0
Baseline Report of the Titukulane
Resilience Food Security Activity 
in Malawi
June 2022 | Volume I
IMPEL | Implementer-Led Evaluation & Learning Associate Award
ABOUT IMPEL
The Implementer-Led Evaluation & Learning Associate Award (IMPEL) 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 USAID Bureau for Humanitarian Assistance (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, Innovations for Poverty 
Action, and International Food Policy Research Institute. 
RECOMMENDED CITATION
IMPEL. (2022). Baseline Report of the Titukulane Resilience Food Security Activities in Malawi (Vol. I). Washington, DC: The 
Implementer-Led Evaluation & Learning Associate Award. 
PHOTO CREDITS
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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.
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c/o Save the Children
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PREPARED BY:
Baseline Report of the Titukulane RFSA in Malawi (Vol. I)
Acknowledgements i
ACKNOWLEDGEMENTS
The baseline survey of Titukulane was made possible through the input and support that the study team 
received from different people and stakeholders from the beginning of the study to the completion of 
the baseline data collection. The study team is grateful for the support provided by staff from Bureau for 
Humanitarian Assistance (BHA), CARE International in Malawi (CIM), Save the Children Malawi, and 
Emmanuel International.
We are also thankful for the great work by field managers and enumerators. The field teams traveled to 
the far areas of Mangochi and Zomba tracking respondents and conducting interviews, and their 
dedication resulted in high-quality data. 
Equally, the team thanks the District Commissioners, Traditional Authorities (TAs), Group Village Heads 
(GVHs), and communities in Zomba and Mangochi. GVHs freely gave field teams access to their 
jurisdictions and in some cases, allocated a person to help field teams find target respondents. The 
warm reception from the study communities indeed helped to smooth the data collection process. 
This report was prepared by John Tengatenga, Rafael Panlilo, Monserrat Lara, Gabriel Olila, Charles 
Amuku and Rachel Strohm from Innovations for Poverty Action and Javier Madrazo and Lasse Brune 
from Northwestern University.
IMPEL | Implementer-Led Evaluation and Learning
ii Table of Contents
TABLE OF CONTENTS
Acknowledgements .............................................................................................i
List of Tables......................................................................................................iv
List of Figures......................................................................................................v
Acronyms...........................................................................................................vi
Executive Summary ..........................................................................................vii
1. Introduction...................................................................................................1
1.1 Activity Overview ...........................................................................................................................1
1.2 Research Overview.........................................................................................................................2
1.3 Purpose of the Baseline Survey......................................................................................................4
2. Methodology .................................................................................................5
2.1 Study Area ......................................................................................................................................5
2.2 Sampling Strategy...........................................................................................................................5
2.3 Baseline Sample Size ......................................................................................................................6
2.4 Random Assignment and Balance..................................................................................................7
2.5 Baseline Questionnaire Development ...........................................................................................7
2.5.1 Household Survey .........................................................................................................7
2.5.2 Baseline Anthropometric Survey ..................................................................................8
3. Fieldwork Organization and Challenges..........................................................9
3.1 Field Organization ..........................................................................................................................9
3.1.1 Team Composition ........................................................................................................9
3.1.2 Pilot Test Survey Training..............................................................................................9
3.1.3 COVID-19 Protocol ........................................................................................................9
3.1.4 Replacement Strategy.................................................................................................10
3.1.5 Data Quality Checks....................................................................................................10
3.1.6 Survey Productivity .....................................................................................................10
3.2 Challenges....................................................................................................................................11
3.2.1 Names of Respondents Not Known in Sampled Villages............................................11
3.2.2 Villages Placed on Wrong GVH List.............................................................................11
3.2.3 Respondents’ Expectations.........................................................................................11
3.2.4 Children Not Available for Anthropometric Measurement........................................11
3.2.5 Handling Children during Anthropometric Measurements........................................11
4. Descriptive Statistics....................................................................................12
4.1 Household Demographics............................................................................................................12
4.2 Sources of Income........................................................................................................................13
Baseline Report of the Titukulane RFSA in Malawi (Vol. I)
Table of Contents iii
4.3 Consumption Poverty Measure ...................................................................................................14
4.4 Food Security................................................................................................................................15
4.5 Farming and Land Ownership ......................................................................................................17
4.6 Farming Practices.........................................................................................................................19
4.7 Farmer Groups .............................................................................................................................21
4.8 Agricultural Sales..........................................................................................................................22
4.9 Off-Farm Business........................................................................................................................23
4.10 Access to Targeted Public Services...............................................................................................24
4.11 Financial Health............................................................................................................................25
4.12 Savings and Loans.........................................................................................................................26
4.13 Children’s Anthropometric Measures..........................................................................................27
4.14 Children’s Nutrition......................................................................................................................29
4.15 Water, Sanitation, and Hygiene (WASH)......................................................................................30
4.16 Mental Health ..............................................................................................................................31
5. Conclusion ...................................................................................................34
Appendix ..........................................................................................................36
IMPEL | Implementer-Led Evaluation and Learning
iv List of Tables and Figures
VOLUME II
Annex A: Titukulane Baseline Survey
Annex B: Anthropometric Survey
Annex C: COVID-19 Protocol
Annex D: Anthropometry Protocol and Manual
LIST OF TABLES 
Table 1. Household categories......................................................................................................................2
Table 2. List of Titukulane interventions provided in treatment and control villages..................................3
Table 3. Sample.............................................................................................................................................7
Table 4. Household demographics..............................................................................................................12
Table 5. Household sources of income over the last 12 months................................................................13
Table 6. Consumption poverty....................................................................................................................15
Table 7. Food Consumption Score and Food Insecurity Experience Scale .................................................16
Table 8. Crops cultivated.............................................................................................................................18
Table 9. Farming inputs...............................................................................................................................19
Table 10. Farming practices........................................................................................................................20
Table 11. Farmer groups.............................................................................................................................21
Table 12. Agricultural sales.........................................................................................................................22
Table 13. Off-farm business........................................................................................................................23
Table 14. Access to extension services (past 12 months)...........................................................................24
Table 15. Financial health ...........................................................................................................................26
Table 16. Savings and loans........................................................................................................................27
Table 17. Anthropometric indicators for children under 5 years old, by gender and age .........................28
Table 18. Small children: diet and health ...................................................................................................29
Table 19. Water, sanitation, and hygiene of Tier-1 Care Group eligible ....................................................31
Table 20. Mental health..............................................................................................................................32
Table 21. Appendix: Nutrition knowledge ..................................................................................................36
Table 22. Appendix: Resilience ...................................................................................................................36
Table 23. Appendix: Women’s dietary diversity among Tier-1 Care Group eligible households, by age...36
Table 24. Appendix: Livestock assets in the last 12 months.......................................................................37
Table 25. Appendix: Livestock practices in the past 12 months.................................................................37
Table 26. Appendix: Consumption..............................................................................................................38
Table 27. Appendix: Gender (cash).............................................................................................................39
Table 28. Appendix: Farming practices and area of application.................................................................39
Table 29. Appendix: Consumption poverty, by household gender composition .......................................44
Table 30. Appendix: Food Consumption Score, by household gender composition..................................45
Table 31. Appendix: Food Insecurity Experience Scale, additional ............................................................46
Table 32. Appendix: Average Food Consumption Score by main household incomes...............................47
Table 33. Appendix: Correlation Food Consumption Score components vs. Food Insecurity Experience 
Scale components.......................................................................................................................................48
Baseline Report of the Titukulane RFSA in Malawi (Vol. I)
List of Tables and Figures v
Table 34. Appendix: Consumption poverty across main source of income or food, by tier ......................48
Table 35. Appendix: Anthropometric indicators for children under 5 years old, by gender and age ........49
Table 36. Appendix: Small children: diet and health, additional details ....................................................51
Table 37. Appendix: Water, sanitation, and hygiene of Tier-1 Care Group eligible, additional details.....52
Table 38. Appendix: Resilience, by household gender composition ..........................................................52
Table 39. Appendix: Balance.......................................................................................................................54
LIST OF FIGURES
Figure 1: Overview of sampling strategy ......................................................................................................6
Figure 2. Appendix: Binned scatter plot showing strong alignment of Food Consumption Score vs Food 
Insecurity Experience Scale scores .............................................................................................................53
IMPEL | Implementer-Led Evaluation and Learning
vi Acronyms 
ACRONYMS
BHA
CIM
CPI 
FCS
FIES
FNM
GVH
HAZ
HFCs
IFPRI
IMPEL
IPA 
MAD
M-TVET
MWK
NASFAM
NCT
NRS
ORT
PPP
RCT
RFSA
TA
USAID
VSLA
WASH
WHZ
Bureau for Humanitarian Assistance
CARE International in Malawi 
Consumer Price Index
Food Consumption Score
Food Insecurity Experience Scale
Female No Male
Group Village Head
Height-for-Age Z-score
High-Frequency Checks
International Food Policy Research Institute
Implementer-Led Evaluation and Learning Associate Award
Innovations for Poverty Action
Minimum Acceptable Diet
Mobile Technical and Vocational Training
Malawi Kwacha
National Smallholder Farmers’ Association of Malawi
Nutritional Cash Transfers
Malawi National Resilience Strategy
Oral Rehydration Therapy
Purchasing Power Parity
Randomized Controlled Trials
Resilience Food Security Activity
Traditional Authority
United States Agency for International Development
Village Savings and Loan Associations 
Water, Sanitation, and Hygiene 
Weight-for-Height Z-Score
Baseline Report of the Titukulane RFSA in Malawi (Vol. I)
Executive Summary vii
EXECUTIVE SUMMARY
While Malawi is moving up on the Human Development Index, in 2017 it is still classified as a low human 
development country (171 of 189)1
. Despite decades of robust government and donor investments in 
livelihoods, food security, nutrition, and resilience, over 50% of the population lives below the poverty 
line2
. Previous activities have not sufficiently reduced the number of chronically food and nutrition 
insecure households nor effectively enhanced the capacity of local and government structures to 
implement resilience focused policies and actions. To address these issues, the Government of Malawi 
has developed a National Resilience Strategy (NRS) to guide investments in agriculture, reduce impacts 
and improve recovery from shocks, promote household resilience, strengthen the management of 
Malawi’s natural resources, and facilitate effective coordination between government institutions, civil 
society organizations and development partners. CARE and consortium partners have designed the 
Titukulane Resilience Food Security Activity (RFSA) which means “let us work together for development” 
in the local Chichewa language—to support implementation and ensure the effectiveness of the NRS. 
The Titukulane RFSA, implemented by CARE International in Malawi (CIM), aims to achieve sustainable, 
equitable, and resilient food and nutrition security for ultra-poor and chronically vulnerable households. 
Titukulane is implemented in Zomba and Mangochi districts of Malawi’s Southern Region. 
Specifically, Titukulane is designed to increase households’ abilities to deal with shocks without 
experiencing food insecurity following a three-purpose approach:
1. Increased diversified, sustainable, and equitable incomes for ultra-poor, chronically vulnerable 
households, women, and youth.
2. Improved nutritional status among children under 5 years of age, adolescent girls, and women 
of reproductive age.
3. Increased institutional and local capacities to reduce risk and increase resilience among poor 
and very poor households in alignment with the Malawi NRS. 
To meet these three purposes, the Titukulane RFSA provides households with a package of 
interventions, including:
● Care Groups with Nutritional Cash Transfers (NCT)
● Farmer Field Business Schools and crop marketing support
● Village Savings and Loan Associations
● Adolescent nutrition
● Irrigation farming
● Youth vocational training including start-up capital
● Gender dialogues
IMPEL | Implementer-Led Evaluation and Learning
viii Executive Summary
Innovations for Poverty Action (IPA) is conducting an impact evaluation of the Titukulane RFSA to assess 
Titukulane’s effectiveness at improving ultra-poor households’ food and nutrition security through the 
Theory of Change laid out in Titukulane’s three-purpose approach. To do so, the study will answer the 
following questions:
1. Does the Titukulane intervention package increase the households’ incomes? 
2. Does the Titukulane intervention package increase households’ diversification of income 
sources?
3. Does the Titukulane intervention package improve the nutritional status of children under 5
years of age, adolescent girls, and women of reproductive age?
IPA is conducting a Randomized Controlled Trial (RCT) to rigorously attempt to answer these questions. 
The impacts of the intervention package will be measured by comparing households in villages that 
were randomly selected to receive the interventions (treatment villages) to households in villages that 
were not (control villages). Specifically, IPA will conduct data collection to measure impacts on 
outcomes such as child nutrition, food security, consumption, asset ownership, agricultural output and 
practices, household income and livelihood activities, and women’s empowerment. 
This report summarizes the evaluation design, describes the sampling strategy and presents summary 
statistics based on data collected as part of the baseline survey. 
The purpose of the baseline survey is to collect data that can be used to describe the study sample, to 
collect data necessary for subgroup analysis of impacts, to allow for the description of time trends in the 
data, and to increase statistical precision for impact estimation. Additionally, the data obtained in the 
baseline survey can help support CIM’s programming decisions and reporting requirements. 
The baseline survey took place between August to November 2021 and included interviews with a total 
of 3,107 households in Mangochi and Zomba districts.
The report presents summary statistics for key baseline measures of interest, including information to 
describe the study sample such as demographics, sources of income and as well as the Bureau for 
Humanitarian Assistance (BHA) indicators. The following is a summary of the findings: 
Demographics: Household heads are 42 years old on average, 37% are women, 66% are married, and 
77% have not completed primary education. The average household has 2.7 children under the age of 
16. 
Livelihoods: The most frequently listed sources of income or food considered to be most important for 
households are farming (55%) and agricultural wage labor (18%), non-agricultural wage labor (8%) and 
non-agricultural self-employment (6%).
Consumption poverty: 56% of households live on less than US$1.90 per day, with the average per capita 
consumption among surveyed households being US$2.19 per day.
Food security: Based on the Food Consumption Score, 53% of households have adequate food 
consumption, 37% are borderline and 10% are categorized as having poor food consumption. 
Households report high levels of experience with food insecurity over the past 12 months according to 
Food Insecurity Experience Scale, with 97% classified as moderately or severely food insecure.
Baseline Report of the Titukulane RFSA in Malawi (Vol. I)
Executive Summary ix
Farming: 
● The vast majority of households engaged in farming in the 12 months prior to the interview 
(93%), and reported cultivating 1.04 acres on average. The three most commonly reported rainy 
season crops are maize (98%), pigeon peas (40%), and groundnuts (23%). Only 17% among those 
with any farming over the past 12 months reported cultivating any crop during the dry season. 
● Many farmers used at least some modern inputs, with 67% reporting the use of inorganic 
fertilizer in the past rainy season and 48% reporting the use of packaged seeds. Among those 
households farming in the dry season, irrigation is essentially a requirement and 96% of those 
with any dry season farming used some form of irrigation. However, irrigation methods are 
basic, with the overwhelming majority watering by hand with small containers. 
● The majority of farmers report some usage of some of the improved management practices 
targeted by the activity (86%). However, many individual practices are not widely used. For 
example, among those reporting the use of any improved practices, only 7% reported practicing 
weed control, 6% reported mulching and 5% reported employing crop rotation. 
● Only a small minority of farming households are a member of any type of farmer group or 
cooperative (4%).
● Slightly less than half of the farming households sold any crop in the past rainy season, and only 
about a quarter sold more than half of their output of any one crop. The most common types of 
crop buyers that farmers sold to were local traders. 
Business ownership: Only 17% of households operate an off-farm business, the majority of which are 
small, with only 25% of business-operating households reporting business inventory valued above
Malawi Kwacha (MWK) 50,000 (purchasing power parity (PPP) $163). 
Agricultural and health services: Only 18% of households reported needing advice on agriculture. 
Among those who did, 28% report having access to advice from a government extension officer. Only 9% 
of households reported needing advice on animal health, which is partially explained by the limited rates 
of livestock ownership (38% of households owned any livestock in the past 12 months). Overall, a 
relatively high rate of households report receiving advice from either a community or a government 
health and nutrition extension worker (34%). Among those households with children under 5 years old, 
about half report their children were screened for malnutrition. 
Children’s health and nutrition: Overall, few children were found to be wasted (2% of children under 5 
years old) though the rate is somewhat higher among poorer households (where 6% of children from 
the Tier-1 Care Group eligible stratum of households are considered wasted). However, 42% of children 
under 5 were measured as stunted. Based on survey responses, only 4% of children under 2 years old in 
the poorer Tier-1 Care Group stratum of households were calculated to be receiving a Minimum 
Acceptable Diet (MAD).
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Baseline Report of the Titukulane RFSA in Malawi (Vol. I)
Introduction 1
1. INTRODUCTION
1.1 Activity Overview
The food and nutrition security of ultra-poor households around the world is vulnerable to negative 
shocks to households’ sources of income. To address this issue in Malawi, the United States Agency for 
International Development’s (USAID) Bureau for Humanitarian Assistance (BHA) awarded a consortium 
led by CARE International in Malawi (CIM) to provide Resilience Food Security Activities (RFSA) for 
723,111 people in 290,413 households in Mangochi and Zomba districts in Malawi. The activity, 
Titukulane, aligns with the National Resilience Strategy (NRS) developed by the Government of Malawi. 
Titukulane is being implemented by CIM along with Save the Children, Emmanuel International, 
WaterAid, the National Smallholders Farmers’ Association of Malawi (NASFAM), and the International 
Food Policy Research Institute (IFPRI).
The goal of Titukulane is to promote “sustainable, equitable, and resilient food and nutrition security for 
ultra-poor and chronically vulnerable households.” By the completion of the activity, targeted 
participants are expected to have “increased incomes from on and off-farm livelihoods, improved 
health, nutrition, and other behaviors equitable gender relations, expanded access to safe water and 
improved hygiene, and quality health and nutrition services, and will benefit from improved district-level 
systems for planning and resource mobilization around development, disaster risk management, and
natural resource management.” To achieve this, Titukulane is employing a wide variety of interventions, 
including but not limited to Integrated Watershed Management, Village Savings and Loan Associations
(VSLA), Gender Dialogues, Care Groups with Nutritional Cash Transfers (NCT), Disaster Risk Reduction 
training, Farmer Field and Business Schools, Youth Savings and Loan Associations, Mobile Technical and 
Vocation Training (M-TVET), and Youth Disaster Risk Management Clubs.
The Titukulane Theory of Change has three main objectives, or purposes: 
1. Purpose 1 (P1): Income. Increased diversified, sustainable, and equitable incomes for ultra-poor, 
chronically vulnerable households, women, and youth.
2. Purpose 2 (P2): Reproductive, Maternal, Newborn, Child and Adolescent Health, Nutrition, and 
WASH. Improved nutritional status among children under 5 years of age, adolescent girls, and 
women of reproductive age.
3. Purpose 3 (P3): Resilience Capabilities. Increased institutional and local capacities to reduce risk and 
increase resilience among poor and very poor households in alignment with the NRS.
Each purpose has several sub-purposes with associated intermediate outcomes, indicators, and impact 
targets for improvement from baseline values. There are also four cross-cutting objectives: Gender Equality, 
Governance & Accountability, Youth Engagement, and Environmental Safeguarding.
The eligibility of households for the various interventions depends both on demographic characteristics and 
socioeconomic status. For example, Care Groups target pregnant and lactating women and caregivers with 
children under 2 years of age and M-TVET programming targets youths. Among those who are eligible for a 
Care Group, only participants from certain categories of poorer households will qualify for NCTs. 
IMPEL | Implementer-Led Evaluation and Learning
2 Introduction
The categorizations of socioeconomic status of households Titukulane uses to determine eligibility is based 
on a community participatory listing exercise. With the help of community leader and other members, 
Titukulane staff categorized all households in all villages of the two districts where Titukulane is active into 
one of four categories: Tier 1 “Hanging in”, Tier 2 “Stepping up”, Tier 3 “Stepping out”, and Tier 4 “Well off”. 
Households in the well-off category are not eligible for any interventions. Table 1 describes each of the first 
three categories that are eligible for Titukulane interventions by socioeconomic status.
Table 1. Household categories
Tier Description
Tier 1 (Hanging in) Ultra-poor households with limited labor capacities and in need of direct 
support.
Tier 2 (Stepping up) Ultra-poor households with some labor capacity but with resources too 
limited to enable them to become food self-sufficient.
Tier 3 (Stepping out)
Chronically vulnerable households that are beginning to step out of poverty 
as they acquire additional assets, but that are food insecure for at least part 
of the year, every year.
The listing data provided by Titukulane has the following distribution of household types—Tier 1: 27%; Tier 2: 
59%; Tier 3: 12%; Tier 4: 4%.
1.2 Research Overview 
Innovations for Poverty Action (IPA) is conducting an impact evaluation of the Titukulane RFSA in 
Mangochi and Zomba districts of Malawi’s Southern Region. The main objective of the impact evaluation 
is to assess Titukulane’s effectiveness at improving ultra-poor households’ food and nutrition security 
through the Theory of Change laid out in Titukulane’s three-purpose approach. To do so, the study will 
answer the following questions:
1. Does the Titukulane intervention package increase the households’ incomes? 
2. Does the Titukulane intervention package increase households’ diversification of income 
sources?
3. Does the Titukulane intervention package improve the nutritional status of children under 5 
years of age, adolescent girls, and women of reproductive age?
IPA is conducting a Randomized Controlled Trial (RCT) to rigorously attempt to answer these questions. 
The impacts of the intervention package will be measured by comparing households in villages that 
were randomly selected to receive all of Titukulane’s interventions (treatment villages) to households in 
villages that were not selected (control villages). Note that control villages will not receive services that 
are offered at the household or village level but may still benefit from services targeted at 
administrative units above the village level. These effects of these services will not be captured by the 
RCT’s impact estimates. Table 2 provides an overview of the list of “evaluation” interventions that only 
treatment villages will be subject to and other “non-evaluation” interventions that all villages in 
Titukulane’s implementation area may be subject to. 
Baseline Report of the Titukulane RFSA in Malawi (Vol. I)
Introduction 3 
Table 2. List of Titukulane interventions provided in treatment and control villages
Treatment Control
Evaluation interventions
Irrigation x
Marketing x
Farmer Field Business Schools x
Care groups x
Village Savings and Loan Associations x
Youth Savings and Loan Associations x
Adolescent nutrition (part 2*) x
Gender dialogues x
Vocational / Entrepreneurial Skills + Capital x
Non-evaluation activities
Strengthening district govovernment and community capacity x x
Improving supply chains for water, sanitation, and hygiene x x
Adolescent nutrition (part 1**) x x
Community scorecards x x
Capacity strengthening of service providers x x
* Only components where participation can be contained at village level
** Parts of the programming that is delivered such that control villages cannot be excluded will not be included in the 
evaluation
IPA estimate impacts of the activity by comparing outcomes measuring outcomes captured in an endline 
survey—such as child nutrition, food security, consumption, asset ownership, agricultural output and 
practices, household income and livelihood activities—and comparing outcomes between households in 
treatment and control villages. 
The study’s sampling strategy is designed to oversample households who are expected to be eligible for 
participation in Care Groups with NCTs, identified in the screening stage as those households with a 
pregnant woman or a child under 2 who are categorized as belonging to Tier 1. This sampling strategy 
reflects the importance of improving children’s nutritional and growth outcomes for the activity and the 
importance of Care Group programming with NCTs in terms of the activity’s overall budget and as well in 
terms of spending per participant. 
IMPEL | Implementer-Led Evaluation and Learning
4 Introduction
1.3 Purpose of the Baseline Survey
As part of the RCT, impacts are measured primarily based on comparing data from follow-up rounds of 
surveying (e.g. from an endline survey) between experimental groups. The baseline survey in contrast, 
serves the following purpose: 
1. Basic description of the study sample. Basic summary statistics from the baseline survey allow 
the description of the study sample including important demographic characteristics and key 
characteristics related to the interventions before the rollout of the Titukulane interventions 
take place.
2. Heterogeneity of impacts by subgroups. Baseline data allows testing for whether the Titukulane 
interventions impacted certain subgroups differently. 
3. Describing time trends. Multiple rounds of data collection allow for a description of how key 
income and food security outcomes changed among households in the study areas over time, 
which can be valuable background information to interpret impact results measured at follow￾up surveys. 
4. Statistical precision. When estimating the impact of the Titukulane interventions using 
indicators collected at endline, controlling for the baseline value of the indicator in the 
regression analysis will improve the statistical precision of the estimate of impact. 
Additionally, the data obtained in the baseline survey will help support CIM’s programming decisions 
and reporting requirements. IPA collected data on certain USAID indicators, selected in consultation 
with BHA staff, to inform BHA on the resilience capacities of study sample households before the rollout 
of the activity.
The baseline indicators presented in this report were selected to provide a basic description of the 
sample and to present information relevant to some of the key interventions as identified by the 
implementer during the design phase. For this reason, this report focuses on the demographic 
characteristics of the study sample and indicators related to household income and livelihood activities, 
food security and nutrition.
Baseline Report of the Titukulane RFSA in Malawi (Vol. I)
Methodology 5
2. METHODOLOGY
2.1 Study Area
Titukulane’s implementation area consists of all villages of 19 Traditional Authorities (TAs) in Southern 
Malawi, nine in Mangochi and 10 in Zomba. The RCT focuses on a subset of 10 TAs in which 
interventions related to all three purposes, including Purpose 2, are taking place. In the remaining nine 
TAs, Purpose 2 interventions are not being carried out. We refer to the 10 TAs where Purpose 2 
interventions are being carried out as “P2 TAs”.1
The RCT focuses on P2 TAs to improve the study’s ability to accurately measure the programs full 
benefits and to capture specifically the impacts of P2 programming. The latter both represents a large 
share of the activity’s budget and targets key indicators of success of the activity, namely child growth 
and nutrition.
Since the focus of the study and related data collection is on P2 TAs only, the evaluation estimates the 
impact of the Titukulane interventions in TAs where all program components (from Purposes 1, 2, and 3) 
are being implemented and will not measure the impact in areas where Purpose 2 interventions are not 
being carried out (but Purpose 1 and Purpose 3 are).
2.2 Sampling Strategy
IPA sampled households for recruitment into the study from all 10 P2 TAs. First, 28 Group Village Heads 
(GVHs) were randomly sampled from each TA, with the number of GVHs sampled per TA proportional to 
the number of Tier 1 households in each TA (according to Titukulane listing data). All 358 villages from 
the 28 sampled GVHs were included in the study. 
The sampling of households within sampled villages was designed as follows. IPA sampled a target 
number of households from Tiers 1, 2 and 3. Tier 4 was excluded because Tier 4 households are not 
eligible for any intervention under Titukulane. Tier 1 households were oversampled relative to Tier 2 and 
Tier 3 households. Households from the Tier 1 sample were then screened for whether they contained a 
pregnant woman or a child under 2. All households for which this was true were invited to participate in 
the baseline survey. We refer to these screened-in Tier 1 households as the Care Group stratum 
(“T1CG”). A random subset of those that were screened out—i.e. of the “Tier 1, screened-out”—was 
also selected for recruitment into the study, at a rate that in expectation was the same as that applied to 
Tier 2 and Tier 3 households (assuming a Tier-1 screen in rate of 40%). The sampling strategy is 
graphically summarized in Figure 1 below. 
The strategy was designed to oversample households from the T1CG stratum relative to the other three 
strata (Tier 1 screened-out, Tier 2, and Tier 3). IPA sampled 6,949 households from Tier 1 (for further 
screening), 878 from Tier 2 and 172 from Tier 3 (for baseline interviews without further screening), for a 
total of 7,999 sampled households in 358 villages across 10 TAs and 28 GVHs.
 1 In Mangochi, these are Chilipa, Chiunda, Chowe, Namabvi and Ntonda; in Zomba, these are Chikowi, Kuntumanji, Malemia, 
Mlumbe and Mwambo.
IMPEL | Implementer-Led Evaluation and Learning
6 Methodology
Figure 1: Overview of sampling strategy
IPA optimized the research design, sampling strata and sample sizes within the evaluation budget and 
calculated the minimum detectable effect (MDE) to ensure it was sufficient based on previous literature. 
In particular, the 80%-power MDE on the Height-for-Age z-score for a two-sided test with a size of 5%, 
assuming an interclass correlation of 10% and a baseline R2 of 68% (from a recent similar study in Rwanda) 
is about 0.15 standard deviations among the T1CG stratum.
2.3 Baseline Sample Size
IPA teams administered screenings and interviews to targeted households in the sampled villages 
between August and November 2021.2 Out of the target number of 6,949 Tier 1 households to be 
screened, 6,263 were successfully screened. Out of the latter group, 29% (N = 1,827) were screened in 
and interviewed for the baseline survey. This group forms the T1CG stratum. In addition, 306 out of 
those that were screened out were interviewed. This group makes up the screened-out Tier 1 stratum of 
households. Finally, 821 Tier 2 and 153 Tier 3 households were interviewed. This information is 
summarized in Table 3. In total, the survey team interviewed 3,107 households, for an average of 8.7 
households per village. Out of the total, 1963 households were interviewed in Zomba and 1171 in 
Mangochi.3
 2 Note that IPA interviewed additional households in areas that were dropped from the study after being informed that one of 
the TAs (Nkapita) where data collection had already started would no longer be receiving P2 interventions. These interviews are 
not included in the counts in this section, which focuses on areas where the study will take place. Initially, Titukulane provided a 
list of TAs that that designated 12 of them as P2. During the first week of baseline data collection, Titukulane advised IPA to drop 
two TAs (Nkapita and Ntholowa) because the Malawi Government was implementing a program similar to Titukulane in these 
TAs. IPA dropped these two TAs and added additional sampling units in the remaining 10 P2 TAs. Fieldwork paused for three days 
after IPA finished interviews in the originally sampled areas while waiting for information about where to recruit additional
households as replacements for the dropped TAs.
3 Note that the sampling plan had another 91 Tier-1 screened-out households scheduled to be interviewed in Mangochi as well 
as an additional 4 in Zomba. However, due to a programming mistake they were skipped. IPA will aim to recruit the missed 
households as part of future follow-up surveying. 
Baseline Report of the Titukulane RFSA in Malawi (Vol. I)
Methodology 7 
Table 3. Sample
Number of Surveys
Overall Zomba Mangochi
Total 3,107 1,936 1,171
Tier 1, screened in (“T1CG”) 1,827 1,080 747
Tier 1, screened-out 306 298 8
Tier 2 821 423 398
Tier 3 153 135 18
IPA’s field team also collected anthropometric measurements from 1,491 (from all T1CG households and 
from a 10% random subsample of all remaining survey strata), in which weight and height were taken 
from 1,921 and 1,812 children respectively.
2.4 Random Assignment and Balance
The unit of randomization was a “village group” which was either equal to a single village or group of 
villages (small villages of fewer than 13 households were grouped with other small villages in the same 
GVH to form a village group). The randomization of a total of 253 units was stratified by GVH and by 
above-median village share of Tier 1 households and resulted in 129 village groups assigned to 
Treatment, 124 to Control. 
Appendix Table 19 confirms that households in treatment villages are comparable to control villages. 
Testing for differences of means between the two groups we find no substantively large or statistically 
significant differences across several groups of outcomes. 
Responses provided during the baseline were not used in the assignment of villages to the treatment or 
the control group and did not influence the likelihood of households being assigned to treatment. 
Random assignment was not revealed to Titukulane before the completion of the baseline survey. 
Assignments were shared only after the completion of the baseline survey to avoid interactions with 
households starting prematurely, which could have influenced responses during the baseline survey.
2.5 Baseline Questionnaire Development
IPA developed the questionnaires for the baseline survey in consultation with BHA and CIM. IPA held 
meetings with BHA and Titukulane Project Management Unit where BHA indicators were discussed and 
the team agreed on modules to include in the baseline questionnaires. The baseline survey had two 
parts, a household survey and an anthropometric survey.
2.5.1 Household Survey
The household survey was carried out as an in-person interview administered with the household head 
(56%), their spouse (37%) or another household member knowledgeable about the household’s affairs 
(7%). Responses were collected using the SurveyCTO software. The household survey had two survey 
variations: a long and a short survey. The long survey was administered to the T1CG sample only since 
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8 Methodology
the T1CG sample is a focal group for the evaluation. All other sampled households (Tier 1 and Tier 2) 
received the short survey. The short survey had fewer modules and focused on basic household 
information (e.g. demographics, household income sources) and covering certain BHA indicators (e.g. 
consumption poverty, food security, or farming practices) while the long survey had both basic modules 
and additional modules.
2.5.2 Baseline Anthropometric Survey
The anthropometric survey was administered to all children under 5 years in T1CG sample households 
and in a 10% random subsample of households from the remainder of the sample. IPA recorded the 
children’s heights and weights using standard anthropometric equipment and the measurements were 
recorded in SurveyCTO. See annex materials for additional details on the protocol and anthropometric 
survey instrument.
Baseline Report of the Titukulane RFSA in Malawi (Vol. I)
Fieldwork Organization and Challenges 9 
3. FIELDWORK ORGANIZATION AND CHALLENGES
3.1 Field Organization
3.1.1 Team Composition
The Titukulane baseline fieldwork and data management was led by IPA’s Research Associates, John 
Tengatenga and Aziz Bunyiza respectively. Three IPA Research Coordinators, Monica Shandal, Wiza 
Ng’ambi and Rafael Panlilio, worked on coordination of research activities. Emily Bream, Lasse Brune, 
Jessica Goldberg, Dean Karlan, and Craig McIntosh are the Principal Investigators for the evaluation.
A team of 32 surveyors, eight supervisors, eight anthropometric surveyors, three Field Managers, and 
eight backcheckers4 was recruited and trained for data collection. The team was divided into two 
groups, one based in Zomba and the other in Mangochi. Data collection took place from August 25th to 
November 19th, 2021. The baseline data was collected on Lenovo ThinkPad tablets using the SurveyCTO 
application and uploaded to the SurveyCTO server after every day of fieldwork.
3.1.2 Pilot Test Survey Training
Before training the enumerators, the survey instruments were bench tested and piloted to fine-tune 
them, to ensure that the questions flowed well, to ensure logic patterns were well implemented and to 
estimate the duration of the interviews. Two further pilot tests were conducted during the training that 
took place between August 17th and September 1st, 2021. The training introduced enumerators to the 
survey instruments and explained the survey questions and procedures using the training manual, 
anthropometric protocol, and survey replacement guidelines. 
During training, the enumerators practiced administering the survey instruments through role-playing 
by interviewing each other. A pilot test was conducted in one village, not part of the study sample, to 
allow enumerators to practice administering the baseline and taking anthropometric measures in a real 
field setting and trouble-shoot any bugs in the programmed survey versions. Subsequently, a debriefing 
session was held in which enumerators shared their experiences and clarified issues that emerged 
during the pilot test. A few changes were made to the logical patterns and other sections of the survey 
based on the enumerators’ observations and recommendations.
3.1.3 COVID-19 Protocol
To minimize the adverse effects of the COVID-19 pandemic on staff and respondents, IPA established a 
protocol for COVID-19. Each enumerator was equipped with a copy of this protocol. The protocol was 
applied from the first day of training and enforced throughout the baseline activities. Enumerators were 
encouraged to get vaccinated and IPA worked with the United Nations Health Malawi group to support 
their vaccination. Furthermore, all enumerators were tested for COVID-19 by officials from Zomba 
 
4 Backcheckers are field auditors who visit a subsample of respondents a second time to re-administer a selection of questions 
from the original questionnaire. Those backcheck responses are then compared to the original responses. Backchecks allow the 
fieldwork team to identify discrepancies between answers, and thus to identify problems in the data collection process.
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10 Fieldwork Organization and Challenges
District Health Office on the first day of the training to ensure that only those who tested negative 
attended the training. The training sessions were conducted in a well-ventilated room. 
3.1.4 Replacement Strategy
A replacement guideline was developed for enumerators to spell out how the field team were to go 
about replacing respondents who could not be surveyed. Enumerators were required to interview either 
the head of the household, spouse of the household head, or a knowledgeable person in the household. 
A household would be replaced after two unsuccessful attempts at finding the right person to interview. 
Each attempt would be documented and sent to the server. On the second failed attempt, the 
supervisor provided the replacement to the enumerator from a list of the replacements that each team 
supervisor was given. Replacements were taken from the same tier as the original respondents, going 
from the top of a replacement list that was randomly ordered.
3.1.5 Data Quality Checks
High-Frequency Checks (HFCs) were performed daily on incoming data using Stata, a statistical software. 
HFCs were performed to identify and resolve outliers in the data, logical inconsistencies, and missing 
data. Issues that were observed during HFCs were followed up with specific enumerators the morning 
after, before sending the teams to the field. In a few cases, follow-ups were conducted with 
respondents to ensure the correct information was captured. Besides addressing outliers and other 
issues with the particular enumerators who encountered them, all teams were briefed about the issues 
discovered from conducting the HFCs.
IPA also instituted backchecks on 10% of the households surveyed. Backcheckers had a survey that was 
used to ensure that sections were not skipped, questions were prompted correctly, and responses were 
not made up by enumerators. Each enumerator was backchecked at least every 3 days and any 
discrepancies in the responses were followed up and clarified.
Field teams were accompanied by field managers to ensure that enumerators were following the 
procedures and asking questions correctly. Field managers would randomly sit-in on any interview and 
perform spot checks in sampled areas to ensure that the target respondents were interviewed.
3.1.6 Survey Productivity
During field planning, IPA planned that each enumerator would complete between four and five of the 
longer interviews administered to the Tier-1 Care Group eligible group per day or six of the shorter 
surveys administered to the Everyone Else group. This estimation meant that IPA would be able to 
complete data collection within two and a half months (from mid-August to the end of October). Due to 
a number of factors outlined below, including difficulty locating target households and distances 
between respondents in a given village, field officers were able to do an average of only 2.63 interviews 
per day. IPA completed data collection in November instead of October, as planned.
Baseline Report of the Titukulane RFSA in Malawi (Vol. I)
Fieldwork Organization and Challenges 11
3.2 Challenges
3.2.1 Names of Respondents Not Known in Sampled Villages
It was observed that in Mangochi some respondents were known by their informal names, which are 
different from the names on IPA’s list of target respondents. This made it hard to track these 
respondents in their communities especially when the next of kin was not known. For example, 
Mlongoti village in TA Ntonda in Mangochi is a large village and about 30% of the target respondents 
were not known to the GVH and other community residents. To address this issue, CIM shared its sign-in 
sheets for some of the villages in Mangochi and Zomba with IPA. However, the sign-in sheets shared by 
CIM did not have all the target respondents in IPA’s sample. Although this challenge did not have a 
significant impact on data collection, IPA teams spent more time in these villages inquiring about these 
respondents as they could not be identified easily. 
3.2.2 Villages Placed on Wrong GVH List
Survey teams found that several villages listed as belonging to a particular GVH did not belong to that 
GVH. Some of these villages belonged to GVHs that were not in the sample. All these instances were 
brought to the attention of the CIM contact person. Some of the villages that faced this challenge were 
Kuminyanga and Gibbisani in GVH Kimu, Justin and Mjojo in GVH Chidothe, Nkapungwa in GVH Kaunde, 
and Kamwaza and Nkupe 1 in GVH Mkwapatira.
3.2.3 Respondents’ Expectations
During the screening for Tier-1 households, some households reported that they had children under 2 
years old even when they did not. The households presumably expected that there were monetary or 
other benefits related to having children and participating in the survey despite that the consent made 
clear that there were no benefits for taking part in the survey. These households failed to present their 
children for the anthropometric measurements. Survey backcheckers or anthropometric enumerators 
reported this issue after backchecking the households and several attempts to track the children who 
were not interviewed during the first visit. A total of 15 households did this and these interviews were 
dropped from the server.
3.2.4 Children Not Available for Anthropometric Measurement
The majority of parents agreed to have their children’s anthropometric measures taken and even 
facilitated the recording of their measurements. However, in some households, eligible children were 
not available on the day of the interview. Even with two attempts, a total of 41 children were still not 
available and the parents indicated the children were away with other adults in household.
3.2.5 Handling Children during Anthropometric Measurements
In about 50 cases, children were afraid to step on the scale or height board to have their anthropometric 
measurements taken. Their guardians indicated that this was probably because the children thought the 
enumerators were from the local hospital and feared the prospect of an injection, common during 
vaccination. In almost all the cases, the guardians were able to convince the children to have their 
anthropometric measurements taken.
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12 Descriptive Statistics
4. DESCRIPTIVE STATISTICS
The following tables present estimates of means and their 95% confidence intervals for a range of 
variables collected at baseline. Where the data is available, values are shown separately for two 
populations. First, we show estimates for the population of all households from Tiers 1, 2, 3 which 
represents the set of those households who could in principle qualify for some Titukulane intervention, 
labeled “All”. Second, we show estimates for the population of households in the Tier 1 Care Group 
stratum (see Sampling section for details), labeled “T1CG”. Mean estimates are computed using 
sampling weights that reflect the probability of a given household being sampled and as such are 
representative of the two populations just described. The “All” sample includes the “T1CG” sample and 
sample weights are used to appropriately account for the fact that the “T1CG” stratum was oversampled 
(by design). 
4.1 Household Demographics
Table 4 shows descriptive statistics on household demographics. Overall 37% of households are headed 
by women and 66% of household heads are married. The average age among household heads is 42 
years. Education levels among household heads are low: 19% have no formal education, 57% have some 
primary schooling, and only 4% completed secondary school. Additionally, 43% of households are 
Christian and 56% are Muslim. The Tier-1 Care Group eligible stratum has broadly similar household 
characteristics to the overall sample.
Table 4. Household demographics
Description
All T1CG only
95% – C.I. 95% – C.I.
Mean N Lo Hi Mean N Lo Hi
Female household head 37% 3,107 34% 41% 40% 1,827 35% 46%
Household (HH) head is married 66% 3,107 62% 69% 66% 1,827 61% 71%
Age of household head 41.66 3,107 40.68 42.65 40.40 1,827 38.76 42.04
Level of education of household head
No formal schooling 19% 3,107 17% 22% 22% 1,827 18% 26%
Some primary schooling 57% 3,107 53% 61% 55% 1,827 50% 59%
Primary school completed 6% 3,107 4% 7% 6% 1,827 4% 8%
Some secondary school 11% 3,107 8% 13% 10% 1,827 8% 13%
Secondary school completed 4% 3,107 3% 5% 4% 1,827 3% 6%
Number of children under...
16 years of age 2.67 3,107 2.52 2.83 2.93 1,827 2.78 3.08
5 years of age 0.92 3,107 0.85 0.99 1.24 1,827 1.15 1.33
Baseline Report of the Titukulane RFSA in Malawi (Vol. I)
Descriptive Statistics 13 
Description
All T1CG only
95% – C.I. 95% – C.I.
Mean N Lo Hi Mean N Lo Hi
2 years of age 0.39 3,107 0.36 0.42 0.79 1,827 0.73 0.85
Religion
Christian 43% 3,050 33% 53% 51% 1,786 44% 59%
Muslim 56% 3,050 47% 66% 48% 1,786 40% 56%
4.2 Sources of Income
IPA collected data on household income sources over the previous 12 months, summarized in Table 5. 
Overall, the most frequently listed sources of income or food considered to be most important for 
households are farming (55%) and agricultural wage labor (18%), non-agricultural wage labor (8%) and 
non-agricultural self-employment (6%). In the T1CG sample, relative to the study sample overall, wage 
labor is relatively more important and farming relatively less important as an income sources.
Table 5. Household sources of income over the last 12 months
Description
All T1CG only
95% – C.I. 95% – C.I.
Mean N Lo Hi Mean N Lo Hi
Sources of food/income
Farming/crop production and sales 67% 3,107 61% 72% 65% 1,827 60% 70%
Agricultural wage labor 34% 3,107 29% 39% 46% 1,827 40% 52%
Non-agricultural wage labor 18% 3,107 15% 21% 24% 1,827 21% 28%
Other self-employment (non-agricultural) 9% 3,107 7% 11% 9% 1,827 6% 12%
Other self-employment (agricultural) 7% 3,107 5% 8% 5% 1,827 3% 6%
Other 14% 3,107 11% 17% 11% 1,827 8% 13%
Most important source of income/food
Farming/crop production and sales 55% 3,107 48% 62% 50% 1,827 45% 55%
Agricultural wage labor 18% 3,107 14% 22% 26% 1,827 21% 30%
Non-agricultural wage labor 8% 3,107 6% 11% 11% 1,827 9% 14%
Other self-employment (non- agricultural) 6% 3,107 4% 7% 5% 1,827 3% 6%
Other 13% 3,107 10% 17% 9% 1,827 6% 11%
Second important source of income/food
None 60% 3,107 55% 66% 53% 1,827 47% 59%
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14 Descriptive Statistics
Description
All T1CG only
95% – C.I. 95% – C.I.
Mean N Lo Hi Mean N Lo Hi
Agricultural wage labor 14% 3,107 10% 17% 18% 1,827 12% 23%
Farming/crop production and sales 10% 3,107 8% 13% 12% 1,827 8% 15%
Non-agricultural wage labor 6% 3,107 5% 8% 9% 1,827 7% 11%
Other 9% 3,107 7% 11% 8% 1,827 6% 10%
Most important source of cash income
Farming/crop production and sales 45% 3,107 40% 50% 39% 1,827 34% 44%
Agricultural wage labor 23% 3,107 20% 27% 32% 1,827 27% 38%
Non-agricultural wage labor 10% 3,107 7% 12% 13% 1,827 11% 16%
Other self-employment (non- agricultural) 5% 3,107 4% 7% 5% 1,827 3% 7%
None 1% 3,107 0% 3% 1% 1,827 0% 2%
Other 15% 3,107 11% 19% 9% 1,827 7% 11%
4.3 Consumption Poverty Measure
IPA collected data on consumption-based indicators to understand the prevalence of poverty among 
households in the sample. Table 6 reports on (1) percentage of people living on less than $1.90 per day; 
(2) mean percent shortfall of the poor relative to the $1.90 per day threshold5
; and (3) consumption per 
capita per day. Overall, 68% of households live on less than $1.90 per day, the mean percent shortfall of 
the poor relative to the $1.90 per day threshold is 21%, and the average consumption per capita per day 
is $2.19.6 The prevalence of poverty is only somewhat higher in the T1CG sample where 72% of 
households live on less than $1.90 per capita per day and the mean percent shortfall relative to the 
$1.90 per day threshold is 33%. Appendix Table 9 in the appendix provides consumption poverty details 
by household type.
 
5 The mean percent shortfall of the poor is an indicator that measures how far below the poverty threshold of $1.90 per day 
poor households are on average. Households with per capita consumption greater than $1.90 per day are not included in 
calculating this indicator. For more information on the construction of consumption poverty indicators, please see BHA’s 
Indicator Handbook, Part I: Indicators for Baseline and Endline Surveys for Resilience Food Security Activities.
6 Njira and UBALE Development Food Assistance Project (DFAP) final performance evaluations reported that 70% and 65% of 
the people, respectively, were living on less than $1.90 per day. 
Baseline Report of the Titukulane RFSA in Malawi (Vol. I)
Descriptive Statistics 15 
Table 6. Consumption poverty
Description
All T1CG only
95% – C.I. 95% – C.I.
Mean N Lo Hi Mean N Lo Hi
[BL01] HH living on less than $1.90/day per 
capita (PC) 68% 3,089 65% 71% 72% 1,816 68% 76%
[BL02] Mean % shortfall of the poor 21% 2,052 20% 22% 33% 1,213 30% 36%
[BL40] Consumption PC per day (PPP $) 2.19 3,089 2.12 2.26 2.03 1,816 1.92 2.13
Notes: The $1.90 threshold is inflated from 2011 to 2021 using the U.S. Consumer Price Index (CPI), in order to match the year of 
the data collection. Mean % shortfall of the poor indicates the percent shortfall of the poor relative to the per capita $1.90/day 
poverty line. The household consumption aggregate is a predicted value based on 7 (short survey) or 29 (long survey) items of 
food consumptions and information about household composition, which are weighted according to the results from a 
regression model based on the latest 2019/2020 round of Malawi’s Integrated Household survey.
Furthermore, we calculated consumption poverty across main household sources of food or income by 
tier. Variations in poverty levels can be seen across sources of food or income and tiers. For households 
living on less than $1.99 per day per capita, low level of poverty is observed in Tier 1 and Tier 3 
households that depend on other sources of income or food while in Tier 2, low level of poverty is 
observed in households that depend on non-agricultural wage labor. See Appendix Table 14 for more 
details on consumption poverty across main sources of income by tiers. 
4.4 Food Security
IPA collected data on household food security using the Food Consumption Score (FCS) and Food 
Insecurity Experience Scale (FIES) modules. The FCS is an indicator of food intake ranging from 0 to 112, 
with higher scores indicating a higher degree of food security. It is calculated by summing the weighted 
responses to questions asking respondents about the frequency of their household’s consumption of 
eight food groups in the previous 7 days.7
As Table 7 indicates, the sample has an average FCS of 37.9 over a 7-day recall period, with 10% of 
households showing poor food consumption, 37% of households showing borderline food consumption, 
and 53% of households showing adequate food consumption.8 Furthermore, cereals, grains and cereals 
products, condiments, and vegetables are the most consumed food groups over a 7-day period, 
compared to other less consumed foods like fruits, roots, tubers and plantains, nuts and pulses, and 
milk. See Appendix Table 6 for specific foods consumed by the household in the past week. Households 
in the T1CG stratum are on average worse-off in terms of food security, with average FCS of 35.2. Refer 
to Appendix Table 10 for FCS details by household type. We also calculated FCS by main household 
income sources and this is shown in Appendix Table 12.
 
7 For more information on the FCS and FIES questionnaires and indicator construction, please see BHA’s Indicator Handbook, 
Part I: Indicators for Baseline and Endline Surveys for Resilience Food Security Activities. 8 Data collection was done between August and November, which is several months out from the last rainy season harvest but 
much before the peak of “lean season” right before harvest. The timing may matter especially for outcomes such as the FCS, 
which is based a 7-day recall period.
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16 Descriptive Statistics
Table 7. Food Consumption Score and Food Insecurity Experience Scale
Description
All T1CG only
95% – C.I. 95% – C.I.
Mean N Lo Hi Mean N Lo Hi
FCS score, 7 day recall 37.87 3107 36.79 38.96 35.22 1,827 33.93 36.51
[BL10] FCS Categories:
Poor 10% 3,107 8% 13% 15% 1,827 11% 20%
Borderline 37% 3,107 34% 40% 37% 1,827 33% 41%
Adequate 53% 3,107 49% 57% 48% 1,827 42% 53%
Over the past 7 days, no. of days consumed:
Cereals, Grains and Cereal Products 6.39 3,107 6.29 6.50 6.29 1,827 6.19 6.39
Condiments 5.08 3,107 4.56 5.61 4.71 1,827 4.30 5.11
Vegetables 4.39 3,107 4.19 4.59 4.07 1,827 3.76 4.37
Oil 2.48 3,107 2.17 2.78 2.20 1,827 1.96 2.43
Meat, Fish and Animal Products 2.51 3,107 2.35 2.67 2.50 1,827 2.30 2.70
Fruits 1.92 3,107 1.63 2.21 1.72 1,827 1.45 1.99
Roots, Tubers and Plantains 1.43 3,107 1.29 1.58 1.24 1,827 1.09 1.40
Nuts and Pulses 1.83 3,107 1.65 2.02 1.44 1,827 1.28 1.61
Sugar 1.13 3,107 0.98 1.29 0.89 1,827 0.72 1.07
Milk 0.22 3,107 0.15 0.30 0.12 1,827 0.08 0.17
FIES: Prevalence of moderate or 
severe food insecurity in the last 12 
months
97% 3,107 79% 100% 97% 1,827 74% 100%
[BL06] Raw FIES Score 7.08 3,107 6.95 7.21 7.32 1,827 7.23 7.42
During the past 12 months, because of a lack of money or other resources, you or others in your household…
...worried you wouldn't have 
enough to eat 92% 3,107 90% 93% 93% 1,827 91% 95%
...unable to eat healthy and 
nutritious food 94% 3,107 93% 96% 95% 1,827 94% 97%
...ate only a few kinds of foods 94% 3,107 93% 96% 96% 1,827 95% 98%
...had to skip a meal 91% 3,107 89% 94% 94% 1,827 93% 96%
...ate less than you thought you 
should 94% 3,107 92% 96% 96% 1,827 95% 98%
...did not have food 90% 3,107 87% 94% 95% 1,827 93% 96%
Baseline Report of the Titukulane RFSA in Malawi (Vol. I)
Descriptive Statistics 17 
Description
All T1CG only
95% – C.I. 95% – C.I.
Mean N Lo Hi Mean N Lo Hi
...were hungry but did not eat 93% 3,107 91% 94% 95% 1,827 93% 96%
...went without eating for a whole 
day 59% 3,107 53% 65% 68% 1,827 63% 72%
Notes: FCS; < 21 = poor, 21.5–35 = borderline; > 35 = acceptable
The Raw FIES Score is a sum of the 8 FIES binary questions (higher = more food insecure)
The results of the FIES module show that there are high levels of experience with food insecurity among 
surveyed households. There is both a high prevalence of moderate or severe food insecurity and on 
average households experience most forms of food insecurity in the 12 months prior to the survey. 
Results from the eight FIES questions administered show that most households report being worried 
about not having enough food to eat, being unable to eat a healthy meal and nutritious food, only 
eating a few kinds of foods or having to skip a meal or eating less than they thought they should. The 
same high levels of food insecurity are present in the T1CG sample. Additionally, more Tier-1 Care Group 
households (65%) went without eating a whole day compared to the rest of the group (59%). Further 
disaggregation of FIES by household type is shown in Appendix Table 11. Appendix Table 13 and 
Appendix Figure 1 show that FCS and Household Food Insecurity Access Scale scores and their 
components are highly correlated. 
4.5 Farming and Land Ownership
IPA collected household-level information about basic farming practices, land ownership besides the 
home, and crop cultivation. Overall, ownership of land is high among sampled households, with 80% of 
the sample owning any land other than where the home is located. On average, households own around 
1.04 acres of land. A majority of households (93%) cultivated crops in the 12 months prior to the survey. 
Maize, pigeon peas, groundnuts and cassava are the four most common crops cultivated by households 
and maize is cultivated by almost every household that engages in farming (98%). Maize was also 
considered by 89% of farming households as the most important crop cultivated in the rainy season. 
Furthermore, 17% of farming households cultivated land in the dry season, with the most common 
crops cultivated in the dry season being tomatoes, maize, pumpkin leaves, sweet potatoes and 
vegetables. Among the T1CG sample, 75% own land, with households owning on average 1.02 acres of 
land. About 90% of the households cultivated crops in the 12 months prior to the survey. Similar to the 
rest of the sample, the majority of Tier-1 Care Group eligible households consider maize as the most 
important crop cultivated in the last rainy season, with almost all households cultivating maize in that 
season. 
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18 Descriptive Statistics
Table 8. Crops cultivated
Description
All T1CG only
95% – C.I. 95% – C.I.
Mean N Lo Hi Mean N Lo Hi
HH owns land, not including plot with
home 80% 3,107 77% 84% 75% 1,827 69% 81%
HH cultivated anything in the last 12 
months 93% 3,107 90% 95% 90% 1,827 87% 93%
Total area of agricultural land (in acre) 1.04 2,427 0.99 1.09 1.02 1,374 0.99 1.05
During the last rainy season cultivation:
Maize 98% 2,831 97% 99% 98% 1,639 97% 99%
Pigeon peas 40% 2,831 35% 45% 43% 1,639 38% 48%
Groundnuts 23% 2,831 13% 33% 12% 1,639 8% 15%
Cassava 10% 2,831 8% 12% 8% 1,639 6% 11%
Bean 8% 2,831 4% 12% 8% 1,639 4% 11%
Vegetables 4% 2,831 3% 6% 6% 1,639 4% 8%
Rice 7% 2,831 5% 9% 6% 1,639 4% 9%
Sorghum/millet 5% 2,831 3% 7% 5% 1,639 3% 7%
Sweet potatoes 4% 2,831 2% 5% 4% 1,639 2% 5%
Most important crop cultivated last rainy season:
Maize 89% 2,831 87% 92% 89% 1,639 86% 92%
Rice 2% 2,831 1% 3% 2% 1,639 1% 3%
Pigeon peas 3% 2,831 1% 4% 3% 1,639 1% 4%
Other 6% 2,831 3% 8% 6% 1,639 4% 8%
Cultivated any land in this dry season 17% 2,831 15% 20% 16% 1,639 13% 19%
Crops cultivated in the dry season:
Tomatoes 30% 579 21% 39% 31% 336 23% 39%
Maize 29% 579 20% 37% 28% 336 21% 36%
Pumpkin leaves 22% 579 13% 31% 19% 336 10% 29%
Sweet potatoes 10% 579 5% 14% 14% 336 9% 19%
Vegetables 8% 579 3% 13% 7% 336 3% 10%
Other 34% 579 26% 42% 28% 336 20% 36%
IPA collected data on households’ use of farming inputs in the previous rainy season. Overall, 67% of 
households that grew something in the previous rainy season used inorganic fertilizer, 47% of them used 
Baseline Report of the Titukulane RFSA in Malawi (Vol. I)
Descriptive Statistics 19 
organic fertilizer, and 48% used packed seeds when cultivating crops. Few households used herbicides, 
hired any labor to help with farming tasks, or rented farming equipment or animals during the previous 
rainy season. Compared to the rest of the households, a smaller percentage of Tier-1 Care Group eligible 
households used organic fertilizer, inorganic fertilizer, and packaged seeds, as Table 9 indicates. 
Table 9. Farming inputs
Description
All T1CG only
95% – C.I. 95% – C.I.
Mean N Lo Hi Mean N Lo Hi
In the last rainy season…
Used any organic fertilizer 47% 2,831 43% 51% 41% 1,639 36% 45%
Used any inorganic fertilizer 67% 2,831 62% 72% 62% 1,639 56% 68%
Used any packed seeds 48% 2,831 43% 52% 45% 1,639 40% 51%
Used any pesticides or herbicides 8% 2,831 6% 10% 7% 1,639 5% 8%
Hired any labor to help with farming tasks 9% 2,831 7% 12% 4% 1,639 3% 5%
Rented any farming equipment 2% 2,831 1% 3% 2% 1,639 1% 3%
Rented any farming animals 0% 2,831 0% 1% 0% 1,639 0% 1%
Used any irrigation last dry season 96% 579 93% 99% 98% 336 96% 99%
Type of irrigation used last dry season:
Water can, pail or bucket 81% 560 74% 88% 75% 327 67% 83%
Other 9% 560 4% 13% 13% 327 6% 20%
Flooding 4% 560 2% 6% 4% 327 2% 7%
Treadle pump 2% 560 1% 3% 3% 327 1% 4%
Drip irrigation 1% 560 0% 2% 1% 327 0% 2%
Hose pipe 1% 560 0% 1% 0% 327 0% 0%
Sprinkler 4% 560 2% 7% 5% 327 2% 8%
Notes: This section was administered only to HH who cultivated anything in the last rainy season or in the last dry season.
IPA also collected information on the types of irrigation used by the households that cultivated crops in 
the dry season. Table 9 shows that 96% of the households that cultivated something in the dry season 
used some form of irrigation. Of those, 81% of these households used water cans, pails, or buckets to 
irrigate crops. 
4.6 Farming Practices
This section focuses on sample households’ use of crop improvement management practices or 
technologies and natural resources management practices 12 months prior to the survey. Table 10 
shows that 86% of the households applied improved farming management practices or technologies in 
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20 Descriptive Statistics
the 12 months before the survey. Some of the improved practices most used include early planting or 
planning with first rains, regular monitoring of crops for pests, application of manure, intercropping, 
modern crop varieties and physically removing pests. Practices such as weed control, mulching and crop 
rotation are the least used practices. Adoption of improved farming practices is slightly lower among 
T1CG households compared to the overall sample, with 81% of Tier-1 Care Group eligible households 
adopting any crop improvement practices. Appendix Table 8 provides additional details on farming 
practices and their application to different crops. 
Table 10. Farming practices
Description
All T1CG only
95% – C.I. 95% – C.I.
Mean N Lo Hi Mean N Lo Hi
[BL21] Applied targeted improved mgmt. 
practices or tech. (A or B below) 88% 3,107 84% 91% 82% 1,827 76% 88%
A. Has applied any improved mgmt. 
practices or tech. in the past 12 months 86% 3,107 83% 90% 81% 1,827 75% 87%
Type of improved management practices or technologies used:
Early planting or planting with first rains 71% 2,653 67% 75% 68% 1,534 64% 73%
Regular monitoring of crop for pests 54% 2,653 48% 60% 54% 1,534 49% 60%
Manure 49% 2,653 45% 53% 43% 1,534 39% 48%
Intercropping 46% 2,653 40% 52% 44% 1,534 39% 48%
Modern (hybrid/improved) crop varieties 45% 2,653 41% 49% 41% 1,534 37% 45%
Physically removing pests 33% 2,653 29% 37% 33% 1,534 29% 37%
Application of locally-made pesticides 8% 2,653 6% 11% 10% 1,534 7% 13%
Weed control 7% 2,653 6% 9% 6% 1,534 4% 7%
Mulching 6% 2,653 4% 7% 6% 1,534 3% 8%
Crop rotation 5% 2,653 2% 8% 3% 1,534 1% 4%
Introducing insects to remove pests 0% 2,653 0% 0% 0% 1,534 0% 0%
B. Has applied any natural resource 
mgmt. practices in the past 12 months 27% 3,101 23% 31% 23% 1,822 19% 27%
Type of natural resource management practices used:
Management of forest plantation 59% 819 52% 65% 66% 432 58% 74%
Regeneration of natural landscapes 49% 819 42% 55% 50% 432 42% 57%
Agro-forestry 37% 819 31% 44% 32% 432 25% 39%
Management/protection of watersheds/
water catchments 30% 819 23% 36% 39% 432 31% 47%
Baseline Report of the Titukulane RFSA in Malawi (Vol. I)
Descriptive Statistics 21 
Description
All T1CG only
95% – C.I. 95% – C.I.
Mean N Lo Hi Mean N Lo Hi
Other 10% 819 5% 14% 14% 432 8% 19%
Notes: Mgmt. = management. Tech. = technologies. 
Besides collecting information on crop farming practices, IPA also collected information on livestock 
management practices. This includes types of livestock and livestock structures owned by households, 
and livestock management practices such as vaccination and use of services from an animal health 
worker. Summary statistics for livestock assets and livestock practices are in Appendix Table 4 and 
Appendix Table 5, respectively. 
4.7 Farmer Groups
IPA collected information on membership in farmer groups and cooperatives and on group activities 
among households that cultivated crops in the 12 months prior to the survey. Households were asked if 
they are a member of farmer group or cooperative. As Table 11 indicates, a very small group of 
households (4%) are members of farmer groups or cooperatives. Among that small group of households, 
31% of them met in the previous rainy season to organize the sale of farm products as a group. The
activities that members of farmer groups engage in to organize their sales include finding markets or 
buyers with good prices as a group, sharing crop transportation and calling buyers to pick up crops as a 
group. 
Table 11. Farmer groups
Description
All T1CG only
95% – C.I. 95% – C.I.
Mean N Lo Hi Mean N Lo Hi
HH is member of a farmer group/coop. 4% 2,831 2% 5% 3% 1,639 2% 5%
Met with other farmers last rainy season 
to organize some sales as a group
31% 140 15% 46% 22% 68 9% 34%
Activities performed to organize sales as a group:
Find markets or buyers with good prices 69% 30 34% 100% 68% 15 34% 100%
Share transport to market 64% 30 38% 91% 24% 15 0% 53%
Call buyer to pick up crop 15% 30 0% 35% 9% 15 0% 24%
Notes: This section was administered to HH who cultivated anything in the last 12 months only. Confidence intervals for binary 
indicators are based on Normal approximations; for very small samples and indicator values near 0 or 1, these confidence 
intervals can exceed 0 or1 and in this table confidence interval bounds are censored at 0 from below and 1 from above. Coop. = 
cooperative.
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22 Descriptive Statistics
4.8 Agricultural Sales
Besides collecting information on crops cultivated, farming practices and farmer groups, IPA asked the 
households whether they sold any of the crops cultivated in the rainy season. Table 12 shows that 44% 
of the households that cultivated any crop in the rainy season sold any of the crops. More households 
sell maize and pigeon peas than those that sell crops like rice groundnuts, beans and sweet potatoes. 
The most common buyers of crops are local traders (either at the market or not) and out-of-town 
mobile traders. A smaller share of households sells their crops to their friends and relatives or at 
regional markets and agricultural cooperatives. 
Table 12. Agricultural sales
Description
All T1CG only
95% – C.I. 95% – C.I.
Mean N Lo Hi Mean N Lo Hi
HH sold crops from last rainy season 44% 2,831 38% 50% 39% 1,639 34% 44%
Rice 62% 286 47% 76% 70% 139 57% 84%
Pigeon peas 50% 1,306 43% 56% 49% 735 42% 56%
Groundnuts 56% 317 44% 69% 47% 151 30% 65%
Sweet potatoes 57% 154 43% 71% 44% 84 19% 69%
Cassava 24% 377 14% 34% 26% 198 12% 39%
Bean 22% 149 12% 33% 22% 78 9% 35%
Vegetables 12% 229 6% 18% 10% 139 3% 17%
Maize 13% 2,747 11% 15% 10% 1,594 8% 13%
Sorghum millet 4% 224 1% 7% 6% 111 0% 14%
HH sold more than half of total output 
(of any crop)
26% 2,831 21% 31% 24% 1,639 20% 29%
Rice 49% 286 36% 62% 60% 139 45% 76%
Groundnuts 32% 317 18% 46% 39% 151 21% 56%
Pigeon peas 34% 1,306 27% 40% 30% 735 24% 35%
Sweet potatoes 41% 154 27% 56% 17% 84 5% 28%
Cassava 14% 377 9% 20% 14% 198 7% 21%
Bean 12% 149 4% 19% 10% 78 2% 17%
Vegetables 11% 229 5% 17% 9% 139 2% 15%
Maize 2% 2,747 1% 3% 2% 1,594 1% 4%
Sorghum millet 2% 224 0% 4% 0% 111 0% 1%
Main buyers across crops (1 main buyer per crop sold):
Baseline Report of the Titukulane RFSA in Malawi (Vol. I)
Descriptive Statistics 23 
Description
All T1CG only
95% – C.I. 95% – C.I.
Mean N Lo Hi Mean N Lo Hi
Local trader at market 44% 1,191 39% 50% 38% 647 32% 44%
Local trader not at market 36% 1,191 30% 41% 40% 647 34% 47%
Out-of-town mobile trader 18% 1,191 14% 23% 16% 647 11% 21%
Relative/Friend 5% 1,191 3% 8% 6% 647 3% 9%
Regional market 2% 1,191 1% 4% 5% 647 1% 9%
Agricultural Cooperative 1% 1,191 0% 1% 1% 647 0% 2%
Other 1% 1,191 0% 2% 1% 647 0% 1%
Notes: This section was administered to HH who cultivated anything in the last 12 months only. Confidence intervals for binary 
indicators are based on Normal approximations; for very small samples and indicator values near 0 or 1, these confidence 
intervals can exceed 0 or1 and in this table confidence interval bounds are censored at 0 from below and 1 from above. 
4.9 Off-Farm Business
In the off-farm business module, IPA asked households about their experiences with owning a business. 
Off-farm business refers to non-agricultural income-generating activities including those that produce or 
trade goods or services, such as owning a shop or operating a trading business, no matter how small. As 
Table 13 indicates, business ownership was low (17%). Among those with a business, the average 
number of years that households have operated their main business is 4 years. A quarter of households 
operating a business had inventories worth more than MWK 50,000, indicating that most of the 
households operate small businesses. 
Table 13. Off-farm business
Description
All T1CG only
95% – C.I. 95% – C.I.
Mean N Lo Hi Mean N Lo Hi
HH operates a business 17% 3,107 14% 20% 14% 1,827 11% 16%
HH operates more than one business 14% 526 10% 19% 16% 281 9% 24%
No. of years operating main business 4.03 526 3.39 4.67 4.67 281 3.54 5.79
Value of business inventory is > MWK 
50,000 25% 526 18% 32% 18% 281 10% 27%
HH owns place it operates the business
from 33% 526 24% 43% 28% 281 18% 37%
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24 Descriptive Statistics
4.10 Access to Targeted Public Services
This section focused on the need and access to targeted public services such as agricultural extension and 
animal and human health advice from government or community workers in the 12 months prior to the 
baseline survey. Starting with agriculture, 18% of households report needing agricultural advice and 
among these households 28% were able to access advice from a government extension worker. Regarding 
advice on animal health, 9% report needing advice and 42% of these households were able to access it. 
About 10% of households received advice from government agricultural extension workers in areas such 
as handling crops after harvest, farming practices, climate-smart agriculture, soil conservation and where 
to buy inputs. 
Table 14 further shows that 34% of households report receiving any advice from community or 
government health or nutritional extension workers. These households mostly receive advice on family 
planning, maternal nutrition during pregnancy, and feeding young children and infants. Furthermore, 14% 
of households indicate participating in a cooking demonstration. 
Table 14. Access to extension services (past 12 months)
Description
All T1CG only
95% – C.I. 95% – C.I.
Mean N Lo Hi Mean N Lo Hi
HH needed advice on agricultural 18% 3,107 15% 21% 16% 1,827 13% 20%
Accessed advice from gov. ext. worker 28% 605 21% 36% 35% 305 27% 43%
HH needed advice on animal health 9% 3,107 6% 11% 7% 1,827 4% 9%
Accessed advice from gov. or community 
animal health extension worker
42% 269 32% 53% 25% 142 12% 37%
HH needed advice on human 
health/nutrition 17% 3,107 14% 20% 16% 1,827 12% 19%
Able to access advice from a government
or a community health worker
58% 567 47% 70% 65% 324 56% 75%
HH received advice from government 
agricultural extension officer 10% 3,107 7% 12% 8% 1,827 6% 10%
Kind of advice received from government extension worker:
Handling of crop after harvest 86% 289 76% 97% 84% 156 76% 92%
Farming practices 82% 289 71% 93% 77% 156 64% 89%
Climate smart agriculture 79% 289 69% 88% 64% 156 49% 80%
Soil and water conservation 83% 289 75% 90% 65% 156 50% 79%
Where to buy inputs 71% 289 59% 82% 66% 156 52% 80%
Prevention of pests/diseases without 
applying chemicals
58% 289 45% 71% 52% 156 39% 66%
Baseline Report of the Titukulane RFSA in Malawi (Vol. I)
Descriptive Statistics 25 
Description
All T1CG only
95% – C.I. 95% – C.I.
Mean N Lo Hi Mean N Lo Hi
Where to sell output 53% 289 40% 66% 59% 156 43% 74%
Prices for output 46% 289 33% 60% 43% 156 28% 58%
HH received any advice from a 
comm./gov. health/nutrition ext. worker
34% 3,107 30% 39% 38% 1,827 33% 44%
From gov. health and nutrition worker 23% 3,107 19% 28% 27% 1,827 23% 32%
From community health and nutrition 
extension worker 28% 3,107 24% 33% 30% 1,827 25% 35%
Received advice on:
Family planning methods 85% 1,153 81% 90% 86% 718 80% 92%
Maternal nutrition during pregnancy 82% 1,153 77% 86% 85% 718 78% 91%
Feeding of young children 78% 1,153 71% 85% 83% 718 77% 89%
Infant feeding 76% 1,153 69% 83% 81% 718 75% 87%
Participated in the cooking 
demonstration 14% 3,107 12% 17% 15% 1,827 12% 18%
Children < 5 screened for malnutrition * 52% 2,125 46% 58% 42% 1,453 37% 46%
Notes: Gov. = government. Ext. = extension. Ag. = agricultural. Comm. = community. *Data for this indicator was only collected 
from HH with children under 5 years old.
4.11 Financial Health
The financial health section of the baseline survey was included to allow us to understand whether 
households would be able to access financial resources to deal with emergencies (like a medical 
emergency) within 30 days. IPA asked the households how difficult it could be to come up with MWK 
10,000 in 30 days, as well as the source where they would get this money from.
Slightly over a quarter of households indicate that they would not be able to raise the money, two-thirds 
said it would be difficult or somewhat difficult to come up with the money, and only 4% of households 
report that it would not be difficult to come up with the money. Among households that would be able 
to come up with the money, regardless of difficulty, 50% report they would obtain the money from 
engaging in informal or piece work; 17% would borrow it from a bank, their employer, or a private 
lender; 20% would sell assets to obtain the money; 9% of households would turn to family, relatives or 
friends to obtain the money; and an additional 3% indicated they would obtain the money through 
other means. 
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26 Descriptive Statistics
Table 15. Financial health
Description
All T1CG only
95% – C.I. 95% – C.I.
Mean N Lo Hi Mean N Lo Hi
Difficulty coming up with MWK 10,000 in next 30 days
Could not come up with funds 28% 3,104 24% 32% 29% 1,825 25% 33%
Difficult 47% 3,104 43% 51% 52% 1,825 47% 56%
Somewhat difficult 20% 3,104 17% 24% 17% 1,825 14% 21%
Not difficult 4% 3,104 3% 6% 2% 1,825 1% 3%
Main source of funds if could come up with funds
Money from informal or piece work 50% 2,142 46% 55% 61% 1,276 55% 66%
Bank/employer/priv. lender (borrow) 17% 2,142 13% 20% 16% 1,276 13% 19%
Selling assets 20% 2,142 16% 24% 13% 1,276 9% 17%
Family, relatives, or friends 9% 2,142 7% 12% 9% 1,276 6% 11%
Other 3% 2,142 2% 5% 2% 1,276 1% 4%
Notes: Priv. = private.
4.12 Savings and Loans
IPA collected data on households’ saving and borrowing practices. Starting with loans, 88% of 
households did not take out a loan in the 12 months prior to the baseline survey, 10% took out a loan 
from a microfinance institution, 2% obtained a loan from a bank, and no one in the sample took out a 
loan from Sacco. Half of households saved money in the 6 months prior to the survey and these 
households mostly kept the money in their pockets or clothes, a secret place at home, or in VSLAs. 
Compared to these other forms of saving, a smaller percentage of households save using mobile money, 
using a box in the household, or with a family member outside the household. Although half of 
households save money, only 11% of all households save cash regularly. 
Table 16 shows that a smaller share of Tier-1 Care Group eligible households took out loans, compared 
to the overall study population. About 91% did not take out a loan, 8% took out a loan from a 
microfinance institution and only 1% took out a loan from a bank. We also find that 44% of Tier-1 Care 
Group eligible households had kept any savings in the 6 months prior to the survey and that, like the 
rest of the study population, Tier-1 Care Group eligible households mostly keep their savings in their 
pockets or clothes, in secret places in the household, and in VSLAs. Only 9% of Tier-1 Care Group eligible 
households save cash regularly. 
Baseline Report of the Titukulane RFSA in Malawi (Vol. I)
Descriptive Statistics 27 
Table 16. Savings and loans
Description
All T1CG only
95% – C.I. 95% – C.I.
Mean N Lo Hi Mean N Lo Hi
In last 12 months, obtained loan from:
None 88% 3,107 85% 91% 91% 1,827 89% 93%
Microfinance institution 10% 3,107 7% 13% 8% 1,827 7% 10%
Banks 2% 3,107 0% 3% 1% 1,827 0% 1%
Sacco 0% 3,107 0% 0% 0% 1,827 0% 1%
Has kept any savings in past 6 months 50% 3,107 46% 54% 44% 1,827 38% 49%
In pocket/clothes/bag that you carry 37% 1,415 31% 43% 44% 811 36% 52%
A secret place in your home 37% 1,415 30% 43% 38% 811 31% 46%
VSLA 33% 1,415 28% 39% 24% 811 18% 30%
Mobile money 13% 1,415 8% 17% 9% 811 6% 13%
With family member outside the HH 6% 1,415 4% 8% 13% 811 1% 24%
Box in the household 9% 1,415 6% 12% 5% 811 3% 7%
Other place 8% 1,415 6% 11% 4% 811 3% 6%
HH saves cash regularly 11% 3,107 8% 13% 9% 1,827 6% 12%
4.13 Children’s Anthropometric Measures
IPA’s anthropometric surveyors measured and recorded the weights and heights of children under the 
age of 5 in the T1CG sample as well as of 10% of children under the age of 5 from the remainder of 
sampled households. Weight and height measurements were used to calculate the prevalence of 
wasted, stunted, and healthy weight children under 5. 
Table 17 provides a breakdown of these three anthropometric measures by age and gender of the 
children. The prevalence of wasted children is 2% in the sampled households. Disaggregated by gender 
and age, we see that wasting among female children is equal to 4% for those 0–23 months old and 2% 
for those 24–59 months old. Among male children, the percentage of wasting is equal to 6% for those 0–
23 months old and wasting among male children 24–59 months old is very rare. The prevalence of 
wasting among children is higher in the Tier-1 Care Group eligible households compared to the overall 
sample. 
The prevalence of stunted children is 41% for the sampled households. The prevalence of stunted 
children is 31% among female children between 0–23 months old, while it is 56% among male children 
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28 Descriptive Statistics
of the same age category. Among children 24–59 months old, 42% of females and 36% of males were 
stunted. 
Furthermore, the prevalence of healthy weight children was 89%. When disaggregated by gender and 
age, 83% and 86% of female and male children 0–23 months old, respectively, had a healthy weight. 
Table 17 shows that healthy weight is also high among female and male children of 24–59 months. 
Appendix Table 15 further breaks down anthropometric measures by age. 
Table 17. Anthropometric indicators for children under 5 years old, by gender and age
Description
All T1CG only
95% – C.I. 95% – C.I.
Mean N Lo Hi Mean N Lo Hi
[BL03] Wasted (Weight-for-height Z￾score (WHZ) < -2) 2% 1,772 0% 4% 6% 1,679 1% 11%
Female
0–23 months 4% 526 2% 5% 5% 516 3% 8%
24–59 months 2% 345 0% 4% 8% 313 0% 20%
Male
0–23 months 6% 559 0% 12% 7% 553 0% 14%
24–59 months 0% 342 0% 0% 1% 297 0% 1%
[BL04] Stunted (Height-for-age Z-score 
(HAZ) < -2) 41% 1,727 31% 51% 37% 1,634 33% 42%
Female
0–23 months 31% 513 17% 46% 25% 503 20% 30%
24–59 months 42% 331 22% 61% 40% 299 31% 48%
Male
0–23 months 56% 552 46% 66% 45% 546 37% 53%
24–59 months 36% 331 17% 55% 40% 286 31% 50%
[BL05] Healthy weight (-2 < WHZ < 2) 89% 1,772 82% 95% 89% 1,679 85% 94%
Female
0–23 months 83% 526 70% 95% 90% 516 87% 93%
24–59 months 91% 345 76% 100% 91% 313 79% 100%
Male
0–23 months 86% 559 78% 94% 86% 553 79% 93%
24–59 months 92% 342 84% 100% 94% 297 90% 98%
Notes: Confidence intervals for binary indicators are based on Normal approximations; for very small samples and indicator 
values near 0 or 1, these confidence intervals can exceed 0 or1 and in this table confidence interval bounds are censored at 0 
Baseline Report of the Titukulane RFSA in Malawi (Vol. I)
Descriptive Statistics 29 
from below and 1 from above. The number of observations higher for weight measurements than for height measurements 
since in a few cases, parents did not allow the height for very small children to be taken given the procedure they were using to 
take height (making the kids lie on the height board) while the weight for these small children could be recorded.
4.14 Children’s Nutrition
IPA collected child-level nutrition data from the Tier-1 Care Group eligible sample. Among households in 
this group with children under 5 years old, 4% were receiving a minimum acceptable diet (MAD). Table 
18 below shows that receiving a MAD is similar among male and female children. Furthermore, 66% of
children are exclusively breastfed, with no differences between female and male children in terms of 
exclusive breastfeeding9
. On average, 17% of children under the age of 5 suffered diarrhea in the 2 
weeks prior to the survey and 56% of children with diarrhea were treated with Oral Rehydration 
Therapy (ORT). Female and male children under the age of 5 suffer from diarrhea at similar rates, 
around 16-17%, but a higher percentage of male children with diarrhea are treated with oral 
rehydration therapy (ORT) (61% for male children vs. 52% for female children). See Appendix Table 16 
for further details on children’s diet and health. For nutrition knowledge among T1CG households, see 
Appendix Table 1. 
Table 18. Small children: diet and health
Description
T1CG only
95% – C.I.
Mean N Lo Hi
[BL12] Children 6–23 months receiving a minimum acceptable
diet (MAD)
4% 1148 3% 6%
Female 4% 584 2% 6%
Male 5% 564 3% 7%
Breastfed 5% 995 3% 7%
Non-breastfed 0% 153 0% 0%
Children 6–23 months with minimum dietary diversity (as defined 
under MAD)
19% 1,149 15% 23%
Breastfed (> = 4 of any food group below) 22% 996 17% 26%
Non-breastfed (> = 4 of any food group below excl. dairy; > = 2 
milk feedings)
1% 153 0% 2%
Children 6–23 consuming any of [food group]:
Grain, roots, and tubers 63% 1,406 59% 67%
Legumes and nuts 21% 1,406 18% 24%
Dairy products (milk, yogurt, cheese) 8% 1,406 5% 10%
Flesh foods (meat, fish, poultry, and liver/organ meats) 38% 1,406 34% 42%
 
9 Njira and UBALE DFAP final performance evaluations reported that 76.6% and 76.4% of children under 6 months old, 
respectively, were exclusively breastfeed. On MAD, Njira reported that 6% of children 6–23 months old received MAD while 
UBALE found 5.2% of children were receiving MAD.
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30 Descriptive Statistics
Description
T1CG only
95% – C.I.
Mean N Lo Hi
Eggs 6% 1,405 4% 7%
Vitamin A-rich fruits and vegetables 39% 1,406 35% 43%
Other fruits and vegetables 26% 1,406 22% 30%
Children 6–23 months with minimum meal frequency 14% 1,148 11% 17%
Breastfed (> = 2 non-liquid feedings if age 6-8m; > = 3 non-liquid
feedings if age 9–23m)
16% 995 13% 19%
Non-breastfed (> = 4 non-liquid feedings + > = 2 milk feedings) 0% 153 0% 1%
[BL13] Children under 6 months of age with exclusive breastfeeding 66% 254 56% 77%
Female 66% 126 53% 78%
Male 67% 128 51% 82%
[BL39] Diet of Minimum Diversity, children 6–23 months 20% 1,150 16% 24%
Female 23% 584 17% 28%
Male 18% 566 13% 22%
[BL14] Children under 5 had diarrhea in the prior 2 weeks 17% 1,403 14% 19%
Female 17% 711 13% 21%
Male 16% 692 12% 20%
[BL15] Children under 5 with diarrhea treated with Oral Rehydration 
Therapy 56% 257 46% 66%
Female 52% 115 39% 65%
Male 61% 142 45% 76%
4.15 Water, Sanitation, and Hygiene
Household-level data was collected on water, sanitation, and hygiene (WASH) indicators from the Tier-1 
Care Group eligible households. IPA collected data on access to soap and water, to a handwashing 
station and to basic sanitation services like toilets. 
Overall, 7% of the households have soap and water at a handwashing station on the household’s 
premises.10 We find that 27% of the households have a handwashing station and among these 
households, 51% have water, 28% have soap, ash, or detergent, and 5% have mud or sand at the 
handwashing station.
Table 19 shows that 20% of the Tier-1 Care Group eligible households have access to a basic sanitation 
service. Regarding the kinds of toilets used by households, we find that 41% of households use an 
 
10 Njira and UBALE DFAP final performance evaluations found 9.9% and 4.2% of its population, respectively, had water and soap 
at the handwashing station.
Baseline Report of the Titukulane RFSA in Malawi (Vol. I)
Descriptive Statistics 31 
uncovered pit latrine without a slab, 35% use covered pit latrines without a slab, 13% use covered 
latrines with a slab, 6% use uncovered pit latrines with a slab and 3% do not have a toilet. Furthermore, 
Appendix Table 17 breaks down WASH indicators by household type.
Table 19. Water, sanitation, and hygiene of Tier-1 Care Group eligible
Description
T1CG only
95% – C.I.
Mean N Lo Hi
[BL17] HH has soap and water at handwashing station on premises 7% 1,761 4% 10%
Surveyor observed a handwashing station on the premises 27% 1,761 23% 31%
Handwashing station has water 51% 450 41% 60%
Cleansing agent at the handwashing station:
Soap, ash, or detergent (bar, liquid, power, paste) 28% 450 18% 37%
Mud or sand 5% 450 2% 8%
Other cleansing agent 0% 450 0% 1%
[BL27] HH with access to a basic sanitation service 20% 1,761 16% 24%
Kind of toilet the HH uses:
Uncovered pit latrine without slab/open pit 41% 1,761 36% 46%
Covered Pit latrine without slab/open pit 35% 1,761 31% 40%
Covered Pit latrine with slab 13% 1,761 10% 16%
Uncovered pit latrine with slab 6% 1,761 4% 8%
No facility/bush/field 3% 1,761 2% 4%
Other 2% 1,761 1% 3%
Notes: Confidence intervals for binary indicators are based on Normal approximations; for very small samples and indicator 
values near 0 or 1, these confidence intervals can exceed 0 or1 and in this table confidence interval bounds are censored at 0 
from below and 1 from above.
4.16 Mental Health
Mental health is an indicator of well-being and can be an important determinant for individuals’ income 
generating capacity. In the mental health section of the survey, IPA collected information on 
respondents’ levels of distress in the previous 30 days using the Kessler Psychological Distress Scale (K6). 
The K6 score, which we compute using the responses from this section, ranges from 0 to 24, with higher 
scores indicating higher levels of psychological distress, such as anxiety and depression.11 
Table 20 shows summary statistics for data from the mental health module (only collected in the long 
survey from the T1CG sample). Respondents score an average Kessler 6 score of 11 (a score of 13, which 
about 45% of respondents reported, is often considered the threshold for serious mental illness). About 
 
11 Prochaska JJ, Sung HY, Max W, Shi Y, Ong M. Validity study of the K6 scale as a measure of moderate mental distress based on 
mental health treatment need and utilization. Int J Methods Psychiatr Res. 2012;21(2):88-97. doi:10.1002/mpr.1349
IMPEL | Implementer-Led Evaluation and Learning
32 Descriptive Statistics
45% of households reported going through a period of worry, tension, or anxiety lasting 30 days or 
longer. Among these households, 87% indicated that said period was still ongoing, 6% reported the 
period was still ongoing but that their distress had reduced, and another 6% reported that the period 
had already ended. A large percentage of households also reported that these worries interfered with 
their ability to carry out normal activities. Food shortage was the most common source of households’ 
worries, followed by employment, living situation, loan or debt, and health. A smaller percentage of 
households reported conflict with others, domestic issues, children’s education, or clothing as sources of 
their worries. Furthermore, 11% of these households visited a health center or consulted a health 
provider for reasons related to their worries.
Table 20. Mental health
Description
T1CG only
95% – C.I.
Mean N Lo Hi
Kessler 6 (0-24) 11.18 1,719 10.49 11.87
Had a period lasting 30 days or longer when felt worried, tense or 
anxious most of the time, in the last 12 months 45% 1,827 40% 51%
The period is it still going on 87% 897 84% 91%
The period is it still going on, but reduced 6% 897 4% 9%
The period ended 6% 897 4% 9%
Kessler 6 (0-24) 11.18 1,719 10.49 11.87
These worries interfered with their ability to carry out normal activities
A lot 74% 897 69% 79%
Some 14% 897 10% 18%
A little 10% 897 7% 13%
Not at all 2% 897 1% 3%
Source of these worries:
Food shortage 82% 897 78% 86%
Employment 37% 897 30% 44%
Living space/Living situation 19% 897 15% 24%
Health 16% 897 11% 20%
Loan/Debt 18% 897 14% 22%
Conflict with other 13% 897 9% 18%
Domestic issues 8% 897 6% 11%
Children's education 5% 897 3% 8%
Clothing 6% 897 3% 8%
Other 4% 897 2% 5%
Baseline Report of the Titukulane RFSA in Malawi (Vol. I)
Descriptive Statistics 33 
Description
T1CG only
95% – C.I.
Mean N Lo Hi
HH have visited a health center or have consulted a health provider 
for reasons related to their concerns 11% 897 8% 15%
Type of health facility/provider visited
Government hospital 69% 120 56% 82%
Government health post 12% 120 4% 21%
Private hospital 12% 120 2% 22%
Other 11% 120 1% 20%
Visited any traditional healer for reasons related to your worries 2% 1,827 2% 3%
Visited any religious authority for reasons related to your worries 12% 1,827 10% 14%
Issues that sometimes are reasons of concern
Food shortage 76% 1,827 71% 81%
Living situation 44% 1,827 39% 50%
Domestic issues 20% 1,827 17% 23%
Clothing 21% 1,827 17% 25%
Health 17% 1,827 14% 21%
Children's education 11% 1,827 9% 13%
Conflict with other 8% 1,827 6% 10%
Employment 5% 1,827 4% 7%
IMPEL | Implementer-Led Evaluation and Learning
34 Conclusion
5. CONCLUSION
In this baseline survey report, we have provided an overview of the Titukulane RFSA in Malawi, including 
a description of the sampled households at baseline. We report on a variety of demographic 
characteristics of the households in the sampled areas, as well as on indicators that are relevant to 
Titukulane’s purposes of improving the incomes, nutrition, and resilience capabilities of participating 
households. The baseline survey revealed that 66% of the households are headed by a married head of 
household and that 37% of the households are headed by females. The average age of the household 
heads is 42 and the levels of education among household heads are very low, as only 5% of them have 
completed secondary school. The average household has 2.7 children under the age of 16. 
In the baseline survey, we find that farming, crop production and sales, and agricultural wage labor are 
the main sources of food or income for most surveyed households, which is common among rural 
households in Malawi. On the other hand, a small percentage of households engage in non-agricultural
wage labor or business. In line with this observation, we find that 93% of households cultivated crops in 
the 12 months prior to the survey and that 98% of these households cultivated maize, which is also 
considered the most important crop cultivated in the rainy season. We find that 17% of the households 
cultivated any land in the dry season and among them, 96% used some form of irrigation. The majority 
of households (81%) that cultivated crops in the dry season use basic irrigation methods, such as water
cans, pails, or buckets. Furthermore, baseline survey results show that majority of households use some 
form of improved management practices although many individual practices are not widely used. 
We find low business ownership among the households. Only 17% of households operate an off-farm 
business, with only 25% having an inventory valued above MWK 50, 000.00 (PPP $163.00). This indicates 
that the majority of the businesses are small. 
The baseline survey included the FCS module for a 7-day recall period and the FIES module. These 
survey modules to help understand households’ food consumption levels and experience with food 
insecurity. For FCS, we find that the average score among the sample is 37.9 (out of a maximum of 112). 
Additionally, we find that 10% of households have an FCS that qualifies their food consumption as poor, 
37% have borderline food consumption, and 53% of households have an adequate food consumption. 
On the other hand, the FIES survey module results showed that 97% of households experience 
moderate or severe food insecurity within a period of 12 months. This was further highlighted by the 
large percentage of households that were worried about not having enough food to eat, that 
experienced being unable to eat a healthy or nutritious meal, that ate few kinds of meals, or that had to 
skip a meal because of a lack of money or other resources. 
The baseline survey has also provides insights into children’s nutrition and key anthropometric 
indicators among the sampled households. Among children under 5 years old, 2% of children are 
wasted, 41% of children are stunted, and 89% of children have a healthy weight. We also find that 14% 
of 5 children under five years old had diarrhea 2 weeks prior to the study and that among these 
children, 56% of them were treated with ORT. On children’s nutrition and health, we find that 4% of 
children under 2 years old received a minimum acceptable diet and that 66% of children under 6 months 
old are exclusively breastfed. 
Baseline Report of the Titukulane RFSA in Malawi (Vol. I)
Conclusion 35 
Lastly, the survey used the Kessler 6 survey module to understand the mental health status of 
household heads. For the Tier-1 Care Group eligible households, the average K-6 score was 11 (out of a 
maximum of 24, indicating highest psychological distress). We also find that 45% of respondents
experienced a period lasting 30 days or longer in which they felt worried, tense, or anxious, in the 12 
months prior to the survey. The most common sources of worries among these households are food 
shortage, employment, health, loan or debt, conflicts with other people and living situation. 
IMPEL | Implementer-Led Evaluation and Learning
36 Appendix
APPENDIX 
Additional Descriptive Statistics
Table 21. Appendix: Nutrition knowledge
Description
T1CG only
95% – C.I.
Mean N Lo Hi
HH considers that: 
Iron is an important nutritional supplement during pregnancy 36% 257 27% 45%
Folic acid is an important nutritional supplement during pregnancy 10% 257 4% 16%
Children under 6 months should be fed normally with breastmilk 93% 242 89% 98%
ORT/Oral Rehydration Solution/Thanzi is an important treatment for 
diarrhea 98% 233 96% 100%
Notes: This section was administered to HH with children under 2 years of age who had diarrhea in the last 2 weeks. 
Table 22. Appendix: Resilience
Description
All T1CG only
95% – C.I. 95% – C.I.
Mean N Lo Hi Mean N Lo Hi
[BL24] HH believes local government will 
respond effectively to future shocks and 
stresses*
75% 1,747 70% 79% 81% 481 75% 87%
Notes: * This question was administered to a random subsample of respondents.
Table 23. Appendix: Women’s dietary diversity among Tier-1 Care Group eligible households, by age
Description
T1CG only
95% – C.I.
Mean N Lo Hi
Women of reproductive age consuming a 
diet of minimum diversity (RiA)
13% 1,411 11% 16%
Women less than 19 years of age 15% 117 6% 25%
Women older than 19 years 13% 1,234 10% 16%
Notes: This section was administered to HH with at least one woman of reproductive age. The ages of 60 women are unknown.
Baseline Report of the Titukulane RFSA in Malawi (Vol. I)
Appendix 37 
Table 24. Appendix: Livestock assets in the last 12 months
Description
All T1CG only
95% – C.I. 95% – C.I.
Mean N Lo Hi Mean N Lo Hi
HH owned livestock in last 12 months 38% 3,107 35% 42% 30% 1,827 25% 34%
HH owned (animals):
Chickens 74% 1,047 70% 78% 74% 542 68% 80%
Goats 32% 1,047 28% 37% 26% 542 20% 32%
Ducks 7% 1,047 5% 9% 8% 542 4% 13%
Pigeons 8% 1,047 5% 12% 6% 542 3% 9%
Pigs 4% 1,047 2% 6% 2% 542 0% 4%
Rabbits 2% 1,047 0% 4% 3% 542 1% 4%
Sheep 1% 1,047 0% 1% 2% 542 0% 4%
Cows/heifers/calves 1% 1,047 0% 2% 1% 542 0% 2%
Oxen/bullocks 1% 1,047 0% 1% 0% 542 0% 0%
Guinea fowl 1% 1,047 0% 3% 1% 542 0% 3%
HH owned (livestock structures):
Bird Pen/Coop 15% 3,107 11% 19% 11% 1,827 9% 14%
Goat house/goat pen 10% 3,107 8% 12% 7% 1,827 5% 9%
Other 5% 3,107 4% 7% 2% 1,827 1% 3%
None 75% 3,107 71% 79% 83% 1,827 80% 86%
Notes: Confidence intervals for binary indicators are based on Normal approximations; for very small samples and indicator
values near 0 or 1, these confidence intervals can exceed 0 or1 and in this table confidence interval bounds are censored at 0 
from below and 1 from above.
Table 25. Appendix: Livestock practices in the past 12 months
Description
All T1CG only
95% – C.I. 95% – C.I.
Mean N Lo Hi Mean N Lo Hi
HH owned livestock 38% 3,107 35% 42% 30% 1,827 25% 34%
Randomly selected for follow-up 
questions
16% 1,047 13% 20% 19% 542 14% 24%
HH used the following practices:
Homemade animal feeds * 33% 213 21% 45% 44% 118 29% 59%
Vaccinations 21% 213 13% 28% 20% 118 9% 30%
IMPEL | Implementer-Led Evaluation and Learning
38 Appendix
Description
All T1CG only
95% – C.I. 95% – C.I.
Mean N Lo Hi Mean N Lo Hi
Services of comm. animal health worker 5% 213 2% 8% 9% 118 1% 17%
Services of ag. ext. development officer 8% 213 2% 14% 6% 118 1% 12%
HH owned chickens 28% 3,107 25% 32% 22% 1,827 18% 26%
Randomly selected for follow-up 
questions
16% 759 12% 21% 16% 402 11% 22%
HH used the following practices:
Homemade animal feeds * 28% 150 12% 44% 37% 87 23% 51%
Vaccinations 12% 150 4% 21% 21% 87 9% 34%
Services of comm. animal health worker 6% 150 1% 12% 12% 87 1% 23%
Services of government animal health 
extension worker 1% 150 0% 2% 3% 87 0% 7%
HH owned goats 13% 3,107 11% 14% 8% 1,827 6% 10%
Randomly selected for follow-up 
questions
14% 309 8% 19% 22% 140 13% 32%
HH used the following practices:
Services of comm. animal health worker 9% 69 1% 16% 12% 34 0% 26%
Services of ag. ext. development officer 7% 69 0% 14% 6% 34 0% 13%
Notes: This section was administered to HH who owns livestock and were randomly selected for follow-up questions. Confidence 
intervals for binary indicators are based on Normal approximations; for very small samples and indicator values near 0 or 1, 
these confidence intervals can exceed 0 or1 and in this table confidence interval bounds are censored at 0 from below and 1 
from above. *Homemade animal feeds made of locally available products. Comm. = community. Ag. = agricultural. Ext. = 
extension.
Table 26. Appendix: Consumption
Description
All T1CG only
95% – C.I. 95% – C.I.
Mean N Lo Hi Mean N Lo Hi
Maize flour 100% 3,107 100% 100% 100% 1,827 99% 100%
Cooking oil 63% 3,107 58% 67% 60% 1,827 55% 65%
Rice 26% 3,107 22% 29% 23% 1,827 19% 27%
Sugar (not incl. sugar cane) 22% 3,107 19% 25% 16% 1,827 13% 20%
Eggs 14% 3,107 12% 17% 10% 1,827 8% 12%
Tea 6% 3,107 5% 8% 3% 1,827 2% 4%
Baseline Report of the Titukulane RFSA in Malawi (Vol. I)
Appendix 39 
Table 27. Appendix: Gender (cash)
Description
All T1CG only
95% – C.I. 95% – C.I.
Mean N Lo Hi Mean N Lo Hi
[BL32] Earned cash in the past 12 months 22% 627 15% 30% 27% 403 20% 34%
[BL33] Women report part. in decisions 
about the use of self-earned cash 50% 112 31% 69% 65% 80 48% 83%
[BL34] Women report part. in decisions 
about the use of spouse's/partner's self￾earned cash
44% 79 29% 60% 44% 79 29% 60%
[BL35] Men report spouse/partner part. 
in decisions about the use of self-earned 
cash
63% 63 37% 88% 65% 44 47% 84%
Notes: This section was administered to randomly subsampled households only. Part. = participation.
Table 28. Appendix: Farming practices and area of application
Description
All T1CG only
95% – C.I. 95% – C.I.
Mean N Lo Hi Mean N Lo Hi
Early planting or planting with first rains 61% 3,107 56% 66% 55% 1,827 49% 60%
Rand. selec. for follow-up questions 16% 1,803 14% 18% 17% 1,030 14% 20%
Grew rice 11% 323 4% 17% 10% 187 4% 16%
Applied practice to rice 22% 38 2% 42% — 19 — —
Area (acre) — 10 — — — 5 — —
Grew beans 10% 323 3% 17% 6% 187 1% 12%
Applied practice to beans — 19 — — — 9 — —
Area (acre) — 10 — — — 5 — —
Grew maize 98% 323 96% 100% 98% 187 94% 100%
Applied practice to maize 99% 317 97% 100% 98% 184 95% 100%
Area (acre) 1.2 309 0.9 1.5 1.1 179 0.8 1.5
Grew pigeon peas 50% 323 38% 63% 53% 187 41% 65%
Applied practice to pigeon peas 43% 177 30% 56% 57% 96 40% 74%
Area (acre) 1.0 90 0.7 1.4 0.6 55 0.3 0.8
Regular monitoring of crops for pests 46% 3,107 40% 53% 44% 1,827 38% 50%
Rand. selec. for follow-up questions 15% 1,459 12% 17% 18% 837 14% 22%
Grew rice 9% 261 3% 14% 11% 157 4% 18%
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40 Appendix
Description
All T1CG only
95% – C.I. 95% – C.I.
Mean N Lo Hi Mean N Lo Hi
Applied practice to rice 27% 33 4% 49% — 18 — —
Area (acre) — 11 — — — 7 — —
Grew beans 12% 261 3% 20% 11% 157 2% 19%
Applied practice to beans — 18 — — — 10 — —
Area (acre) — 12 — — — 6 — —
Grew maize 99% 261 98% 100% 100% 157 100% 100%
Applied practice to maize 100% 259 99% 100% 99% 156 97% 100%
Area (acre) 1.0 257 0.8 1.1 0.9 154 0.7 1.2
Grew pigeon peas 53% 261 38% 67% 69% 157 57% 81%
Applied practice to pigeon peas 61% 163 47% 75% 65% 99 49% 81%
Area (acre) 0.8 92 0.5 1.0 0.6 57 0.4 0.9
Manure 42% 3,107 38% 47% 35% 1,827 30% 39%
Rand. selec. for follow-up questions 19% 1,247 16% 21% 18% 704 13% 22%
Grew rice 11% 240 3% 19% 10% 134 2% 18%
Applied practice to rice — 25 — — — 12 — —
Area (acre) — 5 — — — 3 — —
Grew beans 10% 240 2% 18% 8% 134 0% 16%
Applied practice to beans — 15 — — — 7 — —
Area (acre) — 5 — — — 3 — —
Grew maize 97% 240 94% 100% 94% 134 86% 100%
Applied practice to maize 100% 231 99% 100% 99% 129 98% 100%
Area (acre) 1.1 228 0.8 1.5 1.1 127 0.6 1.5
Grew pigeon peas 46% 240 33% 60% 60% 134 46% 74%
Applied practice to pigeon peas 24% 139 13% 35% 40% 76 17% 63%
Area (acre) 1.3 42 0.5 2.0 — 26 — —
Intercropping 40% 3,107 34% 46% 35% 1,827 31% 40%
Rand. selec. for follow-up questions 17% 1,261 13% 21% 17% 698 13% 21%
Grew rice 7% 233 2% 11% 6% 125 2% 11%
Applied practice to rice — 25 — — — 12 — —
Area (acre) — 1 — — — 0 — —
Grew beans 21% 233 11% 32% 16% 125 4% 28%
Baseline Report of the Titukulane RFSA in Malawi (Vol. I)
Appendix 41 
Description
All T1CG only
95% – C.I. 95% – C.I.
Mean N Lo Hi Mean N Lo Hi
Applied practice to beans — 27 — — — 12 — —
Area (acre) — 25 — — — 12 — —
Grew maize 99% 233 96% 100% 100% 125 100% 100%
Applied practice to maize 98% 231 95% 100% 99% 124 98% 100%
Area (acre) 1.2 226 0.8 1.6 0.9 121 0.6 1.1
Grew pigeon peas 77% 233 66% 88% 86% 125 76% 95%
Applied practice to pigeon peas 89% 193 81% 98% 93% 103 86% 100%
Area (acre) 1.0 179 0.8 1.2 0.8 97 0.5 1.1
Use modern (hybrid/improved) crop 
varieties 39% 3,107 34% 43% 33% 1,827 29% 37%
Rand. selec. for follow-up questions 18% 1,117 14% 21% 19% 602 14% 25%
Grew rice 6% 217 2% 9% 10% 123 3% 17%
Applied practice to rice — 25 — — — 16 — —
Area (acre) — 8 — — — 8 — —
Grew beans 13% 217 4% 22% 6% 123 0% 11%
Applied practice to beans — 14 — — — 6 — —
Area (acre) — 2 — — — 0 — —
Grew maize 100% 217 100% 100% 99% 123 98% 100%
Applied practice to maize 99% 214 98% 100% 98% 120 94% 100%
Area (acre) 1.2 210 0.9 1.6 1.1 117 0.7 1.5
Grew pigeon peas 48% 217 35% 62% 58% 123 43% 73%
Applied practice to pigeon peas 17% 117 6% 28% 16% 67 5% 27%
Area (acre) — 25 — — — 14 — —
Physically removing pests 28% 3,107 24% 33% 27% 1,827 23% 31%
Rand. selec. for follow-up questions 17% 945 12% 21% 18% 533 12% 23%
Grew rice 18% 173 6% 30% 16% 101 5% 27%
Applied practice to rice — 26 — — — 14 — —
Area (acre) — 1 — — — 1 — —
Grew beans 10% 173 2% 18% 7% 101 0% 14%
Applied practice to beans — 11 — — — 5 — —
Area (acre) — 1 — — — 0 — —
Grew maize 99% 173 98% 100% 100% 101 99% 100%
IMPEL | Implementer-Led Evaluation and Learning
42 Appendix
Description
All T1CG only
95% – C.I. 95% – C.I.
Mean N Lo Hi Mean N Lo Hi
Applied practice to maize 98% 171 96% 100% 100% 100 99% 100%
Area (acre) 0.9 168 0.7 1.0 0.9 98 0.6 1.2
Grew pigeon peas 67% 173 52% 81% 63% 101 48% 78%
Applied practice to pigeon peas 10% 110 3% 17% 17% 59 3% 31%
Area (acre) — 19 — — — 12 — —
Application of locally-made pesticides 7% 3,107 5% 9% 8% 1,827 5% 10%
Rand. selec. for follow-up questions 18% 251 9% 26% 17% 145 9% 24%
Grew rice 18% 50 0% 37% 24% 31 0% 50%
Applied practice to rice — 9 — — — 6 — —
Area (acre) — 1 — — — 1 — —
Grew beans 16% 50 0% 33% 18% 31 0% 49%
Applied practice to beans — 3 — — — 1 — —
Area (acre) — 1 — — — 0 — —
Grew maize 100% 50 100% 100% 100% 31 100% 100%
Applied practice to maize 94% 50 86% 100% 86% 31 71% 100%
Area (acre) 0.6 44 0.4 0.9 — 26 — —
Grew pigeon peas 58% 50 24% 92% 70% 31 44% 96%
Applied practice to pigeon peas 12% 38 0% 25% — 24 — —
Area (acre) — 6 — — — 4 — —
Weed control 6% 3,107 5% 8% 5% 1,827 3% 6%
Rand. selec. for follow-up questions 12% 213 6% 19% 12% 112 5% 20%
Grew rice 25% 34 2% 48% — 15 — —
Applied practice to rice — 6 — — — 1 — —
Area (acre) — 1 — — — 0 — —
Grew beans 17% 34 0% 38% — 15 — —
Applied practice to beans — 3 — — — 0 — —
Area (acre) — 1 — — — 0 — —
Grew maize 100% 34 100% 100% — 15 — —
Applied practice to maize 85% 34 65% 100% — 15 — —
Area (acre) 0.8 30 0.4 1.2 — 13 — —
Grew pigeon peas 59% 34 31% 87% — 15 — —
Baseline Report of the Titukulane RFSA in Malawi (Vol. I)
Appendix 43 
Description
All T1CG only
95% – C.I. 95% – C.I.
Mean N Lo Hi Mean N Lo Hi
Applied practice to pigeon peas — 20 — — — 8 — —
Area (acre) — 3 — — — 2 — —
Mulching 5% 3,107 3% 6% 4% 1,827 3% 6%
Rand. selec. for follow-up questions 13% 151 5% 21% 21% 70 8% 33%
Grew rice — 23 — — — 14 — —
Applied practice to rice — 4 — — — 1 — —
Area (acre) — 0 — — — 0 — —
Grew beans — 23 — — — 14 — —
Applied practice to beans — 2 — — — 1 — —
Area (acre) — 0 — — — 0 — —
Grew maize — 23 — — — 14 — —
Applied practice to maize — 23 — — — 14 — —
Area (acre) — 22 — — — 14 — —
Grew pigeon peas — 23 — — — 14 — —
Applied practice to pigeon peas — 12 — — — 7 — —
Area (acre) — 5 — — — 3 — —
Crop rotation 4% 3,107 2% 7% 2% 1,827 1% 3%
Rand. selec. for follow-up questions 8% 99 1% 16% 20% 46 6% 35%
Grew rice — 19 — — — 11 — —
Applied practice to rice — 3 — — — 2 — —
Area (acre) — 2 — — — 1 — —
Grew beans — 19 — — — 11 — —
Applied practice to beans — 1 — — — 1 — —
Area (acre) — 0 — — — 0 — —
Grew maize — 19 — — — 11 — —
Applied practice to maize — 18 — — — 10 — —
Area (acre) — 14 — — — 6 — —
Grew pigeon peas — 19 — — — 11 — —
Applied practice to pigeon peas — 9 — — — 7 — —
Area (acre) — 5 — — — 4 — —
Introducing insects to remove pests 0% 3,107 0% 0% 0% 1,827 0% 0%
IMPEL | Implementer-Led Evaluation and Learning
44 Appendix
Description
All T1CG only
95% – C.I. 95% – C.I.
Mean N Lo Hi Mean N Lo Hi
Rand. selec. for follow-up questions — 13 — — — 8 — —
Grew rice — 3 — — — 3 — —
Applied practice to rice — 0 — — — 0 — —
Area (acre) — 0 — — — 0 — —
Grew beans — 3 — — — 3 — —
Applied practice to beans — 0 — — — 0 — —
Area (acre) — 0 — — — 0 — —
Grew maize — 3 — — — 3 — —
Applied practice to maize — 2 — — — 2 — —
Area (acre) — 2 — — — 2 — —
Grew pigeon peas — 3 — — — 3 — —
Applied practice to pigeon peas — 1 — — — 1 — —
Area (acre) — 0 — — — 0 — —
Notes: Confidence intervals for binary indicators are based on Normal approximations; for very small samples and indicator 
values near 0 or 1, these confidence intervals can exceed 0 or 1 and in this table, confidence interval bounds are censored at 0 
from below and 1 from above. Rand. selec. = randomly selected. — Not available, cell has less than 30 observations.
Table 29. Appendix: Consumption poverty, by household gender composition
Description
95% – C.I.
Mean N Lo Hi
[BL01] HH living on less than $1.90/day PC 68% 3,089 65% 71%
Tier-1 Care Group Eligible 72% 1,816 68% 76%
Female and Male Adults (F&M) 72% 1,327 68% 76%
Adult Female No Adult Male (FNM) 73% 466 65% 81%
[BL02] Shortfall of the poor relative to the $1.90/day PC 21% 2,052 20% 22%
Tier-1 Care Group Eligible 33% 1,213 30% 36%
Female and Male Adults (F&M) 38% 892 35% 40%
Adult Female No Adult Male (FNM) 23% 310 17% 30%
[BL40] Consumption PC per day (2021 PPP$) 2.19 3,089 2.12 2.26
Tier-1 Care Group Eligible 2.03 1,816 1.92 2.13
Female and Male Adults (F&M) 2.01 1,327 1.87 2.14
Adult Female No Adult Male (FNM) 2.07 466 1.95 2.19
Notes: The $1.90 threshold is inflated from 2011 to 2021 to match the year of the data collection using the US CPL. Household
composition information sufficient to compute indicator values separately by household type with respect to male and female 
Baseline Report of the Titukulane RFSA in Malawi (Vol. I)
Appendix 45 
members was only collected in the Tier-1 Care Group Eligible sample. Household type “Child No Adults” and “Adult Male No 
Adult Female” are not shown, since they have less than 30 observations.
Table 30. Appendix: Food Consumption Score, by household gender composition
Description
95% - C.I.
Mean N Lo Hi
[BL10] FCS score, 7-day recall 37.87 3,107 36.79 38.96
Tier-1 Care Group Eligible 35.22 1,827 33.93 36.51
Female and Male Adults (F&M) 35.82 1,333 34.41 37.24
Adult Female No Adult Male (FNM) 33.76 471 31.58 35.95
Everyone else 38.50 1,280 37.32 39.68
[BL10] Poor food consumption score (FCS) 10% 3,107 8% 13%
Tier-1 Care Group Eligible 15% 1,827 11% 20%
Female and Male Adults (F&M) 15% 1,333 11% 19%
Adult Female No Adult Male (FNM) 16% 471 8% 25%
Everyone else 9% 1,280 7% 11%
[BL10] Borderline food consumption score (FCS) 37% 3,107 34% 40%
Tier-1 Care Group Eligible 37% 1,827 33% 41%
Female and Male Adults (F&M) 36% 1,333 32% 40%
Adult Female No Adult Male (FNM) 38% 471 28% 49%
Everyone else 37% 1,280 33% 40%
[BL10] Adequate food consumption score (FCS) 53% 3,107 49% 57%
Tier-1 Care Group Eligible 48% 1,827 42% 53%
Female and Male Adults (F&M) 49% 1,333 44% 53%
Adult Female No Adult Male (FNM) 45% 471 32% 59%
Everyone else 54% 1,280 50% 58%
Over the past 7 days, number of days consumed [...]:
Cereals, Grains and Cereal Products 6.39 3,107 6.29 6.50
Tier-1 Care Group Eligible 6.29 1,827 6.19 6.39
Everyone else 6.42 1,280 6.30 6.54
Condiments 5.08 3,107 4.56 5.61
Tier-1 Care Group Eligible 4.71 1,827 4.30 5.11
Everyone else 5.17 1,280 4.55 5.79
Vegetables 4.39 3,107 4.19 4.59
Tier-1 Care Group Eligible 4.07 1,827 3.76 4.37
Everyone else 4.47 1,280 4.25 4.69
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Description
95% - C.I.
Mean N Lo Hi
Oil 2.48 3,107 2.17 2.78
Tier-1 Care Group Eligible 2.20 1,827 1.96 2.43
Everyone else 2.54 1,280 2.17 2.92
Meat, Fish and Animal Products 2.51 3,107 2.35 2.67
Tier-1 Care Group Eligible 2.50 1,827 2.30 2.70
Everyone else 2.51 1,280 2.35 2.68
Fruits 1.92 3,107 1.63 2.21
Tier-1 Care Group Eligible 1.72 1,827 1.45 1.99
Everyone else 1.97 1,280 1.65 2.28
Roots, Tubers and Plantains 1.43 3,107 1.29 1.58
Tier-1 Care Group Eligible 1.24 1,827 1.09 1.40
Everyone else 1.48 1,280 1.32 1.64
Nuts and Pulses 1.83 3,107 1.65 2.02
Tier-1 Care Group Eligible 1.44 1,827 1.28 1.61
Everyone else 1.93 1,280 1.72 2.13
Sugar 1.13 3,107 0.98 1.29
Tier-1 Care Group Eligible 0.89 1,827 0.72 1.07
Everyone else 1.19 1,280 1.01 1.37
Milk 0.22 3,107 0.15 0.30
Tier-1 Care Group Eligible 0.12 1,827 0.08 0.17
Everyone else 0.25 1,280 0.16 0.34
Notes: Household composition information sufficient to compute indicator values separately by household type with respect to 
male and female members was only collected in the Tier-1 Care Group Eligible sample. Household type “Child No Adults” and 
“Adult Male No Adult Female” are not shown, since they have less than 30 observations.
Table 31. Appendix: Food Insecurity Experience Scale, additional
Description
95% – C.I.
Mean N Lo Hi
Prevalence of moderate or severe food insecurity in last 12 months 97% 3,107 79% 100%
[BL06] Raw Food Insecurity Score (0-8)* 7.08 3,107 6.95 7.21
Tier-1 Care Group Eligible 7.26 1,333 7.15 7.38
Female and Male Adults (F&M) 7.47 471 7.31 7.62
Adult Female No Adult Male (FNM) 7.02 1,280 6.87 7.17
During last 12 months, because of a lack of money or resources, you or others in your HH...
Baseline Report of the Titukulane RFSA in Malawi (Vol. I)
Appendix 47 
Description
95% – C.I.
Mean N Lo Hi
FIES1: Were worried you would not have enough food to eat 92% 3,107 90% 93%
Tier-1 Care Group Eligible 93% 1,827 91% 95%
Everyone else 91% 1,280 89% 93%
FIES2: Were unable to eat healthy and nutritious food 94% 3,107 93% 96%
Tier-1 Care Group Eligible 95% 1,827 94% 97%
Everyone else 94% 1,280 92% 96%
FIES3: Ate only a few kinds of foods 94% 3,107 93% 96%
Tier-1 Care Group Eligible 96% 1,827 95% 98%
Everyone else 94% 1,280 92% 96%
FIES4: Had to skip a meal 91% 3,107 89% 94%
Tier-1 Care Group Eligible 94% 1,827 93% 96%
Everyone else 91% 1,280 88% 93%
FIES5: Ate less than you thought you should 94% 3,107 92% 96%
Tier-1 Care Group Eligible 96% 1,827 95% 98%
Everyone else 94% 1,280 91% 96%
FIES6: Did not have food 90% 3,107 87% 94%
Tier-1 Care Group Eligible 95% 1,827 93% 96%
Everyone else 89% 1,280 85% 93%
FIES7: Were hungry but did not eat 93% 3,107 91% 94%
Tier-1 Care Group Eligible 95% 1,827 93% 96%
Everyone else 92% 1,280 90% 94%
FIES8: Went without eating for a whole day 59% 3,107 53% 65%
Tier-1 Care Group Eligible 68% 1,827 63% 72%
Everyone else 57% 1,280 50% 64%
FIES1: Were worried you would not have enough food to eat 92% 3,107 90% 93%
Notes: *Based on the FIES (0–8); sum of 8 FIES binary questions (higher = more food insecure). Household composition 
information sufficient to compute indicator values separately by household type with respect to male and female members was 
only collected in the Tier-1 Care Group Eligible sample. Household type “Child No Adults” and “Adult Male No Adult Female” are 
not shown, since they have less than 30 observations.
Table 32. Appendix: Average Food Consumption Score by main household incomes
Main source of income or food Mean FCS N
Farming/crop production and sales 38.72 1,447 
Agricultural wage labor 35.41 766 
Non-agricultural wage labor 36.31 344 
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48 Appendix
Main source of income or food Mean FCS N
Other self-employment (non-agr.) 42.70 178 
Other 36.65 372 
Table 33. Appendix: Correlation Food Consumption Score components vs. Food Insecurity Experience 
Scale components
FIES components, binary indicators: In the past 12m, because of a lack of money or other resources, was 
there a time when you or others in your household…
FCS components, 
number of days 
consumed out of 
past 7
were 
worried 
you 
would 
not 
have 
enough 
food to 
eat
were 
unable to 
eat 
healthy 
and 
nutritious 
food
ate 
only a 
few 
kinds 
of 
foods
had to 
skip a 
meal 
ate less 
than 
you 
thought 
you 
should
did not 
have 
food
were 
hungry 
but did 
not eat
went 
without 
eating 
for a 
whole 
day 
Main staples -0.05 -0.03 -0.05 -0.05 -0.06 -0.05 -0.04 -0.13
Nuts and Pulses -0.05 -0.03 -0.03 -0.06 -0.04 -0.03 -0.06 -0.09
Vegetables -0.05 -0.03 -0.04 -0.04 -0.03 -0.06 -0.04 -0.13
Meat, Fish and 
Animal Products -0.09 -0.08 -0.09 -0.08 -0.10 -0.12 -0.09 -0.15
Fruits -0.02 -0.04 -0.02 -0.04 -0.05 -0.07 -0.04 -0.12
Milk Products -0.17 -0.15 -0.16 -0.19 -0.15 -0.16 -0.13 -0.12
Fats/Oil -0.16 -0.14 -0.16 -0.17 -0.16 -0.18 -0.15 -0.20
Sugar -0.14 -0.13 -0.15 -0.19 -0.15 -0.17 -0.14 -0.15
Spices/Condiments -0.04 -0.04 -0.05 -0.04 -0.04 -0.05 -0.02 -0.04
Table 34. Appendix: Consumption poverty across main source of income or food, by tier
Tier 1 Tier 2 Tier 3
Mean N Mean N Mean N
[BL01] HH living on less than $1.90/day per capita 72% 2,122 68% 815 48% 152 
Farming/crop production and sales 74% 930 69% 426 47% 88 
Agricultural wage labor 75% 567 82% 175 84% 21 
Non-agricultural wage labor 73% 273 44% 61 96% 9 
Other self-employment (non-ag.) 73% 105 51% 53 23% 19 
Other 62% 247 66% 100 6% 15 
[BL02] Shortfall of the poor relative to the $1.90/day PC 29% 1,438 18% 549 12% 65 
Farming/crop production and sales 30% 620 18% 283 10% 33 
Baseline Report of the Titukulane RFSA in Malawi (Vol. I)
Appendix 49 
Tier 1 Tier 2 Tier 3
Mean N Mean N Mean N
Agricultural wage labor 28% 410 18% 146 18% 16 
Non-agricultural wage labor 31% 196 17% 36 11% 8 
Other self-employment (non-ag.) 36% 57 16% 24 11% 6 
Other 27% 155 21% 60 6% 2 
[BL40] Consumption per capita per day (2021 PPP$) 2.07 2,122 2.15 815 3.00 152 
Farming/crop production and sales 2.03 930 2.10 426 2.74 88 
Agricultural wage labor 1.92 567 1.98 175 1.89 21 
Non-agricultural wage labor 2.11 273 2.28 61 1.96 9 
Other self-employment (non-ag.) 1.93 105 2.86 53 6.49 19 
Other 2.66 247 2.20 100 3.99 15 
[BL01] HH living on less than $1.90/day per capita 72% 2,122 68% 815 48% 152 
Notes: The $1.90 threshold is inflated to 2011 to 2021 to match the year of the data collection using the US CPI. 
Table 35. Appendix: Anthropometric indicators for children under 5 years old, by gender and age
Overall T1CG only Everyone else
95% – C.I. 95% – C.I. 95% – C.I.
Mean N Lo Hi Mean N Lo Hi Mean N Lo Hi
[BL03] 
Wasted 2% 1,772 0% 4% 6% 1,679 1% 11% 0% 93 0% 0%
Female
0–5 
months 5% 37 0% 12% 5% 37 0% 12% — — — — 
6–11 
months 4% 148 0% 9% 6% 145 1% 12% — 3 — — 
12–23 
months 3% 341 1% 5% 5% 334 2% 8% — 7 — — 
23–59 
months 2% 345 0% 4% 8% 313 0% 20% 0% 32 0% 0%
Male
0–5 
months 19% 49 0% 44% 26% 48 0% 55% — 1 — — 
6–11 
months 10% 140 0% 22% 14% 138 0% 29% — 2 — — 
12–23 
months 2% 370 0% 4% 3% 367 0% 5% — 3 — — 
23–59 
months 0% 342 0% 0% 1% 297 0% 1% 0% 45 0% 0%
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50 Appendix
Overall T1CG only Everyone else
95% – C.I. 95% – C.I. 95% – C.I.
Mean N Lo Hi Mean N Lo Hi Mean N Lo Hi
[BL04] 
Stunted 41% 1,727 31% 51% 37% 1,634 33% 42% 43% 93 27% 59%
Female
0–5 
months 17% 30 0% 44% 17% 30 0% 44% — — — — 
6–11 
months 34% 144 0% 69% 12% 141 5% 19% — 3 — — 
12–23 
months 31% 339 15% 47% 31% 332 24% 38% — 7 — — 
23–59 
months 42% 331 22% 61% 40% 299 31% 48% 42% 32 17% 68%
Male
0-5 
months 38% 45 0% 79% 12% 44 1% 24% — 1 — — 
6–11 
months 67% 138 49% 84% 51% 136 36% 65% — 2 — — 
12–23 
months 54% 369 42% 66% 47% 366 38% 57% — 3 — — 
23–59 
months 36% 331 17% 55% 40% 286 31% 50% 34% 45 8% 61%
[BL05] 
Healthy 
weight
89% 1,772 82% 95% 89% 1,679 85% 94% 88% 93 78% 99%
Female
0–5 
months 90% 37 79% 100% 90% 37 79% 100% — — — — 
6–11 
months 59% 148 27% 90% 86% 145 79% 93% — 3 — — 
12–23 
months 91% 341 83% 99% 91% 334 87% 95% — 7 — — 
23–59 
months 91% 345 76% 100% 91% 313 79% 100% 91% 32 72% 100%
Male
0–5 
months 48% 49 16% 79% 64% 48 36% 92% — 1 — — 
6–11 
months 81% 140 67% 95% 72% 138 57% 87% — 2 — — 
Baseline Report of the Titukulane RFSA in Malawi (Vol. I)
Appendix 51 
Overall T1CG only Everyone else
95% – C.I. 95% – C.I. 95% – C.I.
Mean N Lo Hi Mean N Lo Hi Mean N Lo Hi
12–23 
months 95% 370 91% 98% 94% 367 90% 98% — 3 — — 
24–59 
months 92% 342 84% 100% 94% 297 90% 98% 92% 45 79% 100%
Notes: Confidence intervals for binary indicators are based on Normal approximations; for very small samples and indicator 
values near 0 or 1, these confidence intervals can exceed 0 or1 and in this table confidence interval bounds are censored at 0 
from below and 1 from above.
— Not available, cell has less than 30 observations. Wt = weight. Wasted is defined as having WHZ less than -2. Stunted is 
defined as having a HAZ less than -2. Healthy weight is defined as having a WHZ greater than -2 and less than 2. 
Table 36. Appendix: Small children: diet and health, additional details
Description 
T1CG only
95% – C.I.
Mean N Lo Hi
Children 6–23 months receiving minimum acceptable diet (MAD) 4% 1,148 3% 6%
MAD components:
Yesterday, during the day and night, child ate any:
Grain, roots, and tubers 63% 1,406 59% 67%
Legumes and nuts 21% 1,406 18% 24%
Dairy products (milk, yogurt, cheese) 8% 1,406 5% 10%
Flesh foods (meat, fish, poultry, and liver/organ meats) 38% 1,406 34% 42%
Eggs 6% 1,405 4% 7%
Vitamin A-rich fruits and vegetables 39% 1,406 35% 43%
Other fruits and vegetables 26% 1,406 22% 30%
Times child ate [food type] yesterday during the day or at night:
Solid, semi-solid, or soft foods other than liquids 1.08 1,405 0.98 1.17
Any milk 0.14 1,406 0.10 0.18
Child breastfed yesterday during the day or at night 89% 1,407 86% 92%
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52 Appendix
Table 37. Appendix: Water, sanitation, and hygiene of Tier-1 Care Group eligible, additional details
Description
T1CG only
95% – C.I.
Mean N Lo Hi
[BL17] HH with soap and water at a handwashing station on premises 7% 1,761 4% 10%
Female and Male Adults (F&M) 8% 1,285 4% 12%
Adult Female No Adult Male (FNM) 5% 455 2% 8%
HH where a handwashing station was observed on the premises 27% 1,761 23% 31%
Water at the place for handwashing 51% 450 41% 60%
Cleansing agent at the place for handwashing
Soap, ash, or detergent (bar, liquid, power, paste) 28% 450 18% 37%
Mud or sand 5% 450 2% 8%
Other cleansing agent 0% 450 0% 1%
[BL27] HH with access to a basic sanitation service 20% 1,761 16% 24%
Female and Male Adults (F&M) 21% 1,285 17% 25%
Adult Female No Adult Male (FNM) 17% 455 10% 24%
Kind of toilet the HH uses:
Uncovered pit latrine without slab/open pit 41% 1,761 36% 46%
Covered Pit latrine without slab/open pit 35% 1,761 31% 40%
Covered Pit latrine with slab 13% 1,761 10% 16%
Uncovered pit latrine with slab 6% 1,761 4% 8%
No facility/bush/field 3% 1,761 2% 4%
Other 2% 1,761 1% 3%
Notes: Household composition information sufficient to compute indicator values separately by household type with respect to 
male and female members was only collected in the Tier-1 Care Group Eligible sample. Household type “Child No Adults” and 
“Adult Male No Adult Female” are not shown, since they have less than 30 observations.
Table 38. Appendix: Resilience, by household gender composition
Description
95% – C.I.
Mean N Lo Hi
[BL24] HH believes local government will respond effectively to future 
shocks and stresses*
75% 1,747 70% 79%
Tier-1 Care Group Eligible 81% 481 75% 87%
Female and Male Adults (F&M) 80% 348 72% 87%
Adult Female No Adult Male (FNM) 83% 124 70% 95%
Everyone else 74% 1,266 70% 79%
Notes: *This question was administered to random subsample of respondents. Household composition information sufficient to 
compute indicator values separately by household type with respect to male and female members was only collected in the Tier-
Baseline Report of the Titukulane RFSA in Malawi (Vol. I)
Appendix 53
1 Care Group Eligible sample. Household type “Child No Adults” and “Adult Male No Adult Female” are not shown, since they 
have less than 30 observations.
Figure 2. Appendix: Binned scatter plot showing strong alignment of Food Consumption Score vs Food 
Insecurity Experience Scale scores
IMPEL | Implementer-Led Evaluation and Learning
54 Appendix
Balance
Table 39. Appendix: Balance
Variable
Control Treatment F-test for 
joint 
N Mean/SE N Mean/SE orth.
Demographics
Gender of household head 1,495 0.369
[0.016]
1,612 0.370
[0.017]
0.879
Age of household head 1,495 41.016
[0.588]
1,612 40.298
[0.683]
0.244
Christian 1,443 0.525
[0.046]
1,607 0.597
[0.039]
0.285
Muslim 1,443 0.470
[0.047]
1,607 0.400
[0.040]
0.361
Household head is married 1,495 0.672
[0.015]
1,612 0.656
[0.017]
0.848
No formal schooling 1,495 0.227
[0.016]
1,612 0.203
[0.013]
0.606
Some primary schooling 1,495 0.530
[0.016]
1,612 0.542
[0.017]
0.933
Primary school completed 1,495 0.068
[0.008]
1,612 0.068
[0.008]
0.963
Some secondary school 1,495 0.097
[0.011]
1,612 0.110
[0.013]
0.672
Secondary school / high school completed 1,495 0.045
[0.008]
1,612 0.053
[0.007]
0.547
Number of children under 16 in household 1,495 2.738
[0.070]
1,612 2.705
[0.056]
0.698
Number of children under 5 in household 1,495 1.045
[0.030]
1,612 1.038
[0.032]
0.389
Number of children under 2 in household 1,495 0.567
[0.018]
1,612 0.549
[0.021]
0.575
Number of separate rooms 1,495 2.111
[0.033]
1,612 2.105
[0.037]
0.901
Joint Test p-value: 0.74
Income: Sources of food or income over the last 
12 months
Farming/crop production and sales 1,495 0.615
[0.022]
1,612 0.610
[0.016]
0.751
Agricultural wage labor 1,495 0.431
[0.025]
1,612 0.449
[0.029]
0.994
Baseline Report of the Titukulane RFSA in Malawi (Vol. I)
Appendix 55 
Variable
Control Treatment F-test for 
joint 
N Mean/SE N Mean/SE orth.
Non-agricultural wage labor 1,495 0.232
[0.019]
1,612 0.261
[0.020]
0.411
Other self-employment (non-agricultural) 1,495 0.098
[0.009]
1,612 0.111
[0.012]
0.307
Other self-employment (agricultural) 1,495 0.072
[0.007]
1,612 0.073
[0.008]
0.971
Joint Test p-value: 0.92
Consumption poverty
[BL01] HH living on less than $1.90/day PC 1,487 0.664
[0.015]
1,602 0.664
[0.018]
0.791
[BL02] Shortfall of the poor relative 988 0.283
[0.011]
1,064 0.261
[0.007]
0.257
[BL40] Consumption PC per day (2021 PPP$) 1,487 2.371
[0.230]
1,602 2.218
[0.051]
0.314
Joint Test p-value: 0.20
Food security
Food Consumption Score (FCS) 1,495 37.638
[0.551]
1,612 37.282
[0.837]
0.886
[BL10] Adequate FCS 1,495 0.537
[0.017]
1,612 0.509
[0.024]
0.642
[BL10] Borderline FCS 1,495 0.332
[0.012]
1,612 0.372
[0.016]
0.125
[BL10] Poor FCS 1,495 0.131
[0.012]
1,612 0.119
[0.013]
0.374
[BL06] Raw FIES score 1,495 7.258
[0.043]
1,612 7.240
[0.058]
0.855
Joint Test p-value: 0.17
Household assets
Index of Assets 1,495 0.000
[0.014]
1,612 0.021
[0.018]
0.242
Joint Test p-value: 0.35
Livestock
HH that owns any livestock 1,495 0.332
[0.016]
1,612 0.341
[0.017]
0.568
Index of Livestock ownership 1,495 0.000
[0.012]
1,612 0.021
[0.012]
0.134
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56 Appendix
Variable
Control Treatment F-test for 
joint 
N Mean/SE N Mean/SE orth.
Index of Livestock structures ownership 1,495 -0.000
[0.017]
1,612 0.014
[0.017]
0.479
Joint Test p-value: 0.56
Farming
HH that own agricultural land at time of survey 1,495 0.779
[0.018]
1,612 0.783
[0.021]
0.996
Total area of agricultural land (in acre) 1,495 0.818
[0.025]
1,612 0.794
[0.026]
0.184
HH cultivated anything in the last 12 months 1,495 0.909
[0.009]
1,612 0.913
[0.010]
0.840
Number of crops cultivated in the last rainy 
season
1,495 1.886
[0.063]
1,612 1.937
[0.062]
0.486
No. maize bags harvested in the last rainy 
season
1,495 3.645
[0.991]
1,612 4.087
[0.676]
0.886
HH sold some crops cultivated in last rainy 
season
1,359 0.432
[0.018]
1,472 0.410
[0.017]
0.167
HH cultivated anything in this dry season 1,495 0.185
[0.013]
1,612 0.188
[0.016]
0.905
Number of crops cultivated in this dry season 1,495 0.207
[0.016]
1,612 0.223
[0.021]
0.442
Has used any irrigation in last dry season 1,495 0.179
[0.013]
1,612 0.181
[0.015]
0.992
HH operates a business 1,495 0.166
[0.012]
1,612 0.172
[0.013]
0.845
HH is member of a farmer group/cooperative 1,495 0.047
[0.007]
1,612 0.043
[0.006]
0.925
[BL21] Applied improved management
practices/technologies
1,495 0.860
[0.012]
1,612 0.881
[0.011]
0.098*
Joint Test p-value: 0.34
Wash
[BL17] HH with soap and water at handwashing
station on premises
862 0.060
[0.010]
899 0.059
[0.010]
0.371
[BL27] HH with access to a basic sanitation 
service
862 0.211
[0.019]
899 0.195
[0.021]
0.991
Joint Test p-value: 0.85
Savings and loans
HH saves cash regularly 1,495 0.102
[0.009]
1,612 0.103
[0.012]
0.545
Baseline Report of the Titukulane RFSA in Malawi (Vol. I)
Appendix 57 
Variable
Control Treatment F-test for 
joint 
N Mean/SE N Mean/SE orth.
HH taken out a loan from a bank/Microfinance 
institution/Sacco
1,495 0.104
[0.010]
1,612 0.102
[0.011]
0.903
Joint Test p-value: 0.99
Notes: The value displayed for t-tests are the differences in the means across the groups.
Standard errors are clustered at variable vgp_uniqid.
Fixed effects using variable strat_cell are included in all estimation regressions.
***, **, and * indicate significance at the 1, 5, and 10% critical level.