Indicator 4, No. 8)
i. Principal activity of the head of household: 1/0 variables for Agriculture and 
Commerce (all other responses serve as the omitted category).
j. Village fixed effects (1/0 variables for each village, omitting one).
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Prevalence of Poverty measures the percentage of people living on less than $1.90 per day.
The value is calculated in Local Currency Units (LCU), in this case FCFA; it is based on the 
Purchasing Power Parity conversion from US dollars and accounts for inflation. Because 
income measures are not appropriate for the region, the indicator relies instead on daily per 
capita consumption expenditures. The approach is based on USAID’s Living Standards 
Measurement Survey (LSMS) methodology and the Feed the Future M&E Guidance Series 
Volume 8.
To calculate individual-level poverty, we will first calculate household poverty and then 
divide by the number of people in the household. The procedures follow:
1) Question 505 - Expenditures on Consumption
a. Add the value of all numbers in the column, from 505.101-505.132.
b. The data is recorded in a 12-month time frame. Therefore, divide the total by 365 
to derive daily expenditures.
c. For any items for which the outcome is coded 8 or 9 (don’t know or refused to 
answer), those responses should be replaced with the average amount spent on 
that item in the respondent’s village. Thus, prior to calculating the individual 
expenditures, the village average must be calculated for each item (101-220). Make 
sure to exclude responses coded 8 or 9 when calculating that average. If there are 
few expenditures on a particular item (below five for the village), the average value 
can be calculated using the national average rather than the village average. The 
average value can then be inserted in place of the 8 or 9 in order to calculate the 
household’s expenditures.
d. Any expenditure on an item that is 5 standard deviations or more above the 
mean—either village or national, according to the above guidelines—should be 
replaced by the mean, unless an investigation of the data point (through notes from 
the survey, for example), confirms a legitimate reason for the value entered.
Therefore, calculate standard deviations for each item at the same time the mean 
is calculated (again making sure to exclude those coded 8 or 9). In each case that 
a value for one of the items 101-220 exceeds this threshold of 5 standard 
deviations above the mean, replace that value with the village (or national) mean.
e. There may be items for which the household did not spend any money over the 
past 12 months. That is fine; the zero expenditures do not affect the outcome, 
because the outcome is a sum of expenditures on the items. Be careful not to 
include the zero expenditures in the calculation of averages.
f. Record the outcome as Expenditures on Productive Assets. Each household will 
have one value here that is derived from the Q505 total.
2) Question E2.02 - Expenditures on Non-food Items I
a. Add the value of all numbers in the column, from E2.02 1101 – E2.02 1111.
b. The data is recorded in a 7-day time frame. Therefore, divide the total by 7 to 
derive daily expenditures.
c. If, for any item, Question E2.01 is coded 1 (indicating that the household used or 
bought the item) but no value is given for the item in E2.02, insert the village 
Indicator 4: Prevalence of Poverty
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average value for that item in place of the missing data (or the national average 
value if there are too few households in the village that list a value here).
d. Again, any expenditure on an item that is 5 standard deviations or more above the 
mean should be replaced by the mean.
e. Record the outcome as Expenditures on Non-food Items. Each household will 
have one value here that is derived from the QE2.02 total.
3) Question E3.02 - Expenditures on Non-food Items II
a. Add the value of all numbers in the column, from E3.02 1201 – E3.02 1221.
b. The data is recorded in a 30-day time frame. Therefore, divide the total by 30 to 
derive daily expenditures.
c. If, for any item, Question E3.01 is coded 1 (indicating that the household used or 
bought the item) but no value is given for the item in E3.02, insert the village 
average value for that item in place of the missing data (or the national average 
value if there are too few households in the village that list a value here).
d. Again, any expenditure on an item that is 5 standard deviations or more above the 
mean should be replaced by the mean.
e. Record the outcome as Expenditures on Non-food Items II. Each household will 
have one value here that is derived from the QE3.02 total.
4) Question E4.02 - Expenditures on Non-food Items III
a. Add the value of all numbers in the column, from E4.02 1301 – E4.02 1308.
b. The data is recorded in a 3-month time frame. Therefore, divide the total by 91 to 
derive daily expenditures.
c. If, for any item, Question E4.01 is coded 1 (indicating that the household used or 
bought the item) but no value is given for the item in E4.02, insert the village 
average value for that item in place of the missing data (or the national average 
value if there are too few households in the village that list a value here).
d. Again, any expenditure on an item that is 5 standard deviations or more above the 
mean should be replaced by the mean.
e. Record the outcome as Expenditures on Non-food Items III. Each household will 
have one value here that is derived from the QE4.02 total.
5) Question E5.02 - Expenditures on Non-food Items IV
a. Add the value of all numbers in the column, from E5.02 1401 – E5.02 1417.
b. The data is recorded in a 12-month time frame. Therefore, divide the total by 365 
to derive daily expenditures.
c. If, for any item, Question E5.01 is coded 1 (indicating that the household used or 
bought the item) but no value is given for the item in E5.02, insert the village 
average value for that item in place of the missing data (or the national average 
value if there are too few households in the village that list a value here).
d. Again, any expenditure on an item that is 5 standard deviations or more above the 
mean should be replaced by the mean.
e. Record the outcome as Expenditures on Non-food Items IV. Each household will 
have one value here that is derived from the QE5.02 total.
6) Question E1.04 - Food Expenditures
a. Add the value of all numbers in the column, from E1.04 101 to E1.04 1015.
Question E1.04 is located on the Food Consumption Questionnaire.
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b. The data is recorded in a 7-day time frame. Therefore, divide the total by 7 to 
derive daily expenditures.
c. Again, any expenditure on an item that is 5 standard deviations or more above the 
mean should be replaced by the mean.
d. Record the outcome as Food Expenditures. Each household will have one value 
here that is derived from the QE1.04 total.
7) Calculate the value of Non-purchased Food consumed by the household:
a. Multiply the quantity of non-purchased food consumed from QE1.05a by the 
average value of the item for each item 101 – 906 in the column.
i. To calculate the average value of each item, divide the amount listed in 
E1.04 by the quantity of the item that was purchased, listed in E1.03a. That 
is: E1.04/E1.03a for each item 101 – 906.
ii. Make sure that the unit measure for purchased (E1.03b) and non-purchased 
items (E1.05b) is the same. If it is different, standardize these measures so 
that the values can be compared. For example, suppose the unit measure 
in E1.03b is coded as 08 (a 50kg sac, from the list of codes on the 
questionnaire), and the quantity purchased is reported in E1.03a as 4.
Suppose the unit measure in E1.05b is coded as 09 (a 100kg sac), and the 
quantity consumed is reported in E1.05a as 3. In this case, the average value 
is calculated in terms of 50kg sacs. Therefore, the values in E1.05a and 
E1.05b should be converted into the same 50kg unit measure: 3 100kg sacs 
would be equivalent to 6 50kg sacs. If the unit measures differ for purchased 
and non-purchased items and one or both of the unit measures are less 
precise (such as a pile or a packet), please estimate the comparison.
iii. If a household has values for the non-purchased quantity and units in E1.05a 
and E1.05b but no value for the purchased item, please insert the village 
average for the value of the item. If the household has paid values for the 
item, please use those same paid values to calculate the unit value of non￾purchased items.
b. Create a new column that reflects this output, the value of non-purchased 
consumption for each of the items 101 – 906. Add the value of all numbers in this 
new column. This total reflects the total value of the household’s non-purchased 
food items.
c. The data is recorded in a 7-day time frame. Therefore, divide the total by 7 to 
derive daily expenditures.
d. Again, any expenditure on an item that is 5 standard deviations or more above the 
mean should be replaced by the mean.
e. Record the outcome as Non-purchased Food. Each household will have one value 
here.
8) To calculate the value of lodging for the household, use the average value for the three 
regions of Burkina Faso (Central North, Sahel, and East), as calculated for the EICVM 
2009-2010 survey. This value is 4,725FCFA per month, which comes to 157.50FCFA per 
day. Please use thus value for all households in the RISE zone, as actual lodging 
expenditures were not collected through the survey.
9) Add the amounts for (1) to (7) above. This value represents the daily expenditures for the 
household in LCUs, in this case FCFA.
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10) Divide (8) by the number of individuals in the household, from Question 200. This value 
represents the average daily expenditures for each person in the household.
11) Next, in order to compare individual-level daily expenditures to the poverty line, we need 
to determine the $1.90/day threshold in LCUs, adjusted for Purchasing Power Parity and 
inflation. To do that, we use the following steps:
a. Convert US Dollars into LCUs, using the 2010 Purchasing Power Parity (PPP) 
exchange rate as reported by the World Bank.4
i. For Burkina Faso, 1USD = 223.10 FCFA
ii. For Niger, 1USD = 229.23 FCFA
b. Next, adjust that figure for inflation since 2010 using the Consumer Price Index 
(CPI) for the month closest to the data collection, with average monthly inflation 
in 2010 as the base factor (2010 CPI = 100). Those figures are obtained through 
the International Financial Statistics from the International Monetary Fund (IMF).5
Note that beginning in 2015, the IMF began using 2010 inflation as the base factor, 
instead of 2005. For that reason, the approach here differs slightly from the 
method used for the Niger Food For Peace baseline study conducted earlier.
i. For Burkina Faso, CPIMarch 2015 = 106.534/100
ii. For Niger, CPIApril 2015 = 105.630/100
c. Next, multiply the poverty line threshold of 1.90 by LCUs adjusted for 2010 PPP 
(a) and inflation (b).
i. For Burkina Faso: 1.90 * 223.10 * 106.534/100 = 294.592 FCFA
ii. For Niger: 1.90 * 229.23 * 105.630/100 = 460.058 FCFA
d. The figures reported in (c) are the poverty line thresholds of $1.90/day for Burkina 
Faso and Niger; it is against these figures that individual-level incomes are 
compared in order to determine the proportion living on less than $1.90/day.
12) Create a table that lists each member of all households in the sample, along with the 
average daily expenditures for each person in that household, from (9) above. It is not 
necessary to list the individuals’ names. The following is an example that includes two 
households, the first with four individuals and average daily per capita expenditures of 300 
FCFA and the second with three individuals and average daily per capita expenditures of 
250 FCFA:
Household Individual Daily Expenditures
01 01-01 300 FCFA
01 01-02 300 FCFA
01 01-03 300 FCFA
01 01-04 300 FCFA
02 02-01 250 FCFA
02 02-02 250 FCFA
02 02-03 250 FCFA 
 
4 Data available at http://data.worldbank.org/indicator/PA.NUS.PRVT.PP.
5 Data available at http://elibrary-data.imf.org/DataReport.aspx?c=1449311&d=33061&e=169393.
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13) `Count the weighted number of individuals from the table in (11) who have daily per capita 
expenditures below the poverty line from (10.c) above for each country. This will be the 
numerator.
14) Divide that number by the weighted total number of individuals living in households 
included in the sample (the denominator, from (11) above). This quotient represents the 
prevalence of poverty.
Descriptive Statistics to Calculate:
• The indicator should be calculated for the entire sample and also disaggregated by 
country. Use the number of individuals below the poverty line in Burkina Faso as the 
numerator and the total number of individuals from the sampled households in Burkina 
as the denominator. Repeat for Niger. 
• Disaggregate by sex.
• Disaggregate by sex of the head of household.
• After the implementation of High and Low Exposure programs, the data can eventually 
be disaggregated by exposure type.
Multivariate Regression:
As a next step, multivariate regressions can be conducted to determine the factors that 
predict poverty at the household level.
a) Methodological approach: Ordinary Least Squares (OLS) regression. Alternatively, 
logit regression with binary dependent variable reflecting status of below the poverty 
line or not.
b) Dependent variable: Average per capita expenditures at the household level (from 
(9) above). Alternatively, Status of below the poverty line or not, coded 1/0 (based 
on (12) above).
c) Unit of analysis: the household. Therefore, the number of observations should equate 
to the number of households in the sample, minus any missing data.
d) Possible Independent variables:
i. Country (Q100) – a 1/0 variable
ii. High/Low Exposure (later) – a 1/0 variable
iii. Size of household (Q201)
iv. Ethnicity of HH head (Q205) – 1/0 variables for each group, with one 
omitted
v. Distance from the chef-lieu (Q205 on the Village Questionnaire)
vi. Education level of the head of household (Q206)
vii. Education level of the wife of head of household, if different (Q206)
viii. Village fixed effects (1/0 variables for each village, omitting one)
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This indicator builds on a commonplace tool that measures the opportunities that women in 
surveyed households have to gain control over their own lives through empowerment in 
the agricultural sector. The standard measure is comprised of a five-dimension scale (5DE) 
that is worth 90 percent of the index and a Global Parity Index that contributes 10 percent 
of the score. Each of the five dimensions and their corresponding sub-dimensions are 
assigned a weight toward the total 5DE score.
By design, the REGIS-ER baseline study measures only two dimensions on the 5DE scale:
Production and Resources. Production includes two sub-dimensions: input in production 
Decision Making, and Autonomy in decisions. Resources include three sub-dimensions:
Ownership, Purchases, and Credit Access. Furthermore, the baseline survey gathered 
relevant data only from women, through the Gender Questionnaire, so it is not possible to 
calculate the Gender Parity Index (which requires a comparison of empowerment among 
women and men). Thus, rather than reserving 10 percent of the score for the GPI, the 
totality of the WEAI will be determined by the two dimensions of the 5DE scale.
The weights assigned to the Production and Resources domains using the standard WEAI 
are each 20 percent of the total. Because they are weighted equally, we maintain those 
relative weights, thus assigning new weights of 50 percent to each of these domains (since 
they are the only two components of this revised version). The sub-components within each 
domain are weighted equally, which means that Decision Making and Autonomy are each 
worth 25 percent, and the three Resources sub-dimensions (Ownership, Purchases, and 
Credit Access) are each worth 16.7 percent.
The standard WEAI protocols indicate that a woman is empowered if she reaches 
achievement on 80 percent of the weighted indicators. Because this revised version has 
fewer indicators and thus constitutes a more blunt measure, we use a threshold of 75 
percent. Thus, a surveyed woman must reach achievement on some of the five sub￾dimensions, such that the weights assigned to those in which she is successful accounts for 
75 percent of the weighting.
To calculate Empowerment at the village or country level, the equation is:
𝑊𝑊𝑊𝑊𝑊𝑊 = 𝐻𝐻𝐸𝐸 + 𝐻𝐻𝑁𝑁( )
Where HE is the percentage of women who are empowered based on the above guidelines, 
HN is the percentage of women who are not empowered, and Aa is the average level of 
achievement for those who did not attain empowerment status. The second term is 
important to include because those women may still have reached achievement on some 
sub-dimensions despite that achievement not reaching the 75 percent threshold from the 
weighted indicators, and those achievements should be counted.
Note that the standard measures for the autonomy sub-dimension were not included in this 
survey, but a separate question typically assigned to the Input in Decision Making sub￾dimension asks how much freedom women have to decide. Thus, we revised the indicator 
to treat this question as a measure of the Autonomy sub-dimension. As a result, we also 
adjusted the Production achievement thresholds from ≥ 2 down to ≥ 1, because there are 
Indicator 5: Women’s Empowerment in Agriculture Index (WEAI)
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now fewer measures under the Decision Making and Autonomy sub-dimensions, as noted 
below.
Finally, note that only the female respondents who complete the Gender Questionnaire are 
included in this measure.
1) For Decision Making, go to Question G2.02, A, B, C, and F
a. Count the number of responses from A, B, C, and F that are coded 3 (some), 4 
(most), or 5 (all).
b. Note that D and E are not considered.
c. If the total coded 3, 4, or 5 from items A, B, C, and F is equal to or greater than 
1, mark the respondent as reaching achievement for the Decision Making sub￾dimension.
2) For Autonomy, go to Questions G4.01 and G4.02
a. Count the number of responses from G4.01 A – E that are coded 2 (indicating 
that the woman herself makes the decisions).
b. For the items not coded 2, go to G4.02 (on the freedom to make those decisions 
if she wants). Count the number of items from A – E coded 3 (medium) or 4 (high 
extent).
c. If the sum of those two counts, (a) + (b), is equal to or greater than 1, mark the 
respondent as reaching achievement for the Autonomy sub-dimension.
3) For Ownership, go to Question G303, A – N 
a. Count the number of responses from A – N that are coded 1, 3, 5, 8, or 10 
(indicating manners of female ownership of assets).
b. If the total from (a) is greater than 1, mark the respondent as reaching achievement 
for Ownership.
c. If the total from (a) is equal to 1, check whether the one positive outcome comes 
from items D (chickens), F (non-mechanized farming equipment), or K (long-lasting 
large items). If the one positive outcome does NOT come from one of these three 
items, mark the respondent as reaching achievement for Ownership.
d. If the total from (a) is zero, or if it is 1 and that 1 comes from D, F, or K, the 
respondent does not reach achievement for Ownership.
4) For Purchases, go to Question G301, A – G
a. If none of the items are coded 1 (for household ownership), the respondent does 
not reach achievement for Purchases.
b. If any of the items in G301, A – G are coded 1 for ownership, go to G304 – G307.
c. Count the number of items in G304, A-G that are coded 1, 3, 5, 8, or 10.
d. Count the number of items in G305, A-G that are coded 1, 3, 5, 8, or 10.
e. Count the number of items in G306, A-G that are coded 1, 3, 5, 8, or 10.
f. Count the number of items in G307, A-G that are coded 1, 3, 5, 8, or 10.
g. Tally the number of items with one of those codes from (c), (d), (e), and (f).
h. If (g) is greater than 1, mark the respondent as reaching achievement for Purchases.
i. If (g) is equal to 1, check whether the positive outcome comes from D (chickens) 
or F (non-mechanized farm equipment). If the one positive outcome does NOT 
come from one of these two items, mark the respondent as reaching achievement 
for Purchases.
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j. If the total from (g) is zero, or if it is 1 and that 1 comes from D or F, the 
respondent does not reach achievement for Purchases.
5) For Credit, go to Question G308, A – E.
a. If none of the types of credit are coded 1, 2, or 3 (for various forms of receiving 
credit), the respondent does not reach achievement for Credit.
b. If any of the items A – E are coded 1, 2, or 3, go to G309 and G310.
c. Count the number of items in G309, A – E that are coded 1, 3, 5, 8, or 10.
d. Count the number of items in G310. A – E that are coded 1, 3, 5, 8, or 10.
e. Tally the number of items with one of those codes from (c) and (d).
f. If (e) is equal to or greater than 1, mark the respondent as reaching achievement 
for Credit.
g. If (e) is equal to zero, the respondent does not reach achievement for Credit.
6) For each respondent, calculate her Achievement Rate and her status as Empowered or 
Not Empowered.
a. Refer to the weighted indicators:
i. Achievement in Production = .25
ii. Achievement in Autonomy = .25
iii. Achievement in Ownership = .167
iv. Achievement in Purchases = .167
v. Achievement in Credit Access = .167 
b. For each respondent, sum the weights for each sub-dimension for which she 
reached achievement.
c. If the total share is equal to or greater than .75, code the respondent as 
Empowered.
i. For example, if a respondent reached achievement in Production, 
Ownership, Purchases, and Credit Access, her Achievement Rate is .25 + 
.167 + .167 + .167 = .75, so she is Empowered.
d. If the total share is less than .75, the respondent is Not Empowered.
i. As another example, if a respondent reached achievement in Autonomy, 
Purchases, and Credit Access, her Achievement Rate is .25 + .167 + .167 
= .584, so she is not Empowered.
e. For each respondent, record both the Empowerment status and the Achievement 
Rate.
7) Calculate the village-level WEAI.
a. Disaggregate the responses by village. For each village:
b. Calculate the proportion that is Empowered (HE): Divide the number of 
respondents who are Empowered by the total number of respondents (on the 
Gender Questionnaire) in the village.
c. Calculate the proportion from the village that is Not Empowered (HN): 1 - (HE).
d. Calculate the Achievement Average (Aa) for all respondents in the village who are 
not Empowered:
i. Sum all respondents’ Achievement Rates that are ≤ .75 in the village. 
ii. Divide that sum by the number of respondents whose Achievement Rates 
are ≤ .75 in the village.
e. Add (b) + the product of (c)*(d). This figure represents the Women’s 
Empowerment in Agriculture Index (WEAI) score for each village.
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Descriptive Statistics to Calculate:
• Report the average WEAI across all villages by summing the village WEAI scores and 
dividing by the number of villages.
• Similarly, aggregate the village figures by country to report a WEAI for Burkina Faso 
and Niger.
• Eventually, WEAI can be compared across High and Low Exposure zones.
Notes:
1) The Gender questionnaires do not include demographic data for the respondent (who 
presumably differs from the respondent who completed the Household 
Questionnaire), so individual-level analyses are not possible. If household data from 
the Household Questionnaire can be matched to the Gender Questionnaire, it is 
possible to analyze the likelihood of a household’s female respondent being 
Empowered, but only using household-level, and not individual-level, factors. See the 
regression description below.
Multivariate Analysis:
a) Methodological approach: Logit regression 
b) Dependent variable: Empowered status (1/0 variable).
d) Unit of analysis: the female respondent from the Gender Questionnaire. Therefore, 
the number of observations should equate to the number of households in the sample, 
minus any missing data.
e) Possible Independent variables:
i. Country (Q100) – a 1/0 variable
ii. High/Low Exposure (later) – a 1/0 variable
iii. Size of household (Q201)
iv. Ethnicity of HH head (Q205) – 1/0 variables for each group, with one 
omitted
v. Distance from the chef-lieu (Q205 on the Village Questionnaire)
vi. Education level of the head of household (Q206)
vii. Education level of the wife of head of household, if different (Q206)
viii. Daily Household Income (based on expenditures, from Indicator 4, No. 8)
ix. Principal activity of the head of household: 1/0 variables for Agriculture and 
Commerce (all other responses serve as the omitted category).
x. Village fixed effects (1/0 variables for each village, omitting one).
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This indicator tracks the livelihood activities of households to determine their sources of 
food and income over the past 12 months.
1) Refer to Question 1201, items 201 – 305. If any of the items are coded 1, give the 
household a positive value for non-agricultural income. If all of those items are coded 2, 
the household does not receive any non-agricultural income.
2) For any items in Q1201.201 – 305 that are coded 1, go to Q1203. If the response is ≥ .10 
(meaning that the proportion of income provided by that item is equal to or greater than 
10 percent of the family’s income or food) for any of the items, classify non-agricultural 
sources as an Important source of income for the household.
3) Then, for any items in Q1201.201 – 305 that are coded 1, go to Q1204. If all of the items 
coded 1 in Q1201.201 – 305 are coded as 1 (dry season only) or 2 (wet season only) in 
Q1204, classify non-agricultural sources as a Temporary source of income for the 
household. 
4) Then, for any items in Q1201.201 – 305 that are coded 1, go to Q1205. If any of those 
items are coded 1 (meaning the household relies on the item during times of stress) in 
Q1205, classify non-agricultural sources as a Critical source of income for the household.
5) Calculate the total weighted number of households in the sample that are classified as 
having some form of non-agricultural income, from (1) above. This represents the 
estimated number of households with income from non-agricultural sources.
6) Divide (5) by the total weighted number of households in the sample to obtain the 
estimated proportion of households with income from non-agricultural sources.
7) Sum the percentages from column 1203 for agricultural sources and non-agricultural 
sources for each household. Then calculate the percentage of households for which the 
revenue coming from non-agricultural sources is at least 50 percent.
Descriptive Statistics to Calculate:
• Report both the number and the proportion of households for the total sample.
• Disaggregate the number and the proportion of households with non-agricultural 
income by country.
• Calculate the proportions of households in each country for which non-agricultural 
income is Important, Temporary, and Critical.
• Eventually, we can compare the number and proportion of households with non￾agricultural income across High and Low Exposure zones.
Multivariate Analysis:
a) Methodological approach: Logit regression 
Indicator 6a: Number of Households with Income from Non-Agricultural Sources
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b) Dependent variable: Household relies on some non-agricultural income (1/0 
variable).
c) Unit of analysis: the household. Therefore, the number of observations should 
equate to the number of households in the sample, minus any missing data.
d) Possible Independent variables:
i. Country (Q100) – a 1/0 variable
ii. High/Low Exposure (later) – a 1/0 variable
iii. Size of household (Q201)
iv. Ethnicity of HH head (Q205) – 1/0 variables for each group, with one 
omitted
v. Distance from the chef-lieu (Q205 on the Village Questionnaire)
vi. Education level of the head of household (Q206)
vii. Education level of the wife of head of household, if different (Q206)
viii. Daily Household Income (based on expenditures, from Indicator 4, No. 8)
ix. Village fixed effects (1/0 variables for each village, omitting one)
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Good governance at the village level includes the following components: having natural 
resource management plans, stakeholders involved in addressing climate change, land under 
natural resource management, a conflict management system, success in mediating disputes, 
and community development plans.
We have data that allows us to incorporate some of these elements: natural resource 
management plans, conflict management systems, successful dispute mediation, and 
community development plans. 
1) Question 802 on the Village Questionnaire: if the outcome is coded 1 (for the presence 
of a natural resource management plan), give the village a score of 1. If the outcome is 
coded 2 (for no plan), give the village a score of 0.
2) Question 803 on the Village Questionnaire: if the outcome is coded 1 (for the presence 
of a conflict management system), give the village a score of 1. If the outcome is coded 2 
(for no such system), give the village a score of 0.
3) Question 804 on the Village Questionnaire: if the outcome is coded 1, 2, or 3 (meaning 
that a committee is successful in mediating half or more of local disputes), give the village 
a score of 1. If the outcome is coded 4 or 5 (meaning few disputes are successfully 
mediated), give the village a score of 0.
4) Question 806 on the Village Questionnaire: if the outcome is coded 1 (for the presence 
of a community development plan), give the village a score of 1. If the outcome is coded 
2 (for no such plan), give the village a score of 0.
5) If the sum of the scores from (1) + (2) + (3) + (4) is equal to or greater than 2, mark the 
village as having Good governance.
6) Divide the weighted number of villages with Good governance from (5) by the weighted
total number of villages in the sample. This represents the estimated proportion of 
targeted villages with evidence of good governance.
Descriptive Statistics to Calculate:
• Disaggregate the village data by country.
• Eventually we can compare the data across High and Low Exposure zones.
Multivariate Analysis:
a) Methodological approach: Logit regression 
b) Dependent variable: Village has good governance (1/0 variable).
c) Unit of analysis: the village. Therefore, the number of observations should equate 
to the number of villages in the study, minus any missing data.
d) Possible independent variables:
i. Country (Q100) – a 1/0 variable
Indicator 7: Share of Targeted Communities with Evidence of Good Governance
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ii. High/Low Exposure (later) – a 1/0 variable
iii. Size of village (Q201 from the Village Questionnaire)
iv. Predominant Ethnicity (Q203) – 1/0 variables for each group, omitting one) 
v. Distance from the chef-lieu (Q205 on the Village Questionnaire)
vi. Presence of Formal State Representation (Q801: if coded 2 or 3, outcome = 
1, Otherwise 0).
vii. Average Daily Household Income (based on expenditures, as calculated under 
Indicator 4, Number 8, averaged across all households sampled in the village).
e) Alternative: use an ordered probit model where the dependent variable is a scaled 
variable from 0 – 3, indicating the number of the four elements explained above 
that are present in each village. The unit of analysis remains the village, and the 
independent variables remain the same.
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This indicator measures the capacity of villages to adjust to climate shocks and risks either 
by coping with negative effects or taking advantage of positive climate change opportunities.
For example, soil and water-saving strategies, improved cultural practices, and diversified 
income sources all help to reduce climate shocks at the village level. The data collection 
protocol is derived from the REGIS-ER PIRS related to Strengthened Government and 
Institutions.
The indicator is measured based on three criteria: Practices adopted to manage climate 
change, the level of application of those practices by village members, and the villages’ own 
assessment of the effectiveness of these adaptations for managing climate change.
1) Questions 604b1, 604b2, and 604b3 on the Village Questionnaire: For each of the three 
questions completed (indicating that the village has adopted 1-3 activities from the list in 
603b), give the village a score of 2 if the question is coded 1 (indicating a high level of 
implementation), and a score of 1 if the question is coded 2 (indicating an average level 
of implementation). Otherwise, give the village a score of zero. (Maximum score of 2+2+2 
= 6).
2) Question 605b: If the level of effectiveness is coded as 1 (very effective), give the village 
a score of 4. If the level of effectiveness is coded as 2 (average), give the village a score 
of 3. Otherwise, give the village a score of zero. 
3) If the village achieves a total score of 7 (out of a maximum of 10), code the village as having 
a good capacity for managing shocks and climate risk.
4) Calculate the weighted total number of villages having a good management capacity for 
shocks and climate risk. Divide that number by the weighted total number of villages in 
the sample. The outcome represents the estimated proportion of villages with good 
capacity to manage climate shocks and risk.
Descriptive Statistics to Calculate:
• Disaggregate the village data by country.
• Eventually we can compare the data across High and Low Exposure zones.
Multivariate Analysis:
a) Methodological approach: Logit regression 
b) Dependent variable: Village has good capacity to manage climate risk (1/0 variable).
c) Unit of analysis: the village. Therefore, the number of observations should equate to 
the number of villages in the study, minus any missing data.
d) Possible Independent variables:
i. Country (Q100) – a 1/0 variable
ii. High/Low Exposure (later) – a 1/0 variable
Indicator 8: Share of Targeted Communities with Good Capacity to Manage 
Climate Shocks and Risks
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iii. Size of village (Q201 from the Village Questionnaire)
iv. Predominant Ethnicity (Q203) – 1/0 variables for each group, omitting one
v. Distance from the chef-lieu (Q205 on the Village Questionnaire)
vi. Presence of Formal State Representation (Q801: if coded 2 or 3, outcome 
=1, Otherwise 0).
vii. Average Daily Household Income (based on expenditures, as calculated 
under Indicator 4, Number 8, averaged across all households sampled in the 
village).
e) Alternative: use an ordered probit model where the dependent variable is a scaled 
variable from 0 – 2, where 0 = no activities or training, 1 = activities or training, and 
2 = both activities and training. The unit of analysis remains the village, and the 
independent variables remain the same.
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This indicator measures the extent to which residents have engaged successfully with local 
authorities in order to effect change over the past year.
1) Question 1411 from the Household Questionnaire: if the response is coded 1 (indicating 
that the respondent has successfully engaged with a local authority in order to effect 
change over the past year), mark the respondent as successfully engaging with local power 
structures.
2) If the response to Q1411 is coded 8 or 9 (don’t know or refused to answer), code the 
respondent as missing data.
3) Divide the weighted number of responses coded as successfully engaging with local power 
structures by the weighted total number of households in the sample. Note that you 
should not divide by the total number of individuals within all sampled households, because 
only one individual per household took part in this questionnaire. The outcome represents 
the estimated proportion of individuals who engage with local power structures 
to effect change.
Descriptive Statistics to Calculate:
• Disaggregate the data by country.
• Eventually we can compare the data across High and Low Exposure zones.
Multivariate Analysis:
a) Methodological approach: Logit regression 
b) Dependent variable: Individual engages local power structures (1/0 variable).
c) Unit of analysis: the individual. The number of total observations should equate 
to the number of households in the study, minus any missing data, because only 
one individual is sampled per household for this question.
d) Possible Independent variables:
i. Country (Q100) – a 1/0 variable
ii. High/Low Exposure (later) – a 1/0 variable
iii. Size of household (Q201)
iv. Age of respondent (Q202)
v. Gender of respondent (Q203)
vi. Ethnicity of respondent (Q205) – 1/0 variables for each group, omitting one
vii. Distance from the chef-lieu (Q205 on the Village Questionnaire)
viii. Education level of respondent (Q206)
ix. Daily Household Income (based on expenditures, from Indicator 4, No. 8)
x. Principal activity of respondent (Q210): 1/0 variables for Agriculture and 
Commerce (all other responses serve as the omitted category).
xi. Village fixed effects (1/0 variables for each village, omitting one)
Indicator 9: Proportion of Individuals who engage with Local Power Structures
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This indicator measures the proportion of children under 5 years of age who are acutely 
malnourished, as defined by a weight-for-height Z score of two standard deviations below 
the global mean (which is calculated by the World Health Organization).
A different set of standards is used for children under the age of 2 and those aged 2 – 5 
years, because the older children are measured in terms of standing height while the 
younger children are measured in terms of length.
1) Create a data set for all children from sampled households in the study, based on the data 
from the Food Consumption Questionnaire (which also includes the anthropometry of 
children). Then, for each child:
2) Note the age of the child (Q1707).
3) Note the Gender of the child (Q1704).
4) Note the weight of the child in kilograms (Q1711).
5) Note the length/height of the child in centimeters (Q1712).
6) Compare the weight-for-length/height to the WHO standard to identify children whose 
weight-for-length/height is two or more standard deviations below the global mean.
a. If the child is a boy aged 0 – 23 months, consult the Appendix A.1 table below.
Find the length of the child, and note the corresponding weight that is two standard 
deviations below the mean (under the column SD2neg). If the child’s weight is 
below the listed weight, mark the child as Malnourished.
b. If the child is a girl aged 0 – 23 months, consult the Appendix A.2 table below.
Find the length of the child, and note the corresponding weight that is two standard 
deviations below the mean (under the column SD2neg). If the child’s weight is 
below the listed weight, mark the child as Malnourished.
c. If the child is a boy aged 23 - 59 months, consult the Appendix A.3 table below.
Find the length of the child, and note the corresponding weight that is two standard 
deviations below the mean (under the column SD2neg). If the child’s weight is 
below the listed weight, mark the child as Malnourished.
d. If the child is a girl aged 23 - 59 months, consult the Appendix A.4 table below.
Find the length of the child, and note the corresponding weight that is two standard 
deviations below the mean (under the column SD2neg). If the child’s weight is 
below the listed weight, mark the child as Malnourished.
7) Divide the weighted number of children listed as Malnourished by the weighted total 
number of children in the sample. This represents the Global Acute Malnutrition 
(GAM) Rate. 
Descriptive Statistics to Calculate:
• Disaggregate the data by country to calculate GAM for Burkina Faso and for Niger.
• Disaggregate the data by gender to calculate GAM for boys and girls.
Indicator 10: Global Acute Malnutrition (GAM) in the Zone of Influence
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• Disaggregate by the sex of the head of household.
• Eventually we will disaggregate the data by High and Low Exposure zones.
Multivariate Analysis:
1) Village level analysis
a. Method: OLS regression
b. Unit of Analysis: the village
c. Dependent Variable: the percentage of malnourished children in the village.
d. Independent Variables:
i. Country (Q100) – a 1/0 variable
ii. High/Low Exposure (later) – a 1/0 variable
iii. Size of village (Q201 from the Village Questionnaire)
iv. Predominant Ethnicity (Q203) – 1/0 variables for each, omitting one 
v. Distance from the chef-lieu (Q205 on the Village Questionnaire)
vi. Presence of Formal State Representation (Q801: if coded 2 or 3, 
outcome = 1, Otherwise 0).
vii. Average Daily Household Income (based on expenditures, from 
Indicator 4, Number 8, averaged across all households sampled in the 
village).
2) Household level Analysis
a. Method: Logit regression
b. Unit of Analysis: the household
c. Dependent Variable: presence of any malnourished children in the HH (1/0)
d. Independent Variables:
i. Country (Q100) – a 1/0 variable
ii. High/Low Exposure (later) – a 1/0 variable
iii. Size of household (Q201)
iv. Ethnicity of HH head (Q205) – 1/0 variables for each group, omitting 
one 
v. Distance from the chef-lieu (Q205 on the Village Questionnaire)
vi. Education level of the head of household (Q206)
vii. Education level of the wife of head of household, if different (Q206)
viii. Daily Household Income (based on expenditures, from Indicator 4, No. 
8)
ix. Principal activity of the head of household: 1/0 variables for Agriculture 
and Commerce (all other responses serve as the omitted category).
x. Village fixed effects (1/0 variables for each village, omitting one)
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This indicator measures the proportion of children under 5 years of age whose growth is 
moderately or severely stunted, as defined by a length/height Z score of at least two 
standard deviations below the global mean (which is calculated by the World Health 
Organization).
A different set of standards is used for children under the age of 2 and those aged 2 – 5 
years, because the older children are measured in terms of standing height while the 
younger children are measured in terms of length.
1) Create a data set for all children from sampled households in the study, based on the data 
from the Food Consumption Questionnaire (which also includes the anthropometry of 
children). Then, for each child:
2) Note the age of the child (Q1707).
3) Note the Gender of the child (Q1704).
4) Note the length/height of the child in centimeters (Q1712).
5) Compare the length/height to the WHO standard to identify children whose length/height 
is two or more standard deviations below the global mean.
a. If the child is a boy, use the Boy columns in Appendix B. Find the age of the boy 
(in months) on the table, then note the corresponding length/height that is two 
standard deviations below the mean (under the column SD2neg). If the child’s 
length/height is below the listed number in centimeters, mark the child as Stunted.
b. If the child is a girl, use the Girl columns in the same table, Appendix B. Find the 
age of the girl (in months) on the table, then note the corresponding length/height 
that is two standard deviations below the mean (under the column SD2neg). If the 
child’s length/height is below the listed number in centimeters, mark the child as 
Stunted.
6) Divide the weighted number of children listed as Stunted by the weighted total number 
of children in the sample. This represents the prevalence of stunted children under 
5. 
Descriptive Statistics to Calculate:
• Disaggregate the data by country to calculate Stunted Prevalence for Burkina Faso and 
for Niger.
• Disaggregate the data by gender to calculate Stunted Prevalence for boys and girls.
• Disaggregate by the sex of the head of household.
• Eventually we will disaggregate the data by High and Low Exposure zones.
Indicator 11: Prevalence of Stunted Children Under 5 Years of Age
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Multivariate Analysis:
Village level analysis
a. Method: OLS regression
b. Unit of Analysis: the village
c. Dependent Variable: the percentage of stunted children in the village.
d. Independent Variables:
i. Country (Q100) – a 1/0 variable
ii. High/Low Exposure (later) – a 1/0 variable
iii. Size of village (Q201 from the Village Questionnaire)
iv. Predominant Ethnicity (Q203) – 1/0 variables for each group, omitting one 
v. Distance from the chef-lieu (Q205 on the Village Questionnaire)
vi. Presence of Formal State Representation (Q801: if coded 2 or 3, outcome 
= 1, Otherwise 0).
vii. Average Daily Household Income (based on expenditures, as calculated 
under Indicator 4, Number 8, averaged across all households sampled in 
the village).
Household level Analysis
a. Method: Logit regression
b. Unit of Analysis: the household
c. Dependent Variable: presence of any stunted children in the HH (1/0)
d. Independent Variables:
i. Country (Q100) – a 1/0 variable
ii. High/Low Exposure (later) – a 1/0 variable
iii. Size of household (Q201)
iv. Ethnicity of HH head (Q205) – 1/0 variables for each group, omitting one 
v. Distance from the chef-lieu (Q205 on the Village Questionnaire)
vi. Education level of the head of household (Q206)
vii. Education level of the wife of head of household, if different (Q206)
viii. Daily Household Income (based on expenditures, as calculated under 
Indicator 4, Number 8).
ix. Principal activity of the head of household: 1/0 variables for Agriculture and 
Commerce (all other responses serve as the omitted category).
x. Village fixed effects (1/0 variables for each village, omitting one)
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This indicator measures the proportion of children under 5 years of age who suffer from 
acute or chronic malnutrition and are thus significantly underweight. Underweight status is 
defined by a weight Z score of two standard deviations below the global mean (which is 
calculated by the World Health Organization).
1) Create a data set for all children from sampled households in the study, based on the data 
from the Food Consumption Questionnaire (which also includes the anthropometry of 
children). Then, for each child:
2) Note the age of the child (Q1707).
3) Note the Gender of the child (Q1704).
4) Note the weight of the child in kilograms (Q1711).
5) Compare the weight to the WHO standard to identify children whose weight is two or 
more standard deviations below the global mean.
a. If the child is a boy, use the Boy columns in Appendix C. Find the age of the boy 
(in months) on the table, then note the corresponding weight that is two standard 
deviations below the mean (under the column SD2neg). If the child’s weight is 
below the listed number in kilograms, mark the child as Underweight.
b. If the child is a girl, use the Girl columns in the same table, Appendix C. Find the 
age of the girl (in months) on the table, then note the corresponding weight that 
is two standard deviations below the mean (under the column SD2neg). If the 
child’s weight is below the listed number in kilograms, mark the child as 
Underweight.
6) Divide the number of children listed as Underweight by the total number of children in 
the sample. This represents the Prevalence of Underweight Children under 5. 
Descriptive Statistics to Calculate:
• Disaggregate the data by age groups: 6 – 23 months and 24 – 59 months.
• Disaggregate the data by country to calculate Underweight Prevalence for Burkina 
Faso and for Niger.
• Disaggregate the data by gender to calculate Underweight Prevalence for boys and 
girls.
• Disaggregate by the sex of the head of household.
• Eventually we will disaggregate the data by High and Low Exposure zones.
Multivariate Analysis:
Village level analysis
a. Method: OLS regression
b. Unit of Analysis: the village
c. Dependent Variable: the percentage of underweight children in the village.
d. Independent Variables:
Indicator 12: Prevalence of Underweight Children Under 5 Years of Age
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i. Country (Q100) – a 1/0 variable
ii. High/Low Exposure (later) – a 1/0 variable
iii. Size of village (Q201 from the Village Questionnaire)
iv. Predominant Ethnicity (Q203) – 1/0 variables for each group, omitting one 
v. Distance from the chef-lieu (Q205 on the Village Questionnaire)
vi. Presence of Formal State Representation (Q801: if coded 2 or 3, outcome 
= 1, Otherwise 0).
vii. Average Daily Household Income (based on expenditures, as calculated 
under Indicator 4, Number 8, averaged across all households sampled in 
the village).
Household level Analysis
a. Method: Logit regression
b. Unit of Analysis: the household
c. Dependent Variable: presence of any underweight children in the HH (1/0)
d. Independent Variables:
viii. Country (Q100) – a 1/0 variable
ix. High/Low Exposure (later) – a 1/0 variable
x. Size of household (Q201)
xi. Ethnicity of HH head (Q205) – 1/0 variables for each group, omitting one 
xii. Distance from the chef-lieu (Q205 on the Village Questionnaire)
xiii. Education level of the head of household (Q206)
xiv. Education level of the wife of head of household, if different (Q206)
xv. Daily Household Income (based on expenditures, as calculated under 
Indicator 4, Number 8).
xvi. Principal activity of the head of household: 1/0 variables for Agriculture and 
Commerce (all other responses serve as the omitted category).
xvii. Village fixed effects (1/0 variables for each village, omitting one)
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This indicator measures the shared of households in the sample that use an improved 
source of drinking water. Improved sources include: piped water, a public tap, a protected 
well, a tube well, a protected spring, or rainwater harvesting. These sources are protected 
from outside contamination, especially fecal matter. Bottled water depends on the 
conditions of the bottled water in specific countries, defined in a case-by-case basis.
1) See Question 407 from the Household Questionnaire.
a. If the response is coded as 02 (protected well), 05 (tube well), 06 (public tap), 07 
(indoor tap), 08 (shared outdoor tap), or 11 (bottled), mark the household as using 
an improved source of drinking water.
b. If the response is coded as 12 (other), evaluate the source on a case-by-case basis.
Mark the household as using an improved source of drinking water if the listed 
source offers protection from outside contamination.
c. If the response is coded as any other number, the household’s drinking water is 
considered “unimproved.”
2) Tally the number of households in the sample that use an improved source of drinking 
water.
3) Divide the weighted number of households using an improved source of drinking water 
by the weighted total number of households in the sample. This represents the estimated
percentage of households using an improved drinking water source.
Descriptive Statistics to Calculate:
• Present both the number (2) and the proportion (3).
• Disaggregate the data by country.
• Disaggregate by the type of sources listed in point 1.a.
• Eventually we will disaggregate the data by High and Low Exposure zones.
Multivariate Analysis:
a. Method: Logit regression
b. Unit of Analysis: the household
c. Dependent Variable: presence of an improved source of drinking water in the HH 
(1/0)
d. Independent Variables:
i. Country (Q100) – a 1/0 variable
ii. High/Low Exposure (later) – a 1/0 variable
iii. Size of household (Q201)
iv. Ethnicity of HH head (Q205) – 1/0 variables for each group, omitting one 
v. Distance from the chef-lieu (Q205 on the Village Questionnaire)
vi. Education level of the head of household (Q206)
vii. Education level of the wife of head of household, if different (Q206)
viii. Daily Household Income (based on expenditures, as calculated under 
Indicator 4, Number 8).
Indicator 13: Percentage of Households Using an Improved Drinking Water 
Source
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ix. Principal activity of the head of household: 1/0 variables for Agriculture 
and Commerce (all other responses serve as the omitted category).
x. Village fixed effects (1/0 variables for each village, omitting one)
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A hand-washing station with soap and water is a critical tool for minimizing contamination of 
foods. The station must be observable to enumerators, and the soap and water must be 
reachable from the station. Furthermore, the hand-washing station must be “commonly 
used,” indicating that it is easily observable and indicated by study participants as the place 
where household members typically wash their hands.
1) See Question 411 on the Household Questionnaire.
a. If the response is coded 2, 3, or 4 (indicating no observation of a hand-washing 
station), mark the household as NOT meeting the criteria.
b. If the response is coded 1 for observation of the hand-washing station, proceed to 
Q412.
2) Q412: If the response is coded 2 (indicating no water present), mark the household as 
NOT meeting the criteria. If the response is coded 1 (indicating water), proceed to Q413.
3) Q413: If the response is coded 3 or 4 (indicating no soap), mark the household as NOT 
meeting the criteria. If the response is coded 5 (for “other), evaluate the response to 
determine if it is a form of soap. If the response is coded 1 or 2 (indicating various forms 
of soap), mark the household as meeting all criteria for the soap-and-water hand-washing 
station.
4) To summarize, (1) the hand washing station must be observed, (2) water must be present, 
and (3) soap must be present. If all three conditions are met, the household is recorded 
as having a soap-and-water hand-washing station.
5) Divide the weighted number of households that meet the conditions for a soap-and-water 
hand-washing station by the weighted total number of households in the sample. This 
represents the estimated percentage of households with a soap-and-water hand￾washing station.
Descriptive Statistics to Calculate:
• Disaggregate the data by country.
• Eventually we will disaggregate the data by High and Low Exposure zones.
Multivariate Analysis:
a. Method: Logit regression
b. Dependent Variable: presence of a soap-and-water hand-washing station in the HH 
(1/0)
c. Independent Variables:
Indicator 14: Percentage of Households with a Soap-and-Water Hand-washing 
Station
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This indicator measures whether there is a sanitary facility in the household, as defined by 
the Millennium Development Goals. Sanitary facilities include: piped systems, septic systems, 
other flush facilities, pit latrines with a slab, composting toilets, and ventilated latrines.
1) See Question 406 on the Household Questionnaire.
a. If the response is coded 01 (pit flush toilet), 02 (flush toilet with septic), 03 (flush 
toilet with sewer), 04 (pit latrine with slab), 05 (composting toilet), or 06 
(ventilated latrine), mark the household as using an improved sanitation system.
b. If the response is coded 07, 08, 09, 10, or 11, mark the household as NOT using 
an improved sanitation system.
2) Divide the number of households with an improved sanitation system by the total 
number of households in the sample. This represents the Percentage of Households 
Using an Improved Sanitation System.
Descriptive Statistics to Calculate:
• Disaggregate the data by country.
• Eventually we will disaggregate the data by High and Low Exposure zones.
Multivariate Analysis:
a. Method: Logit regression
b. Unit of Analysis: the household
c. Dependent Variable: presence of a soap-and-water station in the HH (1/0)
d. Independent Variables:
i. Country (Q100) – a 1/0 variable
ii. High/Low Exposure (later) – a 1/0 variable
iii. Size of household (Q201)
iv. Ethnicity of HH head (Q205) – 1/0 variables for each group, omitting one 
v. Distance from the chef-lieu (Q205 on the Village Questionnaire)
vi. Education level of the head of household (Q206)
vii. Education level of the wife of head of household, if different (Q206)
viii. Daily Household Income (based on expenditures, from Indicator 4, No. 
8)
ix. Principal activity of the head of household: 1/0 variables for Agriculture 
and Commerce (all other responses serve as the omitted category).
x. Village fixed effects (1/0 variables for each village, omitting one)
Indicator 15: Percentage of Households Using an Improved Sanitation System
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This indicator measures the mean number of food groups consumed by the household. It 
replaces the indicator for Women’s Dietary Diversity, which is similar but which requires that 
the data relate exclusively to the food consumption of females.
The measure accounts for consumption in the previous 24 hours of a number of food 
groups, such as Grains, roots and tubers; Legumes and nuts; Dairy products (milk, yogurt, 
cheese); meats; eggs; and fruits and vegetables. There are 12 categories in total. The 
guidelines are based on the definition for dietary diversity developed by the Food and 
Agriculture Organization of the United Nations.
1) Go to Questions 1501 to 1512 on the Food Consumption Questionnaire.
a. If the response is coded as 1 (indicating that someone in the household consumed 
that food group in the last day), give the respondent a score of 1.
b. If the response is 2, 8, or 9 (indicating that no one consumed that food group or 
the respondent doesn’t know/refuses to answer), give the respondent a score of 
0.
2) Sum the scores from Q1501-Q1512. The total should be a number between 0 and 12, 
representing the number of food groups from the questionnaire that someone in the 
household has consumed during the last day. This represents the household dietary 
diversity score.
3) Calculate the weighted sum of household dietary diversity score and divide by the 
weighted number of households to determine the estimated average household dietary 
diversity score across the zone.
Descriptive Statistics to Calculate:
• Calculate the mean Household Dietary Diversity Score by country.
• Calculate the mean Household Dietary Diversity Score by village.
• Eventually, we will calculate the mean Household Dietary Diversity Score based on 
High and Low Exposure zones.
Multivariate Analysis:
a. Method: OLS regression
b. Unit of Analysis: the household
c. Dependent Variable: Household Dietary Diversity Score (0 – 12 value)
d. Independent Variables:
i. Country (Q100) – a 1/0 variable
ii. High/Low Exposure (later) – a 1/0 variable
iii. Size of household (Q201)
iv. Ethnicity of HH head (Q205) – 1/0 variables for each group, omitting one 
v. Distance from the chef-lieu (Q205 on the Village Questionnaire)
vi. Education level of the head of household (Q206)
Indicator 16: Household Dietary Diversity
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vii. Education level of the wife of head of household, if different (Q206)
viii. Daily Household Income (based on expenditures, as calculated under 
Indicator 4, Number 8).
ix. Principal activity of the head of household: 1/0 variables for Agriculture and 
Commerce (all other responses serve as the omitted category).
x. Village fixed effects (1/0 variables for each village, omitting one)
e. Alternative: Logit regression, with the dependent variable as the consumption of 
any one particular food group, such as meat (1/0 variable).
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The measure of Minimum Acceptable Diet pertains to children from 6 – 23 months. The 
measure accounts for both diversity—in terms of food groups consumed by the children—
and frequency of meals. Standards differ based on age categories (for example, 6 – 8 month 
old children have different minimum feeding frequencies) and also for breastfed children 
versus those who are not breastfeeding.
1) Create a data set for all children from sampled households in the study, based on the data 
from the Food Consumption Questionnaire (which also includes the anthropometry of 
children). Then, for each child:
2) Note the age of the child from Question 1707. If the child is less than 6 months or older 
than 23 months, exclude the child from this analysis.
3) From Question 17b03, note if the child is breastfed (coded 1 on the questionnaire) or if 
there is no evidence that the child is breastfed (coded 2, 8, or 9).
4) Calculate the child’s dietary diversity in the following manner:
a. If Q17b19 OR Q17b 21 are coded 1, give the child a score of 1 for 
consuming grains. If both Q17b19 and Q17b21 are coded 2, give the child 
a score of 0 for grains.
b. If Q17b29 is coded 1, give the child a score of 1 for consuming legumes. If 
Q17b29 is coded 2, give the child a score of 0 for legumes.
c. If Q17b30 is coded 1, give the child a score of 1 for consuming dairy. If 
Q17b30 is coded 2, give the child a score of 0 for dairy.
d. If Q17b25, Q17b26, OR Q17b28 are coded 1, give the child a score of 1 
for consuming meats. If all three are coded 2, give the child a score of 0 for 
meats.
e. If Q17b27 is coded 1, give the child a score of 1 for consuming eggs. If 
Q17b27 is coded 2, give the child a score of 0 for eggs.
f. If Q17b22 is coded 1, give the child a score of 1 for consuming fruits and 
vegetables high in Vitamin A. If Q17b22 is coded 2, give the child a score 
of 0 for high vitamin A fruits and vegetables.
g. If Q17b24 is coded 1, give the child a score of 1 for consuming other fruits 
and vegetables. If it is coded 2, give the child a score of 0 for other fruits 
and vegetables.
h. For points a-g above, if the response is coded 8 or 9, treat the data as 
missing.
5) If the child is aged 6 – 8 months (from Q1707) AND is breastfed (from Q17b03), calculate 
the minimum acceptable diet in the following manner:
a. If the child has a score equal to or greater than 4 for dietary diversity in step (4) 
above, mark the child as having a diverse diet.
b. Consult Q17b37, which records the number of times the child has eaten foods in 
the last 24 hours. If the number is equal to or greater than 2, mark the child as 
having a frequent diet.
Indicator 17: Prevalence of Children Receiving a Minimum Acceptable Diet 
(MAD)
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c. If the child has a diversity score of at least 4 AND a diet frequency of at least 2 
times per day, mark the child as meeting the standards for a Minimum Acceptable 
Diet. Children who do not meet both of these criteria are considered to not have 
a minimum acceptable diet.
6) If the child is aged 9 – 23 months (from Q1707) AND is breastfed (from Q17b03), 
calculate the minimum acceptable diet in the following manner:
a. If the child has a score equal to or greater than 4 for dietary diversity in step (4) 
above, mark the child as having a diverse diet.
b. Consult Q17b37, which records the number of times the child has eaten foods in 
the last 24 hours. If the number is equal to or greater than 3, mark the child as 
having a frequent diet.
c. If the child has both a diverse diet AND a frequent diet, mark the child as meeting 
the standards for a Minimum Acceptable Diet. Children who do not meet both of 
these criteria are considered to not have a minimum acceptable diet.
d. Note that the difference in age groups is only that the older children should 
consume food at least 3 times per day, rather than 2.
7) If the child is NOT breastfed (coded 2, 8, or 9 from Q17b03), calculate the minimum 
acceptable diet in the following manner for all children aged 6 – 23 months:
a. If the child has a score equal to or greater than 4 for dietary diversity in step (4) 
above, mark the child as having a diverse diet.
b. Sum the numbers from Q17b09 and Q17b11. These questions indicate 
consumption of milk products. If the total for the child is equal to or greater than 
2, mark the child as receiving adequate milk intake.
c. Consult Q17b37, which records the number of times the child has eaten foods in 
the last 24 hours. If the number is equal to or greater than 2, mark the child as 
having a frequent diet.
d. If the child meets all three criteria—diverse diet, adequate milk, and frequent 
diet—mark the child as meeting the standards for a Minimum Acceptable Diet.
Children who do not meet all of these criteria are considered to not have a 
minimum acceptable diet.
8) Sum the weighted number of children (of all ages from 6 – 23 months) who meet the 
standards for a Minimum Acceptable Diet. Divide that number by the weighted total 
number of children between 6 – 23 months in the sample (adding together all children in 
that age range from all households). The outcome represents the estimated prevalence 
of children 6 – 23 months receiving a Minimum Acceptable Diet (MAD).
Descriptive Statistics to Calculate:
• Disaggregate the outcome by age (6 – 8 months and 9 – 23 months)
• Disaggregate the outcome by gender to calculate MAD prevalence for boys and girls
• Disaggregate the outcome by country
• Eventually we will disaggregate the data by High and Low Exposure zones.
Multivariate Analysis: 
Household-level analysis
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a. Method: Logit regression
b. Unit of Analysis: the household
c. Dependent Variable: Presence of any child in the household who does NOT 
receive a Minimum Acceptable Diet (1/0 variable)
d. Independent Variables:
i. Country (Q100) – a 1/0 variable
ii. High/Low Exposure (later) – a 1/0 variable
iii. Size of household (Q201)
iv. Ethnicity of HH head (Q205) – 1/0 variables for each group, omitting one 
v. Distance from the chef-lieu (Q205 on the Village Questionnaire)
vi. Education level of the head of household (Q206)
vii. Education level of the wife of head of household, if different (Q206)
viii. Daily Household Income (based on expenditures, as calculated under 
Indicator 4, Number 8).
ix. Principal activity of the head of household: 1/0 variables for Agriculture and 
Commerce (all other responses serve as the omitted category).
x. Village fixed effects (1/0 variables for each village, omitting one)
e. Alternative: OLS regression, with the dependent variable as the proportion of 
children in the household who receive a Minimum Acceptable Diet.
f. Note: If the household has no children from 6 – 23 months, that household is 
excluded from the analysis.
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Exclusive breastfeeding indicates that a child has received breastmilk but has not received 
any other food or liquid (aside from possible rehydration solutions).
1) Create a data set for all children from sampled households in the study, based on the 
data from the Food Consumption Questionnaire (which also includes the anthropometry of 
children). Then, for each child:
2) Note the age of the child from Question 1707. If the child is older than 6 months, exclude 
the child from this analysis.
3) From Question 17b03, note if the child is breastfed (coded 1 on the questionnaire). If yes, 
give the child a score of 1 for breastfed. If the child is coded 2, mark the child as not being 
breastfed. If the child is coded 8 or 9, code the data as missing.
4) For each child, if ANY of the following questions are coded 1, indicating that the child has 
consumed that item in the past 24 hours, mark the child as consuming Other Food Items:
a. Q17b07 
b. Q17b08
c. Q17b10 
d. Q17b12 
e. Q17b13 
f. Q17b14 
g. Q17b16 – Q17b37 (all inclusive)
5) If ALL of the questions listed above in (4) are coded 2 (indicating that the child did not 
consume the item), mark the child as being Exclusively Breastfed. If any are coded 1, 
meaning the child consumed the item, the child is not exclusively breastfed.
6) If all of the questions listed above in (4) are coded 8 or 9 (indicating don’t know or refused 
to answer), treat the data as missing. If at least one of the items is given a value of 1 ore 
2, treat the data as sufficiently present. 
7) Divide the weighted number of children aged 0 – 6 months who are exclusively breastfed 
by the weighted total number of children aged 0 – 6 from all households in the sample.
This represents the estimated prevalence of exclusive breastfeeding of children 
under 6 months old.
Descriptive Statistics to Calculate:
• Disaggregate the data based on gender
• Disaggregate the data based on country=
• Eventually we will disaggregate the data based on High and Low Exposure zones.
Multivariate Analysis: 
Indicator 18: Prevalence of Exclusive Breastfeeding of Children under 6 
Months Old
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Household-level analysis
a. Method: Logit regression
b. Unit of Analysis: the household
c. Dependent Variable: Presence of an exclusively breastfeeding child (1/0 variable)
d. Independent Variables:
xi. Country (Q100) – a 1/0 variable
xii. High/Low Exposure (later) – a 1/0 variable
xiii. Size of household (Q201)
xiv. Ethnicity of HH head (Q205) – 1/0 variables for each group, omitting one 
xv. Distance from the chef-lieu (Q205 on the Village Questionnaire)
xvi. Education level of the head of household (Q206)
xvii. Education level of the wife of head of household, if different (Q206)
xviii. Daily Household Income (based on expenditures, as calculated under 
Indicator 4, Number 8).
xix. Principal activity of the head of household: 1/0 variables for Agriculture and 
Commerce (all other responses serve as the omitted category).
xx. Village fixed effects (1/0 variables for each village, omitting one)
e. Alternative: OLS regression, with the dependent variable as the proportion of 
children aged 0 – 6 months who are Exclusively Breastfed.
f. Note: If the household has no children from 0 – 6 months, that household is 
excluded from the analysis.
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This indicator measures the degree to which participants agree that males and females 
should have equal access to opportunities. Data are gathered from both men and women, 
allowing for comparisons across gender. Once initiatives, training, and outreach are put in 
place, the data will also provide a measure of the positive impacts that those programs have 
on gender equality.
Note: we will be able to measure the change in this proportion only after the midline study.
1) Go to Question 1410 on the Household Questionnaire, concerning equal access to 
social, economic, and political opportunities.
2) If the response is coded 1, mark the response as a positive outcome; the respondent 
thinks men and women should have equal access to those opportunities.
3) If the response is coded 2, mark the response as a negative outcome; the respondent does 
not think men and women should have equal access to those opportunities.
4) If the response is coded 8 or 9 (indicating doesn’t know or refused to answer), mark the 
response as missing data.
5) Sum the weighted number of responses coded as positive, and divide that number by the 
weighted total number of responses in the sample. This represents the estimated
proportion supporting equal access for males and females to social, economic, 
and political opportunities.
Descriptive Statistics to Calculate:
• Disaggregate the data based on gender, in order to calculate the proportions of 
positive responses for both men and women.
• Disaggregate the data by country.
• Disaggregate the data based on age categories: calculate the proportion of positive 
responses among 18 – 30-year-olds, 31 – 55-year-olds, and those above 55 years old.
• Eventually we will disaggregate the data by High and Low Exposure zones.
Multivariate Analysis:
a) Methodological approach: Logit regression 
b) Dependent variable: Individual supports equal access for males and females (1/0 
variable).
c) Unit of analysis: the individual. The number of total observations should equate to the 
number of households in the study, minus any missing data, because only one individual 
is sampled per household for this question.
d) Possible Independent variables:
Country (Q100) – a 1/0 variable
High/Low Exposure (later) – a 1/0 variable
Indicator 19: Proportion Supporting Equal Access for Males and Females to 
Social, Economic, and Political Opportunities
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Size of household (Q201)
Age of respondent (Q202)
Gender of respondent (Q203)
Ethnicity of respondent (Q205) – 1/0 variables for each group, with one 
omitted
Distance from the chef-lieu (Q205 on the Village Questionnaire)
Education level of respondent (Q206)
Daily Household Income (based on expenditures, from Indicator 4, No. 8)
Principal activity of respondent (Q210): 1/0 variables for Agriculture and 
Commerce (all other responses serve as the omitted category).
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This indicator aims to capture the degree to which women feel that they have opportunities 
to participate meaningfully in household decisions regarding production and income 
generation. The data is drawn only from female respondents who participated in the Gender 
Questionnaire.
1) Go to Module G2, Activity A (food production).
a. If G2.01a is coded 1 for Activity A, meaning that the household conducted this 
activity during the previous 12 months, AND 
b. If G2.01 is coded 1, meaning the female respondent participated, AND
c. If G2.02 is coded 3, 4, or 5, meaning that the female respondent had at least some 
input, give the respondent a score of 1 for Effective Participation in Production 
Decisions for Activity A.
d. All three of those conditions must be met. If one is not, give the respondent a 
score of 0 for Effective Participation in Production Decisions for Activity A.
2) Stay with Module G2, Activity A to evaluate Income Decisions.
a. If G2.01a is coded 1, AND
b. If G2.01 is coded 1, AND
c. If G2.03 is coded 3, 4, or 5, meaning that the female respondent had at least 
some input in income decisions, give the respondent a score of 1 for Effective 
Participation in Income Decisions for Activity A.
d. All three of those conditions must be met. If one is not, give the respondent a 
score of 0 for Effective Participation in Income Decisions for Activity A.
3) Repeat steps (1) and (2) for Activities B (cash crops), C (livestock), D (non-agricultural 
activities), E (employment), and F (fishing).
4) For Activity A, if the respondent scored 1 both for Production Decisions (1.c) and Income 
Decisions (2.c), mark the respondent as Effectively Participating in Activity A.
5) Repeat step (4) for Activities B – F. 
6) Classify respondents by degree of participation:
a. If the respondent effectively participates in at least one activity (either on 
Production or Income), mark the respondent as having Effective Participation.
7) Sum the weighted number of respondents on the Gender Questionnaire who effectively 
participate in at least one activity (either on Production or Income) from (6.a) above.
Divide this number by the weighted total number of respondents in the Gender 
Questionnaire sample. This represents the estimated percentage of women reporting 
effective participation in household decision making.
Descriptive Statistics to Calculate:
• Disaggregate the data by country.
Indicator 20: Percentage of Women Reporting Effective Participation in 
Household Decision Making
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• In addition to the proportion reporting effective participation, also calculate the 
proportion of women that report participating the production decisions and the 
revenue decisions separately. 
• Eventually we will disaggregate the data by High and Low Exposure zones.
Notes:
The Gender questionnaires do not include demographic data for the respondent (who 
presumably differs from the respondent who completed the Household Questionnaire), so 
individual-level analyses are not possible. If household data from the Household Questionnaire 
can be matched to the Gender Questionnaire, it is possible to analyze the likelihood of a 
household’s female respondent having Effective Participation, but only using household-level, 
and not individual-level, factors.
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Appendix B. WHO Height and Weight Standards
Length SD2neg
109 14.983
109.1 15.013
109.2 15.043
109.3 15.073
109.4 15.104
109.5 15.135
109.6 15.165
109.7 15.196
109.8 15.227
109.9 15.258
110 15.289
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Table WFH.
Weight for Height Table – for Boys aged 24-59 months
Height SD2neg Height SD2neg Height SD2neg
65.0 6.335 69.9 7.292 74.8 8.173
65.1 6.355 70.0 7.311 74.9 8.190
65.2 6.376 70.1 7.330 75.0 8.207
65.3 6.396 70.2 7.349 75.1 8.223
65.4 6.416 70.3 7.368 75.2 8.240
65.5 6.436 70.4 7.387 75.3 8.257
65.6 6.456 70.5 7.406 75.4 8.273
65.7 6.476 70.6 7.424 75.5 8.290
65.8 6.496 70.7 7.443 75.6 8.306
65.9 6.516 70.8 7.462 75.7 8.323
66.0 6.536 70.9 7.480 75.8 8.339
66.1 6.556 71.0 7.499 75.9 8.355
66.2 6.575 71.1 7.518 76.0 8.371
66.3 6.595 71.2 7.536 76.1 8.387
66.4 6.615 71.3 7.555 76.2 8.403
66.5 6.635 71.4 7.573 76.3 8.420
66.6 6.654 71.5 7.592 76.4 8.436
66.7 6.674 71.6 7.610 76.5 8.452
66.8 6.694 71.7 7.628 76.6 8.467
66.9 6.713 71.8 7.647 76.7 8.483
67.0 6.733 71.9 7.665 76.8 8.499
67.1 6.752 72.0 7.683 76.9 8.515
67.2 6.772 72.1 7.701 77.0 8.531
67.3 6.791 72.2 7.719 77.1 8.546
67.4 6.811 72.3 7.737 77.2 8.562
67.5 6.830 72.4 7.755 77.3 8.578
67.6 6.850 72.5 7.773 77.4 8.593
67.7 6.869 72.6 7.791 77.5 8.609
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Height SD2neg Height SD2neg Height SD2neg
67.8 6.888 72.7 7.809 77.6 8.624
67.9 6.908 72.8 7.827 77.7 8.640
68.0 6.927 72.9 7.844 77.8 8.655
68.1 6.946 73.0 7.862 77.9 8.671
68.2 6.966 73.1 7.880 78.0 8.686
68.3 6.985 73.2 7.897 78.1 8.702
68.4 7.004 73.3 7.915 78.2 8.718
68.5 7.024 73.4 7.932 78.3 8.733
68.6 7.043 73.5 7.950 78.4 8.749
68.7 7.062 73.6 7.967 78.5 8.764
68.8 7.081 73.7 7.985 78.6 8.780
68.9 7.101 73.8 8.002 78.7 8.795
69.0 7.120 73.9 8.019 78.8 8.811
69.1 7.139 74.0 8.036 78.9 8.826
69.2 7.158 74.1 8.054 79.0 8.842
69.3 7.177 74.2 8.071 79.1 8.858
69.4 7.197 74.3 8.088 79.2 8.874
69.5 7.216 74.4 8.105 79.3 8.890
69.6 7.235 74.5 8.122 79.4 8.906
69.7 7.254 74.6 8.139 79.5 8.922
69.8 7.273 74.7 8.156 79.6 8.938
79.7 8.954 84.8 9.916 89.9 11.002
79.8 8.970 84.9 9.938 90.0 11.022
79.9 8.986 85.0 9.959 90.1 11.043
80.0 9.002 85.1 9.981 90.2 11.063
80.1 9.019 85.2 10.002 90.3 11.083
80.2 9.035 85.3 10.024 90.4 11.103
80.3 9.052 85.4 10.046 90.5 11.123
80.4 9.069 85.5 10.067 90.6 11.144
80.5 9.085 85.6 10.089 90.7 11.164
80.6 9.102 85.7 10.111 90.8 11.184
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Height SD2neg Height SD2neg Height SD2neg
80.7 9.119 85.8 10.133 90.9 11.204
80.8 9.136 85.9 10.154 91.0 11.224
80.9 9.153 86.0 10.176 91.1 11.244
81.0 9.171 86.1 10.198 91.2 11.264
81.1 9.188 86.2 10.220 91.3 11.284
81.2 9.205 86.3 10.242 91.4 11.304
81.3 9.223 86.4 10.263 91.5 11.324
81.4 9.241 86.5 10.285 91.6 11.344
81.5 9.258 86.6 10.307 91.7 11.364
81.6 9.277 86.7 10.328 91.8 11.384
81.7 9.295 86.8 10.350 91.9 11.404
81.8 9.313 86.9 10.372 92.0 11.424
81.9 9.331 87.0 10.393 92.1 11.444
82.0 9.350 87.1 10.415 92.2 11.463
82.1 9.368 87.2 10.436 92.3 11.483
82.2 9.387 87.3 10.458 92.4 11.503
82.3 9.406 87.4 10.479 92.5 11.523
82.4 9.425 87.5 10.501 92.6 11.543
82.5 9.444 87.6 10.522 92.7 11.563
82.6 9.463 87.7 10.544 92.8 11.582
82.7 9.483 87.8 10.565 92.9 11.602
82.8 9.503 87.9 10.586 93.0 11.622
82.9 9.522 88.0 10.607 93.1 11.641
83.0 9.542 88.1 10.629 93.2 11.661
83.1 9.562 88.2 10.650 93.3 11.681
83.2 9.582 88.3 10.671 93.4 11.701
83.3 9.602 88.4 10.692 93.5 11.721
83.4 9.622 88.5 10.713 93.6 11.741
83.5 9.643 88.6 10.734 93.7 11.760
83.6 9.663 88.7 10.755 93.8 11.780
83.7 9.684 88.8 10.775 93.9 11.800
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Height SD2neg Height SD2neg Height SD2neg
83.8 9.705 88.9 10.796 94.0 11.820
83.9 9.725 89.0 10.817 94.1 11.840
84.0 9.746 89.1 10.838 94.2 11.860
84.1 9.767 89.2 10.858 94.3 11.880
84.2 9.788 89.3 10.879 94.4 11.899
84.3 9.809 89.4 10.899 94.5 11.919
84.4 9.831 89.5 10.920 94.6 11.940
84.5 9.852 89.6 10.940 94.7 11.960
84.6 9.873 89.7 10.961 94.8 11.980
84.7 9.895 89.8 10.981 94.9 12.000
95.0 12.020 100.1 13.110 105.2 14.334
95.1 12.040 100.2 13.133 105.3 14.359
95.2 12.060 100.3 13.155 105.4 14.384
95.3 12.080 100.4 13.178 105.5 14.410
95.4 12.100 100.5 13.201 105.6 14.435
95.5 12.121 100.6 13.224 105.7 14.461
95.6 12.141 100.7 13.247 105.8 14.486
95.7 12.161 100.8 13.270 105.9 14.512
95.8 12.182 100.9 13.293 106.0 14.537
95.9 12.202 101.0 13.317 106.1 14.563
96.0 12.223 101.1 13.340 106.2 14.589
96.1 12.243 101.2 13.363 106.3 14.615
96.2 12.264 101.3 13.386 106.4 14.641
96.3 12.284 101.4 13.410 106.5 14.667
96.4 12.305 101.5 13.433 106.6 14.692
96.5 12.326 101.6 13.457 106.7 14.718
96.6 12.347 101.7 13.480 106.8 14.744
96.7 12.367 101.8 13.504 106.9 14.770
96.8 12.388 101.9 13.528 107.0 14.797
96.9 12.409 102.0 13.551 107.1 14.823
97.0 12.430 102.1 13.575 107.2 14.849
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Height SD2neg Height SD2neg Height SD2neg
97.1 12.451 102.2 13.599 107.3 14.875
97.2 12.472 102.3 13.623 107.4 14.902
97.3 12.494 102.4 13.646 107.5 14.928
97.4 12.515 102.5 13.670 107.6 14.954
97.5 12.536 102.6 13.694 107.7 14.981
97.6 12.558 102.7 13.718 107.8 15.008
97.7 12.579 102.8 13.742 107.9 15.034
97.8 12.600 102.9 13.766 108.0 15.061
97.9 12.622 103.0 13.791 108.1 15.088
98.0 12.644 103.1 13.815 108.2 15.115
98.1 12.665 103.2 13.839 108.3 15.142
98.2 12.687 103.3 13.863 108.4 15.168
98.3 12.709 103.4 13.888 108.5 15.195
98.4 12.731 103.5 13.912 108.6 15.223
98.5 12.752 103.6 13.937 108.7 15.250
98.6 12.774 103.7 13.961 108.8 15.277
98.7 12.796 103.8 13.985 108.9 15.304
98.8 12.818 103.9 14.010 109.0 15.332
98.9 12.840 104.0 14.035 109.1 15.359
99.0 12.863 104.1 14.059 109.2 15.386
99.1 12.885 104.2 14.084 109.3 15.414
99.2 12.907 104.3 14.109 109.4 15.442
99.3 12.929 104.4 14.134 109.5 15.470
99.4 12.952 104.5 14.159 109.6 15.497
99.5 12.974 104.6 14.183 109.7 15.525
99.6 12.997 104.7 14.209 109.8 15.553
99.7 13.019 104.8 14.233 109.9 15.581
99.8 13.042 104.9 14.258 110.0 15.609
99.9 13.065 105.0 14.283 110.1 15.637
100.0 13.087 105.1 14.309 110.2 15.666
110.3 15.694 115.4 17.205
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Height SD2neg Height SD2neg Height SD2neg
110.4 15.722 115.5 17.236
110.5 15.751 115.6 17.266
110.6 15.779 115.7 17.297
110.7 15.808 115.8 17.328
110.8 15.836 115.9 17.359
110.9 15.865 116.0 17.389
111.0 15.894 116.1 17.420
111.1 15.922 116.2 17.451
111.2 15.951 116.3 17.481
111.3 15.980 116.4 17.512
111.4 16.009 116.5 17.543
111.5 16.038 116.6 17.574
111.6 16.067 116.7 17.605
111.7 16.096 116.8 17.635
111.8 16.126 116.9 17.666
111.9 16.155 117.0 17.697
112.0 16.184 117.1 17.728
112.1 16.213 117.2 17.759
112.2 16.243 117.3 17.790
112.3 16.272 117.4 17.821
112.4 16.302 117.5 17.852
112.5 16.331 117.6 17.883
112.6 16.361 117.7 17.913
112.7 16.390 117.8 17.944
112.8 16.420 117.9 17.975
112.9 16.450 118.0 18.006
113.0 16.479 118.1 18.037
113.1 16.509 118.2 18.068
113.2 16.539 118.3 18.099
113.3 16.569 118.4 18.130
113.4 16.599 118.5 18.161
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Height SD2neg Height SD2neg Height SD2neg
113.5 16.629 118.6 18.192
113.6 16.659 118.7 18.223
113.7 16.689 118.8 18.254
113.8 16.719 118.9 18.285
113.9 16.749 119.0 18.316
114.0 16.779 119.1 18.347
114.1 16.809 119.2 18.377
114.2 16.840 119.3 18.408
114.3 16.870 119.4 18.439
114.4 16.900 119.5 18.470
114.5 16.931 119.6 18.501
114.6 16.961 119.7 18.532
114.7 16.991 119.8 18.563
114.8 17.022 119.9 18.593
114.9 17.052 120.0 18.624
115.0 17.083
115.1 17.113
115.2 17.144
115.3 17.175
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Weight for Height Table – for Girls aged 24-59 months
Height SD2neg Height SD2neg Height SD2neg
65.0 6.071 69.9 6.954 74.8 7.766
65.1 6.090 70.0 6.971 74.9 7.781
65.2 6.109 70.1 6.988 75.0 7.797
65.3 6.128 70.2 7.006 75.1 7.812
65.4 6.146 70.3 7.023 75.2 7.828
65.5 6.165 70.4 7.040 75.3 7.844
65.6 6.184 70.5 7.057 75.4 7.859
65.7 6.203 70.6 7.074 75.5 7.875
65.8 6.221 70.7 7.091 75.6 7.890
65.9 6.240 70.8 7.108 75.7 7.906
66.0 6.259 70.9 7.125 75.8 7.922
66.1 6.277 71.0 7.142 75.9 7.937
66.2 6.296 71.1 7.159 76.0 7.953
66.3 6.314 71.2 7.176 76.1 7.968
66.4 6.333 71.3 7.193 76.2 7.984
66.5 6.351 71.4 7.210 76.3 7.999
66.6 6.369 71.5 7.227 76.4 8.015
66.7 6.388 71.6 7.244 76.5 8.031
66.8 6.406 71.7 7.261 76.6 8.046
66.9 6.424 71.8 7.278 76.7 8.062
67.0 6.442 71.9 7.294 76.8 8.078
67.1 6.460 72.0 7.311 76.9 8.094
67.2 6.479 72.1 7.328 77.0 8.109
67.3 6.497 72.2 7.345 77.1 8.125
67.4 6.515 72.3 7.361 77.2 8.141
67.5 6.533 72.4 7.378 77.3 8.157
67.6 6.550 72.5 7.395 77.4 8.173
67.7 6.568 72.6 7.411 77.5 8.189
67.8 6.586 72.7 7.428 77.6 8.205
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Height SD2neg Height SD2neg Height SD2neg
67.9 6.604 72.8 7.444 77.7 8.221
68.0 6.622 72.9 7.461 77.8 8.237
68.1 6.640 73.0 7.477 77.9 8.253
68.2 6.657 73.1 7.493 78.0 8.270
68.3 6.675 73.2 7.510 78.1 8.286
68.4 6.693 73.3 7.526 78.2 8.302
68.5 6.710 73.4 7.542 78.3 8.319
68.6 6.728 73.5 7.559 78.4 8.335
68.7 6.745 73.6 7.575 78.5 8.352
68.8 6.763 73.7 7.591 78.6 8.368
68.9 6.781 73.8 7.607 78.7 8.385
69.0 6.798 73.9 7.623 78.8 8.402
69.1 6.815 74.0 7.639 78.9 8.419
69.2 6.833 74.1 7.655 79.0 8.436
69.3 6.850 74.2 7.671 79.1 8.453
69.4 6.868 74.3 7.687 79.2 8.470
69.5 6.885 74.4 7.702 79.3 8.487
69.6 6.902 74.5 7.718 79.4 8.504
69.7 6.919 74.6 7.734 79.5 8.522
69.8 6.937 74.7 7.750 79.6 8.539
79.7 8.556 84.8 9.550 89.9 10.623
79.8 8.574 84.9 9.571 90.0 10.644
79.9 8.592 85.0 9.592 90.1 10.664
80.0 8.609 85.1 9.613 90.2 10.685
80.1 8.627 85.2 9.634 90.3 10.706
80.2 8.645 85.3 9.655 90.4 10.726
80.3 8.663 85.4 9.676 90.5 10.747
80.4 8.681 85.5 9.697 90.6 10.768
80.5 8.700 85.6 9.719 90.7 10.788
80.6 8.718 85.7 9.740 90.8 10.809
80.7 8.736 85.8 9.761 90.9 10.830
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Height SD2neg Height SD2neg Height SD2neg
80.8 8.755 85.9 9.782 91.0 10.850
80.9 8.773 86.0 9.803 91.1 10.871
81.0 8.792 86.1 9.825 91.2 10.892
81.1 8.810 86.2 9.846 91.3 10.912
81.2 8.829 86.3 9.867 91.4 10.933
81.3 8.848 86.4 9.888 91.5 10.953
81.4 8.867 86.5 9.910 91.6 10.974
81.5 8.886 86.6 9.931 91.7 10.995
81.6 8.905 86.7 9.952 91.8 11.015
81.7 8.924 86.8 9.973 91.9 11.036
81.8 8.943 86.9 9.994 92.0 11.056
81.9 8.962 87.0 10.015 92.1 11.077
82.0 8.982 87.1 10.037 92.2 11.098
82.1 9.001 87.2 10.058 92.3 11.118
82.2 9.021 87.3 10.079 92.4 11.139
82.3 9.040 87.4 10.100 92.5 11.159
82.4 9.060 87.5 10.121 92.6 11.180
82.5 9.080 87.6 10.142 92.7 11.201
82.6 9.100 87.7 10.163 92.8 11.221
82.7 9.119 87.8 10.184 92.9 11.242
82.8 9.139 87.9 10.205 93.0 11.262
82.9 9.159 88.0 10.226 93.1 11.283
83.0 9.179 88.1 10.247 93.2 11.304
83.1 9.199 88.2 10.268 93.3 11.324
83.2 9.220 88.3 10.289 93.4 11.345
83.3 9.240 88.4 10.310 93.5 11.366
83.4 9.260 88.5 10.331 93.6 11.386
83.5 9.281 88.6 10.352 93.7 11.407
83.6 9.301 88.7 10.373 93.8 11.428
83.7 9.321 88.8 10.394 93.9 11.448
83.8 9.342 88.9 10.415 94.0 11.469
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Height SD2neg Height SD2neg Height SD2neg
83.9 9.363 89.0 10.436 94.1 11.490
84.0 9.383 89.1 10.457 94.2 11.511
84.1 9.404 89.2 10.477 94.3 11.532
84.2 9.425 89.3 10.498 94.4 11.552
84.3 9.445 89.4 10.519 94.5 11.573
84.4 9.466 89.5 10.540 94.6 11.594
84.5 9.487 89.6 10.561 94.7 11.615
84.6 9.508 89.7 10.581 94.8 11.636
84.7 9.529 89.8 10.602 94.9 11.657
95.0 11.678 100.1 12.795 105.2 14.090
95.1 11.699 100.2 12.818 105.3 14.117
95.2 11.719 100.3 12.842 105.4 14.145
95.3 11.740 100.4 12.865 105.5 14.173
95.4 11.761 100.5 12.889 105.6 14.200
95.5 11.783 100.6 12.913 105.7 14.228
95.6 11.804 100.7 12.937 105.8 14.256
95.7 11.825 100.8 12.960 105.9 14.284
95.8 11.846 100.9 12.984 106.0 14.312
95.9 11.867 101.0 13.008 106.1 14.340
96.0 11.888 101.1 13.033 106.2 14.368
96.1 11.909 101.2 13.057 106.3 14.397
96.2 11.930 101.3 13.081 106.4 14.425
96.3 11.952 101.4 13.105 106.5 14.454
96.4 11.973 101.5 13.130 106.6 14.482
96.5 11.994 101.6 13.155 106.7 14.511
96.6 12.015 101.7 13.179 106.8 14.540
96.7 12.037 101.8 13.204 106.9 14.569
96.8 12.058 101.9 13.229 107.0 14.598
96.9 12.080 102.0 13.253 107.1 14.627
97.0 12.101 102.1 13.278 107.2 14.656
97.1 12.123 102.2 13.303 107.3 14.685
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Height SD2neg Height SD2neg Height SD2neg
97.2 12.144 102.3 13.329 107.4 14.715
97.3 12.166 102.4 13.354 107.5 14.744
97.4 12.188 102.5 13.379 107.6 14.773
97.5 12.209 102.6 13.404 107.7 14.803
97.6 12.231 102.7 13.430 107.8 14.833
97.7 12.253 102.8 13.455 107.9 14.863
97.8 12.275 102.9 13.481 108.0 14.892
97.9 12.297 103.0 13.506 108.1 14.922
98.0 12.319 103.1 13.532 108.2 14.953
98.1 12.341 103.2 13.558 108.3 14.983
98.2 12.363 103.3 13.584 108.4 15.013
98.3 12.385 103.4 13.610 108.5 15.043
98.4 12.407 103.5 13.636 108.6 15.073
98.5 12.429 103.6 13.662 108.7 15.104
98.6 12.452 103.7 13.688 108.8 15.135
98.7 12.474 103.8 13.714 108.9 15.165
98.8 12.496 103.9 13.741 109.0 15.196
98.9 12.519 104.0 13.767 109.1 15.227
99.0 12.542 104.1 13.793 109.2 15.258
99.1 12.564 104.2 13.820 109.3 15.289
99.2 12.587 104.3 13.847 109.4 15.320
99.3 12.610 104.4 13.873 109.5 15.351
99.4 12.633 104.5 13.900 109.6 15.382
99.5 12.655 104.6 13.927 109.7 15.413
99.6 12.679 104.7 13.954 109.8 15.445
99.7 12.702 104.8 13.981 109.9 15.476
99.8 12.725 104.9 14.008 110.0 15.508
99.9 12.748 105.0 14.035 110.1 15.539
100.0 12.771 105.1 14.063 110.2 15.571
110.3 15.603 115.4 17.297
110.4 15.634 115.5 17.331
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Height SD2neg Height SD2neg Height SD2neg
110.5 15.666 115.6 17.365
110.6 15.698 115.7 17.400
110.7 15.730 115.8 17.434
110.8 15.762 115.9 17.468
110.9 15.794 116.0 17.503
111.0 15.827 116.1 17.537
111.1 15.859 116.2 17.571
111.2 15.891 116.3 17.606
111.3 15.924 116.4 17.640
111.4 15.956 116.5 17.674
111.5 15.989 116.6 17.708
111.6 16.021 116.7 17.743
111.7 16.054 116.8 17.777
111.8 16.087 116.9 17.812
111.9 16.119 117.0 17.846
112.0 16.152 117.1 17.881
112.1 16.185 117.2 17.915
112.2 16.218 117.3 17.949
112.3 16.251 117.4 17.984
112.4 16.284 117.5 18.018
112.5 16.317 117.6 18.053
112.6 16.350 117.7 18.087
112.7 16.384 117.8 18.122
112.8 16.417 117.9 18.156
112.9 16.451 118.0 18.190
113.0 16.484 118.1 18.225
113.1 16.517 118.2 18.259
113.2 16.551 118.3 18.294
113.3 16.584 118.4 18.328
113.4 16.618 118.5 18.363
113.5 16.652 118.6 18.397
Sahel Resilience Learning (SAREL)—RISE Midline Quantitative Survey Report
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Height SD2neg Height SD2neg Height SD2neg
113.6 16.685 118.7 18.432
113.7 16.719 118.8 18.466
113.8 16.753 118.9 18.500
113.9 16.786 119.0 18.534
114.0 16.820 119.1 18.569
114.1 16.854 119.2 18.603
114.2 16.888 119.3 18.638
114.3 16.922 119.4 18.672
114.4 16.956 119.5 18.706
114.5 16.990 119.6 18.741
114.6 17.024 119.7 18.775
114.7 17.058 119.8 18.810
114.8 17.092 119.9 18.844
114.9 17.126 120.0 18.878
115.0 17.160
115.1 17.194
115.2 17.229
115.3 17.263
Note: data from http://www.who.int/childgrowth/standards/weight_for_height/en/
Sahel Resilience Learning (SAREL)—RISE Midline Quantitative Survey Report
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WHO standard for “stunted”: length/height in centimeters, 2 standard deviations below child 
growth median, by age and sex.
GIRLS BOYS
Months SD2neg Months SD2neg Months SD2neg Months SD2neg
1 49.727 31 84.297 1 50.773 31 85.754
2 53.006 32 84.939 2 54.438 32 86.352
3 55.569 33 85.57 3 57.313 33 86.937
4 57.777 34 86.21 4 59.741 34 87.532
5 59.585 35 86.819 5 61.669 35 88.096
6 61.217 36 87.439 6 63.362 36 88.675
7 62.654 37 88.031 7 64.82 37 89.226
8 64.042 38 88.634 8 66.21 38 89.787
9 65.315 39 89.209 9 67.485 39 90.324
10 66.532 40 89.777 10 68.696 40 90.855
11 67.737 41 90.355 11 69.887 41 91.399
12 68.893 42 90.906 12 71.022 42 91.916
13 69.97 43 91.469 13 72.078 43 92.444
14 71.009 44 92.006 14 73.091 44 92.946
15 72.046 45 92.553 15 74.1 45 93.46
16 73.017 46 93.076 16 75.042 46 93.952
17 73.959 47 93.607 17 75.955 47 94.456
18 74.904 48 94.116 18 76.868 48 94.939
Sahel Resilience Learning (SAREL)—RISE Midline Quantitative Survey Report
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GIRLS BOYS
19 75.792 49 94.621 19 77.722 49 95.418
20 76.685 50 95.135 20 78.579 50 95.914
21 77.527 51 95.628 21 79.383 51 96.389
22 78.372 52 96.131 22 80.19 52 96.88
23 79.171 53 96.615 23 80.949 53 97.354
24 79.276 54 97.11 24 81.017 54 97.843
25 80.035 55 97.582 25 81.742 55 98.314
26 80.777 56 98.065 26 82.446 56 98.801
27 81.525 57 98.529 27 83.154 57 99.272
28 82.232 58 98.989 28 83.82 58 99.739
29 82.945 59 99.457 29 84.49 59 100.225
30 83.616 60 99.908 30 85.12 60 100.692
Note: data from http://www.who.int/childgrowth/standards/height_for_age/en/
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WHO standard for Underweight: weight in kilograms, 2 standard deviations below child 
growth median, by age and sex.
GIRLS BOYS
Months SD2neg Months SD2neg Months SD2neg Months SD2neg
1 3.148 31 10.118 1 3.376 31 10.654
2 3.944 32 10.257 2 4.322 32 10.781
3 4.531 33 10.395 3 5.012 33 10.906
4 5.017 34 10.535 4 5.565 34 11.033
5 5.402 35 10.669 5 5.994 35 11.155
6 5.733 36 10.806 6 6.357 36 11.28
7 6.008 37 10.938 7 6.653 37 11.4
8 6.257 38 11.073 8 6.917 38 11.524
9 6.473 39 11.202 9 7.145 39 11.643
10 6.671 40 11.33 10 7.354 40 11.762
11 6.863 41 11.46 11 7.556 41 11.885
12 7.047 42 11.585 12 7.747 42 12.004
13 7.22 43 11.712 13 7.924 43 12.125
14 7.389 44 11.834 14 8.095 44 12.243
15 7.562 45 11.96 15 8.267 45 12.363
16 7.728 46 12.08 16 8.431 46 12.479
17 7.892 47 12.204 17 8.591 47 12.598
18 8.061 48 12.323 18 8.753 48 12.713
Sahel Resilience Learning (SAREL)—RISE Midline Quantitative Survey Report
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GIRLS BOYS
19 8.223 49 12.442 19 8.908 49 12.827
20 8.389 50 12.564 20 9.066 50 12.944
21 8.549 51 12.682 21 9.218 51 13.056
22 8.714 52 12.805 22 9.373 52 13.172
23 8.874 53 12.923 23 9.522 53 13.285
24 9.039 54 13.044 24 9.675 54 13.4
25 9.197 55 13.161 25 9.821 55 13.511
26 9.355 56 13.281 26 9.964 56 13.625
27 9.516 57 13.397 27 10.11 57 13.736
28 9.669 58 13.511 28 10.248 58 13.845
29 9.824 59 13.629 29 10.388 59 13.958
30 9.97 60 13.742 30 10.52 60 14.067
Note: data from http://www.who.int/childgrowth/standards/weight_for_age/en/
Sahel Resilience Learning (SAREL)—RISE Midline Quantitative Survey Report
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Appendix C. Baseline Survey Questionnaires
C.1: Household Questionnaire
C.2: Gender Questionnaire 
C.3: Household Food Consumption Survey & Child Anthropometry Questionnaire
C.4: Village Questionnaire
Sahel Resilience Learning (SAREL)—RISE Midline Quantitative Survey Report
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C1. Household Questionnaire
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Sahel Resilience Learning (SAREL)—RISE Midline Quantitative Survey Report
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INFORMED CONSENT SIGNATURE PAGE
Thank you for the opportunity to speak with you. We are from SAREL, a USAID-funded project in partnership with the Governments of Niger and Burkina Faso. 
We are conducting a survey to learn about agriculture, food security, food consumption, nutrition and wellbeing of households in this area. Your household has 
been selected to participate in an interview on topics such as your dwelling characteristics, household expenditures and assets, household food consumption 
and nutrition of children. The survey includes questions about the household generally, and questions about individuals within your household, if applicable. 
These questions in total will take approximately one and half hours (1h30) to complete and your participation is entirely voluntary. If you agree to participate, 
you can choose to stop at any time or to skip any questions you do not want to answer. Your answers will be completely confidential; we will not share information 
that identifies you with anyone. 
Do you have any questions about the survey or what I have just said? If in the future you have any questions regarding the survey and the interview, or concerns 
or complaints we welcome you to contact the USAID/SAREL Project (Stephen Reid | Chief of Party, Sahel Resilience Learning (SAREL) Project / 
Tel.: 227-9663-0291 |227-9025-7197 / sreid@sarelproject.com ). We will leave one copy of this form for you so that you will have record of this contact information 
and about the study.
Name
Consent to participate in 
survey (Insert code) Signature or mark
YES=1 NO=2
1 |___|
2 |___|
3 |___|
4 |___|
5 |___|
6 |___|
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MODULE 2: HOUSEHOLD ROSTER AND DEMOGRAPHICS
QUESTION WORDING AND NUMBER
200 201 202 203 204 205 206 207 208 209 210 211 212 ID
Household member name
(Start with household head)
[name]’s 
Age in full
years 
Put "00" for 
members 
under 1 and 
"80" for 
members over
80
[name]’s 
Sex
1 Male
2 Female
[name]’s 
Relationshi
p to 
household 
head
Enter 
codes 
from list
[name]'s 
ethnic 
group
Enter 
from list
For ages 5 years and above For ages 12 years and 
above
Identification of children between 0 
and 59 months and caregivers 
(mothers, grandmothers, etc.) Maximum
education 
completed
by [name]
Enter 
from 
list
Can [name] 
read or write 
a national 
language?
1 Yes
2 No
Can [name] read or 
write a foreign 
language?
1. Yes-French
2. Yes-English
3. Yes-Arabic (BF)
4. Yes-Other 
5. No
[name]’s 
Marital 
status
Enter from 
list
[name]’s 
Primary 
Occupatio
n
Enter 
from 
list
Write down the 
numbers of 
children under 
5
Write down 
[name]'s 
caregiver's 
number
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QUESTION WORDING AND NUMBER
200 201 202 203 204 205 206 207 208 209 210 211 212 ID
Household member name
(Start with household head)
[name]’s 
Age in full
years 
Put "00" for 
members 
under 1 and 
"80" for 
members over
80
[name]’s 
Sex
1 Male
2 Female
[name]’s 
Relationshi
p to 
household 
head
Enter 
codes 
from list
[name]'s 
ethnic 
group
Enter 
from list
For ages 5 years and above For ages 12 years and 
above
Identification of children between 0 
and 59 months and caregivers 
(mothers, grandmothers, etc.) Maximum
education 
completed
by [name]
Enter 
from 
list
Can [name] 
read or write 
a national 
language?
1 Yes
2 No
Can [name] read or 
write a foreign 
language?
1. Yes-French
2. Yes-English
3. Yes-Arabic (BF)
4. Yes-Other 
5. No
[name]’s 
Marital 
status
Enter from 
list
[name]’s 
Primary 
Occupatio
n
Enter 
from 
list
Write down the 
numbers of 
children under 
5
Write down 
[name]'s 
caregiver's 
number
|
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Sahel Resilience Learning (SAREL)—RISE Midline Quantitative Survey Report
October 2017 (Approved, Feb. 2018) 190
QUESTION WORDING AND NUMBER
200 201 202 203 204 205 206 207 208 209 210 211 212 ID
Household member name
(Start with household head)
[name]’s 
Age in full
years 
Put "00" for 
members 
under 1 and 
"80" for 
members over
80
[name]’s 
Sex
1 Male
2 Female
[name]’s 
Relationshi
p to 
household 
head
Enter 
codes 
from list
[name]'s 
ethnic 
group
Enter 
from list
For ages 5 years and above For ages 12 years and 
above
Identification of children between 0 
and 59 months and caregivers 
(mothers, grandmothers, etc.) Maximum
education 
completed
by [name]
Enter 
from 
list
Can [name] 
read or write 
a national 
language?
1 Yes
2 No
Can [name] read or 
write a foreign 
language?
1. Yes-French
2. Yes-English
3. Yes-Arabic (BF)
4. Yes-Other 
5. No
[name]’s 
Marital 
status
Enter from 
list
[name]’s 
Primary 
Occupatio
n
Enter 
from 
list
Write down the 
numbers of 
children under 
5
Write down 
[name]'s 
caregiver's 
number
|
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Sahel Resilience Learning (SAREL)—RISE Midline Quantitative Survey Report
October 2017 (Approved, Feb. 2018) 191
QUESTION WORDING AND NUMBER
200 201 202 203 204 205 206 207 208 209 210 211 212 ID
Household member name
(Start with household head)
[name]’s 
Age in full
years 
Put "00" for 
members 
under 1 and 
"80" for 
members over
80
[name]’s 
Sex
1 Male
2 Female
[name]’s 
Relationshi
p to 
household 
head
Enter 
codes 
from list
[name]'s 
ethnic 
group
Enter 
from list
For ages 5 years and above For ages 12 years and 
above
Identification of children between 0 
and 59 months and caregivers 
(mothers, grandmothers, etc.) Maximum
education 
completed
by [name]
Enter 
from 
list
Can [name] 
read or write 
a national 
language?
1 Yes
2 No
Can [name] read or 
write a foreign 
language?
1. Yes-French
2. Yes-English
3. Yes-Arabic (BF)
4. Yes-Other 
5. No
[name]’s 
Marital 
status
Enter from 
list
[name]’s 
Primary 
Occupatio
n
Enter 
from 
list
Write down the 
numbers of 
children under 
5
Write down 
[name]'s 
caregiver's 
number
|__|__
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Sahel Resilience Learning (SAREL)—RISE Midline Quantitative Survey Report
October 2017 (Approved, Feb. 2018) 192
QUESTION WORDING AND NUMBER
200 201 202 203 204 205 206 207 208 209 210 211 212 ID
Household member name
(Start with household head)
[name]’s 
Age in full
years 
Put "00" for 
members 
under 1 and 
"80" for 
members over
80
[name]’s 
Sex
1 Male
2 Female
[name]’s 
Relationshi
p to 
household 
head
Enter 
codes 
from list
[name]'s 
ethnic 
group
Enter 
from list
For ages 5 years and above For ages 12 years and 
above
Identification of children between 0 
and 59 months and caregivers 
(mothers, grandmothers, etc.) Maximum
education 
completed
by [name]
Enter 
from 
list
Can [name] 
read or write 
a national 
language?
1 Yes
2 No
Can [name] read or 
write a foreign 
language?
1. Yes-French
2. Yes-English
3. Yes-Arabic (BF)
4. Yes-Other 
5. No
[name]’s 
Marital 
status
Enter from 
list
[name]’s 
Primary 
Occupatio
n
Enter 
from 
list
Write down the 
numbers of 
children under 
5
Write down 
[name]'s 
caregiver's 
number
|__|__
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Sahel Resilience Learning (SAREL)—RISE Midline Quantitative Survey Report
October 2017 (Approved, Feb. 2018) 193
QUESTION WORDING AND NUMBER
200 201 202 203 204 205 206 207 208 209 210 211 212 ID
Household member name
(Start with household head)
[name]’s 
Age in full
years 
Put "00" for 
members 
under 1 and 
"80" for 
members over
80
[name]’s 
Sex
1 Male
2 Female
[name]’s 
Relationshi
p to 
household 
head
Enter 
codes 
from list
[name]'s 
ethnic 
group
Enter 
from list
For ages 5 years and above For ages 12 years and 
above
Identification of children between 0 
and 59 months and caregivers 
(mothers, grandmothers, etc.) Maximum
education 
completed
by [name]
Enter 
from 
list
Can [name] 
read or write 
a national 
language?
1 Yes
2 No
Can [name] read or 
write a foreign 
language?
1. Yes-French
2. Yes-English
3. Yes-Arabic (BF)
4. Yes-Other 
5. No
[name]’s 
Marital 
status
Enter from 
list
[name]’s 
Primary 
Occupatio
n
Enter 
from 
list
Write down the 
numbers of 
children under 
5
Write down 
[name]'s 
caregiver's 
number
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| |__|__| |__| |__|__| |__|__| |__|__| |__| |__| |__| |__| |__|__| |__|__|
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Sahel Resilience Learning (SAREL)—RISE Midline Quantitative Survey Report
October 2017 (Approved, Feb. 2018) 194
QUESTION WORDING AND NUMBER
200 201 202 203 204 205 206 207 208 209 210 211 212 ID
Household member name
(Start with household head)
[name]’s 
Age in full
years 
Put "00" for 
members 
under 1 and 
"80" for 
members over
80
[name]’s 
Sex
1 Male
2 Female
[name]’s 
Relationshi
p to 
household 
head
Enter 
codes 
from list
[name]'s 
ethnic 
group
Enter 
from list
For ages 5 years and above For ages 12 years and 
above
Identification of children between 0 
and 59 months and caregivers 
(mothers, grandmothers, etc.) Maximum
education 
completed
by [name]
Enter 
from 
list
Can [name] 
read or write 
a national 
language?
1 Yes
2 No
Can [name] read or 
write a foreign 
language?
1. Yes-French
2. Yes-English
3. Yes-Arabic (BF)
4. Yes-Other 
5. No
[name]’s 
Marital 
status
Enter from 
list
[name]’s 
Primary 
Occupatio
n
Enter 
from 
list
Write down the 
numbers of 
children under 
5
Write down 
[name]'s 
caregiver's 
number
|__|__
| |__|__| |__| |__|__| |__|__| |__|__| |__| |__| |__| |__| |__|__| |__|__|
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Sahel Resilience Learning (SAREL)—RISE Midline Quantitative Survey Report
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HOUSEHOLD MEMBER ROSTER AND DEMOGRAPHICS CODE LIST 
Cod Question 204: Relationship Code Question 205: Ethnic Code Question 206: Education Code Question: 209 Marital status
01 Household Head Burkina Faso Ethnic 
Groups 01 Never Attended 1 Never married
02 Spouse (wife/husband) 11 Mossi 02 Pre-school 2 Married, monogamous
03 Own son/daughter 12 Fulfuldé/Peul 03 CP1/CI (first year of primary school) 3 Married, polygamous
04 Child from spouse's other 
marriage 13 Gourmantché 04 CP2/CP (second year of primary school) 4 Cohabitation
05 Step-son/step-daughter 14 Songhaï/Sonraï 05 CE1 (third year of primary school) 5 Divorced/separated
06 Grandson/granddaughter 15 Touareg 06 CE2 (fourth year of primary school) 6 Widow(er)
07 Brother/sister 16 Bella 07 CM1 (fifth year of primary school)
08 (Biological) parent father/mother 17 Other ethnic groups 08 CM2 (sixth year of primary school) Code
s Question 210: Main Activity
09 Step-father/step-mother 09 6ème (first year of secondary school) 1 Agriculture
10 Niece/nephew Code
s Niger Ethnic Groups 10 5ème (second year of secondary school) 2 Livestock
11 Co-wife 21 Hausa 11 4ème (third year of secondary school) 3 Trade
12 House Help 22 Djerma 12 3ème (fourth year of secondary school) 4 N/A
13 Another household member 23 Fulfuldé/Peul 13 2nde (fifth year of secondary school) 5 Other
24 Gourmantché 14 1ère (sixth year of secondary school) 8 Unaccounted for
25 Touareg 15 Terminale (seventh year of secondary 
school)
26 Bella 16 Higher
27 Songhaï/Sonraï 17 Vocational before CEP/CFEPD
28 Other ethnic groups 18 Vocational post-CEP/CFEPD
19 Vocational sec. post-BEPC (Junior 
Secondary School Diploma)
Sahel Resilience Learning (SAREL)—RISE Midline Quantitative Survey Report
October 2017 (Approved, Feb. 2018) 196
MODULE 3: SHOCKS (list shocks)
300: During the past five (5) years did your household experience any [shock]?
Yes .................1 (If « yes », skip to 301)
No ...................1 (If « no », skip to module 4)
DK...................8 (If « DK », skip to module 4)
Refused.........9 (If « Refused », skip to module 4)
|___|
SHOCK LIST
QUESTION WORDING AND NUMBER
301 302 303 304 305
List the various 
shocks and 
circle the 
codes of the 
shocks 
experienced 
by the 
household
How many times 
did you 
experience 
[shock] in the last 
five years?
Among the shocks 
experienced in the last 5 
years, which have you 
experienced in the last 12 
months?
Yes = 1
No = 2 (skip to next shock)
What was the severity of 
the impact of this/these 
shock(s) experienced by 
your household in the last 
12 months on your income 
and food consumption?
1. None
2. Slight impact
3. Moderate impact
4. Strong impact
5. Worst ever happened
8. DK
To what extent were you and 
your household able to recover 
after this/these shock(s)
experienced in the last 12 
months?
1. Did not recover
2. Recovered some, but worse 
off than before [event]
3. Recovered to same level as 
before [event]
4. Recovered and better off
5. Not affected by [event]
8. DK
Climatic Shocks Codes
Excessive rains 01 |___|___| |___| |___| |___|
Sahel Resilience Learning (SAREL)—RISE Midline Quantitative Survey Report
October 2017 (Approved, Feb. 2018) 197
SHOCK LIST
QUESTION WORDING AND NUMBER
301 302 303 304 305
List the various 
shocks and 
circle the 
codes of the 
shocks 
experienced 
by the 
household
How many times 
did you 
experience 
[shock] in the last 
five years?
Among the shocks 
experienced in the last 5 
years, which have you 
experienced in the last 12 
months?
Yes = 1
No = 2 (skip to next shock)
What was the severity of 
the impact of this/these 
shock(s) experienced by 
your household in the last 
12 months on your income 
and food consumption?
1. None
2. Slight impact
3. Moderate impact
4. Strong impact
5. Worst ever happened
8. DK
To what extent were you and 
your household able to recover 
after this/these shock(s)
experienced in the last 12 
months?
1. Did not recover
2. Recovered some, but worse 
off than before [event]
3. Recovered to same level as 
before [event]
4. Recovered and better off
5. Not affected by [event]
8. DK
Too little rain/drought 02 |___|___| |___| |___| |___|
Massive insect invasion 03 |___|___| |___| |___| |___|
Epizootic (animal disease outbreak) 04 |___|___| |___| |___| |___|
Bush fires 05 |___|___| |___| |___| |___|
Conflict shocks 
Land conflicts 06 |___|___| |___| |___| |___|
Sahel Resilience Learning (SAREL)—RISE Midline Quantitative Survey Report
October 2017 (Approved, Feb. 2018) 198
SHOCK LIST
QUESTION WORDING AND NUMBER
301 302 303 304 305
List the various 
shocks and 
circle the 
codes of the 
shocks 
experienced 
by the 
household
How many times 
did you 
experience 
[shock] in the last 
five years?
Among the shocks 
experienced in the last 5 
years, which have you 
experienced in the last 12 
months?
Yes = 1
No = 2 (skip to next shock)
What was the severity of 
the impact of this/these 
shock(s) experienced by 
your household in the last 
12 months on your income 
and food consumption?
1. None
2. Slight impact
3. Moderate impact
4. Strong impact
5. Worst ever happened
8. DK
To what extent were you and 
your household able to recover 
after this/these shock(s)
experienced in the last 12 
months?
1. Did not recover
2. Recovered some, but worse 
off than before [event]
3. Recovered to same level as 
before [event]
4. Recovered and better off
5. Not affected by [event]
8. DK
Conflicts between farmers and herders 07 |___|___| |___| |___| |___|
Conflict/violence involving entire 
communities/villages 08 |___|___| |___| |___| |___|
Theft of assets/holdups (animals, crops, 
etc.) 09 |___|___| |___| |___| |___|
Socioeconomic shocks 
Sharp food price increase 10 |___|___| |___| |___| |___|
Sahel Resilience Learning (SAREL)—RISE Midline Quantitative Survey Report
October 2017 (Approved, Feb. 2018) 199
SHOCK LIST
QUESTION WORDING AND NUMBER
301 302 303 304 305
List the various 
shocks and 
circle the 
codes of the 
shocks 
experienced 
by the 
household
How many times 
did you 
experience 
[shock] in the last 
five years?
Among the shocks 
experienced in the last 5 
years, which have you 
experienced in the last 12 
months?
Yes = 1
No = 2 (skip to next shock)
What was the severity of 
the impact of this/these 
shock(s) experienced by 
your household in the last 
12 months on your income 
and food consumption?
1. None
2. Slight impact
3. Moderate impact
4. Strong impact
5. Worst ever happened
8. DK
To what extent were you and 
your household able to recover 
after this/these shock(s)
experienced in the last 12 
months?
1. Did not recover
2. Recovered some, but worse 
off than before [event]
3. Recovered to same level as 
before [event]
4. Recovered and better off
5. Not affected by [event]
8. DK
Unavailability of agricultural or livestock 
inputs 11 |___|___| |___| |___| |___|
Drop in agricultural or livestock product 
demand 12 |___|___| |___| |___| |___|
Disease/exceptional health-related expense 13 |___|___| |___| |___| |___|
Debt repayment 14 |___|___| |___| |___| |___|
Increase in price of agricultural or livestock 
inputs 15 |___|___| |___| |___| |___|
Sahel Resilience Learning (SAREL)—RISE Midline Quantitative Survey Report
October 2017 (Approved, Feb. 2018) 200
SHOCK LIST
QUESTION WORDING AND NUMBER
301 302 303 304 305
List the various 
shocks and 
circle the 
codes of the 
shocks 
experienced 
by the 
household
How many times 
did you 
experience 
[shock] in the last 
five years?
Among the shocks 
experienced in the last 5 
years, which have you 
experienced in the last 12 
months?
Yes = 1
No = 2 (skip to next shock)
What was the severity of 
the impact of this/these 
shock(s) experienced by 
your household in the last 
12 months on your income 
and food consumption?
1. None
2. Slight impact
3. Moderate impact
4. Strong impact
5. Worst ever happened
8. DK
To what extent were you and 
your household able to recover 
after this/these shock(s)
experienced in the last 12 
months?
1. Did not recover
2. Recovered some, but worse 
off than before [event]
3. Recovered to same level as 
before [event]
4. Recovered and better off
5. Not affected by [event]
8. DK
Drop in price of agricultural or livestock 
products 16 |___|___| |___| |___| |___|
Job loss by household member 17 |___|___| |___| |___| |___|
Long-term unemployment 18 |___|___| |___| |___| |___|
Abrupt end of assistance/regular support 
from outside the household 19 |___|___| |___| |___| |___|
Sudden increase in household size 
(including birth: triplets etc.) 20 |___|___| |___| |___| |___|
Sahel Resilience Learning (SAREL)—RISE Midline Quantitative Survey Report
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SHOCK LIST
QUESTION WORDING AND NUMBER
301 302 303 304 305
List the various 
shocks and 
circle the 
codes of the 
shocks 
experienced 
by the 
household
How many times 
did you 
experience 
[shock] in the last 
five years?
Among the shocks 
experienced in the last 5 
years, which have you 
experienced in the last 12 
months?
Yes = 1
No = 2 (skip to next shock)
What was the severity of 
the impact of this/these 
shock(s) experienced by 
your household in the last 
12 months on your income 
and food consumption?
1. None
2. Slight impact
3. Moderate impact
4. Strong impact
5. Worst ever happened
8. DK
To what extent were you and 
your household able to recover 
after this/these shock(s)
experienced in the last 12 
months?
1. Did not recover
2. Recovered some, but worse 
off than before [event]
3. Recovered to same level as 
before [event]
4. Recovered and better off
5. Not affected by [event]
8. DK
Anthropogenic Shocks
Fire (house,...) 21 |___|___| |___| |___| |___|
Psychosocial Shocks
Death of household member 22 |___|___| |___| |___| |___|
Emigration of household member 23 |___|___| |___| |___| |___|
Serious illness of household member 24 |___|___| |___| |___| |___|
Sahel Resilience Learning (SAREL)—RISE Midline Quantitative Survey Report
October 2017 (Approved, Feb. 2018) 202
SHOCK LIST
QUESTION WORDING AND NUMBER
301 302 303 304 305
List the various 
shocks and 
circle the 
codes of the 
shocks 
experienced 
by the 
household
How many times 
did you 
experience 
[shock] in the last 
five years?
Among the shocks 
experienced in the last 5 
years, which have you 
experienced in the last 12 
months?
Yes = 1
No = 2 (skip to next shock)
What was the severity of 
the impact of this/these 
shock(s) experienced by 
your household in the last 
12 months on your income 
and food consumption?
1. None
2. Slight impact
3. Moderate impact
4. Strong impact
5. Worst ever happened
8. DK
To what extent were you and 
your household able to recover 
after this/these shock(s)
experienced in the last 12 
months?
1. Did not recover
2. Recovered some, but worse 
off than before [event]
3. Recovered to same level as 
before [event]
4. Recovered and better off
5. Not affected by [event]
8. DK
Other Shocks
Forced repatriation 25 |___|___| |___| |___| |___|
Household dislocation 26 |___|___| |___| |___| |___|
Sahel Resilience Learning (SAREL)—RISE Midline Quantitative Survey Report
October 2017 (Approved, Feb. 2018) 203
306. How did you cope with the shock(s) you experienced in the last 12 months? 
N° REMEDIES TO SHOCKS
YES=1 NO=2
N° REMEDIES TO SHOCKS YES=
1 NO=2
LIVESTOCK AND LAND HOLDINGS COPING STRATEGIES TO GET MORE FOOD OR MONEY
01 Send livestock in search of pasture |___| 11 Take up new wage labor |___|
02 Sell livestock |___| 12 Sell household items (e.g., radio, bed) |___|
03 Slaughter livestock |___| 13 Sell productive assets (e.g., plow, water pump) |___|
04 Lease out land |___| 14 Take out a loan from an NGO |___|
MIGRATION 15 Take out a loan from a bank |___|
05 Migrate (only some family members) |___| 16 Take out a loan from a money lender |___|
06 Migrate (the whole family) |___| 17 Take out a loan from friends or relatives |___|
07 Send children or an adult to stay with relatives |___| 18 Send children to work for money (e.g., domestic service) |___|
COPING STRATEGIES TO REDUCE CURRENT 
EXPENDITURE 19 Receive money or food from family members |___|
08 Take children out of school |___| 20 Receive food aid from the government |___|
09 Move to less expensive housing |___| 21 Receive food aid from an NGO |___|
10 Limit portion size at mealtimes |___| 22 Participate in food-for-work or cash-for-work |___|
23 Use money from savings |___|
24 Get money from a relative that migrated (remittances) |___|
Sahel Resilience Learning (SAREL)—RISE Midline Quantitative Survey Report
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25 Eating of lean season food: Anza; etc. |___|
26 Excavation of termite mounds |___|
27 Hunting, gathering |___|
28 Consume seed stock held for next season |___|
29 Reduce number of meals eaten in a day |___|
30 Other (specify) |___|
Sahel Resilience Learning (SAREL)—RISE Midline Quantitative Survey Report
October 2017 (Approved, Feb. 2018) 205
MODULE 4. HOUSEHOLD HOUSING CHARACTERISTICS
N° QUESTION WORDING • ANSWERS • Typing
400 What is the occupancy status of dwelling(s)?
• 1. Owner
• 2. Leased property
• 3. Rent
• 4. Lodging provided by the employer
• 5. Lodging provided free of charge by a third party
• 6. Other (specify)_________________________________
|___|
401 Type of dwelling occupied by the head of household • 1. Single housing
• 2. Multi-dwelling building (no block)
• 3. Hut
• 4. Villa
• 5. Apartment Building
• 6. Other (specify)_________________________________
|___|
402 What materials have been used to construct the roof of the dwelling? • 1. Sheet metal
• 2. Cement
• 3. Straw or thatch
• 4. Wood and mud (earth)
• 5. Plastic sheeting
• 6. Other (specify)_________________________________
|___|
403 What materials have been used to construct the floor of the dwelling? • 1. Dirt
• 2. Cow dung
• 3. Concrete/stone/cement
|___|
Sahel Resilience Learning (SAREL)—RISE Midline Quantitative Survey Report
October 2017 (Approved, Feb. 2018) 206
N° QUESTION WORDING • ANSWERS • Typing
• 4. Sand
• 5. Other (specify)_________________________________
404 What materials have been used to construct the walls of the dwelling? • 1. Cement/concrete
• 2. Fired brick
• 3. Clay/clay brick
• 4. Wood/bamboo
• 5. Stones
• 6. Sheet metal
• 7. Straw
• 8. Other (specify)_________________________________
|___|
405 How many rooms does the household have? (Number of rooms) |___|___
|
406 What is the main type of latrine used by your household? • 01. Pit flush toilet
• 02. Flush toilet connected to a sealed septic system
• 03. Flush toilet connected to a sewage system
• 04. Pit toilet with slab
• 05. Composting toilet
• 06. Ventilated improved pit
• 07. Flush toilet with no connection to sewage system
• 08. Pit toilet with no slab or connected to open septic system
• 09. Bucket latrine
• 10. Hanging toilet/latrine
• 11. In the open
|___|__
_|
407 What is the main source of drinking water supply for your household? • 01. Surface water (dam, river, stream, lake, pond, creek, irrigation 
channel, canal) 
• 02. Protected well
• 03. Uncovered, concrete-cased well
• |__
_|___|
Sahel Resilience Learning (SAREL)—RISE Midline Quantitative Survey Report
October 2017 (Approved, Feb. 2018) 207
N° QUESTION WORDING • ANSWERS • Typing
• 04. Traditional well
• 05. Boreholes/tube-wells
• 06. Public fountain/public tap
• 07. Own indoor tap
• 08. Shared outdoor tap
• 09. Cart with small tanks/drums
• 10. Tank trucks
• 11. Bottled water
• 12. Other (specify)_________________________________
408 Do you usually do anything to make the water you drink healthier? • 1. Yes 
• 2. No [if « no », skip to question 410] |___|
409
What do you do to make the water you drink healthier?
• 1. Boil it
• 2. Add bleach/chlorine
• 3. Filter with cloth
• 4. Use a water filter
• 5. Solar disinfection
• 6. Let the water stand
• 7. Add Aquatabs
• 8. Other (specify)_________________________________
|___|
410 How long does it take to get water for domestic use (round trip 
including waiting time for fetching water)? If the water source is in the 
compound, enter 000 as time value. If water is delivered to the
home, enter the Not Applicable code 999
Duration in minutes |___|__
_|___|
411 Please, show me where the household members wash their hands 
most often? 
• 1. Observation
• 2. No observation in the household/compound/plot
• 3. No observation because not allowed to see
• 4. No observation for other reasons
•
• |___|
412 Section dedicated to observations
Check the presence of water at the specified hand washing location
• 1. There is water
• 2. There is no water |___|
Sahel Resilience Learning (SAREL)—RISE Midline Quantitative Survey Report
October 2017 (Approved, Feb. 2018) 208
N° QUESTION WORDING • ANSWERS • Typing
413 Section dedicated to observations
Check the presence of soap, detergent, or other cleaning agent
Also ask if the soap/detergent is kept in another room in the house
• 1. Soap or detergent
• 2. Solid, liquid, powder, paste
• 3. Ash, mud, sand
• 4. None
• 5. Other (specify)_________________________________
|___|
414 When do your household members wash their hands?
Several answers possible (circle the codes corresponding to all 
answers provided by the respondent and enter responses codes 
in the spaces)
Do not read the answers. 
01. Before eating |___|___|
02. After eating |___|___|
03. Before praying |___|___|
04. Before breastfeeding or feeding a child |___|___|
05. Before cooking food |___|___|
06. After using the toilet/latrine |___|___|
07. After cleaning or changing diapers of a child who 
has defecated
|___|___|
08. When hands are dirty |___|___|
09. After cleaning the toilet or bedpan |___|___|
10. Other (specify) |___|___|
88. DK |___|___|
99. Refused |___|___|
Sahel Resilience Learning (SAREL)—RISE Midline Quantitative Survey Report
October 2017 (Approved, Feb. 2018) 209
MODULE 5. ASSETS (EXCLUDING LIVESTOCK)
CONSUMPTION/PRODUCTIO
N ASSETS
QUESTION WORDING AND NUMBER
500 501 502 503 504 505 505a 505b 505c
Does your 
household 
currently 
own 
(name of 
asset)? 
1 = Yes
2 = No 
Number 
owned 
now
Number 
owned 
a year 
ago
Number 
owned 
two 
years 
ago
Have you 
purchased
any of these 
[ITEMS] in 
the last 12 
months?
 Yes = 1
 No = 2 
(skip to 
Q505a)
For purchased 
items, how much 
did you pay in 
total for these 
[ITEMS] in the 
last 12 months? 
(CFA F)
8 = DK 
9 = Refused
Did you acquire 
any of these 
[ITEMS] free of 
charge in the last 
12 months?
Yes = 1
No = 2 (skip to 
Q505c)
If you wanted to sell 
(types of asset) 
acquired free of charge 
over the last 12 months 
today, on average how 
much would you 
receive from the sale? 
(FCFA)
If you wanted to sell 
your old [types of asset] 
today, excluding those 
that you acquired 
(purchased and/or 
received free of charge) 
in the last 12 months, 
on average how much 
would you receive from 
the sale? (FCFA)
Cod
e
1 = CONSUMPTION 
ASSETS
101 Improved 
charcoal/wood stove 
|___| |___|___| |___|___| |___|___| |___| |__|__|__|__|__|__|
__|__|__|
|__|__|__|__|__|__| |__|__|__|__|__|__| |__|__|__|__|__|__|
102 Kerosene stove |___| |___|___| |___|___| |___|___| |___| |__|__|__|__|__|__|
__|__|__|
|__|__|__|__|__|__| |__|__|__|__|__|__| |__|__|__|__|__|__|
103 Gas stove |___| |___|___| |___|___| |___|___| |___| |__|__|__|__|__|__|
__|__|__|
|__|__|__|__|__|__| |__|__|__|__|__|__| |__|__|__|__|__|__|
104 Chairs |___| |___|___| |___|___| |___|___| |___| |__|__|__|__|__|__|
__|__|__|
|__|__|__|__|__|__| |__|__|__|__|__|__| |__|__|__|__|__|__|
105 Blanket/sakala |___| |___|___| |___|___| |___|___| |___| |__|__|__|__|__|__|
__|__|__|
|__|__|__|__|__|__| |__|__|__|__|__|__| |__|__|__|__|__|__|
106 Iron |___| |___|___| |___|___| |___|___| |___| |__|__|__|__|__|__|
__|__|__|
|__|__|__|__|__|__| |__|__|__|__|__|__| |__|__|__|__|__|__|
107 Sofa/armchair |___| |___|___| |___|___| |___|___| |___| |__|__|__|__|__|__|
__|__|__|
|__|__|__|__|__|__| |__|__|__|__|__|__| |__|__|__|__|__|__|
Sahel Resilience Learning (SAREL)—RISE Midline Quantitative Survey Report
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CONSUMPTION/PRODUCTIO
N ASSETS
QUESTION WORDING AND NUMBER
500 501 502 503 504 505 505a 505b 505c
Does your 
household 
currently 
own 
(name of 
asset)? 
1 = Yes
2 = No 
Number 
owned 
now
Number 
owned 
a year 
ago
Number 
owned 
two 
years 
ago
Have you 
purchased
any of these 
[ITEMS] in 
the last 12 
months?
 Yes = 1
 No = 2 
(skip to 
Q505a)
For purchased 
items, how much 
did you pay in 
total for these 
[ITEMS] in the 
last 12 months? 
(CFA F)
8 = DK 
9 = Refused
Did you acquire 
any of these 
[ITEMS] free of 
charge in the last 
12 months?
Yes = 1
No = 2 (skip to 
Q505c)
If you wanted to sell 
(types of asset) 
acquired free of charge 
over the last 12 months 
today, on average how 
much would you 
receive from the sale? 
(FCFA)
If you wanted to sell 
your old [types of asset] 
today, excluding those 
that you acquired 
(purchased and/or 
received free of charge) 
in the last 12 months, 
on average how much 
would you receive from 
the sale? (FCFA)
108 Mosquito net |___| |___|___| |___|___| |___|___| |___| |__|__|__|__|__|__|
__|__|__|
|__|__|__|__|__|__| |__|__|__|__|__|__| |__|__|__|__|__|__|
109 Wooden bed |___| |___|___| |___|___| |___|___| |___| |__|__|__|__|__|__|
__|__|__|
|__|__|__|__|__|__| |__|__|__|__|__|__| |__|__|__|__|__|__|
110 Metal bed |___| |___|___| |___|___| |___|___| |___| |__|__|__|__|__|__|
__|__|__|
|__|__|__|__|__|__| |__|__|__|__|__|__| |__|__|__|__|__|__|
111 Telephone set/cellular 
phone
|___| |___|___| |___|___| |___|___| |___| |__|__|__|__|__|__|
__|__|__|
|__|__|__|__|__|__| |__|__|__|__|__|__| |__|__|__|__|__|__|
112 Radio |___| |___|___| |___|___| |___|___| |___| |__|__|__|__|__|_
_|__|__|__|
|__|__|__|__|__|__| |__|__|__|__|__|__| |__|__|__|__|__|__|
113 Tape player |___| |___|___| |___|___| |___|___| |___| |__|__|__|__|__|_
_|__|__|__|
|__|__|__|__|__|__| |__|__|__|__|__|__| |__|__|__|__|__|__|
114 Television |___| |___|___| |___|___| |___|___| |___| |__|__|__|__|__|_
_|__|__|__|
|__|__|__|__|__|__| |__|__|__|__|__|__| |__|__|__|__|__|__|
115 Jewelry, gold |___| |___|___| |___|___| |___|___| |___| |__|__|__|__|__|_
_|__|__|__|
|__|__|__|__|__|__| |__|__|__|__|__|__| |__|__|__|__|__|__|
116 Jewelry, silver |___| |___|___| |___|___| |___|___| |___| |__|__|__|__|__|_
_|__|__|__|
|__|__|__|__|__|__| |__|__|__|__|__|__| |__|__|__|__|__|__|
Sahel Resilience Learning (SAREL)—RISE Midline Quantitative Survey Report
October 2017 (Approved, Feb. 2018) 211
CONSUMPTION/PRODUCTIO
N ASSETS
QUESTION WORDING AND NUMBER
500 501 502 503 504 505 505a 505b 505c
Does your 
household 
currently 
own 
(name of 
asset)? 
1 = Yes
2 = No 
Number 
owned 
now
Number 
owned 
a year 
ago
Number 
owned 
two 
years 
ago
Have you 
purchased
any of these 
[ITEMS] in 
the last 12 
months?
 Yes = 1
 No = 2 
(skip to 
Q505a)
For purchased 
items, how much 
did you pay in 
total for these 
[ITEMS] in the 
last 12 months? 
(CFA F)
8 = DK 
9 = Refused
Did you acquire 
any of these 
[ITEMS] free of 
charge in the last 
12 months?
Yes = 1
No = 2 (skip to 
Q505c)
If you wanted to sell 
(types of asset) 
acquired free of charge 
over the last 12 months 
today, on average how 
much would you 
receive from the sale? 
(FCFA)
If you wanted to sell 
your old [types of asset] 
today, excluding those 
that you acquired 
(purchased and/or 
received free of charge) 
in the last 12 months, 
on average how much 
would you receive from 
the sale? (FCFA)
117 Jewelry, wristwatches |___| |___|___| |___|___| |___|___| |___| |__|__|__|__|__|_
_|__|__|__|
|__|__|__|__|__|__| |__|__|__|__|__|__| |__|__|__|__|__|__|
118 Firearms |___| |___|___| |___|___| |___|___| |___| |__|__|__|__|__|_
_|__|__|__|
|__|__|__|__|__|__| |__|__|__|__|__|__| |__|__|__|__|__|__|
119 Table |___| |___|___| |___|___| |___|___| |___| |__|__|__|__|__|_
_|__|__|__|
|__|__|__|__|__|__| |__|__|__|__|__|__| |__|__|__|__|__|__|
120 Mat |___| |___|___| |___|___| |___|___| |___| |__|__|__|__|__|_
_|__|__|__|
|__|__|__|__|__|__| |__|__|__|__|__|__| |__|__|__|__|__|__|
121 Portable hand-held 
lighting
|___| |___|___| |___|___| |___|___| |___| |__|__|__|__|__|_
_|__|__|__|
|__|__|__|__|__|__| |__|__|__|__|__|__| |__|__|__|__|__|__|
122 Wheelbarrow |___| |___|___| |___|___| |___|___| |___| |__|__|__|__|__|_
_|__|__|__|
|__|__|__|__|__|__| |__|__|__|__|__|__| |__|__|__|__|__|__|
123 Bicycle |___| |___|___| |___|___| |___|___| |___| |__|__|__|__|__|_
_|__|__|__|
|__|__|__|__|__|__| |__|__|__|__|__|__| |__|__|__|__|__|__|
124 Cart (animal drawn) |___| |___|___| |___|___| |___|___| |___| |__|__|__|__|__|_
_|__|__|__|
|__|__|__|__|__|__| |__|__|__|__|__|__| |__|__|__|__|__|__|
125 Pick-up truck |___| |___|___| |___|___| |___|___| |___| |__|__|__|__|__|_
_|__|__|__|
|__|__|__|__|__|__| |__|__|__|__|__|__| |__|__|__|__|__|__|
Sahel Resilience Learning (SAREL)—RISE Midline Quantitative Survey Report
October 2017 (Approved, Feb. 2018) 212
CONSUMPTION/PRODUCTIO
N ASSETS
QUESTION WORDING AND NUMBER
500 501 502 503 504 505 505a 505b 505c
Does your 
household 
currently 
own 
(name of 
asset)? 
1 = Yes
2 = No 
Number 
owned 
now
Number 
owned 
a year 
ago
Number 
owned 
two 
years 
ago
Have you 
purchased
any of these 
[ITEMS] in 
the last 12 
months?
 Yes = 1
 No = 2 
(skip to 
Q505a)
For purchased 
items, how much 
did you pay in 
total for these 
[ITEMS] in the 
last 12 months? 
(CFA F)
8 = DK 
9 = Refused
Did you acquire 
any of these 
[ITEMS] free of 
charge in the last 
12 months?
Yes = 1
No = 2 (skip to 
Q505c)
If you wanted to sell 
(types of asset) 
acquired free of charge 
over the last 12 months 
today, on average how 
much would you 
receive from the sale? 
(FCFA)
If you wanted to sell 
your old [types of asset] 
today, excluding those 
that you acquired 
(purchased and/or 
received free of charge) 
in the last 12 months, 
on average how much 
would you receive from 
the sale? (FCFA)
126 Motorcycles/mopeds |___| |___|___| |___|___| |___|___| |___| |__|__|__|__|__|_
_|__|__|__|
|__|__|__|__|__|__| |__|__|__|__|__|__| |__|__|__|__|__|__|
127 Fans |___| |___|___| |___|___| |___|___| |___| |__|__|__|__|__|_
_|__|__|__|
|__|__|__|__|__|__| |__|__|__|__|__|__| |__|__|__|__|__|__|
128 Sewing machine |___| |___|___| |___|___| |___|___| |___| |__|__|__|__|__|_
_|__|__|__|
|__|__|__|__|__|__| |__|__|__|__|__|__| |__|__|__|__|__|__|
129 Satellite dish/decoder |___| |___|___| |___|___| |___|___| |___| |__|__|__|__|__|_
_|__|__|__|
|__|__|__|__|__|__| |__|__|__|__|__|__| |__|__|__|__|__|__|
130 Generator |___| |___|___| |___|___| |___|___| |___| |__|__|__|__|__|_
_|__|__|__|
|__|__|__|__|__|__| |__|__|__|__|__|__| |__|__|__|__|__|__|
131 Solar lamp |___| |___|___| |___|___| |___|___| |___| |__|__|__|__|__|_
_|__|__|__|
|__|__|__|__|__|__| |__|__|__|__|__|__| |__|__|__|__|__|__|
132 Refrigerator/freezer |___| |___|___| |___|___| |___|___| |___| |__|__|__|__|__|_
_|__|__|__|
|__|__|__|__|__|__| |__|__|__|__|__|__| |__|__|__|__|__|__|
2 = PRODUCTIVE ASSETS
201 Metalplow |___| |___|___| |___|___| |___|___| |___| |__|__|__|__|__|_
_|__|__|__|
|__|__|__|__|__|__| |__|__|__|__|__|__| |__|__|__|__|__|__|
Sahel Resilience Learning (SAREL)—RISE Midline Quantitative Survey Report
October 2017 (Approved, Feb. 2018) 213
CONSUMPTION/PRODUCTIO
N ASSETS
QUESTION WORDING AND NUMBER
500 501 502 503 504 505 505a 505b 505c
Does your 
household 
currently 
own 
(name of 
asset)? 
1 = Yes
2 = No 
Number 
owned 
now
Number 
owned 
a year 
ago
Number 
owned 
two 
years 
ago
Have you 
purchased
any of these 
[ITEMS] in 
the last 12 
months?
 Yes = 1
 No = 2 
(skip to 
Q505a)
For purchased 
items, how much 
did you pay in 
total for these 
[ITEMS] in the 
last 12 months? 
(CFA F)
8 = DK 
9 = Refused
Did you acquire 
any of these 
[ITEMS] free of 
charge in the last 
12 months?
Yes = 1
No = 2 (skip to 
Q505c)
If you wanted to sell 
(types of asset) 
acquired free of charge 
over the last 12 months 
today, on average how 
much would you 
receive from the sale? 
(FCFA)
If you wanted to sell 
your old [types of asset] 
today, excluding those 
that you acquired 
(purchased and/or 
received free of charge) 
in the last 12 months, 
on average how much 
would you receive from 
the sale? (FCFA)
202 Sickle |___| |___|___| |___|___| |___|___| |___| |__|__|__|__|__|_
_|__|__|__|
|__|__|__|__|__|__| |__|__|__|__|__|__| |__|__|__|__|__|__|
203 Pick axe |___| |___|___| |___|___| |___|___| |___| |__|__|__|__|__|_
_|__|__|__|
|__|__|__|__|__|__| |__|__|__|__|__|__| |__|__|__|__|__|__|
204 Axe |___| |___|___| |___|___| |___|___| |___| |__|__|__|__|__|_
_|__|__|__|
|__|__|__|__|__|__| |__|__|__|__|__|__| |__|__|__|__|__|__|
205 Pruning/Cutting shears |___| |___|___| |___|___| |___|___| |___| |__|__|__|__|__|_
_|__|__|__|
|__|__|__|__|__|__| |__|__|__|__|__|__| |__|__|__|__|__|__|
206 Hoe |___| |___|___| |___|___| |___|___| |___| |__|__|__|__|__|_
_|__|__|__|
|__|__|__|__|__|__| |__|__|__|__|__|__| |__|__|__|__|__|__|
207 Spade or shovel |___| |___|___| |___|___| |___|___| |___| |__|__|__|__|__|_
_|__|__|__|
|__|__|__|__|__|__| |__|__|__|__|__|__| |__|__|__|__|__|__|
208 Traditional beehive |___| |___|___| |___|___| |___|___| |___| |__|__|__|__|__|_
_|__|__|__|
|__|__|__|__|__|__| |__|__|__|__|__|__| |__|__|__|__|__|__|
209 Modern Beehive |___| |___|___| |___|___| |___|___| |___| |__|__|__|__|__|_
_|__|__|__|
|__|__|__|__|__|__| |__|__|__|__|__|__| |__|__|__|__|__|__|
210 Knapsack chemical 
sprayer |___| |___|___| |___|___| |___|___| |___| |__|__|__|__|__|_
_|__|__|__|
|__|__|__|__|__|__| |__|__|__|__|__|__| |__|__|__|__|__|__|
Sahel Resilience Learning (SAREL)—RISE Midline Quantitative Survey Report
October 2017 (Approved, Feb. 2018) 214
CONSUMPTION/PRODUCTIO
N ASSETS
QUESTION WORDING AND NUMBER
500 501 502 503 504 505 505a 505b 505c
Does your 
household 
currently 
own 
(name of 
asset)? 
1 = Yes
2 = No 
Number 
owned 
now
Number 
owned 
a year 
ago
Number 
owned 
two 
years 
ago
Have you 
purchased
any of these 
[ITEMS] in 
the last 12 
months?
 Yes = 1
 No = 2 
(skip to 
Q505a)
For purchased 
items, how much 
did you pay in 
total for these 
[ITEMS] in the 
last 12 months? 
(CFA F)
8 = DK 
9 = Refused
Did you acquire 
any of these 
[ITEMS] free of 
charge in the last 
12 months?
Yes = 1
No = 2 (skip to 
Q505c)
If you wanted to sell 
(types of asset) 
acquired free of charge 
over the last 12 months 
today, on average how 
much would you 
receive from the sale? 
(FCFA)
If you wanted to sell 
your old [types of asset] 
today, excluding those 
that you acquired 
(purchased and/or 
received free of charge) 
in the last 12 months, 
on average how much 
would you receive from 
the sale? (FCFA)
211 Mechanical water pump |___| |___|___| |___|___| |___|___| |___| |__|__|__|__|__|_
_|__|__|__|
|__|__|__|__|__|__| |__|__|__|__|__|__| |__|__|__|__|__|__|
212 Motorized water pump 
(diesel/gasoline) |___| |___|___| |___|___| |___|___| |___| |__|__|__|__|__|_
_|__|__|__|
|__|__|__|__|__|__| |__|__|__|__|__|__| |__|__|__|__|__|__|
213 Motorized grain mill 
(diesel/gasoline) |___| |___|___| |___|___| |___|___| |___| |__|__|__|__|__|_
_|__|__|__|
|__|__|__|__|__|__| |__|__|__|__|__|__| |__|__|__|__|__|__|
214 Motor hoe |___| |___|___| |___|___| |___|___| |___| |__|__|__|__|__|_
_|__|__|__|
|__|__|__|__|__|__| |__|__|__|__|__|__| |__|__|__|__|__|__|
215 Small tractor |___| |___|___| |___|___| |___|___| |___| |__|__|__|__|__|_
_|__|__|__|
|__|__|__|__|__|__| |__|__|__|__|__|__| |__|__|__|__|__|__|
216 Hand-held motorized 
tiller |___| |___|___| |___|___| |___|___| |___| |__|__|__|__|__|_
_|__|__|__|
|__|__|__|__|__|__| |__|__|__|__|__|__| |__|__|__|__|__|__|
217 Farming land |___| |___|___| |___|___| |___|___| |___| |__|__|__|__|__|_
_|__|__|__|
|__|__|__|__|__|__| |__|__|__|__|__|__| |__|__|__|__|__|__|
218 Well |___| |___|___| |___|___| |___|___| |___| |__|__|__|__|__|_
_|__|__|__|
|__|__|__|__|__|__| |__|__|__|__|__|__| |__|__|__|__|__|__|
219 Borehole |___| |___|___| |___|___| |___|___| |___| |__|__|__|__|__|_
_|__|__|__|
|__|__|__|__|__|__| |__|__|__|__|__|__| |__|__|__|__|__|__|
Sahel Resilience Learning (SAREL)—RISE Midline Quantitative Survey Report
October 2017 (Approved, Feb. 2018) 215
CONSUMPTION/PRODUCTIO
N ASSETS
QUESTION WORDING AND NUMBER
500 501 502 503 504 505 505a 505b 505c
Does your 
household 
currently 
own 
(name of 
asset)? 
1 = Yes
2 = No 
Number 
owned 
now
Number 
owned 
a year 
ago
Number 
owned 
two 
years 
ago
Have you 
purchased
any of these 
[ITEMS] in 
the last 12 
months?
 Yes = 1
 No = 2 
(skip to 
Q505a)
For purchased 
items, how much 
did you pay in 
total for these 
[ITEMS] in the 
last 12 months? 
(CFA F)
8 = DK 
9 = Refused
Did you acquire 
any of these 
[ITEMS] free of 
charge in the last 
12 months?
Yes = 1
No = 2 (skip to 
Q505c)
If you wanted to sell 
(types of asset) 
acquired free of charge 
over the last 12 months 
today, on average how 
much would you 
receive from the sale? 
(FCFA)
If you wanted to sell 
your old [types of asset] 
today, excluding those 
that you acquired 
(purchased and/or 
received free of charge) 
in the last 12 months, 
on average how much 
would you receive from 
the sale? (FCFA)
220 Watering can |___| |___|___| |___|___| |___|___| |___| |__|__|__|__|__|_
_|__|__|__|
|__|__|__|__|__|__| |__|__|__|__|__|__| |__|__|__|__|__|__|
Sahel Resilience Learning (SAREL)—RISE Midline Quantitative Survey Report
October 2017 (Approved, Feb. 2018) 216
MODULE 5a. ACCESS TO LAND 
506a Has your household engaged in farming activities in the last 12 months? 
1. Yes (Fill in the table)
2. No (skip to next module) |___|
Farm N°
506b Type of Farm 507 Area (ha) 508 Mode of acquisition
01. Rain-fed farm 
02. Off-season 
03. Orchard 
04 Hydro-agricultural 
developments 
05. Garden
06. Rain-fed + off-season 
07. Rain-fed + off-season + orchard 
08. Orchard + off-season
09 Orchard + rain-fed 
10. Other 
01. Inherited
02. Bought 
03. Sharecropping basis
04. Use right (usufruct)
05. Borrowed
06. Right of the axe
07. Hydro-agricultural 
development
08. Leased
09. Gift, grant
10. Other (specify)
01
|___|___| |___|___|___| , |___| |___|
02
|___|___| |___|___|___| , |___| |___|
03
|___|___| |___|___|___| , |___| |___|
04
|___|___| |___|___|___| , |___| |___|
05
|___|___| |___|___|___| , |___| |___|
06
|___|___| |___|___|___| , |___| |___|
Sahel Resilience Learning (SAREL)—RISE Midline Quantitative Survey Report
October 2017 (Approved, Feb. 2018) 217
07
|___|___| |___|___|___| , |___| |___|
08
|___|___| |___|___|___| , |___| |___|
09
|___|___| |___|___|___| , |___| |___|
10
|___|___| |___|___|___| , |___| |___|
11
|___|___| |___|___|___| , |___| |___|
13
|___|___| |___|___|___| , |___| |___|
14
|___|___| |___|___|___| , |___| |___|
15
|___|___| |___|___|___| , |___| |___|
Sahel Resilience Learning (SAREL)—RISE Midline Quantitative Survey Report
October 2017 (Approved, Feb. 2018) 218
MODULE 6: LIVESTOCK ASSETS
TYPE OF LIVESTOCK
QUESTION WORDING AND NUMBER
601 602 603
Total [livestock types] owned one year 
ago (opening stock)
Total [livestock type] owned now
(closing stock)
if Q602=0 skip to next row)
If you wanted to sell all your [livestock types] 
today, how much in total would you receive 
from the sale? (CFA F)
01 Oxen (bovine) |___|___|___| |___|___|___| |___|___|___|___|___|___|___|
02 Sheep (ovine) |___|___|___| |___|___|___| |___|___|___|___|___|___|___|
03 Goats (caprine) |___|___|___| |___|___|___| |___|___|___|___|___|___|___|
04 Donkeys |___|___|___| |___|___|___| |___|___|___|___|___|___|___|
05 Horse (equine) |___|___|___| |___|___|___| |___|___|___|___|___|___|___|
06 Pigs (porcine) |___|___|___| |___|___|___| |___|___|___|___|___|___|___|
07 Camels – dromedaries |___|___|___| |___|___|___| |___|___|___|___|___|___|___|
08 Rabbits |___|___|___| |___|___|___| |___|___|___|___|___|___|___|
09 Hens |___|___|___| |___|___|___| |___|___|___|___|___|___|___|
10 Guinea fowls |___|___|___| |___|___|___| |___|___|___|___|___|___|___|
11 Turkeys |___|___|___| |___|___|___| |___|___|___|___|___|___|___|
12 Ducks |___|___|___| |___|___|___| |___|___|___|___|___|___|___|
13 Pigeons |___|___|___| |___|___|___| |___|___|___|___|___|___|___|
Sahel Resilience Learning (SAREL)—RISE Midline Quantitative Survey Report
October 2017 (Approved, Feb. 2018) 219
MODULE 7. LIVESTOCK COMMODITIES (Ask these questions even if the household does not own or use livestock.)
Commodity
700 701 702 703 704 705
Did your 
household 
produce (name of 
product) in the last 
12 months? 
Yes = 1
No = 2 (if No, skip 
to next product)
Number of animals 
that have been 
milked in the last 12 
months?
Number of months in 
which milking occurs every 
day in the last 12 months?
Frequency 
(number of 
milkings per day 
during those 
months)?
Daily milk quantity 
in liters collected 
during these 
months?
If some of the milk produced 
was sold, what proportion (%) 
of milk was sold per day during 
those months?
1 Cattle Milk |___| |___|___| |___|___| |___|___| |___|___|___| |___|___|___|
2 Sheep/Goat milk |___| |___|___| |___|___| |___|___| |___|___|___| |___|___|___|
3 Camel milk |___| |___|___| |___|___| |___|___| |___|___|___| |___|___|___|
Sahel Resilience Learning (SAREL)—RISE Midline Quantitative Survey Report
October 2017 (Approved, Feb. 2018) 220
MODULE 7a. HOUSEHOLD AGRICULTURAL PRODUCTION
Commodity
QUESTION WORDING AND NUMBER
701b 702b 703b 704b 705b 706b
Total [commodity] 
produced in the last 12 
months
Total [commodity] sold in 
the last 12 months
Complete for any produce 
sold
If none has been sold, 
skip to Q705b
Value of commodity sold in the 
last 12 months
Where did you 
mainly sell 
[commodity]?
1= Local market
2=Regional market
3=Others
Current stock of 
[commodity]
888 = DK
If you wanted to sell the stock 
today, how much would you 
receive from the sale? (CFA F)
Quantity Unit Quantity Unit Quantity Unit
01 Millet |___|___|___| |___|___| |___|___|___| |___|___| |___|___|___|___|___|___|___| |___| |___|___|___| |___|___| |___|___|___|___|___|___|___|
02 Maize |___|___|___| |___|___| |___|___|___| |___|___| |___|___|___|___|___|___|___| |___| |___|___|___| |___|___| |___|___|___|___|___|___|___|
03 Rice |___|___|___| |___|___| |___|___|___| |___|___| |___|___|___|___|___|___|___| |___| |___|___|___| |___|___| |___|___|___|___|___|___|___|
04 Sorghum |___|___|___| |___|___| |___|___|___| |___|___| |___|___|___|___|___|___|___| |___| |___|___|___| |___|___| |___|___|___|___|___|___|___|
05 Wheat |___|___|___| |___|___| |___|___|___| |___|___| |___|___|___|___|___|___|___| |___| |___|___|___| |___|___| |___|___|___|___|___|___|___|
06 Fonio |___|___|___| |___|___| |___|___|___| |___|___| |___|___|___|___|___|___|___| |___| |___|___|___| |___|___| |___|___|___|___|___|___|___|
07 Cowpea |___|___|___| |___|___| |___|___|___| |___|___| |___|___|___|___|___|___|___| |___| |___|___|___| |___|___| |___|___|___|___|___|___|___|
08 Peanut |___|___|___| |___|___| |___|___|___| |___|___| |___|___|___|___|___|___|___| |___| |___|___|___| |___|___| |___|___|___|___|___|___|___|
09 Sesame |___|___|___| |___|___| |___|___|___| |___|___| |___|___|___|___|___|___|___| |___| |___|___|___| |___|___| |___|___|___|___|___|___|___|
10 Vouandzou |___|___|___| |___|___| |___|___|___| |___|___| |___|___|___|___|___|___|___| |___| |___|___|___| |___|___| |___|___|___|___|___|___|___|
11 Tobacco |___|___|___| |___|___| |___|___|___| |___|___| |___|___|___|___|___|___|___| |___| |___|___|___| |___|___| |___|___|___|___|___|___|___|
12 Cotton |___|___|___| |___|___| |___|___|___| |___|___| |___|___|___|___|___|___|___| |___| |___|___|___| |___|___| |___|___|___|___|___|___|___|
13 Beans |___|___|___| |___|___| |___|___|___| |___|___| |___|___|___|___|___|___|___| |___| |___|___|___| |___|___| |___|___|___|___|___|___|___|
Sahel Resilience Learning (SAREL)—RISE Midline Quantitative Survey Report
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Commodity
QUESTION WORDING AND NUMBER
701b 702b 703b 704b 705b 706b
Total [commodity] 
produced in the last 12 
months
Total [commodity] sold in 
the last 12 months
Complete for any produce 
sold
If none has been sold, 
skip to Q705b
Value of commodity sold in the 
last 12 months
Where did you 
mainly sell 
[commodity]?
1= Local market
2=Regional market
3=Others
Current stock of 
[commodity]
888 = DK
If you wanted to sell the stock 
today, how much would you 
receive from the sale? (CFA F)
Quantity Unit Quantity Unit Quantity Unit
14 Tigernut |___|___|___| |___|___| |___|___|___| |___|___| |___|___|___|___|___|___|___| |___| |___|___|___| |___|___| |___|___|___|___|___|___|___|
15 Henna |___|___|___| |___|___| |___|___|___| |___|___| |___|___|___|___|___|___|___| |___| |___|___|___| |___|___| |___|___|___|___|___|___|___|
16 Sweet potato |___|___|___| |___|___| |___|___|___| |___|___| |___|___|___|___|___|___|___| |___| |___|___|___| |___|___| |___|___|___|___|___|___|___|
17 Irish potato |___|___|___| |___|___| |___|___|___| |___|___| |___|___|___|___|___|___|___| |___| |___|___|___| |___|___| |___|___|___|___|___|___|___|
18 Onion |___|___|___| |___|___| |___|___|___| |___|___| |___|___|___|___|___|___|___| |___| |___|___|___| |___|___| |___|___|___|___|___|___|___|
19 Hot pepper |___|___|___| |___|___| |___|___|___| |___|___| |___|___|___|___|___|___|___| |___| |___|___|___| |___|___| |___|___|___|___|___|___|___|
20 Sorrel |___|___|___| |___|___| |___|___|___| |___|___| |___|___|___|___|___|___|___| |___| |___|___|___| |___|___| |___|___|___|___|___|___|___|
21 Okra |___|___|___| |___|___| |___|___|___| |___|___| |___|___|___|___|___|___|___| |___| |___|___|___| |___|___| |___|___|___|___|___|___|___|
22 Tomato |___|___|___| |___|___| |___|___|___| |___|___| |___|___|___|___|___|___|___| |___| |___|___|___| |___|___| |___|___|___|___|___|___|___|
23 Lettuce (salad) |___|___|___| |___|___| |___|___|___| |___|___| |___|___|___|___|___|___|___| |___| |___|___|___| |___|___| |___|___|___|___|___|___|___|
24 Cabbage |___|___|___| |___|___| |___|___|___| |___|___| |___|___|___|___|___|___|___| |___| |___|___|___| |___|___| |___|___|___|___|___|___|___|
25 Fruit trees
(specify) |___|___|___| |___|___| |___|___|___| |___|___| |___|___|___|___|___|___|___| |___| |___|___|___| |___|___| |___|___|___|___|___|___|___|
26 Other (specify) |___|___|___| |___|___| |___|___|___| |___|___| |___|___|___|___|___|___|___| |___| |___|___|___| |___|___| |___|___|___|___|___|___|___|
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Units of measure code list
01 Kilograms 02 Quintal 03 Ton 04 Stack 05 Basket 06 50 kg bag 07 100 kg bag 08 Pack 09 Bundles 10 Unit 11 « Tine » 12 Other
MODULE 8. HOUSEHOLD CONSUMPTION EXPENDITURE 
Ask these questions about the consumption/expenditures of all household members. Ask whoever is most knowledgeable about the food the 
household members have eaten over the past 7 days, as well as any non-food items that household members have bought. The same respondent 
should be asked questions in Modules E2-E5.
Note: Quantities are often reported in local units of measure. Any unit listed must be able to be converted to a standardized unit. This 
conversion will happen during data analysis. It should not be done in the field by the enumerator.
MODULE 8-E2. NON-FOOD EXPENDITURES OVER PAST 7 DAYS
Over the past week (7 days), did your 
household use or buy any [item]?
Yes = 1
No = 2
DK = 8 skip to next asset
Refused = 9
How much did you pay (how much did [item] cost) in 
total?
What is the estimated value of [item] used in the last 7 
days that:
1. The household received free of charge
2. The household used some of [item] in the last 7 
days
3. Other 
Code Items E2.01
E2.02
(CFAF)
1101 Charcoal or other fuel for cooking |___| |___|___|___|___|___|___|___|
1102 Firewood |___| |___|___|___|___|___|___|___|
1103 Gasoline |___| |___|___|___|___|___|___|___|
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1104 Kerosene |___| |___|___|___|___|___|___|___|
1105 Gas |___| |___|___|___|___|___|___|___|
1106 Batteries |___| |___|___|___|___|___|___|___|
1107 Candles |___| |___|___|___|___|___|___|___|
1108 Matches |___| |___|___|___|___|___|___|___|
1109 Prepaid top-up card/mobile phone credit transfer |___| |___|___|___|___|___|___|___|
1110 Transport |___| |___|___|___|___|___|___|___|
1111 Milling fees for grains |___| |___|___|___|___|___|___|___|
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MODULE 8-E3. NON-FOOD EXPENDITURES OVER THE PAST 30 DAYS
Over the past 30 days (, did your 
household use or buy any [item]?
Yes = 1
No = 2
DK = 8 skip to next asset
Refused = 9
How much did you pay (how much did [item] 
cost) in total?
What is the estimated value of [item] used in the 
last 30 days that:
1. The household received free of charge
2. The household used some of [item] in the 
last 30 days
3. Other 
Code Items E3.01
E3.02
(CFAF)
1201 Milling fees for grains (excluding cost of grain itself), grain |___| |___|___|___|___|___|___|___|
1202 Personal products (body soap, skin creams, shampoo, razor blades, 
toothbrush/paste, etc.). |___| |___|___|___|___|___|___|___|
1203 Soap for clothes |___| |___|___|___|___|___|___|___|
1204 Donation - to church, mosque, charity, beggar, etc. |___| |___|___|___|___|___|___|___|
1205 Insecticides |___| |___|___|___|___|___|___|___|
1206 Cooking gas |___| |___|___|___|___|___|___|___|
1207 Gasoline or diesel |___| |___|___|___|___|___|___|___|
1208 Light bulbs |___| |___|___|___|___|___|___|___|
1209 Electricity fees |___| |___|___|___|___|___|___|___|
1210 Top-up card fees |___| |___|___|___|___|___|___|___|
1211 Transport costs (bush taxi, motorcycle taxi, canoe, carts, etc.) |___| |___|___|___|___|___|___|___|
1212 (Motor vehicle, motorcycle) service, repair, or parts |___| |___|___|___|___|___|___|___|
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1213 Bicycle service, repair, or parts |___| |___|___|___|___|___|___|___|
1214 Repairs & maintenance to dwelling |___| |___|___|___|___|___|___|___|
1215 Repairs to household and personal items (radios, watches, etc., excluding battery 
purchases) |___| |___|___|___|___|___|___|___|
1216 Vehicle batteries |___| |___|___|___|___|___|___|___|
1217 Batteries |___| |___|___|___|___|___|___|___|
1218 Male hairdressing fees |___| |___|___|___|___|___|___|___|
1219 Female hairdressing fees |___| |___|___|___|___|___|___|___|
1220 Health expenditures related to illnesses and injuries |___| |___|___|___|___|___|___|___|
1221 Health expenditures for preventative care (visits, medications, etc.) |___| |___|___|___|___|___|___|___|
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MODULE 8-E4. NON-FOOD EXPENDITURES OVER PAST THREE MONTHS
Over the past 3 months, did 
your household use or buy any 
[item]?
Yes = 1
No = 2
DK = 8 skip to next asset
Refused = 9
How much did you pay (how much did [item] cost) in total?
What is the estimated value of [item] used in the last 3 
months that:
1. The household received free of charge
2. The household used some of [item] in the last 3 months
3. Other 
Code Items E4.01
E4.02
(CFAF)
1301 Clothing |___| |___|___|___|___|___|___|___|
1302 Shoes |___| |___|___|___|___|___|___|___|
1303 Dishware (bowls, plates, glassware) |___| |___|___|___|___|___|___|___|
1304 Cooking utensils (cooking pots, stirring spoons and whisks, 
etc.) |___| |___|___|___|___|___|___|___|
1305 Light bulbs |___| |___|___|___|___|___|___|___|
1306 Torch/flashlight |___| |___|___|___|___|___|___|___|
1307 Kerosene lamp |___| |___|___|___|___|___|___|___|
1308 Music or CD/DVD or video cassette |___| |___|___|___|___|___|___|___|
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MODULE 8-E5. NON-FOOD EXPENDITURES OVER PAST 12 MONTHS
Over the past year (12 months), did 
your household use or buy any [item]?
Yes = 1
No = 2
DK = 8 skip to next asset
Refused = 9
How much did you pay (how much did [item] cost) in 
total?
What is the estimated value of [item] used in the last 12 
months that:
1. The household received free of charge
2. The household used some of [item] in the last 12 
months
3. Other 
Code Items E5.01
E5.02
(CFAF)
1401 Carpet, rugs, mats |___| |___|___|___|___|___|___|___|
1402 Shoe repair |___| |___|___|___|___|___|___|___|
1403 Linen-towels, sheets, blankets |___| |___|___|___|___|___|___|___|
1404 Toys |___| |___|___|___|___|___|___|___|
1405 Mosquito nets |___| |___|___|___|___|___|___|___|
1406 Construction materials (bricks, cement, wood) |___| |___|___|___|___|___|___|___|
1407 Dowry |___| |___|___|___|___|___|___|___|
1408 Marriage ceremony costs |___| |___|___|___|___|___|___|___|
1409 Funeral costs for household members |___| |___|___|___|___|___|___|___|
1410 Funeral costs for non-household members (relatives, neighbors/friends) |___| |___|___|___|___|___|___|___|
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1411 Major health expenses (hospitalizations, traditional healer 
costs) including travel, lodging and food expenses |___| |___|___|___|___|___|___|___|
1412 Education expenses (fees, books, uniforms, etc.). |___| |___|___|___|___|___|___|___|
1413 Rituals and traditional events |___| |___|___|___|___|___|___|___|
1414 Punitive compensation (property damage, injury, loss of life) |___| |___|___|___|___|___|___|___|
1415 Fertilizer purchase |___| |___|___|___|___|___|___|___|
1416 Land or livestock taxes |___| |___|___|___|___|___|___|___|
1417 Tax (paid by household members) |___| |___|___|___|___|___|___|___|
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MODULE 9. ACCESS TO FINANCIAL SERVICES/CREDIT
N° QUESTION WORDING • ANSWERS •
901 Have any household members taken out a loan in the 
last 12 months (cash or in-kind)? • 1. Yes (if "yes", skip to q903)
• 2. No 
• 8. DK (skip to Module 10)
• 9. Refused (skip to Module 10)
• |___|
902 • If not, why not?
Enter respondent's answer and skip to Module 10
• 1. Didn’t need
• 2. Couldn’t find a loan that met my needs” (i.e. “is appropriate” in terms 
of size, terms, Sharia-compliant, etc.); 
• 3. Afraid I couldn’t pay back
• 4. No loan providers in my area
• 5. Other (specify) 
• 8. DK
• 9. Refused
|___|
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If yes, list all the loans taken out by household members.
QUESTION WORDING AND NUMBER
903 904 905 906 907 908 909 910
Loan 
Number
ID of household 
member who took 
the loan
Enter IDs or 
household 
members who took 
the loan 
Source of the loan
01 Money lender 
02 Friend/Neighbor 
03 Family member 
04 Micro credit 
05 Bank 
06 NGO 
07 Religious institution 
08 Savings group, 
including warrantage 
scheme
09 Input supplier 
10 Local trader
11 Community based 
organization (CBO)
12 Other (specify)
88 DK
99 Refused
What was the total value of 
the loan?
(CFA F) 
Do you have to 
pay a monthly 
interest rate or 
service fee on the 
loan?
1=yes
2=no
8 = DK
9 = Refused 
Purpose of the loan
1. Feed family
2. Pay school fees
3. Pay medical fees
4. Production inputs (e.g. 
livestock, agricultural inputs)
5. Business capital
6. Pay veterinary fees
7. Other 
Who made the decision 
from [SOURCE]?
01 Myself
02 Partner
03 Myself and partner/spouse 
together
04 Another household member
05 Myself and other household 
member(s)
06 Partner/spouse
07 Household
08 Myself and another external 
person
09 Partner/spouse and another 
external person
10 Myself, partner/spouse and 
another external person
Who makes the decision on 
what to do with the 
money/item borrowed from 
[SOURCE]?
01 Myself
02 Partner
03 Myself and partner/spouse 
together
04 Another household member
05 Myself and other household 
member(s)
06 Partner/spouse
07 Household
08 Myself and another external 
person
09 Partner/spouse and another 
external person
10 Myself, partner/spouse and 
another external person
1 |____|____| |____|____| |__|__|__|__|__|__|__
|__| |____| |____| |____|____| |____|____|
2 |____|____| |____|____| |__|__|__|__|__|__|__
|__| |____| |____| |____|____| |____|____|
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3 |____|____| |____|____| |__|__|__|__|__|__|__
|__| |____| |____| |____|____| |____|____|
4 |____|____| |____|____| |__|__|__|__|__|__|__
|__| |____| |____| |____|____| |____|____|
5 |____|____| |____|____| |__|__|__|__|__|__|__
|__| |____| |____| |____|____| |____|____|
6 |____|____| |____|____| |__|__|__|__|__|__|__
|__| |____| |____| |____|____| |____|____|
7 |____|____| |____|____| |__|__|__|__|__|__|__
|__| |____| |____| |____|____| |____|____|
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MODULE 10. ACCESS TO FINANCIAL SERVICES/ SAVINGS
1001 Do any of your household members have cash savings? Yes...................... 1
No ....................... 2
DK....................... 8 (skip to next module)
Refused .............. 9
|___|
QUESTION WORDING AND NUMBER
1002 1003 1004 1005 Saving Number
Enter the ID of household member 
owning the savings
Where is the savings held?
1. In cash at home
2. With microfinance institution
3. With bank 
4. With savings group
5. Other (specify) 
8. DK
9. Refused
What is the primary purpose of the saving? 
1. To use in emergencies
2. To buy livestock
3. For non-livestock business investment
4. Seed purchase
5. Invest in agriculture
6. Timber harvesting/reforestation
7. Other (specify)
8. DK
9. Refused
1 |____|____| |____| |____|
2 |____|____| |____| |____|
3 |____|____| |____| |____|
4 |____|____| |____| |____|
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5 |____|____| |____| |____|
6 |____|____| |____| |____|
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MODULE 11. ACCESS TO INFORMATION 
TYPE OF INFORMATION
QUESTION WORDING AND NUMBER
1101 1102
Did you receive any 
information on [topic] in the 
last 12 months?
Yes = 1
No = 2 skip to next topic
DK = 8 skip to next topic
Refused = 9 skip to next topic
What was your main source of information about 
[topic]?
01. Rural development agents
02. Service providers (agricultural, health/hygiene, 
veterinary, etc.)
03. Village/traditional leaders
04. Koranic schoolteachers 
05. Madrasa/Franco-Arabic teachers 
06. Conventional/mainstream education teachers 
07. Neighbors or friends
08. Government officials
09. Family members
10. Newspapers
11. Audiovisual media/TV/radio
12. Internet or SMS
13. Town crier
14. Village Development Committee (CVD)
15. Other (specify)
1 Long-term changes in weather patterns |____| |____|____|
2 Rainfall prospects / weather prospects for coming season |____| |____|____|
3 Water availability and prices of local boreholes, shallow wells etc. |____| |____|____|
4 Methods for animal health/husbandry |____| |____|____|
5 Livestock disease threats or epidemics |____| |____|____|
6 Innovations in cultivation |____| |____|____|
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7 Child nutrition and health information |____| |____|____|
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MODULE 12. LIVELIHOOD ACTIVITIES 
LIVELIHOOD ACTIVITIES
QUESTION WORDING AND NUMBER
1201 1202 1203 1204 1205
What were the sources 
of your household’s 
food/income over the 
whole last 12 months?
Yes = 1
No = 2 
Read list of sources to 
respondents
Rank these sources 
based on the proportion 
of food/income they 
provide for your 
household
Rank all sources listed 
in Q1201, starting with
01 as the highest 
proportion of 
food/income 
Enter the
proportion of 
food/income they 
provide for your 
household
Is this food/income source 
available in the dry season 
only, wet season only, or all 
year?
1. Dry season only
2. Wet season only
3. Both (all year round)
8. DK
9. Refused
Do you only 
rely on this 
source 
during times 
of stress?
1. Yes
2. No
8. DK
9. Refused 
Code
1. Agricultural Sources
101 Farming/crop production and sales |___| |___|___| |___|___|___| |___| |___|
102 Livestock production and sales |___| |___|___| |___|___|___| |___| |___|
103 Farm laborer |___| |___|___| |___|___|___| |___| |___|
104 Production and sale of seedlings, seeds, animal feed |___| |___|___| |___|___|___| |___| |___|
105 Production and sale of firewood, charcoal, poles, timber |___| |___|___| |___|___|___| |___| |___|
106 Sale of wild products |___| |___|___| |___|___|___| |___| |___|
107
Employed in an agricultural and animal product processing 
and marketing company
|___| |___|___| |___|___|___| |___| |___|
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LIVELIHOOD ACTIVITIES
QUESTION WORDING AND NUMBER
1201 1202 1203 1204 1205
What were the sources 
of your household’s 
food/income over the 
whole last 12 months?
Yes = 1
No = 2 
Read list of sources to 
respondents
Rank these sources 
based on the proportion 
of food/income they 
provide for your 
household
Rank all sources listed 
in Q1201, starting with
01 as the highest 
proportion of 
food/income 
Enter the
proportion of 
food/income they 
provide for your 
household
Is this food/income source 
available in the dry season 
only, wet season only, or all 
year?
1. Dry season only
2. Wet season only
3. Both (all year round)
8. DK
9. Refused
Do you only 
rely on this 
source 
during times 
of stress?
1. Yes
2. No
8. DK
9. Refused 
108 Private agricultural service providers (veterinary 
paraprofessionals, agricultural service delivery agent, etc.)
|___| |___|___| |___|___|___| |___| |___|
109 Other (specify) |___| |___|___| |___|___|___| |___| |___|
110 Other (specify) |___| |___|___| |___|___|___| |___| |___|
2. Non-agricultural Sources
201 Retailing (shopkeeper, sale of non-agricultural products 
etc.)
|___| |___|___| |___|___|___| |___| |___|
202 Non-agricultural service delivery agent |___| |___|___| |___|___|___| |___| |___|
203
Technical and professional activities (carpenter, mason, 
bike or motorcycle repairman, tire repairman, mechanic, 
cellular phone repairman, motor pump repairman, tailor, etc.)
|___| |___|___| |___|___|___| |___| |___|
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LIVELIHOOD ACTIVITIES
QUESTION WORDING AND NUMBER
1201 1202 1203 1204 1205
What were the sources 
of your household’s 
food/income over the 
whole last 12 months?
Yes = 1
No = 2 
Read list of sources to 
respondents
Rank these sources 
based on the proportion 
of food/income they 
provide for your 
household
Rank all sources listed 
in Q1201, starting with
01 as the highest 
proportion of 
food/income 
Enter the
proportion of 
food/income they 
provide for your 
household
Is this food/income source 
available in the dry season 
only, wet season only, or all 
year?
1. Dry season only
2. Wet season only
3. Both (all year round)
8. DK
9. Refused
Do you only 
rely on this 
source 
during times 
of stress?
1. Yes
2. No
8. DK
9. Refused 
204 Artisanal mining |___| |___|___| |___|___|___| |___| |___|
205 Non-agricultural worker (factory, company, mine, etc.) |___| |___|___| |___|___|___| |___| |___|
206 Domestic help |___| |___|___| |___|___|___| |___| |___|
207 Crafts (pottery, basketry, carved wood, etc.) |___| |___|___| |___|___|___| |___| |___|
208 Carrier, docker |___| |___|___| |___|___|___| |___| |___|
209 Other (specify) |___| |___|___| |___|___|___| |___| |___|
210 Other (specify) |___| |___|___| |___|___|___| |___| |___|
3. External non-agricultural Sources
301 Migration/Rural exodus |___| |___|___| |___|___|___| |___| |___|
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LIVELIHOOD ACTIVITIES
QUESTION WORDING AND NUMBER
1201 1202 1203 1204 1205
What were the sources 
of your household’s 
food/income over the 
whole last 12 months?
Yes = 1
No = 2 
Read list of sources to 
respondents
Rank these sources 
based on the proportion 
of food/income they 
provide for your 
household
Rank all sources listed 
in Q1201, starting with
01 as the highest 
proportion of 
food/income 
Enter the
proportion of 
food/income they 
provide for your 
household
Is this food/income source 
available in the dry season 
only, wet season only, or all 
year?
1. Dry season only
2. Wet season only
3. Both (all year round)
8. DK
9. Refused
Do you only 
rely on this 
source 
during times 
of stress?
1. Yes
2. No
8. DK
9. Refused 
302 Gifts/inheritance |___| |___|___| |___|___|___| |___| |___|
303 Other (specify) |___| |___|___| |___|___|___| |___| |___|
304 Other (specify) |___| |___|___| |___|___|___| |___| |___|
305 Other (specify) |___| |___|___| |___|___|___| |___| |___|
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Questions to be asked only if the household responded in the table above that migration was a source of food / income in 
the last 12 months 
1206. In your household, how many people have migrated in the last twelve months? |___|___|
Migrant List
QUESTION WORDING AND NUMBER
1207 1208 1209 1210 1211
Where did the person migrate 
to?
1. Another locality in the 
country
2. Another African country
3. Another non-African 
country
8. DK
9. Refused
Is migration seasonal or 
permanent?
1. Seasonal
2. Permanent
8. DK
9. Refused
How long ago (in months) did 
the person migrate?
(enter the number of months 
since the individual 
migrated)
8. DK
9. Refused
What is the main income 
generating activity in which 
the person is engaged over 
there? 
Has the person ever sent 
money back to your 
household from his/her 
place of migration?
1. Yes
2. No
8. DK
9. Refused
1 Person 1 |____| |____| |____|____|
…………………….……..
|____|____|
|____|
2 Person 2 |____| |____| |____|____|
…………………….……..
|____|____|
|____|
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3 Person 3 |____| |____| |____|____|
…………………….……..
|____|____|
|____|
4 Person 4 |____| |____| |____|____|
…………………….……..
|____|____|
|____|
5 Person 5 |____| |____| |____|____|
…………………….……..
|____|____|
|____|
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MODULE 13. SOCIAL AND CAPACITY-BUILDING SUPPORT
N° QUESTION WORDING ANSWERS CODES
FORMAL SOURCES OF SOCIAL SUPPORT
1301 Has your household received any kind of support from the government, an NGO 
or religious organization during the last 12 months?
• 1. Yes
• 2. No 
• 8. DK
• 9. Refused
|___|
1302 Who provided the support? (Multiple response)
NB: Use the answer codes, not the answer number. For example: for Q1302, if 
the household says that they received support from a religious organization (Yes 
=1), put Code “1”, not Code “3”, which is the answer number.
1. Government....................................................... Yes = 
1 No = 2 |___|
2. NGO/Association/Project..................................... Yes = 
1 No = 2 |___|
3. Religious organization......................................... Yes = 
1 No = 2 |___|
4. Other (specify) ................................................... Yes = 
1 No = 2 |___|
1303 What types of support were received? (Read list)
NB: Use the answer codes, not the answer number. For example: for Q1303, if 
the household says that they received “Food for work/Cash for work” (Yes =1), 
put Code “1”, not Code “2”, which is the answer number.
1. Food ration
.......................................................................................... Yes = 
1 No = 2 |___|
2. Food-for-work/Cash-for-work Yes = 
1 No = 2 |___|
3. Housing materials
.......................................................................................... Yes = 
1 No = 2 |___|
4. Installed water points
.......................................................................................... Yes = 
1 No = 2 |___|
5. Installed latrine
.......................................................................................... Yes = 
1 No = 2 |___|
6. School for children
.......................................................................................... Yes = 
1 No = 2 |___|
7. Cash transfer
.......................................................................................... Yes = 
1 No = 2 |___|
8. Loans Yes = No = 2 |___|
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N° QUESTION WORDING ANSWERS CODES
1
9. Other (specify) 
.......................................................................................... Yes = 
1 No = 2 |___|
INFORMAL SOURCES OF SOCIAL SUPPORT
1304a Has your household received any kind of support from relatives, neighbors or 
friends in the past 12 months?)
• 1. Yes
• 2. No 
• 8. DK
• 9. Refused
|___|
1304b What types of assistance has your household received from relatives, neighbors 
or friends in the past 12 months? (Read list)
NB: Use the answer codes, not the answer number. For example: for Q1304b, if 
the household says that they received a “Loan” (Yes =1), put Code “1”, not Code 
“4”, which is the answer number.
1. Zakat
........................................................................ Yes = 
1 No = 2 |___|
2. Remittances 
........................................................................ Yes = 
1 No = 2 |___|
3. Gifts/habbanaye (donation of cash/animals to 
people in need) 
........................................................................
Yes = 
1 No = 2 |___|
4. Loans (cash, labor, seeds, animals) 
........................................................................ Yes = 
1 No = 2 |___|
5. Restocking of poorer relatives 
........................................................................ Yes = 
1 No = 2 |___|
6. Sadaqa
........................................................................ Yes = 
1 No = 2 |___|
7. Other (specify)
........................................................................ Yes = 
1 No = 2 |___|
1305 At the moment, if your household had a problem and needed money or food
urgently, would you be able to get it from relatives living in this community?
• 1. Yes
• 2. No 
• 8. DK
• 9. Refused
|___|
1306 At the moment, if your household had a problem and needed money for food 
urgently, would you be able to get it from relatives living elsewhere?
• 1. Yes
• 2. No |___|
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N° QUESTION WORDING ANSWERS CODES
• 8. DK
• 9. Refused
1307 At the moment, if your household had a problem and needed money for food 
urgently, would you be able to get it from people in your community who are not 
your relatives?
• 1. Yes
• 2. No 
• 8. DK
• 9. Refused
|___|
1308 At the moment, if your household had a problem and needed money for food 
urgently, would you be able to get it from people living someplace else who are 
not your relatives?
• 1. Yes
• 2. No 
• 3. DK
• 4. Refused
|___|
1309 Compared to one year ago has your ability to get this type of assistance: • 1. Increased
• 2. Stayed the same
• 3. Decreased
• 8. DK
• 9. Refused
|___|
1310 At the moment, if someone in your household fell ill or was injured, and you 
needed assistance to perform work in your household, would you be able to get 
it from people in your community or from relatives?
• 1. Yes
• 2. No 
• 8. DK
• 9. Refused
|___|
1311 At the moment, if your household had a problem and needed assistance to 
perform work therein, would you be able to get it from relatives living elsewhere?
• 1. Yes
• 2. No 
• 8. DK
• 9. Refused
|___|
1312 At the moment, if your household had a problem and needed assistance to 
perform work therein, would you be able to get it from people in your community 
who are not your relatives?
• 1. Yes
• 2. No 
• 8. DK
• 9. Refused
|___|
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N° QUESTION WORDING ANSWERS CODES
1313 At the moment, if your household had a problem and needed assistance to 
perform work therein, would you be able to get it from people living elsewhere 
who are not your relatives?
• 1. Yes
• 2. No 
• 8. DK
• 9. Refused
|___|
1314 Compared to one year ago has the number of people you think you could ask for 
assistance to perform work in your household:
• 1. Increased
• 2. Stayed the same
• 3. Decreased
• 8. DK
• 9. Refused
|___|
1315a Has your household given assistance to relatives, neighbors or friends in the past 
12 months?
• 1. Yes
• 2. No 
• 8. DK
• 9. Refused
|___|
1315b What types of assistance has your household given to relatives, neighbors or 
friends in the past 12 months? (Read list)
NB: Use the answer codes, not the answer number. For example: for Q1315b, if 
the household says that they received “Remittances” (Yes =1), put Code “1”, not 
Code “2”, which is the answer number.
1. Zakat................................................................. Yes = 
1 No = 2 |___|
2. Remittances ...................................................... Yes = 
1 No = 2 |___|
3. Gifts/habbanaye (donation of cash/animals to 
people in need) .................................................
Yes = 
1 No = 2 |___|
4. Loans (cash, labor, seeds, animals) ..................... Yes = 
1 No = 2 |___|
5. Restocking of poorer relatives ............................. Yes = 
1 No = 2 |___|
6. Sadaqa ............................................................. Yes = 
1 No = 2 |___|
7. Other (specify) ................................................... Yes = 
1 No = 2 |___|
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N° QUESTION WORDING ANSWERS CODES
1316 At the moment, if a relative in this community had a problem and needed money 
for food urgently, would you be able to give money or food?
• 1. Yes
• 2. No 
• 8. DK
• 9. Refused
|___|
1317 At the moment, if a relative outside this community had a problem and needed
money for food urgently, would you be able to give money or food?
• 1. Yes
• 2. No 
• 8. DK
• 9. Refused
|___|
1318 At the moment, if someone who is not your relative, but lives in this community 
had a problem and needed money for food urgently, would you be able to give 
money or food?
• 1. Yes
• 2. No 
• 8. DK
• 9. Refused
|___|
1319 At the moment, if someone who is not your relative and lives someplace else had
a problem and needed money for food urgently, would you be able to give money 
or food?
• 1. Yes
• 2. No 
• 8. DK
• 9. Refused
|___|
1320 Compared to one year ago has your ability to give this type of assistance: • 1. Increased
• 2. Stayed the same
• 3. Decreased
• 8. DK
• 9. Refused
|___|
1321 At the moment, if a relative who lives in this community had a problem and needed
help with his/her work, would you be able to help him/her with it?
• 1. Yes
• 2. No 
• 8. DK
• 9. Refused
|___|
1322 At the moment, if a relative who lives outside this community had a problem and 
needed help with his/her work, would you be able to help him/her with it?
1. Yes
2. No 
8. DK
9. Refused
|___|
1323 At the moment, if a person who is not your relative but lives in this community had
a problem and needed help with his/her work, would you be able to help him/her 
with it?
1. Yes
2. No 
3. DK
4. Refused
|___|
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N° QUESTION WORDING ANSWERS CODES
1324 At the moment, if a person who is not your relative and lives someplace else had
a problem and needed help with his/her work, would you be able to help him/her 
with it?
1. Yes
2. No 
8. DK
9. Refused
|___|
1325 Compared to one year ago has your ability to give this type of assistance: 1. Increased
2. Stayed the same
3. Decreased
8. DK
9. Refused
|___|
CAPACITY-BUILDING SUPPORT
1326 In the last 12 months, have you or anyone in your household ever received any 
vocational (job) or skill training?
1. Yes
2. No 
8. DK
8. Refused
|___|
1327 Who provided the vocational skills training? 1. Government 
2. NGO/Association/Project
3. Private sector
8. DK
9. Refused
|___|
1328 In the last 12 months, have you or anyone in your household ever received any 
business development training?
1. Yes
2. No 
8. DK
9. Refused
|___|
1329 Who provided the business development training? 1. Government 
2. NGO/Association/Project
3. Private sector
8. DK
9. Refused
|___|
1330 In the last 12 months, have you or anyone in your household received any early 
warning training?
1. Yes
|___|
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N° QUESTION WORDING ANSWERS CODES
2. No 
8. DK
9. Refused
1331 Who provided the early warning training? 1. Government 
2. NGO/Association/Project
3. Private sector
8. DK
9. Refused
|___|
1332 In the last 12 months, have you or anyone in your household received any natural 
resource management training?
1. Yes
2. No 
8. DK
9. Refused
|___|
1333 Who provided the natural resource management training? 1. Government 
2. NGO/Association/Project
3. Private sector
8. DK
9. Refused
|___|
1334 In the last 12 months, have you or anyone in your household received seed 
packets/starter packets from the government or NGOs?
1. Yes
2. No 
3. DK
4. Refused
|___|
1335 Who did you receive them from? 1. Government 
2. NGO/Association/Project
8. DK
9. Refused
|___|
1336 In the last 12 months, have you or anyone in your household received adult 
education (literacy or numeracy or financial education)?
1. Yes
2. No 
8. DK
9. Refused
|___|
1337 Who provided adult education (literacy, numeracy or financial education)? 1. Government 
2. NGO/Association/Project |___|
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N° QUESTION WORDING ANSWERS CODES
3 Private sector
8. DK
9. Refused
1338 In the last 12 months, have you or anyone in your household received training in 
how to use your cell phone to get market information such as prices?
1. Yes
2. No 
8. DK
9. Refused
|___|
1339 Who did you receive training on how to use your cell phone to get market 
information like prices from?
• 1. Government 
• 2. NGO/Association/Project
• 3 Private sector
• 8. DK
• 9. Refused
|___|
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MODULE 14. ASPIRATIONS AND CONFIDENCE TO ADAPT
N° QUESTION WORDING • ANSWER/CODE
1401 Please tell me which one of these views you most agree with. • 1. “Each person is primarily responsible for his/her success or failure in life”.
• 2. “One’s success or failure in life is a matter of his/her destiny”. 
• 3. “One’s success or failure in life is a combination of his/her own efforts and destiny” 
• 8. DK
• 9. Refused
|___|
1402 Please tell me which one of these views you most agree with. • 1. “To be successful, above all one needs to work very hard”. " 
• 2. “To be successful, above all one needs to be lucky”. " 
• 3. “To be successful, above all one needs God”. 
• 8. DK
• 9. Refused
|___|
1403 Are you willing to move somewhere else to improve your life? • 1. Yes
• 2. No 
• 8. DK
• 9. Refused
|___|
1404 Do you agree that one should always follow the advice of the elders? • 1. Yes
• 2. No 
• 8. DK
• 9. Refused
|___|
1405 Do you communicate regularly with at least one person outside the 
village? • 1. Yes
• 2. No 
• 8. DK
|___|
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N° QUESTION WORDING • ANSWER/CODE
• 9. Refused
1406 In the last 7 days, have you engaged in any economic activities with 
members of other groups of people outside your community? For 
example, farming, trading, employment, borrowing or lending money. 
• 1. Yes
• 2. No 
• 8. DK
• 9. Refused
|___|
1407 How many times in the last 30 days have you gotten together with people 
to have food or drinks, either in their home or in a public place?
88= DK ; 99 = Refused
|___|___|
1408 How many times in the last 30 days have you attended a church/mosque 
or other religious service?
888= DK ; 999 = Refused
|____|____|____|
1409 In the last 12 months, how many times have you stayed more than 2 days 
outside this village?
88= DK ; 99 = Refused
|___|___|
1410 Do you think men and women should have equal access to social, 
economic and political opportunities? • 1. Yes
• 2. No 
• 8. DK
• 9. Refused
|___|
1411 Have you successfully engaged with a local authority body to effect a 
change in your village during the past year? • 1. Yes
• 2. No 
• 8. DK
• 9. Refused
|___|
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Below is a series of statements that you may agree or disagree with. Using the scales below indicate your agreement with 
each item. 
N° QUESTION WORDING
CODES/ANSWERS
Strongly 
disagree
Disagre
e
Slightly 
disagree
Slightly 
agree Agree Strongly 
agree
DK Refuse
d
1412 I feel like what happens in my life is mostly determined by powerful 
people. 1 2 3 4 5 6 8 9
1413 My experience in my life has been that what is going to happen will 
happen. 1 2 3 4 5 6 8 9
1414 My life is mainly controlled by other powerful people. 1 2 3 4 5 6 8 9
1415 It is not always wise for me to plan too far ahead because many things 
turn out to be a matter of good or bad fortune. 1 2 3 4 5 6 8 9
1416 I can mostly determine what will happen in my life. 1 2 3 4 5 6 8 9
1417 When I get what I want, it is usually because I worked hard for it. 1 2 3 4 5 6 8 9
1418 My life is determined by my own actions. 1 2 3 4 5 6 8 9
1419 Most people are basically honest. 1 2 3 4 5 6 8 9
1420 Most people can be trusted. 1 2 3 4 5 6 8 9
1421 I trust my neighbors to look after my house if I am away. 1 2 3 4 5 6 8 9
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C.2: Gender Questionnaire 
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INFORMED CONSENT SIGNATURE PAGE
Thank you for the opportunity to speak with you. We are from SAREL, a USAID-funded project in partnership with the Governments of Niger and Burkina Faso. We are 
conducting a survey to learn about agriculture, food security, food consumption, nutrition and wellbeing of households in this area. Your household has been selected to 
participate in an interview on topics such as your dwelling characteristics, household expenditures and assets, household food consumption and nutrition of children. The 
survey includes questions about the household generally, and questions about individuals within your household, if applicable. These questions in total will take approximately 
one and half hours (1h30) to complete and your participation is entirely voluntary. If you agree to participate, you can choose to stop at any time or to skip any questions you 
do not want to answer. Your answers will be completely confidential; we will not share information that identifies you with anyone. 
Do you have any questions about the survey or what I have just said? If in the future you have any questions regarding the survey and the interview, or concerns or complaints 
we welcome you to contact the USAID/SAREL Project (Stephen Reid | Chief of Party, Sahel Resilience Learning (SAREL) Project / 
Tel. : 227-9663-0291 |227-9025-7197 / sreid@sarelproject.com ). We will leave one copy of this form for you so that you will have record of this contact information and 
about the study.
Name
Consent to participate in 
survey (Insert code) Signature or mark
YES=1 NO=2
1 |___|
2 |___|
3 |___|
4 |___|
5 |___|
6 |___|
7 |___|
8 |___|
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9 |___|
10 |___|
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MODULE G2: ROLE IN DECISION MAKING ON PRODUCTION AND INCOME-GENERATING ACTIVITIES
Activity 
Code Activity Description
QUESTION WORDING AND NUMBER
Did your
household 
conduct this 
activity (activity 
name) over the 
past 12 months?
Yes = 1
No = 2
If the answer is 
“NO”, go to the 
next activity
Did you (singular) participate in 
an [ACTIVITY] over the past 12 
months (i.e., during [on/two] 
cropping season(s))?
Yes ..... 1
No.......2 >> skip to 
next activity
What was your level of 
input in the decision 
making on 
[ACTIVITY]?
1. None; 
2. Input in very few 
decisions; 
3. Input in some decisions; 
4. Input in most decisions; 
5. Input in all decisions; 
What was your level of 
input in the decision making 
on the use of revenue 
generated by [ACTIVITY]?
1. None; 
2. Input in very few decisions; 
3. Input in some decisions; 
4. Input in most decisions; 
5. Input in all decisions; 
G2.01a G2.01 G2.02 G2.03
A Food production: crops primarily grown for household 
consumption |___| |___| |___| |___|
B Cash crops: crops primarily grown for sale in markets |___| |___| |___| |___|
C Livestock |___| |___| |___| |___|
D Non-agricultural economic activities: small business, 
self-employment, purchase and sale |___| |___| |___| |___|
E Employment income/salary: work in kind or 
monetary in agriculture and other paid work |___| |___| |___| |___|
F Fishing and fish pond |___| |___| |___| |___|
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MODULE G3: ACCESS TO PRODUCTIVE CAPITAL 
N° Productive Capital
QUESTION WORDING AND NUMBER
Is there anyone in 
your household who 
currently owns 
[item]?
Yes = 1
No = 2
DK = 8
Refused = 9
How many [ITEM] 
does your 
household 
currently own?
01. Myself
02. Partner/spouse
03. Myself and partner/spouse together
04. Another household member
05. Myself and (an)other household member(s)
06. Partner/spouse and (an)other household 
member(s)
07. Someone (or group of people) from outside the 
household
08. Myself and another external person
09. Partner/spouse and another external person
10. Myself, partner/spouse and another external 
person 
88. DK
99. Refused
According to 
you, who owns 
most of [ITEM]?
Most of the time, 
who may decide to 
sell [ITEM], 
according to you?
Most of the time, 
who may decide to 
give [ITEM] away, 
according to you?
Most of the time, who 
may decide to 
mortgage or lease 
[ITEM], according to 
you?
Who contributes the 
most in decisions 
about a new purchase 
of [ITEM]?
Productive Capital G301 G302 G303 G304 G305 G306 G307
A Farming land (smallholdings/lots) |___| |___|___|___| |___|___| |___|___| |___|___| |___|___| |___|___|
B Rearing large livestock (cattle, camels, 
donkeys, horses) |___| |___|___|___| |___|___| |___|___| |___|___| |___|___| |___|___|
C Rearing small livestock (goats, pigs, 
sheep) |___| |___|___|___| |___|___| |___|___| |___|___| |___|___| |___|___|
D Chickens, duck, turkeys, pigeons, 
other poultry |___| |___|___|___| |___|___| |___|___| |___|___| |___|___| |___|___|
E Fish pond or fishing gear |___| |___|___|___| |___|___| |___|___| |___|___| |___|___| |___|___|
F Farming equipment (non￾mechanized) |___| |___|___|___| |___|___| |___|___| |___|___| |___|___| |___|___|
G Farming equipment (mechanized) |___| |___|___|___| |___|___| |___|___| |___|___| |___|___| |___|___|
H Non-agricultural economic equipment |___| |___|___|___| |___|___|
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N° Productive Capital
QUESTION WORDING AND NUMBER
Is there anyone in 
your household who 
currently owns 
[item]?
Yes = 1
No = 2
DK = 8
Refused = 9
How many [ITEM] 
does your 
household 
currently own?
01. Myself
02. Partner/spouse
03. Myself and partner/spouse together
04. Another household member
05. Myself and (an)other household member(s)
06. Partner/spouse and (an)other household 
member(s)
07. Someone (or group of people) from outside the 
household
08. Myself and another external person
09. Partner/spouse and another external person
10. Myself, partner/spouse and another external 
person 
88. DK
99. Refused
According to 
you, who owns 
most of [ITEM]?
Most of the time, 
who may decide to 
sell [ITEM], 
according to you?
Most of the time, 
who may decide to 
give [ITEM] away, 
according to you?
Most of the time, who 
may decide to 
mortgage or lease 
[ITEM], according to 
you?
Who contributes the 
most in decisions 
about a new purchase 
of [ITEM]?
I House (and other buildings) |___| |___|___|___| |___|___| |___|___| |___|___| |___|___| |___|___|
J Long-lasting large consumer goods 
(refrigerator, TV) |___| |___|___|___| |___|___| |___|___| |___|___| |___|___| |___|___|
K Long-lasting large consumer goods 
(radio, pot, utensils) |___| |___|___|___| |___|___| |___|___| |___|___| |___|___| |___|___|
L Cellular phone |___| |___|___|___| |___|___| |___|___| |___|___| |___|___| |___|___|
M
Other land not used for agricultural 
needs (smallholdings, residential and 
commercial land)
|___| |___|___|___| |___|___| |___|___| |___|___| |___|___| |___|___|
N Means of transportation (bicycle, 
motorcycle, car, canoe) |___| |___|___|___| |___|___|
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MODULE G3 (ct'd): ACCESS TO CREDIT 
Credit 
Source 
Code
Names of Credit Source
QUESTION WORDING AND NUMBER
Did anyone in your household 
take out a loan or borrow 
cash/kind from [SOURCE] 
over the past 12 months?
1 = Yes, cash
2 = Yes, in kind
3 = Yes, cash and in kind
4 = No (if no, skip to next credit 
source)
8 = DK (if DK, skip to next credit 
source)
9 = Refused (if refused, skip to 
next credit source)
Who made the decision from 
[SOURCE]?
01. Myself
02. Partner/spouse
03. Myself and partner/spouse together
04. Another household member
05. Myself and other household 
member(s)
06. Partner/spouse and the other 
household members 
07. Someone (or group of people) from 
outside the household 
08. Myself and other external persons
09. Partner/spouse and other external 
persons
10. Myself, partner/spouse and another 
external person.
88 = Don’t know
99 = Refused
Who makes the decision on what to 
do with the money/item borrowed 
from [SOURCE]?
01. Myself
02. Partner/spouse
03. Myself and partner/spouse together
04. Another household member
05. Myself and other household member(s)
06. Partner/spouse and the other 
household members 
07. Someone (or group of people) from 
outside the household 
08. Myself and other external persons
09. Partner/spouse and other external 
persons
10. Myself, partner/spouse and another 
external person.
88 = Don’t know (If DK, go to the next 
source of credit)
99 = Refused (if refused, go to the next 
source of credit)
G308 G309 G310
A Non-governmental organization (NGO) |___| |___|___| |___|___|
B Informal lender |___| |___|___| |___|___|
C Formal lender (bank/financial institution) |___| |___|___| |___|___|
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D Friends or relatives |___| |___|___| |___|___|
E Microfinance run by associations or 
VSLAs/SACCOs loan/swap transaction |___| |___|___| |___|___|
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MODULE G4: DECISION MAKING 
N° ASPECTS OF HOUSEHOLD LIFE
QUESTION WORDING AND NUMBER
When decisions are made on the following aspects of the 
household life, who makes the decision?
01. Husband
02. Myself (if Myself, go to the next aspect)
03. Husband and myself
04. Another household member
05. Jointly with another household member
06. Jointly with another person from outside the household
07. Another person from outside the household
08. No decision
09. Activity not carried out by the household (go to the next aspect)
88. DK
99. Refused
To what extent do you think you can make 
your own decisions on these aspects of the 
household life if you want (wanted)? 
1. Not at all
2. Small extent
3. Medium extent
4. To a high extent
G4.01 G4.02
A Obtaining inputs for agricultural production |___|___| |___|
B Type of crops to be grown |___|___| |___|
C Taking crops to the market (or not) |___|___| |___|
D Livestock |___|___| |___|
E Your (singular) own income or paid job |___|___| |___|
F Major household expenses (such as a large 
household appliance like a refrigerator) |___|___| |___|
G Minor household expenses (such as food 
for daily consumption and other 
household needs)
|___|___| |___|
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H Migration/exodus for paid labor |___|___| |___|
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MODULE G5: USE OF CONTRACEPTION
Now, I would to talk about family planning with you; the various ways or methods a couple may use to delay or avoid 
pregnancy.
G5.01 Have you heard of methods a couple may use to delay or avoid 
pregnancy? 
 1 = yes
2 = no
8 = DK
9 = Refused
|___|
IF RESPONDENT HAS NEVER HEARD OF METHODS THAT A COUPLE MAY USE TO AVOID PREGNANCY, STOP 
THE INTERVIEW HERE
N° QUESTIONS CLASSIFICATION OF CODES Type
G5.02
Are you and your husband/partner doing 
anything or are you currently using any 
method to delay or avoid pregnancy?
1. Yes
2. No
3. N/A
8. DK
9. Refused
|___|
Section 5: DECISION MAKING PROCESS
Now, I would like to discuss the way decisions are made in your household
N° QUESTIONS CODING CLASSIFICATION
G5.03 In your opinion, who should decide the number of children 
a couple should have?
SEVERAL ANSWERS ARE POSSIBLE.
1. Husband/partner
................................................................................ |__|
2. Wife
................................................................................ |__|
3. Husband/partner and wife together
................................................................................ |__|
4. Husband/partner and wife and family members
................................................................................ |__|
5. Family elders
................................................................................ |__|
6. Service provider(s)
................................................................................ |__|
7. Other (specify)
................................................................................ |__|
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8. DK
................................................................................ |__|
9. Refused
................................................................................ |__|
G5.04 In your opinion, who should decide the birth control 
method a couple should use?
SEVERAL ANSWERS ARE POSSIBLE.
1. Husband/partner
................................................................................ |__|
2. Wife
................................................................................ |__|
3. Husband/partner and wife together
................................................................................ |__|
4. Husband/partner and wife and family members
................................................................................ |__|
5. Family elders
................................................................................ |__|
6. Service provider(s)
................................................................................ |__|
7. Other (specify)
................................................................................ |__|
8. DK
................................................................................ |__|
9. Refused
................................................................................ |__|
G5.05 SEE QUESTION #502: IF THE COUPLE CURRENTLY 
USE A BIRTH CONTROL METHOD
Who decided on the choice of the birth control method that 
you or your husband/partner is currently using?
1. Husband/partner
2. Myself
3. Husband/partner and wife together
4. Husband/partner and wife and family members
5. Family elders
6. Service provider(s)
7. Other (specify)
8. DK
9. Refused
G5.06 IF THE COUPLE CURRENTLY USE NO BIRTH 
CONTROL METHOD
Who decided not to use any birth control 
method?
1. Husband/partner
2. Myself
3. Husband/partner and wife together
4. Husband/partner and wife and family members
5. Family elders
6. Service provider(s)
7. Other (specify)
8. DK
9. Refused
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KISH table to select one of the head of household’s wives in a polygamous 
household (where several wives live in the same household) to answer the
GENDER questionnaire
INSTRUCTIONS
1. Check Q204 in the Household questionnaire. If the head of household has more 
than one wife living in the household concerned, use the method described below to 
select one wife to be interviewed.
2. Enter details of all the head of household’s wives who live in the household in the 
table.
3. Check the last digit of the household number (column) on page 1 and circle the 
corresponding number in the column below.
4. See where the last digit of the household number (column) and the number of head 
of household’s wives (range) intersect.
5. The figure in the cell where the range and the column intersect shows which of the 
head of household’s wives should be interviewed for the questionnaire.
For example: If the wife’s number = 3 and the last digit of the household number = 5, 
wife 2 will be selected from the list.
N° Line 
N°
Name Age Last digit of Household Number (see page 1)
1 2 3 4 5 6 7 8 9 0
1 1 1 1 1 1 1 1 1 1 1
2 1 2 1 2 1 2 1 2 1 2
3 1 2 3 1 2 3 1 2 3 3
4 1 2 3 4 1 2 3 4 1 4
5 1 2 3 4 5 1 2 3 4 5
6 1 2 3 4 5 6 4 2 6 1
7 1 2 3 4 5 6 7 1 4 7
8 1 2 3 4 5 6 7 8 4 3
9 1 2 3 4 5 6 7 8 9 2
10 1 2 3 4 5 6 7 8 9 10
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C.3: Household Food Consumption Survey & Child 
Anthropometry Questionnaire
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INFORMED CONSENT SIGNATURE PAGE
Thank you for the opportunity to speak with you. We are from SAREL, a USAID-funded project in partnership with the Governments of Niger and Burkina Faso. 
We are conducting a survey to learn about agriculture, food security, food consumption, nutrition and wellbeing of households in this area. Your household has 
been selected to participate in an interview on topics such as your dwelling characteristics, household expenditures and assets, household food consumption 
and nutrition of children. The survey includes questions about the household generally, and questions about individuals within your household, if applicable. 
These questions in total will take approximately one and half hours (1h30) to complete and your participation is entirely voluntary. If you agree to participate, 
you can choose to stop at any time or to skip any questions you do not want to answer. Your answers will be completely confidential; we will not share information 
that identifies you with anyone. 
Do you have any questions about the survey or what I have just said? If in the future you have any questions regarding the survey and the interview, or concerns 
or complaints we welcome you to contact the USAID/SAREL Project (Stephen Reid | Chief of Party, Sahel Resilience Learning (SAREL) Project / 
Tel. : 227-9663-0291 |227-9025-7197 / sreid@sarelproject.com ). We will leave one copy of this form for you so that you will have record of this contact information 
and about the study.
Name
Consent to participate in 
survey (Insert code) Signature or mark
YES=1 NO=2
1 |___|
2 |___|
3 |___|
4 |___|
5 |___|
6 |___|
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7 |___|
8 |___|
9 |___|
10 |___|
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MODULE 8_E1. FOOD CONSUMPTION OVER PAST 7 DAYS
Ask these questions about the consumption/expenditures of all household members. Ask whoever is most knowledgeable about the food the 
household members have eaten over the past 7 days, as well as any non-food items that household members have bought.
Note: Quantities are often reported in local units of measure. Any unit listed must be able to be converted to a standardized unit. This 
conversion will happen during data analysis. It should not be done in the field by the enumerator.
INCLUDE FOOD EATEN BOTH COMMUNALLY IN 
THE HOUSEHOLD AND SEPARATELY BY 
INDIVIDUAL HOUSEHOLD MEMBERS, BOTH 
INSIDE AND OUTSIDE THE HOME
Over the past 
one week (7 
days), did you or 
others in your 
household eat 
any [food]?
How much [food] in 
total did your 
household eat in the 
past week?
How much [food] 
came from 
purchases made in 
the last 7 days?
How much did you spend on 
[food] that was eaten in the 
last 7 days? 
If family ate part but not
all of something they 
purchased, estimate only 
cost of what was 
consumed 
How much of the 
[food] eaten in the last 
7 days came from 
own-production?
How much of the 
[food] eaten in the 
last 7 days came 
from gifts and other 
sources?
Yes = 1
No = 2
Code E1.01
E1.02a
Quantity
E1.02b
Unit
E1.03a
Quantity
E1.03b
Unit
E1.04
(CFA F)
E1.05a
Quantity
E1.05b
Unit
E1.06a
Quantity
E1.06b
Unit
Cereals, grains and cereal products 
(Category 1)
101 Maize flour |___| |__|__|__| |___|___| |__|__|__| |___|___| |___|___|___|___|___|___|___| |__|__|__| |___|___| |__|__|__| |___|___|
102 Wheat flour |___| |__|__|__| |___|___| |__|__|__| |___|___| |___|___|___|___|___|___|___| |__|__|__| |___|___| |__|__|__| |___|___|
103 Cassava flour (attiéké, tapioca, gari, etc.) |___| |__|__|__| |___|___| |__|__|__| |___|___| |___|___|___|___|___|___|___| |__|__|__| |___|___| |__|__|__| |___|___|
104 Beans four (cowpea flour) |___| |__|__|__| |___|___| |__|__|__| |___|___| |___|___|___|___|___|___|___| |__|__|__| |___|___| |__|__|__| |___|___|
105 Maize |___| |__|__|__| |___|___| |__|__|__| |___|___| |___|___|___|___|___|___|___| |__|__|__| |___|___| |__|__|__| |___|___|
106 Millet |___| |__|__|__| |___|___| |__|__|__| |___|___| |___|___|___|___|___|___|___| |__|__|__| |___|___| |__|__|__| |___|___|
107 Rice |___| |__|__|__| |___|___| |__|__|__| |___|___| |___|___|___|___|___|___|___| |__|__|__| |___|___| |__|__|__| |___|___|
108 Sorghum |___| |__|__|__| |___|___| |__|__|__| |___|___| |___|___|___|___|___|___|___| |__|__|__| |___|___| |__|__|__| |___|___|
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INCLUDE FOOD EATEN BOTH COMMUNALLY IN 
THE HOUSEHOLD AND SEPARATELY BY 
INDIVIDUAL HOUSEHOLD MEMBERS, BOTH 
INSIDE AND OUTSIDE THE HOME
Over the past 
one week (7 
days), did you or 
others in your 
household eat 
any [food]?
How much [food] in 
total did your 
household eat in the 
past week?
How much [food] 
came from 
purchases made in 
the last 7 days?
How much did you spend on 
[food] that was eaten in the 
last 7 days? 
If family ate part but not
all of something they 
purchased, estimate only 
cost of what was 
consumed 
How much of the 
[food] eaten in the last 
7 days came from 
own-production?
How much of the 
[food] eaten in the 
last 7 days came 
from gifts and other 
sources?
Yes = 1
No = 2
Code E1.01
E1.02a
Quantity
E1.02b
Unit
E1.03a
Quantity
E1.03b
Unit
E1.04
(CFA F)
E1.05a
Quantity
E1.05b
Unit
E1.06a
Quantity
E1.06b
Unit
109 Fonio |___| |__|__|__| |___|___| |__|__|__| |___|___| |___|___|___|___|___|___|___| |__|__|__| |___|___| |__|__|__| |___|___|
110 Other cereals |___| |__|__|__| |___|___| |__|__|__| |___|___| |___|___|___|___|___|___|___| |__|__|__| |___|___| |__|__|__| |___|___|
111 Pasta (spaghetti, macaroni, pasta) |___| |__|__|__| |___|___| |__|__|__| |___|___| |___|___|___|___|___|___|___| |__|__|__| |___|___| |__|__|__| |___|___|
112 Bread (wheat, maize) |___| |__|__|__| |___|___| |__|__|__| |___|___| |___|___|___|___|___|___|___| |__|__|__| |___|___| |__|__|__| |___|___|
113 Biscuits |___| |__|__|__| |___|___| |__|__|__| |___|___| |___|___|___|___|___|___|___| |__|__|__| |___|___| |__|__|__| |___|___|
114 Fritter, fried dough |___| |__|__|__| |___|___| |__|__|__| |___|___| |___|___|___|___|___|___|___| |__|__|__| |___|___| |__|__|__| |___|___|
115 Flat cake, griddlecake (rice, corn, etc.) |___| |__|__|__| |___|___| |__|__|__| |___|___| |___|___|___|___|___|___|___| |__|__|__| |___|___| |__|__|__| |___|___|
116 Other pastries |___| |__|__|__| |___|___| |__|__|__| |___|___| |___|___|___|___|___|___|___| |__|__|__| |___|___| |__|__|__| |___|___|
Meat, fish and eggs (Category 2)
201 Beef |___| |__|__|__| |___|___| |__|__|__| |___|___| |___|___|___|___|___|___|___| |__|__|__| |___|___| |__|__|__| |___|___|
202 Goat |___| |__|__|__| |___|___| |__|__|__| |___|___| |___|___|___|___|___|___|___| |__|__|__| |___|___| |__|__|__| |___|___|
203 Mutton |___| |__|__|__| |___|___| |__|__|__| |___|___| |___|___|___|___|___|___|___| |__|__|__| |___|___| |__|__|__| |___|___|
204 Poultry/chicken |___| |__|__|__| |___|___| |__|__|__| |___|___| |___|___|___|___|___|___|___| |__|__|__| |___|___| |__|__|__| |___|___|
205 Camel |___| |__|__|__| |___|___| |__|__|__| |___|___| |___|___|___|___|___|___|___| |__|__|__| |___|___| |__|__|__| |___|___|
206 Pork |___| |__|__|__| |___|___| |__|__|__| |___|___| |___|___|___|___|___|___|___| |__|__|__| |___|___| |__|__|__| |___|___|
207 Eggs |___| |__|__|__| |___|___| |__|__|__| |___|___| |___|___|___|___|___|___|___| |__|__|__| |___|___| |__|__|__| |___|___|
208 Bush meat |___| |__|__|__| |___|___| |__|__|__| |___|___| |___|___|___|___|___|___|___| |__|__|__| |___|___| |__|__|__| |___|___|
209 Other meat |___| |__|__|__| |___|___| |__|__|__| |___|___| |___|___|___|___|___|___|___| |__|__|__| |___|___| |__|__|__| |___|___|
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INCLUDE FOOD EATEN BOTH COMMUNALLY IN 
THE HOUSEHOLD AND SEPARATELY BY 
INDIVIDUAL HOUSEHOLD MEMBERS, BOTH 
INSIDE AND OUTSIDE THE HOME
Over the past 
one week (7 
days), did you or 
others in your 
household eat 
any [food]?
How much [food] in 
total did your 
household eat in the 
past week?
How much [food] 
came from 
purchases made in 
the last 7 days?
How much did you spend on 
[food] that was eaten in the 
last 7 days? 
If family ate part but not
all of something they 
purchased, estimate only 
cost of what was 
consumed 
How much of the 
[food] eaten in the last 
7 days came from 
own-production?
How much of the 
[food] eaten in the 
last 7 days came 
from gifts and other 
sources?
Yes = 1
No = 2
Code E1.01
E1.02a
Quantity
E1.02b
Unit
E1.03a
Quantity
E1.03b
Unit
E1.04
(CFA F)
E1.05a
Quantity
E1.05b
Unit
E1.06a
Quantity
E1.06b
Unit
210 Fresh fish |___| |__|__|__| |___|___| |__|__|__| |___|___| |___|___|___|___|___|___|___| |__|__|__| |___|___| |__|__|__| |___|___|
211 Smoked fish |___| |__|__|__| |___|___| |__|__|__| |___|___| |___|___|___|___|___|___|___| |__|__|__| |___|___| |__|__|__| |___|___|
212 Dried fish |___| |__|__|__| |___|___| |__|__|__| |___|___| |___|___|___|___|___|___|___| |__|__|__| |___|___| |__|__|__| |___|___|
213 Tinned fish |___| |__|__|__| |___|___| |__|__|__| |___|___| |___|___|___|___|___|___|___| |__|__|__| |___|___| |__|__|__| |___|___|
214 Other (specify) |___| |__|__|__| |___|___| |__|__|__| |___|___| |___|___|___|___|___|___|___| |__|__|__| |___|___| |__|__|__| |___|___|
Fruit (Category 3)
301 Mango |___| |__|__|__| |___|___| |__|__|__| |___|___| |___|___|___|___|___|___|___| |__|__|__| |___|___| |__|__|__| |___|___|
302 Pineapple |___| |__|__|__| |___|___| |__|__|__| |___|___| |___|___|___|___|___|___|___| |__|__|__| |___|___| |__|__|__| |___|___|
303 Orange |___| |__|__|__| |___|___| |__|__|__| |___|___| |___|___|___|___|___|___|___| |__|__|__| |___|___| |__|__|__| |___|___|
304 Other citrus fruits (tangerine, lemon 
grapefruit) |___| |__|__|__| |___|___| |__|__|__| |___|___| |___|___|___|___|___|___|___| |__|__|__| |___|___| |__|__|__| |___|___|
305 Banana |___| |__|__|__| |___|___| |__|__|__| |___|___| |___|___|___|___|___|___|___| |__|__|__| |___|___| |__|__|__| |___|___|
306 Watermelon |___| |__|__|__| |___|___| |__|__|__| |___|___| |___|___|___|___|___|___|___| |__|__|__| |___|___| |__|__|__| |___|___|
307 Dates |___| |__|__|__| |___|___| |__|__|__| |___|___| |___|___|___|___|___|___|___| |__|__|__| |___|___| |__|__|__| |___|___|
308 Sugarcane |___| |__|__|__| |___|___| |__|__|__| |___|___| |___|___|___|___|___|___|___| |__|__|__| |___|___| |__|__|__| |___|___|
309 Melon |___| |__|__|__| |___|___| |__|__|__| |___|___| |___|___|___|___|___|___|___| |__|__|__| |___|___| |__|__|__| |___|___|
310 Palm-tree (fruit) |___| |__|__|__| |___|___| |__|__|__| |___|___| |___|___|___|___|___|___|___| |__|__|__| |___|___| |__|__|__| |___|___|
311 Kola nut |___| |__|__|__| |___|___| |__|__|__| |___|___| |___|___|___|___|___|___|___| |__|__|__| |___|___| |__|__|__| |___|___|
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INCLUDE FOOD EATEN BOTH COMMUNALLY IN 
THE HOUSEHOLD AND SEPARATELY BY 
INDIVIDUAL HOUSEHOLD MEMBERS, BOTH 
INSIDE AND OUTSIDE THE HOME
Over the past 
one week (7 
days), did you or 
others in your 
household eat 
any [food]?
How much [food] in 
total did your 
household eat in the 
past week?
How much [food] 
came from 
purchases made in 
the last 7 days?
How much did you spend on 
[food] that was eaten in the 
last 7 days? 
If family ate part but not
all of something they 
purchased, estimate only 
cost of what was 
consumed 
How much of the 
[food] eaten in the last 
7 days came from 
own-production?
How much of the 
[food] eaten in the 
last 7 days came 
from gifts and other 
sources?
Yes = 1
No = 2
Code E1.01
E1.02a
Quantity
E1.02b
Unit
E1.03a
Quantity
E1.03b
Unit
E1.04
(CFA F)
E1.05a
Quantity
E1.05b
Unit
E1.06a
Quantity
E1.06b
Unit
312 Cactus fruit |___| |__|__|__| |___|___| |__|__|__| |___|___| |___|___|___|___|___|___|___| |__|__|__| |___|___| |__|__|__| |___|___|
313 Guava |___| |__|__|__| |___|___| |__|__|__| |___|___| |___|___|___|___|___|___|___| |__|__|__| |___|___| |__|__|__| |___|___|
314 Strawberry |___| |__|__|__| |___|___| |__|__|__| |___|___| |___|___|___|___|___|___|___| |__|__|__| |___|___| |__|__|__| |___|___|
315 Other (specify) |___| |__|__|__| |___|___| |__|__|__| |___|___| |___|___|___|___|___|___|___| |__|__|__| |___|___| |__|__|__| |___|___|
Milk and Dairy Products 
(Category 4)
401 Fresh milk |___| |__|__|__| |___|___| |__|__|__| |___|___| |___|___|___|___|___|___|___| |__|__|__| |___|___| |__|__|__| |___|___|
402 Curdled milk |___| |__|__|__| |___|___| |__|__|__| |___|___| |___|___|___|___|___|___|___| |__|__|__| |___|___| |__|__|__| |___|___|
403 Powder milk |___| |__|__|__| |___|___| |__|__|__| |___|___| |___|___|___|___|___|___|___| |__|__|__| |___|___| |__|__|__| |___|___|
404 Cheese |___| |__|__|__| |___|___| |__|__|__| |___|___| |___|___|___|___|___|___|___| |__|__|__| |___|___| |__|__|__| |___|___|
405 Butter |___| |__|__|__| |___|___| |__|__|__| |___|___| |___|___|___|___|___|___|___| |__|__|__| |___|___| |__|__|__| |___|___|
406 Yogurt (Solani, etc.) |___| |__|__|__| |___|___| |__|__|__| |___|___| |___|___|___|___|___|___|___| |__|__|__| |___|___| |__|__|__| |___|___|
407 Other dairy products |___| |__|__|__| |___|___| |__|__|__| |___|___| |___|___|___|___|___|___|___| |__|__|__| |___|___| |__|__|__| |___|___|
Market garden produce (Category 5)
501 Onion |___| |__|__|__| |___|___| |__|__|__| |___|___| |___|___|___|___|___|___|___| |__|__|__| |___|___| |__|__|__| |___|___|
502 Lettuce (salad) |___| |__|__|__| |___|___| |__|__|__| |___|___| |___|___|___|___|___|___|___| |__|__|__| |___|___| |__|__|__| |___|___|
503 Cabbage |___| |__|__|__| |___|___| |__|__|__| |___|___| |___|___|___|___|___|___|___| |__|__|__| |___|___| |__|__|__| |___|___|
504 Eggplant |___| |__|__|__| |___|___| |__|__|__| |___|___| |___|___|___|___|___|___|___| |__|__|__| |___|___| |__|__|__| |___|___|
Sahel Resilience Learning (SAREL)—RISE Midline Quantitative Survey Report
October 2017 (Approved, Feb. 2018) 275
INCLUDE FOOD EATEN BOTH COMMUNALLY IN 
THE HOUSEHOLD AND SEPARATELY BY 
INDIVIDUAL HOUSEHOLD MEMBERS, BOTH 
INSIDE AND OUTSIDE THE HOME
Over the past 
one week (7 
days), did you or 
others in your 
household eat 
any [food]?
How much [food] in 
total did your 
household eat in the 
past week?
How much [food] 
came from 
purchases made in 
the last 7 days?
How much did you spend on 
[food] that was eaten in the 
last 7 days? 
If family ate part but not
all of something they 
purchased, estimate only 
cost of what was 
consumed 
How much of the 
[food] eaten in the last 
7 days came from 
own-production?
How much of the 
[food] eaten in the 
last 7 days came 
from gifts and other 
sources?
Yes = 1
No = 2
Code E1.01
E1.02a
Quantity
E1.02b
Unit
E1.03a
Quantity
E1.03b
Unit
E1.04
(CFA F)
E1.05a
Quantity
E1.05b
Unit
E1.06a
Quantity
E1.06b
Unit
505 Carrot |___| |__|__|__| |___|___| |__|__|__| |___|___| |___|___|___|___|___|___|___| |__|__|__| |___|___| |__|__|__| |___|___|
506 Green beans |___| |__|__|__| |___|___| |__|__|__| |___|___| |___|___|___|___|___|___|___| |__|__|__| |___|___| |__|__|__| |___|___|
507 Cucumber |___| |__|__|__| |___|___| |__|__|__| |___|___| |___|___|___|___|___|___|___| |__|__|__| |___|___| |__|__|__| |___|___|
508 Field peas |___| |__|__|__| |___|___| |__|__|__| |___|___| |___|___|___|___|___|___|___| |__|__|__| |___|___| |__|__|__| |___|___|
509 Squash and zucchini |___| |__|__|__| |___|___| |__|__|__| |___|___| |___|___|___|___|___|___|___| |__|__|__| |___|___| |__|__|__| |___|___|
510 Fresh tomato |___| |__|__|__| |___|___| |__|__|__| |___|___| |___|___|___|___|___|___|___| |__|__|__| |___|___| |__|__|__| |___|___|
511 Dried tomato |___| |__|__|__| |___|___| |__|__|__| |___|___| |___|___|___|___|___|___|___| |__|__|__| |___|___| |__|__|__| |___|___|
512 Dried okra |___| |__|__|__| |___|___| |__|__|__| |___|___| |___|___|___|___|___|___|___| |__|__|__| |___|___| |__|__|__| |___|___|
513 Dried beans |___| |__|__|__| |___|___| |__|__|__| |___|___| |___|___|___|___|___|___|___| |__|__|__| |___|___| |__|__|__| |___|___|
514 Vouandzou |___| |__|__|__| |___|___| |__|__|__| |___|___| |___|___|___|___|___|___|___| |__|__|__| |___|___| |__|__|__| |___|___|
515 Other dried vegetables |___| |__|__|__| |___|___| |__|__|__| |___|___| |___|___|___|___|___|___|___| |__|__|__| |___|___| |__|__|__| |___|___|
516 In-shell peanuts |___| |__|__|__| |___|___| |__|__|__| |___|___| |___|___|___|___|___|___|___| |__|__|__| |___|___| |__|__|__| |___|___|
517 Peanut kernel |___| |__|__|__| |___|___| |__|__|__| |___|___| |___|___|___|___|___|___|___| |__|__|__| |___|___| |__|__|__| |___|___|
518 Kapok flower (« voaga ») |___| |__|__|__| |___|___| |__|__|__| |___|___| |___|___|___|___|___|___|___| |__|__|__| |___|___| |__|__|__| |___|___|
519 Baobab leaves |___| |__|__|__| |___|___| |__|__|__| |___|___| |___|___|___|___|___|___|___| |__|__|__| |___|___| |__|__|__| |___|___|
520 Moringa leaves |___| |__|__|__| |___|___| |__|__|__| |___|___| |___|___|___|___|___|___|___| |__|__|__| |___|___| |__|__|__| |___|___|
521 Sorrel leaves |___| |__|__|__| |___|___| |__|__|__| |___|___| |___|___|___|___|___|___|___| |__|__|__| |___|___| |__|__|__| |___|___|
522 Yodo (« foye gouto ») |___| |__|__|__| |___|___| |__|__|__| |___|___| |___|___|___|___|___|___|___| |__|__|__| |___|___| |__|__|__| |___|___|
Sahel Resilience Learning (SAREL)—RISE Midline Quantitative Survey Report
October 2017 (Approved, Feb. 2018) 276
INCLUDE FOOD EATEN BOTH COMMUNALLY IN 
THE HOUSEHOLD AND SEPARATELY BY 
INDIVIDUAL HOUSEHOLD MEMBERS, BOTH 
INSIDE AND OUTSIDE THE HOME
Over the past 
one week (7 
days), did you or 
others in your 
household eat 
any [food]?
How much [food] in 
total did your 
household eat in the 
past week?
How much [food] 
came from 
purchases made in 
the last 7 days?
How much did you spend on 
[food] that was eaten in the 
last 7 days? 
If family ate part but not
all of something they 
purchased, estimate only 
cost of what was 
consumed 
How much of the 
[food] eaten in the last 
7 days came from 
own-production?
How much of the 
[food] eaten in the 
last 7 days came 
from gifts and other 
sources?
Yes = 1
No = 2
Code E1.01
E1.02a
Quantity
E1.02b
Unit
E1.03a
Quantity
E1.03b
Unit
E1.04
(CFA F)
E1.05a
Quantity
E1.05b
Unit
E1.06a
Quantity
E1.06b
Unit
523 Other vegetables or leaves |___| |__|__|__| |___|___| |__|__|__| |___|___| |___|___|___|___|___|___|___| |__|__|__| |___|___| |__|__|__| |___|___|
524 Malahia (« Fakkou ») |___| |__|__|__| |___|___| |__|__|__| |___|___| |___|___|___|___|___|___|___| |__|__|__| |___|___| |__|__|__| |___|___|
Sugar, honey, fats, and oil (Category 6)
601 Sugar |___| |__|__|__| |___|___| |__|__|__| |___|___| |___|___|___|___|___|___|___| |__|__|__| |___|___| |__|__|__| |___|___|
602 Honey |___| |__|__|__| |___|___| |__|__|__| |___|___| |___|___|___|___|___|___|___| |__|__|__| |___|___| |__|__|__| |___|___|
603 Palm oil |___| |__|__|__| |___|___| |__|__|__| |___|___| |___|___|___|___|___|___|___| |__|__|__| |___|___| |__|__|__| |___|___|
604 Shea butter |___| |__|__|__| |___|___| |__|__|__| |___|___| |___|___|___|___|___|___|___| |__|__|__| |___|___| |__|__|__| |___|___|
605 Peanut oil |___| |__|__|__| |___|___| |__|__|__| |___|___| |___|___|___|___|___|___|___| |__|__|__| |___|___| |__|__|__| |___|___|
606 Other oils (soy, sesame, maize, etc. to be 
specified) |___| |__|__|__| |___|___| |__|__|__| |___|___| |___|___|___|___|___|___|___| |__|__|__| |___|___| |__|__|__| |___|___|
607 Peanut paste |___| |__|__|__| |___|___| |__|__|__| |___|___| |___|___|___|___|___|___|___| |__|__|__| |___|___| |__|__|__| |___|___|
608 Other (specify) |___| |__|__|__| |___|___| |__|__|__| |___|___| |___|___|___|___|___|___|___| |__|__|__| |___|___| |__|__|__| |___|___|
Beverages and energizers
701 Water |___| |__|__|__| |___|___| |__|__|__| |___|___| |___|___|___|___|___|___|___| |__|__|__| |___|___| |__|__|__| |___|___|
702 Tea |___| |__|__|__| |___|___| |__|__|__| |___|___| |___|___|___|___|___|___|___| |__|__|__| |___|___| |__|__|__| |___|___|
703 Coffee in pot or bag |___| |__|__|__| |___|___| |__|__|__| |___|___| |___|___|___|___|___|___|___| |__|__|__| |___|___| |__|__|__| |___|___|
704 Chocolate |___| |__|__|__| |___|___| |__|__|__| |___|___| |___|___|___|___|___|___|___| |__|__|__| |___|___| |__|__|__| |___|___|
705 Soft drinks/sodas, carbonated drinks |___| |__|__|__| |___|___| |__|__|__| |___|___| |___|___|___|___|___|___|___| |__|__|__| |___|___| |__|__|__| |___|___|
Sahel Resilience Learning (SAREL)—RISE Midline Quantitative Survey Report
October 2017 (Approved, Feb. 2018) 277
INCLUDE FOOD EATEN BOTH COMMUNALLY IN 
THE HOUSEHOLD AND SEPARATELY BY 
INDIVIDUAL HOUSEHOLD MEMBERS, BOTH 
INSIDE AND OUTSIDE THE HOME
Over the past 
one week (7 
days), did you or 
others in your 
household eat 
any [food]?
How much [food] in 
total did your 
household eat in the 
past week?
How much [food] 
came from 
purchases made in 
the last 7 days?
How much did you spend on 
[food] that was eaten in the 
last 7 days? 
If family ate part but not
all of something they 
purchased, estimate only 
cost of what was 
consumed 
How much of the 
[food] eaten in the last 
7 days came from 
own-production?
How much of the 
[food] eaten in the 
last 7 days came 
from gifts and other 
sources?
Yes = 1
No = 2
Code E1.01
E1.02a
Quantity
E1.02b
Unit
E1.03a
Quantity
E1.03b
Unit
E1.04
(CFA F)
E1.05a
Quantity
E1.05b
Unit
E1.06a
Quantity
E1.06b
Unit
706 Fruit juice |___| |__|__|__| |___|___| |__|__|__| |___|___| |___|___|___|___|___|___|___| |__|__|__| |___|___| |__|__|__| |___|___|
707 Local beer (« dolo ») |___| |__|__|__| |___|___| |__|__|__| |___|___| |___|___|___|___|___|___|___| |__|__|__| |___|___| |__|__|__| |___|___|
708 Locally brewed liquor |___| |__|__|__| |___|___| |__|__|__| |___|___| |___|___|___|___|___|___|___| |__|__|__| |___|___| |__|__|__| |___|___|
709 Spirits (whiskey, gin, cognac) |___| |__|__|__| |___|___| |__|__|__| |___|___| |___|___|___|___|___|___|___| |__|__|__| |___|___| |__|__|__| |___|___|
710 Tobacco (chewing, or snuff, smoking) |___| |__|__|__| |___|___| |__|__|__| |___|___| |___|___|___|___|___|___|___| |__|__|__| |___|___| |__|__|__| |___|___|
711 Cigarette |___| |__|__|__| |___|___| |__|__|__| |___|___| |___|___|___|___|___|___|___| |__|__|__| |___|___| |__|__|__| |___|___|
712 Other tisanes and infusions |___| |__|__|__| |___|___| |__|__|__| |___|___| |___|___|___|___|___|___|___| |__|__|__| |___|___| |__|__|__| |___|___|
713 Other (specify) |___| |__|__|__| |___|___| |__|__|__| |___|___| |___|___|___|___|___|___|___| |__|__|__| |___|___| |__|__|__| |___|___|
Spices and miscellaneous (Category 8)
801 Salt |___| |__|__|__| |___|___| |__|__|__| |___|___| |___|___|___|___|___|___|___| |__|__|__| |___|___| |__|__|__| |___|___|
802 Pepper |___| |__|__|__| |___|___| |__|__|__| |___|___| |___|___|___|___|___|___|___| |__|__|__| |___|___| |__|__|__| |___|___|
803 Hot pepper |___| |__|__|__| |___|___| |__|__|__| |___|___| |___|___|___|___|___|___|___| |__|__|__| |___|___| |__|__|__| |___|___|
804 Maggi seasoning |___| |__|__|__| |___|___| |__|__|__| |___|___| |___|___|___|___|___|___|___| |__|__|__| |___|___| |__|__|__| |___|___|
805 « Soumbala » |___| |__|__|__| |___|___| |__|__|__| |___|___| |___|___|___|___|___|___|___| |__|__|__| |___|___| |__|__|__| |___|___|
806 Tomato concentrate |___| |__|__|__| |___|___| |__|__|__| |___|___| |___|___|___|___|___|___|___| |__|__|__| |___|___| |__|__|__| |___|___|
807 Peanut cake (« couracoura », « koulikouli ») |___| |__|__|__| |___|___| |__|__|__| |___|___| |___|___|___|___|___|___|___| |__|__|__| |___|___| |__|__|__| |___|___|
808 Garlic |___| |__|__|__| |___|___| |__|__|__| |___|___| |___|___|___|___|___|___|___| |__|__|__| |___|___| |__|__|__| |___|___|
809 Ginger |___| |__|__|__| |___|___| |__|__|__| |___|___| |___|___|___|___|___|___|___| |__|__|__| |___|___| |__|__|__| |___|___|
Sahel Resilience Learning (SAREL)—RISE Midline Quantitative Survey Report
October 2017 (Approved, Feb. 2018) 278
INCLUDE FOOD EATEN BOTH COMMUNALLY IN 
THE HOUSEHOLD AND SEPARATELY BY 
INDIVIDUAL HOUSEHOLD MEMBERS, BOTH 
INSIDE AND OUTSIDE THE HOME
Over the past 
one week (7 
days), did you or 
others in your 
household eat 
any [food]?
How much [food] in 
total did your 
household eat in the 
past week?
How much [food] 
came from 
purchases made in 
the last 7 days?
How much did you spend on 
[food] that was eaten in the 
last 7 days? 
If family ate part but not
all of something they 
purchased, estimate only 
cost of what was 
consumed 
How much of the 
[food] eaten in the last 
7 days came from 
own-production?
How much of the 
[food] eaten in the 
last 7 days came 
from gifts and other 
sources?
Yes = 1
No = 2
Code E1.01
E1.02a
Quantity
E1.02b
Unit
E1.03a
Quantity
E1.03b
Unit
E1.04
(CFA F)
E1.05a
Quantity
E1.05b
Unit
E1.06a
Quantity
E1.06b
Unit
810 Other spices (to be specified) |___| |__|__|__| |___|___| |__|__|__| |___|___| |___|___|___|___|___|___|___| |__|__|__| |___|___| |__|__|__| |___|___|
Tubers (Category 9)
901 Cassava |___| |__|__|__| |___|___| |__|__|__| |___|___| |___|___|___|___|___|___|___| |__|__|__| |___|___| |__|__|__| |___|___|
902 Yam |___| |__|__|__| |___|___| |__|__|__| |___|___| |___|___|___|___|___|___|___| |__|__|__| |___|___| |__|__|__| |___|___|
903 Irish potato |___| |__|__|__| |___|___| |__|__|__| |___|___| |___|___|___|___|___|___|___| |__|__|__| |___|___| |__|__|__| |___|___|
904 Taro |___| |__|__|__| |___|___| |__|__|__| |___|___| |___|___|___|___|___|___|___| |__|__|__| |___|___| |__|__|__| |___|___|
905 Sweet potato |___| |__|__|__| |___|___| |__|__|__| |___|___| |___|___|___|___|___|___|___| |__|__|__| |___|___| |__|__|__| |___|___|
906 Other tubers (to be specified) |___| |__|__|__| |___|___| |__|__|__| |___|___| |___|___|___|___|___|___|___| |__|__|__| |___|___| |__|__|__| |___|___|
Prepared dishes (Category 10)
1001 Millet ball and milk |___| |___|___|___|___|___|___|___|
1002 Millet ball without milk/milky porridge |___| |___|___|___|___|___|___|___|
1003 Millet and green leaves dish 
(no meat, no fish) |___| |___|___|___|___|___|___|___|
1004 Sorghum and green leaves (no meat, no fish) |___| |___|___|___|___|___|___|___|
1005 Maize and green leaves dish 
(no meat, no fish) |___| |___|___|___|___|___|___|___|
1006 Other millet, sorghum or maize-based dishes 
|___| |___|___|___|___|___|___|___|
1007 Boiled beans |___| |___|___|___|___|___|___|___|
Sahel Resilience Learning (SAREL)—RISE Midline Quantitative Survey Report
October 2017 (Approved, Feb. 2018) 279
INCLUDE FOOD EATEN BOTH COMMUNALLY IN 
THE HOUSEHOLD AND SEPARATELY BY 
INDIVIDUAL HOUSEHOLD MEMBERS, BOTH 
INSIDE AND OUTSIDE THE HOME
Over the past 
one week (7 
days), did you or 
others in your 
household eat 
any [food]?
How much [food] in 
total did your 
household eat in the 
past week?
How much [food] 
came from 
purchases made in 
the last 7 days?
How much did you spend on 
[food] that was eaten in the 
last 7 days? 
If family ate part but not
all of something they 
purchased, estimate only 
cost of what was 
consumed 
How much of the 
[food] eaten in the last 
7 days came from 
own-production?
How much of the 
[food] eaten in the 
last 7 days came 
from gifts and other 
sources?
Yes = 1
No = 2
Code E1.01
E1.02a
Quantity
E1.02b
Unit
E1.03a
Quantity
E1.03b
Unit
E1.04
(CFA F)
E1.05a
Quantity
E1.05b
Unit
E1.06a
Quantity
E1.06b
Unit
1008 Rice and cowpea |___| |___|___|___|___|___|___|___|
1009 Rice and baobab leaves sauce |___| |___|___|___|___|___|___|___|
1010 Rice and tomato sauce |___| |___|___|___|___|___|___|___|
1011 Joloff rice and fish/chicken |___| |___|___|___|___|___|___|___|
1012 Rice and peanut sauce |___| |___|___|___|___|___|___|___|
1013 Pasta with no meat, no chicken, no fish 
|___| |___|___|___|___|___|___|___|
1014 Hot coffee (bought from a seller) |___| |___|___|___|___|___|___|___|
1015 Hot tea, coffee (bought from a seller) |___| |___|___|___|___|___|___|___|
Sahel Resilience Learning (SAREL)—RISE Midline Quantitative Survey Report
October 2017 (Approved, Feb. 2018) 280
MODULE 15: HOUSEHOLD DIETARY DIVERSITY
Ask these questions of whoever is most knowledgeable about the food consumption of household members. Read the list of foods. Choose “yes” if anyone in the 
household ate at least one of the food items under each category. Choose “no” if no one in the household ate the food.
Now I would like to ask you about the types of foods that you or anyone else in your household ate yesterday during the day and at night. 
Please include all food eaten both at your home and away from home.
N° QUESTION WORDING ANSWERS/CODES
1501 Any bread, rice, pasta, fritters, biscuits, or other foods made from millet, sorghum, maize, rice, wheat?
• 1. Yes 
• 2. No 
• 8. DK
• 9. Refused
|___|
1502 Any food made from Irish potato, yam, sweet potato, cassava, taro and other tubers?
• 1. Yes 
• 2. No 
• 8. DK
• 9. Refused
|___|
1503 Any food made with vegetables such as onions, cabbage, green leafy vegetables, gathered wild green leaves, 
tomato, cucumber, mushroom, green pepper, beet root, garlic, or carrots?
• 1. Yes 
• 2. No 
• 8. DK
• 9. Refused
|___|
1504 Any food or fruit juices made from fruits such as mango, banana, oranges, pineapple, papaya, guava, avocado, 
wild fruit, or apple?
• 1. Yes 
• 2. No 
• 8. DK
• 9. Refused
|___|
1505 Any food made from meat such as beef, lamb, goat, wild game, chicken, or other birds, other meats?
• 1. Yes 
• 2. No 
• 8. DK
• 9. Refused
|___|
Sahel Resilience Learning (SAREL)—RISE Midline Quantitative Survey Report
October 2017 (Approved, Feb. 2018) 281
1506 Any eggs?
• 1. Yes 
• 2. No 
• 8. DK
• 9. Refused
|___|
1507 Any fresh fish, smoked fish, fish soup/sauce or dried fish or shellfish?
• 1. Yes 
• 2. No 
• 8. DK
• 9. Refused
|___|
1508 Any foods made from beans (white, brown, horse), peas, lentils, chick peas, rapeseed, linseed, sesame, 
sunflower, vetch, soybean flour or nuts (groundnuts, groundnut flour)?
• 1. Yes 
• 2. No 
• 8. DK
• 9. Refused
|___|
1509 Any cheese, yogurt, milk, powder milk, butter or other milk products?
• 1. Yes 
• 2. No 
• 8. DK
• 9. Refused
|___|
1510 Any foods made with oil, margarine, fat, or butter?
• 1. Yes 
• 2. No 
• 8. DK
• 9. Refused
|___|
1511 Any sugar, sugar cane, tamarind or honey?
• 1. Yes 
• 2. No 
• 8. DK
• 9. Refused
|___|
1512 Any other foods, such as condiments, traditional beer, beer, wine, coffee or tea?
• 1. Yes 
• 2. No 
• 8. DK
• 9. Refused
|___|
Sahel Resilience Learning (SAREL)—RISE Midline Quantitative Survey Report
October 2017 (Approved, Feb. 2018) 282
MODULE 16: HOUSEHOLD HUNGER 
Ask these questions of whoever is most knowledgeable of household members.
N° QUESTION WORDING CODES/ANSWERS
1601
In the past four weeks, did you worry that your household would not 
have enough food?
• 1. Yes
• 2. No 
• 8. DK
• 9. Refused
|___|
1601a
In the past four weeks, how often did you worry that your household 
would not have enough food?
• 1. Rarely (once or twice in the past four weeks)
• 2. Sometimes (three to ten times in the past four weeks)
• 3. Often (more than ten times in the past four weeks)
• 8. DK
• 9. Refused
|___|
1602
In the past four weeks, were you or any household member not able 
to eat the kinds of foods you preferred because of a lack of resources?
• 1. Yes
• 2. No 
• 8. DK
• 9. Refused
|___|
1602a
How often were you or any household member not able to eat the 
kinds of foods you preferred because of a lack of resources?
• 1. Rarely (once or twice in the past four weeks)
• 2. Sometimes (three to ten times in the past four weeks)
• 3. Often (more than ten times in the past four weeks)
• 8. DK
• 9. Refused
|___|
1603
In the past four weeks, did you or any household member have to eat 
a limited variety of foods due to a lack of resources?
• 1. Yes
• 2. No 
• 8. DK
• 9. Refused
|___|
1603a
How often did you or any household member have to eat a limited 
variety of foods due to a lack of resources?
• 1. Rarely (once or twice in the past four weeks)
• 2. Sometimes (three to ten times in the past four weeks)
• 3. Often (more than ten times in the past four weeks)
• 8. DK
• 9. Refused
|___|
1604
In the past four weeks, did you or any household member have to eat 
some foods that you really did not want to eat because of a lack of 
resources to obtain other types of food?
• 1. Yes
• 2. No 
• 8. DK
• 9. Refused
|___|
Sahel Resilience Learning (SAREL)—RISE Midline Quantitative Survey Report
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N° QUESTION WORDING CODES/ANSWERS
1604a
How often did you or any household member have to eat some foods 
that you really did not want to eat because of a lack of resources to 
obtain other types of food?
• 1. Rarely (once or twice in the past four weeks)
• 2. Sometimes (three to ten times in the past four weeks)
• 3. Often (more than ten times in the past four weeks)
• 8. DK
• 9. Refused
|___|
1605
In the past four weeks, did you or any household member have to eat 
a smaller meal than you felt you needed because there was not 
enough food?
• 1. Yes
• 2. No 
• 8. DK
• 9. Refused
|___|
1605a
How often did you or any household member have to eat a smaller 
meal than you felt you needed because there was not enough food?
• 1. Rarely (once or twice in the past four weeks)
• 2. Sometimes (three to ten times in the past four weeks)
• 3. Often (more than ten times in the past four weeks)
• 8. DK
• 9. Refused
|___|
1606
In the past four weeks, did you or any other household member have 
to eat fewer meals in a day because there was not enough food?
• 1. Yes
• 2. No 
• 8. DK
• 9. Refused
|___|
1606a How often did you or any other household member have to eat fewer 
meals in a day because there was not enough food?
• 1. Rarely (once or twice in the past four weeks)
• 2. Sometimes (three to ten times in the past four weeks)
• 3. Often (more than ten times in the past four weeks)
• 8. DK
• 9. Refused
|___|
1607
In the past four weeks, was there ever no food to eat (of any kind) in 
your household because of lack of resources to get food?
• 1. Yes
• 2. No 
• 8. DK
• 9. Refused
|___|
1607a
How often was there ever no food to eat (of any kind) in your 
household because of lack of resources to get food?
• 1. Rarely (once or twice in the past four weeks)
• 2. Sometimes (three to ten times in the past four weeks)
• 3. Often (more than ten times in the past four weeks)
• 8. DK
• 9. Refused
|___|
1608
In the past four weeks, did you or any household member go to sleep 
at night hungry because there was not enough food?
• 1. Yes
• 2. No |___|
Sahel Resilience Learning (SAREL)—RISE Midline Quantitative Survey Report
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N° QUESTION WORDING CODES/ANSWERS
• 8. DK
• 9. Refused
1608a
How often did you or any household member go to sleep at night 
hungry because there was not enough food?
• 1. Rarely (once or twice in the past four weeks)
• 2. Sometimes (three to ten times in the past four weeks)
• 3. Often (more than ten times in the past four weeks)
• 8. DK
• 9. Refused
|___|
1609
In the past four weeks, did you or any household member go a whole 
day and night without eating anything because there was not enough 
food?
• 1. Yes
• 2. No 
• 8. DK
• 9. Refused
|___|
1609a
How often did you or any household member go a whole day and night 
without eating anything because there was not enough food?
• 1. Rarely (once or twice in the past four weeks)
• 2. Sometimes (three to ten times in the past four weeks)
• 3. Often (more than ten times in the past four weeks)
• 8. DK
• 9. Refused
|___|
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MODULE 17. CHILD ANTHROPOMETRY 
Ask these questions of the primary caregiver of each child aged 0–59 months in the household, as identified in Module 2. Check to see if each 
caregiver has given consent to be interviewed on the signature page of the informed consent form. If a caregiver has not yet given consent, return 
to Module 1a and gain caregiver consent before proceeding. 
Fill in the information for q1701-q1703 for all of the children identified in q212 of Module 2.
N° QUESTION WORDING
CODES/ANSWERS
Child 1 Child 2 Child 3 Child 4 Child 5 Child 6 Child 7
1701 Record caregiver’s number from Module 2 |__|__| |__|__| |__|__| |__|__| |__|__| |__|__| |__|__|
1702 Record child’s number from Module 2 |__|__| |__|__| |__|__| |__|__| |__|__| |__|__| |__|__|
1703 Record child’s first name ………….…….. ………….…….. ………….…….. ………….…….. ………….…….. ………….…….. ………….……..
1704 What is child’s sex? 
1 Boy
2 Girl
|____|
1 Boy
2 Girl
|____|
1 Boy
2 Girl
|____|
1 Boy
2 Girl
|____|
1 Boy
2 Girl
|____|
1 Boy
2 Girl
|____|
1 Boy
2 Girl
|____|
AGE OF CHILD
1705
When was [child's name] born (dd/mm/yy)?
If the respondent does not know the exact birth date 
ask:
Does [child’s name] have a health/vaccination card with 
the birth date recorded?
If the health/vaccination card is shown and the 
respondent confirms the information is correct, 
|__|__|
Day
|__|__|
Day
|__|__|
Day
|__|__|
Day
|__|__|
Day
|__|__|
Day
|__|__|
Day
|__|__|
Month
|__|__|
Month
|__|__|
Month
|__|__|
Month
|__|__|
Month
|__|__|
Month
|__|__|
Month
|__|__|__|__|
Year
|__|__|__|__|
Year
|__|__|__|__|
Year
|__|__|__|__|
Year
|__|__|__|__|
Year
|__|__|__|__|
Year
|__|__|__|__|
Year
Sahel Resilience Learning (SAREL)—RISE Midline Quantitative Survey Report
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N° QUESTION WORDING
CODES/ANSWERS
Child 1 Child 2 Child 3 Child 4 Child 5 Child 6 Child 7
record the date of birth as documented on the card.
If the day is unknown, put 88 in the space
If the month is unknown, put 88 in the space
1706 How old was [child’s name] at [his/her] last birthday? 
Record age in completed years. |___|___| |___|___| |___|___| |___|___| |___|___| |___|___| |___|___|
1707 How many months old is [child’s name]? Record age in 
completed months.
|___|___|
Month
|___|___|
Month
|___|___|
Month
|___|___|
Month
|___|___|
Month
|___|___|
Month
|___|___|
Month
N° QUESTION WORDING
CODES/ANSWERS
Child 1 Child 2 Child 3 Child 4 Child 5 Child 6 Child 7
1708 Check 1707. Is the child 
under 60 months [age 
months]?
□ 1. Yes
□ 2. No 
• |___| |___| |___| |___| |___| |___| |___|
1709
Is the child available to be 
weighed and measured?
□ 1. Yes
□ 2. YES (DISABLED)
□ 3. NO (ABSENT)
□ 4. NO (SICK)
|___| |___| |___| |___| |___| |___| |___|
WEIGHT OF CHILD
1710
Does child have edema? 
(observe if child shows 
signs of swelling of the 
feet)
□ 1. Yes
□ 2. No 
•
|___| |___| |___| |___| |___| |___| |___|
Sahel Resilience Learning (SAREL)—RISE Midline Quantitative Survey Report
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1711
Weigh the child
(Weight in kilograms)
•
|__|__|,|__|__
|
Kg
|__|__|,|__|__
|
Kg
|__|__|,|__|__
|
Kg
|__|__|,|__|__
|
Kg
|__|__|,|__|__
|
Kg
|__|__|,|__|__
|
Kg
|__|__|,|__|__
|
Kg
HEIGHT OF CHILD
1712
Measure the child
(Height in centimeters)
Children under 24 months 
should be measured lying 
down; Children 24 months 
or older should be 
measured standing up.
|__|__|__|,|
__|
cm
|__|__|__|,|
__|
cm
|__|__|__|,|
__|
cm
|__|__|__|,|
__|
cm
|__|__|__|,|
__|
cm
|__|__|__|,|
__|
cm
|__|__|__|,|
__|
cm
Sahel Resilience Learning (SAREL)—RISE Midline Quantitative Survey Report
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MODULE 17a. NUTRITIONAL STATUS AND FEEDING PRACTICES FOR CHILDREN UNDER 24 MONTHS OLD
Exclusive Breastfeeding and Minimum Acceptable Diet (MAD)
N° QUESTION WORDING
CODES/ANSWERS
Child 1 Child 2 Child 3 Child 4 Child 5 Child 6 Child 7
17b01 Is (child's name) under 24 months?
Check 1707. Is the child under 24 months [age 
months]?
1. Yes
2. No
If "no" skip to 
next
|___|
1. Yes
2. No
If "no" skip to 
next
|___|
1. Yes
2. No
If "no" skip to 
next
|___|
1. Yes
2. No
If "no" skip to 
next
|___|
1. Yes
2. No
If "no" skip to 
next
|___|
1. Yes
2. No
If "no" skip to 
next
|___|
1. Yes
2. No
If "no" skip to 
next
|___|
17b02 Has (child's name) already been breastfed? 1. Yes
2. No
8. DK
9. Refused
Skip to 17b04
|___|
1. Yes
2. No
8. DK
9. Refused
Skip to 17b04
|___|
1. Yes
2. No
8. DK
9. Refused
Skip to 17b04
|___|
1. Yes
2. No
8. DK
9. Refused
Skip to 17b04
|___|
1. Yes
2. No
8. DK
9. Refused
Skip to 17b04
|___|
1. Yes
2. No
8. DK
9. Refused
Skip to 17b04
|___|
1. Yes
2. No
8. DK
9. Refused
Skip to 17b04
|___|
17b03 Has (child's name) been breastfed during the day 
or at night?
1. Yes
2. No
8. DK
9. Refused
Skip to 17b05
|___|
1. Yes
2. No
8. DK
9. Refused
Skip to 17b05
|___|
1. Yes
2. No
8. DK
9. Refused
Skip to 17b05
|___|
1. Yes
2. No
8. DK
9. Refused
Skip to 17b05
|___|
1. Yes
2. No
8. DK
9. Refused
Skip to 17b05
|___|
1. Yes
2. No
8. DK
9. Refused
Skip to 17b05
|___|
1. Yes
2. No
8. DK
9. Refused
Skip to 17b05
|___|
17b04 Sometimes babies are breastfed in different ways, for 
example with a spoon, a cup or a bottle. This can occur 
when the mother cannot always be with the baby. 
Sometimes babies are breastfed by another woman or 
1. Yes
2. No 
8. DK
1. Yes
2. No 
8. DK
1. Yes
2. No 
8. DK
1. Yes
2. No 
8. DK
1. Yes
2. No 
8. DK
1. Yes
2. No 
8. DK
1. Yes
2. No 
8. DK
Sahel Resilience Learning (SAREL)—RISE Midline Quantitative Survey Report
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N° QUESTION WORDING
CODES/ANSWERS
Child 1 Child 2 Child 3 Child 4 Child 5 Child 6 Child 7
from breast milk donated by another woman with a 
spoon, cup, bottle or another way. This can happen if a 
mother cannot breastfeed her baby.
Has (child's name) got breast milk using one of these 
methods during the day or night yesterday?
9. Refused
|___|
9. Refused
|___|
9. Refused
|___|
9. Refused
|___|
9. Refused
|___|
9. Refused
|___|
9. Refused
|___|
17b05 Now I would like to ask you about certain drugs and 
vitamins which are sometimes given to children 
under 24 months old.
Has (child's name) received vitamin drops or other 
drugs as drops yesterday during the day or evening? 
1. Yes
2. No 
8. DK
9. Refused
|___|
1. Yes
2. No 
8. DK
9. Refused
|___|
1. Yes
2. No 
8. DK
9. Refused
|___|
1. Yes
2. No 
8. DK
9. Refused
|___|
1. Yes
2. No 
8. DK
9. Refused
|___|
1. Yes
2. No 
8. DK
9. Refused
|___|
1. Yes
2. No 
8. DK
9. Refused
|___|
17b06 Has (child's name) received oral rehydration 
solution during the day or night yesterday? 
1. Yes
2. No 
8. DK
9. Refused
|___|
1. Yes
2. No 
8. DK
9. Refused
|___|
1. Yes
2. No 
8. DK
9. Refused
|___|
1. Yes
2. No 
8. DK
9. Refused
|___|
1. Yes
2. No 
8. DK
9. Refused
|___|
1. Yes
2. No 
8. DK
9. Refused
|___|
1. Yes
2. No 
8. DK
9. Refused
|___|
Now, I would like to ask you about some liquids (child's name) may have taken yesterday during the day or night yesterday.
Do you know if (child's name) had:
17b07 Ordinary water (without bubbles or carbonation) 
for example, from a well, spring, or tap?
1. Yes
2. No 
8. DK
9. Refused
|___|
1. Yes
2. No 
8. DK
9. Refused
|___|
1. Yes
2. No 
8. DK
9. Refused
|___|
1. Yes
2. No 
8. DK
9. Refused
|___|
1. Yes
2. No 
8. DK
9. Refused
|___|
1. Yes
2. No 
8. DK
9. Refused
|___|
1. Yes
2. No 
8. DK
9. Refused
|___|
17b08 Preparations for children under 24 months old, 
such as France lait, Nativa, other dairy products 
1. Yes 1. Yes 1. Yes 1. Yes 1. Yes 1. Yes 1. Yes
Sahel Resilience Learning (SAREL)—RISE Midline Quantitative Survey Report
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N° QUESTION WORDING
CODES/ANSWERS
Child 1 Child 2 Child 3 Child 4 Child 5 Child 6 Child 7
such as Nestlé for children?
2. No
8. DK
9. Refused
Skip to 17b10
|___|
2. No
8. DK
9. Refused
Skip to 17b10
|___|
2. No
8. DK
9. Refused
Skip to 17b10
|___|
2. No
8. DK
9. Refused
Skip to 17b10
|___|
2. No
8. DK
9. Refused
Skip to 17b10
|___|
2. No
8. DK
9. Refused
Skip to 17b10
|___|
2. No
8. DK
9. Refused
Skip to 17b10
|___|
17b09 How many times in the day and in the night has 
(child's name) consumed a preparation of formula 
for children under 24 months old yesterday?
|___|___| |___|___| |___|___| |___|___| |___|___| |___|___| |___|___|
17b10 Has (child's name) drunk canned, powdered or 
fresh milk? 1. Yes
2. No
8. DK
9. Refused
Skip to 17b12
|___|
1. Yes
2. No
8. DK
9. Refused
Skip to 17b12
|___|
1. Yes
2. No
8. DK
9. Refused
Skip to 17b12
|___|
1. Yes
2. No
8. DK
9. Refused
Skip to 17b12
|___|
1. Yes
2. No
8. DK
9. Refused
Skip to 17b12
|___|
1. Yes
2. No
8. DK
9. Refused
Skip to 17b12
|___|
1. Yes
2. No
8. DK
9. Refused
Skip to 17b12
|___|
17b11 How many times in the day and in the night has 
(child's name) drunk that milk yesterday? |___|___| |___|___| |___|___| |___|___| |___|___| |___|___| |___|___|
17b12 Has (child's name) drunk juice or beverages? 1. Yes
2. No 
1. Yes
2. No 
1. Yes
2. No 
1. Yes
2. No 
1. Yes
2. No 
1. Yes
2. No 
1. Yes
2. No 
Sahel Resilience Learning (SAREL)—RISE Midline Quantitative Survey Report
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N° QUESTION WORDING
CODES/ANSWERS
Child 1 Child 2 Child 3 Child 4 Child 5 Child 6 Child 7
8. DK
9. Refused
|___|
8. DK
9. Refused
|___|
8. DK
9. Refused
|___|
8. DK
9. Refused
|___|
8. DK
9. Refused
|___|
8. DK
9. Refused
|___|
8. DK
9. Refused
|___|
17b13 Clear broth 1. Yes
2. No 
8. DK
9. Refused
|___|
1. Yes
2. No 
8. DK
9. Refused
|___|
1. Yes
2. No 
8. DK
9. Refused
|___|
1. Yes
2. No 
8. DK
9. Refused
|___|
1. Yes
2. No 
8. DK
9. Refused
|___|
1. Yes
2. No 
8. DK
9. Refused
|___|
1. Yes
2. No 
8. DK
9. Refused
|___|
17b14 Yogurt 1. Yes
2. No
8. DK
9. Refused
Skip to 17b16
|___|
1. Yes
2. No
8. DK
9. Refused
Skip to 17b16
|___|
1. Yes
2. No
8. DK
9. Refused
Skip to 17b16
|___|
1. Yes
2. No
8. DK
9. Refused
Skip to 17b16
|___|
1. Yes
2. No
8. DK
9. Refused
Skip to 17b16
|___|
1. Yes
2. No
8. DK
9. Refused
Skip to 17b16
|___|
1. Yes
2. No
8. DK
9. Refused
Skip to 17b16
|___|
17b15 How many times in the day or in the night has 
(child's name) eaten yogurt yesterday? |___|___| |___|___| |___|___| |___|___| |___|___| |___|___| |___|___|
17b16 Has (child's name) eaten porridge such as 
cowpea puree, porridge, enriched porridge 
(« koko ») Misola, CSB, etc.?
1. Yes
2. No 
1. Yes
2. No 
1. Yes
2. No 
1. Yes
2. No 
1. Yes
2. No 
1. Yes
2. No 
1. Yes
2. No 
Sahel Resilience Learning (SAREL)—RISE Midline Quantitative Survey Report
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N° QUESTION WORDING
CODES/ANSWERS
Child 1 Child 2 Child 3 Child 4 Child 5 Child 6 Child 7
8. DK
9. Refused
|___|
8. DK
9. Refused
|___|
8. DK
9. Refused
|___|
8. DK
9. Refused
|___|
8. DK
9. Refused
|___|
8. DK
9. Refused
|___|
8. DK
9. Refused
|___|
17b17 Other liquids such as tea, decoction, sugar water, 
« rouboutou » (Coranic verses written on a slate 
and washed to give children)?
1. Yes
2. No 
8. DK
9. Refused
|___|
1. Yes
2. No 
8. DK
9. Refused
|___|
1. Yes
2. No 
8. DK
9. Refused
|___|
1. Yes
2. No 
8. DK
9. Refused
|___|
1. Yes
2. No 
8. DK
9. Refused
|___|
1. Yes
2. No 
8. DK
9. Refused
|___|
1. Yes
2. No 
8. DK
9. Refused
|___|
17b18 Other liquids? 1. Yes
2. No 
8. DK
9. Refused
|___|
1. Yes
2. No 
8. DK
9. Refused
|___|
1. Yes
2. No 
8. DK
9. Refused
|___|
1. Yes
2. No 
8. DK
9. Refused
|___|
1. Yes
2. No 
8. DK
9. Refused
|___|
1. Yes
2. No 
8. DK
9. Refused
|___|
1. Yes
2. No 
8. DK
9. Refused
|___|
Yesterday during the day and in the night, has (child's name) drunk/eaten (food under the group)
WRITE (1) IF RESPONDENT SAYS « YES », (2) IF RESPONDENT SAYS « NO », (8) IF S/HE DOES NOT KNOW AND (9) IF S/HE REFUSES
17b19 Cereal-based foods such as bread, biscuit, cake, 
fritters, couscous, rice, pasta, porridge, cereal or 
other foods made from corn, rice, fonio, wheat 
(« bulgur », « doumé »), sorghum, and millet?
1. Yes
2. No 
8. DK
9. Refused
1. Yes
2. No 
8. DK
9. Refused
1. Yes
2. No 
8. DK
9. Refused
1. Yes
2. No 
8. DK
9. Refused
1. Yes
2. No 
8. DK
9. Refused
1. Yes
2. No 
8. DK
9. Refused
1. Yes
2. No 
8. DK
9. Refused
Sahel Resilience Learning (SAREL)—RISE Midline Quantitative Survey Report
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N° QUESTION WORDING
CODES/ANSWERS
Child 1 Child 2 Child 3 Child 4 Child 5 Child 6 Child 7
|___| |___| |___| |___| |___| |___| |___|
17b20 Carrots, squash, monkey bread, « gonda » 
(papaya) whose inside color is yellowish or 
orange-yellow?
1. Yes
2. No 
8. DK
9. Refused
|___|
1. Yes
2. No 
8. DK
9. Refused
|___|
1. Yes
2. No 
8. DK
9. Refused
|___|
1. Yes
2. No 
8. DK
9. Refused
|___|
1. Yes
2. No 
8. DK
9. Refused
|___|
1. Yes
2. No 
8. DK
9. Refused
|___|
1. Yes
2. No 
8. DK
9. Refused
|___|
17b21 Potatoes, yams, cassava, taro, any food made of 
roots or tubers?
1. Yes
2. No 
8. DK
9. Refused
|___|
1. Yes
2. No 
8. DK
9. Refused
|___|
1. Yes
2. No 
8. DK
9. Refused
|___|
1. Yes
2. No 
8. DK
9. Refused
|___|
1. Yes
2. No 
8. DK
9. Refused
|___|
1. Yes
2. No 
8. DK
9. Refused
|___|
1. Yes
2. No 
8. DK
9. Refused
|___|
17b22 Spinach, lettuce, sorrel, « molohiya » 
(« fakkou »), baobab leaf (« kouka »), « yodo », 
okra leaf, Moringa, « tchapatta », other local dark 
green leafy vegetables?
1. Yes
2. No 
8. DK
9. Refused
|___|
1. Yes
2. No 
8. DK
9. Refused
|___|
1. Yes
2. No 
8. DK
9. Refused
|___|
1. Yes
2. No 
8. DK
9. Refused
|___|
1. Yes
2. No 
8. DK
9. Refused
|___|
1. Yes
2. No 
8. DK
9. Refused
|___|
1. Yes
2. No 
8. DK
9. Refused
|___|
17b23 Ripe mangoes, ripe papayas, guava, melon? 1. Yes
2. No 
1. Yes
2. No 
1. Yes
2. No 
1. Yes
2. No 
1. Yes
2. No 
1. Yes
2. No 
1. Yes
2. No 
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N° QUESTION WORDING
CODES/ANSWERS
Child 1 Child 2 Child 3 Child 4 Child 5 Child 6 Child 7
8. DK
9. Refused
|___|
8. DK
9. Refused
|___|
8. DK
9. Refused
|___|
8. DK
9. Refused
|___|
8. DK
9. Refused
|___|
8. DK
9. Refused
|___|
8. DK
9. Refused
|___|
17b24 Other fruits or vegetables such as cabbage, 
cauliflower, watermelon, squash/zucchini, onion, 
tomato, eggplant (« yalo »), green beans?
1. Yes
2. No 
8. DK
9. Refused
|___|
1. Yes
2. No 
8. DK
9. Refused
|___|
1. Yes
2. No 
8. DK
9. Refused
|___|
1. Yes
2. No 
8. DK
9. Refused
|___|
1. Yes
2. No 
8. DK
9. Refused
|___|
1. Yes
2. No 
8. DK
9. Refused
|___|
1. Yes
2. No 
8. DK
9. Refused
|___|
17b25 Liver, kidney, heart, or other offal? 1. Yes
2. No 
8. DK
9. Refused
|___|
1. Yes
2. No 
8. DK
9. Refused
|___|
1. Yes
2. No 
8. DK
9. Refused
|___|
1. Yes
2. No 
8. DK
9. Refused
|___|
1. Yes
2. No 
8. DK
9. Refused
|___|
1. Yes
2. No 
8. DK
9. Refused
|___|
1. Yes
2. No 
8. DK
9. Refused
|___|
17b26 Any meat such as beef, pork, sheep, goat, 
chicken, duck? 1. Yes
2. No 
8. DK
9. Refused
|___|
1. Yes
2. No 
8. DK
9. Refused
|___|
1. Yes
2. No 
8. DK
9. Refused
|___|
1. Yes
2. No 
8. DK
9. Refused
|___|
1. Yes
2. No 
8. DK
9. Refused
|___|
1. Yes
2. No 
8. DK
9. Refused
|___|
1. Yes
2. No 
8. DK
9. Refused
|___|
17b27 Eggs? 1. Yes 1. Yes 1. Yes 1. Yes 1. Yes 1. Yes 1. Yes
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N° QUESTION WORDING
CODES/ANSWERS
Child 1 Child 2 Child 3 Child 4 Child 5 Child 6 Child 7
2. No 
8. DK
9. Refused
|___|
2. No 
8. DK
9. Refused
|___|
2. No 
8. DK
9. Refused
|___|
2. No 
8. DK
9. Refused
|___|
2. No 
8. DK
9. Refused
|___|
2. No 
8. DK
9. Refused
|___|
2. No 
8. DK
9. Refused
|___|
17b28 Fresh or dried fish, shellfish, seafood? 1. Yes
2. No 
8. DK
9. Refused
|___|
1. Yes
2. No 
8. DK
9. Refused
|___|
1. Yes
2. No 
8. DK
9. Refused
|___|
1. Yes
2. No 
8. DK
9. Refused
|___|
1. Yes
2. No 
8. DK
9. Refused
|___|
1. Yes
2. No 
8. DK
9. Refused
|___|
1. Yes
2. No 
8. DK
9. Refused
|___|
17b29 Any food made from beans, peas, lentils or beans, 
« vouandzou »/cowpea (« dan-wari »), 
néré/« soumbala »? 
1. Yes
2. No 
8. DK
9. Refused
|___|
1. Yes
2. No 
8. DK
9. Refused
|___|
1. Yes
2. No 
8. DK
9. Refused
|___|
1. Yes
2. No 
8. DK
9. Refused
|___|
1. Yes
2. No 
8. DK
9. Refused
|___|
1. Yes
2. No 
8. DK
9. Refused
|___|
1. Yes
2. No 
8. DK
9. Refused
|___|
17b30 Cheese, yogurt or other dairy products? 1. Yes
2. No 
8. DK
9. Refused
|___|
1. Yes
2. No 
8. DK
9. Refused
|___|
1. Yes
2. No 
8. DK
9. Refused
|___|
1. Yes
2. No 
8. DK
9. Refused
|___|
1. Yes
2. No 
8. DK
9. Refused
|___|
1. Yes
2. No 
8. DK
9. Refused
|___|
1. Yes
2. No 
8. DK
9. Refused
|___|
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N° QUESTION WORDING
CODES/ANSWERS
Child 1 Child 2 Child 3 Child 4 Child 5 Child 6 Child 7
17b31 Any oil, grease, or butter or any food based on any 
of these products?
1. Yes
2. No 
8. DK
9. Refused
|___|
1. Yes
2. No 
8. DK
9. Refused
|___|
1. Yes
2. No 
8. DK
9. Refused
|___|
1. Yes
2. No 
8. DK
9. Refused
|___|
1. Yes
2. No 
8. DK
9. Refused
|___|
1. Yes
2. No 
8. DK
9. Refused
|___|
1. Yes
2. No 
8. DK
9. Refused
|___|
17b32 Any sugary food such as chocolates, candies, 
sweets, pastries, cakes, cookies?
1. Yes
2. No 
8. DK
9. Refused
|___|
1. Yes
2. No 
8. DK
9. Refused
|___|
1. Yes
2. No 
8. DK
9. Refused
|___|
1. Yes
2. No 
8. DK
9. Refused
|___|
1. Yes
2. No 
8. DK
9. Refused
|___|
1. Yes
2. No 
8. DK
9. Refused
|___|
1. Yes
2. No 
8. DK
9. Refused
|___|
17b33 Any seasoning for flavor, such as pepper, spices, 
herbs or fish powder?
1. Yes
2. No 
8. DK
9. Refused
|___|
1. Yes
2. No 
8. DK
9. Refused
|___|
1. Yes
2. No 
8. DK
9. Refused
|___|
1. Yes
2. No 
8. DK
9. Refused
|___|
1. Yes
2. No 
8. DK
9. Refused
|___|
1. Yes
2. No 
8. DK
9. Refused
|___|
1. Yes
2. No 
8. DK
9. Refused
|___|
17b34 Any larvae, snails, insects? 1. Yes
2. No 
8. DK
9. Refused
1. Yes
2. No 
8. DK
9. Refused
1. Yes
2. No 
8. DK
9. Refused
1. Yes
2. No 
8. DK
9. Refused
1. Yes
2. No 
8. DK
9. Refused
1. Yes
2. No 
8. DK
9. Refused
1. Yes
2. No 
8. DK
9. Refused
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N° QUESTION WORDING
CODES/ANSWERS
Child 1 Child 2 Child 3 Child 4 Child 5 Child 6 Child 7
|___| |___| |___| |___| |___| |___| |___|
17b35 Any foods made of red palm oil, red palm nut or 
red palm nut pulp sauce?
1. Yes
2. No 
8. DK
9. Refused
|___|
1. Yes
2. No 
8. DK
9. Refused
|___|
1. Yes
2. No 
8. DK
9. Refused
|___|
1. Yes
2. No 
8. DK
9. Refused
|___|
1. Yes
2. No 
8. DK
9. Refused
|___|
1. Yes
2. No 
8. DK
9. Refused
|___|
1. Yes
2. No 
8. DK
9. Refused
|___|
17b36 Has [child's name] eaten any solid, semi-solid or 
soft food during the day or in the night yesterday?
1. Yes
2. No 
8. DK
9. Refused
|___|
1. Yes
2. No 
8. DK
9. Refused
|___|
1. Yes
2. No 
8. DK
9. Refused
|___|
1. Yes
2. No 
8. DK
9. Refused
|___|
1. Yes
2. No 
8. DK
9. Refused
|___|
1. Yes
2. No 
8. DK
9. Refused
|___|
1. Yes
2. No 
8. DK
9. Refused
|___|
17b37 How many times has [child's name] eaten any 
solid, semi-solid or soft food other than liquids 
during the day or in the night yesterday?
|___|___| |___|___| |___|___| |___|___| |___|___| |___|___| |___|___|
**THANK YOU**
After the interview thank the respondent for giving you his/her time and for the co-operation in providing the 
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information. Inform them that you may possibly be returning to collect more information or seek any necessary 
clarification on the information provided at later date. At this point invite the respondent to ask you any questions 
that he/she might have. Answer where you can. If you do not know the answer(s), tell the respondent that his/her 
questions will be forwarded to a relevant person who can respond.
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C.4: Village Questionnaire
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INFORMED CONSENT SIGNATURE PAGE
Thank you for the opportunity to speak with you. We are from SAREL, a USAID-funded project in partnership with the Governments of Niger and Burkina Faso. 
We are conducting a survey to learn about agriculture, food security, food consumption, nutrition and wellbeing of households in this area. Your community has 
been selected to participate in an interview on topics such as the types of services available here, the community organizations, and the stressors that have 
affected you. These questions in total will take approximately one hour to complete and your participation is entirely voluntary. If you agree to participate, you 
can choose to stop at any time or to skip any questions you do not want to answer. Your answers will be completely confidential; we will not share information 
that identifies you with anyone. 
Do you have any questions about the survey or what I have just said? If in the future you have any questions regarding the survey and the interview, or concerns 
or complaints we welcome you to contact the USAID/SAREL Project (Stephen Reid | Chief of Party, Sahel Resilience Learning (SAREL) Project / 
Tel. : 227-9663-0291 |227-9025-7197 / sreid@sarelproject.com ). We will leave one copy of this form for you so that you will have record of this contact information 
and about the study.
Name
Consent to participate in 
survey (Insert code) Signature or mark
YES=1 NO=2
1 |___|
2 |___|
3 |___|
4 |___|
5 |___|
6 |___|
7 |___|
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8 |___|
9 |___|
10 |___|
11 |___|
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MODULE 2. VILLAGE CHARACTERISTICS
N° QUESTION WORDING CODES/ANSWERS
201 What is the total population of this village?
|___|___|___|___|___|
202 In the last five years, has the population of this village stayed the same, increased or 
decreased?
1. Stayed the same
2. Increased
3. Decreased
|___|
203 What are the three largest ethnic groups in this village? Burkina Faso Ethnic 
Groups
Niger Ethnic Groups
1st |___|___|
2nd |___|___|
3rd |___|___|
11. Mossi
12. Fulfuldé/Peul
13. Gourmantché
14. Songhaï/Sonraï
15. Touareg
16. Bella
21. Haoussa
22. Djerma
23. Sonraï
24. Peul 
25. Gourmantché 
26. Touareg
27. Bella
28. Kanouri
204
How far is this village from the nearest town? (kms)
Town: e.g. presence of important educational centers like schools, integrated health centers or 
hospitals, banks, business services, major markets, input supplies facilities, other facilities...)
|___|___|___|
205 How far is this village from the zonal capital? (kms) |___|___|___|
206 For how many years has this village existed? 
1. More than 20 years 
2. Between 10 and 20 years
3. Less than 10 years
8. DK
|___|
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N° QUESTION WORDING CODES/ANSWERS
207 In addition to the rainy season campaign does your village have a second cropping 
season?
1. Yes
2. No |___|
208 Does this village have corridors and communal grazing areas?
1. Yes
2. No (Skip to q211) |___|
209 If yes, is there a group in the village that decides who can use these grazing areas and 
when they can use them?
1. Yes
2. No |___|
210 In the last 12 months, has there ever been a problem of too many animals on the 
communal grazing land?
1. Yes
2. No |___|
211 Does this community have a communal water source for livestock?
1. Yes
2. No (Skip to q214) |___|
212 What is this communal water source?
1. River
2. Pond
3. Borehole
4. Well
|___|
213 In the last 12 months, has there ever been a time when there was not enough water for 
all the animals?
1. Yes
2. No |___|
214 Do people in this community get their firewood from communal land?
1. Yes
2. No (Skip to q217) |___|
215 If yes, is there a group in the community that decides who can gather the wood and how 
much?
1. Yes
2. No |___|
216 In the last 12 months, has there ever been a problem of not enough firewood on the 
communal land?
1. Yes
2. No |___|
217 Is there a water users’ group that manages the water used for irrigation in this community? 
(Enter N/A if the village does not practice irrigation)
1. Yes
2. No
3. N/A
|___|
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MODULE 3. COMMUNITY INFRASTRUCTURE AND SERVICES
N° QUESTION WORDING CODES/ANSWERS
WATER
301 Does this village have access to piped water? 1. Yes
2. No (Skip to q304) |___|
302 If yes, is the water in public standpipes or piped into houses? 1. Public standpipes
2. Piped into houses
3. Public standpipes and piped into houses
|___|
303 What share of the households in the village has access to piped 
water?
1. All households
2. Most of the households 
3. About half of the households 
4. Less than half of the households
5. Very few
|___|
304 What are the main sources of drinking water supply in the dry 
season?
01. Tube wells 
02. Public standpipes
03. Protected hand-dug wells
04. Protected springs
05. Rainwater collection
06. Ponds and rivers
07. Unprotected springs/wells
08. Truck/vendor
09. Borehole 
10. Piped into houses
11. Other (specify)_________________________________ 
1st |___|___|
2rd |___|___|
3rd |___|___|
305 What are the main sources of drinking water supply in the rainy 
season?
01. Tube wells 
02. Public standpipes
1st |___|___|
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N° QUESTION WORDING CODES/ANSWERS
03. Protected hand-dug wells
04. Protected springs
05. Rainwater collection
06. Ponds and rivers
07. Unprotected springs/wells
08. Truck/vendor
09. Borehole 
10. Piped into houses
11. Other (specify)_________________________________
2rd |___|___|
3rd |___|___|
ELECTRICITY
306 Do any of the households in the village have electricity? 1. Yes
2. No (Skip to q309) |___|
307 What share of households in the village has electricity? 1. All households
2. Most of the households 
3. About half of the households 
4. Less than half of the households
5. Very few
|___|
308 What is the main source of electricity? 1. Public utility
2. Generator
3. Other (specify)_________________________________
|___|
TELEPHONE SERVICE
309 Does this village have cell phone service? 1. Yes
2. No (Skip to q311) |___|
310 What share of households in this village has cell phones? 1. All households
2. Most of the households 
3. About half of the households 
4. Less than half of the households
5. Very few
|___|
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N° QUESTION WORDING CODES/ANSWERS
311 Does this village have public telephones? 1. Yes (Skip to q317)
2. No (Skip to q312) |___|
312 How far from the village is the nearest public telephone? (kms) |___|___|___|
ROADS AND TRANSPORTATION
313 What are the main routes used to reach this village? (multiple 
responses possible)
Paved road = road protected by a waterproof surface (surface￾dressed laterite)
Rural road = earth road (unpaved)
1. Paved road .................................................................................................. |___|
2. Dirt road (laterite)......................................................................................... |___|
3. Mixed paved and dirt.................................................................................... |___|
4. Footpath ...................................................................................................... |___|
5. Trail ............................................................................................................. |___|
6. Other (specify) ............................................................................................ |___|
314 Are there times of the year when people cannot travel because of 
poor road/trail conditions?
1. Yes
2. No |___|
315 Is this village served by a public transport system? 1. Yes (Skip to q317)
2. No |___|
316 How far from the village is the nearest public transport? (kms) |___|___|___|
317 What is the share of households in this village that uses public 
transportation?
1. All households
2. Most of the households 
3. About half of the households 
4. Less than half of the households
5. Very few
|___|
INFRASTRUCTURE
317a How far from the village is there a passable road that leads to the 
municipal capital?
1. Village (Skip to 317c)
2. Less than 1 km
3. 1 to 2 km
|___|
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N° QUESTION WORDING CODES/ANSWERS
4. 3 to 5 km
5. More than 5 km
317b Are there times of the year when people cannot access this road? 1. Yes
2. No |___|
317c How far from the village is there a passable road that leads to the 
departmental/provincial capital?
1. Village (Skip to 317e)
2. Less than 1 km
3. 1 to 2 km
4. 3 to 5 km
5. More than 5 km
|___|
317d Are there times of the year when people cannot access this road? 1. Yes
2. No |___|
317e How far from the village is there a passable road that leads to the 
regional capital?
1. Village (Skip to 318)
2. Less than 1 km
3. 1 to 2 km
4. 3 to 5 km
5. More than 5 km
|___|
317f Are there times of the year when people cannot access this road? 1. Yes
2. No |___|
HOUSING
318 What share of households in the village has tin (corrugated sheet 
metal) roofs?
1. All households
2. Most of the households 
3. About half of the households 
4. Less than half of the households
5. Very few
6. None
|___|
319a What share of households in the village has adobe (laterite mud) 1. All households
|___|
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N° QUESTION WORDING CODES/ANSWERS
housing? 2. Most of the households 
3. About half of the households 
4. Less than half of the households
5. Very few
6. None
319b What share of households in the village has semi-solid (cement 
and adobe) housing?
1. All households
2. Most of the households 
3. About half of the households 
4. Less than half of the households
5. Very few
6. None
|___|
319c What share of households in the village has solid material 
housing (hard)?
1. All households
2. Most of the households 
3. About half of the households 
4. Less than half of the households
5. Very few
6. None
|___|
SCHOOLS
320 Is there a primary school in this village? 1. Yes (Skip to q322)
2. No (Skip to q321) |___|
321 How far from the village is the nearest primary school? (kms) |___|___|___|
322 What share of eligible school-age children attends primary 
school?
1. All
2. Most
3. About half
4. Less than half
5. Very few
6. None
|___|
323 Are there enough teachers for the primary school that the children 1. Yes
|___|
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N° QUESTION WORDING CODES/ANSWERS
in this village attend? 2. No
324 What is the physical condition of the primary school that the 
children in this village attend?
1. Very good
2. Good
3. Poor
4. Very poor
|___|
325 Is there a secondary school in this village? 1. Yes (Skip to q327)
2. No (Skip to q326) |___|
326 How far from the village is the nearest secondary school? (kms) |___|___|___|
327 What share of eligible school-age children attends secondary 
school?
1. All
2. Most
3. About half
4. Less than half
5. Very few
|___|
328 Are there enough teachers for the secondary school that the 
children in this community attend??
1. Yes
2. No |___|
329 What is the physical condition of the secondary school that the 
children attend?
1. Very good
2. Good
3. Poor
4. Very poor
|___|
HEALTH SERVICES
330 Is there a health center in this village? 1. Yes (skip to q332)
2. No (Skip to q331) |___|
331 How far is this village from the nearest health center? (kms) |___|___|___|
332 What is the physical condition of the village health center? 1. Very good
2. Good
3. Poor
|___|
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N° QUESTION WORDING CODES/ANSWERS
4. Very poor
333 In the last 12 months, was there a time when people in the village 
needed health services but could not get them from the health 
center?
1. Yes
2. No (Skip to q335) |___|
334 If yes, why were the village members not able to get health 
services from the health center?
(multiple responses possible)
List reasons
01. No beds, health center was full
........................................................................................... Yes = 1 No = 2 |___|
02. No staff in the health center
........................................................................................... Yes = 1 No = 2 |___|
03. Health center was destroyed/burnt
........................................................................................... Yes = 1 No = 2 |___|
04. Security problem reaching the center
........................................................................................... Yes = 1 No = 2 |___|
05. No transportation to reach the center
........................................................................................... Yes = 1 No = 2 |___|
06. No road or poor road conditions on the way to the center
........................................................................................... Yes = 1 No = 2 |___|
07. No drugs at the health center
........................................................................................... Yes = 1 No = 2 |___|
08. No money for services
........................................................................................... Yes = 1 No = 2 |___|
09. Quality of the health service is very poor
........................................................................................... Yes = 1 No = 2 |___|
10. Other (specify)_________________________________ Yes = 1 No = 2 |___|
VETERINARY AND VALUE-ADDED ANIMAL SERVICES
335 Is there a public animal health service in this village? 1. Yes (skip to q337)
2. No (Skip to q336) |___|
336 If no, how far from the village is the nearest public animal health
service? (kms) |___|___|
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N° QUESTION WORDING CODES/ANSWERS
337 What is the physical condition of the nearest public animal health 
service to this village?
1. Very good
2. Good
3. Poor
4. Very poor
|___|
338 In the last 12 months, was there a time when people in the village 
needed veterinary services but could not get them from the public 
animal health service? 
1. Yes
2. No (Skip to q340) |___|
339 If yes, why were the village members not able to get veterinary 
services from the public animal health service?
(multiple responses possible)
List reasons
1. No staff in the service
........................................................................................... Yes = 1 No = 2 |___|
2. The service was too busy
........................................................................................... Yes = 1 No = 2 |___|
3. Security problem reaching the service
........................................................................................... Yes = 1 No = 2 |___|
4. No transportation to reach the service
........................................................................................... Yes = 1 No = 2 |___|
5. No road or poor road conditions on the way to the service
........................................................................................... Yes = 1 No = 2 |___|
6. The service had no equipment/drugs
........................................................................................... Yes = 1 No = 2 |___|
7. Households had no money for services
........................................................................................... Yes = 1 No = 2 |___|
8. Quality of the services is poor
........................................................................................... Yes = 1 No = 2 |___|
9. Other (specify)_________________________________ Yes = 1 No = 2 |___|
340 Which services does the public animal health service provide?
(multiple responses possible)
1. Livestock vaccinations
........................................................................................... Yes = 1 No = 2 |___|
2. Livestock antibiotics
........................................................................................... Yes = 1 No = 2 |___|
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N° QUESTION WORDING CODES/ANSWERS
List services
3. De-worming
........................................................................................... Yes = 1 No = 2 |___|
4. Dipping inoculation
........................................................................................... Yes = 1 No = 2 |___|
5. Other treatment for diseases
........................................................................................... Yes = 1 No = 2 |___|
6. Supplemental feeding (commercial feeding) 
........................................................................................... Yes = 1 No = 2 |___|
7. Other (specify)_________________________________ Yes = 1 No = 2 |___|
340b1 Are there any other forms of veterinary services to maintain 
animal health in the village? 
1. Yes
2. No
|___|
340b2 If yes, what services are on offer? 1. Local and private veterinary services (LPVS) Yes = 1 No = 2
2. Female poultry vaccinators Yes = 1 No = 2
3. Other (specify) Yes = 1 No = 2
AGRICULTURAL EXTENSION SERVICES
341 Are there agricultural extension services offered in this village? 1. Yes
2. No (Skip to q343) |___|
342 If yes, what agricultural extension services are provided?
(multiple responses possible)
List services
1. Seed supply
........................................................................................... Yes = 1 No = 
2 |___|
2. Fertilizer supply 
........................................................................................... Yes = 1 No = 
2 |___|
3. Training 
........................................................................................... Yes = 1 No = 
2 |___|
4. Climate-adapted technologies (e.g., drought-tolerant seeds) 
........................................................................................... Yes = 1 No = |___|
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N° QUESTION WORDING CODES/ANSWERS
2
5. Other (specify)_________________________________ Yes = 1 No = 
2 |___|
343 In the last 12 months, was there a time when people in the village 
needed these services but could not get them?
1. Yes
2. No (Skip to q345) |___|
344 Is yes, why were the village members not able to get agricultural 
extension services? 
(multiple responses possible)
List reasons
01. Extension service center was closed
........................................................................................... Yes = 1 No = 
2 |___|
02. There was no extension worker
........................................................................................... Yes = 1 No = 
2
|___|
03. Security problem
........................................................................................... Yes = 1 No = 
2
|___|
04. Extension workers were not cordial
........................................................................................... Yes = 1 No = 
2
|___|
05. The extension center was too far away.
........................................................................................... Yes = 1 No = 
2
|___|
06. There was no transportation to reach the service
........................................................................................... Yes = 1 No = 
2
|___|
07. No road or poor road condition
........................................................................................... Yes = 1 No = 
2
|___|
08. No money to access services
........................................................................................... Yes = 1 No = 
2
|___|
09. Quality of the services is very poor
........................................................................................... Yes = 1 No = 
2
|___|
10. Other (specify)_________________________________ Yes = 1 No = 
2
|___|
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N° QUESTION WORDING CODES/ANSWERS
MARKETS
345 How far away is the nearest livestock market from this village? 
(kms) |___|___|___|
346 In the last 12 months, was there a time when people in this village 
needed to buy or sell livestock in the market but could not?
1. Yes
2. No (Skip to q348)
|___|
347 If yes, why were the village members not able to buy or sell 
livestock in the market?
(multiple responses possible)
List reasons
1. Market closed
........................................................................................... Yes = 1 No = 
2
|___|
2. No road or poor road condition
........................................................................................... Yes = 1 No = 
2
|___|
3. No transportation
........................................................................................... Yes = 1 No = 
2
|___|
4. Could not pay for transportation
...........................................................................................
Yes = 1 No = 
2
|___|
5. Security problem
...........................................................................................
Yes = 1 No = 
2
|___|
6. Other (specify)_________________________________ Yes = 1 No = 
2
|___|
348 Is there an emergency plan for livestock offtake if a drought hits? 1. Yes
2. No
|___|
348a Does your village have facilities to buy or sell agricultural products 
(foodstuffs, agricultural inputs such as seed, etc.)? 1. Yes
2. No. If no, skip to q349
|___|
348b If yes, what facilities does it have? 1.Cereal banks (CB) Yes = 1 No = 2
2. Agricultural input banks Yes = 1 No = 2
3. Other (specify) Yes = 1 No 
= 2
|___|
|___|
|___|
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N° QUESTION WORDING CODES/ANSWERS
349 If no, how far from this village is the nearest market that sells
agricultural products? (kms) |___|___|___|
350 In the last 12 months, was there a time when people in this village 
needed to buy or sell agricultural products at cereal banks or 
agricultural input banks in the village but were unable to do so?
1. Yes
2. No
|___|
350a If yes, why were villagers unable to buy or sell agricultural 
products in the village?
(multiple responses possible)
List reasons
1. Cereal/agricultural input bank not open at the right time Yes = 1 No = 
2 
2. Cereal/agricultural input bank lacked supplies Yes = 1 No = 
2
3. Other (specify) Yes = 1 No = 
2
|___|
|___|
|___|
350b In the last 12 months, was there a time when people in this village 
needed to buy or sell agricultural products at cereal banks or 
agricultural input banks at the market but were unable to do so?
1. Yes
2. No. If no, skip to q352
351 If yes, why were people in the village unable to buy or sell 
agricultural products at the market?
(multiple responses possible)
List reasons
1. Market closed
............................................................................................ Yes = 1 No = 
2
|___|
2. No road or poor road condition
............................................................................................
Yes = 1 No = 
2
|___|
3. No transportation
............................................................................................
Yes = 1 No = 
2
|___|
4. Could not pay for transportation
............................................................................................
Yes = 1 No = 
2
|___|
5. Security problem
............................................................................................
Yes = 1 No = 
2
|___|
6. Other (specify)_________________________________ Yes = 1 No = 
2
|___|
352 How far away is the nearest market for purchasing agricultural 
inputs from this village? (kms) |___|___|___|
353 In the last 12 months, was there a time when people in this village 
needed to buy agricultural inputs in the market but could not? 1. Yes
2. No (Skip to q355)
|___|
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N° QUESTION WORDING CODES/ANSWERS
354 If yes, why were people in the village not able to buy agricultural 
inputs in the market?
(multiple responses possible)
List reasons
1. Market closed
............................................................................................ Yes = 1 No = 
2
|___|
2. No road or poor road condition
............................................................................................ Yes = 1 No = 
2
|___|
3. No transportation
............................................................................................ Yes = 1 No = 
2
|___|
4. Could not pay for transportation
............................................................................................ Yes = 1 No = 
2
|___|
5. Security problem
............................................................................................ Yes = 1 No = 
2
|___|
6. Other (specify)_________________________________ Yes = 1 No = 
2
|___|
SECURITY
355 Does this village have a security or police force? 1. Yes
2. No (Skip to q357)
|___|
356 If yes, who provides the security/police force?
(multiple responses possible)
List providers
1. Local government
............................................................................................ Yes = 1 No = 
2
|___|
2. National government
............................................................................................ Yes = 1 No = 
2
|___|
3. Community members
............................................................................................ Yes = 1 No = 
2
|___|
4. Other (specify) 
............................................................................................ Yes = 1 No = 
2
|___|
357 How long does it take for security/police force to reach this 
village? 1. Over one hour
2. About one hour
3. Half an hour
|___|
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N° QUESTION WORDING CODES/ANSWERS
4. Minutes
SAVINGS/CREDIT
358 Are there people or institutions in this village where people can 
save money? 1. Yes
2. No (Skip to q360)
|___|
359 If yes, which persons or institutions provide these services?
(multiple responses possible)
List providers
1. Banks
................................................................................................. Yes = 1 No = 
2
|___|
2. NGO/Project
................................................................................................. Yes = 1 No = 
2
|___|
3. Community group/Association/Group
................................................................................................. Yes = 1 No = 
2
|___|
4. Friends/relatives
................................................................................................. Yes = 1 No = 
2
|___|
5. Shops/merchants
................................................................................................. Yes = 1 No = 
2
|___|
6. Microfinance institution (MFI) 
................................................................................................. Yes = 1 No = 
2
|___|
7. Other (specify)_________________________________ Yes = 1 No = 
2
|___|
360 Are there people or institutions in this village from which people 
can borrow money? 1. Yes
2. No (Skip to q362)
|___|
361 If yes, which persons or institutions provide these services?
(multiple responses possible)
List providers
1. Banks
................................................................................................. Yes = 1 No = 
2 |___|
2. NGO/Project
................................................................................................. Yes = 1 No = 
2 |___|
3. Community group/Association/Group Yes = 1 No = |___|
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N° QUESTION WORDING CODES/ANSWERS
................................................................................................. 2
4. Friends/relatives
................................................................................................. Yes = 1 No = 
2 |___|
5. Shops/merchants
................................................................................................. Yes = 1 No = 
2 |___|
6. Microfinance institution (MFI) 
................................................................................................. Yes = 1 No = 
2 |___|
7. Other (specify)_________________________________ Yes = 1 No = 
2 |___|
OTHER PROGRAMS AND SERVICES
362 Are there institutions in this village where people can receive 
adult education or training? 1. Yes
2. No (Skip to q364)
|___|
363 If yes, who provides these services?
(multiple responses possible)
List providers
1. Government
................................................................................................. Yes = 1 No = 
2
|___|
2. NGO/Project
.................................................................................................
Yes = 1 No = 
2
|___|
3. Religious organization
.................................................................................................
Yes = 1 No = 
2
|___|
4. Community group/Association/Group
................................................................................................. Yes = 1 No = 
2
|___|
5. Other 
(specify)_________________________________
Yes = 1 No = 
2
|___|
364 Are there institutions in this village where people can receive food 
assistance?
1. Yes
2. No (Skip to q366) |___|
365 If yes, who provides these services?
(multiple responses possible)
List providers
1. Government
................................................................................................. Yes = 1 No = 
2
|___|
2. NGO/Project
.................................................................................................
Yes = 1 No = 
2
|___|
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N° QUESTION WORDING CODES/ANSWERS
3. Religious organization
.................................................................................................
Yes = 1 No = 
2
|___|
4. Community group/Association/Group
................................................................................................. Yes = 1 No = 
2
|___|
5. Other 
(specify)_________________________________
Yes = 1 No = 
2
|___|
366 Are there institutions in this village where people can receive 
housing materials or other non-food items assistance?
1. Yes
2. No (Skip to q368) |___|
367 If yes, who provides these services?
(multiple responses possible)
List providers
1. Government
.................................................................................................
Yes = 1 No = 
2 |___|
2. NGO/Project
.................................................................................................
Yes = 1 No = 
2 |___|
3. Religious organization
.................................................................................................
Yes = 1 No = 
2 |___|
4. Community group/Association/Group
.................................................................................................
Yes = 1 No = 
2 |___|
5. Other 
(specify)_________________________________
Yes = 1 No = 
2 |___|
368 Are there people/institutions in this village from which people can 
receive assistance in the case of livestock losses? 1. Yes
2. No (Skip to q370)
|___|
369 If yes, who provides these services?
(multiple responses possible)
List providers
1. Government
...............................................................................................
Yes 
= 1
No 
= 
2 |___|
2. NGO/Project
...............................................................................................
Yes 
= 1
No 
= 
2 |___|
3. Religious organization
Yes 
= 1
No 
= |___|
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N° QUESTION WORDING CODES/ANSWERS
............................................................................................... 2
4. Community group/Association/Group
...............................................................................................
Yes 
= 1
No 
= 
2 |___|
5. Other 
(specify)_________________________________
Yes 
= 1
No 
= 
2 |___|
370 Are there people/institutions in this village from which people can 
receive assistance due to losses of crops? 1. Yes 
2. No (Skip to next module)
|___|
371 If yes, who provides these services?
(multiple responses possible)
List providers
1. Government
...............................................................................................
Yes 
= 1
No 
= 
2 |___|
2. NGO/Project
...............................................................................................
Yes 
= 1
No 
= 
2 |___|
3. Religious organization
...............................................................................................
Yes 
= 1
No 
= 
2 |___|
4. Community group/Association/Group
...............................................................................................
Yes 
= 1
No 
= 
2 |___|
5. Other 
(specify)_________________________________
Yes 
= 1
No 
= 
2 |___|
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MODULE 4. COMMUNITY ORGANIZATIONS
TYPES OF COMMUNITY ORGANIZATION
QUESTION WORDING AND NUMBER
401 402 403
What are the 
community 
organizations and
groups that are active 
in this village?
Circle the codes for the 
following community 
organizations and
groups that are active in 
this village
Who participates in this 
group?
1= Men
2= Women
3= Both 
Which age group participates in 
this group?
1=Youth
2=Adults
3=Older persons
4=Everyone
List of the types of community organization Code
Water users' group 01 |___| |___|
Grazing land users' group 02 |___| |___|
Disaster planning group (SCAP RU in Niger) 03 |___| |___|
Health committee 04
Students’ group 05
Community police/monitoring group 06
Credit or micro-finance group 07 |___| |___|
Mutual help group (including burial companies) 08 |___| |___|
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Trade or business associations 09 |___| |___|
Civic group (improving community) 10 |___| |___|
Charitable group (helping others) 11 |___| |___|
Religious group 12 |___| |___|
Political group 13 |___| |___|
Women's group 14 |___| |___|
Youth group 15 |___| |___|
Other (specify) 16 |___| |___|
Other (specify) 17 |___| |___|
Other (specify) 18 |___| |___|
|___| |___|
|___| |___|
|___| |___|
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MODULE 5. GOVERNMENT AND NGO PROGRAMS 
N° QUESTION WORDING CODES/ANSWERS
501 Were there any government programs implemented in 
this village in the last 5 years?
1. Yes 
2. No (Skip to q503) |___|
502 If yes, what kinds of government programs are there?
(List all programs) 
1. Livestock 
.................................................................................. Yes = 
1
No = 
2
|___|
2. Agriculture 
.................................................................................. Yes = 
1
No = 
2
|___|
3. Water
.................................................................................. Yes = 
1
No = 
2
|___|
4. Health
.................................................................................. Yes = 
1
No = 
2
|___|
5. Disaster planning
.................................................................................. Yes = 
1
No = 
2
|___|
6. Disaster response
.................................................................................. Yes = 
1
No = 
2
|___|
7. Other (specify) 
________________________________ Yes = 
1
No = 
2
|___|
8. Other (specify) 
________________________________ Yes = 
1
No = 
2
|___|
9. Other (specify) 
________________________________ Yes = 
1
No = 
2
|___|
503 Were there any NGO programs implemented in this 
village in the last 5 years?
1. Yes 
2. No (Skip to next module)
|___|
504 If yes, what kinds of NGO programs are there? 1. Livestock 
.................................................................................. Yes = 
1
No = 
2
|___|
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(List all programs) 2. Agriculture 
.................................................................................. Yes = 
1
No = 
2
|___|
3. Water
.................................................................................. Yes = 
1
No = 
2 |___|
4. Health
.................................................................................. Yes = 
1
No = 
2
|___|
5. Disaster planning
.................................................................................. Yes = 
1
No = 
2
|___|
6. Disaster response
.................................................................................. Yes = 
1
No = 
2
|___|
7. Other (specify) 
________________________________ Yes = 
1
No = 
2
|___|
8. Other (specify) 
________________________________ Yes = 
1
No = 
2
|___|
9. Other (specify) 
________________________________ Yes = 
1
No = 
2
|___|
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MODULE 6. SHOCKS
TYPES OF SHOCKS
QUESTION NUMBERS AND ANSWER CODES
601 602 603 604 605 606
SHOCK LIST
List shocks and circle the answer. Put the 
year when the shocks occurred, even if a 
shock occurred several times in the same 
year
Over the past five years, what 
shock(s) has this village 
experienced?
Circle the shock(s) 
experienced by this village over 
the past 5 years
Date (mo/year)
(2017)
If the month is 
unknown, enter the 
year when the shock 
was experienced
Date (mo/year)
(2016)
If the month is 
unknown, enter the 
year when the shock 
was experienced
Date (mo/year)
(2015)
If the month is 
unknown, enter the 
year when the shock 
was experienced
Date (mo/year)
(2014)
If the month is 
unknown, enter the 
year when the shock 
was experienced
Date (mo/year)
(2013)
If the month is 
unknown, enter the 
year when the shock 
was experienced
Climatic shocks Code
Excessive rains/floods 01 |__|__|/|__|__|__|__| |__|__|/|__|__|__|__| |__|__|/|__|__|__|__| |__|__|/|__|__|__|__| |__|__|/|__|__|__|__|
Too little rain/drought 02 |__|__|/|__|__|__|__| |__|__|/|__|__|__|__| |__|__|/|__|__|__|__| |__|__|/|__|__|__|__| |__|__|/|__|__|__|__|
Massive insect invasion 03 |__|__|/|__|__|__|__| |__|__|/|__|__|__|__| |__|__|/|__|__|__|__| |__|__|/|__|__|__|__| |__|__|/|__|__|__|__|
Epizootic 04 |__|__|/|__|__|__|__| |__|__|/|__|__|__|__| |__|__|/|__|__|__|__| |__|__|/|__|__|__|__| |__|__|/|__|__|__|__|
Bush fires 05 |__|__|/|__|__|__|__| |__|__|/|__|__|__|__| |__|__|/|__|__|__|__| |__|__|/|__|__|__|__| |__|__|/|__|__|__|__|
Erosion 06 |__|__|/|__|__|__|__| |__|__|/|__|__|__|__| |__|__|/|__|__|__|__| |__|__|/|__|__|__|__| |__|__|/|__|__|__|__|
Conflict shocks 
Land conflicts 07 |__|__|/|__|__|__|__| |__|__|/|__|__|__|__| |__|__|/|__|__|__|__| |__|__|/|__|__|__|__| |__|__|/|__|__|__|__|
Conflicts between farmers and breeders 08 |__|__|/|__|__|__|__| |__|__|/|__|__|__|__| |__|__|/|__|__|__|__| |__|__|/|__|__|__|__| |__|__|/|__|__|__|__|
Conflict/violence involving entire 
communities/villages 09 |__|__|/|__|__|__|__| |__|__|/|__|__|__|__| |__|__|/|__|__|__|__| |__|__|/|__|__|__|__| |__|__|/|__|__|__|__|
Theft of assets/holdups (animals, crops, 
etc.) 10 |__|__|/|__|__|__|__| |__|__|/|__|__|__|__| |__|__|/|__|__|__|__| |__|__|/|__|__|__|__| |__|__|/|__|__|__|__|
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TYPES OF SHOCKS
QUESTION NUMBERS AND ANSWER CODES
601 602 603 604 605 606
Economic shocks 
Sharp food price increase 11 |__|__|/|__|__|__|__| |__|__|/|__|__|__|__| |__|__|/|__|__|__|__| |__|__|/|__|__|__|__| |__|__|/|__|__|__|__|
Unavailability of agricultural or livestock 
inputs 12 |__|__|/|__|__|__|__| |__|__|/|__|__|__|__| |__|__|/|__|__|__|__| |__|__|/|__|__|__|__| |__|__|/|__|__|__|__|
Drop in agricultural or livestock product 
demand 13 |__|__|/|__|__|__|__| |__|__|/|__|__|__|__| |__|__|/|__|__|__|__| |__|__|/|__|__|__|__| |__|__|/|__|__|__|__|
High increase in price of agricultural or 
livestock inputs 14 |__|__|/|__|__|__|__| |__|__|/|__|__|__|__| |__|__|/|__|__|__|__| |__|__|/|__|__|__|__| |__|__|/|__|__|__|__|
Drop in price of agricultural or livestock 
products 15 |__|__|/|__|__|__|__| |__|__|/|__|__|__|__| |__|__|/|__|__|__|__| |__|__|/|__|__|__|__| |__|__|/|__|__|__|__|
Job loss by household member 16 |__|__|/|__|__|__|__| |__|__|/|__|__|__|__| |__|__|/|__|__|__|__| |__|__|/|__|__|__|__| |__|__|/|__|__|__|__|
Abrupt end of support/regular support from 
outside the household 17 |__|__|/|__|__|__|__| |__|__|/|__|__|__|__| |__|__|/|__|__|__|__| |__|__|/|__|__|__|__| |__|__|/|__|__|__|__|
Sudden increase in household size 
(including birth: triplets etc.) 18 |__|__|/|__|__|__|__| |__|__|/|__|__|__|__| |__|__|/|__|__|__|__| |__|__|/|__|__|__|__| |__|__|/|__|__|__|__|
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MODULE 6b. MANAGEMENT OF CLIMATE SHOCKS
N° QUESTION WORDING CODES/ANSWERS
601b Over the last 5 to 10 years have you noticed a significant change in climate in this village? 1=Yes
2=No >> Skip to next module |___|
602b If yes, list the two main effects of climate change that have had the most impact on 
villagers' welfare? 
1=Irregular rains; 
2=Poor rainfall distribution in time and space; 
3=Drought; 
4=Floods; 
5=Poor groundwater recharge;
6=Loss of vegetation cover; 
7=Disappearance of certain wild animal species; 
8=Other (specify)
1st |___|___|
2nd |___|___|
603b List the three main new practices or techniques adopted in this village to address the 
impact of climate change
01=Improved seed; 
02=Irrigation (off-season crops) 
03=Mineral fertilizer 
04=Organic fertilizer 
05=Zai; 
06=Half-moon; 
07=Bunds; 
08=Trenches; 
09=Benches (contour earth bunds); 
10=Tree planting; 
11=Mulching; 
12=Composting 
13=Fallow; 
14=Cultivation techniques (seeding rate, crop 
1st |___|___|
2nd |___|___|
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N° QUESTION WORDING CODES/ANSWERS
rotation...);
15=Plant treatment; 
16=Breed improvement; 
17=Feed improvement; 
18=De-worming; 
19=Immunization; 
20=Feed treatment/conservation; 
21=Fish farming techniques; 
22=Other (specify)___________________
3rd |___|___|
604b1 What is the level of implementation of the first new practice or technique to adapt to 
climate change by inhabitants? 1. Very high (75% - 100%)
2. Average (50% - 74%)
3. Low (1% - 49%)
4. No implementation (0%)
|___|
604b2 What is the level of implementation of the second new practice or technique to adapt to 
climate change by inhabitants? 1. Very high (75% - 100%)
2. Average (50% - 74%)
3. Low (1% - 49%)
4. No implementation (0%)
|___|
604b3 What is the level of implementation of the third new practice or technique to adapt to 
climate change by inhabitants? 1. Very high (75% - 100%)
2. Average (50% - 74%)
3. Low (1% - 49%)
4. No implementation (0%)
|___|
605b What is the level of effectiveness of adaptation to the impact of climate change in this 
village? 1. Very effective
2. Average
3. Low
4. Not effective at all
|___|
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N° QUESTION WORDING CODES/ANSWERS
606b In your village, are there resource people trained in techniques to cope with climate 
change who disseminate those techniques?
1. Yes 
2. No |___|
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MODULE 7. LAND MANAGEMENT
N°
TYPES OF LAND TENURE
List the types of land tenure
What are the types of land tenure that exist in your village?
1=Yes 2=No
701. Customary – privately held |___|
702. Customary land – communally held |___|
703. Leasehold |___|
704. Freehold |___|
705. Public land |___|
706. Other (specify) |___|
707. What is the main mode of acquisition of 
a farm in your village today?
Enter the answer
1. Cash purchase
...........................................................................................................................
|___| 2. Allocation by the community/local authorities Inheritance
...........................................................................................................................
3. Obtained for free/gift
...........................................................................................................................
4. Possession taken (after deforestation) 
...........................................................................................................................
5. Other (specify) 
...........................................................................................................................
What is the second most common 1. Cash purchase
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708 mode of acquisition of a farm in your 
village today? 
Enter the answer
...........................................................................................................................
|___|
2. Allocation by the community/local authorities Inheritance
...........................................................................................................................
3. Obtained for free/gift
...........................................................................................................................
4. Possession taken (after deforestation) 
...........................................................................................................................
5. Other (specify) 
...........................................................................................................................
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MODULE 8. GOVERNANCE
N° QUESTION WORDING CODES/ANSWERS
801
What type of community governance do you have in your village? 1. Traditional 
2. Formal government 
representative
3. Both
|___|
802 Has your village defined clear and widely accepted rules to ensure good 
management of natural resources? 
1. Yes
2. No |___|
803 Do you have a natural resources management-related conflict resolution committee 
in your village?
1. Yes
2. No (Skip to q805) |___|
804
Is the conflict resolution committee successful in finding appropriate and sustainable 
solutions to conflicts that arise? 
1. All
2. Most
3. About half 
4. Less than half 
5. Very few
|___|
805
Does your village take regular initiatives to engage with commune (municipal) and 
state authorities to increase the quality of public infrastructure and services (health, 
agriculture, education, roads, etc.)?
1. Often
2. Periodically
3. Very rarely
4. Never
|___|
806
Does your commune (municipality) have a commune (municipal) development 
plan?
1. Yes
2. No
3. DK
|___|
807
Does your village chief share commune (municipal) development plan 
implementation-related information with the public?
1. Often
2. At least once a year
3. Never
4. DK
|___|
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**THANK YOU**
After the interview thank the respondents for giving you their time and for the co-operation in providing the 
information. Inform them that you may possibly be returning to collect more information or seek any necessary 
clarification on the information provided at later date. At this point invite the respondents to ask you any questions 
that they might have. Answer where you can. If you do not know the answer(s), tell them that their questions will 
be forwarded to a relevant person who can respond.
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Appendix D. Midline Sample Villages
Villages in RISE Midline Sample – BURKINA FASO
Region Province Commune Village Stratum RISE Project(s) X Y
1
EST
Gnagna
Coalla Ganta H FASO -0.074 13.524
2 Mani Koulfo H REGIS-ER, FASO -0.001 13.232
3
Bilanga
Dipienga L 0.218 12.779
4 Kabaré L 0.101 12.564
5 Tobou L 0.087 12.612
6 Benhourgou L 0.506 12.393
7 Piela Piéla L -0.140 12.719
8
Komandjari
Gayeri
Toumbenga H REGIS-ER, FASO 0.566 12.762
9 Kourgou H REGIS-ER, FASO -0.766 12.321
10 Foutouri Tankoualou H REGIS-ER, FASO 0.954 12.987
11
Gourma
Matiacoali
Oubriounou L 1.065 12.410
12 Boaligou L 1.068 12.458
13 Ouro-Aou L 0.901 12.677
14
Yamba
Bogolé L 0.515 12.288
15 Diankongou L -0.118 13.283
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Region Province Commune Village Stratum RISE Project(s) X Y
16
SAHEL
Yagha
Mansila
Mansila L 0.638 13.164
17 Téparé L 0.539 13.186
18 Solhan Gongorgouol H REGIS-ER, FASO 0.495 13.318
19 Boundore Louba L 0.909 13.264
20
Soum
Tongomayel
Kobaoua L -1.519 13.939
21 Touronata L -1.329 14.245
22 Kadiel L -1.435 13.909
23
Arbinda
Sikiré L -0.732 14.310
24 Yirakoulga L -0.719 14.007
25
Seno
Gorgadji Boundounyoudji L -0.457 14.064
26
Falagountou
Falagountou L 0.186 14.364
27 Fétobarabé L 0.092 14.378
28 Seytenga Oussaltan-Dongobé H REGIS-ER 0.447 13.908
29
Oudalan
Gorom-Gorom
Bosséye-Barabé L -0.332 14.539
30 Essakane-Site L 0.025 14.395
31 Adiaréye-Diaréye L -0.571 14.354
32
Gorom-Gorom-Secteur 
5 L -0.232 14.439
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Region Province Commune Village Stratum RISE Project(s) X Y
33 Kel-Eguief L -0.184 14.427
34 Bidi 2 L -0.328 14.372
35 Dambouguél L -0.364 14.202
36
Markoye
Markoye L 0.034 14.645
37 Déibanga-Tafororat L -0.031 14.795
38 Weldé-Tondobanda L 0.057 14.581
39
CENTR
E￾NORD
Sanmatenga
Kaya Kaya-Secteur 4 H VIM -1.087 13.072
40 Kaya-Secteur 5 H VIM -1.107 13.088
41 Foura H VIM -1.300 13.188
42 Konéan H VIM -0.984 13.099
43 Basnéré H VIM -1.261 13.255
44 Nongfaeré-Bangré H VIM -1.059 13.185
45 Ilyalla H VIM -1.117 13.236
46
Pissila
Pissila H VIM -0.825 13.163
47 Poulallé H VIM -0.850 13.094
48
Mane
Guinsa L -1.322 13.101
49 Forgui L -0.952 12.997
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Region Province Commune Village Stratum RISE Project(s) X Y
50 Namisgma Nyonranga H VIM -1.301 13.357
51 Pensa Zinibéogo L -0.747 13.832
52
Namentenga
Boulsa
Belga L -0.491 12.878
53 Kobouré L -0.519 12.620
54 Niega L -0.504 12.525
55 Konkoara-Yarsé L -0.586 12.540
56
Tougouri
Tilga H FASO -0.596 13.109
57 Taonsogo H FASO -0.641 13.230
58 Bouroum Bélogo H REGIS-ER, FASO -0.568 13.774
Villages in RISE Midline Sample – NIGER
Region Department Commune Village Stratum RISE Project(s) X Y
1
MARADI
Aguie Tchadoua Hardo Bi Seyni H LAHIA 7.540 13.385
2
Dakoro
Mayara
Itta Ibro L 7.244 14.070
3 Tajae Agolla L 7.217 13.886
4 Sabon Machi Zabouré Maikasso H REGIS-ER 7.231 13.136
5 Gazaoua Gangara Makada H LAHIA 7.870 13.427
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Region Department Commune Village Stratum RISE Project(s) X Y
6
Guidan 
Roumdji
Chadakori
Dan Baouchi L 7.084 13.719
7 Garin Moutoun Daya L 7.019 13.682
8 Guidan-Ara L 7.067 13.684
9 Talala L 6.990 13.680
10 Guidan Roumdji Dan Turké H REGIS-ER; Sawki 6.770 13.670
11
Mayahi Kanin Bakache
Dillali Maissongo H PASAM-TAI 7.744 13.897
12 Zaroumey H PASAM-TAI 8.019 13.924
13
TILLABERI
Filingue Kourfeye Centre Chical Chanyassou L 3.435 14.236
14
Gotheye Dargol
Agoufour L 1.417 14.033
15 Djoubourga L 1.318 13.852
16 Goria Bangou Tara L 1.319 13.802
17 Goungo Djoubourga L 1.290 13.825
18 Tondi Tchiria L 1.319 14.071
19 Wiya Banguia L 1.135 14.007
20 Kollo Hamdallaye Nazey Gado Baba Koira L 2.552 13.819
21
Ouallam
Dingazi Tanga Koira L 2,252 14.248
22 Alfagaydo L 2.488 13.984
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Region Department Commune Village Stratum RISE Project(s) X Y
23 Simiri Gaobanda Guesse L 2.174 14.186
24 Tchedi Kouara L 2.201 14.052
25
Tera Mehana
Kobachire L 1.042 14.537
26 Mehana L 1.137 14.398
27
ZINDER
Dungass Dungass
Garin Dan Baba L 9.103 13.143
28 Garin Ml Garke L 9.394 13.057
29
Kantche
Dan Barto Zakarawa H PASAM-TAI 8.403 13.243
30
Daouche
Amsoudou H PASAM-TAI 8.410 13.500
31 Badahi Haoussa H PASAM-TAI 8.420 13.452
32
Ichirnawa
Daratchama H PASAM-TAI 8.618 13.619
33 Tacheri H PASAM-TAI 8.625 13.502
34 Kantche Kourni Bougage H PASAM-TAI 8.420 13.570
35 Kourni Walawa 2 H PASAM-TAI 8.435 13.190
36 Yaouri Guidan Elhadj Zakko H PASAM-TAI 8.675 13.253
37 Matameye Maguirami Hausa H PASAM-TAI 8.535 13.369
38
Magaria Bande
Bandé H REGIS-ER 8.891 13.170
39 Dan Ala H REGIS-ER 8.835 13.103
40 Mirriah Gouna Garin Arewa L 9.052 13.519
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Region Department Commune Village Stratum RISE Project(s) X Y
41 Tchoukoulaoua I L 9.153 13.585
42 Zangou Malam Kadre L 9.114 13.469
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Appendix E1. Scope of Work – Data Collection
Termes de Référence :
Enquête quantitative à mi-parcours dans la 
zone USAID/RISE
Collecte et traitement des données
Septembre 2016
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CONTEXTE ET JUSTIFICATION DE LA PRESTATION
“Sahel Résilience Learning Project” (SAREL) est un projet d’apprentissage sur la résilience au 
Sahel d’une durée de cinq ans (2014 à 2019), financé par l’Agence américaine pour le 
Développement International (USAID) et mis en œuvre par The Mitchell Group, Inc. (TMG), 
un bureau d’études américain de conseil en développement, avec un consortium de 
partenaires.
L’objectif du projet SAREL consiste à assurer un soutien aux activités de suivi, d’évaluation, 
de collaboration et d’apprentissage dans le cadre de la programmation en matière de résilience 
de l’USAID au Sahel. En tant que tel, il ne s’agit pas d’une intervention autonome. C’est l’un 
de trois nouveaux projets financés par l’USAID dans les régions du Centre-nord, du Sahel, et 
de l’Est du Burkina Faso, ainsi que les régions de Tillaberi, Maradi, et Zinder au Niger, dont : 
• Résilience et Croissance Économique au Sahel – Résilience Améliorée ou « Enhanced 
Résilience Coopérative Agreement » (REGIS-ER), lancé en fin 2013 ; et 
• Résilience et Croissance Économique au Sahel – Croissance Accélérée et Création de 
Chaîne de Valeur ou « Accelerated Growth (Value Chain) » (REGIS-AG), lancé en 
2015.
L’initiative RISE inclut également les Projets Vivres pour la Paix ou « Food for Peace » (FFP) 
financés par l’USAID qui interviennent au Niger (dans les régions de Maradi et de Zinder) 
depuis 2013 et au Burkina Faso dans la région du Sahel (Dori) et dans la région du Centre 
Nord (Kaya) depuis 2011 (voir carte ci-dessous).
Carte de la zone d’intervention de RISE (en bleu)
RAMSAR 
tl d
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Les résultats attendus du SAREL sont :
1. Tester, élargir, et accélérer l’adoption de technologies éprouvées permettant de 
renforcer la résilience et les innovations en cours
2. Développer, tester et catalyser l’adoption généralisée de nouveaux modèles intégrant 
l’assistance humanitaire et au développement
3. Promouvoir l’appropriation, accroitre les capacités des institutions nationales et 
régionales, et coordonner les interventions humanitaires de développement dans les 
zones d’intervention
4. Traiter des questions relatives au genre qui sont essentielles à la résilience et à la 
croissance
5. Créer une base de données de gestion des connaissances qui abritera une évaluation 
de base, des données de suivi en cours, et des évaluations d’impact de l’initiative RISE.
Dans le cadre de l’objectif 5, il est prévu la réalisation d’études pour collecter les données 
quantitatives et qualitatives nécessaires au suivi et à l’évaluation de l’initiative RISE au Burkina 
Faso et au Niger.
Ainsi SAREL a réalisé en 2015 une étude quantitative de base auprès de 2492 ménages répartis 
dans 100 villages (42 au Niger et 58 au Burkina Faso) en vue d’établir la situation de référence 
de 23 indicateurs de performance de l’Initiative RISE. La collecte des données de cette 
première enquête s’est déroulée sur le terrain de fin avril à fin mai 2015. Cette étude 
quantitative a été complétée par une étude qualitative conduite par une autre firme 
(TANGO). 
Pour la réalisation de cette enquête de base, SAREL, avec l’appui d’une structure universitaire 
basée à Ouagadougou (Burkina Faso), a élaboré un document méthodologique (méthode 
d’évaluation, plan de sondage, tirage de l’échantillon au premier degré) et a finalisé les outils 
de collecte des données (en adaptant les outils utilisés dans le cadre d’un projet similaire de 
l’USAID en Ethiopie) comprennent un questionnaire-ménage, un questionnaire village, un 
questionnaire sur l’anthropométrie, un questionnaire genre. SAREL a également développé 
des manuels pour faciliter la mise en œuvre de cette enquête (manuels de l’enquêteurs, 
manuels de contrôleurs, les guides en langues sur les concepts et questions clés des 
questionnaires).
Conformément à son plan d’évaluation, en vue de mesurer le niveau de progrès au niveau de 
ces indicateurs, deux ans après la mise en œuvre de cette première enquête, SAREL envisage 
de conduire une enquête à mi-parcours dans les mêmes villages au cours de la même période 
(mars-avril 2017) en s’appuyant sur les mêmes outils et la même méthodologie développés 
pour l’enquête de base. 
Dans le cadre de la mise en œuvre de cette enquête à mi-parcours, SAREL recherche les 
services d’une organisation ou un bureau d’étude avec une expérience solide de conduite des 
études quantitatives auprès d’un nombre important de ménages, et bien imprégné de la 
question de la résilience pour l’appuyer dans la réalisation de l’enquête de mi-parcours. 
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OBJECTIFS DE LA PRESTATION
L’objectif global de la présente mission est de réaliser une enquête quantitative à mi-parcours 
dans les 100 villages de la zone RISE.
Les objectifs spécifiques sont :
• Assurer le recrutement, la formation du personnel ; 
• Assurer la collecte des données sur le terrain ;
• Assurer le traitement des données.
ACTIVITES
Il s’agit de préparer et conduire l’enquête dans les mêmes villages que ceux de l’enquête de 
base. Il est important de rappeler que l’enquête de base a permis de collecter les données 
sur :
• 100 villages (questionnaires villages) ;
• 2492 ménages (sur une prévision de 2500) à travers le questionnaire ménage ;
• 2488 femmes (épouses des chefs de ménages échantillonnés) dans le cadre du 
questionnaire genre) ;
• 2403 enfants de moins de 5 ans des ménages échantillonnés dans le cadre du 
questionnaire anthropométrie (mesure de poids, taille, longueur des enfants).
L’enquête de mi-parcours a pour objectif de collecter les données sur les mêmes groupes 
cibles (villages, ménages, les femmes épouses des chefs des ménages et les enfants de moins 
de 5 ans des ménages) afin de pouvoir mesurer le niveau des indicateurs de performance de 
RISE. 
Dans le cadre cette mission, le Consultant aura à :
• produire la méthodologie de mise en œuvre de l’enquête (sur la base des éléments 
d’orientation formulés par SAREL-voir point V. Méthodologie) ; 
• recruter et former le personnel de terrain (enquêteurs, contrôleurs et superviseurs) ;
• réaliser l’enquête pilote (et éventuellement finaliser la méthodologie et les outils de 
collecte des données sur la base des leçons apprises) ;
• préparer et conduire une campagne d’information auprès des autorités administratives 
et communales, et des autorités traditionnelles et communautaires ;
• mettre en place et déployer des équipes pour la conduite de l’enquête ;
• procéder au tirage des unités secondaires (ménages) ;
• administrer les questionnaires ;
• recruter et former les agents de saisie ;
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• développer les programmes de saisie ;
• saisir et apurer les données ;
• faire l’archivage électronique et physique des questionnaires de l’enquête.
LIVRABLES
Les livrables suivants sont attendus par le consultant au terme de la prestation :
Livrable 1 : La proposition méthodologique détaillée de mise en œuvre de l’enquête sur le 
terrain comprenant :
• la démarche méthodologique de mise en œuvre de l’enquête ;
• le plan de communication (campagne d’information) de l’enquête ; 
• le chronogramme de travail détaillé.
Livrable 2 : Les programmes de saisie des données.
Livrable 3 : Le rapport de recrutement et de formation du personnel de terrain comprenant 
entre autres :
• la liste des candidats recrutés pour la formation et leurs CVs; 
• le programme de formation ;
• le déroulement de l’enquête pilote ;
• l’instrument et la méthode d’évaluation et de sélection des superviseurs et 
enquêteurs ;
• la liste du personnel retenu après la formation ;
• le plan de déploiement des équipes sur le terrain ;
• la logistique.
Livrable 4 : Le rapport de la campagne d’information de l’enquête auprès des autorités 
administratives et communales, et les autorités traditionnelles et communautaires.
• Le déroulement de la mission (étapes, période) ;
• Le point saillant des activités conduites (rencontres, thèmes débattus, les réactions 
pertinentes des acteurs rencontrés relativement à l’objet de l’enquête en termes de 
suggestions, remarques, recommandations etc…) ;
• Les adresses des personnes rencontrées (noms et prénoms, structures, fonctions, 
numéros de téléphone, mails etc.) ;
• Une conclusion succincte axée sur les leçons apprises de cette mission notamment la 
participation des acteurs, leurs réactions et toutes autres suggestions qui pourraient 
aider lors de la mise en œuvre de l’enquête sur le terrain.
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Livrable 5 : Le rapport terrain de l’enquête décrivant notamment :
• le déploiement des équipes ;
• le processus de collecte, de supervision et de contrôle qualité ;
• les difficultés rencontrées ;
• les recommandations. 
Livrable 6 : Les bases des données sur les logiciels SPSS, STATA, EXCEL accompagnées d’un 
guide de codification ;
Livrable 7 : Rapport final de l’enquête ;
Livrable 8 : Questionnaires papier remplis archivés ;
Livrable 9 : CD-Rom d’archivage électronique de l’enquête.
METHODOLOGIE 
La méthodologie du consultant devra faire ressortir les éléments sur lesquels il doit s’appuyer 
pour mener le travail ci-dessus décrit. A titre d’orientation, le Consultant doit bâtir sa 
méthodologie sur les points suivants (non limitatif) :
1 Recrutement du personnel de terrain 
La collecte de données de haute qualité est essentielle pour le succès de l'enquête. Il est 
important de recruter des personnes matures, responsables pour jouer le rôle d'enquêteurs 
et qu'elles accomplissent leurs missions avec soins et précisions. Le Consultant devra 
constituer un nombre adéquat d’équipes d’enquêteurs et d’enquêtrices, de contrôleurs et de 
superviseurs de manière à couvrir l’ensemble des villages échantillons dans le délai imparti. 
Dans le recrutement, le Consultant doit veiller à une bonne répartition entre les hommes et 
les femmes et la connaissance de la langue locale des villages à enquêter.
Dans sa proposition méthodologique, le Consultant devra préciser notamment :
• Comment mettra-t-il en place son personnel (superviseurs, contrôleurs et 
enquêteurs) ?
• Comment compte-t-il assurer la collecte des données au niveau des femmes et des 
données anthropométriques au niveau des enfants de moins de cinq (5) ans ?
• Comment tenir compte de la diversité linguistique des villages échantillonnés dans la 
collecte des données ?
2 Formation du personnel
La formation des équipes d’enquêtes étant la clé de réussite du processus, le Consultant devra 
proposer un programme de formation et une stratégie en vue de la mise en œuvre de cette 
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formation. Cette formation devra couvrir toutes les taches, techniques et approches 
méthodologiques et aspects d’éthiques indispensables que les équipes doivent maitriser pour 
la mener à bien leurs missions. La formation doit par ailleurs permettre aux équipes de se 
familiariser avec les outils de collecte des données (questionnaires, utilisation des outils de 
mesures anthropométriques, etc.) et les procédures de tirage des ménages, entretien avec 
enquêteurs). La formation doit permettre une maitrise des rôles et des responsabilités des 
différents membres des équipes d’enquêtes indispensable pour assurer une bonne 
collaboration sur le terrain.
Le consultant proposera une démarche à suivre pour tester les candidats ainsi que des critères 
d’évaluation permettant de juger de l’attitude des candidats face aux répondants et leur 
aptitude à administrer le questionnaire dans des temps acceptables. Les candidats qui 
démontreront des aptitudes supérieures durant la formation et l’enquête pilote pourront être 
retenus comme contrôleurs.
Le consultant élaborera à l’attention du SAREL un rapport de la formation qui devra contenir 
des éléments permettant de connaître le nombre d’enquêteurs recrutés, leur profil, leur 
répartition hommes / femmes, leur niveau d’instruction, leur lieu d’affectation et leurs 
aptitudes à communiquer dans la langue de la zone. 
En ce qui concerne particulièrement les éléments de stratégie pour cette formation, le 
Consultant devra expliquer : 
• Comment compte-t-il assurer le processus de formation du personnel de 
l’enquête ?
• Quels sont les aspects généraux les plus importants que le Consultant prendra en 
compte pour outiller les équipes d’enquêtes pour mieux asseoir une bonne 
collaboration et réussir la collecte des données sur le terrain ?
• Le SAREL est soucieux d’assurer la comparabilité et la fiabilité des résultats des 
enquêtes entre la zone RISE du Niger et celle du Burkina Faso. Pour ce faire, il est 
important que tout le personnel chargé de l’enquête y compris les coordinateurs, 
les contrôleurs, les superviseurs et les deux équipes d’enquêteurs aient une même 
compréhension et une même maîtrise des questionnaires et de la méthodologie 
de conduite de l’enquête. Quelles sont les dispositions que le Consultant propose 
pour répondre à cette préoccupation ?
• Pour que les questions soient posées de la même manière par tous les enquêteurs 
en vue de minimiser les biais des manuels en langues ont été élaborés prenant en 
compte les questions et concepts clés des questionnaires. Le Consultant dans son 
approche méthodologique devra indiquer comment son plan de formation prendra 
en compte la maîtrise en langues par les enquêteurs de ces questions et concepts 
clés ? 
• Comment le Consultant devra assurer la formation sur des aspects thématiques 
comme l’anthropométrie ?
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• Quelle démarche méthodologique à suivre pour tester les candidats ainsi que des 
critères d’évaluation pour juger l’attitude des candidats face aux répondants et leur 
aptitude à administrer le questionnaire dans des temps acceptables ?
• Etc. 
3. Réaliser l’enquête pilote
Cette phase de l’enquête est primordiale pour permettre aux enquêteurs de mieux 
s’imprégner des outils de collecte des données et à l’utilisation des autres manuels notamment 
le guide traduit en langue. Elle doit par ailleurs permettre de détecter les enquêteurs aptes à 
mener convenablement l’enquête. Elle doit permettre aussi de recenser des difficultés afin de 
mieux asseoir un dispositif cohérent et une organisation conséquente pour la collecte des 
données, la gestion de la logistique etc.
Dans sa méthodologie, le Consultant doit décrire comment il compte s’organiser pour mieux 
conduire cette phase. En particulier il doit ressortir :
• Quelles sont les dispositions qu’il compte prendre dans les deux pays pour la conduite 
de l’enquête pilote ?
• Comment compte-t-il faire pour évaluer la capacité des enquêteurs à faire usage des 
leçons apprises au cours de cette phase ?
• Etc.
4 Conduire la campagne d’information et de sensibilisation auprès des autorités 
administratives et coutumières
En prélude au déploiement des équipes d’enquête et à la collecte des données, il sera 
nécessaire de conduire une mission d’information et sensibilisation des acteurs dans les 
régions, les départements/provinces, les communes et les villages retenus – comme SAREL a 
fait pour l’enquête de base. La campagne – qui doit être achevée au moins 10 jours avant le 
premier déploiement des équipes d’enquêteurs – a pour objectif de porter l’information à 
tous les niveaux en vue de susciter l’adhésion des différents acteurs pour cette enquête. C’est 
pourquoi, SAREL a identifié et ciblé les acteurs ci-dessous pour cette campagne d’information : 
les Gouverneurs des régions concernées ; les Préfets ou Haut-Commissaires ; les Maires ; et 
les chefs de canton et de villages. Au niveau des autorités administratives, le Consultant devra 
fera un bref exposé (oral) de l’initiative RISE, le projet SAREL et situer l’objectif de l’enquête 
de mi-parcours. Au niveau village, la campagne devra rappeler le contexte de l’enquête et 
insister sur l’adhésion massive et la forte implication du village notamment au cours de 
l’énumération et de l’entretien avec les ménages échantillonnés. La mission discutera avec les 
autorités villageoises sur les facilités à accorder aux équipes d’enquêteurs qui seront dans les 
villages notamment l’identification de local pour les abriter tout au long de leur séjour, etc.
Dans sa proposition méthodologique, le Consultant devra préciser notamment :
• Comment il organisera la campagne d’information et de sensibilisation dans chaque 
pays (nombre d’équipes, composition, profil des membres) ?
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• Les supports à utiliser pour les rencontres avec les autorités ?
• Le calendrier indicatif
5.5. Déploiement des équipes d’enquête 
Dans sa proposition méthodologique, le Consultant devra faire ressortir :
• Comment compte-t-il assurer le déplacement des équipes d’enquête sur le terrain ?
• Comment compte-t-il gérer la logistique (contrats, véhicules, moto, les fournitures 
etc.) :
• Comment compte-t-il apporter un appui technique et organisationnel aux enquêteurs 
dans la collecte des données ?
• Quel mécanisme compte-t-il mettre en place pour assurer le contrôle de qualité des 
données ?
• Comment le Consultant compte-t-il surmonter et documenter les difficultés 
rencontrées par les équipes d’enquête ? 
• Quelle stratégie de communication le Consultant compte-t-il mettre en place pour 
une bonne mise en œuvre de la collecte des données sur le terrain ?
5.6. Collecte des données 
Le consultant procédera à la collecte des données conformément au plan de déploiement 
prévu. Au cours de cette phase, le Consultant mettra en œuvre sa stratégie de communication 
en vue de permettre une bonne mise en œuvre du processus. Il doit en outre veiller au 
mouvement des enquêteurs et des chefs d’équipes conformément au plan de déploiement. Il 
doit coordonner la logistique conformément au plan de travail et apporter un appui technique 
et organisationnel aux enquêteurs dans la collecte des données. 
Le consultant veillera à l’application des procédures convenues pour la vérification et le 
contrôle de qualité des données. L’application de ces procédures devrait permettre 
d’intervenir rapidement si des erreurs systématiques se produisent au niveau de 
l’administration des questions ou au niveau d’un enquêteur. Tout problème rencontré par les 
enquêteurs durant l’administration des questionnaires devrait être résolu par le consultant. 
Les contrôleurs et les superviseurs devront documenter fidèlement les difficultés rencontrées 
dans leurs zones.
Pour cette phase, le Consultant devra faire ressortir dans sa méthodologie :
• Les différentes étapes de mise en œuvre de l’enquête dans chaque village ;
• Quelle stratégie d’information et de sensibilisation du village et des ménages à 
enquêter que le Consultant compte mettre en place pour une meilleure adhésion des 
populations à l’enquête ?
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• Le contrôle qualité de la collecte des données étant la fonction la plus importante 
qui garantit la qualité des données, la fiabilité des données et la cohérence des 
données, le Consultant devra préciser dans son approche méthodologique, le 
mécanisme qu’il compte mettre en place pour assurer le contrôle qualité ?
• Quel sont les éléments que le Consultant devra prendre en compte pour le suivi 
des performances des enquêteurs sur le terrain ?
5.7. Traitement et constitution de la base de données 
Au cours de cette étape, le Consultant devra procéder à la saisie des données collectées. Afin 
de garantir la fiabilité dans la saisie des données, SAREL opte pour le principe de la double 
saisie manuelle des questionnaires de l’enquête, c’est-à-dire que chaque questionnaire devra 
être saisi deux fois pour permettre la comparaison des saisies afin de corriger immédiatement 
toute erreur de saisie. Pour ce faire, le consultant développera les masques de saisie une fois 
les questionnaires validés. 
Le Consultant devra mettre en place un dispositif de contrôle de saisie des données. Il doit 
au cours de cette phase, procéder à l’apurement et au nettoyage de ces données. 
Il est à noter que toutes les informations issues de l’enquête et les données collectées seront 
la propriété exclusive de SAREL, et le consultant devra à cet effet transférer tous les 
documents à la fin de l’enquête à SAREL. Il est à noter que les questionnaires papiers remplis 
seront également livrés à SAREL pour archivage.
Note : Pour la durée de l’opération de la saisie, SAREL prêtera au Consultant 10 ordinateurs 
desktops avec claviers, souris, et UPS, en bon état. 
• Comment le Consultant compte mettre en place l’équipe de saisie ?
• Comment le Consultant compte-t-il centraliser les données collectées des deux pays ? 
• Comment le Consultant compte-t-il assurer la supervision de la saisie de données ;
• Quel mécanisme compte-t-il mettre en place pour assurer le contrôle de qualité de la 
saisie des données ?
• Comment le Consultant compte-t-il pour assurer le nettoyage et l’apurement des 
données ?
• Par ailleurs, compte tenu du fait que SAREL a opté pour le principe de la double saisie, 
le Consultant devra décrire dans sa méthodologie comment il compte traiter les 
données de l’enquête conformément à ce souhait de SAREL.
Durée de la consultation 
La durée envisagée de la présente consultation est estimée à sept (07) mois à compter de sa 
date de notification de l’ordre de service. La collecte des données sur le terrain doit 
impérativement démarrer au plus tard en mars 2017 pour s’achever au plus tard en avril 2017. 
La double saisie des questionnaires et le nettoyage et l’apurement devra être achevé au plus 
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tard le 10 juin 2017.
Le consultant proposera un chronogramme de travail détaillé pour la réalisation de l’enquête 
conformément aux exigences de l'étude.
Ressources humaines clés
Pour la réalisation de l’enquête, les soumissionnaires proposeront une équipe d’experts clés 
répondant au minimum aux exigences que requiert la mise en œuvre de l’enquête dans la 
zone RISE à cheval les deux pays. Les soumissionnaires proposeront une équipe technique 
compétente capable de conduire cette enquête. Le personnel technique clé doit pouvoir 
coordonner, superviser, et traiter les données de l’enquête. 
Pour les Experts clés proposés dans le cadre de cette mission, les soumissionnaires devront 
joindre leurs CVs détaillés avec la description de leurs qualifications et expériences.
Tout membre de l’équipe désigné comme « expert-clé » doit garantir son engagement pour 
toute la durée requise par ce contrat et ne pourra être remplacé sans l’accord préalable de 
SAREL.
CONTROLE DE QUALITE 
Afin de s’assurer de la qualité de cette enquête, SAREL s’attachera les services d’un consultant 
indépendant pour réaliser ce contrôle qui se fera tout au long de l’enquête. Le Consultant en 
charge de la réalisation de l’enquête devra tout mettre en œuvre pour assurer une bonne 
collaboration avec ce dernier.
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Appendix E2. Scope of Work Data Analysis
Scope of work for the SAREL RISE MIDLINE DATA ANALYSIS – Coordinator
CONTEXT and JUSTIFICATION of the service to be provided
The Mitchell Group, Inc. was contracted by USAID in March 2014 to implement the Sahel 
Resilience Learning (SAREL) project. SAREL is one of four new and ongoing projects funded 
by USAID that contribute to strengthening the resilience of households and villages in 
chronically vulnerable zones of Niger and Burkina Faso. Convinced that the impact of 
humanitarian and development investments in the Sahel have been considerably reduced by 
weak collaboration among stakeholders and the absence of rigorous approaches and systems 
for assessing and learning from interventions, USAID designed SAREL to boost adaptive, 
evidence-based, collaborative learning among resilience stakeholders. If this approach is 
successful, it will speed the development and adoption of resilience-enhancing best practices, 
innovations and models, and enable USAID and other stakeholders to better leverage and 
integrate scarce humanitarian and development resources. 
The overall objective of SAREL is to provide monitoring, evaluation, collaboration and learning 
support to USAID’s resilience programming in the Sahel. The project has five specific 
objectives:
1. Test, expand and accelerate the adoption of proven resilience-enhancing technologies 
and innovations already underway;
2. Develop, test and catalyze widespread adoption of new models that integrate 
humanitarian and development assistance;
3. Promote ownership, build the capacity of national and regional institutions, and 
coordinate humanitarian and development interventions in the zone of intervention;
4. Address gender issues key to resilience and growth; and
5. Create a knowledge management database that will house a baseline assessment, 
ongoing monitoring data, and impact evaluations for REGIS-ER and REGIS-AG.
OBJECTIVES
In 2015, the SAREL team and its local partners completed a baseline quantitative survey of 
approximately 2500 households across 100 villages in the RISE zone (see figure below). A 
portion of those villages constitute a High-intensity stratum, wherein a combination of RISE￾related programs were implemented; the remaining villages were designated as a Low￾intensity stratum of comparable localities but without the RISE interventions. Currently 
underway in 2017 is a midline quantitative survey of approximately the same size, conducted 
in the same villages (though it is not a household panel design; household selection was 
randomized during each phase). The data collection instruments include a household 
questionnaire, a village questionnaire, a women’s questionnaire, and a food and child 
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anthropometry questionnaire.
The midline quantitative survey has two components. The first concerns the data collection 
process which will be conducted by SAREL’s partner CESAO.
RISE Intervention Zone Map (in blue)
The second component is comprised of data analysis and a report. According to SAREL’s 
evaluation methodology developed in 2015 for evaluating the impact of RISE Initiative, data 
analysis will rely on data gathered during the midline as well as data collected during the 
baseline. SAREL solicits the assistance of a qualified Data Coordinator to develop an 
appropriate, comprehensive methodological approach to the data analysis, and to oversee and 
conduct rigorous statistical analyses of the midline data, of changes over time from baseline 
to midline, and of differences across the High and Low strata. The Coordinator must have 
necessary experience, demonstrated capacity in analysis, and skill leading consultant teams. 
With this mission in mind, the Coordinator will:
• Assist in the recruitment of a statistical analysis expert
• Collaborate with SAREL staff in the development of testable hypotheses
• Make recommendations to SAREL concerning data analysis and statistical package to 
be used
• Work as a team with the data analyst on data analysis for both surveys
• Oversee tests of significance and hypotheses tests outlined by SAREL
• Ensure application of appropriate weighting and analysis techniques
RAMSAR 
tl d
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• Collaborate with the analyst on the development of appropriate tables and figures
• Write summary briefs, a draft report, and a final report
• Store the survey data analyses and do-files 
DELIVERABLES AND RESPONSIBILITIES
The Coordinator will be familiar with conducting data analyses using STATA, SPSS, R, or a 
comparable statistical software package, in order to supervise and assist the data analyst. In 
particular, the coordinator must take into consideration any data weighting issues and must 
ensure appropriate design-based calculations of precision (e.g., standard errors, confidence 
intervals) and p-value. 
The deliverables expected from the Coordinator are as follows:
2.1. Refining and finalizing the methodology and work plan:
During the first week of mobilization, the Coordinator will refine and finalize a technical 
proposal and work plan with support and input from the Data Analyst. The proposal and work 
plan will be adapted to take into account the comments made during a preliminary meeting
which will be held immediately after notification by SAREL of the award of the contract to the 
Coordinator.
The technical proposal of the Coordinator must be accompanied by a timetable of work 
describing the chronology of the different tasks associated with the analysis, the use of 
material resources, the submission and validation of deliverables, etc.
The results and expected deliverables are:
Results Deliverables
The final methodology for 
analyses is developed.
Deliverable 1: a revised, final proposal detailing the
methodological approach to the analyses:
• The methodological approach to each principal set of 
analyses
• The data analysis plan 
• The use of human and material resources
• The timeline of detailed work plans
2.2. Weighting of the SAREL midline sample
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In order to reflect the selection scheme and ensure that the sample represents the target
population, the sample weights will be computed for use in the statistical analysis. The 
Coordinator is not responsible for ensuring all design variables necessary to the weighting 
calculation will be available on the final data collected file. Instead the data collection team will 
be responsible to provide the sufficient information for sample weighting.
The Coordinator will be mainly responsible for the weights calculations with appropriate 
support from the Data Analyst. 
Results Deliverables
Final sample weights 
added to the data.
Deliverable 2: set of sample weights necessary for the 
analysis:
• A technical document providing the methodology 
used to calculate the weights including a detailed 
description of the formulas used
• The dataset including the added variables related to 
the weighting
2.3. Summary Analyses of key indicators and demographic information
The RISE initiative includes a set of 21 key indicators used to track progress toward resilience 
among households and villages in the intervention zone. In addition, data has been collected 
on numerous demographic and livelihood factors that help to describe the context in 
systematic terms. This includes measures of family size and structure, family dwelling 
conditions, exposure to shocks, and community services. All estimates should be derived 
following the stratified two-stage sample design used to collect the data. 
It is important to note that the RISE baseline and midline surveys are probability-based sample 
surveys, so to analyze the data, the Coordinator and data analyst must take into consideration
the survey design. During this step, the Coordinator will advise on the statistical software 
scripts for producing survey-based estimates and he will verify the summary statistics 
calculated by the Data Analyst for all the key indicators and the estimates of precision 
(standard errors, significance levels "p-values", and confidence intervals). The Coordinator will 
also verify and assist with the calculation of statistics for the demographic and social factors 
described in the baseline report.
• Specify the design (the design structure, as well as the weights) to a suitable statistical 
software program procedure, such as the various Stata svy procedures (e.g., svy: mean)
• Review the indicators and demographic factors addressed in the baseline report
• Apply the data analysis plan developed for the analysis of baseline data to calculate all 
the 21 key indicators for the midline data (request from SAREL)
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• Verify overall means, standard deviations, and confidence intervals
• Verify disaggregated statistics by strata and country
• Oversee significance tests for the key indicators to analyze comparison between strata, 
country and sex
• Write the summary of findings
Results Deliverables
Midline summary 
statistics and a write￾up are provided.
Deliverable 3: A summary write-up that accompanies a table and 
figures that present summary statistics for the key indicators and 
additional demographic and social factors from the midline data
• Means, SD, and CI for key indicators
• Disaggregated indicator data by stratum, country
• Means, SD, and CI for demographic factors
• Disaggregated demographic data by stratum, country
• Test of significance for selected indicators
• Do-files for calculations
• A 2-3 page summary of findings, with note of any notable 
coding choices
2.4. Difference-in-Differences over time across strata
SAREL is interested in determining the extent to which the RISE interventions have impacted 
the villages and households where those interventions have been implemented. Doing so 
requires a difference-in-difference analysis with two components: the change over time in the 
High-intensity villages, and a comparison of that change to the change over time in the Low￾intensity villages. This strategy accounts for any differences in the High and Low strata at the 
baseline, and for the fact that secular changes (having nothing to do with the RISE 
interventions) may have taken place over time across the entire RISE zone, thus potentially 
affecting both the High and Low strata:
D-i-D: (Hight1 – Lowt1) – (Hight0 – Lowt0)
The difference-in-difference analyses should focus on village-level data (from the village 
surveys) and from village means (calculated from the individual-level surveys). Analyses should 
include the 21 key indicators plus additional demographic and social factors that SAREL 
requests. The Data Analyst will generate the tables and figures that present the difference-in￾differences analyses. The Coordinator will provide methodological oversight and prepare the 
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written (narrative) write-up that accompany the tables and figures. The results and expected 
deliverables are:
Results Deliverables
Difference-in￾difference analyses 
are conducted across 
strata to evaluate the 
effects over time and 
across strata since 
the baseline. 
Deliverable 4: A summary write-up that accompanies a tables 
and figures presenting difference-in-differences across the High 
and Low strata
• D-i-D for key indicators
• D-i-D for additional demographic factors
• Do-files for calculations
• A brief write-up: a few-sentence description of each 
finding, plus any notable coding choices
2.5. Propensity Score Matching analyses
The design of the RISE interventions is quasi-experimental: similar villages were assigned to 
the High- and Low-intensity strata so that differences might reasonably be attributed to the 
interventions themselves, and not to pre-existing differences in the villages. Regarding the 
individual-level data, the assumption is that participants in the High and Low strata are also 
relatively similar, but because they were not assigned to those villages at random (instead 
having already lived there and thus been assigned to the High or Low strata in clusters), it is 
important to match household participants as rigorously as possible across the High and Low 
strata in conducting the analyses of household and individual-level data. Doing so holds as 
much constant as possible while varying the exposure to RISE programs, in order to most 
precisely determine their effects.
The Coordinator will collaborate with the Data Analyst in identifying appropriate matching 
techniques and assist him in conducting nearest-neighbor propensity score matching analyses 
that match on a standard set of demographic and geographical factors (e.g., gender, age, 
education, household size, standard of living) to determine the effects of exposure to RISE 
programs (High stratum) on the key RISE indicators. The Coordinator will prepare a summary 
write-up of the matching results.
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Results Deliverables
Propensity score 
matching analyses 
for individual-level 
data are conducted 
to test the effects of 
strata on individual￾level outcomes.
Deliverable 5: A summary write-up that accompanies tables and 
figures presenting the results of nearest- neighbor propensity score 
matching to test the effects of stratum on key RISE indicators
• Propensity score matching analyses of key indicators from 
the household survey data
• Propensity score matching analyses from the gender survey 
data
• Propensity score matching analyses from the food & 
anthropometry survey data
• Do-files for calculations
• A brief write-up: a few-sentence description of each finding, 
plus any notable coding choices
2.6. Standard multivariate analyses with controls
As a complement to propensity score matching analyses, SAREL also requires analyses of the 
household- and individual-level indicators using standard regression analysis (e.g. OLS, Logit, 
etc.) with controls. Multivariate regression, i.e. regression model with more than dependent 
variable, will be considered if appropriate a. This will allow for a comparison of matched and 
conventional regression results. Exposure to the High or Low stratum again constitutes the 
key explanatory variable of interest.
The Coordinator will provide methodological oversight to the Data Analyst in generating the 
tables and figures that present the results of standard multivariate analyses of key indicators. 
The Coordinator will prepare the written (narrative) write-up that accompany the tables and 
figures. The results and expected deliverables are the following:
Result Deliverables
Standard regression 
analyses are run to 
test the effects of 
strata on key 
outcomes.
Deliverable 6: A summary write-up that accompanies tables and 
figures presenting the results of standard multivariate analyses of 
key indicators
• Regression analysis from the household survey data
• Regression analysis from the gender/women’s survey data
• Regression analysis from the food & anthropometry survey 
data
• Regression analysis from the village survey data
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• Do-files for calculations
• A brief write-up: a few-sentence description of each finding, 
plus any notable coding choices
2.7. Additional hypothesis testing
In addition to evaluating the effects of stratum assignment on the key RISE indicators, SAREL 
is interested in exploring a number of complementary hypotheses. The Coordinator will 
oversee additional difference-in-differences, matching, or standard multivariate analyses to 
test the hypotheses that SAREL proposes. These tests may implicate independent and 
dependent variables drawn from survey questions not otherwise used in the analyses of 
indicators. SAREL will provide the hypotheses for testing after contract approval and may 
update the request as appropriate during the course of the contract. 
The results and expected deliverables are the following:
Results Deliverables
Hypothesis testing is 
conducted based on 
complementary 
hypotheses provided 
by SAREL.
Deliverable 7: A summary write-up of tables displaying the 
results of hypothesis tests requested by SAREL.
• Multivariate analyses using an appropriate approach given 
the subset of data and the hypotheses
• Do-files for calculations
• A brief write-up: one short paragraph per hypothesis, plus 
notable coding choices
2.9. Do-files and data sets
As a point of emphasis, SAREL will need to receive the do-files (which indicate the commands 
for regression analysis) for all final analyses. As a reminder, the Coordinate should ensure that 
appropriate weighting techniques are used and should apply appropriate precision estimators.
Furthermore, if the Coordinator reorganizes the data set in any way to facilitate data analysis 
(e.g., merging modules, disaggregating by stratum or country, creating a separate data set for 
children, etc.), he must provide SAREL with copies of those reorganized data sets. 
The results and expected deliverables are the following:
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Results Deliverables
Do-files and data 
sets are provided 
to SAREL.
Deliverable 8: Do-files for all final analyses and any reorganized 
data sets
• Do-files can be provided with each analysis separately
• Any merged, disaggregated, or reorganized data sets
• A brief description of any decisions related to the 
reorganization of data sets to facilitate analysis
2.8. Final reporting
The Coordinator will draft a report that summarizes key findings from each deliverable 
section. The Coordinator will hold a workshop to share the survey results and to allow for 
discussion of the findings. In addition, at the end of this survey, the Coordinator is required 
to give SAREL a technical report on the overall execution of the data analysis.
The workshop will bring together members of the SAREL team and its evaluation partner 
CESAO and USAID at Niamey (Niger) or Ouagadougou (Burkina Faso). The workshop timing 
as well as the list of participants will be established by SAREL.
The final report should be a complement to the tables and summaries provided for each 
deliverable; its goal is to highlight key findings, underscore notable trends, and describe data
analysis challenges. It is not necessary to repeat all findings, though SAREL should be able to 
easily combine the tables and analyses with the report. The report will be transmitted, 
in French and in English, in three hard copies and in electronic format. This report will be 
accompanied by any necessary annexes.
The results and expected deliverables are the following:
Results Deliverables
The midline
analysis report is 
produced, 
approved and 
finalized.
Deliverable 9: Analysis report and workshop
• Draft analysis report
• Workshop report
• Final analysis report
• Analyses archived
Duration of the Activity and Level of Effort
The proposed duration of the analyses is estimated at seven (14) weeks from the date of 
notification to the Coordinator. The Level of Effort is estimated at 50 days.
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October 2017 (Approved, Feb. 2018) 361
The Coordinator will propose a detailed schedule of work for the completion of the data 
analysis, adhering to the expected responsibilities and deliverables. A guideline for work 
activities is as follows:
Activity Period
In-depth review of RISE baseline survey and data analysis 
methodology and report, of RISE midline survey reports, and 
other key background documents
Week 0 (3 days)
Inception in-country visit 5 days (period to be determined)
Review of the sample design and weighting of the SAREL 
sample
Week 1 (5 days - assuming all necessary 
information is available on the files)
Development of Methodological Approach Week 2 (4 days)
Summary Statistics and Diff-in-Diff analysis Week 3 and 4 (5 days)
Propensity Score and Multivariate analysis Week 5 and 6 (5 days)
Additional Hypothesis Testing Week 7 and 8 (5 days)
Draft Report in one language (English or French) Week 9 and 10 (5 days)
Review by the SAREL team Week 11 and 12 (0 days)
Finalize Report and Translation to the second language Week 13 (8 days)
Prepare and Deliver Workshop (in-country visit) Week 14 (5 days)
PROFILE OF COORDINATOR
In order to conduct the analyses and prepare the required reports, the Coordinator must 
respond, at a minimum, to the criteria and to the experience described below. The 
Coordinator will also assist in identifying and vetting the Data Analyst. Both "key-expert" 
members of the team (Coordinator and Data Analyst) must ensure his or her commitment 
for the entire time required by this Service Agreement.
4.1. Expected Experience
The Coordinator will be the main technical manager ensuring the professional implementation 
of this RISE data analysis work. He/she will oversee the management of the Data Analyst and 
the technical communication with SAREL, and will participate, as needed, in periodic meetings 
or phone conferences with USAID to provide progress updates. He/she will be guarantor of 
the quality of the work and of good management and the coordination of the overall team. 
He/she will be responsible for the quality control of the entire process and of expected 
deliverables of the analysis.
The Coordinator must:
• Hold an advanced university degree (Masters or higher) in statistics, economics, sociology, 
Sahel Resilience Learning (SAREL)—RISE Midline Quantitative Survey Report
October 2017 (Approved, Feb. 2018) 362
agronomy, demography or other equivalent degrees in relevant areas
• Have strong experience - at least ten (10) years in organization of quantitative research 
of a large scale (covering at least 1500 rural households and of focus groups), particularly 
in Burkina Faso, Niger and/or in the sub-region
• Have a proven ability in processing databases, analyzing survey data, writing reports and 
disseminating findings in a timely manner
• Have skills in systems establishment of control and verification of the quality of survey 
procedures
• Have strong experience in the organization of impact evaluations of rural development 
programs and projects;
• Maintain close relations with the Quality Control Consultant in charge of quality control 
that will be recruited by SAREL 
• Have experience with or familiarity with USAID programming
• Possess knowledge of the socio-political environment, cultural and economic in Burkina 
Faso and Niger
U.S. Agency for International Development
Almadies Road
PO Box 49
Dakar, Senegal