IMPEL | Implementer-Led Evaluation and Learning
Baseline Study of the Resilience Food 
Security Activities (RFSAs) in Niger: 
Final Report
July 2021 | Volume I
IMPEL | Implementer-Led Evaluation & Learning Associate Award
ABOUT IMPEL
The Implementer-Led Evaluation & Learning (IMPEL) Associate Award works to improve the design and implementation of 
Bureau for Humanitarian Assistance (BHA)-funded resilience food security activities (RFSAs) through implementer-led 
evaluations and knowledge sharing. Funded by the United States Agency for International Development (USAID) BHA, IMPEL 
will gather information and knowledge in order to measure performance of RFSAs, strengthen accountability, and improve 
guidance and policy. This information will help the food security community of practice and USAID to design projects and 
modify existing projects in ways that bolster performance, efficiency, and effectiveness. IMPEL is a seven-year activity (2019-
2026) implemented by Save the Children (lead), TANGO International, Tulane University, Causal Design, and Innovations for 
Poverty Action. 
Cooperative Agreement Number: 72DFFP19LA00003
RECOMMENDED CITATION
IMPEL. (2021). Baseline Study of the Resilience Food Security Activities (RFSAs) in Niger: Final Report (Vol. I). Washington, DC: 
The Implementer-Led Evaluation & Learning Associate Award. 
STUDY TEAM 
Tim Frankenberger Management Oversight
Jeanne Downen Chief of Party
Mark Langworthy, PhD Management Oversight/Survey Methods Specialist
Gheda Temsah, PhD Baseline Study Lead
Monica Mueller Senior Qualitative Specialist/Quality Assurance
Victoria Brown, PhD Senior Research Methodologist/CAPI Specialist
PHOTO CREDIT 
Gheda Temsah / TANGO International 2019
DISCLAIMER
This report is made possible by the generous support of the American people through the United States Agency for 
International Development (USAID). The contents are the responsibility of the Implementer-Led Evaluation & Learning (IMPEL) 
award and do not necessarily reflect the views of USAID or the United States Government. 
CONTACT INFORMATION
IMPEL Activity 
c/o Save the Children 
899 North Capitol Street NE, Suite #900 
Washington, DC 20002 
www.fsnnetwork.org
IMPEL@savechildren.org
SUBMITTED BY:
PREPARED BY: 
Baseline Study of the RFSAs in Niger: Final Report (Vol. I)
Acknowledgements i
ACKNOWLEDGEMENTS
We would like to thank several individuals for the support they provided to the baseline study of the 
RFSAs in Niger, starting with USAID BHA: Mara Mordini, Benita O’Colmain, Mariko Dramane, and Oumar 
Moussa S. Diallo. We wish to acknowledge Ibrahima Issa Bagna, Zakou Issaka Moussa and other staff at 
Bagna Solutions for their work in organizing the training and logistics for the survey and conducting the 
data collection. In addition, we would like to thank the independent survey monitors, Ali Ousmane, 
Askia Makhamed, Oumaro Zakari, and Nakoari Abdoulaye. We are grateful for the support of the Girma, 
Hamzari, and Wadata RFSA technical and Monitoring and Evaluation staff for contributing to the 
development of training materials, providing technical presentations to the field teams in advance of 
fieldwork, and reviewing the report. Lastly, we wish to thank all of the gracious people in the RFSA areas 
who took the time to be interviewed for this survey.
Sincerely,
Tim Frankenberger, President
TANGO International
IMPEL | Implementer-Led Evaluation and Learning
ii Table of Contents
TABLE OF CONTENTS
Acknowledgements .............................................................................................i
List of Tables and Figures....................................................................................v
Acronyms..........................................................................................................vii
Executive Summary ......................................................................................... viii
1. Introduction....................................................................................................1
1.1 Overview of the Baseline Study ....................................................................................................1
1.2 Background on RFSAs....................................................................................................................1
1.3 Country context ..............................................................................................................................3
1.3.1 Background ........................................................................................................................3
1.3.2 Overview of the Current Food Security Situation..............................................................3
2. Methodology and Limitations .........................................................................6
2.1 Study Design..................................................................................................................................6
2.2 Sample Design...............................................................................................................................6
2.3 Questionnaire Design....................................................................................................................8
2.4 Field Procedures..........................................................................................................................11
2.4.1 Timing of the Survey .......................................................................................................11
2.4.2 Listing Exercise ................................................................................................................12
2.4.3 Training............................................................................................................................12
2.4.4 Pilot .................................................................................................................................13
2.4.5 Fieldwork.........................................................................................................................13
2.5 Data Analysis...............................................................................................................................14
2.5.1 Sampling Weights ............................................................................................................14
2.5.2 Indicator Definitions and Tabulations..............................................................................16
2.6 Study Limitations and Issues Encountered .................................................................................16
2.6.1 Study Limitations.............................................................................................................16
2.6.2 Issues Encountered During Fieldwork.............................................................................18
2.7 Qualitative Data ..........................................................................................................................19
3. Findings.........................................................................................................20
3.1 Characteristics of the Study Population......................................................................................20
3.2 Activity Participation...................................................................................................................24
3.3 Household Food Security ............................................................................................................25
Baseline Study of the RFSAs in Niger: Final Report (Vol. I)
Table of Contents iii
3.3.1 Relationship Between Crops Harvested and Food Consumption Score..........................27
3.3.2 Practices Associated with Household Food Security .......................................................28
3.4 Agriculture ..................................................................................................................................31
3.4.1 Type of Land Access and Farmland Size..........................................................................31
3.4.2 Use of Financial Services.................................................................................................35
3.4.3 Use of Improved Post-Harvest Handling and Storage Practices.....................................39
3.4.4 Use of Improved Crop Practices......................................................................................40
3.4.5 Use of Improved Livestock Practices...............................................................................51
3.4.6 Factors Affecting Adoption of Improved Practices.........................................................55
3.5 Water, Sanitation, and Hygiene..................................................................................................60
3.5.1 Drinking Water Source ....................................................................................................60
3.5.2 Sanitation Facility ............................................................................................................62
3.5.3 Handwashing Station ......................................................................................................64
3.5.4 Knowledge of Critical Moments for Handwashing .........................................................64
3.6 Women’s Health and Nutrition...................................................................................................66
3.6.1 Women’s Minimum Dietary Diversity.............................................................................66
3.6.2 Antenatal Care.................................................................................................................70
3.6.3 Contraceptive Methods: Knowledge, Use and Decision-Making....................................70
3.7 Children’s Health and Nutrition..................................................................................................72
3.7.1 Children’s Minimum Dietary Diversity ............................................................................72
3.7.2 Diarrhea and Oral Rehydration Therapy .........................................................................76
3.8 Gender ........................................................................................................................................77
3.8.1 Gender and Cash-Earning Activities................................................................................77
3.8.2 Gender and Group Participation.....................................................................................78
3.8.3 Gender Differences in Access to and Decisions About Credit.........................................79
3.9 Resilience ....................................................................................................................................81
3.9.1 Perceptions of Local Government Capacity to Respond Effectively to Future Shocks and 
Stressors....................................................................................................................................81
3.9.2 Social Capital ...................................................................................................................81
3.9.3 Household Participation in Group-Based Savings, Microfinance, or Lending Programs 83
4. Conclusions and Recommendations..............................................................84
IMPEL | Implementer-Led Evaluation and Learning
iv Table of Contents
Volume II Annexes
Annex 1: FFP Burkina Faso and Niger Baseline Protocol
Annex 1a: Revisions to Sampling
Annex 1b: Training Schedule
Annex 1c: Informed Consent Statement
Annex 2: Questionnaire
Volume III Annexes
Annex 3: 2020 Niger Baseline Study Personnel
Annex 4: Summary of Data Treatment and Analysis
Annex 5: Tabular Summary of Indicators
Annex 6: Descriptive Tables
Annex 7: Bivariate and Multivariate Tables
Annex 8: COVID-19 Awareness, Impacts, and Coping Strategies
Baseline Study of the RFSAs in Niger: Final Report (Vol. I)
List of Tables and Figures v
LIST OF TABLES AND FIGURES
Table 1: Geographic coverage of RFSAs, Niger.............................................................................................2
Table 2: Sampled households, by RFSA area ................................................................................................8
Table 3: Indicators measured in the 2020 baseline survey of the RFSAs in Niger........................................9
Table 4: Response rates by sampling group and RFSA area, Niger 2020 RFSA baseline survey.................15
Table 5: Household characteristics, total and by RFSA area.......................................................................23
Table 6: Sex and age distribution of farmers, by RFSA area (%).................................................................31
Table 7: Heat map of adoption of targeted improved crop practices and technologies, by RFSA area and 
crop .............................................................................................................................................................40
Table 8: Distribution of sorghum farmers by sex and age in the RFSA areas, Niger (%) ............................43
Table 9: Distribution of millet farmers by sex and age in the RFSA areas, Niger (%) .................................45
Table 10: Distribution of cowpea farmers by sex and age in the RFSA areas, Niger (%)............................47
Table 11: Distribution of peanut farmers by sex and age in the RFSA areas, Niger (%).............................49
Table 12: Sex and age distribution of goat, sheep, and poultry farmers by RFSA area, Niger (%).......................51
Table 13: Heat map of adoption of targeted improved livestock practices and technologies – goats and 
sheep, by RFSA area....................................................................................................................................52
Table 14: Heat map illustrating adoption of targeted improved livestock practices and technologies –
poultry, by RFSA area..................................................................................................................................52
Table 15: Targeted improved crop and post-harvest practices more likely to be applied by farmers using 
a financial service than farmers who are not, by RFSA area and commodity ............................................56
Table 16: Targeted improved livestock practices more likely to be applied by farmers using a financial 
service than farmers who are not, by RFSA and commodity......................................................................57
Figure 1: Seasonal calendar for a typical year, Niger....................................................................................5
Figure 2: Share of key demographic groups from the overall population, combined RFSA areas.............22
Figure 3: Household receipt of social assistance among direct and indirect participants, by RFSA area ..24
Figure 4: Mean Food Consumption Score and distribution of households by FCS group and RFSA area..26
Figure 5: Frequency of consumption of food groups, by RFSA area...........................................................27
Figure 6: Percent of harvest completed, by RFSA area...............................................................................28
Figure 7: Summary of statistically significant findings from the bivariate analyses of household food 
consumption score......................................................................................................................................30
Figure 8: Type of land access by farmer’s sex, combined RFSA areas........................................................33
Figure 9: Type of land access by farmer’s age, combined RFSA areas .......................................................33
Figure 10: Area of total farmland cultivated (hectares), by sex of farmer; combined RFSA areas............34
Figure 11: Use of any financial services, by sex of farmer and RFSA area..................................................37
Figure 12: Use of agricultural credit and savings schemes, by sex of farmer and RFSA area.....................39
Figure 13: Sorghum farmers adopting targeted improved crop practices, by RFSA area (%)....................44
Figure 14: Millet farmers adopting targeted improved crop practices, by RFSA area (%).........................46
Figure 15: Cowpea farmers adopting targeted improved crop practices, by RFSA area (%)......................48
Figure 16: Peanut farmers adopting targeted improved crop practices, by RFSA area (%).......................50
IMPEL | Implementer-Led Evaluation and Learning
vi List of Tables and Figures
Figure 17: Farmers adopting targeted improved livestock practices, by livestock type and RFSA area and 
percent........................................................................................................................................................54
Figure 18: Household drinking water source facility, by RFSA area ...........................................................62
Figure 19: Household sanitation facility, by RFSA area ..............................................................................63
Figure 20: Percentage of households with knowledge of the critical moments for handwashing, by RFSA 
area .............................................................................................................................................................65
Figure 21: Food groups consumed by women 15–49 years, combined RFSA areas ..................................68
Figure 22: Statistically significant associations between MDD-W and intervention-specific factors.........69
Figure 23: Knowledge of modern family planning methods among women 15–49 in a union, by RFSA 
area .............................................................................................................................................................71
Figure 24: Contraceptive use among non-pregnant women 15–49 years in a union, by RFSA area .........72
Figure 25: Food groups consumed by children 6–23 months, combined RFSA areas................................75
Figure 26: Gender gap in participation in cash-earning activities, by RFSA area .......................................77
Figure 27: Gender gap in community group participation, by RFSA area ..................................................78
Figure 28: Gender gap in access to and decisions about credit, by RFSA area...........................................80
Figure 29: Social capital and component indices, by RFSA.........................................................................82
Baseline Study of the RFSAs in Niger: Final Report (Vol. I)
Acronyms vii
ACRONYMS
ANC Antenatal care
BHA Bureau for Humanitarian Assistance
DEMI-E Développement pour un Mieux Être
DFAP Development Food Assistance Program
DHS Demographic and Health Survey
ECVM/A Niger National Survey On Household Living Conditions and Agriculture
FAO Food and Agriculture Organization
FCS Food Consumption Score 
FEWS NET Famine Early Warning Systems Network
FFP Food for Peace 
FMNR Farmer-managed natural resource generation
GIEWS Global Information and Early Warning System
IMPEL Implementer-Led Evaluation and Learning Associate Award
IP Implementing partner 
MDD-C Minimum Dietary Diversity – Children
MDD-W Minimum Dietary Diversity – Women 
NRM Natural resource management
OFDA Office of Foreign Disaster Assistance
ORT Oral rehydration therapy
RFSA Resilience Food Security Activity
RISE Resilience in the Sahel-Enhanced
PBS Population-based survey
TANGO Technical Assistance to NGOs
ToT Training of trainers
USAID United States Agency for International Development
VSLA Village Savings and Loan Association
WASH Water, sanitation, and hygiene
WFP World Food Program
IMPEL | Implementer-Led Evaluation and Learning
viii Executive Summary
EXECUTIVE SUMMARY
This report is a baseline study of three Resilience Food Security Activities (RFSAs) funded by the United 
States Agency for International Development (USAID) Bureau for Humanitarian Assistance (legacy Office 
of Food for Peace [FFP] in Niger. Part of the Resilience in the Sahel-Enhanced (RISE) initiative, the RFSAs 
in Niger are: Girma in the Zinder region, implemented by Catholic Relief Services; Hamzari in the Maradi 
region, implemented by CARE; and Wadata in the Zinder region, implemented by Save the Children. The 
RFSAs aim to address critical challenges in food security, nutrition, and poverty, and to improve the 
resilience of households and communities.
The baseline study was conducted by Technical Assistance to Non-governmental Organizations (TANGO) 
International with its local partner, Bagna Solutions, under the Implementer-Led Evaluation and 
Learning (IMPEL) Associate Award. The purpose of the study is to provide baseline population-level 
estimates for a limited number of intermediate but critical outcome indicators as a comparison for the 
interim performance and final evaluations. Given that the study does not include a qualitative 
component, survey results are integrated with qualitative data and information from relevant recent 
studies conducted in Niger—namely, the 2020 USAID RISE I impact evaluation endline and the 2017 
performance evaluation of USAID Title II Development Food Assistance Programs (DFAPs) in Niger. 
Secondary sources were used to gain additional context and understanding of prevailing conditions and 
perceptions in the RFSA areas and to inform conclusions and recommendations, which were further 
refined based on feedback received from implementing partners during a series of data utilization 
workshops.
Study Design
The baseline study included a representative population-based survey (PBS) of 2,325 households (775 
households per RFSA area). Data collection was scheduled for May–April 2020 but due to the COVID-19 
pandemic fieldwork was suspended until local regulations and conditions indicated that face-to-face 
interviewing could safely resume with COVID-19 mitigation procedures in place. The survey was 
conducted in September 2020 and ended at the start of the harvest period in October 2020. The sample 
was selected using a multi-stage clustered sampling design to provide a statistically representative 
sample of the three RFSA areas. The questionnaire was streamlined from the standard FFP
questionnaire for a non-permissive environment. Estimates of impact-level indicators pertaining to 
poverty and anthropometry were expected to be derived from the RISE II baseline survey, scheduled to 
take place a few months after the RFSA baseline survey. 
Study Limitations
Timing of the survey: Data collection was originally planned to take place in March–April 2020 but due 
to COVID-19 restrictions was re-scheduled to September, ahead of the main harvest season in October, 
to avoid an upward bias of food security estimates. Despite efforts to avoid spillover into the harvest 
period, data collection ended on October 11. Because of this and because RFSA interventions began 
before the survey could be conducted, the estimates may not necessarily reflect a true “baseline.”
Limitations of combining data sources: The original plan to derive poverty and anthropometry 
indicators not collected by the baseline study from the RISE II baseline survey was complicated by the 
Baseline Study of the RFSAs in Niger: Final Report (Vol. I)
Executive Summary ix
delay of RISE II baseline data collection to August–September 2021. While RISE II baseline timing 
coincides with about the same timeframe as this baseline, the impact-level indicator data will be 
separated from the current baseline data by approximately 12 months. This could result in differences in 
price and market data, which will also likely be affected by the COVID-19 pandemic.
Validity and reliability of self-reported data: Most data collected for the household survey are self￾reported. The reliability of self-reported data is particularly challenging for questions related to 
agricultural yield because farmers may not be able to provide correct estimates. Steps taken to minimize 
the effect of errors include 1) applying conversion factors to render non-standard units suitable for 
analysis; 2) obtaining plausible weight ranges for goats and sheep and using these as a data reliability 
check; and 3) identifying outliers in plot size and livestock weights in the preliminary analysis of yield￾related data. Several post-data collection-processing routines were performed to address outliers, but 
considering the measurement challenges described above, no further analysis of the yield data was 
performed.
Non-response: To account for potential non-response, the study design uses a higher-than-usual non￾response factor of 25%. Field teams were also trained to explain to respondents the study objectives 
and measures to preserve respondents’ anonymity and thus encourage participation.
Key Findings and Conclusions
Key findings are presented for each topic; each set of findings is immediately followed by conclusions 
and recommendations.
Food Security
Food Consumption Score (FCS) and FCS groups: Baseline estimates indicated higher-than-expected food 
consumption in the RFSA areas; most households across the three RFSA areas achieve an acceptable FCS 
(Girma, 75.6%; Hamzari, 76.5%; Wadata, 85.9%). The average FCS exceeds the standard threshold for 
acceptable food consumption (35) in each of the RFSA areas (Girma, 48.3; Hamzari, 51.5; and Wadata, 
56.2). Statistical analyses did not indicate an association between the percentage of harvest completed 
and household FCS; however, it is possible that the timing of the survey, which overlapped with the start 
of the harvest period, may have resulted in inflated results since more than 80% of households had 
harvested at least some of their crops at the time of the survey. Other households may have received 
food items from households that harvested their crops, and/or may have purchased food items from the 
market.
The higher-than-expected levels of food security in the RFSA areas may also be related to the 
methodology of calculating the indicator. FCS is more likely to overstate food security compared to most 
indicators.
1 FCS factors in the frequency of consumption of eight food groups and assigns higher weights 
to more-nutritious, micronutrient-dense foods, but the weights and thresholds assigned to the FCS 
groups may need adjustment: the FCS does not consider quantities consumed, so food groups with a 
high weight (such as pulses and meat) that are consumed frequently but in small quantities will 
 
1 Maxwell, Daniel, Jennifer Coates, and Bapu Vaitla (2013). How Do Different Indicators of Household Food Security Compare? 
Empirical Evidence from Tigray. Feinstein International Center, Tufts University: Medford, USA.
IMPEL | Implementer-Led Evaluation and Learning
x Executive Summary
artificially inflate the FCS value. Further analysis is needed to determine whether an adjustment in 
weights and/or thresholds is relevant for the Nigerien context.
Households across the RFSA areas consume staples almost daily. Pulses are consumed almost 5 days per 
week. Intake of animal-based proteins is infrequent (1–3 days per week across all households in the 
combined RFSA areas). Intake of fruits and vegetables is also rare (0–1 day per week). Agriculture￾related trainings could focus on growing new types of fruits and vegetables. Limited financial resources, 
especially during the lean season, may constrain households’ abilities to incorporate diverse food groups 
on a frequent basis, and households that grow more nutritious foods may opt to sell them. Increasing 
the use of improved post-harvest storage can help households extend food provisioning for a few 
months during the lean period. Qualitative research and/or cost-of-diet studies could help identify 
locally available nutritious wild foods and/or cheaper foods to promote for household consumption.
There is some evidence that household food consumption increases with access to financial services, 
certain livestock holdings, the application of soil-related fertility practices, and the adoption of improved 
post-harvest handling and storage practices. This underlines the importance of layering interventions 
that aim to improve food access and incomes through nutrition-sensitive agriculture programming.
Agriculture
The baseline survey collected information on size of farmland, use of financial services, and adoption of
targeted improved crop, livestock, and post-harvest handling and storage practices for each commodity 
of interest (sorghum, millet, cowpeas, and peanuts) as well as on improved livestock practices for raising 
goats, sheep, and poultry. Enumerators interviewed all farmers with access to a plot of land over which 
they make decisions and all farmers with access to livestock over which they make decisions. 
Use of financial services: Use of agriculture-related financial services is low in the RFSA areas (Girma, 
36.6%; Hamzari, 23%; Wadata, 25.8%). Farmers are more likely to take loans than participate in saving 
schemes, and male farmers are more likely to take out an agricultural loan compared to female farmers.
Agriculture-related meetings and trainings could focus on improving financial literacy and build on 
traditional community-based borrowing mechanisms to increase the use of financial services. There is a 
need to understand barriers on the demand side such as lack of financial literacy, lack of collateral, high 
interest rates, and household indebtedness, but also supply-side factors such as the willingness of 
formal lenders to facilitate access to agricultural credit to smallholder farmers.
Application of targeted improved management practices: The practices most commonly adopted by 
farmers across all four crops of interest are the application of organic manure, crop association, sowing
after first useful rains, and delimiting animal corridors and pasture areas. Adoption rates for these 
practices range between moderate (about 20% to 49%) to widespread (about 50% or more). Less than 
10% of farmers in the RFSA areas use improved seed varieties, pest and disease management practices, 
non-irrigation-based agricultural water practices, or climate adaptation and risk mitigation practices. 
Findings from the RISE I program suggest that farmers are more likely to adopt practices with 
demonstrable results and those that are passed down across generations, and less likely to adopt 
practices they perceive as risky or that require cash inputs. Encouraging experimentation and focusing 
on field demonstrations to raise the visibility of the efficacy of approaches could be useful, with benefits 
extending to the wider population. Knowledge of whether farmers are applying practices correctly 
Baseline Study of the RFSAs in Niger: Final Report (Vol. I)
Executive Summary xi
would be useful to determine the quality of implementation and whether the chosen practice suits their 
individual context, since these factors can affect agricultural productivity.
Locally made storage structures such as metal silos are the most-used type of improved post-harvest 
storage practice, followed by sealed/airtight bags. These structures are not equally effective at keeping 
out moisture, insects, pests, and rodents. Future interventions could focus on building capacity to use 
more-effective locally made storage structures. A better understanding of post-harvest loss per crop, 
drivers of loss, and the role of the myriad factors that can reduce loss would be helpful for informing 
future initiatives.
Vaccination of goats and sheep is at moderate levels (20%–49%) across the RFSA areas. Use of 
vaccination among poultry farmers ranged from 3.5% in the Wadata RFSA area to 18.8% in the Girma 
and 30.7% in the Hamzari RFSA areas. There was moderate use of antiparasitic treatment of goats and
sheep (20%–49%). With a few exceptions, less than 10% of goat and sheep farmers used animal 
selection, improved fodder production, licking and multi-nutritional blocks, para-veterinary services, 
veterinary monitoring of food quality and quantity, weight monitoring, and optimum weight market 
prices. About 10% or less of poultry farmers use improved poultry breeds, improved feed, or improved 
shelters. Future initiatives should consider the extent to which livestock farmers are able to access 
existing veterinary services (such as government programs) on a permanent basis and farmers’ ability to 
afford veterinary services and products. Further research should be undertaken to assess the extent of 
these potential barriers.
Relationship between application of targeted improved practices and use of financial services: There is 
some evidence from this baseline study that farmers who accessed agricultural credit are more likely to 
adopt targeted improved agricultural management practices such as using improved seed varieties, 
applying phosphatic manure or micro-doses of fertilizer, treating grains with agro-chemicals, and using 
community facilities or warehouses, sealed/airtight bags or triple bags to store grains. Use of licking 
and/or multi-nutritional blocks and paraveterinary services was higher among goat and sheep farmers 
who took out an agricultural loan compared to those who did not. Poultry farmers who took agricultural 
credit were more likely to use improved breeds and veterinary products compared to poultry farmers 
who did not. These results underline the importance of integrating interventions in financial services 
and agricultural techniques.
Water, Sanitation, and Hygiene (WASH)
Drinking water, sanitation, and hygiene facilities: Access to a basic sanitation facility is low across the 
RFSA areas (Girma, 5%; Hamzari, 13%; Wadata, 4.4%). The overwhelming majority of households have 
no basic sanitation facility and practice open defecation (Girma, 90.3%; Hamzari, 73.4%; Wadata, 
87.7%). Because the survey did not collect information on year-round water access, the official indicator 
for access to a basic water source cannot be calculated. Instead, the percentage of households whose 
water source meets all other criteria (i.e., improved source; 30 minutes or less round trip; production of 
at least 20 liters per person per day; and no interruptions in the last 2 weeks) was calculated. Few 
households have access to a drinking water source that meets all four criteria (Girma, 22.7%; Hamzari, 
30.8%, Wadata, 11.1%). The percentage of households with a handwashing station with soap or ash
varied from 8.9% in the Girma RFSA area to 18.2% and 40.6% in the Wadata and Hamzari RFSA areas, 
respectively.
IMPEL | Implementer-Led Evaluation and Learning
xii Executive Summary
Results from studies of previous programs, such as the 2012–2017 DFAPs and the RISE I program, point 
to several barriers to achieving WASH objectives, such as the costs of materials and labor for building 
improved latrines, cost of purchasing soap or cleaning agents, engineering issues around certain latrine 
types, and cultural preferences. Future interventions could consider supporting approaches that finance 
the construction of WASH facilities through community-based savings and credit vehicles; marketing 
different design models that are accepted by the community; and supporting community-based service￾provider models so that materials are locally available and affordable.
Nearly all households are knowledgeable about the importance of handwashing before eating. 
Households were less likely to report other critical moments for handwashing. Sensitization should focus 
on the latter, namely, before cooking and food preparation, before breastfeeding or feeding children, 
and when engaging in activities posing a risk of fecal contact. Additional research could be helpful to 
better understand which WASH messages households prioritize and why. 
Women’s Health and Nutrition
Dietary diversity, antenatal care (ANC), and family planning: Less than one-half of women of 
reproductive age in the RFSA areas achieve a diet of minimum diversity. Findings from other qualitative 
studies indicate that kitchen demonstrations, in which women from the community show how to 
incorporate diverse, locally available, affordable food and wild foods into daily meals could be useful.
There is some evidence that household access to and use of financial services and the adoption of 
improved agricultural management practices translate into a higher likelihood of women achieving 
minimum dietary diversity. RFSAs should thus continue to integrate activities that promote savings and 
access to credit with interventions that foster the adoption of improved agricultural practices.
More than one-third of the most-recent births that occurred in the 5 years prior to the survey received 
at least four ANC visits by a skilled health professional. Behavior-change communication efforts should 
continue to emphasize the importance of ANC, focusing on frequency and timing of the visits and who is 
qualified to provide those services. Behavior change communication should also target men via husband 
schools and/or husband-wife meetings so that fathers can support women in ANC visits and other 
aspects of pregnancy.
Knowledge of modern contraceptive methods among women in a union is widespread in the RFSA areas,
ranging from 61.2% in the Wadata RFSA area to 71.6% and 74.5% in the Girma and Hamzari RFSA areas, 
respectively. In contrast, very few women use any form of modern or traditional family planning 
(Wadata, 14.1%; Girma, 14.8%; Hamzari, 21.8%). Most women who use modern contraception 
participated in the decision to use modern family planning (Girma, 81%; Hamzari, 77.3%; Wadata, 
68.1%). Further exploration is needed to identify and address barriers to using family planning, including 
cultural or religious beliefs and affordability of consultation services and contraception. Sensitization 
efforts around contraception (e.g., role of family planning and benefits of birth spacing) should target 
both women and men and underscore the significance of family planning for the well-being of women
and the overall family.
Children’s Health and Nutrition
Dietary diversity, diarrhea, and oral rehydration therapy (ORT): Grains, roots and tubers, vitamin-A-rich 
fruits and vegetables, and legumes and nuts are consumed by more than two-thirds of children aged 6–
Baseline Study of the RFSAs in Niger: Final Report (Vol. I)
Executive Summary xiii
23 months across the RFSA areas, but the prevalence of children aged 6–23 months achieving a diet of 
minimum diversity (MDD-C) is moderate and varied (Girma, 37.8%; Hamzari, 54.6%; Wadata, 46.3%). 
RFSAs should continue to raise awareness among primary caregivers on the health benefits of 
complementary feeding and the appropriate time to introduce complementary foods without cutting 
back on breastfeeding. Sensitization around complementary feeding could be rolled into ANC and 
perinatal care visits and through mothers’ groups with demonstrations on how to integrate diverse 
foods into children’s meals. 
About one-third of children under 5 years experienced diarrhea in the 2 weeks preceding the survey. 
Among children who experienced diarrhea, close to one-half received ORT. Bivariate analyses of the 
prevalence of diarrhea among children under 5 years indicated no difference in diarrhea prevalence by 
household WASH status except for lower prevalence with the use of basic sanitation facilities in the 
Girma and Wadata RFSA areas. While access to WASH facilities is generally correlated with use, access 
does not guarantee households are using those facilities. Although previous qualitative studies in the 
country have underscored growing awareness of the importance of WASH practices, there is a need to 
continue sensitization on the linkages between diarrhea and basic hygiene. Additional sensitization 
focused on how to prepare homemade alternatives to oral rehydration salts would be helpful given 
challenges in accessing health centers and the cost of those services. 
Gender, group participation and access to credit: In each of the RFSA areas, the percentage of women 
in a union participating in paid work is less than one-half that of men in a union participating in paid 
work. Close to two-thirds of men in a union in the Hamzari (66.6%) and Girma (65.5%) RFSA areas are 
paid in cash or a combination of cash and in-kind, compared to one-third of women in a union (Hamzari, 
37.5%; Girma, 35.6%). In the Wadata RFSA area, participation in cash-earning activities among 
individuals in a union is lower for men and women (47.6% and 21.4%, respectively), suggesting few cash￾earning opportunities. 
Between one- and two-thirds of women and men belong to community groups, and group membership 
is generally lower among women than among men. The most common groups for women are credit or 
microfinance groups, savings groups, mutual help or insurance groups, and mothers’ groups. The most 
common groups for men are producers’ groups, trade and business associations, water users’ groups, 
communal grazing land groups, religious groups, youth groups, and conflict resolution groups. A better 
understanding of the barriers to group membership is needed. Women’s time constraints may limit their 
ability to participate in community groups; sensitization of women and men on homemaking and 
childrearing as collaborative processes could free up women’s time to participate in community groups 
and cash-earning opportunities. 
Most women and men had some input into the decision to borrow and/or what to do with any loan
taken by the household in the past 12 months. Joint credit decision-making is generally less prevalent 
than deciding alone, especially in the Hamzari RFSA area, where just 11% of men and 19% of women, 
decide jointly. Men are more likely than women to make credit decisions alone. Sensitization of men 
through fathers’ groups or husband school could also enhance the sharing of household decision￾making, including women’s ability to decide whether to borrow and what to do with the loan.
IMPEL | Implementer-Led Evaluation and Learning
xiv Executive Summary
Resilience
More than one-half of households across the RFSAs believe that local government institutions can 
respond effectively to future shocks and stresses (Girma, 63.8%; Hamzari, 60.1%; Wadata, 55.6%). The 
bonding social capital index score is generally higher than the bridging social capital score, suggesting 
that social obligation networks are stronger within the community than outside. Few households in the 
RFSA areas participate in group-based savings, microfinance, or lending programs (Girma, 12.9%; 
Hamzari, 3.4%; Wadata, 2.8%). There is some evidence that household participation in community￾based credit groups is associated with a higher FCS and that participation in community-based savings 
groups is associated with a higher percentage of women achieving a diet of minimum diversity. Further 
investigation is merited to understand better those linkages and how to expand access to financial 
services via community-based groups.
Baseline Study of the RFSAs in Niger: Final Report (Vol. I)
Introduction 1
1. INTRODUCTION
1.1 Overview of the Baseline Study
In fiscal year 2018, the USAID Office of Food for Peace funded three 5-year Resilience Food Security 
Activities in the Maradi and Zinder regions of Niger. In 2020, FFP merged with the Office of Foreign 
Disaster Assistance (OFDA) to form the Bureau for Humanitarian Assistance (BHA) to streamline USAID 
humanitarian responses. BHA provides life-saving humanitarian emergency and non-emergency aid—
including food, water, shelter, sanitation and hygiene, and nutrition services—to the world’s most 
vulnerable and hardest-to-reach populations. The goal of the 2018 RFSA awards is to address critical 
challenges in food security, nutrition, and poverty, and to improve the resilience of households and 
communities.
Technical Assistance to NGOs (TANGO) International was contracted under the IMPEL Associate Award
to conduct a baseline study in the RFSA implementation areas. The baseline study includes a population￾based household survey (PBS) and qualitative information from secondary sources. TANGO contracted a 
local firm, Bagna Solutions, to perform the data collection for the PBS. The primary purpose of the PBS is 
to provide baseline population-level estimates for a limited number of intermediate but critical outcome 
indicators and a limited number of additional indicators proposed by the USAID Mission and 
implementing partners (IPs). These indicators will serve as points of comparison for the interim 
performance evaluation and future endline PBS. The baseline study results will be used to refine 
program targeting and, where possible, inform program design by exploring relationships among 
variables based on the project theory of change.
1.2 Background on RFSAs
Part of the RISE initiative, the RFSAs in Niger are:
• Girma in the Zinder region, implemented by Catholic Relief Services (CRS) in partnership with 
Développement pour un Mieux Être (DEMI-E), Community Development Assistance, Education 
Development Center, International Crops Research Institute for the Semi-Arid Tropics, Institute for 
Reproductive Health at Georgetown University, Tufts University and Viamo;
• Hamzari in the Maradi region, implemented by CARE in partnership with L’Association pour la 
Redynamisation de L’Elevage au Niger, Association Nigérienne pour le Bien-Etre Familial, Karkara, 
DEMI-E and WaterAid; and
• Wadata in the Zinder region, implemented by Save the Children in partnership with the National 
Cooperative Business Association CLUSA, the Kaizen Company and DEMI-E.
Table 1 provides additional details on the geographic coverage of each RFSA.
IMPEL | Implementer-Led Evaluation and Learning
2 Introduction
Table 1: Geographic coverage of RFSAs, Niger
RFSA/IP Region Communes Number of 
villages
Number of 
Households
Number of 
individuals
Girma/
Catholic Relief 
Services
Zinder Bande
Dantchio
Dogo-Dogo
Dungass
Gouchi
Kawaya
Magaria
Malawa
Sassoumbroum
Wacha
Yekoua
689 153,271 1,072,897
Hamzari/
CARE
Maradi Chadakori
Guidan Roumdji
Guidan Sori
325 40,089 332,793
Wadata/
Save the Children
Zinder Damagaram-Takaya
Guidimouni 
Mazamni
Guidiguir
641 45,493 263,804
Source: The information in this table is generated from the censuses performed by each of the IPs in their respective areas. In the 
case of Girma, the number of individuals was estimated using census information on the number of households and assuming an 
average household size of seven members. 
Although the approach for each RFSA differs, all RFSAs implement activities across technical sectors, 
layering and sequencing interventions at both the individual and household levels. Key interventions are 
designed around improving food access and incomes through agriculture and other livelihoods 
initiatives; enhancing natural resource and environment management; combating undernutrition, 
especially for children under 2 years and pregnant and lactating women; and mitigating disaster impact 
through early warning and community preparedness activities. 
This report begins with an overview of the current food security situation in Niger. Section 2 describes 
the methods used for the PBS and limitations of the study design. Section 3 presents the PBS findings, 
organized by sector. Where possible, the results of the quantitative analyses are integrated with 
qualitative data and information from secondary sources to gain additional context and understanding 
of prevailing conditions and perceptions of the populations in the RFSA implementation areas. The 
report ends with conclusions and recommendations based on key findings.
Baseline Study of the RFSAs in Niger: Final Report (Vol. I)
Introduction 3
1.3 Country context 
1.3.1 Background
Niger has an estimated population of 24.2 million people (2020)2 and is the second-least urbanized 
country in Africa (16% urban).3 The country ranks last of the 189 countries on the Human Development 
Index, with a Human Development Index score of 0.394 (2020).4 Niger’s economy is highly dependent on 
agriculture, which constitutes 40% of the gross domestic product;5 three-quarters of the population 
(75.1%) work in agriculture.6 Agriculture is primarily rain-fed. Favorable agricultural conditions, along 
with investments in infrastructure and agricultural productivity, have supported a positive trend in 
national economic growth, which was 6.3% in 2019.7 Factors that may hinder Niger’s future economic 
performance include insecurity, the impacts of COVID-19, lower prices for oil, fluctuations in global non￾oil commodity prices, and vulnerability to climate shocks. Despite national economic gains in recent 
years, almost half the population (44.5%) lives below the national and purchasing power parity poverty 
line of $1.90 U.S. Dollar per day).8 Just 11.7% of the rural population has access to electricity.9 Mean 
years of schooling is 2.1.10 Niger’s fertility rate is seven births per woman, among the highest on the 
continent (birth rate in sub-Saharan Africa: 4.7).11
1.3.2 Overview of the Current Food Security Situation
The Famine Early Warning Systems Network (FEWS NET) report at the time of the baseline survey shows 
minimal food insecurity (Integrated Food Security Phase Classification Phase 1) in Maradi and Zinder 
regions as of October 2020; the southwestern area of Maradi is categorized as Integrated Food Security 
Phase Classification Phase 2. In October, price trends for cereals were following seasonal norms, though 
they were also higher than recent years due to border closures that disrupted trade flow, high transport 
costs for imports, and low production in 2019. The improvement in food security is attributed to “the 
 
2 United Nations Population Fund. 2020. State of the World Population 2020. Available at https://www.unfpa.org/data/world￾population-dashboard
3 United Nations, Department of Economic and Social Affairs, Population Division. 2019. World Urbanization Prospects: The 
2018 Revision (ST/ESA/SER.A/420). New York: United Nations
4 United Nations Development Program. 2020. Human Development Report 2020. Available at 
http://hdr.undp.org/en/countries/profiles/NER
5 World Bank. 2021. Website accessed 5 March 2021: https://www.worldbank.org/en/country/niger/overview (Overview page, 
updated 17 April 2020)
6 United Nations Development Program. 2020. Human Development Report 2020. 
7 World Bank. 2021. Website accessed 5 March 2021: https://www.worldbank.org/en/country/niger/overview (overview page, 
updated 17 April 2020)
8 United Nations Development Program. 2020. Human Development Report 2020. 
9 Ibid.
10 Ibid.
11 World Bank. 2018. World Bank database. Database query 5 March 2021.
IMPEL | Implementer-Led Evaluation and Learning
4 Introduction
generalization of harvests, the beginning of seasonal price declines, and increased income opportunities 
with the sale of crops, annuity products, and livestock.”12 Citing above-average rainfall, the FEWS NET 
report gives a positive outlook for pastoral and agricultural areas during the main harvest season, October 
to May (see seasonal calendar in Figure 1), with average yields predicted for both cereals and cash crops. 
However, the rain also caused flooding in all regions, including Maradi, resulting in substantial losses of 
materials and rice, millet, and sorghum crops. Livestock production prospects are also positive due to good 
fodder production and favorable terms of trade, though livestock producers’ purchasing power is 
forecasted to decline from April to May 2021 due to below-average prices, a downstream effect of 
mobility restrictions and animal export sales. Favorable grazing conditions may start to decline in March 
due to “…high concentrations of herds in good and secure production areas, which will accelerate the 
depletion of fodder stocks and impact the body condition and market value of livestock.”13
An April 2020 Nigerien government analysis of the impact of the COVID-19 pandemic on food and 
nutrition security found that 2.7 million people were facing food insecurity at crisis or worse levels.14 As 
of October 15, 2020, near the time of the baseline survey, FEWS NET reported a favorable pandemic 
trajectory, with maintenance of social and sanitary measures and land border closures but opening of air 
borders with COVID testing provisions in place at airports.15 Nevertheless, the pandemic has had a 
steady impact on household livelihoods—especially in urban areas—and national economic 
opportunities. The Global Information and Early Warning System (GIEWS) quarterly reports leading up to 
the baseline survey indicated favorable growing conditions for 2020, yet still projected an estimated 2 
million severely food insecure for the lean season (June–August), an increase from 1.2 million in 2019. 
This is due in large part to the persistent conflict and renewed violence by armed groups in the Diffa, 
Tahoua and Tillabery regions, as well as containment activities related to COVID-19. The three quarterly 
GIEWS reports on Niger from September 2020 to March 2021 have indicated worsening food insecurity; 
in March 2021 GIEWS categorized Niger as having widespread lack of access to food resulting from an 
increase in civil unrest that has disrupted agricultural and marketing activities and diminished 
households’ livelihood opportunities and food security. In addition to internal displacement due to 
conflict in Diffa, Tahoua and Tillabery regions, the substantial influx of refugees from neighboring 
Nigeria and Mali is also noted. The GIEWS considers Niger among those countries requiring external 
food assistance due to its food insecurity crisis (March 2021). In response to the crisis, by September 
2020, the Government of Niger Food Crisis Unit had distributed cereals and cowpeas to more than 1.2 
million Nigeriens under the Free Targeted Distribution program.16 It also provided fortified flour to 
 
12 FEWS NET. 2020. Food Security Outlook: The ongoing harvests improve food security except in the conflict zones. October 
2020. Available at https://fews.net/west-africa/niger/food-security-outlook/october-2020
13 Ibid. 
14 FAO. 2020. The Niger: Revised humanitarian response (May–December 2020): Coronavirus disease 2019 (COVID-19). Rome. 
Available at http://www.fao.org/3/cb0180en/CB0180EN.pdf
15 FEWS NET. 2020. Food Security Outlook: The ongoing harvests improve food security except in the conflict zones. October 
2020. Available at https://fews.net/west-africa/niger/food-security-outlook/october-2020
16 FEWS NET. 2020. Food Security Outlook: The ongoing harvests improve food security except in the conflict zones. October 
2020. Available at https://fews.net/west-africa/niger/food-security-outlook/october-2020
Baseline Study of the RFSAs in Niger: Final Report (Vol. I)
Introduction 5
children in 21 communes in six regions, including Zinder and Maradi, through its Blanket Feeding 
program.
Figure 1: Seasonal calendar for a typical year, Niger
Source: FEWS NET
IMPEL | Implementer-Led Evaluation and Learning
6 Methodology and Limitations
2. METHODOLOGY AND LIMITATIONS
2.1 Study Design
The baseline study is based on a pre-post (cross-sectional) design to allow for the detection of 
statistically significant change in key indicators between the baseline survey and interim performance 
evaluation, and between the baseline and endline surveys. 
2.2 Sample Design
The baseline survey sampling is designed to power adequately a statistical test of differences between 
the baseline and endline estimates for key performance indicators for each RFSA. The indicators used for 
the sample size calculations were selected with BHA and include the proportion of respondents that 
have adopted: 1) improved WASH practices, 2) improved agricultural storage practices and financial 
services, and 3) recommended maternal and child health and nutrition practices. The following 
parameter values were applied in the calculations: 1) design effect of 5 for WASH and agricultural 
practices indicators and 2 for maternal and child health and nutrition indicators;
1 2) 95% confidence 
level for one-tailed test; 3) 80% power for one-tailed test; 4) expected change of 15 percentage points 
over the life of the project; and 5) non-response factor of 25% to account for estimated household non￾response rate. The highest minimum required sample size was selected based on these calculations. 
Additional details on the sampling methodology, including the indicators and parameters for 
determining the sample size, can be found in the study protocol in Annex 1.
A stratified multi-stage clustered sample design was used with three stages of sampling: 1) selection of 
villages (25 villages per stratum/RFSA); 2) selection of households (31 households per village), and 3) 
selection of individuals.17 A total of 75 villages were sampled, with 31 households sampled in each 
village, resulting in a sample size of 2,325 households.18
 
17 The study protocol (See Annex 1) provides a detailed description of the sampling methodology, including criteria for defining 
“household” and household member selection procedures and the indicators and parameters for determining the sample size.
18 Based on the sample size calculations, the minimum sample size required was 750 households per RFSA area. However, 
during the listing exercise, TANGO determined that several of the villages in the Wadata RFSA area have a low household 
population (i.e., less than 30 households). To reach the minimum required sample size of 750, TANGO increased the number of 
households drawn per village in the second stage from 30 to 31 and adopted this threshold across all RFSA areas for 
consistency. Thus, the number of sampled households was increased from 750 households per RFSA area to 775 households, 
giving a total sample size of 2,325. See Annex 1a for details on revisions to the sampling.
Baseline Study of the RFSAs in Niger: Final Report (Vol. I)
Methodology and Limitations 7
Table 2 illustrates the derived sample size by RFSA area.
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8 Methodology and Limitations
Table 2: Sampled households, by RFSA area
RFSA Region Number of sampled villages Number of sampled 
households
Girma/Catholic 
Relief Services Zinder 25 775
Hamzari/CARE Maradi 25 775
Wadata/Save the 
Children Zinder 25 775
TOTAL 75 2,325
2.3 Questionnaire Design
The questionnaire used for the baseline survey is derived from the core BHA PBS questionnaire. The 
survey was streamlined for a non-permissive environment. USAID describes a non-permissive 
environment as a context, at the national or sub-national level, in which uncertainty, instability, 
inaccessibility or insecurity constrain USAID's ability to operate safely and effectively. The baseline 
survey is more limited than the core BHA PBS questionnaire but includes critical lower-level indicators.19
At the time of the study design, estimates of impact-level indicators pertaining to poverty and children 
and women’s anthropometry were expected to be derived from the RISE II baseline survey, then 
scheduled for May/June 2020, a few months after the RFSA baseline surveys (March/April).20 Although 
there are methodological limitations21 to combining results from different surveys, this approach is 
considered acceptable given the geographic overlap of the target populations and the temporal overlap 
originally expected in the timing of the two surveys.
All questionnaire modules follow FFP and Feed the Future guidelines, as described in the FFP Indicators 
Handbook (May 2020)22 and questionnaire template.23 The baseline survey questionnaire includes 
modules on the following topics: 
Module A: Household Identification and Informed Consent.
Module B: Household Roster.
Module C: Food Consumption Score.
Module D: Child Feeding Practices and Diarrhea.
Module E: Women’s Dietary Diversity, ANC, Contraceptive Prevalence Rate, and Family Planning.
 
19 The survey tool did not collect anthropometric measurements for children or women, or household consumption 
expenditure data.
20 This schedule was later changed; see study limitations in Sec. 2.6.1.
21 There are limitations to the approach of combining outcome-level indicators from one source with impact-level indicators 
from another survey relating to differences in study design and timing of data collection. The forthcoming RISE II baseline 
survey will not be powered to provide estimates at the level of individual RFSA areas, an approach approved by BHA. This 
contrasts with the current BHA baseline survey, which is powered to provide RFSA-level estimates. Differences in the timing of 
the surveys may impact some indicators that are sensitive to seasonality.
22 Available at https://www.usaid.gov/food-assistance/documents/ffp-indicators-handbook-part-i-indicators-baseline-and￾endline-surveys-rfsa
23 Ibid. 
Baseline Study of the RFSAs in Niger: Final Report (Vol. I)
Methodology and Limitations 9
Module F: Water, Sanitation and Hygiene.
Module G: Agriculture (crop, livestock, natural resource management [NRM], storage, financial 
services).
Module J: Gender and Cash.
Module KF: Access to Credit and Group Membership (youngest woman in a union).
Module KM: Access to Credit and Group Membership (partner of youngest woman in a union).
Module P: Activity Participation.
Module Q: COVID-19 Awareness, Impacts, and Coping Strategies.
Module R: Social Capital.
Module 7.51: Agricultural Production – Goats.
Module 7.52: Agricultural Production – Sheep.
Module 7.90: Plot/Land map.
Module 7.9: Plot Area.
Module 7.92: Crop Yield.
Questions and response options were adapted to the country context such as those that involve food in 
Modules C, D, and E, and the types of containers and sanitation facilities listed in Module F. The survey 
was also contextualized to capture information on different improved agricultural practices promoted in 
each RFSA area. A COVID-19 module was added to collect information on knowledge and adoption of 
COVID-19 mitigation practices, the impacts of COVID-19 on households’ livelihoods and food security 
and coping strategies to manage those impacts. Another module was incorporated to collect 
information on household participation in the RFSA given that RFSA interventions started before the 
baseline survey could be performed (due to COVID-19 delays) and some life-saving activities and 
essential services may have continued throughout the COVID-19 pandemic. 
Table 3 illustrates the indicators measured and the level of disaggregation as prescribed in the FFP 
handbook supplement on indicator tabulations.24
Table 3: Indicators measured in the 2020 baseline survey of the RFSAs in Niger
Indicator Disaggregation Level
FOOD SECURITY 
Percentage of households with poor, borderline, and adequate FCS
Mean FCS Gendered household type*
WATER, SANITATION AND HYGIENE
Percentage of households using basic drinking water services Gendered household type*
Percentage of households with access to a basic sanitation service Gendered household type*
Percentage of households with soap and water at a hand-washing station on 
premises Gendered household type*
AGRICULTURE
Percentage of farmers who used financial services (savings, agricultural credit 
and/or agricultural insurance) in the past 12 months Sex
 
24 Available at https://www.usaid.gov/food-assistance/documents/ffp-indicators-handbook-supplement-part-1
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10 Methodology and Limitations
Indicator Disaggregation Level
Percentage of farmers who used improved storage practices in the past 12 
months Sex
Proportion of producers who have applied targeted improved management 
practices or technologies**
Commodity
Sex
Age (15–29, 30+)
Management practice or 
technology type
Yield of targeted agricultural commodities within target areas1
Crops: commodity, farm size, 
sex, age (15–29, 30+)
Livestock: commodity, 
production system, sex, age
WOMEN’S HEALTH AND NUTRITION
Percentage of women of reproductive age consuming a diet of minimum 
diversity Age: <19, 19+ years
Percent of births receiving at least four antenatal care visits during pregnancy None
Contraceptive prevalence rate Traditional, modern
Percent of women in union who have knowledge of modern family planning 
methods that can be used to delay or avoid pregnancy Age: 15–19, 20–29 and 30–49
Percent of women in union who made decisions about modern family planning 
methods in the past 12 months
Decision-making: alone, 
jointly, spouse
Age: 15–19, 20–29, 30–49
CHILD HEALTH AND NUTRITION
Prevalence of children 6–23 months consuming a diet of minimum diversity Sex
Percent of children under age five (0–59 months) who had diarrhea in the prior 
2 weeks Sex
Percentage of children under age five (0–59 months) with diarrhea treated 
with Oral Rehydration Therapy Sex
GENDER – CASH
Percent of women/men in union who earned cash in the past 12 months 
Sex 
Age: female 15–19, 20–29, 30–
49, ≥50; male 15–19, 20–29, 
30–49, ≥50
Percent of women in union and earning cash who report participation in 
decisions about the use of self-earned cash2 Age: 15–19, 20–29, 30–49, ≥50
Percent of women in union and earning cash who report participation in 
decisions about the use of spouse/partner's self-earned cash2 Age: 15–19, 20–29, 30–49, ≥50
Percent of men in union and earning cash who report spouse/partner 
participation in decisions about the use of self-earned cash2 Age: 15–19, 20–29, 30–49, ≥50
GENDER CREDIT AND GROUP PARTICIPATION3
Percent of women/men who are members of a community group 
Sex
Age: female 15–19, 20–29, 30–
49, ≥50; male 15–19, 20–29, 
30–49, ≥50
Percent of women/men in union with access to credit 
Age: female 15–19, 20–29, 30–
49; male 15–19, 20–29, 30–49, 
≥50
Baseline Study of the RFSAs in Niger: Final Report (Vol. I)
Methodology and Limitations 11
Indicator Disaggregation Level
Percent of women/men in a union who make decisions about credit 
Decision actors: alone, jointly
Sex
Age: female 15–19, 20–29, 30–
49, ≥50 
male 15–19, 20–29, 30–49, 
≥50
RESILIENCE-RELATED
Proportion of households that believe local government will respond 
effectively to future shocks and stresses Gendered household type*
Index of social capital at the household level
Social capital components:
overall index, bonding sub￾index, bridging sub-index
Gendered household type*
Proportion of households participating in group-based savings, microfinance,
or lending programs 
Financing type 
Gendered household type*
Notes: * Following FFP indicator descriptions, Feed the Future defines four gendered household types: households with 1) 
female and male adults, 2) adult female, no adult male, 3) adult male, no adult female, and iv) child, no adults. USAID, 2020. 
Food for Peace Indicators Handbook. Part I: Indicators for Baseline and Endline Surveys for Resilience Food Security Activities. 
May.
**This applies to crops and livestock of interest. For Niger, the crops of interest are sorghum, millet, cowpeas, and peanuts. The 
livestock of interest are goats, sheep, and poultry.
1 The survey collected information on agricultural yield; however, due to measurement challenges, particularly in relation to size of 
cultivated plot area and weight of livestock, indicator estimates for agricultural yield are not included in this report or Annex 5. 
2 The Open Data Kit skip logic was not programmed to allow for the calculation of the gender and cash indicators because the 
following groups were excluded: 1) respondents who worked for a combination of cash and in-kind and 2) respondents who 
reported not discussing their earnings with anyone. 
3 Because of the prevalence of polygamy (and multigenerational households) in the region, the youngest woman in a union was 
selected to obtain a more accurate understanding of gender equality and female empowerment, since the youngest married 
female often faces the most challenges and is the least empowered.
2.4 Field Procedures
2.4.1 Timing of the Survey
Data collection for the baseline study was scheduled to commence in early 2020 (March–April) and end 
by April 23, 2020, before the start of Ramadan. However, due to the onset of the COVID-19 pandemic, 
fieldwork for the baseline survey was suspended until local regulations (e.g., travel restrictions) and 
conditions (e.g., local transmission of virus, willingness of households to be interviewed in-person) 
indicated that face-to-face interviewing could safely resume with COVID-19 mitigation procedures in 
place. Based on the revised schedule, the survey was conducted in September 2020 and ended at the 
start of the harvest period in October 2020. 
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12 Methodology and Limitations
In advance of fieldwork, TANGO, in partnership with Bagna, updated its fieldwork protocol to include 
COVID-19 safety measures to mitigate the risk of virus transmission and safeguard the well-being of 
staff, households, and communities25 (see the survey protocol in Annex 1 for additional details).
2.4.2 Listing Exercise
The listing training and exercise took place between August 24 and September 15, 2020. Bagna 
conducted the listing training, mapping of selected villages, and listing of households. Listers were 
trained on how to locate a cluster (village), prepare sketch maps of the cluster, list households, and 
segment large clusters. The household listing operation was conducted by 30 listers across 75 clusters 
with oversight by three supervisors. During the listing exercise, GPS coordinates for each village were 
taken by using a designated central point in the village. GPS coordinates were also taken for each listed 
household to facilitate locating sampled households during data collection. During the listing exercise, 
TANGO made several revisions to the list of villages initially selected for the baseline survey. Revisions to 
the initial sampling were necessary due to expansion in the implementation area of the Wadata RFSA in 
Zinder, selection of replacement clusters to avoid overlap with the RISE I endline survey sample, small 
number of households in a village, security risks, or inaccessibility due to weather. The results of the 
listing exercise were used for second-stage household sampling.
2.4.3 Training 
Due to the COVID pandemic and security risks, regional trainings were held in Maradi and Zinder to 
minimize travel and avoid large gatherings. Training curricula were mainstreamed with COVID-19 
mitigation and safety protocols (see Annex 1 for details).26
Training of trainers
TANGO led a virtual training of trainers (ToT) for Bagna field supervisors, local independent survey 
monitors, and team leads. The 6-day ToT was conducted via Zoom from August 31 to September 6. 
TANGO trained three field supervisors, 15 team leads and four local survey monitors. The ToT focused 
on roles and responsibilities, organization and supervision of fieldwork, data quality assurance, and 
performance monitoring. Sessions also involved a question-by-question review of the instrument. To 
capitalize on time zone differences, the training schedule was adapted to begin in the afternoon in 
Nigerien time so that the mornings could be used for study periods to review manuals and conduct 
 
25 The underlying principle guiding the adaptations to the baseline survey data collection procedures is Do No Harm. Per the 
USAID/FFP and USAID/OFDA Interim Guidance for Applicants Engaging in COVID-19 Humanitarian Response: in all 
programming, the safety and security of community members and implementing partner staff are critical; where remote 
monitoring is not feasible, update data collection tools and protocols to limit proximity, frequency, and duration of face-to-face 
contact.
26 In addition to the standard training on the instrument and tablets, participants were trained on Do No Harm principles and 
COVID-sensitive data collection protocols. Trainings included background on how COVID-19 is transmitted and methods to 
prevent its spread.
Baseline Study of the RFSAs in Niger: Final Report (Vol. I)
Methodology and Limitations 13
mock interviews using tablets to ensure that all participants were well versed in the instrument and in 
navigating the electronic survey. 
Main training
The 7-day (enumerator) training was conducted from September 13 to September 18. A total of 90 
enumerators were trained.27 Bagna field supervisors and the independent survey monitors, previously 
trained by TANGO during the ToT, conducted the main training with remote support from TANGO.28
Local independent survey monitors, trained during the ToT, participated in the main training, observed 
the mock interviews, and provided feedback. Training topics included data gathering, sampling strategy, 
human subjects research, a review of the survey questionnaire, how to gather data using mobile 
devices, data checks for quality control, creating backup copies of data, and data archiving and transfer. 
The training included a combination of plenary sessions for question-by-question guidance and breakout 
groups to practice and role-play using the tablets. The breakout groups were followed by a plenary 
session to discuss issues experienced and how to handle them. An events calendar for Niger was 
developed as a reference to help enumerators estimate the age of respondents when the age could not 
be ascertained. Photographs of sanitation facilities and water containers were provided to improve 
accuracy in recoding responses. Local IP staff participated in the training and gave technical 
presentations on their RFSAs.
2.4.4 Pilot
At the end of the enumerator training, a 1-day pilot test was conducted on September 19 in Maradi and 
Zinder. Each enumerator completed two full interviews during the pilot test. Each interview took 
approximately 2 hours, depending on the size of the household. Team leads and field supervisors 
observed enumerators and took notes on their performance. On September 20, the Bagna survey 
manager, field supervisors, and team leads debriefed their teams. Separate debriefs were held for each 
RFSA to discuss challenges and issues experienced during the pilot. The debrief sessions were attended 
by TANGO staff. 
2.4.5 Fieldwork
The start of fieldwork was postponed due to the need to redo the listing exercise in several villages in 
the Girma and Hamzari RFSA areas.29 Fieldwork commenced on September 27, nearly a week after the 
pilot. During this period, TANGO revised the electronic questionnaire based on the results of the pilot, 
 
27 Bagna recruited and trained 75 enumerators plus an additional 20% (total: 90 people trained) to serve as replacements if 
needed and to reduce the number of days in the field to mitigate COVID-19-related risks. 
28 TANGO and the trainers were connected on a WhatsApp group and communicated daily and as needed when issues arose 
during the training. In addition, TANGO staff connected via Zoom and participated in the daily de-brief plenary sessions where 
issues were discussed among trainers and participants. 
29 The study protocol (Annex 1) provides details on the issues encountered during the listing exercise that contributed to delays 
in the start of data collection. 
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14 Methodology and Limitations
and data collection teams were provided with a refresher training before travelling to their respective 
first clusters. Fifteen teams conducted the data collection (five teams per RFSA area). Each team was 
comprised of one team lead and five enumerators. In addition, Bagna’s field team included one survey 
manager, one coordinator, three field supervisors, and two Information Technology specialists for a 
total of 97 field staff. Four local survey monitors (two in the Girma RFSA area and one each in the 
Hamzari and Wadata RFSA areas) independent of Bagna and hired directly by TANGO accompanied the 
teams for the duration of data collection to provide quality control and oversight of fieldwork.30 Data 
were collected using tablets programmed with Open Data Kit, an open-source data capture program. 
Completed interviews were uploaded daily to a TANGO cloud server via secure transmission.31 TANGO 
convened daily debriefs with the Bagna survey manager and local survey monitors to discuss and resolve 
issues (e.g., issues with the instrument, data collection program/tablet, survey protocols, etc.…) as they 
emerged. 
2.5 Data Analysis
2.5.1 Sampling Weights
Separate sampling weights were calculated for indicators and adjusted to compensate for household 
and individual non-response. Sampling weights were calculated separately for each RFSA area for each 
of the following distinct groups by taking the inverse of the probabilities of selection from each stage of 
sampling:
• Households (modules C, F, P, Q, R).
• Children under 5 years (Module D).
• Women 15–49 (Module E).
• Male cash earners married or in a union (Module J).
• Female cash earners married or in a union (Module J).
• Spouse of youngest female in household (Module JM).
• Youngest female in household (Module JK).
• All farmers (Module G).
32
Table 4 illustrates response rates by sampling group for each RFSA area.33 Refer to Annex 4 for details on 
the calculation of sampling weights.
 
30 Annex 3 provides a list of the study personnel.
31 Data for each RFSA were managed and maintained on separate secure TANGO servers.
32 Separate sampling weights were calculated for goat and sheep farmers to be used for estimating mean producer-level yield. 
33 Enumerators attempted to complete interviews with all eligible respondents in the household. Possible reasons for non￾response include refusal to participate or the member being absent from the household at the time of the visit (and subsequent 
revisits). In some cases where the eligible respondent is unavailable, it is possible to interview a knowledgeable person (adult) 
Baseline Study of the RFSAs in Niger: Final Report (Vol. I)
Methodology and Limitations 15
Table 4: Response rates by sampling group and RFSA area, Niger 2020 RFSA baseline survey
Sampling group Number eligible Number 
interviewed Response rate (%)
Girma/Catholic Relief Services
Households (modules C, F, P, Q, R) 775 767 99.0
Children under 5 years (Module D) 1,089 1,055 96.9
Women 15-49 (Module E) 865 784 90.6
Male cash earners married or in a union 
(Module J) 543 491 90.4
Female cash earners married or in a union 
(Module J) 378 344 91.0
Youngest female in a union (Module KF) 705 666 94.5
Spouse of youngest female in a union 
(Module KM) 679 584 86.0
All farmers (Module G) 1,336 1,201 89.9
Goat herders (Module 7.51) 526 526 100.0
Sheep herders (Module 7.52) 197 197 100.0
Hamzari/CARE
Households (modules C, F, P, Q, R) 770 754 97.9
Children under 5 years (Module D) 1,304 1,231 94.4
Women 15-49 (Module E) 1,322 1,230 93.0
Male cash earners married or in a union 
(Module J) 579 513 88.6
Female cash earners married or in a union 
(Module J) 474 434 91.6
Youngest female in a union in (Module KF) 769 711 92.5
Spouse of youngest female in a union 
(Module KM) 722 623 86.3
All farmers (Module G) 1,426 1,329 93.2
Goat herders (Module 7.51) 530 530 100.0
Sheep herders (Module 7.52) 215 215 100.0
Wadata/Save the Children
Households (modules C, F, P, Q, R) 768 740 96.4
Children under 5 years (Module D) 867 820 94.6
Women 15-49 (Module E) 827 751 90.8
Male cash earners married or in a union 
(Module J) 393 338 86.0
Female cash earners married or in a union 
(Module J) 225 196 87.1
 
in place of the selected respondent after three re-visits/attempts have been made to interview the selected member. This type 
of substitution is allowed for modules capturing household-level information (i.e., modules A, B, C, F, P, Q, and R). It is also 
possible to interview a responsible adult knowledgeable of farming/livestock practices in lieu of the eligible farmer/herder if 
s/he is absent after three visits. However, substitutes are not allowed for other modules such as Module D (children); Module E 
(women), Module J (gender and cash), as well as modules KF and KM (youngest female in a union and her spouse). This can 
help explain why response rates for modules that do not allow substitution are lower than those of other modules that allow 
substitutions. It also possible, that the youngest female in a union and her spouse may be harder to find at home than other 
household members.
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16 Methodology and Limitations
Sampling group Number eligible Number 
interviewed Response rate (%)
Youngest female in a union in (Module KF) 647 604 93.4
Spouse of youngest female in a union 
(Module KM) 625 478 76.5
All farmers (Module G) 913 828 90.7
Goat herders (Module 7.51) 260 260 100.0
Sheep herders (Module 7.52) 111 111 100.0
Note: The response rate is calculated by dividing the number interviewed by the number eligible and multiplying the result by 
100. The number eligible is derived from the responses to the household roster data.
2.5.2 Indicator Definitions and Tabulations
The calculation and tabulation of indicators was performed based on FFP and Feed the Future guidance 
as described in the FFP Indicators Handbook Part 1 and the Supplement to Part 1.Annex 4 describes 
data processing routines, including the handling of missing data, and the full suite of analyses conducted 
for the baseline study. Results are weighted to represent the entire target population in each of the 
three RFSA areas.34 Point estimates with 95% confidence intervals and variance estimations were 
derived for all indicators using Taylor series expansion and considering the design effect associated with 
the complex sampling design. Annex 5 provides a tabular summary of the indicator estimates and 
sampling statistics. Annex 6 presents the results of additional descriptive analyses. Results of the 
bivariate and multivariate analyses are included in Annex 7. 
2.6 Study Limitations and Issues Encountered
2.6.1 Study Limitations
Timing of the Survey: Data collection was originally planned for March/April 2020 but due to COVID-19 
restrictions was re-scheduled to September, ahead of the main harvest season in October, to avoid an 
upward bias of food security estimates in the RFSA areas.35 The timeline for pre-fieldwork activities and 
data collection was thus condensed from its original schedule and the number of enumerators was 
increased from four to five per team to be able to complete data collection before the start of the 
harvest. Despite efforts to avoid spillover into the harvest period, data collection ended on October 
11.36 To assess the possible effects of the timing of data collection on food security estimates, 
households were asked whether they cultivated any crops at any time directly before or during data 
collection. 
 
34 Because the estimates are based on a sample of the target population rather than the full target population (i.e., a census),
sampling weights are applied to correct for unequal selection probabilities, coverage issues and non-response. If sampling 
weights are not applied to survey data, the results can be biased.
35 The timing of data collection can exert an upward bias on the food consumption score (i.e., overstate the extent to which 
households are food secure) if data collection spills further into the harvest period, when households are likely to have better 
access to diverse and nutritious food.
36 Delays occurred due to several issues encountered in the field and are described in Section 2.6.2.
Baseline Study of the RFSAs in Niger: Final Report (Vol. I)
Methodology and Limitations 17
Another consequence of the survey timing is that because RFSA interventions began before the survey 
could commence, the estimates may not necessarily reflect a true “baseline.” Therefore, the study 
collected information on direct participation in RFSA interventions to assess differences in baseline 
estimates between direct and indirect participants.
Limitations of Combining Data Sources: The original plan to derive poverty and children and women’s 
anthropometry indicators from the RISE II baseline survey was complicated by the delay of RISE II 
baseline data collection. While the timing of the RISE II baseline coincides with about the same 
timeframe as the current study, avoiding any differences in seasonality, these impact-level indicator
data collected from the RISE II baseline will be separated by approximately 12 months from the 
indicators presented in the current study. Differences in prevailing conditions at the time of the two 
surveys (e.g., prices, markets, and COVID-19 conditions) should be taken into consideration in the 
interpretation of results. 
Validity and Reliability of Self-reported Data: Most of the data collected for the household survey are 
self-reported. Limitations of self-reported data include the potential for exaggeration or omission of 
information; inaccurate recall; the potential for respondents to give responses they perceive as 
desirable, expected, or acceptable; reporting of untruthful information; and reduced validity if 
respondents do not fully understand a question. Enumerators were trained in techniques to help 
mitigate these types of measurement bias. 
The reliability of self-reported data is particularly challenging for questions related to agricultural yield. 
The baseline survey relied on self-reported data rather than direct measurement to collect information 
on cultivated plot area, amount of crop harvested per plot, and weight of livestock.37 While direct 
(physical) measurement by experts can generate more accurate estimates of agricultural yield, this 
procedure is more expensive and time-consuming.38 Farmer estimates are a simpler, less costly, and 
more efficient method of data collection but can introduce measurement error due to recall bias (for 
longer recall periods or if data collection does not occur soon after harvest), lack of knowledge, or
perceived incentives for under- or over-reporting production estimates.39 Accurate measures of both 
area and production are ideal, but accurate measurement of area is more crucial for reducing errors in 
 
37 Several factors can influence the quality of estimates of agricultural yield, including but not limited to method of data 
collection (i.e., direct measurement versus farmer estimates), inter-cropping, continuous harvesting, and use of non-standard 
units. For a more comprehensive review of issues related to the measurement of agricultural indicators refer to the 2013 Feed 
the Future Agricultural Indicators Guide: Guidance on the collection and use of data for selected Feed the Future Agricultural 
Indicators by Suzanne Nelson and Anne Swindale, available at 
https://www.agrilinks.org/sites/default/files/resource/files/FTF_Agriculture_Guide_Jan2014.pdf. 
38 Diskin, Patrick. 1997. Agricultural Productivity Indicators Measurement Guide. Washington, D.C.: Food and Nutrition Technical 
Assistance Project, Academy for Educational Development. Available at 
https://reliefweb.int/sites/reliefweb.int/files/resources/842682301AA98504C1256F070044D507-
USAID_Agricultural_indicators_December_1997.pdf.
39 Nelson and Swindale 2013 and Diskin 1997. 
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18 Methodology and Limitations
the calculation of agricultural yield.40 Preliminary analysis of self-reported yield-related data found 
outliers in plot size and weight of livestock data. This is unsurprising given that farmers in the RFSA areas 
may lack the knowledge or equipment needed to measure the size of their plots, and very few farmers 
weigh their cattle (see Section 3.4.5). This issue was discussed prior to the start of fieldwork, and several 
steps were taken to minimize the effect of errors associated with self-reported estimates: 1) applying 
conversion factors to render non-standard units suitable for analysis;41 2) obtaining plausible ranges
from the IPs for the weight of female and male adult and young goats and sheep and using these as a 
data reliability check; and 3) performing several post-data collection processing routines to identify and 
address outliers in plot size, quantity harvested, and livestock weight data.42Nevertheless, considering 
the measurement challenges described above, no further analysis of the yield data was performed. 
Non-response: Respondents may be reluctant to participate in the survey due to general mistrust that 
may arise in politically volatile situations and fears of falling ill in the baseline context of the COVID-19 
pandemic. It is also possible that households may relocate or move due to the political situation. The 
study employed various measures to account for potential non-response, emphasize the anonymous 
and voluntary nature of study participation, and implement COVID-19 safety measures. As a 
methodological measure, the study design uses a higher-than-usual non-response factor of 25%. In 
terms of implementing the survey, field teams were trained to explain to respondents the objectives of 
the study and measures taken to preserve the anonymity of their responses and thus encourage 
participation. TANGO also updated the consent statement to include potential exposure to COVID-19 
risks, and enumerators were trained and required to explain the risks associated with participating in a 
face-to-face interview in the context of the pandemic to each eligible household. 
2.6.2 Issues Encountered During Fieldwork
Difficulties locating households: One sampled village in the Wadata RFSA area was replaced prior to 
data collection because most adult household members had migrated to their fields to harvest their 
crops due to a pest infestation. The replacement was made following study protocol.
 
40 Nelson and Swindale 2013. 
41 Conversion factors for non-standard units were based on the 2018 Enquête Harmonisée sur les Conditions de Vie des 
Ménages.
42 Two approaches were used to adjust producer-level yield to mitigate the effects of extreme values (outliers): trimming the 
top 5% (i.e., exclusion of outliers from analysis) and winsorizing (retaining observations but capping numeric outliers so that 
they fall at the edge of the distribution using the 95th percentile). Thresholds for capping were determined for each RFSA area 
separately. 
Baseline Study of the RFSAs in Niger: Final Report (Vol. I)
Methodology and Limitations 19
Discrepancy in household listing. The household listing was re-done in seven villages in the Girma and 
Hamzari RFSA areas because they had significantly fewer households than reported in IP census data.43
The field movement plan was adjusted so that data collection could begin in other villages.
Poor network connectivity: Because of poor and intermittent network connectivity, the training period 
was extended in order to schedule make-up training sessions. 
Impassable roads due to seasonal rains: Deployment of data collection teams to the field was slowed 
down due to heavy rains that made roads impassable. 
Compact schedule: The timeline for the pre-fieldwork activities and data collection was condensed in 
order to complete data collection at the start of the harvest period and reduce the duration of data 
collection. TANGO modified the training agenda as needed to keep with the schedule. TANGO 
coordinated closely with its independent survey monitors and the local supervisors to ensure that 
fieldwork was progressing as planned.
2.7 Qualitative Data
In accordance with the study protocol, the baseline study did not collect primary qualitative data; 
qualitative data will be collected for the interim performance evaluation. To contextualize and help 
interpret the PBS baseline quantitative findings, the baseline study incorporates qualitative data 
available in relevant recent studies conducted in Niger, primarily the qualitative data TANGO collected 
for the USAID RISE I impact evaluation endline and 2017-performance evaluation of USAID Title II DFAPs
in Niger. The use of existing data reinforces USAID’s focus on the use and dissemination of data and 
lessons learned across countries and within the Implementer-Led Design, Evidence, Analysis and 
Learning (IDEAL) activity-supported food security and nutrition community of practice. The baseline 
study report also draws contextual information from external sources that are publicly available, e.g., 
FEWS NET, World Bank, and United Nations agencies. The final baseline report was additionally 
informed by the review of the draft report by BHA staff and IPs and by input provided in a series of data 
utilization workshops that TANGO conducted with technical and monitoring and evaluation staff from 
each of the IPs.44 These exercises sought to further triangulate findings, help explain unexpected 
quantitative results, and validate the relevance, utility, and feasibility of baseline recommendations.
 
43 The discrepancy in the number of households between the listing data and IP data could be partially explained by the 
following factors: 1) definition of a village/boundaries of a village: IPs tended to define a village as a cluster of smaller villages or 
nearby hamlets whereas Bagna listers defined the boundaries of a village based on the natural boundaries of the “main village;” 
2) village segmentation: several larger villages were segmented into smaller villages. For villages that were segmented, Bagna 
provided TANGO with information on the size of the village and number of segments into which it was divided. 
44 TANGO conducted three virtual data utilization workshops (one per RFSA) to review the baseline results, interpret and 
contextualize findings, and identify potential program adjustments. 
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20 Findings
3. FINDINGS
This section presents the baseline survey findings by topic, integrating information from secondary 
qualitative data sources where possible. Results are provided for each RFSA area. In cases where the 
pattern or distribution of the indicator results is similar across RFSA areas, the results are illustrated and 
discussed in the aggregate. Findings are considered statistically significant at the level of p < 0.05. Annex 
4 summarizes the full set of analyses performed as part of the baseline study, including the 
methodology for the bivariate and multivariate analyses. Annex 5 provides a tabular summary of 
indicator estimates and sampling statistics. The results of the descriptive analyses are presented in 
Annex 6 and the results of the bivariate and multivariate analyses are presented in Annex 7. Annex 8 
presents the results of the COVID-19 module.
3.1 Characteristics of the Study Population
In 2020, the estimated population of Niger was 24.2 million.45 The population in the combined RFSA
areas is estimated at 1.14 million,46 approximately 4.7% of the country’s total population. 
 
45 UNFPA State of the World Population 2020. Available at https://www.unfpa.org/data/world-population-dashboard
46 The estimate is based on the baseline study.
Baseline Study of the RFSAs in Niger: Final Report (Vol. I)
Findings 21
Figure 2 illustrates the share of key demographic groups from the overall population in the combined 
RFSA areas. Among the RFSA-area population aged 15 years or older, 44% are cash earners (male 56.8%; 
female 32.4%) and 56.4% are farmers (male 61.5%; female, 51.8%). Among women 15–49 years, 85%
are married or in a union and 66% have had a live birth in the 5 years preceding the survey. About one￾quarter of children under 5 years (26.5%) are between 6 and 23 months.47
 
47 See Annex 6, Table A6.1 for additional details on estimated population counts in the RFSA areas disaggregated by subgroup.
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22 Findings
Figure 2: Share of key demographic groups from the overall population, combined RFSA areas
one child 6–23 months of age. 
Table 5 presents the characteristics of households in the RFSA areas. Household size and composition may 
have implications for women’s and children’s health and nutrition and for food security of the overall 
household because these factors influence access to income-generating opportunities and other 
resources, the division of labor, and the distribution of resources among household members. Larger 
households may have fewer resources depending on the ratio of working-age adults to dependents. 
There are an estimated 168,308 households in the combined RFSA areas. The average household has 
about 6.8 members, of which about 2.9 are 15 years or older.48 Most households are comprised of both 
 
48 For the purposes of the survey, a household is defined as adults or children that live together and “eat from the same pot." It 
includes anyone who has lived in the house for at least 6 months in the 12 months prior to the survey but does not include anyone 
who lives in the household but eats separately.
Baseline Study of the RFSAs in Niger: Final Report (Vol. I)
Findings 23
adult males and females (Girma, 83.9%; Hamzari, 93.2%; Wadata, 78.6%).49 Adult-female-only 
households, defined as households with at least one adult female and no adult males, account for more 
than 10% of all households in the Girma (11.1%) and Wadata (12.8%) RFSA areas, and just under 5% in 
the Hamzari RFSA area (4.7%). Adult-male-only households constitute a relatively smaller percentage of 
the overall household population in the Girma (4.8%) and Hamzari (2%) RFSA areas.
50 In the Wadata
RFSA area, 8.2% of households are adult-male-only.51 Most households include at least one child under 
the age of 5 years (Girma, 75%; Hamzari, 77.9%; Wadata, 71.1%). About one third of households (Girma, 
32.2%; Hamzari, 35.7%; Wadata, 27.4%) include at least one child 6–23 months of age. 
Table 5: Household characteristics, total and by RFSA area
Household Characteristics Combined 
RFSAs
Girma Hamzari Wadata
Gendered household type (Number of households)1 168,308 98,502 28,095 41,711
Male and female adults 141,611 82,656 26,182 32,772
Female adult(s) only 17,548 10,900 1,324 5,324
Male adult(s) only 8,710 4,737 568 3,404
Child(ren) only (no adults) ^ ^ ^ ^
Gendered household type (Percentage of households) 100.0 100.0 100.0 100.0
Male and female adults 84.1 83.9 93.2 78.6
Female adult(s) only 10.4 11.1 4.7 12.8
Male adult(s) only 5.2 4.8 2.0 8.2
Child(ren) only (no adults) ^ ^ ^ ^
Average household size (Number of persons) 6.8 6.6 8.7 5.9
Average number of adults 15 years of age or older per 
household 2.9 2.8 3.7 2.6
Percentage of households with children under 5 years 74.5 75.0 77.9 71.1
Percentage of households with a child 6–23 months of age 31.6 32.2 35.7 27.4
Household headship (Percent female) 13.6 14.1 6.3 17.1
Number of responding households 2,261 767 754 740
 
49 As stipulated in Feed the Future guidelines, adults for gendered household type are defined as individuals 18 years of age or 
older. The interviews and all other analyses include individuals 15 or older. Following FFP indicator descriptions, Feed the 
Future defines four gendered household types: households with 1) female and male adults, 2) adult female, no adult male, 3) 
adult male, no adult female, and 4) child, no adults. USAID, 2020. Food for Peace Indicators Handbook. Part I: Indicators for 
Baseline and Endline Surveys for Development Food Security Activities. May. Available at https://www.usaid.gov/food￾assistance/documents/ffp-indicators-handbook-part-i-indicators-baseline-and-endline-surveys-rfsa.
50 Because the definition of gendered household type classifies individuals 18 years or older as adults, households with female 
spouses aged 15–17 are counted as adult-male-only. Adult-male-only households can also include single/unmarried men or 
widowed men.
51 Most adult-male-only households in the Wadata RFSA area are households where the female spouse is between the ages of 
15 and 17, therefore falling below the threshold defined for gendered household type.
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24 Findings
Household Characteristics Combined 
RFSAs
Girma Hamzari Wadata
Male and female adults 1,936 651 705 580
Female adult(s) only 204 76 30 98
Male adult(s) only 114 38 17 59
Child(ren) only (no adults) 7 2 2 3
Source: BHA 2020 Niger baseline survey weighted population estimates. Based on household counts from the baseline listing 
operation, which defined villages based on the natural boundaries of the "main village."
^ Results not statistically reliable, n < 30.
3.2 Activity Participation
The baseline survey collected information on household participation in RFSA activities given that 
implementation of RFSA interventions commenced before the baseline survey began. The estimates are 
based on self-reported information; households are considered direct participants in the RFSA if 
someone in the household participated in any of the RFSA interventions. Households in which no 
member participated in any RFSA interventions are considered indirect participants. A total of 34.8% of 
households in the Girma RFSA area were direct participants, 44.9% in the Hamzari RFSA area, and 54.9%
in the Wadata RFSA area.
52
Figure 3 illustrates the percentage of direct and indirect participant households that received social 
assistance in the RFSA areas by type of assistance received. Significance tests indicated that direct 
participants were more likely to receive food rations and participate in agriculture, nutrition and WASH 
trainings and meetings in all three RFSA areas with one exception: in the Girma RFSA area there was no 
difference in the receipt of food rations between direct and indirect participant households.53
Figure 3: Household receipt of social assistance among direct and indirect participants, by RFSA area 
Notes: Households were asked "Have you or someone in your household participated in [Girma/Hamzari/Wadata]?" Households 
that responded 'yes' are considered direct participants in the RFSA and households that responded 'no' are considered indirect 
 
52 See Annex 6, Table A6.3.
53 Refer to Annex 6, Table A6.3 for additional details.
Baseline Study of the RFSAs in Niger: Final Report (Vol. I)
Findings 25
participants because although no household member participated directly in any of the RFSA interventions, the household falls 
in the RFSA intervention area.
3.3 Household Food Security
The U.S. Government Global Food Security Strategy Fiscal Year 2017–2021 defines food security as “access 
to—and availability, utilization, and stability of—sufficient food to meet caloric and nutritional needs for 
an active and healthy life.”54 The main measure of food security used in this survey is the FCS. The FCS is a 
proxy indicator for food intake and is calculated considering dietary diversity, food frequency, and the 
relative nutritional value of nine different food groups consumed by the household in the seven days prior 
to the survey.55 Based on weighted scores and using World Food Programme (WFP) thresholds, 
households are categorized into three groups: poor, borderline, or acceptable food consumption.56
Although the FCS can give an idea of the caloric sufficiency of the diet, it does not account for 
micronutrient deficiencies.57
Figure 4 illustrates the mean FCS and percentage of households with poor, borderline, and acceptable FCS 
by RFSA area. Baseline results suggest that most households across the three RFSA areas achieve an 
acceptable food consumption score (Girma, 75.6%; Hamzari, 76.5%; Wadata, 85.9%). Average FCS exceeds 
35 (the standard threshold for acceptable food consumption) in all RFSA areas (Girma, 48.3; Hamzari, 51.5; 
and Wadata, 56.2).
 
54 Available at https://www.usaid.gov/sites/default/files/documents/1867/USG-Global-Food-Security-Strategy-2016.pdf.
55 For additional details refer to the FFP Indicators Handbook Part 1: Indicators for Baseline and Endline Surveys for 
Development Food Security Activities. 
56 Category thresholds: poor (0–21); borderline (21.5–35); and acceptable (>35). 
57 For additional details refer to the FFP Indicators Handbook Part 1: Indicators for Baseline and Endline Surveys for 
Development Food Security Activities. 
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26 Findings
Figure 4: Mean Food Consumption Score and distribution of households by FCS group and RFSA area
The distribution of households by FCS group and mean FCS does not vary by gendered household type in 
any of the RFSA areas, with a few exceptions. In the Hamzari RFSA area, the average FCS of female adult￾only households is lower than that of households with both adult males and females (p < 0.01).58 In the 
Wadata RFSA area, households with adult males and females achieve a higher FCS score on average 
compared to female-adult-only households (p < 0.05) or male-adult-only households (p < 0.01).59 Refer 
to Annex 5 for estimates of mean FCS and the percentage of households with poor, borderline, and 
acceptable FCS by gendered household type. 
Figure 5 illustrates the frequency of consumption of food groups by RFSA area. Households across the 
RFSA areas consume staples almost daily. Pulses are consumed frequently—5 days per week. Intake of 
dairy and animal-based proteins such as beef, lamb, fish, and eggs is infrequent. Intake of fruits and 
vegetables is also rare.60
 
58 Mean FCS does not differ statistically between adult-male-only households and adult-female-only households, or between adult 
male-only households and households with both adult males and females.
59 Mean FCS does not differ statistically between adult-male-only households and adult-female-only households.
60 For additional details on the components of the FCS score refer to Annex 6, Table A6.4.
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Findings 27
Figure 5: Frequency of consumption of food groups, by RFSA area
3.3.1 Relationship Between Crops Harvested and Food Consumption Score
Given that data collection extended into the first week of the harvest period and FCS is expected to be 
higher in the harvest period compared to the lean season, the survey asked farmers in the household 
how much of their crops they had harvested in the current season as a proxy for assessing the impact of 
the timing of the survey on household food consumption. About 80% or more of households in the RFSA
areas harvested some of their crops (see Figure 6). 
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28 Findings
Figure 6: Percent of harvest completed, by RFSA area
Households that harvested at least some of their crops are expected to achieve higher food 
consumption. However, the bivariate analyses results did not indicate a statistically significant 
association between the percent of harvest completed and households’ FCS group or mean FCS in the 
RFSA areas except Girma.61 It is possible that the FCS of households that did not harvest any crops would 
not differ from those that did because food consumed can come from multiple sources other than own 
agricultural production. Households that did not harvest any crops at the time of the survey may have 
received food items from households that harvested their crops, and/or may have purchased food from 
the market. 
3.3.2 Practices Associated with Household Food Security 
Additional bivariate and multivariate analyses were performed to explore the association between FCS 
and intervention-specific factors expected to contribute to household food consumption, e.g., improving
access to credit to invest in productivity-enhancing inputs and adopting improved management 
practices that increase yield and reduce post-harvest loss.
62 This analysis assumes that if a single 
household member participates in a particular practice, e.g., taking agricultural credit, participating in 
group-based savings, or adopting an improved agricultural technology or technique, then the benefits of 
this practice accrue to the household as a whole. Details on the methodology of the bivariate and 
multivariate analyses can be found in Annex 4. 
The results of the bivariate analyses of FCS groups indicated that households that used financial services, 
possessed livestock holdings, and adopted certain targeted improved management practices are more 
likely to achieve an acceptable FCS rather than borderline or poor FCS compared to households that did
 
61 In the Girma RFSA area, the mean FCS score was higher among households that harvested their crops compared to those that 
did not (see Annex 7, Table A7.1b).
62 See Annex 7, Tables A7.1a–A7.1f.
Baseline Study of the RFSAs in Niger: Final Report (Vol. I)
Findings 29
not.
63 Bivariate analyses of the FCS score indicated similar results as well as some additional 
associations.64 The results of the bivariate analyses of household food consumption groups and FCS are 
summarized in Figure 7.
Multivariate analyses were conducted to explore whether intervention-specific factors, such as access to 
financial services or application of improved management practices, may influence FCS while controlling 
for background socio-economic factors and village-specific influences that are unrelated to the RFSA. 
The results of the multivariate analyses show that the FCS increases with the following factors:
65
• Obtaining an agricultural loan (Wadata).
• Participation in agricultural saving schemes (Hamzari).
• Participation in group-based savings programs (Wadata).
• Participation in group-based credit programs (Girma).
• Raising sheep (Hamzari, Wadata).
• Adoption of soil-related fertility enhancing practices—specifically, application of organic manure 
(Girma) and phosphatic manure (Hamzari).
• Crop rotation (Hamzari).
One factor to keep in mind is that the FCS does not consider quantities consumed so food groups with a 
high weight (such as pulses and meat) that are consumed frequently but in small quantities will 
artificially inflate the FCS value. A Tufts University comparative study of various measures of food 
security finds that, after the household hunger scale, FCS is the most likely to overstate food security.66
FCS may be overly sensitive to seasonality or other factors (e.g., prices) that affect food availability and 
accessibility during the period of data collection. 67 While the FCS is a snapshot of a household’s “usual” 
food consumption over the past week and useful for comparisons when data are collected cyclically 
across seasons or years, it typically varies with the agricultural calendar, which itself is subject to 
variation based on weather conditions and trends. Agricultural planning—by farmers and by 
development interventions—seeks to account for this year-round fluctuation that directly affects food 
security over the seasons. The RISE I endline qualitative findings offer a few examples of how farmers 
have sought to optimize their food security even in lean seasons by planning the use of food supplies 
and prioritizing nutrition. One respondent in Maradi explained that they divide their food supplies into 
three parts: one part for household consumption to last until the next agricultural season, one part in 
 
63 See Annex 7, Table A7.1a for details.
64 See Annex 7, Table A7.1b for details.
65 See Annex 7, Tables A7.1c–A7.1f for detailed results of the OLS regression of FCS for the combined RFSA areas and for each 
RFSA area separately. 
66 Maxwell, Daniel, Jennifer Coates, and Bapu Vaitla. 2013. How Do Different Indicators of Household Food Security Compare? 
Empirical Evidence from Tigray. Feinstein International Center, Tufts University: Medford, USA. Available at 
https://fic.tufts.edu/assets/Different-Indicators-of-HFS.pdf. The study found that about 40% of households classified as 
moderately/severely food insecure using HFIAS classification were categorized as having acceptable FCS. Similarly, around 20%
of households classified as moderately/severely food insecure using the CSI classification were found to have acceptable food
consumption using the FCS indicator. 
67 WFP 2008. Food Consumption Analysis: Calculation and Use of the Food Consumption Score in Food Security
Analysis. Available at https://documents.wfp.org/stellent/groups/public/documents/manual_guide_proced/wfp197216.pdf.
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30 Findings
case of need for household consumption during a lean period, and one part reserved for ceremonies. 
Similarly, a respondent in Zinder stated, "The main change at the community level is above all this new 
culture and the awareness that men are learning not to waste too much their food stocks on festive 
ceremonies.”
Figure 7: Summary of statistically significant findings from the bivariate analyses of household food 
consumption score
Note: G = Girma RFSA area; H = Hamzari RFSA area; W = Wadata RFSA area
See Annex 7, Table A7.1a and Table A7.1b for details.
FCS GROUPS
Households are more likely to 
achieve an acceptable FCS than 
borderline or poor if they:
Access to/use of financial services
• Participated in agriculture saving schemes (H)
Livestock holding
•Raised sheep (H)
Adoption of improved agriculture practices
• Applied organic manure (G, H)
• Applied phosphatic manure (H)
• Applied compost (H)
• Stored harvested crops in sealed/airtight 
bags (H) 
• Used agro-chemical grain treatment (W)
Participation in social assistance programs
• Ag trainings/meetings (W)
MEAN FCS SCORE
Mean FCS score was higher among 
households that adopted the following 
practices compared to those that did not:
Access to/use of financial services
• Participated in agriculture saving schemes (G, 
H)
• Participated in community-based savings 
groups (H, W)
• Participated in community-based credit 
groups (G)
Livestock holdings
• Raised goats (W)
• Raised sheep (G, W, H)
• Raised poultry (H)
Adoption of improved ag practices
• Applied organic manure (G, H)
• Applied phosphatic manure (H)
• Applied compost (G, H)
• Applied microdoses of fertilizer (H)
• Controlled for sida cordifolia (G, H)
• Used improved seeds (W)
• Used locally-made storage (G)
• Stored harvest in sealed/airtight bags (H) 
• Used community storage facility (H)
• Used solar/fuel powered dryers (W)
• Used seed/grain treatment (W)
• Used agrochemical grain treatment (H)
• Used triple bags (G, H)
Participation in social assitance programs
• Nutrition trainings/ meetings (W)
• Ag trainings/meetings (W)
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3.4 Agriculture 
The baseline survey collected information on size of farmland, use of financial services, and adoption of 
targeted improved crop, NRM, livestock and post-harvest handling and storage practices for 
commodities of interest. The crops of interest in the RFSA areas are sorghum, millet, cowpeas, and 
peanuts. The livestock of interest are goats, sheep, and poultry. Enumerators interviewed all farmers 
with access to a plot of land over which they make decisions68 and farmers with livestock over which 
they make decisions. In this study, characterizing farmers as having access to a plot of land does not 
require legal ownership of the land.69 Similarly, identifying farmers as having livestock does not require 
that they own the livestock, but they should be able to make decisions about their management or how 
to dispose, store, or sell production. Demographic characteristics of farmers (e.g., age and sex) by 
commodity and RFSA area are provided in Annex 6, Tables A6.5a–A6.5g.
3.4.1 Type of Land Access and Farmland Size
Table 6 illustrates the percent distribution of farmers in the RFSA areas by sex and age. 
Table 6: Sex and age distribution of farmers, by RFSA area (%)
Combined RFSA areas Girma/Catholic 
Relief Services Hamzari/CARE Wadata/Save 
the Children
Sex
Male 51.8 50.4 50.5 57.8
Female 48.2 49.6 49.5 42.2
Total 100.0 100.0 100.0 100.0
Age 
15–29 28.1 29.1 24.8 28.1
30+ 71.9 70.9 75.2 71.9
Total 100.0 100.0 100 100.0
Number of farmers 3,358 1,201 1,329 828
Note: Includes all farmers with access to a plot of land over which they make decisions. Access includes owning, renting, or 
sharecropping the land. 
Baseline results indicate most farmers in the RFSA areas own the farmland they access and have 
decision-making authority over; however, female farmers and younger farmers (15–29 years) are less 
likely to own farmland compared to male farmers and older farmers (30+ years), respectively (see Figure 
 
68 Decisions over a plot of land include what will be grown, how it will be grown, and how to dispose/sell/store the harvest.
69 The survey asked, "Do you own, rent, or sharecrop the land over which you make decisions?" Respondents who answered 
“yes” are considered to have access to land. Respondents who do not own, rent, or sharecrop are not considered to have 
access to a plot of land and are not interviewed. The analysis also uses this response to disaggregate by type of access (i.e., 
access by virtue of owning, renting, or sharecropping); these results are discussed in Sec. 3.4.1. 
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32 Findings
8 and Figure 9). Female farmers and younger farmers are more likely to sharecrop compared to male 
farmers and older farmers, respectively.70
 
70 See Annex 6, Table A6.6a for additional details on land tenure, disaggregated by farmer age and sex by RFSA area.
Baseline Study of the RFSAs in Niger: Final Report (Vol. I)
Findings 33
Figure 8: Type of land access by farmer’s sex, combined RFSA areas
* p < 0.05, ** p < 0.01, *** p < 0.001
Note: Includes all farmers with access to a plot of land over which they make decisions. Access includes owning, renting, or 
sharecropping the land.
Figure 9: Type of land access by farmer’s age, combined RFSA areas
* p < 0.05, ** p < 0.01, *** p < 0.001
Note: Includes all farmers with access to a plot of land over which they make decisions. Access includes owning, renting, or 
sharecropping the land.
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The area of total farmland cultivated is smaller for female farmers than for male farmers (see Figure 10); 
it is also smaller for younger farmers relative to older farmers (see Error! Reference source not found.). 
This pattern is similar in all RFSA areas.
71 The pattern also holds when disaggregating farmland size by 
crop type.72
Figure 10: Area of total farmland cultivated (hectares), by sex of farmer; combined RFSA areas
* p < 0.05, ** p < 0.01, *** p < 0.001
Note: Includes total area of farmland (owned, rented, sharecropped) over which the farmer makes decisions on what will be 
grown, how it will be grown, or how to dispose/store/sell the harvest.
The findings on land ownership from this study differ from others; however, differences in survey 
populations, survey timing, question wording and response options should be considered when 
comparing estimates on a similar topic across multiple data sources.73 For example, a Food and 
 
71 See Annex 5 Table A6.6a for details.
72 See Annex 6, Table A6.6b–A6.6e for disaggregation of results by crop and RFSA area.
73 The Niger ECVM/A and DHS surveys are based on nationally representative samples covering urban and rural areas in all eight 
regions of the country whereas the BHA baseline study is representative of the RFSA areas in Maradi and Zinder. For 
information on land ownership, the ECVM/A collected information on land ownership by asking the household respondent 
whether the household as a whole or one of its members possess agricultural land and subsequently inquired about the tenure 
for each plot of land. The DHS interviewed all women 15–49 years and all men 15–59 years in households selected to 
participate in the survey. The BHA baseline study estimates of land ownership are based on interviews with farmers (aged 15 
years and older) with access to a plot of land over which they make decisions. Given the respondent eligibility criteria used by 
the baseline study, the target population of the baseline study may be more likely to own land compared to the target 
populations on which the ECVM/A or DHS estimates of land ownership are based.
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Findings 35
Agriculture Organization (FAO) working paper using data from the 2011 Niger National Survey on 
Household Living Conditions and Agriculture (ECVM/A), indicates that 63% of men in Niger own land 
compared to 35% of women.74 A World Bank policy paper using data from the 2012 Niger Demographic 
and Health Survey (DHS) shows similar results for land ownership among men (67.3%) and women 
(41.5%) in rural areas.75
The 2020 baseline study estimates of land ownership in the RFSA areas should be interpreted in the 
context of customary land tenure practices in Niger. The 1993 Rural Code aimed to improve land 
security for women and men and give women the right to own and transfer land.76 However, the current 
reality is that rural land in Niger remains largely governed by the “right of the axe” or firstcomer—
namely, the first occupant of the land to clear it for use is given ownership rights and can pass on the 
land.
77 Newcomers are given use rights. In this context, it is helpful to distinguish between self-reported 
ownership and documented ownership;78 the notion of property is rarely formalized by a title or deed,
except in cases where a certificate of sale is established by the customary authorities to attest to the 
change of "owner." Thus, it possible that when asked “Do you own, rent, or sharecrop the land over 
which you make decisions,” that respondents considered themselves the owners of the land because 
they inherited it or because they currently have locally accepted right of use, regardless of possessing a 
formal land title or deed. This could explain the higher-than-expected percentage of farmers reporting 
“ownership” compared to other sources.
3.4.2 Use of Financial Services
Access to financial services enables households to make investments in productivity-enhancing inputs, 
manage risk, and diversify livelihood strategies.79 Financial services include credit (loans), savings 
schemes, and insurance plans provided by formal and informal groups.80 Examples of financial services 
providers include banks, microfinance institutions, farmer associations, savings and loan facilities, Village 
Savings and Loan Associations (VSLAs), and other types of communal social funds. Between one-quarter 
to one-third of farmers in the RFSA areas used any financial services in the 12 months prior to the survey 
(Girma, 36.6%; Hamzari, 23%; Wadata, 25.8%) (See Annex 5). Male farmers are more likely to use any 
financial services compared to female farmers (see 
 
74 Slavchevska, Vanya, Ana Paula de la O Campos, Chiara Brunelli and Cheryl Doss. 2017. “Beyond Ownership: Women’s and 
Men’s Land Rights in Sub-Saharan Africa.” Paper presented at the 2017 Annual (World) Bank Conference on Africa. Rome: Food 
and Agriculture Organization of the United Nations. Available at https://pubdocs.worldbank.org/en/170131495654694482/A2-
ABCA-Slavcheska-et-al-2016-Beyond-ownership-working-paper.pdf. 
75 Gaddis, Isis and Lahoti, Rahul Suresh and Li, Wenjie, Gender Gaps in Property Ownership in Sub-Saharan Africa (August 30, 
2018). World Bank Policy Research Working Paper No. 8573. Available at 
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3246145. 
76 Hughes, Oliver. 2014. “Literature Review of Land Tenure in Niger, Burkina Faso, and Mali: Context and Opportunities.” Available 
at https://www.crs.org/sites/default/files/tools-research/literature-review-of-land-tenure-in-niger-burkina-faso-mali.pdf. 
77 Hughes 2014. 
78 Slavchevska et al 2017.
79 For additional details refer to the FFP Indicators Handbook Part I. 
80 Ibid. 
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36 Findings
Figure 11).
81
 
81 Annex 6, Table A6.7 provides additional details on use of financial services in the RFSA areas.
Baseline Study of the RFSAs in Niger: Final Report (Vol. I)
Findings 37
Figure 11: Use of any financial services, by sex of farmer and RFSA area
The RISE I endline study pointed out that community-based savings schemes, and education about the 
function and use of savings, are not only widely promoted, but in Niger build on the indigenous savings 
culture of tontine groups, which were found in control villages without RISE interventions. These 
antecedents may help explain the use of financial services in the current study. Nevertheless, and 
despite RISE partners’ targeting of women for financial services activities, the use of financial services in 
the current study is fairly low, especially for women. 
This study finds that use of agricultural savings schemes does not differ by the sex of the farmer (see 
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38 Findings
Figure 12); however, male farmers are more likely to take out an agricultural loan compared to female 
farmers. About 1% or less of farmers take out agricultural insurance plans to mitigate risks. 
The RISE endline qualitative study uncovered a couple of issues that may discourage and create access 
barriers to using financial services, including high interest rates for loans, as related by one respondent in 
Zinder:
“For the operation of the fund: in the beginning there were 17 people, each paying 225F per week. The 
fund was then open only after six months, to distribute the money with the members. Some used it for 
income-generating activities like processing peanuts or selling patties. But now, there are seven 
members who have left because of the interest issue on the loans…the group can give credit to a person 
who wants it but if she wants 5,000F we will give her 4,500F and 500F will be interest. People in the 
village said that they perceived illegality with the interest, so we had to stop charging it, which has 
caused a lot of women to quit.”
Another concerning trend noted in the RISE I endline qualitative study was households’ use of land as 
collateral for loans, which was found to be a common practice and especially high risk for households 
with small plots (e.g., less than half a hectare). 
Baseline Study of the RFSAs in Niger: Final Report (Vol. I)
Findings 39
Figure 12: Use of agricultural credit and savings schemes, by sex of farmer and RFSA area
3.4.3 Use of Improved Post-Harvest Handling and Storage Practices
Use of improved post-harvest handling and storage practices can help minimize post-harvest losses due 
to pests (insects, rodents), microorganisms (molds), or chemical alterations within grains due to 
environmental factors such as temperature and humidity.82 The definition of “improved storage 
practice” is based on input from IPs and not all improved practices were considered (e.g., control for 
temperature, control for humidity, or design modifications to traditional storage practices). Program 
investments and design decisions for post-harvest storage programs should be based on a crop-by-crop 
assessment of drivers of loss.
A total of 27.5% of farmers in the Girma RFSA area, 58.3% in the Hamzari RFSA area, and 43.2% in the 
Wadata RFSA area used improved storage.
83 Male farmers are more likely to use at least one improved 
storage practice compared to female farmers. Annex 5 provides details on the percentage of farmers using 
at least one improved storage practice. Locally made storage structures such as metal silos are the most 
commonly used type of improved post-harvest storage practice, followed by sealed/airtight bags. More 
than one-third of sorghum and millet farmers in the Hamzari and Wadata RFSA areas use locally made 
storage structures. In the Hamzari RFSA area, sealed/airtight bags are used by more than one-quarter of 
cowpea farmers and greater than one-third of peanut farmers. In general, use of improved storage 
practices does not differ by farmer’s sex or age, with a few exceptions.
84
 
82 See FAO definition of post-harvest losses. Available at http://www.fao.org/3/t0522e/T0522E04.htm. Definitions of improved 
targeted post-harvest and storage practices are provided in Annex 4.
83 See Annex 4 for the list and definitions of improved post-harvest handling and storage practices promoted by the RFSAs.
84 See Annex 6, Tables A6.8a – A6.8d for details on use of post-harvest practices, disaggregated by crop and RFSA area.
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40 Findings
3.4.4 Use of Improved Crop Practices
The baseline survey collected information on the use of improved crop and NRM practices or 
technologies promoted by the RFSAs to increase agricultural productivity and support more resilient and 
better-functioning systems.85 The adoption of targeted improved crop practices follows a similar pattern 
across the four crops of interest in the RFSA areas (see Error! Reference source not found.).
86 The 
subsequent sections discuss the use of targeted improved crop practices in more detail.
Table 7: Heat map of adoption of targeted improved crop practices and technologies, by RFSA area 
and crop
Girma Hamzari Wadata
So Mi C P So Mi C P So Mi C P
Crop genetics Use of improved seeds L L L L S S S S L L L L
Cultural practices 
Control of sida cordifolia S S S S S S M M L L L L
Crop association W W W W W W W W M M M S
Crop rotation L L L L L L L L L L L L
Sowing after first useful 
rains
M M M M W W W W S M M M
Natural resources or 
ecosystem
management
Farmer managed natural 
regeneration (FMNR) W W W W S S S S M M M W
Animal corridors/pasture 
areas
W M M W M M M M M M M W
Pond protection L L L L L L L L L L L M
Community conflict mgmt L L L L L L L L L L L L
Pest and disease 
management
Delay seedlings (3rd/4th
rains) L L L S L L S L L L L L
Seed treatment 
w/fungicides L L L L S S S S L L L L
Soil-related fertility 
and conservation 
Zai pits L L L L S S S S L L L L
Organic manure W W W W W W W W W W W W
Phosphatic manure L L L L L S S S L L L L
Compost M M M M M M M M L L L L
Micro-doses of fertilizer L L L L L L L L L L L L
Agriculture water 
mgmt. non￾irrigation
Agricultural half-moons L L L L L L L L L L L L
Climate adaptation/
risk mgmt
Use of climate 
information L L L L L L L L L L L L
Other practices Performing 3+ weedings M M M M M M W W L S S L
Note: So = sorghum; Mi = millet; C = cowpeas; P = peanuts
W Wide application 
(~50% or more) M Moderate application 
(~20–49%) S Some application 
(~11–19%) L Low/no application 
(~10% or less)
 
85 Definitions of these practices are provided in Annex 4.
86 Annex 5 provides sampling statistics for the percentage of farmers using improved practices, disaggregated by type and crop.
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Findings 41
The baseline survey results indicate the following overarching findings for the use of crop and NRM 
practices:
• Crop association (i.e., intercropping) and sowing after first useful rains are the most popular 
targeted improved cultural practices; adoption rates range between moderate (about 20% to 49%) 
to widespread (about 50% or more). 
• Within the suite of soil-fertility related conservation practices, application of organic manure is 
widespread, followed by compost. 
• FMNR and the delimitation of animal corridors and pasture areas are the leading improved NRM 
practices and are used by a moderate percentage of farmers. 
• Less than 10% of farmers use improved seed varieties that are high yielding, drought-tolerant, or 
disease-resistant.87
• Farmers in the RFSA areas rarely use targeted pest and disease management practices, non￾irrigation-based agricultural water practices, or climate adaptation and risk mitigation practices; 
less than 10% use any of these practices. 
• Other infrequently applied targeted practices include crop rotation, pond protection, and 
functional community-based conflict management. 
Sorghum
A total of 2,203 sorghum farmers were interviewed for the baseline study. Most are male and between 
the ages of 25–54 years, although close to 20% are 60 years and older. See 
 
87 Farmer recall is likely to understate access to improved seed (i.e., varieties originating from agricultural research) as farmers 
often confound long-held improved seed (varieties originating from agricultural research) with traditional land races.
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Table 8 for the percentage distribution of sorghum farmers by sex and age in the RFSA areas. 
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Findings 43
Table 8: Distribution of sorghum farmers by sex and age in the RFSA areas, Niger (%)
Combined RFSA areas Girma Hamzari Wadata
Sex
Male 65.5 64.0 68.6 67.3
Female 34.5 36.0 31.4 32.7
Total 100.0 100.0 100.0 100.0
Age
15–19 3.5 3.3 3.3 4.5
20–24 7.5 7.5 4.7 10.2
25–29 10.4 10.8 8.6 10.5
30–34 12.8 14.5 10.4 9.6
35–39 13.2 12.2 16.5 13.7
40–44 13.2 13.4 12.6 13.0
45–49 7.2 6.2 10.2 7.9
50–54 10.1 11.0 9.4 8.0
55–59 5.0 4.5 7.5 4.3
60+ 17.0 16.6 16.8 18.3
Total 100.0 100.0 100.0 100.0
Number of sorghum 
farmers 2,203 785 822 596
Figure 13 illustrates the use of improved crop and NRM practices among sorghum farmers by RFSA area. 
Use of improved practices among sorghum farmers generally does not differ statistically by farmer sex 
or age, with a few exceptions.88
 
88 See Annex 6, Table A6.9a for details.
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Figure 13: Sorghum farmers adopting targeted improved crop practices, by RFSA area (%)
Note: Results are presented for practices used by five% or more of farmers. See Annex 6, Table A6.9a for details, including 
disaggregation by age and sex.
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Findings 45
Millet
A total of 2,663 millet farmers were interviewed for the baseline study. Table 9 illustrates the percent
distribution of millet farmers by sex and age in the RFSA areas. About two-thirds of farmers engaged in 
millet production are male and most are 25–54 years old; close to 15% are 60 years and older.
Table 9: Distribution of millet farmers by sex and age in the RFSA areas, Niger (%)
Combined RFSA areas Girma Hamzari Wadata
Sex
Male 61.2 59.1 64.5 65.1
Female 38.8 40.9 35.5 34.9
Total 100.0 100.0 100.0 100.0
Age
15–19 4.4 4.9 2.8 4.4
20–24 8.4 9.2 4.6 9.5
25–29 11.5 11.6 10.8 11.9
30–34 12.9 14.5 11.2 9.2
35–39 12.9 11.3 16.9 14.3
40–44 12.9 12.7 13.4 13.3
45–49 7.2 6.3 9.5 7.8
50–54 10.1 11.1 9.0 8.0
55–59 4.4 3.9 6.4 4.3
60+ 15.3 14.6 15.4 17.2
Total 100.0 100.0 100.0 100.0
Number of millet farmers 2,663 968 1,018 677
Figure 14 illustrates the use of improved practices among millet farmers in each of the RFSA areas. Use 
of improved practices among millet farmers generally does not differ statistically by farmer sex or age, 
with a few exceptions.89
 
89 See Annex 6, Table A6.9b for details.
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Figure 14: Millet farmers adopting targeted improved crop practices, by RFSA area (%)
Note: Results are presented for practices used by five% or more of farmers. See Annex 6, Table A6.9b for details, including 
disaggregation by age and sex.
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Findings 47
Cowpeas
A total of 2,582 cowpea farmers were interviewed for the baseline study. The sex and age distribution of 
cowpea farmers resembles that of sorghum and millet producers; about two-thirds or more are male,
and most are aged 25–54 years (see Table 10).
Table 10: Distribution of cowpea farmers by sex and age in the RFSA areas, Niger (%)
Combined RFSA areas Girma Hamzari Wadata
Sex
Male 61.3 59.4 67.2 62.5
Female 38.7 40.6 32.8 37.5
Total 100.0 100.0 100.0 100.0
Age
15–19 5.1 5.6 2.7 5.4
20–24 9.1 9.7 4.7 10.6
25–29 11.1 11.2 10.0 11.7
30–34 12.9 14.3 11.0 9.7
35–39 12.8 11.5 17 13.5
40–44 12.7 12.4 13.6 13
45–49 7.1 6.2 9.7 7.7
50–54 10.0 10.9 9.2 7.7
55–59 4.5 3.9 7.1 4.3
60+ 14.9 14.4 15 16.3
Total 100.0 100.0 100.0 100.0
Number of cowpea farmers 2,582 961 909 712
Figure 15 illustrates the percentage of cowpea farmers using improved practices, by RFSA area. Use of 
targeted improved practices by cowpea farmers generally does not differ statistically by farmer sex or 
age, with a few exceptions.90
 
90 See Annex 6, Table A6.9c for details. 
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Figure 15: Cowpea farmers adopting targeted improved crop practices, by RFSA area (%)
Note: Results are presented for practices used by five% or more of farmers. See Annex 6, Table A6.9c for details, including 
disaggregation by age and sex.
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Findings 49
Peanuts 
A total of 1,132 peanut farmers were interviewed for the baseline study. Table 11 illustrates the age and 
sex distribution of peanut farmers by RFSA area. Between one-third to one-half of peanut farmers in the 
Girma and Hamzari RFSA areas are female. The overwhelming majority of peanut farmers in the Wadata 
RFSA area are male. 
Table 11: Distribution of peanut farmers by sex and age in the RFSA areas, Niger (%)
Combined RFSA areas Girma Hamzari Wadata
Sex
Male 67.6 63.0 74.1 92.0
Female 32.4 37.0 25.9 8.0
Total 100.0 100.0 100.0 100.0
Age
15–19 3.3 4.0 2.2 0.8
20–24 6.7 8.3 3.2 1.6
25–29 9.1 10.0 7.1 7.4
30–34 13.1 14.5 10.0 9.5
35–39 12.7 11.6 16.5 12.2
40–44 14.3 14.4 13.7 15.0
45–49 8.0 6.4 11.2 13.7
50–54 10.4 10.3 9.8 12.8
55–59 4.9 4.2 8.1 2.3
60+ 17.4 16.4 18.2 24.6
Total 100.0 100.0 100.0 100.0
Number of peanut farmers 1,132 444 571 117
Figure 16 illustrates the percentage of peanut farmers using improved practices by RFSA area. Use of 
improved practices among peanut farmers generally does not differ statistically by farmer sex or age,
with a few exceptions.91
 
91 See Annex 6, Table A6.9d for details. 
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50 Findings
Figure 16: Peanut farmers adopting targeted improved crop practices, by RFSA area (%)
Note: Results are presented for practices used by five% or more of farmers. See Annex 6, Table A6.9d for details, including 
disaggregation by age and sex.
Baseline Study of the RFSAs in Niger: Final Report (Vol. I)
Findings 51
3.4.5 Use of Improved Livestock Practices
A total of 1,316 goat farmers, 523 sheep farmers, and 547 poultry farmers were interviewed for the 
baseline study. In the Girma RFSA area, close to two-thirds of goat farmers are female and under one￾half of sheep and poultry farmers are female. In the Hamzari RFSA area, female farmers account for
three-quarters of goat farmers, two-thirds of sheep farmers, and one-third of poultry farmers. Between 
one-third to one-half of goat, sheep, and livestock farmers in the Wadata RFSA area are female. See 
Table 12 for details on the percent distribution of goat, sheep, and poultry farmers by age and sex.
Table 12: Sex and age distribution of goat, sheep, and poultry farmers by RFSA area, Niger(%)
Combined RFSA Areas Girma Hamzari Wadata
Goat Sheep Poultry Goat Sheep Poultry Goat Sheep Poultry Goat Sheep Poultry
Sex
Male 36.4 54.4 59.3 36.7 56.2 54.8 21.2 38.2 65.5 54.6 68.2 68.6
Female 63.6 45.6 40.7 63.3 43.8 45.2 78.8 61.8 34.5 45.4 31.8 31.4
Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0
Age
15–19 4.3 2.9 4.1 4.2 3.0 3.7 7.2 3.5 7.5 0.9 2.1 3.1
20–24 9.7 7.2 11.4 10.3 7.9 14.0 10.3 4.7 6.3 5.7 7.7 6.9
25–29 14.7 13.1 8.0 14.5 13.7 8.1 17.3 12.6 3.8 12.0 11.4 10.6
30–34 16.8 15.6 15.7 18.8 16.7 16.9 15.9 13.9 15.9 8.6 13.3 11.9
35–39 10.7 12.6 12.9 9.6 9.8 10.9 13.2 20.5 16.7 12.5 14.1 16.2
40–44 13.0 15.0 13.4 12.8 15.5 12.8 11.1 17.8 14.5 16.4 9.5 14.4
45–49 5.5 6.6 6.5 4.9 5.9 5.8 5.2 8.5 7.9 8.4 7.0 7.7
50–54 9.3 10.7 9.4 10.0 12.9 11.3 7.4 3.5 5.0 8.6 11.1 6.6
55–59 3.7 5.0 5.5 3.5 4.8 5.6 4.1 5.8 9.0 3.7 4.8 2.9
60+ 12.4 11.1 13.1 11.4 9.9 11.0 8.1 9.1 13.4 23.2 19.0 19.6
Total 100.0 100.0 100 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100
Number 
of 
farmers
1,316 523 547 526 197 223 530 215 178 260 111 146
Table 13 and Table 14 provide “heat maps” illustrating the extent of adoption of targeted improved 
livestock practices in the RFSA areas.92
 
92 Definitions of these practices are provided in Annex 4. Refer to Annex 5 for sampling statistics for the percentage of farmers 
using improved livestock practices, disaggregated by commodity.
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Table 13: Heat map of adoption of targeted improved livestock practices and technologies – goats and 
sheep, by RFSA area
Girma Hamzari Wadata
Goats Sheep Goats Sheep Goats Sheep
Antiparasitic treatments M M M M M M
Vaccinations M M M W S M
Improved fodder production S S L L L L
Use of licking and/or multi-nutritional block L L L L L L
Animal selection S S L L L L
Use of para-veterinary services L S L L L L
Veterinary monitoring of food quality and quantity over time L L L L L L
Weight monitoring L L L L L L
Optimum weight-market price criteria for the sale decision L L L L L L
W Wide application 
(~50% or more) M Moderate application 
(~20–49%) S Some application 
(~11–19%) L Low/no application 
(~10% or less)
Table 14: Heat map illustrating adoption of targeted improved livestock practices and technologies –
poultry, by RFSA area
Girma Hamzari Wadata
Vaccinations S M L
Use of improved poultry variety/breed S L L
Use of improved shelters L S L
Use of veterinary products and services L S L
Use of improved feed L L L
W Wide application 
(~50% or more) M Moderate application 
(~20–49%) S Some application 
(~11–19%) L Low/no application 
(~10% or less)
Antiparasitic treatments and vaccinations are the most-used targeted improved practices (see
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Findings 53
Figure 17). Relatively few goat or sheepherders use animal selection, improved fodder production, licking 
and multi-nutritional blocks or paraveterinary services. Relatively low percentages of farmers (Girma, 
9.8%; Hamzari, 15.5%; Wadata, 5.9%) use or consult public or government animal workers for veterinary 
services such as prevention or treatment of livestock disease, production, artificial insemination, or 
products such as antibiotics and vitamins. About 10% or less of the poultry farmers use improved poultry 
breeds, improved feed, or improved shelters. There are generally no statistically significant differences by 
farmers’ sex or age in the application of targeted improved livestock practices.93
 
93 See Annex 6, Tables A6.10a, A6.10b and A6.10c for details.
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Figure 17: Farmers adopting targeted improved livestock practices, by livestock type and RFSA area 
and percent
Notes: Results are presented for practices used by five% or more of farmers. 
Baseline Study of the RFSAs in Niger: Final Report (Vol. I)
Findings 55
3.4.6 Factors Affecting Adoption of Improved Practices
Use of financial services is expected to contribute to the adoption of improved agricultural practices, 
particularly those practices that require cash for the purchase of inputs such as fertilizer, improved 
seeds, equipment, and feed, or cash for the payment of services such as labor or veterinary services. 
Table 15 and Table 16 summarize targeted improved agricultural practices that are more likely to be 
applied by farmers using a financial service compared to those who are not, by RFSA area and 
commodity.94
There is some evidence that obtaining agricultural credit or participating in agricultural saving schemes 
is associated with a higher likelihood of farmers adopting improved practices that require cash inputs. 
For example, farmers who took out agricultural credit were more likely to:
• Use improved seeds (Hamzari – sorghum, millet, cowpeas, and peanuts; Wadata – millet).
• Apply phosphatic manure or micro-doses of fertilizer (Hamzari – millet, cowpeas, and peanuts).
• Treat grains with agro-chemicals (Hamzari – cowpeas).
• Store grains in community facilities or warehouses (Girma – peanuts; Hamzari – millet; Wadata –
millet).
• Preserve harvested grains in sealed/airtight bags (Hamzari – cowpeas and peanuts; Wadata –
cowpeas).
• Use triple bags to store grains (Hamzari – millet, cowpeas, and peanuts).
• Use improved poultry varieties (Girma).
• Use licking and/or multi-nutritional blocks (Hamzari – goats and sheep).
• Use paraveterinary services (Hamzari – goats and sheep) and veterinary products (Girma –
poultry).
The baseline survey results also show positive and statistically significant associations between the use 
of agriculture-related financial services and the adoption of improved practices that do not necessarily 
require cash inputs (e.g., applying organic manure, sowing after first useful rains, performing at least 
three weedings, and controlling for sida cordifolia growth). This suggests that underlying factors 
associated with the use of financial services may also be contributing to the adoption of improved 
agricultural practices. For example, farmers that participated in agricultural saving schemes or who 
borrowed agricultural credit may have participated in agricultural trainings or meetings where they 
gained exposure to those practices.
 
94 See Annex 7, Tables A7.2–A7.8 for additional details.
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Table 15: Targeted improved crop and post-harvest practices more likely to be applied by farmers 
using a financial service than farmers who are not, by RFSA area and commodity
Obtained 
agri-credit
Participated in agri￾saving schemes
Crop genetics 
Use of improved seeds H (S, M, C, P)
W (M)
W (M)
Cultural practices/technologies
Control of sida cordifolia growth H (P) G (S, C, P)
Crop rotation H (M, C, P)
Sowing after useful rains W (S, M)
H (M, C)
Improved natural resources or ecosystem management 
Delimitation of animal corridors/pasture areas W (S, M) H (M, C, P)
Protection of ponds against silting up W (S, M) W (S, M)
Improved pest and disease management 
Delay of seedlings until third or fourth rains W (S)
Seed treatment with fungicides W (M)
Improved soil-related fertility and conservation
Zai pits G (P)
Organic manure G (P)
W (M)
G (S, M, C, P)
Phosphatic manure H (M, C, P) G (S, M, C, P)
Compost H (P)
Micro-doses of fertilizer H (M, C, P) H (S)
Improved agriculture water management non-irrigation-based 
Agricultural half-moons W (M, C, P)
Improved climate adaptation/climate risk management 
Use of climate information G (C)
Other improved practices/technologies
Performing at least three weedings H (M, C)
Improved post-harvest handling and storage 
Grain treatment with agro-chemicals H (C) G (S)
W (C)
Use of solar or fuel-powered dryers to reduce post-harvest moisture G (S)
Sealed/airtight bags H (C, P)
W (C)
H (S, M)
Triple bags H (M, C, P) G (M)
Community storage facilities, including warehouse receipting G (P)
H (M)
W (M)
H (S, M, P)
Locally made storage structures such as sheet metal silos H (P)
Seed or grain treatment techniques (e.g., botanical pest control 
agents or phytosanitary irradiation)
H (M)
Notes: G = Girma RFSA area; H = Hamzari RFSA area; W = Wadata RFSA area
S = sorghum; M = millet; C = cowpeas; P = peanuts
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Findings 57
Table 16: Targeted improved livestock practices more likely to be applied by farmers using a financial 
service than farmers who are not, by RFSA and commodity
Obtained 
agri-credit
Participated in agri￾saving schemes
Improved livestock practices – goats and sheep
Improved fodder production H (Go, Sh) G (Go, Sh)
H (Go, Sh)
Use of licking and/or multi-nutritional block H (Go, Sh) H (Go, Sh)
Animal selection G (Go, Sh)
H (Go, Sh)
Veterinary monitoring of food quality and quantity over time H (Go, Sh)
Weight monitoring H (Go, Sh) W (Go, Sh)
Optimum weight-market price criteria for the sale decision H (Go, Sh) H (Go, Sh)
Use of para-veterinary services for goats and sheep H (Go, Sh) H (Go, Sh)
Improved livestock practices – poultry
Improved poultry variety/breed G H
Improved feed (poultry) W
Use of veterinary products G
Notes: G = Girma RFSA area; H = Hamzari RFSA area; W = Wadata RFSA area
Go = Goats; Sh = Sheep
The qualitative component of the RISE I endline study provides some insights into factors that contribute 
to the adoption of improved agricultural practices in Niger; these factors are discussed in turn, below.
Demonstrated results. A strong theme in the RISE I endline qualitative findings was that farmers and 
livestock producers were motivated to adopt new practices when they were tested against existing 
techniques and the differences in results were observable. As one respondent in Maradi stated, people 
are always skeptical of replacing ancestral techniques with new ones, so they try the new methods in 
one part of their fields while continuing the old methods in another. Several RISE I participants noted 
the increase in yield after applying project-promoted techniques (including using improved seed 
varieties) and attributed the improvement to the new techniques, giving quantified examples of their 
yields over time with the application of new methods. The good results were particularly valued by 
farmers with small plots who were able to improve yields. The following account from Maradi captures 
how RISE I training methodology was effectively applied:
“They conducted training courses during which they specified the different varieties of millet and 
cowpea, the technique of producing pesticides to fight against crop pests, compost production, and 
fertilizer storage techniques. Then we moved on to experimenting with the techniques we learned. The 
first year we experimented with the HKP millet variety that we tried on four fields. First, we cleared the 
fields, then came the seeds. After 3 weeks we ploughed the fields and every week we went around with 
the trainer; we measured the evolution of the seedlings and counted them. 
The four fields are differentiated by the type of fertilizer used. In the first field we used organic fertilizer. 
In the second we used chemical fertilizer, in the third at the beginning we put organic fertilizer and after 
the hoeing we added chemical fertilizer. And finally, in the fourth field we did not put fertilizer. This 
experiment allowed us to see for ourselves the method that has more yield. And it turned out to be the 
third, where we used both types of fertilizer in the same field.
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58 Findings
In the second year, we experimented with the IT89, IT90 and KBX varieties of cowpea. And it turned out 
that after the harvest, we preferred to resume our traditional seed variety (“fitila”) because it was more 
profitable than the three experienced.”
The RISE I endline qualitative data also provided support for the power of demonstrating results in 
livestock production; for example, one participant noted that after applying new animal husbandry 
techniques, his sheep fattened in significantly less time than usual and fetched a high price in the 
market. Another noted “remarkable change in livestock production due to fodder…there are times when 
it is difficult to find hay for our livestock, but after the project we prepare rich food for them that we 
keep for difficult times.” These findings lend more support for the teaching technique of introducing 
new practices on a trial basis, allowing producers to see results for themselves and make future choices 
based on their own experiences.
Indeed, the RISE I endline qualitative findings underline that the centrality of experimentation is 
crucial—also because it allows farmers to spread risk, which is especially important for smallholders. As 
a respondent in Zinder stated, “Since the beginning of the project activities, I have always divided my 
field into three parts to cultivate three different varieties. That way I take less risk when one of the 
strains isn't working.” Similarly, another stated that while improved seeds were attacked by caterpillars, 
the traditional seeds were not touched.
Another advantage of demonstrating results in the field is that the results are visible to all farmers, not 
only those who participated in sensitization trainings, as one farmer in Zinder pointed out. A few 
respondents in the RISE I endline gave examples of how non-project participants sought advice from 
participating farmers who had successful plots demonstrating project-promoted techniques such as zai
pits. 
A further appeal of field demonstration may also lie in the communal nature of the work; as one 
respondent in Maradi stated, when their group goes to the field to work their land in joy and good 
humor, they make others envious and want to join their group. Moreover, there can be a positive aspect 
of competition between farmers in applying what they learn, according to a Maradi respondent: “In 
terms of change, at the community level, many people continue to apply the production techniques 
they have learned to build their productive capacities and systems. Through the application of 
techniques, they observe for themselves the differences that allow them to increase production. There 
is competition between producers at this level. For example, if you operate by applying the 200 m2
technique, another will take the initiative to operate 400 m2
.”
It bears noting that not all trials are successful: unintended results may also be demonstrated, and this 
also influences people’s willingness to adopt a new technique. The RISE I endline presented an example 
where a women’s group in Zinder experimented on their fields with different fertilizer treatments and 
trials of donated seeds of millet, cowpea, and peanuts. One of their conclusions related to cowpea: they 
stated that they prefer the traditional variety because the variety made available by project had not 
produced well. This re-emphasizes the power of demonstration to forming opinions while also 
highlighting the importance of testing the effectiveness of different techniques or inputs in different 
contexts, and monitoring implementation to optimize results. 
Complementarity of techniques. Building on the observation above, that observable results have a 
strong influence on adoption (or non-adoption) of promoted techniques, the qualitative data from the 
Baseline Study of the RFSAs in Niger: Final Report (Vol. I)
Findings 59
RISE I baseline study suggest that participants took notice of enhanced effectiveness when certain 
techniques are applied together. Respondents highlighted results of using zai pits and composting 
together, for example: “Composting… consists of an assimilation of natural elements, which allow the 
farmer in record time to produce fertilizer (especially during the seventh month). There are zai at this 
level that complement the composting techniques for improving agricultural production.” Another 
frequently mentioned combination was plant spacing and plant row arrangement techniques, applied 
together in order to efficiently exploit the arable space but also to concentrate the application of 
fertilizer close to the plant.
Access to inputs. The RISE I project provided chemical fertilizer, and its use was common among RISE I 
participants, but the sustainability of access to fertilizers was raised as a challenge in the 2017 summative 
evaluation of RISE. As stated by a respondent in Maradi, “…the new techniques… strengthen our 
productive capacity … [which is] … a clear evolution. But the problem with modernity lies in the fact that 
the producer has to obtain certain agricultural inputs (fertilizers that are either unavailable at times of 
need, or inaccessible to the majority of small producers).” Access to and affordability of inputs to 
smallholder farmers may explain the low adoption rates for micro-dosing of fertilizer shown in Error! 
Reference source not found..
Veterinary services. As shown in the heat maps (Table 13 and Table 14), use of veterinary services and 
products was low for all types of livestock (with the exception of poultry in the Hamzari RFSA area). The 
qualitative findings of the RISE I endline suggest that while that project included para-veterinary services 
and education regarding animal vaccination, consistent technical support for managing animal health 
was a challenge both during the project and as a permanent service. Challenges to using these services 
included lack of veterinarians, not calling on the veterinary service in time to save the animal, 
perceptions that vaccinations cause livestock disease, and inaccessibility or high price of veterinary 
products. COVID-19 exacerbated some of these challenges: for example, containment protocols made it 
difficult to access vaccinations and drove up prices. Moreover, a respondent in Maradi pointed out that 
vaccination was deprioritized because people were forced to sell or slaughter their livestock: “…You can 
think of other things only when you manage to eat well to satisfy your hunger. Vaccinations were 
available, but there were no livestock to be vaccinated.”
Habbanaye. The RISE I endline qualitative findings suggest that blending project interventions with the 
indigenous practice of habbanaye contributes to the success of those interventions. The habbanaye
system traditionally consists of lending an adult female sheep, goat, or cow to a villager in need; when that 
animal gives birth, the adult animal is returned while the villager keeps the lamb, kid, or calf. Working with 
this indigenous practice helps emphasize local ownership of development and is an opportunity for 
introducing new animal husbandry and rearing practices in a culturally sensitive way. With the growing 
influence of RISE projects, habbanaye started to become intertwined with agriculture and income￾generating activities, and, as stated by a respondent in Maradi, “…reinforce women already united in 
groups. The animals circulate between the different members. With the activities, there are seven groups 
today compared to two groups 7 years ago. There is active participation in the extraction of peanut oil, and 
reinforcements of small [income] activities.” Moreover, habbanaye was noted several times by RISE I 
endline informants as contributing to women’s earning power, which in turn raises the woman’s status in 
contributing to household income and decision-making. For example, a Maradi respondent stated, 
“Women's roles have changed markedly through changing their economic power through the feeding and 
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60 Findings
fattening of animals, as they have the capacity to increase an animal’s value from 10,000F to 30,000F or 
more.” RISE I endline respondents viewed the greater availability of sheep and goats in the community as 
beneficial in itself and felt this was leading to more competition in buying and selling. They also saw its 
contribution in expanding value chains such as milk and dairy products, raising awareness of potential new 
customers, and contributing to social cohesion. Building on the habbanaye practice also favors 
sustainability, as women’s groups were noted to continue sharing livestock and ultimately all members 
would have their own animals—and thus, income sources—a desirable outcome. 
Another indigenous structure that bears noting is the tontine, a traditional savings group. While the RISE 
I endline study did not specifically detail how project interventions were integrated with tontines, given 
the success with habbanaye, it may be assumed that working closely with these existing groups would 
contribute to positive outcomes and sustainability. Testament to this is that tontines were found to exist 
even in control villages without RISE I interventions.
3.5 Water, Sanitation, and Hygiene
Household access to and use of basic water and sanitation facilities coupled with the adoption of proper 
hygiene practices, such as handwashing with water and soap (or ash) at critical moments, can help 
reduce the spread of waterborne illnesses such as diarrhea and other diseases among all household 
members, especially children under 5 years.
95 This section describes household access to WASH 
facilities.96 While the indicators discussed provide a robust measure of access to basic facilities, they do 
not measure actual use of those facilities.
3.5.1 Drinking Water Source
FFP defines basic drinking water services as improved sources or delivery points97 that fulfill the 
following criteria: 
• Protected from fecal contamination;
• Collection time is 30 minutes or less (round-trip including wait time); 
• Consistently produce (i.e., year-round) 20 liters per person per day of basic drinking water; and
• No interruptions in service in the 2 weeks prior to data collection.
Because the survey did not collect information on year-round water access, the official indicator for 
access to a basic water source cannot be calculated. Instead, the percentage of households whose water 
source meets all other criteria (i.e., improved source, 30-minutes-or-less round trip, production of at 
least 20 liters per person per day, and no interruptions in the last 2 weeks) was calculated. 
 
95 For additional details refer to the FFP Indicators Handbook Part 1. 
96 Annex 6, Table A6.11 provides details on household WASH practices, disaggregated by RFSA area.
97 Improved sources of drinking water include piped water into dwelling, piped water into yard/plot, piped to neighbor, public 
tap/standpipe, tubewell or borehole, protected well, protected spring, rainwater, tanker truck, cart with small tank, and bottled 
water. Unimproved sources are unprotected well, unprotected spring, and surface water. Refer to the FFP Indicators Handbook 
Part 1.
Baseline Study of the RFSAs in Niger: Final Report (Vol. I)
Findings 61
As illustrated in 
Figure 18, an improved drinking water source is available to most households in the Girma (79.2%) and 
Hamzari RFSA areas (83.2%) and a little over one-half in the Wadata RFSA area (54.1%). The most 
common improved source of drinking water in the Girma RFSA area is a tubewell or borehole (45.7%), 
protected well in the Hamzari RFSA area (38.6%), and public standpipe in the Wadata RFSA area. Public 
taps and standpipes were the second-most common type of improved drinking water sources in the
Girma (28.7%) and Hamzari (34.3%) RFSA areas. Indeed, drilling wells was mentioned by a few 
participants in the RISE I endline, though it was understood that water supply interventions were in a 
limited number of communities; various respondents expressed a need for more interventions of this 
nature.
Most households can access a water source in 30 minutes or less round-trip (Girma, 80.8%; Hamzari, 
63.4%; Wadata, 65.1%). However, for many households those sources do not produce the daily 
minimum requirement to meet their drinking, sanitation, and hygiene needs. Household access to a 
water source that produces at least 20 liters per person per day is 59.6% in the Girma RFSA area and 
60.5 and 50.4% in the Hamzari and Wadata RFSA areas, respectively. 
The analysis indicates that few households have access to a drinking water source that meet all four 
criteria collected by the baseline survey (Girma, 22.7%; Hamzari, 30.8%, Wadata, 11.1%). Few 
households do anything to make their water safer to drink (Girma, 28%; Hamzari, 20.9%; Wadata, 
20%).98
 
98 Household respondents were asked "Do you do anything to the water to make it safer to drink?" Possible response options 
are “yes,” “no,” and “don't know.” Households were not asked about the technique used to make water safer to drink (e.g., 
boiling, chlorination, etc.). Therefore, conclusions on the use of correct treatment methods cannot be made. 
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62 Findings
Figure 18: Household drinking water source facility, by RFSA area
3.5.2 Sanitation Facility 
According to the World Health Organization (WHO)/United Nations Children’s Fund Joint Monitoring 
Program, a “basic sanitation facility” must meet two conditions: 1) it is an “improved sanitation facility” 
(i.e., hygienically separate excreta from human contact)99 and 2) it is not shared with other households. 
As shown in Figure 19, access to a basic sanitation facility is low across the RFSA areas (Girma, 4.5%; 
Hamzari, 13%; Wadata, 4.4%).100 A small percentage of households have “limited service,” i.e., access to 
an improved sanitation facility that is shared (Girma, 3.4%; Hamzari, 8.9%; Wadata, 3.6%). The most 
common improved sanitation facility used (in both the shared and unshared categories) is a pit latrine 
with a slab. The overwhelming majority of households have no facility and practice open defecation 
(Girma, 90.3%; Hamzari, 73.4%; Wadata, 87.7%).
 
99 Improved sanitation facilities include those that flush or pour to a piped sewer system, septic tank, or pit latrine; ventilated 
improved pit latrines, composting toilets, and pit latrines with slabs. See https://washdata.org/monitoring/sanitation. 
100 See Annex 6, Table A6.11 for details.
Baseline Study of the RFSAs in Niger: Final Report (Vol. I)
Findings 63
Figure 19: Household sanitation facility, by RFSA area
RISE I endline participants reported increased awareness of the importance of hygiene, including a trend 
away from open defecation and noticing positive health results from applying the hygiene practices 
promoted, such as decreased cases of diarrhea and waterborne illness. However, these practices are not 
evident in the current baseline data. It is unclear why sanitation facilities are not more common and 
only minimally used. It is also important to differentiate reports of raised awareness from actual 
changes in behavior. Possible reasons for a lag in adoption of improved hygiene and sanitation practices 
include the still-limited coverage of sanitation facilities,101 long-held practices of open defecation, and 
inflated progress reports of the abandonment of open defecation due to stigma.
 
101 The limited coverage of sanitation latrines may require outside resources to construct; in fact, the 2017 endline evaluation 
of the Niger DFAPs raised the cost of latrines as a challenge.
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64 Findings
3.5.3 Handwashing Station
A handwashing station is a location (fixed or mobile) where household members wash their hands with 
water and soap or ash.102 The measurement of this indicator is based on observation by the enumerator 
rather than self-reported information—the enumerator is shown the station where household members 
commonly wash their hands; water and soap or ash must be observed there. The percentage of 
households with a handwashing station with soap or ash varied from 8.9% in the Girma RFSA area and 
18.2% in the Wadata RFSA area to 40.6% in the Hamzari RFSA area.
103 The variation in the prevalence of 
handwashing stations is possibly attributable to differences in the operating contexts, e.g., structural 
differences education level, poverty level, and access to water. It may also be related to urban-rural 
differences: the Hamzari RFSA area, which has the highest percentage of households with handwashing 
facilities, is more urban than the other two RFSA areas.
3.5.4 Knowledge of Critical Moments for Handwashing
Handwashing with water and soap or ash at critical moments can lower the incidence of diarrhea and 
other illnesses. Critical junctures for handwashing include: 1) after possible fecal contact, e.g., after 
defecation, changing a diaper, or cleaning the toilet, and 2) before handling food, such as prior to 
preparing food, eating, or feeding a child.
104
 
102 For additional details refer to the FFP Indicators Handbook Part 1. 
103 See Annex 5 for the percentage of households with a handwashing station with water and soap or ash, disaggregated by 
gendered household type. 
104 For additional details refer to the FFP Indicators Handbook Part 1. 
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Figure 20: Percentage of households with knowledge of the critical moments for handwashing, by
RFSA area
Note: Respondents were asked about the important moments to wash hands. Multiple responses were allowed. Percentages can 
add up to more than 100.
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presents the percentage of households with knowledge of the critical moments for handwashing. Nearly 
all households are knowledgeable about the importance of handwashing before eating. Few are aware 
of critical moments for handwashing that relate to other food-handling activities such as before cooking 
and food prep (Girma, 19.6%; Hamzari, 29.5%; Wadata, 16.6%) and before breastfeeding or feeding 
children (Girma, 7.2%; Hamzari, 12%; Wadata, 3.2%). Many households understand the importance of 
handwashing when hands are dirty, but less are aware of the need to do so when engaging in activities 
posing a risk of fecal contact. For example, in the Girma RFSA area, 42.2% of households are 
knowledgeable of the need for handwashing after defecation, 7.2% after cleaning a toilet, and 2.6%
after changing a diaper. The percentage of households aware of the importance of handwashing after 
fecal contact follow similar patterns in the Hamzari RFSA area (41.1%, 16.6%, 10.6%, respectively) and 
Wadata RFSA area (29.9%, 4.3%, 2.7%, respectively). 
3.6 Women’s Health and Nutrition
3.6.1 Women’s Minimum Dietary Diversity
Diverse diets are associated with better micronutrient content, which in turn contributes to better 
health and nutrition.
105 The women’s minimum dietary diversity indicator (MDD-W) captures the
percentage of women of reproductive age (15–49 years) who consume five or more of ten food groups 
in the day and night before the survey. Though this indicator does not capture the frequency of 
consuming food items, the threshold of five groups is correlated with higher micronutrient adequacy.106
The baseline survey results show that the percentage of women 15–49 years who achieve an MDD-W 
ranges from 38.9% in the Wadata RFSA area to 44.5% and 49.8% in the Girma and Hamzari RFSA areas, 
respectively. The percentage of women receiving an MDD-W does not differ statistically between 
women 15–19 years and women 20–49 years.107
 
105 For additional details refer to the FFP Indicators Handbook Part 1. 
106 See FFP Indicators Handbook Part I. 
107 Refer to Annex 5 for details on MDD-W, disaggregated by age.
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Figure 21 illustrates the food groups consumed by women in the combined RFSA areas (the pattern is 
similar across all three RFSA areas). Nearly all women of reproductive age (98.5%) consume grains, 
roots, and tubers. Most women’s diets include dark green leafy vegetables and pulses (87.3%). A little 
over one-half consume dairy products (53.1%); more than one-third consume meat, poultry, and fish 
(34.6%) and other vegetables (37.2%), and close to one-quarter (24%) consume vitamin A-rich fruits and 
vegetables.108
 
108 Annex 6, Table A6.12 provides details on MDD-W food groups, disaggregated by RFSA area. 
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Figure 21: Food groups consumed by women 15–49 years, combined RFSA areas
Bivariate analyses of MDD-W were conducted to identify background characteristics and intervention￾specific factors expected to contribute to women’s nutrition. Figure 22 summarizes statistically 
significant findings of the bivariate analyses. The results show that women are more likely to achieve a 
diet of minimum diversity if they:
• Participate in cash-earning opportunities.
• Reside in households in higher FCS groups.
• Reside in households with livestock holdings.
• Reside in households with access to or use of financial services.
• Reside in households that apply targeted improved agricultural management practices that are 
expected to enhance agricultural productivity and reduce post-harvest loss.
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Figure 22: Statistically significant associations between MDD-W and intervention-specific factors
Notes: G = Girma RFSA area; H = Hamzari RFSA area; W = Wadata RFSA area
See Annex 7, Table A7.9 for details on the bivariate analyses of MDD-W. 
Multivariate analyses were conducted to explore whether intervention-specific factors such as access to 
financial services or application of improved management practices may influence MDD-W while 
controlling for individual and household characteristics and village-specific influences. The results show 
that women are more likely to achieve a diet of minimum diversity if they resided in households that:
109
• Raised sheep (Girma).
• Participated in community-based savings groups (Hamzari).
• Applied organic manure (Girma, Hamzari).
• Treated seeds with fungicides (Girma, Hamzari).
• Controlled sida cordifolia growth (Hamzari) or performed at least three weedings (Wadata).
 
109 See Annex 7, Tables A7.10a – A7.10d for detailed results of the logistic regression of MDD-W for the combined RFSA areas 
and for each RFSA area separately. 
• Participation in cash-earning activities (G)
Women’s characteristics
• Residing in households in higher FCS group (G, H, W)
Household food security
• Livestock holdings (sheep [G] or poultry [H])
• Participation in group-based savings programs (H) 
• Participation in any form of group-based savings or microfinance/lending (G)
• Participation in ag-related saving schemes (G, H) 
• Taking out an agricultural loan (H)
Household assets and access to/use of financial services:
•Digging zai pits (H)
•Applying organic manure or phosphatic manure (G, H), or compost (H)
•Seed treatment with fungicides (G, H)
•Cultural practices such as control of sida cordifolia, crop rotation, or sowing after first 
useful rains (H)
•Use of improved seeds (H)
•Use of climate information (H)
•Use of at least one improved livestock management practice for any type of livestock (H)
Household adoption of targeted improved management practices
•Locally made storage/metal silos (H)
•Sealed/airtight bags (G, H) 
•Triple bags (G)
•Community storage facilities (H)
•Solar or fuel powered dryers (G)
Household use of improved storage practices
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• Reduced post-harvest loss by storing harvested grains in sealed/airtight bags (Girma), triple bags
(Girma), or community storage facilities (Hamzari).
• Reduced post-harvest loss by using solar or fuel powered dryers (Hamzari, Wadata).
3.6.2 Antenatal Care
Antenatal care can help reduce maternal and perinatal morbidity and mortality through early detection 
and treatment of complications that may arise during pregnancy, as well as through the management of 
concurrent diseases and illnesses such as HIV and malaria via integrated health care delivery.110 ANC 
should be provided by skilled health personnel such as a doctor, midwife, or nurse. To detect and 
effectively treat underlying problems the first ANC visit should occur as early as possible, and within the 
first trimester.111
A total of 1,725 live births occurred in the RFSA areas in the 5 years prior to the survey (Girma, 565; 
Hamzari, 712; Wadata 448).112 The percentage of most-recent births receiving at least four ANC visits by 
a skilled health professional ranged from 36.3% in the Wadata RFSA area to 48.4% in the Girma and 
56.9% in the Hamzari RFSA areas.
113 The majority of live births received at least one ANC visit with a 
skilled health professional (Girma, 90.7%; Hamzari, 94.2%; Wadata, 90.5%). Among those births that 
received at least one ANC visit, in the Girma RFSA area, 30.5% received their first ANC visit during the 
first three months of pregnancy compared to 28.6% and 25.3% in the Hamzari and Wadata RFSA areas, 
respectively.114
3.6.3 Contraceptive Methods: Knowledge, Use and Decision-Making 
Voluntary and safe family planning are central to improving women and children’s health, reducing 
HIV/AIDS, advancing gender equality and women’s empowerment, and reducing poverty.115 Knowledge 
of family planning methods is a prerequisite to accessing and using those methods. Women’s ability to 
make educated and voluntary choices about childbearing, including the use of contraception, is critical 
for their empowerment and overall well-being. 
 
110 For additional details refer to the FFP Indicators Handbook Part 1.
111 WHO. 2004. Standards for Maternal and Newborn Health: Provision of Effective Antenatal Care (Section 1.6). Geneva, 
Switzerland: World Health Organization. Available at http://whqlibdoc.who.int/hq/2007/a91272.pdf. 
112 A woman may have had more than one birth in the past 5 years. The survey collected information only for the most recent 
birth.
113 As of 2019, the WHO revised its recommendation for the minimum number of visits from four to eight. Of the 1,602 most 
recent births that occurred in the 5 years prior to the survey in the combined RFSA areas, only five (less than 1%) received eight 
visits. WHO 2016 Guidelines on Antenatal Care are available at https://www.who.int/publications/i/item/978924154991. 
114 Annex 6, Table A6.13 provides additional details on the use of ANC services, including information on ANC provider, 
disaggregated by RFSA area.
115 Refer to https://www.usaid.gov/global-health/health-areas/family-planning. 
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The survey considers women to be knowledgeable of modern contraception if they are aware of at least 
three modern family planning methods that can be used to delay or avoid pregnancy.116 As shown in 
Figure 23, knowledge of modern contraceptive methods among women in a union is widespread in the 
RFSA implementation areas (Wadata, 61.2%; Girma, 71.6%; Hamzari, 74.5%). 
Most women in the RFSA areas do not use any form of contraception (modern or traditional) (see 
Figure 24).117 The contraceptive prevalence rate (modern and traditional methods combined) ranged 
from 14.1% and 14.8% in the Wadata and Girma RFSA areas, respectively, to 21.8% in the Hamzari RFSA
area. As illustrated in 
Figure 24, most contraceptive users rely on modern methods. The pill and injectables are the most-used 
methods of modern contraception. Less than 1% of women use fertility awareness methods such as the 
Standard Days Method or Lactational Amenorrhea Method. Those results and additional details on 
contraceptive use by type for modern and traditional methods are shown in Annex 6, Table A6.14. That 
analysis finds that most women who use modern contraception participated in the decision to use 
modern family planning (Girma, 81%; Hamzari, 77.3%; Wadata, 68.1%). This percentage is almost evenly 
divided between women who decided alone and those who decided jointly with their spouse.118
Figure 23: Knowledge of modern family planning methods among women 15–49 in a union, by RFSA
 
116 The modern family planning methods used for the calculation of this indicator are female sterilization, male sterilization, 
intrauterine devices, injectables, implants, contraceptive pills, male condom, female condom, diaphragm with spermicide, 
emergency contraception, standard days method, and lactation amenorrhea method. Refer to Annex 5 for details on 
knowledge of modern family planning methods, disaggregated by age group.
117 In this survey, traditional family planning methods are the rhythm method, withdrawal, and other traditional methods.
118 Refer to Annex 5 for additional disaggregation of contraceptive decision-making by age and actor(s) (i.e., alone, or jointly 
with spouse).
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area
Figure 24: Contraceptive use among non-pregnant women 15–49 years in a union, by RFSA area
3.7 Children’s Health and Nutrition
3.7.1 Children’s Minimum Dietary Diversity
Like women’s dietary diversity, children’s dietary diversity has been linked to micronutrient adequacy. A 
child is considered to achieve a diet of MDD-C if they consumed five or more of eight food groups during 
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the day or night before the survey. The indicator is restricted to children 6–23 months and includes both 
breastfed and non-breastfed children. Although breastmilk is included as one of the food groups, this 
indicator does not capture breastfeeding status but rather serves as a proxy measure for complementary 
feeding. The percentage of children consuming MDD-C varied across RFSA areas (Girma, 37.8%; Hamzari, 
54.6%; Wadata, 46.3%).
119
 
119 Based on a sample size of 834 children 6–23 months in the combined RFSA areas (Girma, N = 294; Hamzari, N = 324; Wadata, 
N = 216). For those results and additional details on the distribution of children achieving MDD-C disaggregated by sex, see 
Annex 5. 
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Figure 25 illustrates the food groups consumed by children 6–23 months for the combined RFSA areas
(the pattern is similar in the three areas). In addition to breastmilk (84.4%), grains, roots, and tubers 
(92.2%), vitamin-A rich fruits and vegetables (73.4%), and legumes and nuts (65%) are widely consumed 
by children 6–23 months. 
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Figure 25: Food groups consumed by children 6–23 months, combined RFSA areas
Most results of the bivariate analyses of MDD-C were statistically nonsignificant owing to small sample 
size.120 Key findings indicate:
• No difference in the percentage of children 6–23 months achieving MDD-C by household FCS 
group except in the Hamzari RFSA area, where children in households with an acceptable FCS 
score were almost twice as likely to have MDD-C compared to children in households with a 
borderline FCS, and three times as likely to achieve an MDD-C compared to children in households 
with poor FCS.
• The percentage of children with MDD-C is higher among children living in households that 
participated in an agriculture-related savings scheme (Girma).
• Children living in households that raise sheep are twice as likely to achieve MDD-C compared to 
children living in households that do not raise sheep (Girma).
• Prevalence of MDD-C was higher among children living in households that adopted any of the 
following intervention-specific practices:121
 
120 The analytical sample for the bivariate analyses of MDD-C was restricted to children 6–23 months with data available across 
all variables (Girma, N = 259; Hamzari, N = 305; Wadata, N = 163). Annex 4 describes the methodology for conducting the
analyses. Detailed results by RFSA area and for the combined RFSA areas are provided in Annex 7, Table A7.11. 
121 In a few cases, MDD-C prevalence was lower among children living in households that adopted improved agricultural 
practices—namely, application of compost (Girma), control of sida cordifolia (Girma) and crop association/intercropping 
(Wadata). It is possible that households adopting these practices in the Girma and Wadata RFSA areas represent a poorer 
segment of households in their respective areas because they require relatively fewer or no investment in inputs. Thus, the 
lower prevalence of MDD-C in those households could reflect overall lack of resources rather than the consequences of 
adopting practices that are ultimately expected to improve agricultural productivity, food security and, by extension, children’s 
dietary diversity.
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• Soil-related fertility and conservation practices such as digging zai pits (Hamzari), applying organic 
manure (Girma and Hamzari) or phosphatic manure (Girma).
• Cultural practices such as control of sida cordifolia or sowing after first useful rains (Hamzari).
• Non-irrigation-based agricultural water management practices such as digging half-moons 
(Hamzari).
• Household receipt of food rations from any donor is associated with a higher percentage of 
children with MDD-C (Girma).
3.7.2 Diarrhea and Oral Rehydration Therapy
Diarrhea is the leading cause of mortality for children under 5 years, despite the availability of low-cost 
management treatments such as ORT (FFP Indicators Handbook 2020). Prolonged and repeated bouts of 
diarrhea are also linked to malnutrition. In the Girma RFSA area, 33% of children under 5 years
experienced diarrhea in the 2 weeks preceding the survey. The rates in the Hamzari and Wadata RFSA
areas are 24.5% and 37.7%, respectively. Among children who experienced diarrhea, close to one-half 
received ORT (Girma, 47.9%; Hamzari, 52%; Wadata, 44.6%).122
Bivariate analyses of the prevalence of diarrhea among children under 5 years with various WASH 
indicators indicated that children living in households with a basic sanitation facility in the Girma and 
Wadata RFSA areas were less likely to experience diarrhea compared to children living in households 
with access to an unimproved sanitation facility in those areas.123 There was no difference in the 
prevalence of diarrhea by household sanitation facility in the Hamzari RFSA area. The bivariate analyses 
also indicated that diarrhea prevalence did not differ statistically by drinking water source, use of water 
treatment, access to a handwashing station with water and soap (or another cleansing agent), or 
knowledge of the critical moments for handwashing in any of the RFSA areas. 
Several factors may partially explain the lack of statistical significance between diarrhea prevalence and 
other WASH indicators. While many households have access to an improved water source (combined 
RFSA areas, 73.7%) or can obtain water in 30 minutes or less round trip (combined RFSA areas, 74%), a 
sizable percentage of households (combined RFSA areas, 42.5%) are not able to obtain enough water to 
meet their daily cooking, cleaning, and hygiene needs. A small percentage of households (combined 
RFSA areas, 21.2%) have access to a water source that meets all four criteria of a basic water source
collected by the survey, but the type of containers used to store the water may not offer sufficient 
protection from outside contamination. Few households (combined RFSA areas, 24.8%) do something to 
make their water safer to drink but the survey did not collect information to distinguish between 
households that are using correct water treatment techniques and those that are not. Although access 
to WASH facilities serve as proxies for use, access does not guarantee households are using those 
facilities, let alone in any consistent fashion. 
 
122 Annex 5 provides additional disaggregation of the prevalence of diarrhea and treatment via ORT, disaggregated by sex.
123 See Annex 7, Table A7.12.
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3.8 Gender
This section discusses gender findings 
related to cash-earning, access to credit,
and participation in community groups. The 
baseline survey collected information on 
women and men’s participation in cash￾earning activities, group membership, and 
access to credit. Cash can be used toward 
making investments in productivity￾enhancing inputs and for the purchase of 
diverse and more nutritious food. For 
women, partaking in cash-earning activities 
can contribute toward empowerment and 
gender equality, for example by giving 
women a greater say in the allocation of 
household resources and other decision￾making regarding their own well-being and 
that of their children. Access to credit, like 
participation in cash-earning activities, 
provides access to productive resources and 
is important for gender equality and 
women’s economic empowerment.124
Participation in community groups 
facilitates access to information and 
resources. By strengthening social networks and community bonds, participation in community groups 
also enhances the resilience of households and communities in the face of shocks and stressors.
3.8.1 Gender and Cash-Earning Activities
In this survey, a household member is considered to participate in cash-earning activities if they are paid 
for their work in cash or a combination of cash and in-kind. Individuals who are unpaid or paid in-kind￾only are excluded. Work includes employment in the formal and/or informal sectors, including full-time, 
part-time, or seasonal work performed within and/or outside the home.125 Care work, such as looking 
after children and other household members, is not included. The survey asked all household members 
 
124 For additional details refer to the FFP Indicators Handbook Part 1.
125 Examples of cash-earning activities include agricultural daily wage labor, off-farm daily wage labor, sale of goods produced 
or processed outside the home or at the home, homestead garden or farm, petty trading, cash for work, food for work, 
conditional cash transfers and/or productive safety net programs. 
Figure 26: Gender gap in participation in cash-earning 
activities, by RFSA area
* p < 0.05, ** p < 0.01, *** p < 0.001
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78 Findings
aged 15 years and older about their work participation in the past 12 months. However, the indicator on 
cash-earning is calculated based on the response of women and men in a union rather than all cash 
earners.126
The percentage of women in a union participating in paid work is less than one-half that of men in a 
union in each of the three RFSA areas (see Figure 26). Close to two-thirds of men in a union in the
Hamzari (66.6%) and Girma (65.5%) RFSA areas are paid in cash or a combination of cash and in-kind 
compared to one-third of women in a union (Hamzari, 37.5%; Girma 35.6%). Participation in cash￾earning activities is generally low for both men and women in a union in the Wadata RFSA area (men in 
a union, 47.6%; women in a union, 21.4%), suggesting few opportunities for cash-earning activities.127
3.8.2 Gender and Group Participation
Community groups can be formal or 
informal and include agricultural and 
livestock producers’ groups, land users’ 
groups, water users’ groups, credit or 
microfinance groups (e.g., VSLAs), savings 
groups, local government, religious groups, 
mothers’ groups, and women’s groups. 
Questions on participation in community 
groups were asked only to the youngest 
female in a union and her spouse in 
households comprised of more than one 
married female. 
In the Girma RFSA area, men’s participation 
in community groups is relatively high 
(62.1%) compared to women’s (45.9%) (see 
Figure 27). In the Hamzari RFSA area, 58.2%
of men participate in community groups 
compared to 48% of women. Group 
participation in the Wadata RFSA area is 
generally low: 48.7% and 33.8% for men and 
women, respectively. Gender differences in 
group participation are statistically 
significant in each of the RFSA areas.
 
126 Refer to Section 3.1 and Annex 6, Table 6.1 for estimates of the percentage and number of cash earners in the RFSA areas, 
respectively.
127 See Annex 5 for the percentage of women and men in a union participating in cash-earning activities, disaggregated by age.
Figure 27: Gender gap in community group 
participation, by RFSA area
* p < 0.05, ** p < 0.01, *** p < 0.001
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The most common community groups for women are credit or microfinance groups, savings groups,
mutual help or insurance groups, and mothers’ groups. The most common community groups for men 
are producers’ groups, trade and business associations, water users’ groups, communal grazing land 
groups, religious groups, youth groups, and conflict resolution groups. Across the three RFSA areas, 
there is relatively high participation of women and men in mutual help or insurance groups and civic 
groups.128
3.8.3 Gender Differences in Access to and Decisions About Credit
Women and men are considered to have access to credit if anyone in their household took out a loan or 
borrowed cash or in-kind from a formal or informal source in the 12 months preceding the survey. 
Formal channels of borrowing include banks, NGOs, and group-based microfinance/VSLAs. Informal 
channels of credit include family and friends, money lenders, and informal credit and savings groups. 
Questions on gender differences in access to credit and group membership were asked to the youngest 
woman in a union and her partner. A woman or man is considered to “access credit” if anyone in the 
household took out a cash or in-kind loan from any of the six formal and informal sources mentioned in 
the survey.
As shown in Figure 28, 75.1% of men and 63.5% of women in the Girma RFSA area accessed credit in the 
past 12 months. In the Hamzari RFSA area, 66.5% and 55.9% of men and women, respectively, accessed 
cash or in-kind loan. The percentages of women and men accessing credit in the Wadata RFSA area were
70.3% and 61.9%, respectively. Gender differences in access to credit are statistically significant. 
Figure 28 provides details about credit decision-making by households that took a loan in the last 12 
months. A woman or man is considered to participate in credit decisions if they decided, alone or jointly,
whether to borrow or what to do with the loan for at least one of the loan sources accessed by the 
household.129 A woman or man is considered to decide alone on credit decisions if they decided alone 
whether to borrow and what to do with the loan for all loans accessed by the household.
Most women and men belonging to households that took out a loan in the past 12 months had some 
input into the decision to borrow and/or what to do with the loan.130 The percentage of men 
participating in decisions about credit was high (Girma, 93.9%; Hamzari, 93.6%; Wadata, 85.8%). These 
 
128 Refer to Annex 6, Table A6.16 for the percentage of women and men participating in community groups, disaggregated by 
type of group and RFSA area.
129 The survey has two questions on credit decision-making for each lending source that the respondent reported from 
someone in the household took a loan. Response options for each of the credit decision questions are 'self,’ 'partner/spouse,' 
'other household member,' 'other non-household member,' and 'not applicable.’ Multiple responses are allowed. For example, 
a respondent can report 'self', 'spouse,' and 'other household member." In this case they would be considered to participate in 
the decision (jointly).
130 Includes individuals who decide alone and those who decide jointly with someone else. Two decisions are considered: 1) 
whether to borrow; and 2) what to do with the loan. Multiple responses are allowed for the lending source and decision actors. 
Joint decision-making includes individuals who decide with their partner, with another household member, or with a non￾household member on whether to borrow or what to do with the loan for at least one of the loans made by the household. Sole 
decision-making (i.e., making decisions alone) includes individuals who decide alone on whether to borrow and what to do with 
the loan for all loans taken by the household. 
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rates were lower for women (Girma, 72.8%; Hamzari, 77%; Wadata, 62.6%). Gender differences in 
participation in credit decisions are statistically significant. 
Figure 28: Gender gap in access to and decisions about credit, by RFSA area
* p < 0.05, ** p < 0.01, *** p < 0.001
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The survey findings indicate that men are more likely than women to make credit decisions alone. For 
example, 52.2% of men in the Girma RFSA area make credit decisions alone compared to 26.9% of 
women. In the Wadata RFSA area, the percentage of men deciding alone about whether to borrow and 
what to do with the loan is 56.6% compared to 33.7% among women. In the Hamzari RFSA area, 82.6%
of men and 58% of women decide alone. Joint credit decision-making is generally less prevalent, 
especially in the Hamzari RFSA area, where 11% and 19% of men and women, respectively, decide 
jointly. There are no gender differences in joint decision-making in the Girma (males, 41.7%; females, 
45.9%) and Wadata (males, 29.3%; females, 28.9%) RFSA areas. 
3.9 Resilience
Shocks and stresses such as droughts, floods, and loss of income threaten progress toward food and 
nutrition security. The RFSAs aim to build the resilience of chronically poor and vulnerable households as 
a conduit for achieving sustainable food and nutrition security. USAID defines resilience as “the ability of 
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.”131 The 
baseline survey collected information on the financial and social aspects of households’ resilience capacities 
that are critical for mitigating the effects of shocks and stresses. Specifically, the baseline gathered data on 
the perceptions of local government capacity to respond to future shocks and stressors, households’ social 
capital, and access to group-based savings and cash. This section discusses the results by RFSA.
3.9.1 Perceptions of Local Government Capacity to Respond Effectively to 
Future Shocks and Stressors
Perceptions of local government capacity to respond to future shocks and stressors is a proxy measure 
of trust and belief in the efficacy and legitimacy of public institutions, one of the underlying dimensions 
of transformative capacity. More than one-half of households across the RFSAs believe local 
government institutions can respond effectively to future shocks and stresses (Girma, 63.8%; Hamzari, 
60.1%; Wadata, 55.6%).132
3.9.2 Social Capital
Social capital refers to the network of relationships that foster support and collaboration among 
individuals, households, and communities. Social capital is a significant predictor of households’ ability 
to manage shocks and stressors.133 The social capital index is constructed from two sub-indices: an index 
of bonding social capital and an index of bridging social capital. The bonding social capital index 
measures the strength of households’ support networks within their community (i.e., ability to give and 
receive support from family and friends in times of need). The bridging social capital index measures the 
 
131 https://www.usaid.gov/sites/default/files/documents/1870/USAIDResiliencePolicyGuidanceDocument.pdf. 
132 Chi squared tests of differences in proportions were performed and indicated no statistically significant difference (p < 0.05) 
between gendered household types for this indicator. 
133 For additional details refer to the FFP Indicators Handbook Part 1.
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strength of households’ social support networks with outside communities. Both indices range from 0 to 
4 and are subsequently normalized to range from 0 to 100. The overall social capital index is the average 
of the bonding and bridging sub-indices. A higher score reflects stronger networks of mutual obligation 
that households can draw on in difficult times. 
Figure 29 illustrates the overall index of social capital and its component indices. The bonding social 
capital index is higher than the bridging social capital index in all RFSA areas, suggesting that social 
obligation networks are stronger within the community than outside.134 Differences by gendered 
household type are statistically nonsignificant.
Figure 29: Social capital and component indices, by RFSA
* p < 0.05, ** p < 0.01, *** p < 0.001
 
134 See Annex 6, Table A6.17 for the percentage of households who can receive from and provide support to relatives and non￾relatives during difficult times.
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3.9.3 Household Participation in Group-Based Savings, Microfinance, or 
Lending Programs
The use of financial services enables households to diversify livelihood strategies and manage risks.
135
The indicator measuring participation in group-based savings, microfinance or lending programs
includes both formal and informal groups such as VSLAs, credit unions, and other formal and informal 
group-based finance or lending groups. This indicator differs from estimates of access to credit and 
savings among farmers and estimates of access to credit among women and men in a union in that the 
latter two estimates include a broader range of service providers or sources, and therefore are likely to 
be higher than the estimates of group-based access to credit and savings discussed in this section.136 The 
results indicate that few households in the RFSA areas participate in group-based savings, microfinance, 
or lending programs (Girma, 12.9%; Hamzari, 3.4%; Wadata, 2.8%). 137 In the Girma RFSA area, 
households are almost twice as likely to participate in group-based savings groups than group-based 
credit or microfinance groups. 
 
135 For additional details refer to the FFP Indicators Handbook Part 1.
136 Refer to FFP Indicators Handbook for detailed description of the calculation of these indicators. 
137 See Annex 5 for additional details.
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4. CONCLUSIONS AND RECOMMENDATIONS
This section outlines conclusions and recommendations for future initiatives. Because the 2020 baseline 
study did not include a qualitative component, data from secondary qualitative sources were used to 
help interpret and contextualize the results as well as inform conclusions and recommendations. The 
conclusions and recommendations were further refined based on feedback received from IPs during a 
series of data utilization workshops.
Food security: Most households in the RFSA areas meet the threshold for acceptable food consumption. 
However, FCS is known to overstate food security138 and may be overly sensitive to seasonality or other 
factors that affect food availability and accessibility at the time of the survey.
139 Although statistical 
analyses did not indicate an association between the percentage of harvest completed and household
food consumption, it is possible that the overlap of data collection with the start of the harvest period 
inflated results for food consumption: households that did not harvest any crops at the time of the 
survey may have received food items from households that harvested their crops, and/or may have 
purchased food items from the market. Further analysis is needed to determine whether an adjustment 
in weights and/or thresholds is relevant for the Nigerien context. 
Households across the RFSA areas consume staples almost daily. Pulses are consumed frequently—
almost 5 days per week. Intake of dairy and animal-based proteins is infrequent, and intake of fruits and 
vegetables is also rare. Nutrition meetings and trainings could demonstrate ways to incorporate 
different food groups into daily meals. Agriculture-related trainings can focus on new varieties of fruits 
and vegetables to grow. Limited financial resources, especially during the lean season, may constrain 
households’ abilities to incorporate diverse food groups on a frequent basis, and households that grow 
more-nutritious foods may opt to sell them. Increasing the use of improved post-harvest storage can 
help households extend food provisioning for a few months during the lean period. Qualitative research 
and/or cost-of-diet studies could help identify locally available nutritious wild foods and/or cheaper 
foods to promote for household consumption.
There is some evidence that household food consumption is positively associated with access to 
financial services, certain livestock holdings, and the application of soil-related fertility practices. This 
underlines the importance of supporting interventions that aim to improve food access by promoting 
agricultural/livestock livelihood activities and access to financial services. 
Land ownership: Female farmers with access to a plot of land over which they make decisions are less 
likely to own the land (and in some cases more likely to access it via a sharecropping arrangement) 
compared to male farmers. Regardless of type of land access (i.e., own, rent, or sharecrop), the size of 
farmland over which female farmers make decisions is generally smaller compared to male farmers. 
Further research is needed to understand the structural factors (i.e., cultural, religious, economic, 
 
138 Maxwell, Coates, and Vaitla. 2013. 
139 WFP 2008. Food Consumption Analysis: Calculation and Use of the Food Consumption Score in Food Security
Analysis. Available at https://documents.wfp.org/stellent/groups/public/documents/manual_guide_proced/wfp197216.pdf.
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Conclusions and Recommendations 85
ecological, and institutional) that impede women’s access to land for cultivation, and to support 
initiatives that improve women’s land rights. 
Use of financial services: Use of agriculture-related financial services is low in the RFSA areas and even 
lower among female farmers compared to male farmers. Farmers are more likely to take out loans than 
participate in saving schemes. Agriculture-related meetings and trainings could focus on improving 
financial literacy and build on traditional community-based borrowing mechanisms to increase use of 
financial services. There is a need to understand barriers on the demand side, such as lack of financial 
literacy, lack of collateral, high interest rates, and household indebtedness, but also supply-side factors 
such as the willingness of formal lenders such as microfinance institutions to facilitate access to 
agricultural credit to smallholder farmers.
Use of improved post-harvest handling and storage practices: Locally made storage structures such as 
metal silos are the most common type of improved post-harvest storage practice used, followed by 
sealed/airtight bags. However, these structures are not equally effective at keeping out moisture, 
insects, pests, and rodents. Future interventions could focus on building capacity to use more effective 
locally made structures and address barriers to female farmers’ access to community grain storage 
facilities. A better understanding of post-harvest loss per crop, drivers of loss, and the role of the myriad 
factors that can reduce loss would be helpful for informing future initiatives. 
Use of improved crop management practices: The most common crop management practices are 
applying organic manure, crop association, sowing after first useful rains, and NRM approaches such as 
FMNR and delimiting animal corridors and pasture areas. Use of improved seed varieties and pest and 
disease management practices are less pervasive. Findings from the RISE I program areas suggest that 
farmers are more likely to adopt traditional practices inherited from their ancestral past and have 
demonstrable results, and less likely to use practices that are unfamiliar or require resources to 
purchase inputs. The findings suggest that encouraging experimentation and focusing on field 
demonstrations in the RFSA areas to raise the visibility of the efficacy of approaches could be useful, 
with benefits extending to the wider population. 
Use of improved livestock practices: Application of targeted improved livestock management practices 
is low. Results from the RISE I program point to potential program options (e.g., training community 
members in veterinary services, raising awareness on critical moments to call on veterinary services) 
that can address some of the barriers to uptake of improved livestock practices. Further analysis is 
needed to understand the main providers of veterinary-related services in the RFSA areas, as well as 
barriers to their use and/or sustainability. Future initiatives should also consider the extent to which 
livestock farmers are able to access existing veterinary services (such as government programs) on a 
permanent basis and farmers’ ability to afford veterinary services and products. Further research should 
be undertaken to assess the extent of these potential barriers. 
Application of improved management practices and use of financial services: There is some evidence 
from the baseline study that farmers who accessed agricultural credit are more likely to adopt some 
targeted improved agricultural management practices and technologies, such as using improved seed 
varieties, applying phosphatic manure or micro-doses of fertilizer, treating grains with agro-chemicals, 
and using community facilities or warehouses, sealed/airtight bags or triple bags to store grains. Use of 
licking and/or multi-nutritional blocks and paraveterinary services was higher among goat and sheep 
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farmers who took out an agricultural loan compared to those who did not. Poultry farmers who used 
agricultural credit were more likely to use improved varieties and veterinary products compared to 
poultry farmers who did not. These findings underline the importance of integrating interventions in 
financial services and agricultural techniques, as well as promoting techniques that farmers can sustain 
without continued external support. 
Extending access to credit can be one pathway for improving adoption of post-harvest handling and 
storage. Additional analysis on factors associated with the application of improved crop management 
practices should be undertaken to help bolster adoption rates and facilitate sustainability beyond the 
life of the RFSAs. An understanding of how farmers source new varieties can inform IPs’ design decisions 
around appropriate entry points for new germplasm. It would also be useful to monitor how farmers are 
applying the new techniques, to determine whether the chosen practice suits their individual context 
and whether they are applying it correctly, since these factors can affect agricultural productivity.
WASH: Access is low in the RFSA areas to basic sanitation facilities, handwashing stations with water and 
soap, and improved drinking water sources that consistently meet the minimum daily needs of 
households. Results from studies of previous programs such as the 2012–2017 DFAPs and the RISE I 
program point to several barriers, such as the costs of materials and labor for building improved latrines, 
cost of purchasing soap or cleaning agents, engineering issues around certain latrine types, and cultural 
preferences. Participants in the baseline data utilization workshop noted that the timing of the survey 
coincided with heavy rains/flooding that resulted with the destruction of water points, thereby 
impacting access to water sources. RFSAs could consider supporting approaches that finance the 
construction of latrines, handwashing stations and water points through community-based savings and 
credit vehicles; marketing different design models that are accepted by the community; and supporting 
community-based service provider models so that materials (e.g., for the construction of WASH facilities
and soap production) are locally available and affordable. 
Nearly all households are knowledgeable about the importance of handwashing before eating. 
Sensitization should focus on other critical times that households were less likely to report as critical 
moments for handwashing—namely, before cooking and food preparation, before breastfeeding or 
feeding children, and when engaging in activities posing a risk of fecal contact. Additional research could 
be helpful to better understand which WASH messages households prioritize and why.
Women’s dietary diversity: Less than one-half of women of reproductive age in the RFSA areas achieve 
a diet of minimum diversity. Kitchen demonstrations in which women from the community show how to 
incorporate different food groups, including nutritious wild foods, into daily meals could be useful. 
Results underscore that women consume more-diverse diets when their households are more food 
secure, and when household members participate in an agriculture-related savings scheme, take out an 
agricultural loan, or use improved practices that support higher yields and protect against post-harvest 
losses. RFSAs should continue to integrate activities that promote savings and access to credit and 
interventions that foster the adoption of improved agricultural practices. 
Antenatal care: More than one-third of (most-recent) births that occurred in the five years prior to the 
survey received at least four ANC visits by skilled health personnel. Behavior change communication 
efforts should continue to emphasize the importance of ANC, focusing on frequency and timing of the 
visits and who is qualified to provide those services. In some cases, the lack of availability of ANC 
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Conclusions and Recommendations 87
services or distance to a health center may be a barrier. In addition to supporting access to ANC during 
the first trimester, there is a need to tackle social and cultural norms around ANC and around husbands’ 
participation. Sensitization should not only target mothers but also men via husband schools and/or
husband-wife meetings so that fathers can support women in ANC visits and other aspects of their 
pregnancy and delivery. 
Family planning: Knowledge of modern contraceptive methods among women in a union is widespread 
in the RFSA areas; however, very few women use any form of family planning. Further exploration is 
needed to identify and address barriers to using family planning, including affordability of consultation 
services, cost of purchasing contraception, and underlying cultural or religious beliefs. Results from the 
baseline survey point to the role of husbands in contraceptive decision-making; about one-half of 
women who use family planning made the decision with their spouse. Sensitization efforts should target 
both women and men and underscore the significance of family planning for the well-being of women
and the overall family (e.g., benefits of birth spacing).
Children’s dietary diversity and diarrhea: Grains, roots and tubers, vitamin-A-rich fruits and vegetables, 
and legumes and nuts are widely consumed by children 6–23 months, but the prevalence of children 6–
23 months achieving MDD-C is moderate in all RFSA areas. RFSAs should continue to raise awareness 
among primary caregivers on the health benefits of complementary feeding and the appropriate time to 
introduce complementary foods without cutting back on breastfeeding. Sensitization around 
complementary feeding could be rolled into ANC and perinatal care visits and through mothers’ groups 
with demonstrations on how to integrate diverse foods into children’s meals. Sensitization for fathers 
through fathers’ groups or husbands’ schools could also enhance the sharing of household decision￾making (e.g., how much to spend and what to cook). 
About one-third of children under 5 years experienced diarrhea in the 2 weeks preceding the survey. 
Bivariate analyses of the prevalence of diarrhea among children under 5 years indicated no difference in 
diarrhea prevalence by household WASH status except for lower prevalence with the use of basic 
sanitation facilities in the Girma and Wadata RFSA areas. While access to WASH facilities is generally 
correlated with use, access does not guarantee households are using those facilities. Although previous 
qualitative studies in the country have underscored growing awareness of the importance of WASH 
practices, there is a need to continue sensitization on the linkages between diarrhea and basic hygiene.
Among children who experienced diarrhea, close to one-half received ORT. Additional sensitization 
focused on how to prepare homemade alternatives to oral rehydration salts or recommended home 
fluids would be helpful given challenges in accessing health centers and the cost of those services. 
Gender, group participation and access to credit: Between one- to two-thirds of women and men belong 
to community groups; however, group membership is generally lower among women. A better 
understanding of the barriers to group membership is needed. Women’s time constraints may limit their 
ability to participate in community groups; sensitization of women and men on homemaking and 
childrearing as collaborative processes could free up women’s time to participate in community groups.