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OFDA_ ENDLINE EVALUATION REPORT_WEST POKOT JULY 2021
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Table of Contents
................................................................................................................................................................1
Background .............................................................................................................................................4
1.1 Objective .......................................................................................................................................4
1.2 Specific objectives.........................................................................................................................4
2.0 Methodology.....................................................................................................................................5
2.1 Study Population...........................................................................................................................5
2.2 Sampling method and sample size determination .......................................................................5
2.3 Data Collection..............................................................................................................................5
2.4 Data Analysis................................................................................................................................5
2.5 Ethical consideration.....................................................................................................................5
3.0 Key Findings and Results...................................................................................................................5
3.1 Socio demographic characteristics ...............................................................................................5
3.2 Household Composition................................................................................................................6
4.0 Households source of income, expenditure, savings and borrowing...............................................6
4.1 Source and predictability of income .............................................................................................6
4.2 Ability to meet basic needs...........................................................................................................7
4.3 Households expenditure, savings and borrowing.........................................................................8
5.0 Household Food Security ..................................................................................................................9
5.1 Household Economic Status .......................................................................................................10
5.2 Household crop cultivation.........................................................................................................11
5.2 Ownership of Kitchen Garden.....................................................................................................11
6.0 Household shocks or emergencies .............................................................................................12
6.1 Household Vulnerability..............................................................................................................14
7.0 Family MUAC...............................................................................................................................14
7.2 Respondent physiological status.................................................................................................16
7.3 Child Anthropometrics................................................................................................................16
8.0 Conclusion and Recommendation ..................................................................................................16
8.1 Conclusion...................................................................................................................................16
8.2 Recommendations......................................................................................................................17
List of Tables
Table 1: Socio demographic characteristics............................................................................................5
Table 2: Sources of Income.....................................................................................................................6
Table 3: Households mitigation measures..............................................................................................7
Table 4: Households food security status per sub county....................................................................10
Table 5: Households productive assets.................................................................................................11
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Table 6: Ownership of kitchen garden per MtMSG..............................................................................11
Table 7: Access to vegetables and household food security ................................................................12
Table 8:Coping Strategies to economic shocks.....................................................................................13
Table 10: Respondents interpretation of family MUAC colours...........................................................15
Table 11: Comparison of mean MUAC measurements by gender .......................................................16
List of Figures 
Figure 1: Households ability to meet basic needs..................................................................................7
Figure 2: Households liquid assets..........................................................................................................8
Figure 3: comparison of amount borrowed and saved during baseline and endline.............................9
Figure 4: Comparison of food security status during baseline and endline .........................................10
Figure 5: Ownership of kitchen garden.................................................................................................12
Figure 6: Households recovery from previous shocks..........................................................................13
Figure 7: MUAC measurements............................................................................................................15
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Background 
Most families in West Pokot County depend on agriculture, livestock and livestock by- products as 
their main source of income and livelihoods in the urban and rural Households with the county having 
three main livelihood zones namely: pastoral, agro-pastoral and mixed farming composed of 33%, 37% 
and 30% respectively. 69% of the households in West Pokot County derive their food and income from 
livestock and livestock by-products. The prolonged heavy rainfall experienced in West Pokot led to 
poor performance of the season because of heavy rainfall that led to water logging in mixed and agro￾pastoral livelihood zones, reducing crop production. In addition, most irrigation infrastructure was 
destroyed, and high incidences of pests and diseases reported, notably desert locusts. Cases of 
livestock disease outbreak like Foot and Mouth Disease (FMD) and Lumpy Skin Disease (LSD) were 
prevalent in various parts of the county. 
A recent evaluation of the systems revealed various gaps which include: under-reporting of zoonotic 
diseases, lack of integration due to challenges in data sharing, which itself may be a consequence of 
technological barriers, inadequate number of trained personnel, lack of harmonization of reporting 
among different sectors making it harder to then collate and interpret. Further risky practices such as 
drinking unpasteurized milk, eating uninspected meat and failure to vaccinate animals has led to 
outbreaks of zoonotic diseases in the county such as anthrax, rabies and brucellosis. Due to the 
vastness of the County, the veterinarian officers may not respond to immediately save livestock and 
prevent livestock disease outbreaks. As a result, the communities are unable to meet the veterinary 
service fee for logistical arrangements required by the County Veterinary Department to vaccinate 
their animals.
In response to this, Action Against Hunger through the Office of U.S Foreign Disaster assistance 
funding (OFDA) (15-08-2020 to 15-09-2021) through livestock and agriculture interventions which
included training of TOTs and sensitization of Community Disease Reporters and Community Health 
Volunteers on One Health Approach, Sensitization of the Community on Diseases and Animal 
Husbandry. Other interventions on livestock include training of Livestock Technicians and Sensitization 
of Community Disease Reporters on Participatory Disease Surveillance, Support timely response, 
vaccination and treatment of livestock in hard to reach areas of West Pokot County. In agriculture,
Action Against Hunger intends to support the community through poultry farming at community level, 
training on Good Agricultural Practices (GAP) with focus on crop diversification and utilization of 
nutritious food at household level and promotion of beekeeping through provision of 
modern/improved hives.
1.1 Objective
To assess the impact of the food security and livelihood interventions supported by Action Against 
Hunger in 8 Mother to mother support group members which include the food security situation , 
nutrition status of children 6-59 months and PLWs in Pokot South, Pokot Central and Pokot North.
1.2 Specific objectives
To determine:
 The socio economic status of the households
 Whether the households are food insecure
 The nutrition status of children 6-59 months and pregnant and lactating women
 The Mother to mother support groups (mtmsg) members are able to measure, interpret 
MUAC (Mid Upper Aram Circumference) colours and refer cases.
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2.0 Methodology
2.1 Study Population
The study population included eight mother to mother support groups (mtmsgs) in Pokot south(3), 
Pokot south(3) and Pokot North(2).
2.2 Sampling method and sample size determination
The survey incorporated all members of the targeted mtmsgs that benefited from the seed funds as 
well as trainings and sensitizations to improve their livelihood. The final sample size was 178 
households.
2.3 Data Collection
Data Collection was done for 4 days (8th to 11th July 2021) by four teams composed of four members
(three enumerators and 1 team leader). This was done in strict adherence to COVID-19 preventive 
measures as stipulated by the MOH. The teams were trained for a day prior to field work on the survey 
objectives, methodology, sampling methods, data collection tools, Open Data Kit (ODK) data collection 
process as well as interviewing skills as part of data quality assurance measures. A role-play was 
included in the training to give the teams practical skills on data collection. 
2.4 Data Analysis
All the quantitative data was analyzed using Excel and SPSS.
2.5 Ethical consideration
Informed consent was obtained from the study participants after explaining the purpose of the study. 
Participation of all respondents in the assessment was on voluntary basis, respect, dignity, 
confidentiality, and freedom of each assessment participant was maintained during and after the 
assessment. 
3.0 Key Findings and Results
3.1 Socio demographic characteristics
Information regarding the gender of the respondent, age, population distribution in the household, 
residency status, education level and the sex of the household head were assessed in order to map 
the demographic characteristics of the project target beneficiaries. (Table 1)
Table 1: Socio demographic characteristics
Characteristic Frequency Percent 
(%)
Household headship Male 147 82.6
Female 31 17.4
Household residency Resident 178 100
Pay for house Yes 3 1.7
No 175 98.3
Incidence of adult premature death in 
household 
Yes 49 27.5
No 129 72.5
Age of respondent Above 55 years 21 11.8
18-24 years 26 14.6
25-34 years 69 38.8
35-44 years 36 20.2
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Characteristic Frequency Percent 
(%)
45-54 years 26 14.6
Marital status Divorced 1 0.6
Married 157 88.2
Separated 2 1.1
Widowed 18 10.1
Education level Primary (class 1 - 8) 94 52.8
Secondary (form 1 -4) 14 7.9
Tertiary 15 8.4
None of the above 55 30.6
Total 178 100
3.2 Household Composition 
The average household composition was 7 members (mean 7.46+ 2.909) with the minimum number 
being 2 members and maximum number being 16 members. The average number of males per 
household was 3 (mean 3.76+ 2.064) with a minimum of 0 and a maximum of 10. On the other hand, 
average number of female members was 3 (mean 3.67+ 1.628) with the minimum number being 1 
and the maximum being 8. 77% (n= 137) of the households had children under 5 years of age, the 
average number of children per household being one child (mean 1.65+ 0.723).The maximum number 
of children per household was 3 while the minimum number was 1. The number of households with 
children aged 6-59 months was 130 (73%).
16.3% (n=29) of the households reported that a child had come to live with them in the recent past 
whereas 83.7% (n=149) did not. These children were in the present household due to reasons such as 
death of the caregiver (24.1%), lack of access to food (13.8%) and some had reported that the parent 
had left home (27.6%). Other reasons (34.5%) cited include visitation, relatives, coming to help with 
childcare and as well as going to school. 
4.0 Households source of income, expenditure, savings and borrowing
4.1 Source and predictability of income 
The main source of income was sales from farm products (47.8%, n= 85), followed by salaries and/or 
wages (17.4%, n=31), business (21.3%, n=38) a significant increase from what was reported during 
baseline 13.9% (n=23. This is an indication that some of the MtMSG members had started practicing 
what they were trained on IGAs through the support of Action Against Hunger. Other sources of 
income included rental income and interest and remittances (10.7% n=19) a 7% increase from what 
was reported during baseline. Majority (42.1%, n=75) reported that their income was predictable but 
changes dramatically depending on the season, while 33.1% (n=59) reported predictability with slight
changes depending on the season, 19.7% (n=35) unpredictability and only 5.1% (n=9) having a 
predictable source of income.
Table 2: Sources of Income
Sources of income Baseline Endline
Frequency Percent Frequency Percent
Salaries/wages/commission 35 21.1 31 17.4
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Income from business 23 13.9 38 21.3
Remittances (money received from 
people living elsewhere)
0 0 3 1.7
Grants 0 0 2 1.1
Sales of farming products and 
services
105 63.3 85 47.8
Other income sources e.g rental 
income, interest
3 1.7 19 10.7
Total 165 100 178 100
4.2 Ability to meet basic needs.
On the ability of households to meet basic needs, which included food, shelter, education and health 
care, most of the households (78.7%) stated that they usually pay for food but struggle to make lump 
sum payments for health and education expenses. 
Figure 1: Households ability to meet basic needs
The respondents were further asked on the mitigation measures that they would put in place if 
something bad happened and they could no longer earn money through their primary source of
livelihood. 31.8% stated that they would rely on family for support, 11.1% would rely on charity a 
significant decrease from what was reported during baseline; 50.2% and 40% which indicates that 
households have become self-reliant and less vulnerable. 24.1% would start new income generating 
activities, and 21.3% would rely on other existing income generating activities, while 8% would find 
new informal jobs respectively.
Table 3: Households mitigation measures
Baseline Endline
Percent Percent
Find new formal job 0 3.7
Start a new Income-generating activity 15.7 24.1
Rely more on other existing income-generating 
activity
34.3 21.3
Find new Informal job 4.8 8
78.7
13.5
7.3
0.6
0 10 20 30 40 50 60 70 80 90
We can usually pay for food and shelter, but struggle
with lumpsum payments for health and education
We struggle to pay for food
We can usually pay fo food, shelter and education and
health care expenses. sometimes struggle but we can…
We are always able to pay for food, shelter, education
and healthcare without struggle
Households ability to meet basic needs
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Rely on family for support 50.2 31.8
Rely on charity 40 11.1
On household assetssuch as livestock, food stores or personal belongingsthat could quickly be turned 
into cash, it was established that most of the respondents 53.9% % had some liquid assets, but the 
amount changed a lot during the year. 33.7% had some liquid assets but the amount changed a little 
during the year while 12.4% never had many liquid assets while (Figure 2).
Figure 2: Households liquid assets
4.3 Households expenditure, savings and borrowing
In regards to household expenditure in the last one month the assessment revealed that majority of 
respondents had spent Ksh. 2,001- 5,000 (50.6%), followed by Ksh. 5,001-10,000 (23.6%), Ksh. 1-
2,000 (20.8%) and greater than Ksh. 10,000 (5.1%). When asked how much they had in savings, 18.5% 
(n=33) responded that they had none or nearly none in savings, 49.4% (n=88) had some savings with
the amount changing a lot during the year, 32% (n=57) had some savings with the amount changing a 
little during the year. A comparison on the amount of money saved and borrowed in the past one 
month was further done and it was established that there was a significant increase in people who 
saved Ksh. 1-2000 from 39.2% to 56.2%. This is an indication that the training they received on loans 
and savings was useful and they can caution themselves in case of an emergency. (Figure 3).
53.9
33.7
12.4
We have some liquid assets, but the
amount changes alot during the year
We have some liquid assets, but the
amount changes a little during the
year
We never have many liquid assets
Households liquid assets
Percent
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Figure 3: comparison of amount borrowed and saved during baseline and endline
5.0 Household Food Security
Food security means having, at all times, both physical and economic access to sufficient food to meet 
dietary needs for a productive and healthy life.
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In regards to food security situation in the households, 
60.7% % (n=108) stated that there were instances in the past 30 days where there had no food to eat 
because of lack of resource to get food. Among them, 52.8% (n=38) cited a rare frequency of 1-2 
times, 33.3% (n=36) cited that it happened sometimes (3-10 times) while 13.9% (n=15) cited that it 
happened often (more than 10 times).
When asked whether there was any instance in the past 30 days where there was no food to eat 
because of lack of resource to get food, 50% (n=89) responded ‘Yes’ and the other 50% (n=89) 
responded ‘No’. 58.4% (n=52) of those that responded positively cited a rare frequency of 1-2 times, 
31.5% cited that it happened sometimes (3-10 times) while the remaining 10.1% (n=9) cited that it 
happened often (more than 10 times). 
To the question of whether in the past 30 days any household member went to sleep at night hungry 
because there was not enough food, a negative response was obtained from 68.1% (n=113) whereas 
31.9% (n=53) responded positively. Of these, 62.3% (n=33) reported a frequency of 1-2 times while a 
frequency of 3-10 times was reported by the remaining 37.7% (n=20). 
On the other hand, the question of whether any household member went a whole day and night 
without food due to there not being enough food in the past 30 days elicited a negative response from 
82% and a positive response from 18%. This was reported to have happened 1-2 times (43.8%), 3-10 
times (50%) as well as more than 10 times (6.3%). 
Majority of the respondents were moderately food insecure 33.1% (n=59). Only 13.5% (n = 24) were 
severely food insecure. There was a significant decrease of households that were food secure from 
57.8% during baseline to 31.5% at endline as shown in the figure 4 below:
 
1 https://www.usaid.gov/what-we-do/agriculture-and-food-security 37.3 16.3 40.4
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39.2
56.2
30.7
38.8
18.7
15.7
13.9
20.2
3
7.9
8.4
9.6
1.8
3.9
6.6
4.5
A M O U N T S A V E D 
( B A S E L I N E )
A M O U N T S A V E D 
( E N D L I N E )
A M O U N T B O R R O W E D 
( B A S E L I N E )
A M O U N T B O R R O W E D 
( E N D L I N E )
Comparison Of Amount Saved And Borrowed During 
Baseline and Endline
Ksh. 0 Kshs. 1 - 2000 Kshs. 2001 - 5000 Kshs. 5001 - 10,000 Kshs. >10,000
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Figure 4: Comparison of food security status during baseline and endline
Food security status distribution per sub – county revealed that majority of respondents from Pokot 
South (39%) were food secure, whereas those hailing from Pokot North were severely food insecure 
(24.%) as shown in the table below:Of importance to note, there was a significant decrease of 
households that were severely food insecure in Pokot Central from 24.6% during baseline to 13% at 
end line. This can be attributed to.…..
Table 4: Households food security status per sub county
5.1 Household Economic Status
An unstable economic status was reported by majority of the respondents (87.6%) with them 
struggling to make ends meet. 7.9% described their status as being prepared to grow, in that they 
were mostly stable and investing in stable opportunities, 9.0% described themselves as being destitute 
in that they were barely surviving while only 4.9% reported to be stable and secure. There was no 
much difference based on the enumerator’s assessment as they cited 83.1% of the households to be 
struggling to make ends meet, 11.8% prepared to grow, 4.5% destitute while 0.6 were not vulnerable.
In regards to households productive assets that are used to generate income such as livestock and 
business, it was established that there was a significant increase in households that owned few 
productive assets from 51.8% during baseline to 69.7% at endline. This indicates that majority of the 
households have capacity to generate income in the future and cope with future shocks.(Table 5)
57.8
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19.3
10.8
31.5
21.9
33.1
13.5
0 10 20 30 40 50 60 70
Food Secure
At risk of food insecurity
Moderately food insecure
Severely food insecure
Comparison of food security status between baseline and 
endline
Endline
Baseline
Household food security Total
Food secure At risk of 
food 
insecurity
Moderately 
food insecure
Severely 
food 
insecure
Sub county Pokot 
Central
14 17 28 9 68
21% 25% 41% 13% 100%
Pokot North 15 2 14 10 41
37% 5% 34% 24% 100%
Pokot South 27 20 17 5 69
39 29 25 7 100%
Total 56% 39% 59% 24% 178
31.5 21.9 33.1 13.5 100%
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Table 5: Households productive assets
Baseline Endline
Frequency Percent Frequency Percent
We have no 
productive assets
39 23.5 4 2.2
We have few 
productive assets
86 51.8 124 69.7
We have some 
productive assets
41 24.7 50 28.1
Total 166 100 178 100
5.2 Household crop cultivation
It was established that 32.6% (n=58) had 1 acre under cultivation, 28.7% (n=51) had more than an 
acre, 30.3% (n=54) had 0.5 acres, 4.5% (n=8) had less than 0.25 and 3.5% (n=7) had 0.25 acres under 
cultivation. The most cultivated crop was maize at 59.9% (n=145), then vegetables cited at 13.6%
(n=33), potatoes at 10.3% (n=25), millet at 7.4% (n=18), sorghum at 7% (n=17) and the least one was 
fruits cited at 1.7% (n=4). The mean amount of crop harvested was 73kg for beans, 852kg for maize, 
73kg for sorghum, and 35kg for millet, 758kg for potatoes 107kg for fruits and 2kg for vegetables 
respectively. 
5.2 Ownership of Kitchen Garden 
Ownership of a kitchen garden was reported by 75.3% (n=134) (Figure 5) a significant increase from 
what was reported at baseline at 54.2% (n=90). This is a good indication that the MtMSG members 
replicated kitchen gardens at their homesteads courtesy of the training and kitchen garden 
demonstration by the Ministry of Agriculture with Support from Action Against Hunger. However, 
there were some groups such as Kalemngorok and Korelach that performed poorly in replicating 
kitchen gardens at their homesteads as only 34.8% and 38.5% respectively had. Of those with kitchen 
garden, only 28.4% (n=38) agreed that they had access to vegetables from the garden throughout the 
year with 71.6% (n=77) not having all year round access.
Table 6: Ownership of kitchen garden per MtMSG
Name of MtMSG Do you have a kitchen garden? Total Percentage
N0 Yes
Emkokon 0 25 25 100
Kalemngorok 15 8 23 34.8
Kapcheror 1 17 18 94.4
Kapkarawai 0 24 24 100
Kasaka 0 17 17 100
Korelach 16 10 26 38.5
Lalat 5 15 20 75
Tokorion 7 18 25 72
Total 44 134 178 75.3
Methods used to access vegetables through the year included mulching, water harvesting, irrigation,
crop rotation, sunken beds and Planting step by step.94.4%(n=168) confirmed that they had been 
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trained on sustainable good agriculture as compared to the low proportion 38.1% that was reported 
during baseline indicating that they were more knowledgeable on good agricultural practices. The 
topics trained on included dryland farming (17.7%), multi storey kitchen garden (23.4%), organic 
farming (27.6%), post-harvest and storage (11.9%), value addition (2.2%), double digging (4%) and 
water harvesting (13.3%).
A chi – square test of association revealed 
a significant association (X (3) = 23.113, P 
= 0.00) between household food security 
and ownership of kitchen gardens. 
Households that reported ownership of 
kitchen garden were food secure than 
those that did not have. However, there 
was an insignificant 
Figure 5: Ownership of kitchen garden
Association (X (3) = 5.468, P = 0.141) observed between access to vegetables and household food 
security. It was evident that though ownership of a kitchen garden had significant contribution to the 
household food security, households with access to vegetables were statistically insignificant to 
household food security. It did not matter whether you had access to vegetables throughout the year 
to be food secure.
Table 7: Access to vegetables and household food security
Household food security 
Access to 
vegetables
Food secure At risk of food 
insecurity
Moderately 
food insecure
Severely 
food 
insecure
Total
Yes 18 9 10 1 38
47.4 23.7 26.3 2.6 100.0%
No 32 26 10 15 83
38.6 31.3 12.0 18.1 100.0%
Total 50 35 33 16 134
37.3 26.1 24.6 11.9 100.0%
6.0 Household shocks or emergencies
Respondents were asked to state the last time the household experienced a shock or an emergency 
that had a major effect on the household’s finances. 59.6% (n=106) reported that shocks had never 
occurred to them, 20.2% (n=36) reported a period of 1-5 years ago, 8.4% (n=15) had shocks occur to 
them in the last year, 6.7% (n=12) reported 5-10 years ago whereas 5.1% (n=9) reported more than 
ten years ago. Types of shocks reported to have occurred in the past included natural disasters such 
24.7
75.3
Ownership of Kitchen garden
No Yes
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as drought (54.2%), loss of wages (8.0%), family conflict (2.8%), loss of wage earner (5.6%) business 
failure (.4%) and others (36.1%) such as spending money on illnesses, loss of livestock, and loss of a 
relative. The state of household recovery from the shocks as reported as shown in figure 6.
Figure 6: Households recovery from previous shocks
In case a similar shock recurred, 87.5% of the households would slowly recover, 6.9% would never 
recover, 2.9% would quickly recover while 2.8 would not be affected or would recover immediately. 
Instances where unexpected shocks or major emergencies like death in the family would occur, most 
of the respondents (23.2%) stated that they would borrow from a friend or relative. No household 
reported that they would send children to others to be taken care or go without food an indication 
that they were economically stable and are prepared for any economic shock that may occur. (Table 
6)
Table 8: Coping Strategies to economic shocks
Response Baseline Endline
Frequency Percen
t (%)
Frequency Percen
t (%)
Pay with cash on hand/savings 1 1.3 12 6.2%
Request help from a charitable 
organization
28 37.3 18 9.3%
Borrow from a friend or relative 34 45.3 45 23.2%
Borrow from savings group or VSLA 41 54.7 37 19.1%
Look for other source of income near 
my home 
1 1.3 9 4.6%
Reduce household spending a little 1 1.3 6 3.1%
Reduce household spending a lot 2 2.7 1 0.5%
Sell livestock, household goods or 
items
36 48 40 20.6%
Migrate for work 2 2.7 0 0.0%
Household 
never 
recovered, 
2.8
Household is 
still 
recovering, 
30.6 Household 
recovered 
over time, 63.9
Household 
recovered 
immediately, 
2.8
Households Recovery from previous 
shocks
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Sell bicycle, tool, land or other items 
that help produce income 
13 17.3 13 6.7%
Break up household – send children 
to others to care for
2 2.7 0 0.0%
Go without food 1 1.3 0 0.0%
Engage in gold mining for income 2 2.7 0 0.0%
6.1 Household Vulnerability 
Household vulnerability is usually influenced by the economic status, which is sometimes dictated by 
the source of income and occupation. Therefore, to further understand the household’s vulnerability 
status, chi – square tests for associations were conducted to establish if female – headed households 
were more vulnerable when compared to male – headed households. Gender of the households was 
determined to be significantly associated with household vulnerability for the following variables; 
household’s liquid assets (X (2) = 12.544, P = 0.002 P = 0.044); household’s productive assets(X(2) = 
6.685, P = 0.035); household’s ability to withstand shocks or emergencies (X(4) = 11.167, P 0.025). 
7.0 Family MUAC
The survey sought to establish the level of knowledge on family MUAC and 63.5% (n=113) a decrease 
from what was reported during baseline 66.3% (n=63) agreed that they had heard of it while 36.5% 
(n=36.5) did not have knowledge on MUAC. Among the mothers that reported to have the 
knowledge 52.2% (n=59) reported that they had used it to measure their children. All of them (100%) 
stated that they knew how to interpret MUAC tape. Results on how the level of knowledge on MUAC 
tape colour interpretation are illustrated in Table 10.
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Table 9: Respondents interpretation of family MUAC colours
Response Frequency Percent 
RED
Child is in bad condition 8 13.5
It means child is malnourished 2 3.3
Child is weak 10 16.9
The child is severely malnourished 39 66.1
YELLOW
At risk 2 3.3
Moderately malnourished 40 67.7
The child is fair 1 1.6
The child is not very bad 6 10.1
The child is suffering from lack of food 1 1.6
The child is not healthy 9 15.2
GREEN
The child is okay 2 3.3
The child is healthy 7 11.8
The child is normal 50 84.7
When asked to state their child’s MUAC reading the last time they measured, 91.5% (n=54) had a green 
colour reading , 6.8% (n=4) obtained a yellow reading, while 1.7% (n=1) obtained a red colour as shown it 
figure 7. Of those who obtained the red and yellow colour 2 of them stayed at home while 3 referred to 
the health facility. They further reported that assistance was received at the health facility in the form of 
the child being enrolled in a program while got the health facility closed.
Monthly meetings were reported 
to be held by all of them. The topics 
discussed at these monthly 
meetings included infant and 
young child feeding, maternal 
nutrition, progress on income 
generating activities, family 
planning and child spacing.
An observation of caregivers’ 
Figure 7: MUAC measurements
Green, 91.5
Red, 1.7 Yellow, 6.8
Family MUAC Measurements
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ability to take the child’s MUAC measurement revealed that majority (66%, n= 39) could correctly take 
the measurement, 30.5% (n=18) struggled to take the measurement and only 3.4% (n=2) children were 
not at home. 
7.2 Respondent physiological status 
Of the 178 respondents, 18% (n=32) reported that they were currently pregnant or lactating. The average 
age of children for lactating mothers’ children was 4 months (std. deviation 3.694) with the oldest being 
17 months and the youngest being 1 month old. The average MUAC measurement for both pregnant and 
lactating mothers was 264.6mm (std. deviation 34.007) with a maximum reading being 336mm and a 
minimum of 222mm indicating a normal nutritional status for all. 
7.3 Child Anthropometrics
MUAC measurements were taken and recorded for children aged 6 – 59 months (n = 191). On average, 
the children aged 32 months (mean 32.65 months, stand dev 15.95), with the oldest being 58 months and
the youngest aged 6 months. The mean MUAC was 145.95 mm (stand dev 13.445 mm) with the highest 
MUAC at 216mm and the lowest at 104mm. 85.3%(n=163) were normal, 10.5%(n=20) at risk, 3.1%(n=6) 
MAM,1 while 1.0%(n=2) were SAM
On further analysis there was a statistically insignificant difference between the male and the female 
MUAC readings as determined by one-way ANOVA (F (1,189) = 14.377, P = 0.779). The mean MUAC for
females was higher (146.21mm) than that of males (145.66mm). 
Table 10: Comparison of mean MUAC measurements by gender
N Mean Std. 
Deviation
Std. 
Error
95% Confidence Interval for 
Mean Minimum Maximum
Lower Bound Upper 
Bound
Male 92 145.66 14.254 1.486 142.71 148.61 104 216
Female 99 146.21 12.715 1.278 143.68 148.75 118 198
Total 191 145.95 13.445 0.973 144.03 147.87 104 216
One-way ANOVA tests revealed that there were no statistically significant relationships observed between 
nutrition statuses of the children (MUAC). The age of the respondent (F (53,137) = 1.288, P = 0.124), the 
education level of the respondent (F (53,137) = 0.846, P = 0.753), household’s productive assets(F (53,137) 
= 1.047, P = 0.407) and household having experienced shock or emergency (F (53,137) = 0.601, P = 0.982). 
However, there was an observed statistically significant relationship between household economic status 
and nutrition status of a child. (F (4, 4) = 11.167, P = 0.025).
8.0 Conclusion and Recommendation
8.1 Conclusion
Generally, among the households interviewed 31.5% were food secure, 33.1 were moderately, 21.9 were 
at risk of food insecurity, while 13.5% were severely food insecure. Of importance to note there was a 
significant decrease of food secure households from 57.8% during baseline to 31.5% which could be 
17
attributed to…. In addition, a chi – square test of association revealed a significant association (X (3) = 
23.113, P = 0.00) between household food security and ownership of kitchen gardens. In regards to 
households ability to meet basic needs such as food, shelter, education and health care most of them 
could not comfortably meet them as 78.7% could pay for food, but struggled to make lump sum payments 
for health and education expenses a slight increase from what was reported during baseline (71.1%).
Support of seed funds and trainings on financial management and good and sustainable agricultural 
practices from Action Against Hunger played a major role in households socio economic status. There was 
a significant increase in people who saved Ksh. 1-2000 from 39.2% during baseline to 56.2% and 53.9% % 
had some liquid assets, and at least 69.7% had few productive assets.
The members validated sensitization of mother to mother support groups on family MUAC by Action 
Against Hunger and their knowledge on it was encouraging. At least 63.5% had the knowledge and all of 
them could interpret the colours. Most of the pregnant and lactating women and children 6-59 months 
nutrition status was established to be good. Nutrition status for both PLWs and children 6-59 months was 
good with a mean MUAC of 264.6mm (std. deviation 34.007)) for PLWs and 145.95 mm (stand dev 13.445
mm) for children aged 6-59 months respectively.
8.2 Recommendations
 CHEWs and the Ministry of Agriculture Officers to continue sensitizing groups especially those 
hailing from Kalemng’orok and Korelach on the importance of replicating kitchen gardens as the 
produce might contribute to the household food security as well as increasing the household 
income.
 Action Against Hunger in collaboration with the Ministry of Health to sensitize women on the use 
of family MUAC as only 63.5% stated that they had the knowledge of family MUAC. This will help 
in early detection and admission of malnourished cases in the community.
 There is need for the mtmsg members to be sensitized on the importance of referring their 
malnourished to the CHV or the health facility for further management in order to avoid further 
deterioration of their nutrition status as two of them stayed at home after obtaining a yellow 
reading from their children MUAC measurements.
 CHEWS in collaboration with Action Against Hunger to conduct a sensitization/ refresher training 
on family MUAC as 30.5% (n=18) of the respondents were still struggling to take the 
measurement.