DIETARY DIVERSITY AND NUTRIENT ADEQUACY OF CHILDREN 
AGED 6-23 MONTHS AMONG PASTORALIST AND AGRO-PASTORALIST 
COMMUNITIES IN LOIMA, TURKANA COUNTY-KENYA 

 

 

 

 

MAXWELL HONGO OWITI (BSc-FN&D) 

REG NO. H60/CTY/PT/37815/2016 

 

 

 

DEPARTMENT OF FOOD, NUTRITION AND DIETETICS 

 

 

 

A RESEARCH THESIS SUBMITTED IN PARTIAL FULLFILMENT FOR 
THE REQUIREMENTS OF THE AWARD OF THE DEGREE MASTERS OF 
SCIENCE IN FOOD, NUTRITION AND DIETETICS IN THE SCHOOL OF 
PUBLIC HEALTH AND APPLIED HUMAN SCIENCE KENYATTA 
UNIVERSITY 

 

 

 

September, 2021. 


DECLARATION 

This thesis is my original work and has not been presented for a degree in any other 
University. 

Signature………………………………… Date ………………. 

Name: Maxwell Hongo Owiti Registration; H60/CTY/PT/37815/2016 

 

 

Supervisors: We confirm that the work reported in this thesis was carried out by the 
candidate under our supervision. 

1. Signature ……………………… Date……………… 


Judith Munga (PhD) 

Department of Food, Nutrition and Dietetics 

Kenyatta University 

 

2. Signature ……….. Date ………… 


Joseph Kobia (PhD) 

Department of Food, Nutrition and Dietetics 

Kenyatta University 

 

 

 

 

 

 

 

 

 


DEDICATION 

This thesis is dedicated to Ruth A. Ogango (my wife), Sarah Gift (daughter), 
Sarah Favour (daughter), Simon Noah Imani (son) and Syprose A. Owiti 
(Mum) for their prayers and enduring support during the study period. 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 


ACKNOWLEDGEMENT 

I take this great moment to thank God the Father, the Son and the Holy Spirit 
for the good health I enjoyed throughout the study period. My family and I 
will forever serve in the house of the Lord. 

My sincere gratitude goes to my supervisors Dr. Judith Munga and Dr. Joseph 
Kobia of Kenyatta University, Department of Food, Nutrition and Dietetics for 
their professional guidance and constructive inputs throughout my research 
work. Their time to time supervision and prompt feedback ensured that I 
worked and delivered my best effort within the limited time frame. 

I am highly grateful to convey my heartfelt gratitude to Dr. Celine Termote, 
Mr. Francis Odhiambo and Bioversity International, Kenya for allowing me to 
use their data for this master thesis. My sincere gratitude goes to Dr. Sophie 
Ochola of Kenyatta University for her willingness and readiness to share her 
rich knowledge and experience in micro-nutrient data analysis and guidance in 
formulation of my study objectives. 

I wish to reserve my thanks to Prof. Okello Abonyo and his family for their 
material support, motivation and sense of love during my study. They never 
hesitated to support me in realization of my success. Lastly, I extend my 
gratitude to my parent, brothers, sisters and friends for their unlimited support 
and prayers throughout my studies. 

 

 

 

 

 

 

 

 

 

 

 


TABLE OF CONTENTS 
Declaration................................................................................................................... II 
Dedication .................................................................................................................. III 
Acknowledgement ..................................................................................................... IV 
List of figures ............................................................................................................. XI 
List of tables.............................................................................................................. XII 
Abbrevations and acronyms ................................................................................. XIII 
Definition of terms ................................................................................................. XIV 
Operation definition of terms ............................................................................... XVI 
Abstract .................................................................................................................. XVII 
CHAPTER ONE: INTRODUCTION ........................................................................ 1 
1.1 Background information .......................................................................................... 1 
1.2 Problem statement .................................................................................................... 3 
1.3 The Purpose of the study.......................................................................................... 5 
1.4 Objectives of the study............................................................................................. 6 
1.5 Hypothesis of the study ............................................................................................ 6 
1.6 Significance of the study .......................................................................................... 7 
1.7 Limitation ................................................................................................................. 7 
1.8 Delimitation ............................................................................................................. 7 
1.9 Conceptual framework ............................................................................................. 8 
CHAPTER TWO: LITERATURE REVIEW ......................................................... 10 
2.1 Demographic and socio-economic characteristics of pastoralist and agro-
pastoralist communities ............................................................................................... 10 
2.2 Dietary diversity of children 6-23 months among pastoralist and agro-pastoralist 
communities ................................................................................................................. 11 
2.3 Nutrient adequacy of children 6-23 months among pastoralist and agro-pastoralist 
communities ................................................................................................................. 13 
2.4 Relationship between dietary diversity and nutrient adequacy of of children 6-23 
months .......................................................................................................................... 13 
2.5 Summary of literature review ................................................................................ 14 
CHAPTER THREE: METHODOLOGY................................................................ 16 
3.1 Research design ..................................................................................................... 16 
3.2 Study variables ....................................................................................................... 16 
3.3 Study area............................................................................................................... 16 
3.4 Target population ................................................................................................... 17 
3.4.1 Inclusion criteria .............................................................................................. 17 
3.4.2 Exclusion criteria............................................................................................. 17 
3.5 Sample size ............................................................................................................ 18 
3.6 Sampling techniques .............................................................................................. 18 
3.8 Research instruments ............................................................................................. 21 
3.9 Pre-testing of instruments ...................................................................................... 21 
3. 9.1 Validity ........................................................................................................... 21 
3. 9.2 Reliability ....................................................................................................... 22 
3.10 Data collection procedures and techniques .......................................................... 22 
3.11 Data analysis and presentation ............................................................................. 23 
3.12 Logistical and ethical consideration..................................................................... 24 
CHAPTER FOUR: RESULTS ................................................................................. 25 
4.0 Introduction ............................................................................................................ 25 
4.1 Demographic and socio-economic characteristics of the participants ................... 25 
4.1.1 Demographic characteristics of the participants ............................................. 25 
4.1.2 Socio-economic characteristics of pastoralist and agro-pastoralist................. 27 
4.1.3 Hygiene and sanitation of pastoralist and agro-pastoralist.............................. 28 
4.2 Dietary diversity of children aged 6-23 months in pastoralist and agro-pastoralist 
communities in the previous 24 hours ......................................................................... 29 
4.2.1 Food consumption pattern for children aged 6-23 months based on 24 hour-
recall ......................................................................................................................... 30 
4.2.2 Individual dietary diversity score of children (6-23) months among pastoralist 
and agro-pastoralist households in the previous 24 hours ........................................ 32 
4.2.3 Minimum dietary diversity of children (mdd) among pastoral and agro-
pastoral communities................................................................................................ 35 
4.2.4 Minimum meal frequency of children mmf-c (6-23 months) ......................... 36 
4.2.5 Minimum acceptable diet ................................................................................ 37 
4.3 Nutrient adequacy among children aged 6-23 months .......................................... 38 
4.3.1 Micronutrient intakes among children 6-23 months at various percentages of 
rni across the two livelihood zones .......................................................................... 41 
4.3.2 Nutrient adequacy ratio (NAR) and mean adequacy ratio of pastoralist and 
agro-pastoralist children ........................................................................................... 43 
4.4 Relationship between variables.............................................................................. 44 
4.4.1 Relationship between dietary diversity and nutrient adequacy ....................... 44 
4.4.2 Relationship between dietary diversity of children aged 6-23 months and 
demographic and socio-economic characteristics of the households ....................... 45 
CHAPTER FIVE:DISCUSION ................................................................................ 46 
5.0 Introduction ............................................................................................................ 46 
5.1 Demographic and socio-economic characteristics of the participants. .................. 46 
5.1.1 Marital status ................................................................................................... 46 
5.1.2 Gender of the household head ......................................................................... 47 
5.1.3 Household size ................................................................................................ 47 
5.1.4 Age of the household head .............................................................................. 48 
5.1.5 Educational level of the participants ............................................................... 49 
5.2 Dietary diversity score of children age 6-23 months among pastoralist and agro-
pastoralist community .................................................................................................. 50 
5.2.1 Minimum dietary diversity of children aged 6 to 23 months in turkana ......... 52 
5.2.2 Minimum meal frequency of turkana children aged 6 to 23 months .............. 53 
5.3 Energy and macro-nutrient intake of children ....................................................... 54 
5.4 Micronutrient intake among children 6-23 months ............................................... 55 
5.5 Mean adequacy ratio (mar) of pastoralist and agro-pastoralist .............................. 56 
5.6 Relationship between dietary diversity and maternal demographic and socio-
economic characteristics .............................................................................................. 57 
5.6.1 Dietary diversity and marital status ................................................................. 57 
5.6.2 Dietary diversity and occupation/ income ....................................................... 57 
5.6.3 Dietary diversity and sex of the household head............................................. 58 
5.6.4 Dietary diversity and maternal age.................................................................. 58 
5.6.5 Dietary diversity and age of the household head ............................................ 59 
5.6.6 Dietary diversity and mother education level ................................................. 59 
5.6.7 Dietary diversity and household head education level .................................... 60 
5.6.8 Dietary diversity and household size .............................................................. 60 
5.7 Hypothesis testing .................................................................................................. 61 
CHAPTER SIX: SUMMARY, CONCLUSSIONS AND RECOMMENDATIONS..................................................................................................................................... 63 
6.0 Introduction ............................................................................................................ 63 
6.1 Summary ................................................................................................................ 63 
6.2 Conclusions ............................................................................................................ 65 
6.3 Recommendation for policy, practice and further research ................................... 66 
6.3.1 Recommendation for policy ............................................................................ 66 
6.3.2 Recommendation for practice ......................................................................... 67 
6.3.3 Recommendation for further research ............................................................. 67 
REFERENCES ........................................................................................................... 69 
APPENDICES ............................................................................................................ 78 
APPENDIX A: INFORMED CONSENT ................................................................... 78 
1. Procedure to be followed ...................................................................................... 78 
2. Denefits and compensation ................................................................................... 79 
3. Discomfort and risks ............................................................................................. 79 
4. Confidentiality ...................................................................................................... 79 
5. Voluntary participation ......................................................................................... 79 
6. Contact information .............................................................................................. 80 
7. Participant.s statement .......................................................................................... 81 
8. Investigator.s statement ........................................................................................ 81 
APPENDIX B: DEMOGRAPHIC AND SOCIO-ECONOMIC INFORMATION .... 82 
APPENDIX C:INDIVIDUAL DIETARY DIVERSITY QUESTIONNAIRE ........... 86 
APPENDIX D: HOUSEHOLD AGROBIODIVERSITY SURVEY 
QUESTIONNAIRE ..................................................................................................... 89 
1. Household on – farm species edible diversity ...................................................... 89 
2. Household wild edible plant species diversity ..................................................... 90 
3. Domesticated animal species maintained by the household ................................. 91 
4. Wild animal species hunted or collected by the household .................................. 92 
APPENDIX E: QUANTITATIVE 24-HOUR RECALL QUESTIONNAIRE ........... 93 
1. 24 – Hour recall form for the child ....................................................................... 94 
APPENDIX F: MARKET SURVEY SHEET ............................................................. 95 
APPENDIX G: KREJCIE AND MORGAN TABLE OF SAMPLE SIZE 
DETERMINATION .................................................................................................... 96 
APPENDIX H: KU RESEARCH APPROVAL AND AUTHORIZATION .............. 97 
APPENDIX I: KENYTTA UNIVERSITY ETHICAL CLEARANCE ...................... 98 
APPENDIX J: RESEARCH PERMITS .................................................................... 100 
APPENDIX K: MAP OF TURKANA COUNTY ..................................................... 102 


 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 


LIST OF FIGURES 

Figure 1. 1 Conceptual framework on factors affecting dietary diversity and nutrient 
adequacy ........................................................................................................................ 8 
Figure 3. 2: Study sampling techniques ....................................................................... 20 


 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 


LIST OF TABLES 

Table 3. 1 Study Variables ........................................................................................... 16 
Table 3. 2 Data Analysis Matrix .................................................................................. 23 
Table 4. 1 Demographic characteristics of pastoralist and agro-pastoralist ................ 26 
Table 4. 2 Socio-economic characteristics of pastoralist and agro-pastoralist ............ 28 
Table 4. 3 Hygiene and sanitation of the community .................................................. 29 
Table 4. 4 Foods patterns for children aged 6-23 months (Food groups consumed)... 31 
Table 4. 5 Individual dietary diversity Score for breastfed children (6-23 months) 
among pastoral and agro-pastoral community ............................................................. 33 
Table 4. 6 Individual dietary diversity score for non-breastfed children (6-23 months) 
across the two communities in the previous 24 hours ................................................. 34 
Table 4. 7 Minimum Dietary Diversity of children (MDD-C) by Aage in the previous 
24 hours ........................................................................................................................ 36 
Table 4. 8 Minimum Meal Frequency of children MMF-C (6-23 months) in the 
previous 24 hours ......................................................................................................... 37 
Table 4. 9 Minimum Acceptable Diet of children aged 6-23 in the previous 24 hours..................................................................................................................................... 38 
Table 4. 10 Mean intakes of macro-nutrients per day across the two livelihood zones 
in the previous 24 hours ............................................................................................... 40 
Table 4. 11 Micro-Nutrient Intake of children across the two livelihood zones in the 
previous 24 hours. ........................................................................................................ 42 
Table 4. 12 Nutrient Adequacy Ratio (NAR) of pastoralist and agro-pastoral ........... 43 
Table 4. 13 Relationship between dietary diversity and nutrient adequacy ................ 44 
Table 4. 14 Relationship between dietary diversity and maternal demographic and 
socio-economic characteristics .................................................................................... 45 


 

 


ABBREVATIONS AND ACRONYMS 

ASALs Arid and Semi- Arid Lands 

ASF Animal Source Foods 

CDDS Child Dietary Diversity Score 

CHEWs Community Health Extension Workers 

CHVs Community Health Volunteers 

DDS Dietary Diversity Score 

FANTA Food and Nutrition Technical Assistance 

GAM Global Acute Malnutrition 

GDP Gross Domestic Products 

HDDS High Dietary Diversity Score 

HH Household Head 

IPC Integrated Phase Classification 

IYCF Infant and Young Child Feeding 

KPHC Kenya Population and Housing Census 

KII Key Informant Interview 

KNBS Kenya National Bureau of Statistics 

LDDS Low Dietary Diversity Score 

MAR Mean Adequacy Ratio 

MDDS-C Mean Dietary Diversity Score-children 

MoH Ministry of Health 

NACOSTI National Commission of Science, Technology and Innovation 

RDA Recommended Dietary Allowances 

SAM Severe Acute Malnutrition 

SD Standard Deviation 

SDGs Sustainable Development Goals 

SPSS Statistical Package for Social Sciences 

UNICEF United Nations Children Emergency Fund 

WHO World Health Organization 

 

 

 


DEFINITION OF TERMS 

Chronic Food Insecurity is a long-term or persistent inability to meet minimum food 
consumption requirement as a result of overwhelming poverty indicated by a lack of 
assets (means of living) (Food, 2015). 

Dietary diversification intervention is an intervention that change food consumption 
at the household level, such as increasing the consumption of animal-source foods 
(Gibson and Anderson 2009; Gibson, Perlas, and Hotz 2006) 

Food security a situation that exists when all people, at all times, have physical, 
social and economic access to sufficient, safe and nutritious food that meets their 
dietary needs and food preferences for an active and healthy life (FAO. 2002) 

GAM is the percentage of children, aged 0 to 59 months, whose height-for-age is 
below minus two standard deviations (moderate and severe stunting) and minus three 
standard deviations (severe stunting), from the median of the WHO Child Growth 
Standards (WHO, 2017). 

Household Dietary Diversity refers to as the number of different foods or food 
groups consumed over a given referenced period (Keding, Schneider, & Jordan, 
2013). 

Hunger is a short-term physical discomfort as a result of chronic food shortage, or in 
severe cases, a life-threatening lack of food. (National Research Council, 2006) 

Individual dietary diversity score (IDDS) was for 8 groups of foods which include, 
Breast milk, cereals (grains roots and tubers), legumes and nuts, dairy products (milk, 
yogurt, cheese), flesh foods (meat, fish, poultry and liver/organ meats), eggs, vitamin-
A rich fruits and vegetables, and other fruits and vegetables. Consumption of five (5) 
groups of food within the previous 24 hours will be considered adequate ((FAO, 
2012). 


Malnutrition is defined as a state when the body does not have enough or excess of 
required macro and micronutrient nutrients for physiological functioning (World 
Health Organization, WHO, 2010). 

Minimum Accepted Diet is a composite indicator of minimum dietary diversity and 
minimum meal frequency; it is the proportion of children 6-23 months of age who 
receive a minimum diversified diet and minimum meal frequency (World Health 
Organization, 2016). 

Minimum Dietary Diversity for children ages 6-23 months defined as the proportion 
of children ages 6-23 months who receive minimum dietary diversity score of at least 
five (5) Food groups from eight food groups with breast milk as a food group, the 
previous day (World Health Organization, 2016). 

Minimum Meal Frequency child receives solid, semi-solid, or soft foods (but also 
includes milk for non-breastfed children) the minimum number of times or more over 
the previous day (World Health Organization, 2016). 

Nutrient insecurity refers to the insufficient supply of essential macro and 
micronutrients despite the adequate food supply (McGuire, 2015); Yen et al., 2011). 

Stunting refers to low height or length-for-age that is less than or equal to -2 SD 
below the mean of the reference population (Z =-2) (WHO, 2010). 

Z-scores refers to the number of Standard Deviations (SD) below or above the 
reference median value (WHO, 2006). 

 

 

 

 

 


OPERATION DEFINITION OF TERMS 

Agro-pastoralists are people who practice pastoralism and small scale agriculture as 
a source livelihood. 

Cultural factors are norms and beliefs about foods and dietary diversity practices. 
Myths surrounding acquiring, consumption and utilization of foods in the household 
were classified as cultural factors. 

Food consumption patterns this refers to the number of foods groups consumed by 
children 6-23 months in the previous 24 hours. 

Lucille program is food intake software developed by university of Ghent, Belgium 
which enhances computation of specific nutrients of different foods per 100g of 
cooked food. 

Nutrient Adequacy this will include adequate intake energy, protein, vitamin A, iron 
and zinc, fiber and water consumed adequately. 

Pastoralist referred to people who derived most of their subsistence and income from 
keeping livestock under natural pastures. 

RAND function referred to a preset formula, which helps perform mathematical, 
statistical and logical operations. 

Shambas is a Kiswahili word that refers to a piece of land under cultivation. Referred 
to a small subsistence farm for growing crops and fruits-bearing trees, often including 
the dwelling of the farmer. 

 


 

 

 


ABSTRACT 

Malnutrition is a public health concern in many arid and semi-arid lands (ASALs) 
areas. Literature shows that Africa is the continent experiencing the highest number of 
food emergencies particularly in the ASALs. In Kenya, high cases of malnourished 
children among the pastoralist communities have typically increased. Despite the 
large herd of cattle and camels among the pastoralists community of Turkana, there 
are high rates of poor physical growth in children, impaired cognition, high morbidity 
and mortality. Global acute malnutrition (GAM) rate remains at 20.2 percent, while 
the prevalence of underweight and stunting rates remain at 31.2 and 25.3 percent 
respectively. Food-based strategies such as agro-pastoralism had been recommended 
as the first priority to meet micronutrient needs in Loima Sub-county by Ministry of 
Devolution and Planning in 2015. However, the contribution of this intervention to 
dietary diversity and nutrient adequacy of children (6-23 months) in these households 
had not been determined. This study analyzed and compared the dietary diversity and 
nutrient adequacy of pastoralists and agro-pastoralist communities in Loima Sub-
County in Turkana County. The study adopted cross-sectional analytical study design 
that expedited collection of quantitative and qualitative data and enabled 
documentation of differences between the two communities and additionally 
determined associations between the dependent and independent variables of the 
study. A sample size of 248 children was selected to participate in the study. The 
study tools were 24-hour Recall to collect the information on foods consumed 24 
hours preceding the interview, dietary diversity questionnaires were used to gather 
information on foods consumed by the children seven days preceding the interview 
and structured questionnaires used to collect data on social demographic 
characteristics. Data was analyzed using SPSS version 21.0. Socio-demographic 
attributes such as education, marital status, household size, and age were analyzed by 
descriptive statistics such as frequency, percentages, median and mode. Nutrient 
adequacy of macronutrient (Energy, carbohydrate, lipids, protein, fiber and water) and 
micronutrients (iodine, iron, and vitamin A) were analyzed using Lucille Program. T-
test was used to determine differences between continuous variables in the two study 
groups. Chi-square was used to test for associations between the variables. A p=0.05 
level of significance applied. Study results showed that 95.0% of the participants both 
in pastoral and agro-pastoral communities were married. Household size was 
established at 7.0 in both pastoral and agro-pastoral zones. About 90.9% of children 
both from pastoral and agro-pastoral communities had drawn energy from grains, 
white roots and tubers and plantains in form of Ugali. Mean Dietary Diversity score 
among agro-pastoral children was 4.19 ±1.043 compared to pastoral 3.79 ±1.249. 
Only (30.8%) of children from pastoral and agro-pastoral communities had attained a 
Mean Dietary Diversity Score of more than five with breast milk as food group. 
About a quarter, (26.0%) of breastfeeding children aged 6-8.9 months from the two 
communities had met a minimum meal frequency of 4 meals a day. Only a third 
(29.4%) of breastfed children across the two zones had met required Minimum 
Acceptable Diet. There was a positive correlation between the consumption of energy, 
carbohydrates, Proteins, Vitamins A, Riboflavin, Vitamin C and other nutrients with 
Individual Dietary Diversity Score for Children, with p==0.001. The result also 
showed positive correlation between the age of the mothers and Iron consumed by the 
children, r =0.191, p =0.004. The study recommends that future research should 
assess dietary patterns in other seasons of the year and compare the dietary score of 
children during those seasons since this study was conducted during dry season. 


CHAPTER ONE: INTRODUCTION 

1.1 Background Information 

Dietary diversity is a recommended strategy of improving nutritional condition 
arising from inadequate intake of micronutrients. Dietary diversification is important 
to dietary adequacy since no single food, besides breast milk for exclusive 
breastfeeding, which contains all the required essential macro and micronutrient for 
optimal health and nutritional status (Barrett, 2010). Consumption of a wide variety of 
different food groups and items is essential in promoting and maintaining adequate 
intake of micronutrient among children. 

Dietary diversification has been universally identified as a proxy measure for high 
quality diets. A diverse diet containing a wide range of food groups such as 
vegetables, fruits, cereals, meat, legumes and dairy products is fundamental for 
achieving the Recommended Dietary Allowances (Bukania et al., 2014; Abebe, Haki, 
& Baye, 2016). However, monotonous diets, primarily based on cereals, roots and 
tubers which are common in Arid and Semi-Arid Lands (ASALs) part of Kenya 
contribute to high rates of malnutrition. Macro and micronutrient deficiencies are a 
public health concern in most Arid and Semi-arid regions among pastoral 
communities due to low dietary diversity score and mean adequacy ratio (Keding, 
Schneider & Jordan, 2013). 

FAO reports have further established that overall nutritional quality of the diet is 
improved with dietary diversity (FAO, 2012). Dietary diversity is, therefore, an 
essential aspect of nutrition practices which aids in meeting the requirements for 
energy and other essential nutrients among children from pastoral and agro-pastoralist 
community. A low dietary diversity score has been linked to stunted growth, 


cardiovascular risk, dyslipidemia and higher probability of metabolic syndrome 
among children (Boedecker et al 2019). 

In addition, human growth, development, and health throughout the life course, from 
preconception to adulthood, are dependent upon adequate nutrition (FAO. 2015). 
Nutrient adequacy refers to being nutrient secure through appropriate consumption of 
recommended dietary allowance of energy and all essential nutrients. Nutrient 
adequacy enhances optimal nutritional status among children in which both under and 
over nutrition disorders are avoided. It is a pre-requisite for normal growth, 
development, and health. Pre-school children in their first and second years of life are 
nutritionally at risk, mainly when they are fed on a limited range of foods 
(Burlingame, 2011). There are several dietary factors which may prompt household to 
feed children on high calorie diet but nutrient poor. These diets lead to low nutrient 
adequacy score. High malnutrition cases have been reported in Kenya especially from 
the pastoralism communities due to low nutrient adequacy score (World Health 
Organization, 2017). 

Despite the improvement of nutrition situation in Arid and Semi-Arid Lands in Kenya 
(ASALs) based on the Integrated Phase Classification (IPC) for Acute Malnutrition, 
the level of Acute Malnutrition remains at Critical level (Phase 4; GAM WHZ 15.0 -
29.9 percent) in Turkana County (IPC Global Platform, Feb, 2020). The nutrition 
situation is anticipated to continue remaining in the same phase as a result of the 
scale-down of the emergency nutritional interventions such as Blanket Supplementary 
Feeding Program (BSFP) and other nutrition outreaches. Compared to June 2019 IPC 
report, the general nutrition situation has slightly improved in Turkana County though 


the rates of acute malnutrition are still critical (Phase 4), which is 15-29.9 percent of 
children acutely malnourished with elevated mortality and morbidity levels. 

Nutrient insecurity is an endemic problem among pastoralists in the arid and semi-
arid lands (ASALs) (Waterlander et al., 2010). The majority of Kenyan pastoralists 
inhabit the ASALs, where livestock rearing is the primary source of income. The 
ASALs population has limited livelihood options (Ministry of Devolution and 
Planning, 2015). Recurrent droughts seasons have become frequent and gradually 
diminishing pastoralist income reservoirs without allowing them ample duration to 
readjust from the shock. Even though some families cope with meager cash transfer 
from extended relatives working in towns, majority of the ASALs populations 
exclusively survive on social protection mechanisms such as relief food. 

WHO reports of 2017 established that over seventy-five percent (75.0%) of the ASAL 
populations live below poverty line with limited livelihood options, leading to low 
individual dietary diversity score (World Health Organization, 2017). Agro 
pastoralism has been introduced by Save the Children International Organization and 
World Vision in some parts of Turkana bordering Lake Turkana region to help in 
diversifying the livelihood activities. However, for the past five years, Global Acute 
Malnutrition rates have been ranging from 10 to 28 percent, exceeding the emergency 
threshold of 15 percent set by WHO (World Health Organization, 2017). 

1.2 Problem Statement 

Micronutrient malnutrition is a serious public health concern in many African 
countries. Children aged 5 years and below are disproportionately affected due to 
higher physiologically micronutrient requirements during early childhood stage. The 
impact of inadequate nutrient intake is transmitted even into adulthood, resulting to 


stunted growth, low productivity and reduced performance in school. In Turkana 
County, it is estimated that 31,225 children (54 percent) suffer from acute 
malnutrition (Turkana County Smart Nutrition Surveys Final Report, 2020). Despite 
this high rate of malnutrition in Turkana, children dietary diversity score and mean 
adequacy ratio has received insufficient attention particularly among the pastoralists 
and agro-pastoralists communities. In Loima Sub County for instance, there is no 
reported data on children.s food intake. 

Pastoralism culture is production system for the majority of Africans occupying arid 
and semi-arid land. Approximately, about 268 million Africans are pastoralists, thus 
making the pastoral culture as a core part of African's culture, history, and heritage 
(World Health Organization, 2017). Despite the crucial contribution of pastoralists 
and agro-pastoralists to the African economies, their food intake and nutritional status 
is the poorest among all communities in Africa. Their economic contribution is not 
reflected in their food intake and dietary diversity (Parlesak, Geelhoed & Robertson, 
2014). 

Standardized Monitoring and Assessment of Relief and Transitions (SMART) 
Nutrition surveys conducted in September 2019 reported GAM rates in Turkana 
County ranging from 17.2 percent to 31.1 percent (Turkana County Smart Nutrition 
Surveys Report, 2020). These figures indicated the nutrition situation was ranging 
from poor to critical situation with 31,225 children suffering from acute malnutrition 
and at high risk of dying. The report further classifies 14,420 of these children as 
being severely malnourished, and in need of urgent treatment to avoid further 
deterioration of their situation. 


According to Turkana Smart Nutrition Survey conducted on February 2019, the total 
number of children requiring treatment of acute malnutrition in the ASAL areas has 
increased to 343,559 (MAM-268,549 and SAM 75010) from 294,330 (MAM 233,700 
and SAM 60,600) in August, 2018 (Turkana County Smart Nutrition Surveys Report, 
2019). 

High rates of malnutrition among children in Turkana are attributed to low dietary 
diversity score and nutrient adequacy score. Food-based strategies such as agro-
pastoralism livelihood have been recommended as nutrition intervention programs to 
meet micronutrient needs in Loima (Ministry of Devolution and Planning, 2015). The 
International Council for Research in Agroforestry (ICRAF) introduced agro-
pastoralism in Loima Sub County in Turkana; however, its contribution to dietary 
diversity and nutrient adequacy has not been established. This study will therefore 
focus to compare individual dietary diversity score (IDDS) and nutrient adequacy 
among children aged 6-23 months among pastoralists and agro-pastoralist 
communities of Loima Sub-County in Turkana County. 

1.3 The Purpose of the Study 

This study aimed at examining the nutrient adequacy and dietary diversity among the 
children aged 6-23 months of pastoralist and agro-pastoralist groups in Loima Sub 
County in Turkana County. 

 

 


1.4 Objectives of the Study 

The objectives of this study were: 

1. To determine demographic and socio-economic characteristics of the 
pastoralist and the agro-pastoralist communities in Loima Sub County in 
Turkana County. 
2. To compare dietary diversity of children aged 6-23 months among pastoralists 
and agro-pastoralist communities in Loima Sub County in Turkana County. 
3. To determine nutrient adequacy of children aged 6-23 months among 
pastoralist and agro-pastoralist communities in Loima Sub County in Turkana 
County. 
4. To establish the relationship between dietary diversity, demographic and 
socio-economic characteristics of children aged 6-23 months among 
pastoralist and agro-pastoralist communities in Loima Sub County in Turkana 
County. 


1.5 Hypothesis of The Study 

H01: There is no significant difference in dietary diversity of children aged 6-23 
months between Pastoralist and Agro-pastoralist communities of Turkana County 

H02: There is no significant difference in nutrient adequacy of children aged 6-23 
months between Pastoralist and Agro-pastoralist communities of Turkana County 

H03: There are no associations between dietary diversity and nutrient adequacy of 
children aged 6-23 months among Pastoralists and Agro-pastoralists communities of 
Turkana County 


H04: There are no associations between the dietary diversity of children aged 6-23 
months and demographic and socio-economic characteristics of households among 
Pastoralists and Agro-pastoralists communities of Turkana County 

1.6 Significance of the Study 

The study findings can be used to inform the Ministry of Agriculture, Livestock, 
Fisheries and Cooperatives and Non-Governmental Organizations on programs aimed 
at improving dietary diversity and nutrient adequacy among the pastoral communities. 
The findings can further be used by the national government and the County 
Government of Turkana to make informed policies and regulations regarding the 
promotion of dietary diversity and nutrient adequacy among pastoralist and agro-
pastoralist groups in Turkana County. In addition, the findings can be added to the 
body of knowledge on the relationship between dietary diversity and nutrient 
adequacy among pastoralist and agro-pastoralist livelihoods. 

1.7 Limitation 

Since the study adopted cross-sectional analytical design, the data was collected at 
one point in time and hence not extrapolated to varying seasons of the year. The study 
was conducted in the month of September, which is a dry season in Turkana County. 
Dietary data was collected on a recall basis hence recall bias reduced by collecting 
24-hour recall on 3 separate days of the week (Monday, Thursday and Saturday). 

1.8 Delimitation 

The study was carried out in only pastoralist and agro-pastoralist communities in 
Loima Sub County targeting households with a child within the age bracket of 6-23 
months. Loima Sub County was selected since it had got high malnutrition rate with 


the global acute malnutrition (GAM) rate at 20.2 percent, the prevalence of 
underweight and stunting in children rate at 32.1 and 18.2 percent respectively 
(Turkana County Smart Nutrition Surveys Final Report, 2019). 

1.9 Conceptual Framework 

 

Nutrient Adequacy 

 

 

 

Dietary Diversity 

 

 

 

 

Socio-Economic 
Characteristics 

. Income 
. Occupation 
. Education 


 

Demographic 
characteristics 

. Household size 
. Age 
. Marital status 
. Religion 


 

Livelihoods 

. Pastoral 
. Agro pastoral 


 

 

 

 

Figure 1. 1 Conceptual framework on factors affecting dietary diversity and 
nutrient adequacy 

Source: Adapted and modified from UNICEF conceptual framework for 
determinants of malnutrition (2008). 

This study was based on UNICEF conceptual framework for malnutrition (Figure 
1:1). Demographic characteristics such as marital status, household size, age and 
religion directly influence dietary diversity thus nutrient adequacy. Small household 
size has low dependency ratio hence high purchasing power of variety of food items 
to improve dietary diversity and nutrient adequacy. Women headed household are 
likely to record high dietary diversity score than male headed households. Households 


with an elderly population are likely to suffer from low dietary diversity score 
because they have reduced accessibility to various food items (Burlingame, 2011). 

Economic factors like education, level of income and occupation may also associated 
with dietary diversity. Education informs an individual on the nutritional importance 
of consuming fruits and vegetables. Tertiary level of education is associated with high 
dietary diversity score. The level of income influences the purchasing of an 
individual. A household with adequate income to purchase food items may record 
high dietary diversity score than a house with little resources. Occupation may also 
influence an individual.s capacity to buy food (Juma, 2017; Azagba, & Sharaf, 
2011).) 

Other studies have further linked the nutrient adequacy to dietary diversity where low 
dietary diversity score (LDDS) leads to low mean adequacy ratio while high dietary 
diversity Score improve nutrient adequacy (Taruvinga, Muchenje & Mushunje, 2013; 
Vereecken, Covents, & Maes, 2010). 

 

 

 

 

 

 

 


CHAPTER TWO: LITERATURE REVIEW 

2.1 Demographic and Socio-Economic Characteristics of Pastoralist and Agro-
Pastoralist Communities 

Pastoral communities are those communities who derive most of their subsistence and 
income from keeping livestock under natural pastures whereas agro-pastoral 
communities are those communities who practice pastoralism and small scale 
agriculture as a source of livelihood. 

 According to Mayanja, Maureen, et al., (2015), large households have more people 
available for herding, thus increasing income. The study further established that large 
households spend little or no money hiring labour, since they can produce their own 
labour. Sufficient labour at the household level is likely to improve nutrient security 
since more effort is directed towards livestock production and other income sources 
(Azagba & Sharaf, 2011; Li et al., 2012). Despite the contribution of these studies, 
there is limited information on how household size affects dietary diversity and 
nutrient adequacy of children aged (6-23 months) among pastoralist and agro-
pastoralist communities of Turkana. 

Gender of household heads has also been associated with dietary diversity and 
nutrient adequacy. According to (Dehghan et al., 2011) households headed by females 
are likely to access more diversified diet than male-headed households. Silk et al. 
(2008) further established that female-headed households give priority to food 
purchase in their budget rather than non-food purchase. A study conducted by Rani, 
Arends, & Brouwer, (2010), confirmed that female-headed households in ASALs 
engage in many other economic activities like selling honey, weaving and small-scale 
business, thus increasing their level of income for purchasing food items. Despite 


these findings, no single study has reported on the composition of the household 
heads among the pastoralist and agro-pastoralist communities in Loima Sub County. 

A study conducted by Finkelstein & Strombotne, (2010) reported that education level 
attained by the household head plays a major role in an individual.s decision-making 
on how to spend the household income which has an impact on dietary diversity. 

Barrett (2010) confirms that household heads with formal education have a better 
chance of securing civil employment to supplement livestock production. However, 
no study has reported the level of education of pastoralists and agro-pastoralist 
communities in Loima Sub County. 

Finkelstein & Strombotne (2010) noted that with an increase in age, the head has 
more wisdom and experience in livestock production and livelihood diversification. 
Finkelstein & Strombotne (2010) further established that with advanced age, 
household heads are capable of making good decisions on dietary diversity based on 
the past experience they have had during the dry and wet seasons. However, 
households with younger heads in ASALs region are believed not to have good 
experience in food planning (Keding et al., 2012). Despite the contribution of the age 
of the household heads, no study has reported on the age of the household heads 
among pastoralist and agro-pastoralist communities in Loima Sub-County. This study 
therefore determined demographic and socio-economic characteristics of the 
pastoralist and agro pastoralist communities. 

2.2 Dietary Diversity of children 6-23 months among Pastoralist and Agro-
Pastoralist Communities 

Dietary Diversity which refers to the number of different foods or food groups 
consumed over a given referenced duration is a good indicator for quality diet (FAO 


and FHI 360, 2016). Dietary diversification of people in a community can be 
established by a variety of factors such as past community consumption pattern and 
traditional behavior. The extent of the available technology related with food 
production, processing, preparation and storage can also be essential in determining 
dietary diversity (Keding, Schneider & Jordan, 2013), seasons in question (Knueppel, 
Demment, & Kaiser, 2010), agricultural biodiversity in the region and diversity of its 
farming systems (Herforth, 2010), economic status of the population (Taruvinga, 
Muchenje, & Mushunje, 2013) and socio-demographic characteristics of 
communities. A study conducted by Barrett (2010) on dietary diversity as a proxy 
indicator of nutrient adequacy further established that a more diversified diet is 
associated with some enhanced outcomes in areas such as growth and development of 
children through acquisition of micronutrients. 

Reports from dietary intake research in the Philippines revealed that large percentage 
of children diets are deficient in Iron, Vitamin A, and Calcium (Denney et al., 2018). 
The study further reported that the average energy intake of preschool children was 
further below the Recommended Dietary Allowance (RDA). Agize, Jara, & Dejenu, 
(2017) further established that more diversified diet enhances hemoglobin 
concentrations. Despite detailed reports on the significance of diet diversification on 
children, no single study has targeted the dietary diversity of children among 
pastoralists and agro-pastoralists communities in Turkana. Therefore, this study aimed 
at filling this gap. 


2.3 Nutrient Adequacy of children 6-23 months among Pastoralist and Agro-
Pastoralist Communities 

The preferred staple food for the majority of pastoral communities is milk from 
livestock while agro pastoralists balance between animal products and farm harvest. 
Pastoral diets are deficient in energy, but adequate in protein from dairy products. 
Lawson et al., (2014) researched on health and nutritional status of Maasai and other 
ethnic groups in Tanzania and reported that over half of the Maasai children had 
stunted growth compared to only 20 percent of agricultural children. This is because 
the Maasai children had little access to carbohydrate, and other essential nutrients. 

In Kenya, a study by Iannotti, & Lesorogol (2014), on dietary intakes and 
micronutrient adequacy related to the changing livelihoods of two pastoralist 
communities in Samburu, focused on the probability of micronutrient intake adequacy 
to livelihood transitions. Iannotti, & Lesorogol (2014), further found that livestock 
ownership was associated with nutrient adequacy for vitamin A, B12, and zinc, while 
income was associated with vitamin C adequacy. Despite the relevance of these 
studies in relationship to pastoralists and agro-pastoralist communities of Turkana, 
none of them reported the nutrient adequacy of children among pastoralist and agro-
pastoralist communities of Turkana. This study therefore aimed at determining the 
nutrient adequacy of children in these two communities. 

2.4 Relationship between Dietary Diversity and Nutrient Adequacy of of children 
6-23 months 

A study of 10 countries including Kenya reported a positive association with 
increasing dietary diversity with energy availability (Juma et al., 2017; Kennedy et 
al., 2010; Stevens et al., 2017). Besides, a review of developing country studies 


further confirms a robust positive association between dietary diversity, nutrient 
adequacy, and energy availability. The review reports suggested that diet diversity 
could be a useful indicator of dietary adequacy (Finkelstein, & Strombotne, 2010). A 
study in South Africa reported dietary diversity score and nutrient adequacy (Keding 
et al., 2012; Amo-Adjei & Annim, 2015). 

 A review of scientific peer reviewed articles on the use of the individual dietary 
diversity and the probability of adequate micronutrient intake, reported that dietary 
diversity scores were valid proxy indicators for energy adequacy and other 
micronutrient adequacy of diets of preschool children and women of reproductive age 
(Kumi-Kyereme, 2014 & Fanzo et al., 2013). This study, therefore, compared nutrient 
adequacy among children of pastoralist and agro-pastoralist communities by using 
individual dietary diversity score as a proxy indicator. The study considered the 
research question “how does household dietary diversity differ between pastoral and 
agro pastoral households?” 

2.5 Summary of Literature Review 

Diverse literature reviewed reveals that indeed dietary diversity is a proxy indicator of 
nutrient adequacy. Reviewed literature further established that low child dietary 
diversity score contributes to stunted growth, low productivity, morbidity, and 
mortality. The dietary diversity score has not been determined between pastoralists 
and agro pastoralist communities. The literature further confirms that micronutrient 
deficiencies a republic concern particularly among the children of the ASALs 
population of Kenya. However, the contribution of agro-pastoralism in child 
malnutrition in the ASALs population of Loima Sub-County has not been explored. 


This study determined dietary diversity and nutrient adequacy of children aged (6-23 
months) among pastoralist and agro-pastoralist communities in Loima Sub-County. 

According to a study conducted by Agize, Jara & Dejenu (2017) on dietary diversity 
as a proxy indicator of nutrient adequacy, it is clearly documented that a more 
diversified diet, through improved acquisition of micronutrients has a positive 
association with some enhanced outcomes in areas such as growth and development 
of children. However, there is limited information on the dietary diversity of children 
among pastoralist and agro-pastoralist communities in Turkana. 

Studies comparing health and nutritional status of Maasai and other ethnic groups in 
Tanzania have established that over a half of the Maasai children had stunted growth 
compared to only 20 percent of agricultural children (Keding, Schneider & Jordan, 
2013 & Stevens et al., 2017). However, these studies did not report information on 
nutrient adequacy among children of pastoralists and agro-pastoralist communities. 
The study therefore, compared dietary diversity and nutrient adequacy of children 
aged (6-23 months) among pastoralists and agro-pastoralists communities in Loima 
Sub-County, Turkana-Kenya. 

 

 

 

 

 

 

 


CHAPTER THREE: METHODOLOGY 

3.1 Research Design 

This study adopted a cross-sectional analytical study design since the survey was 
conducted at one point in time to analyze dietary diversity and nutrient adequacy of 
agro-pastoral and pastoral communities in Loima Sub-County in Turkana County. 
The design established relationship between the dependent and independent variables 
of the study and expedited collection of quantitative and qualitative data to enable 
documentation of differences between the two communities (Almalki, 2016). 

3.2 Study Variables 

Nutrient adequacy was determined using Lucille Program for food intake. Dietary 
diversity was determined using Dietary diversity questionnaires (Appendix C). 
Whereas the relationship between nutrient adequacy and dietary diversity score was 
determined using Chi-square & T-Test as shown in Table 3.1. 

Table 3. 1 Study Variables 

Dependent variables 

Independent variables 

1. Dietary diversity (non-
consecutive 3 days recall, two 
week days and one weekend 
day preferably Saturday) 


. Socio-demographic characteristics 
(i.e., age, marital status and household 
size) 
. Economic characteristics (i.e., income 
and occupation education) 


2. Nutrient Adequacy 


(24 hour Recall) 

. Dietary diversity 
. Socio-demographic characteristics 
(age, marital status and household 
size) 
. Economic characteristics (income and 
occupation education) 




3.3 Study Area 

The study area was Loima Sub County, Turkana County. Loima had a population of 
107,794 (KPHC, 2019). The global acute malnutrition (GAM) rate remains at 20.2 


percent, the prevalence of underweight and stunting in children rate remains at 32.1 
and 18.2 percent respectively (Turkana County Smart Nutrition Surveys Final Report, 
2019). Rainfall in the sub-county follows a reasonably erratic pattern that changes 
over seasons. January, February, and September are the driest months in Turkana. 
Some of the physiographic features in Loima are low-lying open plains, mountain 
ranges and river drainage patterns. The mountain ranges in Loima make the area 
green with dense bushes with high woody cover. These ranges support critical 
economic activities like grazing and other small-scale shambas for agro-pastoralism 
livelihood. 

3.4 Target Population 

The study targeted households in Agro-pastoral and Pastoral with children aged 6-23 
months. These children are primarily targeted since they have been introduced into 
the household pot and their meals would reflect the family dietary diversity and 
nutrient adequacy. 

3.4.1 Inclusion Criteria 

The inclusion criteria for this study was households with children from 6 to 23 
months in both Agro pastoral and pastoral communities in Loima Sub County 
Turkana County 

3.4.2 Exclusion Criteria 

Households with children aged 6-23 months in pastoral and agro pastoral 
communities in Loima Sub County but on a special diet due to illness or other reasons 
were excluded in the study. 


3.5 Sample Size 

Krejcie and Morgan, (1970) table of sample size determination from finite population 
was used to estimate desired sample size. 

The total population of children aged 6-23 months in both pastoral and agro-pastoral 
zones in Loima was 550 children. Therefore, the sample size representative of 
children aged 6-23 months was 226 children as shown in (appendix H). 

A further 10% (22 children) was added to cater for non-response, 226+22 =248 
children. 

Hence, 248 children were the calculated study sample size of children ages 6-23 
months in both pastoral and agro-pastoral livelihoods. 

3.6 Sampling Techniques 

Loima Sub County was purposively sampled because of the following reasons; it had 
both the targeted pastoralism and agro-pastoralism livelihood while pastoralism 
practices only dominate other sub-counties. Loima Sub County was selected since it 
had a high malnutrition rate with the global acute malnutrition (GAM) rate at 20.2 
percent, the prevalence of underweight and stunting in children rate at 32.1 and 18.2 
percent respectively (Turkana County Smart Nutrition Surveys Final Report, 2019). 
Secondly, Loima Sub-County was also sampled out since agro-pastoralism as a food 
intervention strategy has been introduced in the region by various non-governmental 
organizations like Save the Children among others. 

1st stage: The study area was stratified into two livelihood zones: Agro pastoral and 
pastoral livelihood zones. Pastoral villages were densely populated with a population 
of about three times that agro-pastoral villages. Fifteen (15) villages and six (6) 
villages were respectively identified as agro pastoral and pastoral villages in Loima. 


Those identified as agro pastoral villages are Naurenpuu, Nadapal, Tiya, Nakamane, 
Nanyee, Naagis, Kaitese, Nakwapua, Kalemnayang, Kotela, Kablokor, Kangalita, 
Lobei, Naremit, and Lokipetot Arengan. The pastoral villages are Lorugum, Loya. 
Namoruputh, Lokiriama, Urum and Lorengipi. All border-villages were excluded 
during the sampling to reduce cross contamination of food intake across the 
livelihood zones. Among the agro pastoral villages Nakwapua was excluded from the 
sampling frame because it was insecure and inaccessible at the time of the 
reconnaissance visit due to bad roads. As for the pastoral villages Urum and 
Lorengipi were both excluded. The two villages were excluded due to high insecurity 
cases rampant amongst them. 

Three villages per livelihood zone were randomly sampled from the two livelihood 
strata. Pastoral villages were densely populated with about twice the population of 
agro-pastoral villages. Small pieces of papers bearing the names of the villages in the 
sampling frame were folded differently, placed in a bowl, mixed vigorously and an 
independent person not part of the research team asked to pick three from each 
livelihood zone. The pastoral villages sampled were Lorugum, Namoruputh and 
Lokiriama while the agro pastoral villages are Nadapal, Lobei and Kablokor. 

2nd stage: At the household level, sampling frames of all households in the sampled 
villages were composed with the help of the Community Health Extension Workers 
(CHEWs), Community Health Volunteers (CHVs). A sample frame of children 6-23 
months was drawn per village in households with children 6-23 months across the two 
zones. At each livelihood zones, a proportionate to size sampling was conducted to 
get 124 children. In each village a sample frame of children was used to randomly 
select the children to participate in the study using the RAND function of excel. 


Figure 3. 2: Study Sampling Techniques 

 

Loima Sub-County 

• 4 wards 
• 21 villages 


 

 

 

Purposive sampling 

 

 

Purposive sampling 

Pastoralist zone 

• 6 villages 


 

Agro-pastoralist zone 

• 15 villages 


 

 

Exhaustive sampling 

4 villages 

14 villages 

 

 

Random sampling 

3 villages 

3 villages 

 

 

Proportional to size of 
the village 

124 children 

124 children 

 

 

Total sample of children 

The total sample was 248 
children 

 

 

3.7 Recruitment and Training of Research Assistants 

Twelve enumerators were recruited (8 men and 4 women) to assist in this study. This 
was because villages in Loima are far apart. The enumerators were recruited on the 
criteria that they had a minimum of KCSE certificate, had previous experience in data 
collection exercise, and fluent in English, Kiswahili and Turkana languages. The 
enumerators were trained for two days by the Principal Investigator (PI). On the third 
day, pretesting of tools and procedures was carried out. The training focused on: 
objectives of the study, interview techniques, filling of the questionnaires, research 


ethics and storage and tracking of questionnaires (Draper & Swift, 2011). The training 
was conducted through lectures, demonstrations, brain storming and role plays. 

3.8 Research Instruments 

The following tools were used to collect data; 

24-hour Recall questionnaires to gather the information on foods consumed a day 
preceding the interview (Appendix E). A 7-day Frequency Recall used to solicit the 
information on foods consumed seven days preceding the interview (Appendix C). 
Structured Questionnaires to collect data on social demographic characteristics 
(Appendix B). 

3.9 Pre-testing of Instruments 

The study questionnaires were administered to two villages each from both pastoral 
and Agro-pastoral group. The two villages were selected Turkana Central Sub 
County, within Turkana County. Turkana Central Sub-County was selected for 
pretesting of study questionnaires since the sub county has both pastoral and agro-
pastoral communities who are the targeted populations in the study while other sub 
counties were purely dominated by pastoralist communities. 

3. 9.1 Validity 

Validity- content and face validity was done before data collection exercise. A panel 
of nutrition experts from Foods, Nutrition and Dietetics Department, Kenyatta 
University established face validity for clarity of wording, layout, and style and the 
likelihood that the target audience would be able to answer the questions (Young et 
al., 2013). Their feedback was used to improve the tools. For content validity, the 


study used 24 hour recall and Dietary Diversity Questionnaires which are WHO 
validated tools with WHO indicators (World Health Organization, 2017). 

3. 9.2 Reliability 

For reliability, a test-retest method was used at an interval of 2 days. The responses 
were analyzed using Cronbach's Alpha (a) (2005). A reliability coefficient of more 
than 0.7 was considered adequate. This study obtained a co-efficient of 0.83. 

3.10 Data Collection Procedures and Techniques 

The data was collected for a period of seven days to obtain the required sample size. 
A formal self-introduction by the researcher was done, followed by informed consent 
and then data collection. The data collection technique adopted in this study was face-
to-face interviews with the mother or the caregiver. Face-to-face interview helped to 
solicit information on demographic and socio-economic characteristics using pre-
tested structured questionnaires. A 24-hour Recall questionnaire was used to collect 
information on foods consumed in a household a day preceding the interview (World 
Health Organization, 2017). 

Individual Dietary Diversity Questionnaires was used to collect information on foods 
consumed seven days preceding the meeting. To minimize the bias of respondent 
memory lapses, interviews were held following a standardized schedule. First, the 
caregivers were asked to mention all the foods and beverages they had eaten during 
the preceding 24-hours (from the time they woke up the day before the interview to 
the time they woke up again on the day of interview). Then they were asked to state 
the foods and beverages consumed or fed to children, including ingredients and 
cooking methods of mixed dishes. The amounts of all foods, drinks, and components 


of mixed dishes consumed were estimated either in weight, household units (volume 
determined by water content). 

3.11 Data Analysis and Presentation 

Descriptive data such as demographic and socio-economic characteristics collected 
were cleaned, coded, entered in MS Excel and analyzed using Statistical Package for 
Social Scientists (SPSS) version 21.0, 2018. Chi-square test, T-test, Pearson Product 
Moment Correlation were used to analyze study variables at p=0.05 as indicated in 
Table 3.2. Data presentation was done on tables and charts. 

 

Table 3. 2 Data Analysis Matrix 

Objectives 

Variables 

Indicators 

Statistical test 

Socio-
demographic 
characteristics 

Education, 
marital status, 
household size, 
age 

 

Descriptive statistics like 
frequency, percentages, 
Mean, Chi-square test 
and T-test 

Nutrient- 
Adequacy 

Amount of 
selected 
nutrient Intake 

Macronutrient (Energy (1140 
Kcal/day for boys and 
1090Kcal/day for girls, protein 
1.17 g protein/kg per day) Fibre 
and Water. 

Micronutrients(vitamin A 
(300µg), Iron (7.0 mg/d) and Zinc 
(3.0 mg/d) 

Lucille Programe for food 
intake 

Dietary- 
Diversity 

Individual 
Dietary 
Diversity Score 

Individual Dietary diversity 
scores of = 5 food groups 

Mean scores Percentages 

Relationship between socio-demographic characteristics and dietary 
diversity 

Chi-square & T-Test 

Relationship between dietary diversity and nutrient adequacy 

Chi-square & T-Test 

Relationship between pastoralism, agro-pastoralism and dietary 
diversity and nutrient adequacy 

Pearson Product Moment 
Correlation 



 

 


3.12 Logistical and Ethical Consideration 

Approval seeking to conduct the research was obtained from Kenyatta University 
Graduate School. Ethical clearance was obtained from Kenyatta University ethical 
review committee. The research permit to conduct the study in Loima Sub County, 
Turkana was also obtained from National commission for Science, technology and 
innovation (NACOSTI). The participation was voluntary through written consent. The 
confidentiality of information was maintained by ensuring that the information 
gathered was used for the intended research purpose. The participants were treated 
with care and handle with high dignity. 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 


CHAPTER FOUR: RESULTS 

4.0 Introduction 

This chapter presents the findings of the study. The study targeted 248 children; 124 
children from pastoralist community and 124 children from agro pastoralist 
community. The analysis excluded 10 children from agro-pastoral households and 19 
children from pastoral households due to incomplete dietary and socio-economic and 
demographic data from the respondents 

4.1 Demographic and socio-economic characteristics of the participants 

4.1.1 Demographic characteristics of the participants 

Almost half (49.8%) of the households across pastoralist and agro-pastoral 
communities had polygamous marriages with significantly higher proportions 
(58.1%) in pastoral households compared to agro-pastoral households (42.1%) with 
p=0.019. A significantly higher proportion (6.1%) of widows among agro-pastoralism 
were reported compared to (0.0%) in the pastoralist communities (p=0.036). Overall, 
majority (79.9%) of the households were male headed with higher proportions 
(84.8%) in the pastoral community compared to (75.4%) in the agro-pastoral 
communities. The difference was not significant (p=0.085), as shown in Table 4.1 

 

 

 

 

 

 


Table 4. 1Demographic characteristics of pastoralist and Agro-pastoralist 

Variables 

Pastoralism 
(N=105) 

Agro-
pastoralism 

TOTAL 

(N=219) 

Chi-
square 

 

(N=114) 

 

test (P- 

n 

% 

n 

% 

n 

% 

Value) 

Marital 
Status 

 

 

 

 

 

Monogamous 

marriages 

42 

40.0 

57 

50.0 

99 

45.2 

0.137 

 

Polygamous 

marriages 

61 

58.1 

48 

42.1 

109 

49.8 

0.019** 

Widowed 

0 

0.0 

7 

6.1 

7 

3.2 

0.036* 

Single 

2 

1.9 

2 

1.8 

4 

1.8 

0.934 

Sex of 
the 
House 
Head 

Male 

89 

84.8 

86 

75.4 

175 

79.9 

0.085 

Female 

16 

15.2 

28 

24.6 

44 

20.1 

0.064 

 

 

 

 

 

 

 

 

 

Mother’s Age 

 

 

Below 20 

28 

26.7 

29 

25.4 

57 

26.0 

0.836 

20-29 

46 

43.8 

53 

46.5 

99 

46.0 

0.690 

30-39 

27 

25.7 

27 

23.7 

54 

24.7 

0.728 

 

Above 40 

4 

3.8 

5 

4.4 

9 

4.1 

0.830 

Household 
Head’s 
Age 

 

Below 20 

0 

0.0 

3 

2.6 

3 

1.4 

0.094 

20-29 

14 

13.3 

16 

14.0 

30 

13.7 

0.880 

30-39 

56 

53.3 

63 

55.3 

119 

54.3 

0.398 

Above 40 

31 

29.5 

37 

31.1 

68 

31.1 

0.944 

Variables 

Mean (±SD) 

Mean (±SD) 

Mean (±SD) 

t-test (P- 
Value) 

Household Size 

 

8 (±2.9) 

6 (±2.6) 

7 (±2.75) 

0.043* 

Mother’s Age (Mean 
±SD) 

 

27.70 (± 6.57) 

27.49 (± 6.57) 

27.60 (±6.57) 

0.902 

HH’s Age (Mean ±SD) 

 

33.86 (± 9.90) 

31.63 (± 9.44) 

32.75 (±9.67) 

0.845 



** Statistical significance p<0.05 

The overall mean age of mothers was 27.60 (± 6.57) that remained similar in both 
livelihood zones with pastoralist women mean age at 27.70 (± 6.57) while agro-
pastoral 27.60 (±6.57) with (p= 0.902). Majority of mothers were aged between 20-29 


years with about 43.8% pastoral compared to 46.5% agro-pastoral mothers. There was 
no significant difference in mean age of women between the two communities 
(p=0.690). A significantly larger household size was observed among pastoralist 
household 8 (±2.9) compared to agro-pastoralist 6 (±2.6) at p=0.043. 

4.1.2 Socio-economic characteristics of pastoralist and Agro-pastoralist 

About three quarter (65.8%) of the mothers across the pastoral and agro-pastoral 
communities had not attended any formal school. This remained similar (p=0.330) 
across the two livelihood zones with about 65.7% pastoral mothers compared to 
65.8% agro-pastoralist mothers. A significantly higher number of agro-pastoral 
mothers (1.8%) attained post-secondary education compared to pastoral mothers 
(0.0%), even though this still remained low. However, there was no significant 
difference in the number of mothers with post-secondary education between the two 
communities (p=0.140). On overall, about 62.1% of household heads both in pastoral 
and agro-pastoral households had not attended any formal school, with a significantly 
higher proportion (69.3%) of agro-pastoral household heads compared to pastoral 
household heads that reported 54.3%, (p=0.046). 

On overall, only 34.7% of the two communities had access to land for farming, with a 
significantly higher (50.9%) proportion of agro pastoral households compared to 
17.1% pastoral households (p<0.001). 

There was a significantly higher income from subsistence farming among agro-
pastoral households (13.2%) compared to pastoral households 1.0%, (p=0.001) as 
shown in Table 4.2 

 

 


Table 4. 2 Socio-economic characteristics of pastoralist and Agro-pastoralist 

Variables 

Pastoralism 
(N=105) 

Agro-
pastoralism 
(N=114) 

Total 

(N=219) 

Chi-
square 
test (P- 

n 

% 

n 

% 

N 

% 

Value) 

Mothers 
education 
level 

No schooling 

69 

65.7 

75 

65.8 

144 

65.8 

0.330 

Primary 

29 

27.6 

28 

24.6 

57 

26.0 

0.509 

Secondary 

4 

3.8 

1 

0.9 

5 

2.3 

0.120 

Higher than 
secondary 

0 

0.0 

2 

1.8 

2 

0.9 

0.140 

Others 

3 

2.9 

8 

7.0 

11 

5.0 

0.159 

Household head 
Education level 

No Schooling 

57 

54.3 

79 

69.3 

136 

62.1 

0.046* 

Primary 

21 

20.0 

12 

10.0 

33 

15.1 

0.092 

Secondary 

11 

10.5 

8 

7.0 

19 

8.7 

0.700 

Higher than 
Sec. 

9 

8.6 

7 

6.1 

16 

7.3 

0.787 

Others 

7 

6.7 

8 

7.0 

15 

6.8 

0.918 

Source of 
household income 

Sale of own 
animals 

23 

21.9 

38 

33.3 

61 

27.9 

0.059 

Sale of own 
produced 
goods 

35 

33.3 

50 

43.9 

85 

38.8 

0.110 

Casual wage 

22 

21.0 

23 

20.2 

45 

20.5 

0.887 

Small business 

38 

36.2 

44 

38.6 

82 

37.4 

0.713 

Employment 

2 

1.9 

3 

2.6 

5 

2.3 

0.719 

Remittances 

21 

20.0 

16 

14.0 

37 

16.9 

0.239 

Public 
transfers 

6 

5.7 

7 

6.1 

13 

5.9 

0.894 

Subsistence 
farming 

1 

1.0 

15 

13.2 

16 

7.3 

0.001**
* 

Household access to land 

18 

17.1 

58 

50.1 

76 

34.7 

<0.001*** 



** Statistical significance p<0.05 

4.1.3 Hygiene and Sanitation of Pastoralist and Agro-pastoralist 

On overall, 78.1% of the total population from pastoral and agro-pastoral had access 
to piped water, with a significantly higher proportion from agro-pastoral households 
at 93.9% compared to pastoral households reported at 61.0% (p=0.001). A 
significantly higher proportion (39.0%) of pastoral households were found to be 
having access to unprotected spring water compared to agro pastoral reported at 6.1%, 
(p=0.001). Less than a quarter (19.6%) of both pastoral and agro-pastoral 


communities had access to latrine, which remained similar across the livelihood zones 
with pastoral at 21.9% compared to agro-pastoral households at 17.5% (p=0.417). 

Table 4. 3 Hygiene and Sanitation of the community 

Variable 

Pastoral 
(N=105) 

Agro-
pastoralist 
(N=114) 

Total 
(N=219) 

Chi-Square 
(P-Value) 

n 

% 

N 

% 

n 

% 

Sources 
of 
Drinking 
Water 

Piped 
Water 

 

64 

61.0 

107 

93.9 

171 

78.1 

<0.001*** 

Unprotected 
Spring 
water 

 

41 

39.0 

7 

6.1 

48 

21.9 

<0.001*** 

Household access to 
latrine 

23 

21.9 

20 

17.5 

43 

19.6 

0.417 



** Statistical significance p<0.05 

4.2 Dietary diversity of Children aged 6-23 months in Pastoralist and Agro-
pastoralist communities in the previous 24 hours 

Dietary diversity score was computed based on eight (8) foods groups as 
recommended by World Health Organization WHO (2015) to assess diet diversity as 
part of infant and young child feeding (IYCF) practices among children 6-23 months 
old. The 8 food groups include: Breast milk; grains, white roots, tubers and plantains; 
legumes and nuts; dairy products, flesh foods (meat, fish, poultry and organ meats); 
eggs; vitamin-A rich fruits and vegetables; other fruits and vegetables. Counting was 
done on the consumption of any amount of food from each food group except when 
the food item was used as a condiment. 

 


4.2.1 Food Consumption Pattern for Children aged 6-23 months based on 24 
hour-recall 

Over three quarters (80.8%) of children from both pastoral and agro-pastoral 
community had consumed food prepared from grains, white roots, tubers and 
plantains, with higher proportion (85.1%) among agro-pastoral children compared to 
pastoral children which reported 76.2%. There was no significant difference in the 
consumption of food prepared from grains, white roots, tubers and plantains between 
agro-pastoral children and pastoral children (p=0.095). Overall, large proportion 
(82.6%) of children from both pastoral and agro-pastoral communities had an intake 
of dairy products within their meals with higher proportion of pastoral children 89.5% 
compared to agro-pastoral children (76.3%). However, no significant difference in the 
consumption of dairy products between the two livelihood zones was reported, 
(p=0.078). 

About (66.7%) of children from both pastoral and agro-pastoral communities were 
breastfed, which is similar across the two livelihood zones with pastoralist at 67.6% 
compared to agro-pastoral at 65.8%, (p=0.774). Overall, less than a quarter (12.3%) 
of children from both pastoral and agro-pastoral zone had consumed flesh foods 
(meat, fish, poultry and organ meats), with a significantly higher proportion (19.0%) 
among pastoralist children compared to agro-pastoral at 6.1%, (p=0.004). Very few 
children 0.9% from the two communities had consumed eggs, with a higher 
proportion (1.8%) reported among agro-pastoral compared to pastoral children at 
0.0%. There was no significant difference in the consumption of eggs between the 
two livelihood zones (p= 0.173). 


Only 23.3 % of children aged 6-23 months from both pastoral and agro-pastoral 
communities had consumed Vitamin A rich fruits and vegetables with a higher 
proportion (26.3%) reported among agro pastoral compared to pastoral children at 
20.0%. However, there was no significant difference in the consumption of Vitamin A 
rich fruits and vegetables between the two livelihood zones (p= 0.269), as shown in 
Table 4.4. 

Table 4. 4 Foods consumption patterns for children aged 6-23 months (Food 
groups consumed) 

Food Groups 

Pastoral 
(N=105) 

Agro-pastoral 
(N=114) 

Total (N=219) 

p-value 

n 

% 

n 

% 

n 

% 

Breast Milk 

 

71 

67.6 

75 

65.8 

146 

66.7 

0.774 

Grains, white 
Roots, tubers 
and plantains 

91 

86.2 

108 

95.1 

199 

90.9 

0.095 

Legumes and 
nuts 

 

33 

31.4 

44 

38.6 

77 

35.2 

0.267 

Dairy products 

 

94 

89.5 

87 

76.3 

181 

82.6 

0.078 

Flesh Foods 

 

20 

19.0 

7 

6.1 

27 

12.3 

0.004*** 

Eggs 

 

0 

0.0 

2 

1.8 

2 

0.9 

0.173 

Vitamin A 
rich fruits and 
vegetables 

21 

20.0 

30 

26.3 

51 

23.3 

0.269 

Other fruits 
and vegetables 

3 

2.9 

5 

4.4 

8 

3.7 

0.547 



** Classification of eight food groups for Children ages 6-23 months was based on 
WHO (2015), for IYCF classification. Statistical significance p<0.05 


4.2.2 Individual Dietary Diversity Score of children (6-23) months among 
pastoralist and agro-pastoralist households in the previous 24 hours 

The study analyzed and established individual dietary diversity score for breastfed 
and non-breastfed children across the community and presented the findings as 
follows; 

4.2.2.1 Individual Dietary Diversity Score of Breastfed Children (6-23 months) 
among pastoral and agro-pastoral communities 

Mean Dietary Diversity Score among agro-pastoral children was 4.19 ±1.043 
compared to pastoral 3.79 ±1.249, which was below =5 foods groups as 
recommended. There was no significant difference in mean dietary diversity score 
between pastoral and agro-pastoral, (p=0.130). Dietary diversity score of one was 
recorded only among pastoral children (1.4%) compared to agro-pastoral children 
with 0.0%. 

Only (30.8%) of children from pastoral and agro-pastoral communities had attained a 
dietary diversity score of more than five with breast milk as food group, with a higher 
proportion (32.0%) among agro-pastoral compared to pastoral children (29.5%). 
There was no significant different in the proportion of children who had attained 
dietary diversity score of five (5) and above between pastoral and agro-pastoral zone, 
(p=0.903) as shown in Table 4.5. 

 

 

 

 


Table 4. 5 Individual Dietary Diversity Score for Breastfed Children (6-23 
months) among pastoral and agro-pastoral community 

IDDS-C 

Pastoralism 
(N=71) 

Agro-pastoralism 
(N=75) 

Total 
(N=146) 

Chi-
square 

(P-Value) 

n 

% 

N 

% 

n 

% 

1 

2 

2.8 

0 

0.0 

2 

1.4 

0.706 

2 

20 

28.1 

15 

20.0 

35 

23.9 

0.091 

3 

14 

19.7 

17 

22.6 

31 

21.2 

0.243 

4 

13 

18.3 

19 

25.3 

31 

21.2 

0.524 

5 

11 

15.4 

16 

21.3 

27 

18.5 

0.333 

6 

8 

11.2 

6 

8.0 

14 

9.5 

0.255 

7 

3 

4.2 

2 

2.6 

5 

3.4 

0.667 

=5 

21 

29.5 

24 

32.0 

45 

30.8 

0.903 

MDDS-
C (±SD) 

3.79 ±1.249 

 

4.19 ±1.043 

 

3.99 ±1.146 

0.130 



* Dietary diversity Scores (DDS) and Percentage of Breast Fed Children Ages 6-23 
months under each Score. Statistical significance p<0.05 

4.2.2.2 Individual Dietary Diversity Score for Non-Breastfed Children (6-23 
months) among pastoral and agro-pastoral 

Mean Dietary Diversity Score among agro-pastoral children was 3.98 ±1.043 
compared to pastoral children that recorded 3.56 ±1.249. However, there was no 
significant difference in the mean dietary diversity score between pastoral and agro-
pastoral children (p=0.102). 

On overall, about 1.4% of children from pastoral and agro-pastoral had dietary 
diversity score of zero, with a higher proportion 2.9% among non-breastfed pastoral 
children compared to non-breastfed agro-pastoral children that recorded 0.0%. 
However, there was no significant difference in number of non-breastfeed children 
who had a dietary diversity score of zero between pastoral and agro-pastoral 
community. 


Only a quarter (26.0%) of non-breastfed children from both pastoral and agro-pastoral 
had met a dietary diversity score of five and above, with a higher number of children 
among agro-pastoral children at 28.2% compared to pastoral children that recorded 
23.5%. However, no statistical significance difference in the proportion of children 
who had met a dietary diversity score of five and above between pastoral and agro-
pastoral community, (p=0.275) as shown in Table 4.6. 

Table 4. 6 Individual Dietary Diversity Score for Non-Breastfed Children (6-23 
months) across the two communities in the previous 24 hours 

DDS-C 

Pastoralism 
(N=34) 

Agro-
pastoralism 
(N=39) 

Total (N=73) 

Chi-square 

(P-Value) 

n 

% 

N 

% 

n 

% 

0 

1 

2.9 

0 

0.0 

1 

1.4 

0.742 

1 

5 

14.7 

4 

10.2 

9 

12.3 

0.091 

2 

9 

26.4 

7 

17.9 

16 

21.9 

0.243 

3 

6 

17.6 

10 

25.6 

16 

21.9 

0.524 

4 

5 

14.7 

7 

17.9 

12 

16.4 

0.333 

5 

5 

14.6 

9 

23.0 

14 

19.1 

0.275 

6 

3 

8.8 

2 

5.1 

5 

6.8 

0.908 

=5 

8 

23.5 

11 

28.2 

19 

26.0 

0.275 

MDDS-C 
(±SD) 

3.56 ±1.249 

 

3.98 ±1.043 

 

3.77 ±1.046 

0.102 



NB: Dietary diversity Scores (DDS) and Percentage of Non-Breast Fed Children 
Ages 6-23 months under each Score. * Statistical significance p<0.05 

 


4.2.3 Minimum Dietary Diversity of children (MDD) among pastoral and agro-
pastoral communities 

The study showed that on overall, the minimum dietary diversity score of breastfed 
children aged 6-23 months was 30.8%, with a higher MDD among agro-pastoral 
children at 32.0% compared to pastoral children that recorded 29.5%. There was no 
significant difference in the minimum dietary diversity between pastoral and agro-
pastoral children aged 6-23 months, (p=0.479). 

Overall, about a quarter (26.0%) of non-breastfed children 6-23 months from both 
pastoralist and agro-pastoralist communities had received foods from =5 out of 8 food 
groups. A higher proportion (28.2%) of non-breastfed children 6-23 months from 
agro-pastoralist children had consumed foods from =5 out of 8 food groups compared 
to pastoral children at 23.5%, (p=0.432). 

Only a quarter (29.2%) of children both breastfed and non-breastfed 6-23 months 
across the two livelihood had received food from =5 out of 8 food groups, with a 
higher proportion (30.7%) among agro-pastoral children 6-23 months compared to 
pastoral children at 27.6%, (p=0.422) as shown in Table 4.7. 

 

 

 

 

 


Table 4. 7 Minimum Dietary Diversity of Children (MDD) by Age in the 
previous 24 hours 

Minimum dietary 
diversity: 

Pastoralist 
(N=71) 

Agro-pastoralist 
(N=75) 

Total 
(N=146) 

P-
Value 

n 

% 

N 

% 

N 

% 

Breastfed Children 
6-23 months who 
received foods 
from =5 out of 8 
groups 

21 

29.5 

24 

32.0 

45 

30.8 

0.479 

Minimum dietary 
diversity: 

Pastoralist 
(N=34) 

Agro-pastoralist 
(N=39) 

Total (N=73) 

P-
Value 

n 

% 

N 

% 

N 

% 

Non-Breastfed 
Children 6-23 
months who 
received foods 
from =5 out of 8 
groups 

8 

23.5 

11 

28.2 

19 

26.0 

0.432 

Minimum dietary 
diversity: 

Pastoralist 
(N=105) 

Agro-pastoralist 
(N=114) 

Total 
(N=219) 

P-
Value 

n 

% 

N 

% 

N 

% 

Breastfed and 
Non-Breastfed 
Children 6-23 
months who 
received foods 
from =5 out of 8 
groups 

29 

27.6 

35 

30.7 

64 

29.2 

0.422 



** Statistical significance p<0.05 

4.2.4 Minimum Meal Frequency of Children MMF-C (6-23 months) 

On overall, about 48.7 percent of breastfeeding children aged 6-8.9 months from the 
two communities had met a minimum meal frequency of 4 meals a day, which is 
similar across the two livelihood zones with agro-pastoral children at 55.0 % 
compared to pastoral children that recorded 42.1%. There was no significant 
difference in the minimum meal frequency of breastfed children aged 6-8.9 months 
between agro-pastoral and pastoral communities, p=0.107. The study also established 
that only 8.2% of all non-breastfed children across the two livelihood zones had met a 


minimum meal frequency of 4 meals a day with agro-pastoral children recording at 
10.2% compared to pastoral children 5.9% with no significant difference, p=0.756 as 
shown in Table 4.8; 

Table 4. 8 Minimum Meal Frequency MMF of children (6-23 months) in the 
previous 24 hours 

Age of children Breastfed 
(months). 

N1= Pastoralist (71) 

N2=Agro-pastoralist (75) 

Pastoralist 

Agro-
pastoralist 

Total 
(N1+N2) 

P-
Value 

N 

% 

n 

% 

N 

% 

Children 6-8.9 who ate =2 
times /day 

N1=38; N2=40 

 

16 

42.1 

22 

55.0 

38 

48.7 

0.107 

Children 9-23 months old 
who ate =3 times /day 

N1=33; N2=35 

 

16 

48.4 

14 

40.0 

30 

44.1 

0.458 

Age of Non-Breastfed 
Children (months). 

N1= Pastoralist (34) 

N2=Agro-pastoralist (39) 

 

Pastoralist 

Agro-
pastoralist 

Total 
(N=73) 

P-
Value 

N 

% 

n 

% 

N 

% 

Children 6-23 old who ate 
=4 times /day 

2 

5.9 

4 

10.2 

6 

8.2 

0.756 



* Statistical significance p<0.05 

4.2.5 Minimum Acceptable Diet 

Almost a third (29.4%) of breastfed children both from pastoral and agro-pastoral 
community had met required Minimum Acceptable Diet, with higher proportion 


(30.6%) among agro-pastoral children compared to pastoral (28.1%), at p=0.398 as 
shown in Table 4.9 

Table 4. 9 Minimum Acceptable Diet (MAD) of children 6-23 in the previous 24 
hours 

Age of Breastfed 
Children (months) 

N1= Pastoralist (71) 

N2=Agro-pastoralist (75) 

Pastoralist 

Agro-
pastoralist 

Total 
(N1+N2) 

P-
value 

(n) 

(%) 

(n) 

(%) 

(n) 

(%) 

Children (6-11 Months) 

N1=46; N2=51 

 

11 

23.9 

13 

25.5 

24 

24.7 

0.682 

Children (12-17 Months) 

N1=17; N2=19 

 

7 

41.1 

9 

47.3 

16 

44.4 

0.544 

Children(18-23 Months) 

N1=8; N2=5 

 

2 

25.0 

1 

20.0 

3 

23.0 

0.223 

Children (6-23 months) 

N1=71; N2=75 

 

20 

28.1 

23 

30.6 

43 

29.4 

0.398 

Age of Non-Breastfed 
Children (months) 

N1=34; N2=39 

Pastoralist 

Agro-
pastoralist 

Total 

P-
value 

n 

% 

n 

% 

N 

% 

6-23 Months 

2 

5.8 

5 

12.8 

7 

9.4 

0.082 



* Statistical significance p<0.05 

 

4.3 Nutrient adequacy among children aged 6-23 months 

The mean intakes of nutrients per day were comparable across the community. The 
study established a higher mean intake of energy per day among agro-pastoralist 
children 954.20 (±545.43) Kcal/day compared to pastoral children 885.31 (±382.31) 
Kcal/day. However, no statistical difference was observed as the P-value between the 
two means was; p=0.278. 


The study established a higher fiber intake among the agro-pastoralist households 
with a mean intake of 73.83 (±44.32) g/day compared to the pastoral household 59.05 
(±34.34) g/day, with p=0.025. The intake of Vitamin A was generally low across the 
community. However, the study established a high mean intake of vitamin A among 
children from agro-pastoral households 158.27 (±147.66) µgRE/day compared to 
pastoral households with a mean intake of 126.22 (±114.43) µgRE/day, though the 
difference was not statistically different p=0.073. The study further established a 
statistically higher Riboflavin intake among agro-pastoral household with a mean 
intake of 1.12 (±0.73) mg/day compared to pastoral households 0.68 (±0.43) mg/day, 
with a p=0.001. The results further showed a higher intake of Vitamin C among agro-
pastoral children with a mean intake of 21.01 (18.69) mg/day compared to pastoral 
children with a mean intake of 12.84 (9.01) mg/day, with a p=0.021. Calcium intake 
per day across the community was very low with agro-pastoral households. mean 
intake of 21.01 (18.69) mg/day compared to pastoral households at 12.56 (±8.64) 
mg/day, with p=0.416. The study also established a significantly higher intake of 
folate among the agro-pastoral household with a mean intake of 73.83 (±44.32) 
mg/day compared to pastoral household 59.05 (±34.34) mg/day, with a p=0.006, 
(Table 4.10). 

 

 

 

 

 

 


Table 4. 10 Mean intakes of macro-nutrients per day across the two livelihood 
zones in the previous 24 hours 

Age group months 
N1=Pastoral (105) 

N2 = Agro-pastoral 
(114) 

Nutrients 

RDA 

Mean Intake (SD) 

P-
Value 

Breastfed 

Pastoral 

Agro-
pastoral 

6-8.9 (N1=14, 
N2=17) 

Energy 
(Kcal/day) 

320 

278.87 
±(124.12) 

315.32 
±(150.61) 

0.228 

Carbohydrates 
(g/day) 

40 

27.49 
±(14.91) 

35.18 
±(18.99) 

0.034* 

Protein 
(g/day) 

10 

11.82 
±(6.11) 

10.32 ±(5.47) 

0.653 

9-11.9 (N1=24, 
N2=18) 

Energy 
(Kcal/day) 

330 

250.92 
±(40.78) 

285.58 
±(44.03) 

0.346 

Carbohydrates 
(g/day) 

41.3 

40.09 
±(12.51) 

48.52 
±(22.69) 

0.182 

Protein 
(g/day) 

12 

11.60 
±(7.82) 

12.99 ±(6.05) 

0.735 

12-23 (N1=33, 
N2=40) 

Energy 
(Kcal/day) 

550 

443.21 
±(226.10) 

510.15 
±(244.03) 

0.050* 

Carbohydrates 
(g/day) 

68.8 

45.41 
±(34.62) 

65.51 
±(33.46) 

0.046* 

Protein 
(g/day) 

12.4 

11.71 
±(3.17) 

11.45 ±(3.54) 

0.886 

Non-Breastfed 

Pastoral 

Agro-
pastoral 

P-
value 

12-23 (N1=34, 
N2=73) 

Energy 
(Kcal/day) 

894 

748.78 
±(338) 

847.51 
±(378.24) 

0.039*
* 

Carbohydrates 
(g/day) 

112 

82.54 
±(30.88) 

105.78 
±(32.84) 

0.028* 

Protein 
(g/day) 

16 

13.11 
±(8.34) 

15.33 ±(7.13) 

0.634 



NB: Recommended Dietary Allowance (RDA) (FAO/WHO/UNU, 2004; IOM, 2005). 
*Statistical significance p<0.05. 


4.3.1 Micronutrient Intakes among children 6-23 months at various percentages 
of RNI across the two livelihood zones 

For micronutrient, the study established a high intake of Vitamin C and Riboflavin 
(B2) among agro-pastoral children compared to pastoral children. Over (89.5%) of 
agro-pastoral children met Recommended Dietary Allowance (0.5mg/day) of 
Riboflavin for FAO/WHO for young children compared to only (61.0%) of pastoral 
children, with a p=0.001. The study further established a higher number of pastoral 
children 15.2% meeting between 60-79.9% RDA for Riboflavin compared to pastoral 
children 3.5%, with p=0.003. 

 For Vitamin C, the study showed a significantly higher number of agro-pastoral 
children (42.0 %) who meet RDA (15mg/day) for FAO/WHO for young children 
compared to (27.6%) of pastoral children, with p=0.027. The intake of vitamin A was 
very low across the community with only (2.9%) of pastoral children and (7.0%) of 
agro-pastoral children meeting RDA (400µgRE/d) for FAO/WHO for young children 
in developing countries, with p=0.159. Folate intake was also low in both pastoral and 
agro-pastoral with only (2.9%) and (7.0%) meeting the Estimated Average 
Requirement (EAR) of (150mg/day) for FAO/WHO for young children, with 
p=0.159. For mineral, there was a general low intake of mineral across the 
community. Iron intake was low across the community but the study established a 
significantly higher intake among agro-pastoral 7.0% compared to pastoral 1.0% 
meeting the RDA (11.6mg/day) of iron for FAO/WHO for young children, p=0.024. 
The study further established a higher intake of zinc among agro-pastoral households 
with 5.3% of children compared to pastoral household 0.0% of children meeting the 
RDA (8.3mg/day) for FAO/WHO for young children, with p=0.017. The result 


established a low calcium intake across the community. There was no child across the 
community who met RDA (700mg/day) of calcium for FAO/WHO for young 
children. The study further established all the children across the community had 
calcium intake of less than 50% of RDA 700mg/day) of calcium for FAO/WHO for 
young children as shown on Table 4.12. 

Table 4. 11 Micronutrient Intake of children 

NUTRIENTS 

RNI 

%RNI 

Pastoral 
(N=105) 

Agro-
pastoral 
(N=114) 

Total 
(N=219) 

Chi-
square 
(p-value) 

N 

% 

n 

% 

N 

% 

Vitamin A 

 

 

400 

=100 

3 

2.9 

8 

7.0 

11 

5.0 

0.159 

80-99.9 

3 

2.9 

6 

5.3 

9 

4.1 

0.370 

60-79.9 

10 

9.5 

11 

9.6 

21 

9.6 

0.975 

Riboflavin 
(mg/d) 

 

0.5 

 

=100 

64 

61.0 

102 

89.5 

166 

75.8 

0.001*** 

80-99.9 

11 

10.5 

7 

6.1 

18 

8.2 

0.243 

60-79.9 

16 

15.2 

4 

3.5 

20 

9.1 

0.003** 

Vitamin C 
(mg/d) 

 

 

30 

=100 

29 

27.6 

47 

42.0 

76 

34.7 

0.027* 

80-99.9 

12 

11.4 

8 

7.1 

20 

9.1 

0.275 

60-79.9 

12 

11.4 

15 

13.4 

27 

12.3 

0.661 

Folate (mg/d) 

 

 

150 

=100 

3 

2.9 

8 

7.0 

11 

5.0 

0.159 

80-99.9 

3 

2.9 

7 

6.1 

10 

4.6 

0.245 

60-79.9 

9 

8.6 

15 

13.2 

24 

11.0 

0.278 

Iron (mg/d) 

 

 

10.0 

=100 

1 

1.0 

8 

7.0 

9 

4.1 

0.024** 

80-99.9 

5 

4.8 

10 

8.8 

15 

6.9 

0.193 

60-79.9 

9 

8.6 

17 

14.9 

26 

11.9 

0.147 

Zinc (mg/d) 

 

 

4.1 

=100 

0 

0.0 

6 

5.3 

6 

2.7 

0.017** 

80-99.9 

3 

2.9 

6 

5.3 

9 

4.1 

0.370 

60-79.9 

15 

14.3 

14 

12.3 

29 

13.2 

0.662 

Calcium 
(mg/d) 

 

 

700 

= 100 

0 

0.0 

0 

0.0 

0 

0 

.a 

80-99.9 

0 

0.0 

0 

0.0 

0 

0 

.a 

60-79.9 

0 

0.0 

0 

0.0 

0 

0 

.a 



NB: Nutrient adequacy is the amount of nutrient taken in by a child which is more 
than Recommended Nutrient Intake. RNI sourced from FAO-WHO (2004). *Statistical 
significance p<0.05. 

 


4.3.2 Nutrient Adequacy Ratio (NAR) and Mean Adequacy Ratio of pastoralist 
and agro-pastoralist children 

The population of children across the community with nutrients intake below the 
Recommended Dietary Allowance varied from nutrient to nutrient. Each of the 11 
NARs in Table 4.12 was truncated at 1, so that a nutrient with a high NAR could not 
compensate for another nutrient with a low NAR. 

The study compared Nutrient Adequacy Ratio (NAR) across the community. None of 
the children across the community had a sufficient intake of essential nutrients. The 
study established a low Nutrient Adequacy Ratio of energy among pastoral children 
with 18% of pastoral children having inadequate intake of energy compared to 15% of 
agro-pastoral children, with p=0.067 as shown in Table 4.12 

Table 4. 12 Nutrient Adequacy Ratio (NAR) of pastoralist and Agro-pastoral 

Nutrients 

Pastoralist 

Agro-pastoralist 

t-test (P-
value) 

Mean of NAR (±SD) 

Mean of NAR (±SD) 

Energy 

0.8236 (±0.2256) 

0.8456 (±0.2038) 

0.067 

Carbohydrates 

0.8394 (±0.2378) 

0.8684 (±0.1968) 

0.326 

Protein 

0.8669 (±0.1974) 

0.8762 (±0.2034) 

0.733 

Vitamin A 

0.3044 (±0.2477) 

0.3707 (±0.3016) 

0.014* 

Riboflavin 

0.8662 (±0.2176) 

0.9782 (±0.0798) 

0.001*** 

Vitamin C 

0.5897 (±0.3532) 

0.6881 (±0.3489) 

0.039* 

Calcium 

0.0179 (±0.0123) 

0.0198 (±0.0207) 

0.080 

Folate 

0.3890 (±0.2143) 

0.4746 (±0.2501) 

0.032* 

Iron 

0.4151 (±0.1939) 

0.4507 (±0.2838) 

0.001*** 

Zinc 

0.4200 (±0.1956) 

0.4372 (±0.2378) 

0.002** 

Fiber 

0.6198 (±0.2570) 

0.6261 (±0.3313) 

0.875 

MAR 

0.5593 (±0.1472) 

0.6032 (±0.1670) 

0.042** 



NB: Nutrient adequacy ratio (NAR), and mean adequacy ratio (MAR) of children 
aged 6-23 months in the previous 24 hours. *Statistical significance p<0.05. 


The study further showed a low Nutrient Adequacy Ratio of Vitamin A across the 
community. Nutrient Adequacy Ratio of Vitamin A was significantly higher among 
agro-pastoral children 37.07% compared to pastoral children 30.44%, with p=0.014. 
The study showed a good Nutrient Adequacy Ratio of Riboflavin across the 
community. Agro-pastoral household had a higher Mean Nutrient Adequacy Ratio of 
Riboflavin 97.82 (±7.98) compared to pastoral household 86.62 (21.76), with p=0.001 

4.4 Relationship between variables 

4.4.1 Relationship between dietary diversity and Nutrient Adequacy 

A Pearson product-moment correlation coefficient was computed to assess the 
relationship between dietary diversity and nutrient adequacy. The study established a 
positive correlation between the consumption of energy, Carbohydrates, Proteins, 
Vitamins A, Riboflavin, Vitamin C and other nutrients with Individual Dietary 
Diversity Score for Children; with p== 0.001, (Table 4.13). 

Table 4. 13 Relationship between dietary diversity and Nutrient Adequacy 

Variable 

Nutrients 

r 

Correlation Coefficient 
(Value) 

 

 

 

 

Dietary Diversity (IDDS) 

Energy 

0.345 

= 0.001*** 

Carbohydrates 

0.271 

= 0.001*** 

Proteins 

0.454 

= 0.001*** 

Vitamin A 

0.293 

= 0.001*** 

Riboflavin 

0.295 

= 0.001*** 

Vitamin C 

0.483 

= 0.001*** 

Calcium 

0.199 

0.003*** 

Iron 

0.302 

= 0.001*** 

Zinc 

0.387 

= 0.001*** 

Folate 

0.537 

= 0.001*** 

Fiber 

0.357 

= 0.001*** 



* Statistical significance p<0.05. 


4.4.2 Relationship between dietary diversity of children aged 6-23 months and 
demographic and socio-economic characteristics of the households 

The study established a significant association between the maternal level of 
education and the dietary diversity (.2=41.06, p= 0.016) of the children in both zones. 
The results imply that as the level of education increased the dietary diversity 
increased. When Chi-square test was performed on the marital status of household 
and the dietary diversity, the study established no significant relationship between 
marital status and dietary diversity (.2=10.65, p=0.0909) of the children in both zones. 
Pearson.s correlation coefficient revealed insignificant negative relationship (r=-
0.078, p=0.253) between dietary diversity and maternal age. The study further showed 
significant positive relationship (r=-0.019, p=0.042) between dietary diversity and 
household size as shown in Table 4.14. 

Table 4. 14 Relationship between dietary diversity and maternal demographic 
and socio-economic characteristics 

Dietary 
Diversity 

 Variables 

Statistics 

P-Value 

 

Mother Education Level 

(.2)=41.06 

0.016** 

Household head Education 

(.2)=40.80 

0.018** 

Sex of Household Head 

(.2)=3.95 

0.683 

Marital Status 

(.2)=10.65 

0.909 

Maternal Age 

r=-0.078 

0.253 

Age of household head 

r=0.061 

0.366 

Household Size 

r=-0.019 

0.042* 

 

Occupation 

(.2)= 3.65 

0.739 

 

Livelihood (Pastoral/Agro-pastoral) 

(.2)=0.001 

0.969 



* Statistical significance p<0.05. 

 

 

 


CHAPTER FIVE:DISCUSION 

5.0 Introduction 

This was a cross-sectional analytical study which aimed to determine dietary 
diversity and nutrient adequacy of children aged 6-23 months among pastoral and 
agro- pastoral community in Turkana County. This chapter discusses the finding of 
this study in relation to the study objectives as well as how the results compare with 
other research findings . 

5.1 Demographic and Socio-Economic Characteristics of the participants. 

5.1.1 Marital Status 

Majority (95.0%) of the participants across the two livelihood zones were married. 
The result concurs to the findings of a study conducted by Pauline (2015) that found 
that the rationale of high rate of marriage among the Turkana community is anchored 
on economic and social value. The study also found a significantly higher 
polygamous marriage among pastoralist compared to agro-pastoralist communities. 
This result is similar to report by Johannes (2010), which reported high rates of 
polygamous marriage among pastoral communities of Turkana. This is attributed to 
the fact that according to Turkana women, a wife generally considers a polygamy as 
an economic advantage for her family to have a co-wife since the women help each 
other in doing domestic chore and caring for their animals (Johannes 2010; Baker, 
Gilley, James, & Kimani, 2012). 

There were many widow households among agro-pastoralist, compared to pastoral 
because pastorals are practiced wife inheritance culture thus high polygamous 
households. This result is in agreement with the finding of a study conducted by 


Harari (2019), which found that wives among the Turkana pastoralist communities 
are often inherited by a brother or the son of a co-wife upon the death of a husband. 

5.1.2 Gender of the Household Head 

Majority of the households in the study area were male-headed across the two 
livelihood zones. The few households headed by females were either located in towns 
or their male partners had died, mostly through cattle-related raids. 

In this study, only 20.1 % of the households were female-headed compared to 79.9% 
households which were male-headed. This result is consistent with the result of a 
study conducted by Omolo, (2010), that found that only 11% of the households were 
female-headed compared to 89% households which were male-headed in Turkana. 
Female-headed households were found to be more food secures than male-headed 
which was largely attributed to the fact that females pay more attention to food 
procurement than men (Barrett, 2010). The results therefore imply the majority of the 
households across the study area are highly vulnerable to food insecurity. 

5.1.3 Household Size 

The average household size across pastoralist and agro-pastoralist communities in 
Turkana County was 7.0, about 2.6 higher than the national household size of 4.4 
(KDHS, 2019). 

This result was consistent with the report from Kenya Population and Housing Census 
(KPHC, 2019) which found that poor counties Mandera, Wajir and Turkana have the 
highest household sizes averaging 6.9, 6.1 and 5.6, respectively. Larger household 
size among pastoral households is because many families were polygamous. Bigger 
households among pastoral are viewed as advantageous because they have more 


labour to take care of the livestock. A study conducted on factors influencing 
household food security in Nigeria by Amaza et al., (2006) using logistic regression 
methodology revealed that food insecurity increases with the increase in the number 
of family members. This study therefore established that, most vulnerable household 
to food insecurity and thus low dietary diversity score for children were pastoral 
communities because they have a bigger household size with little economic 
advantage. 

5.1.4 Age of the Household Head 

Over a half (54.3%) of the household heads were aged between 30 and 39 years. The 
study presented a relatively young population with the majority of the study 
participants aged 40 years and below. This youthful population in the study was 
evident because majority of Turkana residents marry at a tender age and is expected 
to have children. This report is consistent with the report from Ministry of Devolution 
and Planning (2015) on National Policy for the Sustainable Development of Northern 
Kenya and other Arid Lands, which indicated that Turkana population structure has a 
comparatively large youthful age group. Youthful age is very productive age group in 
the society which can diversify on other livelihood activities to supplement family 
income. According to Keding, Schneider & Jordan (2013), household with diversified 
livelihoods are more food secure than those depending on the livestock keeping. 
However, pastoral communities are only specialized on livestock rearing hence more 
food insecure compared to agro-pastoral households who have diversified livelihood. 
The mean age of the household heads across the two livelihood zones is 32.75 year. 
The average age of the household heads favors agro-pastoral households with 


diversified livelihood, leading relatively higher dietary diversity score among agro-
pastoral children. 

5.1.5 Educational Level of the participants 

In Turkana, only (37.9%) of both pastoralist and agro-pastoralist had formal 
education. This result is consistent with the report from Kenya Population and 
Housing Census (KPHC, 2019), which found that as many as 68% of Turkana County 
residents have no formal education. The main reason cited for this limitation in 
education is that children have to walk very long distances to school since education 
centers are not only few but also far apart. Other reasons why parents do not commit 
their children to school is lack of interest and fear from hostile neighborhood who 
target helpless school children for revenge mission. 

Daily Nation Report of 25/11/2013 showed that Arid and semi-arid counties; Wajir, 
Garissa, Mandera, Marsabit, Samburu and Tana River, in that order after Turkana 
have the least educated people, with an average of 70 in every 100 people having no 
education. Some parents rooted in cultural practices prefer their children attending 
Alternative Basic Education, focusing mainly on Turkana social and cultural way of 
life. Immediate efforts by authorities, including the county government, to increase 
the number of both primary and secondary schools have not been easy due to limited 
funds allocation, recurrent conflicts, poor infrastructure and recurrent natural 
calamities like drought and flood. In relation to food security, participants across the 
livelihood zones confirmed that those households with members who have attained 
formal education have diversified their livelihoods given that they can easily secure 
formal employment even in the county government and other agencies working in 
Turkana to earn income which increases their purchasing power to buy different food 


staffs. With formal education, household heads are capable of making informed food 
choices to enrich household diet, hence improved dietary diversity and nutrient 
adequacy for children. Keding, Schneider, & Jordan (2013), found that people with 
formal education can easily adopt innovations and new technologies, and hence 
substantially improve their production capacity more than their contemporaries with 
no education who largely depend on their traditional way of production. 

5.2 Dietary Diversity Score of Children age 6-23 months among pastoralist and 
agro-pastoralist community 

According to World Health Organization WHO (2016), children aged 6-23 months 
both breastfed and non-breastfed should receive 5 or more food groups. Dietary 
diversity, which is the consumption of an adequate variety of food groups, is a critical 
aspect of dietary quality and can be considered as an indicator of general nutritional 
adequacy among young children (Nontobeko et al., 2008). The dietary diversity score 
was established based on the different number of food groups the index child 
consumed in the previous 24 hours prior to the data collection. Eight food groups as 
recommended globally by WHO (2016) were considered in the study. The value of a 
diverse diet has over time been recognized and is highly recommended since it is 
strongly and positively associated with nutrient adequacy (Jayawardena et al., 2013; 
Kadiyala & Rathnayak et al., 2012). Majority of breastfed children in this study had a 
mean individual dietary diversity score of 3.99 (SD 1.15), whereas non breastfed 
children had a mean individual dietary diversity score of 3.77 (SD 1.05). This result 
was consistent with a report released by Turkana County Smart Nutrition Surveys 
Final Report (2018), which showed that the mean dietary diversity score of children 
in Turkana was 3.07 (SD 1.1) food groups, which is below the recommended 
threshold of at least 5 food groups. About seventy-one percent (71.5%) of children, 


more than two thirds of the children had low dietary diversity score. Fruits, vegetables 
and eggs were the least consumed food groups. 

Similarly, Walingo, & Ekesa, (2013) in a study on role of agricultural biodiversity on 
dietary intake and nutrition status of pre-school children in Matungu division western 
Kenya reported that majority of children in the region were consuming inadequate 
and monotonous diets mainly from two food groups which were carbohydrates and 
few sources of proteins. Another observation has also been reported in Malawi in a 
study that showed that 44.1% of children had low dietary diversity of (=3) food 
groups which were cereals and vegetables. In the same study in Malawi it was 
reported that high dietary diversity score consisted of foods from the following 
groups; cereals, vegetables, fruits and tubers (Mtimuni et al., 2010). 

In another study conducted on dietary diversity as a good predictor of the 
micronutrient density of diet among children aged 6 to 23 months in Madagascar by 
Mourald et al., (2008) reported that grains, roots, and tubers were the main food 
source, which is consistent with the result of this study that showed an average 
consumption of grains, roots, and tubers at 90.9% across the two livelihood zones. 
The result further showed that only (41.1%) of breastfed children aged 6 to 23 months 
in both pastoralist and agro-pastoralist had met minimum standards with respect to 
food diversity (had managed to consume a minimum of 5 food groups) in the previous 
24 hours preceding the study. In conclusion, majority of children across Turkana 
region were not receiving adequate and essential nutrients hence vulnerable to risk of 
micronutrient deficiencies. 

Several studies have indicated that higher dietary diversity score is associated with 
increased nutrient intake among children (Knueppel, Demment, & Kaiser, 2010; 


Fanzo et al 2013; Niven et al 2014; Keding et al., 2012). According to the reports of 
KDHS (2019), providing variety of foods from different food groups seems to be 
more of a problem in young children. The report further highlighted that increasing 
diversity of foods given to children therefore would help meet the IYCF targets. 

5.2.1 Minimum Dietary Diversity of children aged 6 to 23 months in Turkana 

Minimum dietary diversity is considered to be consumption of foods from =5 food 
groups out of 8 food groups (Knueppel, Demment, & Kaiser, 2010). The dietary 
diversity indicator is based on the on the premise that the more diverse the diets are 
the more likely they are to provide adequate levels of a range of nutrients. Higher 
scores correspond to a more adequate range of food groups in the diet. 

The minimum dietary diversity was analyzed for children 6 to 23 months of age. The 
findings showed that only 32.9% of children 6 to 23 months of age having received 
food from at least 4 food groups. The findings of this study is consistent with the 
reports from Maternal Infant And Young Child Nutrition (MIYCN) Knowledge, 
Attitudes, Beliefs And Practices (KABP) Survey Report Turkana County (November, 
2017), that found that an average of 29.1% of children in Turkana not having eaten 
any such foods. These findings implied that for majority of the children, the meals did 
not have an adequate range of food groups and were thus likely to be limited in the 
diversity of nutrients received. It is recommended that complementary foods be 
introduced at 6 months as breast milk is not adequate to provide all the necessary 
nutrients in the required quantities from this age onwards. 


5.2.2 Minimum Meal Frequency of Turkana Children aged 6 to 23 months 

The minimum meal frequency indicators are based on the breastfeeding status of the 
children. The minimum meal frequency indicator is 2 times per day inclusive of 
snacks for the breastfed children 6 to 11.9 months of age. The study showed that the 
proportion of breastfed children 6 to 11.9 months of age who ate =2 meals was 
26.0%. This finding is consistent with the report from Turkana County Smart 
Nutrition Surveys Final Report (2018) that found that Minimum Meal frequency of 
children 6 to 11.9 months in Turkana Central (Loima) was 22.3%. The indicator for 
the minimum meal frequency for breastfed children 12-23 months of age is 3 times 
per day inclusive of snacks. The study showed that only 20.5% of children aged 12 to 
23 months attained the recommended minimum meal frequency. This finding was 
also consistent with the reports from Turkana County Smart Nutrition Surveys Final 
Report (2018) that found that minimum meal frequency of children 12 to 23 months 
in Turkana Central was 16.0%. In conclusion, these findings suggest that many 
children were not getting appropriate quantity of nutrients for adequate growth and 
healthy development hence high micronutrient deficiencies. 

The indicator for the minimum meal frequency for non-breastfed children 6-23 
months of age is 4 times per day inclusive of snacks. This study finding showed that 
only 5.4% of the surveyed non-breastfed children age 6 to 23 had attained WHO 
recommendations on minimum meal frequency. The result of this study concur with 
the reports from World Vision Kenya, Assessment of Infant and Young Child Feeding 
Practices in Turkana District, Kenya; (2006) and MOH/UNICEF, Qualitative 
Assessment of the Infant and Young Child Feeding Practices in UNICEF-Kenya 
Focus Districts, (2007) that found minimum meal frequency for non-breastfed 


children 6-23 months at 4.8% and 4.1% respectively. The frequency of feeding was 
below the WHO recommendations. 

5.3 Energy and Macro-Nutrient Intake of children 

The mean energy intake in the two zones both for breastfed children aged 6-8.9 
months, 9-11.9 months, 12-23 months and non-breastfed children 6-23 months was 
below the WHO/FAO RNI recommendation (FANTA, 2014). This result is consistent 
with the report from a previous review which associated low energy intake with high 
rates of under nutrition in 40 sub-Saharan African countries (Abrahams et al., 2011). 
However, it could be possible that energy intake was underreported during the study. 
Several surveys have illustrated that observational studies experience limitations 
related to underreporting of energy intake as well as recall bias like underestimation 
of portion sizes (Jomaa, Naja, Cheaib, & Hwalla, 2017; Auestad et al., 2015; FAO, 
2010; Arimond et al., 2010). Vir (2016) found that low energy intake among children 
from arid and semi-arid regions of South Asia, which is not only linked to inadequate 
dietary consumption but also inadequate education among caregivers and household 
heads which hinder them from making appropriate food choices in relation to 
household expenditure. Additionally, energy intake coupled with micronutrient 
deficiencies not only leads to stunted growth and reduced cognitive performance but 
also poses high economic costs (up to 11% of gross domestic product) to affected 
countries; in particular, sub-Sahara and South Asia (Ochieng et al., 2017). 

The study also showed a low intake of carbohydrates and protein across the two 
zones, which was below the WHO/FAO RNIs. Similar findings were reported in the 
National Micronutrient survey (Ministry of Health, 2011). Evidence from sub-
Saharan Africa shows that majority of children have intakes below their daily 


requirements for energy, protein and micronutrients which is linked to low dietary 
diversity (Jones et al., 2014; Sibhatu et al., 2015). Liu et al., (2014), found that 
children 6-23 months living in rural set-up have intakes below RNIs in terms of 
energy, protein and micronutrients compared to children living in urban areas; which 
are attributed to higher dietary diversity among urban children 6-23 months despite 
the economic status of the household. 

5.4 Micronutrient Intake among children 6-23 months 

Micronutrient deficiencies are a major contributor to childhood morbidity and 
mortality. Micronutrient deficiencies result from inadequate intake of micronutrient-
rich foods and inadequate utilization of available micronutrients because of infections, 
parasitic infestations, or other factors in diet such as phytates and tannnins. Overall, 
dietary vitamin A intake among children 6-23 months was low across the two zones 
with only (18.7%) of the study population, meeting =60% of RNI (400µgRE/d). 
Similar findings were reported from a study conducted by a Persson et al., (1998) 
which showed that only 40% of children 6-23 months in Bangladesh met 60% of this 
RDI, using RDI of 250 RE of vitamin A for children aged 6-23 months. Barrett 
(2010), found that young children in industrialized countries receive most of their 
vitamin A rich food from animal sources, whereas poor children in developing 
countries consume most of their vitamin A from the less expensive plant sources. The 
study reported low consumption of dark-green leafy vegetables and deep-yellow fruits 
and vegetables among children in Turkana country due to drought hence Vitamin A 
deficiency among children. 

Majority 93.1% of the children 6-23 months across the two livelihood zones had 
consumed =60% of RNI (0.5mg/day) of Riboflavin in the previous 24 hours prior to 


the data collection. The findings are consistent with the report of Save the Children 
(2013) that revealed high intake of Riboflavin, with the majority (95.2%) of children 
meeting =60% of RNI (0.5mg/day) of Riboflavin during dry season. High 
consumption of Riboflavin was recorded among children 6-23 months in this study 
since the survey was conducted during dry season. The study participants had little 
access to fruits and vegetable thus majority could be surviving on animal meat and 
meat organs from aged livestock. 

Overall, calcium mean intakes in this study did not meet estimated needs/RNI for 
breastfed and non-breastfed IYC across the two livelihood zones. The result is 
consistent with report of Baye et al., (2013) that revealed low calcium intake among 
young children (aged 12–23 months) from North Wollo, Northern Ethiopia. Despite 
the wide consumption of dairy products, calcium intake did not meet estimated needs 
for breastfed IYC. Such suboptimal intake of calcium is quite common both in 
Turkana and elsewhere (Wayua, 2017), but was a surprising finding for this 
community that heavily relied on milk. Low intake of milk was attributed to low 
consumption of milk which fluctuates with season. 

5.5 Mean Adequacy Ratio (MAR) of pastoralist and agro-pastoralist 

Overall, the MAR for pastoral children was 0.56 ± 0.15 while mean MAR for agro-
pastoral children was at 0.60 ± 0.17. The ideal cut-off for nutrient adequacy should be 
1, which would mean that all nutrients were covered. In this study, none of the 
children both in pastoral and agro-pastoral met this Cut-off. The study established that 
about 45% of children in pastoral zone had inadequate intake of essential nutrients 
compared to 40% of agro-pastoral children per day, with a p=0.042. 


5.6 Relationship between dietary diversity and maternal demographic and socio-
economic characteristics 

According to Walingo & Kidake (2013), socio-demographic characteristics including 
mothers. education level, household size, marital status, and access to agricultural 
land and livestock ownership influence dietary diversity of the child (Jones, Shrinivas, 
& Bezner-kerr, 2014). However, in this study, the main factors associated with dietary 
diversity of children among pastoralist and agro-pastoralist communities were 
established as maternal factors (education of mothers) and household characteristics 
like household size. These findings are consistent with the findings of a study carried 
out by Murakami et al., (2011) in Japan which established positive association 
between maternal education and favorable dietary intake among children. 

5.6.1 Dietary diversity and Marital Status 

The study results established that there was no significant relationship between 
marital status of the household and dietary diversity score of the children in the two 
zones (.2 =10.65, p=0.909). Although researches have shown that marital status 
influence consumption of diversity diets as reported by (Nuzhat, 2011 & Kimiywe et 
al., 2007), this study finding differed on that. The results of this study could be 
explained by the fact that majority of the participants were married (95.0%) with only 
a few single and widowed households (3.2% and 1.8%) respectively. This implied 
that nearly both of all parents were there to contribute to care of the child therefore 
undiversified diets among the children would have been attributed to other factors. 

5.6.2 Dietary diversity and Occupation/ Income 

This study also revealed that there was no significant relationship (.2 =6.35, p=0.739) 
between the occupation of the participants and dietary diversity score (DDS) of the 


children among the two zones. Knueppel, Demment, & Kaiser (2010), established that 
foods such as fruits, vegetables, pulses and eggs were consumed more frequently 
among the SES groups; however, this study finding were not in agreement with 
findings from that study. As noted earlier on these same study results, the participants 
from the two zones relied on small income activities with unstable income and this 
would explain why occupation would not have made any significant influence on the 
dietary diversity of the children. 

5.6.3 Dietary Diversity and Sex of the Household Head 

The study further noted similar insignificant (.2=3.95 p= 0.683) relationship between 
the sex of the household head and the dietary diversity of the child. This observation 
concurs with the findings and the results of Table 4.1 in this same study which 
showed that according to sex of the household head, majority of the households were 
male headed and thus dietary diversity among the children would have been 
contributed by other factors. Another study conducted by Mayanja et al (2015) on 
Diet diversity in pastoral and agro-pastoral households in Ugandan rangeland 
ecosystems further found that household diet diversity score varied significantly with 
gender and age but not with household size or sex of the household head. 

5.6.4 Dietary Diversity and Maternal Age 

When Pearson.s correlation coefficient was done, the study revealed insignificant 
negative relationship (r=-0.078, p=0.353) between maternal age and dietary diversity 
of the children. Agize, Jara, & Dejenu, (2017) established a significant negative 
relationship (r=-0.16728, p=0.01) between maternal age and dietary diversity of the 
child. This implies that maternal age influenced the dietary diversity of food 
consumed by the children. However, the results from this study deferred from Agize, 


Jara, & Dejenu, (2017) because; majority of the mothers in this study (95.9%) were 
aged 39 years and below which a productive age to generate income to the families 
thus the elderly population here were very few. Therefore, low dietary diversity score 
of children among the pastoralist and agro-pastoralist would have been attributed to 
other factors. 

5.6.5 Dietary diversity and Age of the household head 

Studies from other part of Africa (Oldewage-Theron and Kruger, 2008 and 
Labadarios et al., 2011) have reported that Child Dietary Diversity Score (CDDS) and 
Mean Dietary Diversity Score) MDD-S decreased with the increase in the age of the 
household head. However, these study findings have established insignificant positive 
relationship (r=0.061, p= 0.366) between the age of the household head and dietary 
diversity score of the children which did not concur with other studies findings. The 
observation concurs with the findings and results of Table 4.1 in these same study 
results which showed majority of the household head were aged 49 below, which is 
still a productive age and have the capacity to provide for their households. needs. 
Therefore, low dietary diversity score among the children would have been caused by 
other factors. 

5.6.6 Dietary diversity and Mother education level 

The study established significant relationship (.2=41.06, p=0.016) between mothers. 
educational level and dietary diversity of children. These study results concur with the 
findings from a study conducted by (Kimiywe et al., 2007) which reported that 
education influenced consumption of diversity of diets. Another study further showed 
that education is likely to have an impact on the household.s nutritional knowledge 
and skills to conceptualize and use nutritional promotional messages, which 


consequently contribute to better dietary diversity (Rajendran et al., 2017). A previous 
study in Morogoro in Tanzania reported that households who were provided with 
nutritional education improved the quality of their household diets (Pillai, Kinabo, & 
Krawinkel, 2016). 

5.6.7 Dietary diversity and Household head education Level 

Education determines the lifestyles and the position a person enjoys in the society. 
This study established a significant relationship (.2=40.80, p=0.018) between 
educational level of the household head and dietary diversity score of the children. 
The findings of this present study concur with the other studies that have shown that 
educational attainment has a strong effect on the dietary practices of an individual 
(Ali et al., 2014; Rani, Arends, & Brouwer, 2010). The findings of this study are also 
in agreement with other studies conducted by Tiyou et al., (2012), Walingo & Kidake 
(2013), which found out that more educated people tend to get better jobs with the 
county government of Turkana or engage in supply and tender deals that generate 
more income and hence tend to have access to diverse diet. The study is also in 
agreement with another study which revealed that a higher educational level is 
associated with better employment opportunities and higher incomes and may 
translate into higher purchasing power and better nutrition knowledge for all 
household members through improved dietary diversity (Kennedy et al., 2010). 

5.6.8 Dietary diversity and Household Size 

In this present study, household size had a significant negative relationship (r=-0.019, 
p=0.042) with the dietary diversity of the children. This implies that larger household 
size negatively influenced dietary diversity. The results could partly be explained by 
the fact that as the number of family members. increases, the intra-household food 


distribution is affected and food may become more limited, which in turn would limit 
access to different food groups. These results are also in agreement with a study 
regarding household size, which has shown that increasing household size means 
more mouths to feed, increased expenditure on food, and thus reduced levels of 
consumptions on quantity, quality and variety (Baker et al., 2012). Thus, smaller 
households are more likely to have more diverse food consumption compared to 
larger households. 

5.6.9 Relationship between dietary diversity and nutrient adequacy 

Dietary diversity is useful as an indicator of nutrient adequacy. It is therefore 
important to examine how various food groups consumed among pastoralist and agro-
pastoralist household contributed to nutrient adequacy of children aged 6-23 months. 
This study showed that dietary diversity positively associated with nutrient adequacy. 
The findings were similar to another study conducted Torheim et al, 2003. The 
correlation coefficient were further similar to that of a study among children in an 
urban area in Mali (Hoddinott & Yohannes, 2002) 

5.7 Hypothesis Testing 

The hypothesis one which stated that “There is no significant difference in dietary 
diversity of children aged 6-23 months between Pastoralist and Agro-pastoralist 
communities of Turkana County” was accepted because from the Chi-Square test, 
there was no significant different in the number of children who attained dietary 
diversity score of five (5) and above between pastoral and agro-pastoral, (p=0.916). 
Hypothesis number two was also rejected as there was significant difference in 
nutrient adequacy of children aged 6-23 months between pastoralist and agro-
pastoralist communities of Turkana County. This was explained by the facts that there 


was no significant difference in Mean Adequacy Ratio (MAR) of nutrients p= 0.042, 
between pastoral and agro-pastoral communities in Turkana County. 

The third hypothesis which stated that “There are no associations between dietary 
diversity and nutrient adequacy among pastoralists and agro-pastoralists communities 
of Turkana County” was rejected as a Pearson.s product-moment correlation 
coefficient computed established a positive correlation between the consumption of 
(Energy, Carbohydrates, Proteins, Vitamins A, Riboflavin, Vitamin C, Calcium, Iron, 
zinc, Folate and fibre) and Individual Dietary Diversity Score for Children, with p == 
0.001. The fourth hypothesis which stated that “there are no associations between 
dietary diversity and demographic and socio-economic characteristics among 
Pastoralists and Agro-pastoralists communities of Turkana County” was rejected as 
there were various socio-demographic factors which are established to have 
significant association with the dietary diversity of the children across the two 
livelihoods. Pearson.s correlation coefficient revealed significant positive relationship 
(r=-0.019, p=0.042) between dietary diversity and household size. 

 

 

 

 

 

 

 

 


CHAPTER SIX: SUMMARY, CONCLUSSIONS AND RECOMMENDATIONS 

6.0 Introduction 

This chapter presents the summary of main findings, conclusions, implications of 
findings and recommendations for policy, practice and further studies. 

6.1 Summary 

Majority of the households in both pastoral and agro-pastoral were married with male 
as the household head in line with Turkana cultural belief and practice. Polygamous 
marriages were significantly higher among pastoral communities compared to agro-
pastoral communities. In pastoral communities, widowed mothers were getting 
remarried to form polygamous family, which was a common cultural practice 
compared to agro-pastoral household. Larger household size was noted among 
pastoral communities compared to agro-pastoral communities since pastoral 
communities believed that many hands provide cheap and ready labour to take of care 
cattle. Slightly above half of the household heads were in the age category of 30-39 
years, while most mothers/caregivers in both pastoral and agro-pastoral communities 
were in the age categories of 20-29 years. 

Majority of the household heads had no formal education in both pastoral and agro-
pastoral communities. Majority of mother across the two zones had no formal 
education. Most of the study participants were unemployed with their main source of 
income as sale of own produced goods, while large livestock ownership simply 
remains a sign of wealth and prestige. About half of agro-pastoral community had 
access to agricultural land compared to pastoral communities who dwelled on dry and 
unfertile land. 


Most of the children aged 6-23 months across the two livelihood zones drew their 
energy from grains, white roots, tubers and plantains, with a comparatively higher 
intake among agro-pastoral households compared to pastoral households. The diets of 
children were low in nutrient dense foods such as dairy products, eggs, flesh floods, 
legumes and others fruits and vegetables. Despite low consumption of flesh food 
across the two zones, significantly higher intake of flesh was observed among pastoral 
children compared to agro-pastoral children. 

An overall Mean Adequacy Ratio (MAR) for pastoral children was 0.56 ± 0.15 while 
agro-pastoral children at 0.60 ± 0.17. Therefore, none of the children across the two 
livelihood zones received sufficient and adequate nutrients recommended for proper 
growth and development. Despite the perceived high consumption of milk and dairy 
products, which are rich sources of calcium, the overall calcium mean intakes in this 
study did not meet estimated needs/RNI for breastfed and non-breastfed IYC across 
the two livelihood zones. This is because the survey was conducted during dry season 
and the livestock were spending away from home thus no milking was taking place 
leading to low consumption of milk and milk products. 

About a third of children aged 6-23 months from pastoral and agro-pastoral 
communities had acceptable dietary diversity score of 5 and above with breast milk as 
food group, with a higher proportion of children among agro-pastoral compared to 
pastoral children. Mean dietary diversity score for breastfed children (6-23 months) 
was higher among agro-pastoral children compared to pastoral children in the 
previous 24 hours. Mean dietary diversity score for non-breastfed children was also 
higher among agro-pastoral children compared to pastoral children at in the previous 
24 hours. 


6.2 Conclusions 

The following conclusions were drawn from this study; 

Marital status had insignificant relationship with the dietary diversity score of 
children across the two livelihood zones. Other demographic and socio-economic 
characteristics with insignificant relationship with dietary diversity score of the 
children aged 6-23 months included occupation, age and sex of the household head 
and maternal age. 

Maternal education level established to have a significant relationship with dietary 
diversity of the child. Household head education level also established to have a 
significant relationship with dietary diversity score of the child since it determines the 
lifestyles and the purchasing power of person to feed the family. 

Household size was also found to have a significant negative relationship with the 
dietary diversity of the children. The larger the household size, the lower the dietary 
diversity score of the child. 

Generally, the study concluded that the dietary patterns of children age 6-23 months 
living in pastoral and agro-pastoral zones were comparable. This showed that energy 
and nutrient intake of children aged 6-23 months living in pastoral and agro-pastoral 
zones in Turkana County were inadequate. Formal education was low and the 
majority of the participants were unemployed. Consumption of animal products 
across the region is low making them vulnerable to high risks of micronutrient 
malnutrition. 

 

 


6.2.1 Conclusion on hypothesis 

H01: There is no significant difference in dietary diversity of children aged 6-23 
months between Pastoralist and Agro-pastoralist communities of Turkana County, 
was not rejected; 

H02: There is no significant difference in nutrient adequacy of children aged 6-23 
months between Pastoralist and Agro-pastoralist communities of Turkana County, 
was rejected; 

H03: There are no associations between dietary diversity and nutrient adequacy of 
children aged 6-23 months among Pastoralists and Agro-pastoralists communities of 
Turkana County, was rejected; 

H04: There are no associations between the dietary diversity of children aged 6-23 
months and demographic and socio-economic characteristics of households among 
Pastoralists and Agro-pastoralists communities of Turkana County, was rejected. 

6.3 Recommendation for Policy, Practice and Further Research 

The study recommendations for policy, practice and further research are given to the 
Government of Kenya, nongovernmental organization, the Ministry of health, 
Turkana County Government through the ministry of health and the community 
nutritionist. 

6.3.1 Recommendation for policy 

The study findings have demonstrated that factors such education and household size 
adversely affect dietary diversity and nutrient adequacy of children living in pastoral 
and agro-pastoral zones. 


i. The ministry of health should scale up nutrition education on dietary diversity 
of children aged 6-23 months among pastoral and agro-pastoral households in 
Loima, Turkana. 
ii. The health service providers especially the nutritionist and dieticians in 
collaboration with nongovernmental organizations and County Government of 
Turkana should educate residence on the importance of consuming a diet that 
is diverse in order to prevent risk of micronutrient deficiencies. 


6.3.2 Recommendation for practice 

i. Agro-pastoralism should be fully embraced in Loima Sub-County and other 
Arid and semi-arid regions as a food intervention strategy to enhance dietary 
diversity and nutrient adequacy of children. 
ii. The government of Kenya in collaboration with the county Government of 
Turkana and other non-governmental organization in the region should create 
awareness to caregivers on the need to increase intake of flesh foods, fruits 
and vegetables across the livelihood zones especially among pastoral groups 
for improved micronutrient intake 


6.3.3 Recommendation for Further Research 

i. This study was conducted during the dry harvest season. There was low 
consumption of animal products since livestock were on the move in quest for 
pasture and water. Future research should assess dietary patterns in other 
seasons of the year and compare the dietary score of children during those 
seasons. 



ii. Studies on drivers to low dietary diversity in both pastoral and agro-pastoral 
communities to be carried out. 


 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 


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APPENDICES 

APPENDIX A: INFORMED CONSENT 

My name is Maxwell Hongo Owiti, a student at Kenyatta University pursuing Master 
of Science in Food, Nutrition and Dietetics. I am carrying out a study on “Dietary 
diversity and nutrient adequacy of children aged 12-23 months of age in pastoralist 
and agro-pastoralist communities in Loima Sub-County.” The information you may 
provide will be useful to both the County and National Government and other Non-
Governmental Organization who provide some nutrition programs in quest of 
reducing the rate of malnutrition in Turkana County. 

1. Procedure to be Followed 

The participation in this study will require that I ask you some questions, which I will 
record a questionnaire. I will collect information on socio-economic and demographic 
characteristics, Food you gave your child from morning until you go to bed, foods 
consumed in the last seven days within the households, and the foods and items sold 
in the market. 

As a Kenyan citizen protected by the supreme Constitution of Kenya Chapter Four; 
The Bill of Rights, you have the rights to refuse participation in this study in case the 
information required will violates your privacy affairs or that of your family. You are 
still entitle to the same services provided by the County Government and National 
Government, whether you agree to join the study or not and your decision will not 
change the services you will receive as a resident of Loima Sub County. 

Kindly be informed that participation in this study is voluntary. You have the freedom 
to ask any questions related to this study. Feel free to respond to any questions and 


you have the freedom to stop the interview at any time. There will be no 
consequences attached to this. 

2. Benefits and Compensation 

There are no rewards or incentives offered for participation in this study. The 
participation is purely voluntary. If you honestly participate in this study, you will 
help us get useful information on how to improve the dietary diversity and nutrient 
adequacy among the pastoralists and agro-pastoralists community in the region. This 
will in turn help to reduce the rate malnutrition in the region. As a participant, you 
will be given an opportunity to present your views and opinion that can be used to 
improve dietary diversity score. 

3. Discomfort and Risks 

Some of the questions you may be asked are on intimate subject and may be 
technical, embarrassing and make you uncomfortable. If you face this, you are free to 
excuse yourself from providing answers to such questions. The interview may take 
approximately 30-45 minutes of your time. 

4. Confidentiality 

Your name as a participant will not be recorded on the questionnaire. Upon 
answering, the questionnaire will only be used by the researcher and relevant 
institution. All the information given by you will be used for the research purpose 
only. 

5. Voluntary Participation 

The participation is purely voluntary and should you feel unhappy with the process, 
you can discontinue or decline to answer the any questions. I however encourage you 


to participate in the study as findings will be important for improvement of dietary 
diversity and nutrient adequacy in the Sub County. 

6. Contact Information 

In the event you may need further clarification about this study, you are free to 
contact; 

1. Kenyatta University Ethics Review Committee 


P.O. Box 43844, 

Nairobi, 00100 

Fax: 8711242/8711575 

Tel: 8710901/12 

Email: chairman.kuerc@ku.ac.ke 

 Kuerc.secretary@ku.ac.ke 

Website: www.ku.ac.ke 

2. Dr. Judith Munga 


Lecturer Kenyatta University 

munga.judith@ku.ac.ke 

Cell: +254722974465 

3. Dr. Joseph Kobia 


Lecturer Kenyatta University 

mwitiliria@gmail.com 

Cell: +254722359925 

 


7. Participant’s Statement 

The above written information regarding my participation in the study is clear to me. I 
have given a chance to ask questions and have been answered to my satisfaction. I 
have further been assured of confidentiality on any information that will be shared. 
My participation in this study is entirely voluntary. 

Signature of Participant ………………….. Date ……………………. 

Signature of Witness ……………………. Date ……………………… 

8. Investigator’s Statement 

I, the undersigned, have explained to the volunteer of the study procedure, benefits, 
risks, compensation, confidentiality and contact information in a language she or he 
understands best. 

Name of the investigator …………………………………………………… 

Signature of investigator……………....... Date…………………………… 

 

 

 

 

 

 

 

 

 

 

 

 

 


APPENDIX B: DEMOGRAPHIC AND SOCIO-ECONOMIC INFORMATION 

Village ID 

|_|_| 

Enumerator ID 

|_|_| 

Household ID 

|_|_| 

Name of Mother/ 
Caregiver: 

 

Date (dd/mm/yyyy) 

|_|_| |_|_| |_|_|_|_| 



 

1 

What is the birth date of your child (include name of 
child)? 

(If she does not know, ask the mother to show you 
the birth certificate/ MCH/ /vaccination card and 
record the birth date from it) 

If there is no written record, try to find the birth date 
using a local calendar of events 

BIRTH DATE 

|_|_| |_|_| |_|_|_|_| 

Day Month Year 

2 

Is your child a boy or girl? 

1= Male 

2= Female 

SEX CHILD 

|_| 

3 

What is your year of birth or age in 
years? 

 

A. Record 
year of birth 

88= don.t 
know 

BIRTH DATE OF 
MOTHER 

|_|_|_|_| 

Year 

B. Record age in years 

88= don.t know 

AGE 
MOTHER 

|_|_| 

4 

What is your marital status? 

1= Married monogamous 

2= Married polygamous 

3= Widowed 

4= Divorced or separated 

5= Single 

MARITAL 
STATUS 

|_|_| 

5 

How many children have you given 
birth to? (whether alive or dead) 

Record total number 

NO. 
CHILDREN 

|_|_| 

6 

What is the sex of the head of this 
household? 

1= Male 

2= Female 

SEXHHH 

|_|_| 

7 

What is the age of the head of your 
household? 

B Record age in years 

88= don.t know 

AGEHHH 

 

8 

How many people live permanently 

Record total number of household 

HHMEMNO 

|_|_| 




in your household? 

(In the past 6 months) 

 

members 

9a 

What is the highest level of school 
attended you? 

 

0= no schooling If no, go to . 
Q10a 

1= primary 

2= secondary 

3= more than secondary 

99=Other 
(Specify):________________ 

MOTHEDULEV 

|_|_| 

9b 

What is the highest class completed 
at school by the head of this 
household? 

 

Record number of years at level of 
schooling 

88=Don’t know 

MOTHEDUYR 

|_|_| 

10a 

What is the highest level of school 
attended by the head of this 
household? 

 

0= no schooling If no, go to . 
Q11 

1= primary 

2= secondary 

3= more than secondary 

99=Other 
(Specify):________________ 

HHHEDULEV 

|_|_| 

10b 

What is the highest class you 
completed at school? 

 

Record number of years at level of 
schooling 

88=Don’t know 

HHHEDUYR 

|_|_| 

11 

What are the sources of income for your household throughout the year? 

List as many as relevant to the household. 

0= no, 1= yes 

88= don.t know 

 

Sale of own produced crops including grains, vegetables and fruits 
(market sale) 

INCCROP 

|_|_| 

Sale of own animal or produced animal products 

INCANIMA 

|_|_| 

Sale of own produced or gathered goods/crafts (charcoal, stones, firewood, 
baskets, etc…) 

INCGOOD 

|_|_| 

Casual labour/temporary salary (daily wages) 

INCTEMP 

|_|_| 

Small business (mini shops, local drinks (brew), etc…) 

INCBUISN 

|_|_| 




Employment/ regular salary 

INCSALAR 

|_|_| 

Remittances from relatives/husband 

INCREMITT 

|_|_| 

Income generated by sale or exchange of public transfers (cash for work, 
food for work, food vouchers, fertilizer or seed vouchers, HSNP (Hunger 
Safety Net Programme etc.) 

INCPUBTR 

|_|_| 

Subsistence farming 

INCSUBS 

|_|_| 

Other(Specify): ____________________________________ 

INCSPEC 

|_|_| 

12 

What is the floor of your main 
residence made of? 

1=Earth floor; 

2=stone; 

3=cement; 

4= tile; 

5=wood; 

99= Other 
(specify)________________ 

FLOORMAT 

|_|_| 

13 

What are the walls of your main 
residence made of? 

1=Wood; 

2=earth wall; 

3=iron sheet; 

4=stone; 

5=brick; 

6=cement; 

99=Others 
(specify)________________ 

WALLMAT 

|_|_| 

14 

What is the roof of your main 
residence made of? 

1=Straw/grass; 

2=iron sheet; 

3=tile; 

4=cement; 

5=bamboo; 

99=Others 
(specify)_______________ 

ROOFMAT 

|_|_| 

15 

Does any member of this household 
have access to any land that can be 
used for agriculture? 

0= no 

1= yes 

HHLAND 

|_| 

16 

Does this household own any 

0= no 

HHANIMAL

|_| 




livestock herds, or farm animals, or 
poultry, or fishponds? 

1= yes 

S 

17a 

What is the main source of drinking 
water for members of your 
household during the rainy/ wet 
season? 

1= piped water into dwelling, to 
yard or plot, public tap/standpipe, 
tube well / borehole, protected dug 
well, protected spring, rainwater 
collection 

DRINKWAW 

|_| 

2= unprotected spring, 
unprotected dug well, cart with 
small tank/drum, tanker truck, 
surface water (river, stream, dam, 
lake, pond, canal, irrigation 
channel), bottled water) 

18a 

Does this household have access to a 
toilet facility? 

Observe if there is any toilet facility 
in the homestead 

0= no 

1= yes 

88= don.t know 

LATRINE 

|_|_| 

19b 

What kind of toilet facility do 
members of your household usually 
use? 

 

1= Pit latrine with slab, 
composting toilet 

 

2= Pit latrine without slab/open pit, 
bucket, hanging toilet/hanging 
latrine, bush or field or lake. 

TYPLATRINE 

|_| 



 

 


APPENDIX C:INDIVIDUAL DIETARY DIVERSITY QUESTIONNAIRE 

Please describe the foods (meals and snacks) that you ate yesterday during the 
day and night, whether at home or outside the home. Start with the first food 
eaten in the morning. 

 

Write down all food and drinks mentioned by the respondent. When 
the respondent has finished, probe for meals and snacks not 
mentioned. 

Breakfast 

Snack 

Lunch 

Snack 

Dinner 

Snack 

 

 

 

 

 

 



 

When the respondent recall is complete, fill in the food groups based on the 
information recorded above. For any food groups not mentioned, ask the 
respondent if a food item from this group was consumed. 

Question 

Food group 

Examples 

YES=1 

number 

NO=0 

 

 

 

 

 

 

1 

CEREALS 

corn/maize, rice, wheat, sorghum, millet or 
any other 

 

 

 

grains or foods made from these (e.g. 
bread, noodles, 

 

 

 

porridge or other grain products) + insert 
local foods e.g. 

 

 

 

ugali, nshima, porridge or pastes or other 
locally 

 

 

 

available grains 

 

 

 

 

 

2 

VITAMIN A 
RICH 

pumpkin, carrots, squash, or sweet potatoes 
that are 

 

 

VEGETABLES 

orange inside + other locally available 

 




AND 

vitamin-A rich 

 

TUBERS 

vegetables (e.g. red sweet pepper) 

 

 

 

 

 

3 

WHITE TUBERS 
AND 

white potatoes, white yams, white cassava, 
or other 

 

 

ROOTS 

foods made from roots 

 

 

 

 

 

4 

DARK GREEN 
LEAFY 

dark green/leafy vegetables, including wild 
ones + locally 

 

 

VEGETABLES 

available vitamin-A rich leaves such as 
amaranth, 

 

 

 

cassava leaves, kale, spinach etc. 

 

 

 

 

 

5 

OTHER 
VEGETABLES 

other vegetables (e.g. tomato, onion, 
eggplant) , 

 

 

 

including wild vegetables 

 

 

 

 

 

6 

VITAMIN A 
RICH 

ripe mangoes, cantaloupe, apricots (fresh or 
dried), ripe 

 

 

FRUITS 

papaya, dried peaches + other locally 
available vitamin 

 

 

 

A-rich fruits 

 

7 

OTHER FRUITS 

other fruits, including wild fruits 

 

 

 

 

 

8 

ORGAN MEAT 
(IRON- 

liver, kidney, heart or other organ meats or 
blood-based 

 

 

RICH) 

Foods 

 

 

 

 

 

9 

FLESH MEATS 

beef, pork, lamb, goat, rabbit, wild game, 
chicken, duck, 

 

 

 

or other birds 

 

 

 

 

 

10 

EGGS 

chicken, duck, guinea hen or any other egg 

 

 

 

 

 

11 

FISH 

fresh or dried fish or shellfish 

 

 

 

 

 

12 

 

LEGUMES, NUTS 
AND 

beans, peas, lentils, nuts, seeds or foods 
made from 

 

 

 

 

SEEDS 

These 

 

 

 

 

 

 

 

13 

 

MILK AND MILK 

milk, cheese, yogurt or other milk products 

 

 

 

 

PRODUCTS 

 

 




 

 

 

 

 

 

14 

 

OILS AND FATS 

oil, fats or butter added to food or used for 
cooking 

 

 

 

 

 

 

 

15 

 

RED PALM 
PRODUCTS 

Red palm oil, palm nut or palm nut 
pulp sauce 

 

 

 

 

 

 

 

16 

 

SWEETS 

sugar, honey, sweetened soda or sugary 
foods such as 

 

 

 

 

 

chocolates, candies, cookies and cakes 

 

 

 

 

 

 

 

17 

 

SPICES, 
CONDIMENTS, 

spices(black pepper, salt), condiments (soy 
sauce, hot 

 

 

 

 

BEVERAGES 

sauce), coffee, tea, alcoholic beverages OR 
local 

 

 

 

 

 

examples 

 

 

 

 

 

 

 

 

 

 

 

 

YES=1 

 

 

 

 

 

NO=0 

 

 

 

 

 

 

 

Individual 

 

Did you eat anything (meal or snack) OUTSIDE of the home 
yesterday? 

 

 

level only 

 

 

 

 

 

 

 

 

 

 

 

 

 

Household 

 

Did you or anyone in your household eat anything (meal or 
snack) OUTSIDE of the 

 

 

 

Home yesterday? 

 

 

 

level only 

 

 

 

 

 

 

 

 

 

 

 

 

 

 



 


APPENDIX D: HOUSEHOLD AGROBIODIVERSITY SURVEY QUESTIONNAIRE 

 

Enumerator ID 

 

Respondent name 

 

Village ID 

 

Age of respondent 

 

Household ID 

 

Sex of respondent 

 

Date (dd/mm/yyyy) 

 

1Relationship of respondent to household head 

 



11=household head, 2=spouse, 3=child, 4=parent, 99=Others (specify) 

1. Household on – farm species edible diversity 

Please list all the useful species on your farm that are used for food by you or any member of your household. 

 

Species 
Name 

Language 

How many years 
have you grown 
this species on 
your farm? 
(number) 

What is the 
acreage under 
this species 
(approximate 
in acres) 

Who takes primary 
care of the species? 
(1=Husband, 2=wife; 
3=both; 4=child, 
5=elders, 99=other 
(specify))(1ANSWER) 

What contribution does 
the species make to 
overall household food 
consumption? 
(1=Major; 2=medium; 
3=minor; 4=no 
contribution) 
(1ANSWER) 

If sold, what contribution 
does the species make to 
overall household income? 
(1=Major; 2=medium; 
3=minor; 4=no 
contribution) (1ANSWER) 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 




 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 



2. Household wild edible plant species diversity 

Please list all the useful species collected from the wild and used for food by you or any member of your household. 

 

Species Name 

Language 

Who collects/harvests the 
species from its habitat? 
(1=Husband, 2=wife; 3=both; 
4=child, 5=elders, 99=other 
(specify))(1ANSWER) 

What contribution does the species 
make to overall household food 
consumption? (1=Major; 2=medium; 
3=minor; 4=no contribution) 
(1ANSWER) 

If sold, what contribution does the 
species make to overall household 
income? (1=Major; 2=medium; 
3=minor; 4=no contribution) 
(1ANSWER) 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 




 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 



 

 

3. Domesticated animal species maintained by the household 

Please list all useful animal species used for food that you maintain on farm (including birds, insects and cultured fish). 

 

Name of 
animal 

Language 

How many animals 
of this species do 
you currently own? 
(number) 

What product from the 
animal is used for food? 
(1=eggs, 2= milk, 3 =meat, 
99 = others (specify)) 

How is the product used? 
(1=household 
consumption, 2=sale, 
3=both, 99=others 
(specify)) 

How do you estimate the 
total contribution (milk, eggs, 
meat) the species makes to 
overall household food 
consumption? (1=Major, 
2=medium, 3=minor, 4=no 
contribution)(1ANSWER) 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 




 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 



 

4. Wild animal species hunted or collected by the household 

Can you please list all useful animal species that you or someone in your household hunts or collects from the wild for FOOD? This includes 
any animals, fish, insects, worms or their products from the wild that you use for food. 

 

Name of 
animal 
species 

Language 

What is the 
species used 
for? (1=HH 
consumption, 
2=sale, 
3=both) 

Who harvests/hunts 
the species? 
(1=Husband; 2=wife; 
3=both; 4=child, 
5=elders, 99=other 
(specify)) 

Who makes the 
primary decision about 
the consumption of 
this species? 
(1=Husband; 2=wife; 
3=both; 4=child, 
5=elders, 6= not 
consumed; 99=other 
(specify)) (1ANSWER) 

What contribution 
does the species 
make to overall 
household food 
consumption? 
(1=Major; 
2=medium; 
3=minor; 4= no 
contribution)(1ANSWER) 

If sold, what 
contribution does the 
species make to 
overall household 
income? (1=Major; 
2=medium; 3=minor; 
4= no 
contribution)(1ANSWER) 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 




APPENDIX E: QUANTITATIVE 24-HOUR RECALL QUESTIONNAIRE 

Interview Date: 

Day of the week for recall: 

Recall number: 1 2 (circle) 

Enumerator Name: 

Childs Name: 

Household ID _ _ _ 

Mothers Name: 

 

 

Yesterday: 

 

 

Did the child take medicine? 

If yes, name: _____________________ 

 

1= Yes 2= No |_| 

Was yesterday a celebration or feast day where the child ate unusual foods? 

1= Yes 2= No |_| 

Did you feel unwell yesterday? 

 

1= Yes 2= No |_| 



 

List of household measures and volumes 

Foods 

Household measure (cup, spoon, plate) 

Volume 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 



 


1. 24 – Hour recall form for the child 

Time 

2Meal code 

3Place of 
preparation 

Dish 

Ingredients 

Total Quantity 
cooked 

Quantity of food 
served 

Plate waste 

Quantity 
consumed 

Description of 
dish/food 

Description 

Quantity 

 

4Source 

Wild5 

Quantity 

Unit 

Quantity 

Unit 

Quantity 

Unit 

Quantity 

Unit 

A 

B 

C 

D 

E 

F 

H 

 

I 

J 

K 

L 

M 

N 

O 

P 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 



21=before breakfast, 2=breakfast, 3= mid-morning, 4= lunch, 5=afternoon, 6=dinner/supper, 7=before sleep, 8=during night 

3Place: 1= Home 2= Outside home 

41= Own production 2= Purchase 3 = Gifts/Aid 4 = Others (specify) 

5 1 = Yes 2= No 

 


Date 

 

Village/place of trade 

 

Trader ID/Sheet number 

 

Interviewer 

 

Foods are to be measured at least three different weights if only there are different weights at which foods are sold 
If the unit of measurement is different from the stated (g), write the right unit for that food. 

 

Local Name 

English Name 

Price (KES) Plenty 
season 

Weight 1 

Weight 2 

Weight 3 

Portion sizes 

Comments 

Food 

 

 

 

 

g 

g 

g 

 

 

 

 

 

g 

g 

g 

 

 

 

 

 

g 

g 

g 

 

 

 

 

 

g 

g 

g 

 

 

 

 

 

g 

g 

g 

 

 

 

 

 

g 

g 

g 

 

 

 

 

 

g 

g 

g 

 

 

 

 

 

g 

g 

g 

 

 

 

 

 

g 

g 

g 

 

 

 

 

 

g 

g 

g 

 

 

 

 

 

g 

g 

g 

 

 



 APPENDIX F: MARKET SURVEY SHEET 


APPENDIX G: KREJCIE AND MORGAN TABLE OF SAMPLE SIZE 
DETERMINATION 

 


APPENDIX H: KU RESEARCH APPROVAL AND AUTHORIZATION 

 


APPENDIX I: KENYTTA UNIVERSITY ETHICAL CLEARANCE 

 

 


 

 


APPENDIX J: RESEARCH PERMITS 

 

 


 


APPENDIX K: MAP OF TURKANA COUNTY 

 Image result for loima map in turkana