Determinants of Under-Fivechild Malnutritionin Arsi

ADAMA SCIENCE AND TECHNOLOGY UNIVERSITY DEPARTMENT OF GEOGRAPHY AND ENVIRONMENTAL MANAGEMENT

DETERMINANTS OF UNDER-FIVE CHILD MALNUTRITION IN ARSI NEGELE

WOREDA, WEST ARSI ZONE OF OROMIA

MA THESIS SUBMMITED TO THE DEPARTMENT OF GEOGRAPHY AND ENVIRONMENTAL MANAGEMENT

BY ALEMAYEHU ERENA

JUNE 6, 2016

ADAMA

ADAMA SCIENCE AND TECHNOLOGY UNIVERSITY DEPARTMENT OF GEOGRAPHY AND ENVIRONMENTAL MANAGEMENT

DETERMINANTS OF UNDER-FIVE CHILD MALNUTRITION IN ARSI NEGELE WOREDA, WEST ARSI ZONE OF OROMIA MA THESIS SUBMMITED TO THE DEPARTMENT OF GEOGRAPHY AND ENVIRONMENTAL MANAGEMENT

BY ALEMAYEHU ERENA

ADVISOR DR MESSAY MULUGETA

Thesis Submitted to the School of Humanities and Law of Adama Science and Technology University in a partial fulfillment of the Requirement for the Degree on Masters of Art in Population and Socio Economic Development Planning

June 6, 2016 Adama

SIGNATURE PAGE

Submitted by

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Name of Student Signature Date

Approved by:

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Advisor Signature Date

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Examiner Signature Date

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Examiner Signature Date

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DGC chairman Signature Date

TABLE OF CONTENTS

CONTENTS PAGES

TABLE OF CONTENTS ...... iii Acronyms ...... v List of Tables ...... vi List of Figures ...... vii Acknowledgement ...... viii Abstract ...... ix

CHAPTER ONE ...... 1 INTRODUCTION ...... 1 1.1 Background of the Study ...... 1 1.2 Statement of the Problem ...... 2 1.3 Objectives of the Study ...... 3 1.4 Research Questions...... 3 1.5 Significance of the study ...... 4 1.6 Scope and limitations of the study...... 4 1.7 Data quality control procedures ...... 5 1.8 Ethical Considerations ...... 5

CHAPTER TWO...... 6 RELATED LITERATURE REVIEW ...... 6 2.1 Theoretical Literature ...... 6 2.1.1 Food, Nutrition and Food Security ...... 6 2.1.2 Malnutrition, its Causes and Vulnerability ...... 7 2.1.3 Manifestation of Malnutrition ...... 8 2.2 Empirical Literature ...... 8 2.3 Conceptual Framework ...... 10 2.3.1 Immediate Causes ...... 10 2.3.2 Underlying Causes ...... 12 2.3.3 Basic Determinants ...... 13 2.4 Literature gap ...... 13

CHAPTER THREE ...... 14 BACKGROUND OF THE STUDY AREA AND THE RESEARCH METHOD ...... 14 3.1 Description of the study area ...... 14 3.1.1 Location and Biophysical setups ...... 14 3.1.2 Demographic profile ...... 15 3.1.3 Socioeconomic setups ...... 15 3.2 Methods and Materials...... 17

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3.2.1 Study design ...... 17 3.2.2 Study population ...... 17 3.2.3 Sources and types of data ...... 17 3.2.4 Tools of data collection ...... 18 3.2.5 Study variables ...... 19 3.2.6 Sample size determination and sampling techniques ...... 19 3.2.7 Method of Data Analysis...... 21 3.2.8 Regression ...... 23

CHAPTER FOUR ...... 24 RESULTS AND DISCUSSION ...... 24 4.1 Demographic and parental characteristics ...... 24 4.2 Socio economic characteristics ...... 25 4.3 Maternal and child health related characteristics ...... 26 4.4 Nutritional status and its determinants ...... 29

CHAPTER FIVE ...... 34 CONCLUSION AND RECOMMENDATIONS ...... 34 5.1 Conclusion ...... 34 5.2 Recommendations ...... 36

References ...... 38

Annexes ...... 41

Acronyms ANWHO: Arsi Negele Woreda Health Office CHD: Child Health Day DPPC: Disaster Prevention and Preparedness Commission DPPO: Disaster Prevention and Preparedness Office ECSA: Ethiopian Central Statistical Agency EDHS: Ethiopian Demographic and Health Survey FAO: Food and Agriculture Organization FGD: Focus Group Discussion IFPRI: International Food Policy Research Institute IISD: International Institute for Sustainable Development KII: Key Informant Interview MDG: Millennium Development Goal MUAC: Middle Upper Arm Circumference NCHS: National Center for Health Statistic NGO: Non-Governmental Organization NNP: National Nutrition Program PEM: Protein Energy Malnutrition UMR: Under-five Mortality Rate UN: United Nations UNCPE: United Nations Country Program Ethiopia UNICEF: United Nations Children Fund UNWFP: United Nations World Food Program VCHW: Volunteer Community Health Worker WHO: World Health Organization

List of Tables

Table Name Page

1: Proportion of sample allocated to each cluster...... 21 2: Classification of malnutrition for weight-for-height, height-for-age, and weight-for-age based on Z-score...... 22 3: Demographic and parent related characteristics of the sample respondents...... 25 4: Socioeconomic characteristics of the sample respondents...... 26 5: Child health related characteristics of sampled respondents...... 31 6: Nutritional status of sample children distributed by age group based on weight-for-height, weight-for-age and height-for-age...... 32 7: Prevalence of malnutrition by sex of the sample children ...... 32 8: Statistical analyses showing the influence of selected variables on malnutrition as measured by stunted, April 2015. n=556 ...... 33 9: Statistical analyses showing the influence of selected variables on malnutrition as measured by underweight, n=556 ...... 33 10: Statistical analyses showing the influence of selected variables on malnutrition as measured by wasted, n=556...... 33

LIST OF FIGURS

FIGURES PAGES 1: Conceptual framework ………………………………………………………….12

2: Map of Arsi Negele Woreda …………………………………………………….15

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ACKNOWLEDGEMENT I would like to express my deep appreciation to my advisor Dr. Messay Mulugeta for his valuable support in corrective comments and criticism throughout this study. I would like to extend my thanks to Mr. Abas Kedir for his full support in statistical analysis of the household survey data. I would like to express my appreciation to Mr. Andinet Bekele (Disaster Prevention and Preparedness Office of Arsi Negele) and Gambelto, Ali Weyo and Galena Kelo Kebele health extension workers for their unreserved support in data collection and organizing its activities.

I would also like to express my thanks to Mr Gadisa Jebesa, Mr Eliyas Kebede, Mr Dhufera Ijigu, Mr Siraj Abdulahi and my classmates who supported me and interested to share me their knowledge. Finally, I would like to express my deepest appreciation to my wife W/o Mulu Addis for her unreserved assistance throughout the course.

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ABSTRACT Malnutrition of under-five children is one of the major problems in the world particularly in developing countries. It is becoming recurrent in Africa and Asia. Different studies indicate that malnutrition is chronic and Ethiopian Demographic and Health Survey is one of such studies which supply continuous data every five years. EDHS shows that there is a decreasing tendency in malnutrition cases though not in the assumed pace. In Oromia regional state in Arsi Negele woreda, this study was conducted to identify the nutritional status of under-five children and the factors associated to malnutrition cases. To reach to the planned result, 556 under-five children were measured and their caretakers made to respond to structured questioner in three rural kebeles (Gambelto, Ali Weyo and Gale & Kelo). The height, weight and age data obtained revealed that acute malnutrition (wasting) is 18.3%, underweight (less weight for its age) is 35.1% and stunting (less height for his age) is 57.9%. This is very high when compared with the national average 10%, 30% and 46% respectfully for wasting, underweight and stunting. In addition to this the study revealed that household size, income status, use of birth control, child age, child sex and education status of mother have significant association with malnutrition cases. Therefore, the researcher proposed a well targeted and coordinated nutrition supplementation, to prepare a program to aware and empower women, to strengthen family planning program, to plan and implement targeted income generating scheme, to capacitate health institutions and others to solve those appreciated problems or factors.

Keywords: Malnutrition, under-five children, wasting, underweight, stunting, nutrition supplementation, family planing.

CHAPTER ONE INTRODUCTION

1.1 Background of the Study

Malnutrition (which mostly refer for under-nutrition in this study) occurs when an individual doesn’t get adequate quantity and quality of food or the individual body can’t fully utilize the food consumed as a result of illness. Most importantly, nutritional status in early life, primarily during the early 12 months, is very crucial for the future adulthood healthy life. Generally, children under the age of five are the most vulnerable group and from those malnourished children who might survive may experience stunted growth, illness and lifelong malnutrition (FAO, 1997).

Princess of Jordan, on her address to November 2014 United Nations conference recalled her meeting with a woman “who did not name her baby girl because she knew she would die” from malnutrition. This shows how far its effect goes (IISD, 2014). Malnutrition is considered as an underlying factor in many diseases for both children and adults, and is particularly prevalent in developing countries, where it affects one out of every 3 preschool-age children (Mahgoub et al., 2006).

Malnutrition affects about 805 million people worldwide and at least one third of them are children (IISD, 2014). According to Emergency Nutrition Network of 2012, due to the underlying causes of malnutrition more than 3.5 million children under the age of five die each year globally (Ferew Lemma et al, 2012). When it comes to the developing nations, more than half of all deaths among children under-five years old are due to malnutrition (FAO, 1997).

Looking into the increasing and complexity of the problem, in the year 1990, United Nations assembly discussed and agreed on a global plan called Millennium Development Goal (MDG). One of these eight MDG goals, MDG4, plans to decrease the under-five child mortality by two-third by the year 2015. As to ongoing annual reports of United Nations a number of countries were making the best performance, and Ethiopia is one of these countries (UNCPE, 2012).

When this issue is viewed occupation wise, subsistence farmers, pastoralists, and agro-pastoralists whose livelihoods largely depend only on agriculture and animal production, are the main categories of food insecure people, and thus vulnerable to

1 malnutrition. Furthermore, the childhood and current nutritional status of women will contribute to the high level of child malnutrition through intergenerational relationship (FAO, 1997).

In Ethiopia, although malnutrition rates among children are steadily decreasing, they remain at unsatisfactorily high levels. The 2011 Ethiopian Demographic and Health Survey estimate the national prevalence of stunting in rural Ethiopia to be 46% and underweight 30% (ECSA, 2011).

According to Arsi Negele Woreda Health office, a continuous assessment of under- five children and pregnant & lactating mothers for malnutrition is conducted monthly. On the recent April 2015 CHD screening report, there were 4,623 moderate, 361 sever and 45 oedematic cases. The data obtained monthly from this assessment shows fluctuating result, few times down but most of the time an increased figure. Though government and NGO’s were working on a number of programs, to alleviate the problems by targeting children under the age of five, no significant change has been observed. Responding to malnutrition in such a community requires a thorough understanding of the socioeconomic and other related causes. This study conducted an assessment of the status of malnutrition and the socioeconomic factors which are determinant for child malnutrition in Arsi Negele Woreda.

1.2 Statement of the Problem

Due to their mental, physical and emotional development, children are particularly prone to the dangerous combination of malnutrition and illness (FAO, 1997). Economic constraints are considered as the major factors in poor child nutrition, but limited knowledge and bad practice of child feeding and food hygiene also have a significant contribution (Abera, 1996; FAO, 1997). Furthermore, region of residence, birth order and birth interval of the child, number of antenatal care visit for the mother, education of mother, access to basic health care, and availability of safe drinking water and sanitation services are also those affecting the nutritional status of children. In general, malnutrition is the manifestation of macronutrients and micronutrients deficiencies.

Malnutrition can be explained using three classifications namely wasting, stunting and a combination of both (wasting and stunting) called underweight (FAO, 1997). These

2 classifications are identified based on anthropometric measurements like weight and height of the child. These measurements were first used to detect growth failure and then other under-nutrition manifestations are identified by comparing collected data with international reference data. On such nutritional assessments, the growth of children of similar age and sex in developed countries are used as reference. This nutritional status (in our case under-nutrition) is manifested due to different factors highlighted above. Therefore, assessing these causes and trying to identify the determinant factors of malnutrition in Arsi Negele Woreda was the main purpose of the study. The study applied a household survey and key informants interviews to acquire primary data, and analyzed it to distinguish the determining factors. According to the report obtained from this Woreda health office, there were more than three NGO’s and government programs working on malnutrition. Therefore, in order to help bring an improved output, it was important to assess and determine the underlying factors of malnutrition in Arsi Negele Woreda.

1.3 Objectives of the Study

General Objective

The general objective of this study was to assess and identify determinants of under- five children malnutrition in Arsi Negele Woreda, West Arsi zone of Oromia regional state.

Specific Objectives

The specific objectives of the study were to:

1. assess the status of under-nutrition (wasting, underweight and stunting) among under-five children in the study area.

2. identify the factors influencing the nutritional status of under-five children in the study area.

3. propose possible interventions which help in the reduction of under-nutrition of under-five children in the study area.

1.4 Research Questions

The research tries to answer the following basic questions.

1. What was the status of under-nutrition among under-five children in the study area?

2. What were the factors influencing nutritional status of under-five children in the study area?

3. What type of intervention would be recommended to play an important role in reducing the under-nutrition of under-five children in the study area?

1.5 Significance of the study

According to the quarter report of Woreda health office, the level of malnutrition in Arsi Negele Woreda is one of the highest in West Arsi zone. As a result of this situation different health and nutrition intervention programs implemented by NGOs and government were underway and there is no significant decrease in program beneficiary figure. There are times where these figures show a significant increment. This means number of children were still vulnerable to disease and other life threatening consequences which intern have social as well as economic problems. In addition, nutrition studies or assessments were limitted and concerned sector offices were unable to refer one. So, studying the major factors playing an aggravating role will help those intervening partners. It could also be considered as an effort made with a hope that the result will be helpful to strengthen knowledge and understanding about these determinant factors and initiate further studies.

1.6 Scope and limitations of the study

The main focus of this research was to identify those factors leading to child malnutrition. As it is well known most of this factors were associated with human behavior which will be hard to crack. Some of the information required in this study like income and overall household capital were not disclosed by respondents, due to unknown reasons. Furthermore, such study requires an in-depth investigation which demands a vast primary and secondary data collection and ample time. Due to shortage of budget and time, the researcher focused only on limited kebeles as indicated in the following sections. However, due to similar socioeconomic background of this kebeles, it is assumed that the result obtained could reflect the situation in the district. Moreover, effort was exerted to well support the study by secondary information reported by other organizations.

1.7 Data quality control procedures

Anthropometric measurements were prone to reading errors. Salter scale is adjusted to zero reading after each measurement. The other instrument taken care-off is Middle Upper Arm Cercumference (MUAC). Mostly errors emanate during reading and recording. For a better result all enumerators training was made to give emphasis to measurement steps and care needed. The supervisors were strictly advised to closely follow these sensitive measurement areas. Furthermore, following data entry, editing, cleaning, checking extreme values and unexpected results were done using SPSS V20 computer software.

1.8 Ethical Considerations

Ethical clearance obtained from the department of Geography and Environment Management. Written consent was obtained from regional, zone and Woreda health offices to conduct the study in Arsi Negele Woreda sample sites. In the same way explanations was provided to the Woreda sector offices and Kebele administrators. On every survey procedure the objective of the study and why this data collected was explained to each respondent and verbal permission obtained before each activity. Participants were assured that their name will not be used in the report. Data on private issues confidentiality is guaranteed.

CHAPTER TWO RELATED LITERATURE REVIEW

2.1 Theoretical Literature 2.1.1 Food, Nutrition and Food Security Human beings require food, which is the most basic need, to grow, reproduce and maintain good health. More specifically, according to FAO’s 1997 publication, food serves mainly for growth, energy and body repair, maintenance and protection. Most food in the world comes from cereals. There have been remarkable development in agriculture in the past decades where high-yielding varieties of the important cereals (rice, wheat and maize) have been successfully developed, and much progress has been made in increasing food yields per hectare of land.

All foods are made up of a combination of macronutrients (protein, fat, carbohydrate) and micronutrients (vitamins and minerals) (FAO, 1997). The food consumed is said to be nutritious, when it gives these nutrients in required quality and quantity to the body. The cereal grains provide some of the constituents needed for energy, growth and body repair and maintenance (WFP, 2005). As we increase the variety of these food items, more of the nutrients needed for a body will be obtained. These macronutrients form the bulk of the daily diet and supply all the energy needed by the body. For a person, household and community to be nutritionally secure, the food must provide all the nutrients needed for good nutrition and there must also be adequate health and care. Micronutrients are needed in lesser amount but are very necessary for healthy body development (WFP, 2000).

Furthermore, if there is an insufficient quantity of food to meet the food needs of a population, then some persons or some households will be food insecure. Thus, the concept of food security deals with the basic needs of human being. It will be explained in terms of food supply availability in adequate quantity and variety. There are a number of broader definitions forwarded by different scholars and institutions. FAO’s 1997 publication puts food security as ‘access by all people at all times to sufficient food required for healthy and active life’. Food security will be discussed under two major titles, national and household food security. Local seasonal factors have very important influences on food supply and on the other hand access to food is influenced by economic issues, physical infrastructure and consumer preferences.

Hence, inadequate food, be it due to food shortage or inappropriate consumer behavior or intra-household distribution, is termed as food insecurity. It should also be noted that an overall availability of food in a country, community or household is no guarantee for its equitable consumption (WFP, 2005).

2.1.2 Malnutrition, its Causes and Vulnerability Malnutrition is a dangerous condition that develops when a body does not get enough nutrients to function properly. Inadequate availability of food for a family because of poverty, inequity or lack of sufficient arable land, and problems related to intra-family food distribution will be some of the causes. It is affecting about 805 million people worldwide and at least a third of them are children (IISD, 2014).

In the past, malnutrition was thought to be a medical problem with a single cause: protein deficiency. By the mid-seventies energy intake became a key issue. In recent years the multi-factorial nature of malnutrition has been recognized. This raised social and economic issues around access to food by the poor, and malnutrition was no longer viewed just as a medical problem to be treated. It is now widely accepted that most of malnutrition, more specifically under-nutrition, in developing countries is due to inadequate intake of both protein and energy and that it is often associated with infectious diseases. Moreover, poverty and the conditions associated with it, were recognized as the overriding causes of malnutrition (FAO, 1997).

The United Nations Children’s Fund (UNICEF) conceptual framework is a useful tool for the analysis of the causes of malnutrition. These causes were treated in three stages; at individual level, at household level and at community or population level. Exerting effort in identifying these causes of malnutrition will be very essential in deciding the appropriate intervention (DPPC, 2013; IISD, 2014).

As detailed earlier, malnutrition can be caused by eating too little, or an unbalanced diet that does not contain all nutrients necessary for good nutritional status. For adequate food to be available, certainly there must be adequate food production or sufficient capacity to purchase enough food. As a result, almost all over the world, people who are poor or who live in poverty-stricken areas are at the greatest risk for malnutrition (FAO, 1997; DPPC, 2002). It affects people of every age, although children under the age of five suffer the most. Adults and older children can access proportionally larger reserve of energy in their body than young children during

7 periods of reduced macronutrient intake. Since children have modest deposit of body fat, it is this young children who may be the most at risk (FAO, 1997; IFPRI, 2000; WFP, 2000).

2.1.3 Manifestation of Malnutrition Malnutrition can be identified in to three categories namely, stunting (shortness), wasting (thinness) and a combination of both called underweight (DPPC, 2002).

Stunting is past chronic malnutrition, where weight for age and height for age are low but weight for height is normal.

Wasting is acute current, short-duration malnutrition, where weight for age and weight for height are low but height for age is normal.

Wasting and Stunting are acute and chronic or current and long-duration malnutrition, where weight for age, height for age and weight for height are all low (FAO, 1997; DPPC, 2002).

Malnutrition in young children is currently the most important nutritional problem in most developing countries. Failure to grow adequately is the first and most important manifestation of malnutrition. A child who shows this growth failure may become shorter in height or lighter in weight than expected for a child of his or her age, or may be thinner than expected for height (FAO, 1997; UNICEF, 2009).

Malnourished body has a reduced ability to defend itself against infections. When their interaction on a body is further explained, infection makes malnutrition worse and poor nutrition increases the severity of infectious diseases. This interaction of malnutrition and infection is the leading cause of morbidity and mortality in children in most countries like Africa, Asia and Latin America (FAO, 1997). On the other hand, children who suffer from malnutrition at an early stage of life score lower on tests of cognitive skill, with the deficits persisting in to adulthood and thus diminishing income-earning potential. In general, malnutrition not only affects people’s health and wellbeing but also poses a high burden in the form of socioeconomic consequences to a country (IISD, 2014).

2.2 Empirical Literature As a result of economic and social causes, children who have not taken sufficient amount of food do not grow, and under more sever circumstances, they lose weight

(Belay, 2011). According to Standardized Monitoring and Assessment of Relief and Transition (SMART) methodology, malnutrition takes three forms: 1) failure to grow, results in height stunting; 2) loss of body tissue which results in wasting, and 3) accumulation of fluid which results in nutritional oedema (also called kwashiorkor or hunger oedema). The prevalence of each of these, malnutrition forms, are assessed during a nutritional survey by recording age, measuring weight and height (IFPRI, 2000; Belay, 2011).

According to International Institute for Sustainable development (IISD, 2014) publication, globally approximately 805 million people remain undernourished and two billion people suffer from micronutrient deficiencies. About 165 million under- five children are stunted, with short height for their age; about 52 million under-five children suffer from wasting, which is low weight for their height; and about 101 million under-five children are underweight, which is when weight-for-age is below - 2SD (UNICEF, 2013).

When viewed regionally, high prevalence level of stunting among children under-five years of age in Africa is 56 million in 2011 while it is 96 million in the same year in Asia. The prevalence of underweight of children under-five years of age for Africa is 28 million and for Asia 69 million in the years 2011. Similarly, the prevalence of wasting of under-five children in Africa is 13 million and that of Asia shows 36 million in 2011 (UNICEF et al., 2012).

According to Ethiopian Demographic Survey (ECSA, 2011), the prevalence of stunting of under-five children is about 46%, those underweight are about 30% and those with wasting are 10% in the year 2011.

Household food availability is the most important determinant of the nutritional status of a community which is influenced by local production and price. Furthermore, study from Brazil has showed that, of the social variables studied, family income and father’s education level were the two risk factors that have the strongest association with the nutritional status (Abera, 1996). Additionally, study conducted in Tanzania also showed that mother’s education and frequency of feeding have considerable effect on nutritional status of children (Abera, 1996; IFPRI, 2000). Different assessments conducted by target Woreda health office for 2013 and 2014 show a

9 fluctuating figure of malnourished children, few times down but most of the time an increasing tendency beside the number of intervention activities (ANWHO, 2014).

In general, factors that are contributing to malnutrition vary from country to country, among regions, zones and communities, as well as over time. Therefore, identifying those major factors playing a determinant role will be an important approach for the effectiveness of future interventions.

2.3 Conceptual Framework Malnutrition or undesirable physical or disease conditions related to nutrition can be caused by eating too little or an unbalanced diet that does not contain all nutrients necessary for good nutritional status. Literatures further explain that nutrition is directly related to food intake and infectious diseases such as diarrhea, acute respiratory illness, malaria and measles. Both infectious disease and food intake were explained as immediate causes and this further reflects underlying social and economic conditions at the household, community and national levels which are supported by political, economic and ideological structures existing within a country (DPPC, 2002).

The following diagram (Figure: 1) is a conceptual framework for nutrition adapted from UNICEF, as cited in IFPRI, 2000. It reflects relationships among factors and their influences on children’s nutritional status. It recognizes three levels of causality corresponding to immediate, underlying, and basic determinants of child nutritional status.

2.3.1 Immediate Causes These determinants of child nutritional status manifest themselves at the level of the individual human being. They are dietary intake (energy, protein, fat, and micro nutrients) and health status. These factors themselves are inter dependent. A child with inadequate dietary intake is more susceptible to disease. In turn, disease depresses appetite, inhibits the absorption of nutrients in food, and competes for a child’s energy. Dietary intake must be adequate in quantity and in quality, and nutrients must be consumed in appropriate combinations for the human body to be able to absorb them. The immediate determinants of child nutritional status are, in turn, influenced by three underlying determinants manifesting themselves at the household level (IFPRI, 2000).

Figure 1: Conceptual framework (Source: IFPRI, 2000)

2.3.2 Underlying Causes There are three factors influencing the immediate cause. These are food security, adequate care for mothers and children, and a proper health environment, including access to health services. Associated with each is a set of resources necessary for their achievement (IFPRI, 2000).

Food Security which is the first determinant component of underlying causes, is achieved when a person has access to enough food to lead an active and healthy life (IFPRI, 2000). The conditions necessary for gaining access to food are food production, income for food purchases, or in-kind transfers of food (whether from other private citizens, national or foreign governments, or international institutions).

Care is the second determinant component of underlying causes. No matter how much food is available, no child grows without nurturing from other human beings. This aspect of child nutrition is captured in the concept of care for children and their mothers, who gave birth to the children and who are commonly their main caretakers after they are born. Care is the provision by households and communities of “time, attention, and support to meet the physical, mental, and social needs of the growing child and other house hold members”. Examples of caring practices are child feeding, health-seeking behaviors, support and cognitive stimulation for children, and care and support for mothers during pregnancy and lactation. The adequacy of such care is determined by the caretaker’s control of economic resources, autonomy in decision making, and physical and mental status. All of these conditions of care are influenced by the caretaker’s status relative to other household members. A final resource for care is the caretaker’s knowledge and beliefs. Likewise, the educational status of women has been shown to have a great impact on children’s growth in Ethiopia: women who have more formal schooling are more likely to have better nourished children (CSA and ORC Macro, 2001, as cited in DPPC, 2002).

Health Environment and Services is the third underlying determinants component of child nutritional status. Health environment and services, rests on the availability of safe water, sanitation, health care, crowded household with many young children, unhygienic food preparation, hot and dusty dry season and environmental safety, including shelter (DPPC, 2002).

As indicated on the conceptual framework, a key factor affecting all underlying determinants is poverty. A person is considered to be in absolute poverty when he or she is unable to satisfy adequately his or her basic needs—such as food, health, water, shelter, primary education, and community participation. Poor households and individuals are unable to achieve food security, have inadequate resources for care, and are not able to utilize (or contribute to the creation of) resources for health on a sustainable basis. Finally, the underlying determinants of child nutrition (and poverty) are, in turn, influenced by basic determinants (IFPRI, 2000).

2.3.3 Basic Determinants It includes the potential resources available to a country or community, which are limited by the natural environment, access to technology, and the quality of human resources. Political, economic, cultural, and social factors affect the utilization of these potential resources and how they are translated into resources for food security, care, and health environments and services (IFPRI, 2000).

2.4 Literature gap

Research and different assessment works produced in country and outside the country were referred and some of their data used as comparison. But to get a closer look and comparison of the study area assessments or research works done in the woreda are needed. The researcher tried to assess concerned offices and was unable to get and refer for detail information. Most of the literature was accessed from internet and United Nations websites working on nutrition. Majority of them were focused on other woredas that were not in the same neighborhood and livelihood of the woreda I have conducted the research in. Hence, I faced challenge to get previous result to compare how the nutrition situation is going in the woreda.

CHAPTER THREE BACKGROUND OF THE STUDY AREA AND THE RESEARCH METHOD

3.1 Description of the study area

3.1.1 Location and Biophysical setups Arsi Negele Woreda is one of the ten woredas in West Arsi zone. It was bordered by Adami Tulu Jido Kombolcha Woreda and Lake Langano at the Northern side, Shalla Woreda and Lake Shalla at the Western side, Shashemene Woreda at the Southern side and Arsi zone at the Eastern side. The Woreda has a total area of 183,800 hectars out of which 44,000 hectars was covered by water body. It is found about 220 kms to the South of Addis Abeba on the main asphalt highway to Hawasa. It is located between 7008’-7044’N latitude and 38025’-38057’E longitude. Crater lakes Shala and Abjata border it at North-Western side and Lake Langano borders it at Northern side (DPPO, 2015).

Arsi Negele Woreda receives bimodal rainfall, the main one being that covers large part and occurs during June to September. The second and smaller rainfall occurs during March and April. Part of the Woreda which is above 2000 meters above sea level have fair annual rainfall ranging 900-1300mm while the vast area which is below 2000 meters above sea level have smaller average annual rainfall of 500- 900mm. Ingeneral in recent years the rainfall in the Woreda was becoming unreliable in terms of amount, time and distribution which is affecting the crop production. The Woreda has an almost flat terrain and the whole Woreda drains in to Shala, Abjata, and Langano lakes. A vast area of the Woreda is found in the Great Rift Valley and thus known by its acacia tree (DPPO, 2015).

Total land area of the Woreda is divided in to three agro-climatic zones namely Dega (10%) which is about 2000-2300 meters above sea level, Woina Dega (75%) which is about 1600-2000 meters above sea level, and Kola (15%) which is about 1500-1600 meters above sea level. It has lower and upper average temperature of 10-170C, 14- 210C and 18-260C for Dega, Woina Dega and Kola respectively (DPPO, 2015).

3.1.2 Demographic profile According to the June 2015 Arsi Negele Woreda profile, the Woreda comprises a rural population composed of 140,552 male and 155,120 female totaling 295,672 and urban population comprised of 39,000 male and 33,000 female totaling 72,000 which gives a sex ratio of 110 female per 100 male in rural area and 85 female per 100 male in urban area (DPPO, 2015).

The majority of the people living in the Woreda belongs to the Oromo ethnic group and almost all speak Afan Oromo. Regarding religion, the majority of the people living in the study area which is more than 84% follow Islam while 15.5% were Christians (DPPO, 2015).

3.1.3 Socioeconomic setups According to 2015 Woreda profile, about 65% of the Woreda people was served with potable pipe water. There is atleast one health post and one elementary school in each rural Kebele. Each rural Kebele was well connected using gravel roads and the main asphalt road to Hawasa cross the Woreda dividing it in to two (DPPO, 2015).

Almost all the Woreda population livelihood is based on agriculture. The major agricultural products are wheat, maize, potato, tomato, teff, and red pepper. The Woreda capital, which shares the same name with the Woreda, Arsi Negele is famous by its local alcohol distillation (DPPO, 2015).

Figure 2. Arsi Negele Woreda map in its regional and country setting 2016 (source: CSA 2007, MoW and ERA 2010)

3.2 Methods and Materials

3.2.1 Study design According to the Disaster Prevention and Preparedness Commission-Emergency Nutrition Assessment guideline (2002), cross-sectional data are used to describe the nutritional situation of a population at a given place and time. Thus, this study utilizes a cross-sectional survey applying structured questionnaires and anthropometric measurements. The study covered the three sampled rural Kebeles namely Gambelto, Ali Weyo and Gale-Kelo in Arsi Negele Woreda, West Arsi zone, Oromia Regional State.

3.2.2 Study population The study population were all children in the age group 6 to 59 months in the three selected rural Kebeles. All children of the target age group available and resided in the area were included. A child is excluded only if he/she cann’t be available during the entire survey time.

3.2.3 Sources and types of data A. Household Survey

A structured questionnaire was prepared using English language. This questionnaire was translated to the local language (Afan Oromo) for better communication and data retrieval. During the household survey an anthropometric measurement was made to the target children. Three enumerators, six assistant enumerators and a supervisor were recruited, who were selected based on their education status (12 grade complete) and deployed.

These enumerators were trained on key survey issues before their deployment. The training took 5 days and the training comprises the objective of the research, content of the questionnaire, on how to conduct the interview to complete the questionnaire and how to conduct anthropometric measurements (weight, height and MUAC).

B. Key Informant Interview (KII)

The key informant’s interview was prepared to obtain information on community knowledge and experience. A standard interview guide prepared and implemented. The guide was prepared in English and later translated in to Afan Oromo. Overall monitoring and care was given on the facilitation and handling of the interview by the

17 researcher. The interviewee comprises people having particular insight about the topic under discussion and the study area. This includes experts from health (one from Community Health and Nutrition Section); Disaster Prevention and Preparedness offices (one from Early Warning and Response Section); one health extension worker from each sample Kebeles, one Volunteer Community Health Worker (VCHW) from each sample Kebele and one each from two NGOs (International Medical Corpus (IMC), Bole Bible Baptist Church (BBBC), Society of International Missionary (SIM), etc.) working on nutrition. These participants were selected through discussion with sample Kebele chair persons and Woreda sector office heads. They were asked about their practice and opinion on family feeding, food habits of the area, food taboos, child rearing, breast feeding, complementary feeding, timing & frequency of child feeding, weaning age, etc.

C. Secondary Data

The researcher reviewed pre-harvest and post-harvest assessment reports, nutritional assessment reports, quarterly & monthly screening data from health office and quarter early warning reports from DPP offices at Woreda, Zone & Region and UNWFP & UNICEF recent nutrition related reports of 2015. Population and socioeconomic data were referred from Disaster Prevention and Preparedness (DPP) office annual profile report. Different health and nutrition data collected and printed were also the main focus to the researcher.

3.2.4 Tools of data collection The data collection tools applied for this research include structured questionnaire which was prepared to collect the bulk quantitative and qualitative data for this research. A questionnaire guide prepared for the enumerators which supported to the quality and consistent data collection.

Middle Upper Arm Circumference (MUAC), a tool used to collect the thinness of the child has also been implemented. Based on UNICEF cut-off points three categories of measurements were identified for children. The MUAC measurements which are equal or above 12 cms were considered as a well nourished child. A MUAC measurement equal or above 10 cms and below 12 cms were considered as moderately malnourished. MUAC measurements below 10 cms were considered as severly malnourished.

Nutritional surveys usually upply two types weighting tools which were utilized based on their age. Accordingly, Salter hanging scale (for children below 24 months) and Basin scale (for children above 24 months) were those commonly applied to measure the weight of the target children. The weight measure obtained was compared with the international standard weight data for similar age and sex child (z-score) to determine the nutritional status of the child.

Length/height measuring boards (for children below/above 2 years respectively) were also used to obtain length/height of the child. This measuring board was called length measuring board when we measure the length of children below the age of two years who can’t stand up straight. When the children pass the age of two they can stand straight up with little support and hence we use height measuring board. Again these length/height data was compared with the international standard length/height data for similar age and sex child (z-score) to determine the nutritional status of the child as detailed under data analysis.

3.2.5 Study variables Dependent variable Independent variables

 Malnutrition (PEM)  Demographic factors (age, sex, HH size…)

 Stunting  Socio cultural factors (education, …)

 Wasting  Economic factors (income, house type, …)

 Underweight  Maternal factors (ANC, birth control, …)

 Child factors (immunization, sickiness, …)

 Water and sanitation factors (water source, laterine, …)

 Behavioral factors (breastfeeding, waning, …)

3.2.6 Sample size determination and sampling techniques The specific study sites and the size of respondents was determined using stratified multistage sampling design. The Woreda has 48 rural Kebeles and as stated under the Biophysical setups, is divided into three agro-climatic zones. Three Kebeles (Gale and Kelo, Ali Weyo and Gambelto) were purposely selected one from each agro-climatic zones, Kola, Woina Dega and Dega respectively. This was decided due to its vast area which has cost and time implication. On the other hand, similarity of the livelihood

19 activities, identical nature of physical as well as social setup of the community, similar landscape, culture, religion and language ease the issue on the selection.

During a visit to the kebeles it was observed that the population registered was not accurate as expected and the study was implemented in three sample rural Kebeles. Thus, in such cases it was recommended to use the two-stages, cluster sampling. First, to make the sample data more representative and then existing clusters were registered. These three sample Kebeles have three clusters/Gots each. On the second stage, the calculated sample size was proportionaly assigned to these clusters. The formula commonly used to calculate sample size for such cluster sampling is as indicated under equation 1 below.

Equation 1:

(1 − ) =

Where n = sample size.

t2 = abscissa of the normal curve (commonly obtained in statistical tables as 1.96) which is linked to the standard error.

e = desired level of precision (+3%).

p = expected prevalence of malnutrition from previous survey (7%).

K = design factor which is used when we apply cluster sampling.

Then n = 2[(1.96)2 x 0.07 x 0.93]/ (0.03)2 = 556 children

After the sample size needed was determined, proportional number of sample under- five children were assigned to each cluster based on their population size. Accordingly, the sample children in each cluster were calculated and detailed as depicted in table 1 below.

Table 1: Proportion of sample allocated to each cluster

Geographic Total Estimated children Proportional No units (clusters) population 6-59 months sample allocated 1 Adansho 1650 248 45 2 Omba & Shondi 2540 381 69 3 Awade Soko 2555 383 70 4 Wachota 3826 574 105 5 Kiltota 2944 442 81 6 Ali 3604 541 99 7 Kune 1096 164 30 8 Hateta 942 141 26 9 Kelo Chancho 1176 176 32 Total 20333 3050 556 Source: Household survey of the study area (April, 2015).

Again after the sample size was assigned to each cluster, each enumeration team was made move to the center of its respective randomly selected cluster. The teams choose a direction by spinning a pencil/pen and counted the number of houses available in the selected direction. Each team selected the first house to be visited using random number method. In each household all under-five children were measured. The next visited households were choosen by proximity and always to the right direction until the required number of children were measured. All the team were advised to continue to the next household if they don’t encounter under-five child and revisit the house if the under-five child is abscent at the visiting time.

3.2.7 Method of Data Analysis Growth assessment is the single measurement that best defines the health and nutritional status of children, because disturbances in health and nutrition, regardless of their origin, invariably affect child growth. It also provides an indirect measurement of the quality of life in an entire population (DPPC, 2002). The major quantitative data expected from household survey comes as a result of anthropometric measurements. This anthropometric information can be used, as explained above, to determine an individual’s nutritional status by comparing it with an internationally accepted reference mean, using software for a bulk data. Hence, in this study anthropometric data is used to determine the prevalence of malnutrition in the surveyed population. The basic information and measurements that constitute anthropometric measurements of the children are: age, sex, length/height, weight and oedema (WFP, 2005).

These anthropometric indicators in surveys are calculated and expressed in terms of standard deviations, or Z-scores. The Z-score is recommended, particularly for surveys of nutritional status assessments (Young et al., 2004). Z-score is the difference between the measured value of an individual and the median value of the reference population for the same age or height, divided by the standard deviation of the reference population as indicated below (WFP, 2005).

Equation 2:

ℎ − ℎ − =

To define nutritional status of a population based on this anthropometric indices, standard cutoff values stated under table 1 bellow are used.

Table 2: Classification of malnutrition for weight-for-height, height-for-age, and weight-for-age based on Z-score.

Classification Z-score value Adequate -2 < Z-score < +2 Moderately malnourished -3 < Z-score < -2 Severely malnourished Z-score < -3 Source: Guideline on Emergency Nutrition Assessment (DPPC, 2002).

After the individual persons nutritional status is obtained, using the above cutoff point, the prevalence of malnutrition of a population is calculated as equal to the number of malnourished children divided by all children assessed in the population.

To identify the relation of socioeconomic factors, questionnaire referring about household income, education status, land ownership, possession of livestock, feeding habits, health situations, housing conditions, and major household utilities have been included. Binary Logistic regression is applied to assess factors associated with malnutrition. Before applying this model multicollinearity and outliers’ checked and encountered no collinearity. The quantitative data collected through household survey fed to computer software SPSS V20 and also SMART Nutrisurvey software which is recommended for Nutrition Surveys by DPPC.

3.2.8 Regression The quantitative data was obtained from household questionnaire and Anthropometric measurements. This quantitative data collected through the above two methods was analysed using Emergency Nutrition Assessment (ENA) for SMART 2011 and Statistical Package for Social Science (SPSS) version 20 softwares. Following data entry, data editing and cleaning were done using frequency and crosstabulation. In preparation for final analysis using Binary Logistic Regression, the data was tested for multicollinearity and outliers. A strong relation among independent variables is not required in this analysis and thus a multicollinearity test has been done. Accordingly no strong relation was observed among Independent Variables. The other important check done was for the outliers. This case is identified by using or inspecting the values of residuals. Finally, after these primary checks Binary Logistic Regression has been used to assess the association of independent variables with dependent variable.

CHAPTER FOUR RESULTS AND DISCUSSION

4.1 Demographic and parental characteristics

A total of 556 targeted children’s data was gathered out of which 281 (50.54%) are boys and 275 (49.46%) are girls. From the total children 259 (46.6%) are from Gambelto kebele, 219 (39.4%) are from Ali Weyo kebele and 77 (14%) are from Gale & Kelo kebele. 536 (96.9%) of these children came from married and in union family. With this survey to reach the targeted respondents a total of 380 households were visited.

From the total respondent mothers or caretakers 305 (55%) which is below the national average 58% (EDHS, 2011) were illiterate. Out of the total respondents 552 (99.5%) children are from the Oromo ethnic society. The dominant religion is Muslim which registered 469 (84.4%) of the respondents followed by 86 (15.5%) from Christian religion. About 517 (93.3%) of the respondents family heads and 522 (94.4%) of respondents mothers’ occupation was farming.

When the respondents household size is seen, 200 (36%) of the respondents came from family with household size of less than 5 and 325 (58.5%) of the respondents came from family with household size of 6-10 while only 31 (5.5%) of the respondents came from family with household size greater than 11. An increased number of malnourished children were registered under household size of six to ten. This situation is more pronounced as the household size reaches its highest figure namely above 11.

Nearly half of the respondents 255 (45.9%) have a house with corrugated iron sheet roof. From the respondents 535 (97.6%) houses floor was soil/earth while 263 (54.5%) of the respondent’s family share a single room and 187 (38.7%) of them have two rooms. A little more than half or 262 (55.4%) of the respondents houses have separate kitchen. Though the rooms of most of the households is limitted to one or two 97 (23.7%) of the respondents share their room with livestock they have.

Table 3: Demographic and parent related characteristics of the sample respondents.

No Characteristics Number % 1 Children age by months - 6-17 132 23.7 - 18-29 140 25.2 - 30-41 132 23.7 - 42-53 146 26.3 - 54-59 6 1.1 2 Marital status of the children parents - Married and in union 536 96.9 - Married & not in union 9 1.6 - Widow 6 1.1 - Separated 2 0.4 3 Number of children under 5 years of age who came from a family with: - One child 148 26.6 - Two children 287 51.6 - Three >> 120 21.6 - Four >> 1 0.2 4 Education level of mother or caretaker - Illiterate 305 55.0 - Read and write 77 13.9 - Formal education 173 31.2 5 Childrens ethnic origin - Oromo 552 99.4 - Amhara 1 0.2 - Others 2 0.4 6 Respondents Religion - Muslim 469 84.4 - Christian 86 15.5 - Others 1 0.2 7 Number of children from household size: - Less than five 200 36.0 - Six to ten 325 58.4 - Greater than eleven 31 5.6 Source: Household survey of the sampled area (April 2015)

4.2 Socio economic characteristics

From the total, 525 (94.4%) caretakers/respondents own a farm land. Data collected for income depicts that the majority which is 495 (89.4%) of the respondents live on agriculture, 30 (5.4%) on daily wage and 16 (2.9%) on monthly salary. The monthly average income of the study site reveals that 428 (65.6%) of the families get an estimated monthly income of more than 150 Birr. From these six categories the bigest

25 respondents’ figure which is 165 (29.7%) is in the category of average monthly income above 500 birr.

Maize, teff and wheat are the staple food of 437 (78.7%), 75 (13.5%) and 36 (6.5%) respondents respectively. Out of the study children families 527 (94.8%) get their food from own production. It is known that these days nutrition messages, maternal and child health issues are transmitted by government media but 376 (67.9%) and 517 (94.2%) of the respondents do not have radio and television respectively. This data indicates that a bulk of the study community doesn’t have information which has a significant impact on its health environment in general and its livelyhood in particular.

Table 4: Socioeconomic characteristics of the sample respondents.

No Characteristics Number % 1 Ownership of farm land by respondents - Yes 525 94.4 - Missing 31 5.6 2 Source of income by caretakers - Salary 16 2.9 - Daily wage 30 5.4 - House rent 2 0.4 - Land rent 7 1.3 - Livestock and crop production 495 89.3 - Gift 4 0.7 3 Means of access to food by caretakers - Production 527 94.8 - Bought from market 27 4.8 - Donated 2 0.4 4 Estimated monthly income of caretakers - Less than 50 Birr 64 11.5 - Between 50 & 149 Birr 63 11.4 - Between 150 & 249 Birr 104 18.7 - Between 250 & 349 Birr 79 14.2 - Between 350 & 449 Birr 80 14.4 - Above 500 Birr 165 29.7 Source: Household survey of the sampled area (April 2015).

4.3 Maternal and child health related characteristics

Out of the total respondent mothers or caretakers, for 267 (48%) the age of their first marriage was below 18 years and 105 (39%) of these mothers were still below 18 years at their first delivery. The number of these mothers is very high when compared

26 with the national average 22% as described on ECSA 2011, which indicates an alarming result for Arsi Negele. When the median of the age of women at first marriage which is 18 years in this study is compared with the national level, it shows an increased magnitude or better than the country’s figure, 16.5 years as described on ECSA 2011. This age of marriage and delivery after 18 years is assumed appropriate for child and maternal health. This fact should be well addressed by government through the Health Extension Program (HEP).

Having a planned number of children in a family mostly have effect on the food security situation and hence on nutritional status of the household. The data shown on table 4 indicates that 216 (38.9%) of the mothers or caretakers have got the chance to use different types of birth control services which shows an increased result compared to 29% of the national average as indicated on ECSA 2011. When discussing use of birth control, this survey and ECSA 2011 refer to the use of all means of contraceptives. The main concern according to the information obtained from key informants is discontinuation of the family planning follow up process. As also discussed in the demographic and health survey there is a 37% discontinuation rate.

A pregnant mother who regularly check up here health status (receive Anti Natal Care) secure health of here child and hereself. It is a very crucial component of most countries health program. On table 5 below, 524 (94.6%) mothers or caretakers of the study area attended Anti Natal Care (ANC) during their pregnancy. Out of these mothers 19.9% attended less than 3 times and 327 (74%) attended 3-6 times per their pregnancy. At country level 88 (43%) of mothers attend at least once while 19% mothers attend about 4 times during their pregnancy (ECSA, 2011). This improved result could be due to health structure development in the area of the study.

Delivery with the support of appropriate health proffetional was the other important child health factor. It avoides an expected complexities and immediate response provided. In this study out of the whole caretakers/respondents only 213 (38.3%) delivered at health facility. This result shows a better and significant difference when compared with the national figure which states for mothers whose delivery was supported by skilled health personnel is only 10% (ECSA, 2011). One of the factors under study was number of pregnancy one mother or care taker have. The data obtained by this survey reveals a very wide range, which varies from 1 to 12. It

27 depicts an increasing tendency as the number of pregnancy increases up to 3 and then after it goes on decreasing.

Regarding the mothers or caretakers age of delivery, 105 (18.9%) of the respondents gave birth between the age of 14-17 while 316 (56.8%) of them delivered between the age of 18-20 years. The median of first delivery shows 19 years while the national median is 16.5 years (ECSA, 2011). Both age at first marriage and at first delivery, on this study, have no significant association with cases of malnutrition. But these practices will have adverse effect on the health of child and mother and this early startup also facilitates for an increased number of family size unless corrected with appropriate action.

As indicated in Table 5, 552 (99.5%) of the respondents family use drinking water from pipe. This data reflects a better situation when seen with the national data 34% improved water service (ECSA, 2011). About 481 (86.7%) of the respondents use latrine [both 118 (21.3%) VIP and 363 (65.4%) pit] and on the otherhand, 384 (69.2%) of the respondents use open field for their refuse or waste disposal. This data indicates that there is high risk to children health which is an immediate cause to under-five child malnutrition.

Out of the total target children, 450 (82%) were fully vaccinated and 76 (17.7%) were partially vaccinated. Though statistically has no significant association with malnutrition cases, this data shows an impressive output when compared with national figure of 24% for fully vaccinated rural children. From the total, 500 (91.2%) children received Vitamin A supplement and deworming tablets.

From the target children 449 (82.2%) grew up feeding breast milk and 20 (4.4%) of these children were made to quite feeding breast milk before their 6th month due to different reasons. It is a concerning issue because it makes these children vulnerable to malnutrition. Breastfeeding status at national level was stated as 52% (ECSA, 2011).

A child is exclusively fed breast milk up to 6th month after which must start supplementary food. Late and inappropriate nutrition intervention leads to malnutrition. More specifically, inadiquate nutrition in the first two or three years of the child leads to stunted to life (DPPC, 2002). As presented in Table 5, 498 (91.9%) of the total children started supplementary food immediately after 6th month of their

28 age which shows a good trend. According to the responding mothers the first supplementary food given was sequentially soup 291 (53.6%), pourage 122 (22.5%) and milk 102 (18.8%). The frequency of feeding less than three times was about 22.2% (119) and 3-4 times reported to be 65.8% (352). Though the data obtained shows a better performance, statistical analysis shows no significant association with malnutrition cases. Practically, this frequency of feeding is a crucial issue where action should be taken if the nutritional status of children should be improved. It has its own minimum standard and Ethiopians fulfilling the minimum meal frequency are only 49% (UNICEF, 2011).

The data obtained on recent child health status shows that, out of the children who were sick in the preceding week to the survey, 179 (77.5%) of respondent’s children refused to be fed, 20 (8.7%) encountered difficulty to swallow and 11 (4.8%) were with cough and difficulty to breath. The remaining 21 (9%) children were with fever, diarrhea, vomiting, etc. Such children are mostly vulnerable to malnutrition unless closely followed and cured.

4.4 Nutritional status and its determinants

The prevalence of stunting (shortness for his/her age) in the surveyed area shows 57.9%, moderate stunting 14.6% and sever stunting 43.3%. The statistical analysis of the nutritional condition as measured by stunting was strongly associated with household size with P = 0.041 (OR 0.409 (0.174, 0.965)), child age P = 0.000 (OR 0.967 (0.954, 0.981)) and monthly income P = 0.014. Though monthly income shows P-value less than 0.05 it is not supported by odds ratio. In the crosstabulated data of monthly income, it shows a decreasing tendency as the monthly income increases. This type of malnutrition results due to long time effect and mostly prevails as a result of poor supplementation, improper breastfeeding, different types of disease, etc. The survey data reveals that an increase of mothers educational status results in decrease in the status of stunted but statistically no significant association.

The secondary data obtained from UNICEF, 2011 explains that boys are more prevalent (61.2%) than girls (54.5%). The survey result of this study also registered the highest prevalence of male children as 56% compared to 52.6% for female children. With regard to the stunted prevalence, similar study like the one conducted in Adami Tulu Jido Kombolcha Woreda shows stunted children of 52.3% which

29 shows better outcome (Abera, 1996). There is also a significantt increase when compared with national average which is 46% for rural area (ECSA, 2011). This increase of stunted cases in this study might be due to last year production decrease and the timing of the survey which is close to food shortage season.

The prevalence of acute malnutrition in the study area shows 18.4% for Global Acute Malnutrition (GAM), 8.2% for Moderate Acute Malnutrition (MAM) and 10.2% for Sever Acute Malnutrition (SAM). Similar study conducted in Gumbrit of North West Ethiopia indicates wasted prevalence of 17.7%. Both results were high compared to the national average which is 10% and the Sub-Saharan average which is 9% (ECSA, 2011). This could be again due to the survey time, as April and May were time for the start of hunger season in most of the countries rural community. In addition, the information obtained from key informant’s interview shows that there was a decreased production on the main production season of last year. The measurement of acute malnutrition done using Middle Upper Arm Circumference (MUAC) also shows 14.6% confirming its high prevalence. The statistical analysis of the nutritional condition as measured by wasted was associated with child age P = 0.032 (OR 1.019 (1.002, 1.037)) and child sex P = 0.036 (OR 1.645 (1.032, 2.622)). In this survey data an increase in frequency of feeding, immunization status and monthly income the status of wasting decreases though the statistical analysis revealed that there is no association.

Similarly, the weight-for-age data collected to indicate the prevalence of underweight shows 35.1%, moderate underweight 15.5% and sever underweight 19.6%. Similar study like the one conducted in Adami Tulu Jido Kombolcha Woreda shows underweight status of 49.5% showing very high or an increased prevalence. On the other hand the average underweight prevalence of Sub-Saharan countries is 21% showing us that we remain a long way back. A small increase is also observed when compared to the national average which is 30%. The statistical analysis of nutritional condition as measured by underweight was associated with mothers education status P = 0.014 (OR 0.568 (0.363, 0.890)), monthly income of the household P = 0.042 (OR 2.121 (1.029, 4.372)) and utilization of birth control P = 0.040 (OR 1.498 (1.019, 2.202)). Underweight (less weight for age) is a composite index of stunting and wasting. A child can be underweight for his/her age because he/she is stunted, wasted, or both. Thus, it is taken as an overall indicator of a population’s nutritional health

(ECSA, 2011). Thus, the study figure reveals that there is a significant malnutrition case in the study Woreda. For all cases there is no oedema observed.

Table 5: Child health related characteristics of sampled respondents.

No Characteristics Number % 1 Age of mother at first marriage - 11-17 years 267 48.0 - 18-28 >> 289 52.0 2 Age of mother at her first delivery - 14-17 years 105 18.9 - 18-29 >> 451 81.1 3 Use of birth control by caretakers - Yes 216 38.9 - No 339 61.1 4 Attendance of Anti Natal Care by mothers - Yes 524 94.6 - No 30 5.4 5 Place of child delivery - Health facility 213 38.3 - With Traditional Birth Attendants (TBA) 11 2.0 - At their house 332 59.7 6 Mothers working outside home - Yes 136 24.5 - No 418 75.5 7 Source of drinking water by caretakers - Pipe 552 99.4 - Protected well 1 0.2 - Unprotected well 2 0.4 8 Existence of latrine by respondents - Yes 481 86.7 - No 74 13.3 9 Place of refuse disposal by respondents - Pit 171 30.8 - Open field 384 69.2 10 Immunization status of children - Not vaccinated 21 3.8 - Partially vaccinated 76 13.8 - Fully vaccinated 450 82.0 - Do not know 2 0.4 11 Delivery of vitamin A & deworming tablets - Yes 500 91.2 - No 48 8.8 12 Breast feeding of the child - Yes 449 82.2 - No 97 17.8

No Characteristics Number % 13 Length of time the child breast fed in months - < 6 months 20 4.4 - 6-12 months 62 13.7 - 1-2 years 287 63.6 - More than 2 years 64 14.2 - Do not know 18 4.0 14 Age of starting supplementary food - Before 6 months 25 4.6 - Immediately after 6 months 498 91.9 - 6-12 months 14 2.6 - After 12 months 5 0.9 Source: Household survey of study area (April, 2015).

Table 6: Nutritional status of sample children distributed by age group based on weight-for-height, weight-for-age and height-for-age.

Wasting Underweight Stunting Age Number < -2 z-score < -2 z-score < -2 z-score Oedema (months) No % No % No % 6-17 132 18 13.6 44 33.3 93 70.5 0 18-29 140 22 15.9 47 33.6 96 68.6 0 30-41 132 24 18.6 50 37.9 74 56.1 0 42-53 146 36 24.6 52 35.6 56 38.4 0 54-59 6 1 16.7 2 33.4 3 50.0 0 Total 556 101 18.4 195 35.1 322 57.9 Source: Household survey of the sample area (April, 2015)

Table 7: Prevalence of malnutrition by sex of the sample children

Prevalence of malnutrition Boys Girls All N=281 N=275 N=556 Wasting (<-2 z-score) (WHZ) (49) 17.5% (52) 19.2% (101) 18.3% Underweight (<-2 z-score) (WAZ) (94) 33.5% (101) 36.7% (195) 35.1% Stunting (<-2 z-score) (HAZ) (172) 61.2% (150) 54.5% (322) 57.9% Source: Household survey in sampled area (April, 2015)

Note: - Prevalence of oedema = 0 - C.I. = 95% - All the three classifications were calculated separatly by the SMART software and hence adding down wards may missleads.

Table 8: Statistical analyses showing the influence of selected variables on malnutrition as measured by stunted, April 2015. n=556

95% C.I. Variables No Yes OR Lower Upper Household size 254 302 0.409 0.174 0.965* Use of birth control 254 301 1.286 0.878 1.886 Attendance of ANC 253 301 1.048 0.430 2.551 Mother's working condition out side the house 252 302 0.774 0.487 1.229 Child age 254 302 0.967 0.954 0.981* Existance of laterine 254 302 0.999 0.541 1.844 * shows significant association Source: Household survey of sampled area (April 2015)

Table 9: Statistical analyses showing the influence of selected variables on malnutrition as measured by underweight, n=556

95% C.I. Variables No Yes OR Lower Upper Education level of mother 325 230 0.568 0.363 0.890* Monthly income status 325 230 2.121 1.029 4.372* Use of birth control 326 229 1.498 1.019 2.202* Child age 326 230 1.002 0.988 1.016 Existance of laterine 325 230 0.796 0.435 1.456 * shows significant association Source: Household survey of sampled area (April 2015)

Table 10: Statistical analyses showing the influence of selected variables on malnutrition as measured by wasted, n=556

95% C.I. Variables No Yes OR Lower Upper Use of birth control 450 105 1.065 0.659 1.721 Mother's working condition out side the house 449 105 1.359 0.748 2.470 Child age 451 105 1.019 1.002 1.037* Child sex 451 105 1.645 1.032 2.622* Existance of laterine 450 105 1.016 0.482 2.143 * shows significant association Source: Household survey of sampled area (April 2015)

CHAPTER FIVE CONCLUSION AND RECOMMENDATIONS

5.1 Conclusion

The findings of this study indicate that the magnitude of malnutrition in the study population is high. Child hood malnutrition is among the main public health problems and it affects survival of individuals and development of the family, society and the nation. Despite all the efforts being made by the country to overcome the problem, malnutrition is still persisting and in some cases, like the one in this study, shows a significant increment. Stunted child exibit the result of a long time nutritional effect. This survey data reflects a high prevalence of 57.9% which is very high compared to the national figure. Similar assessments done in Borena (Mekonnin W/Yesus, 2011) presented 52.30% which is lower from this study area. Again a similar assessment conducted in Botswana presented a stunted result of 38.70% (Mahgoub et al, 2006) which is even lower than the national average of 46% (ECSA, 2011). As indicated by the analysis, as the household size increases the magnitude of the stunted nutritional status increases showing a positive relation. The statistical analysis indicates that household size has strong association. An increase in the size of the household which leads to decrease of the size of the shared food. The quality of care for under-five children also continues on decreasing and both affect the nutritional and health status of the children. The other associated factor child age increase, resulted in decrease in stunted nutritional status. The statistical analysis reported the existance of a strong association. This study and other similar assessments like the one done in Borena explain that stunting affects more male children than female and older children are affected least. Though the other factors like mother’s education status, frequency of feeding, type of staple food, etc data shows their influence on the nutritional status of the children, the statistical analysis reveals no association. The prevalence of underweight which is 35.10% was the next higher malnutrition status in the study area. Similar studies in the country in Borena obtained underweight of 49.50% and in Adami Tulu underweight of 43.3% (Abera, 1996). This shows that there is a better status in the study area. A similar nutritional assessment conducted in Botswana got underweight nutritional status of 15.60% which is by far lower than the

34 situation in this country (Mahoub et al, 2006). When the associated factors are looked, an increase in mother’s education level decreases the rate of underweight nutritional status. In similar way as the number of mothers utilizing birth control increases the underweight nutritional status decreases. Monthly income is the third factor showed a significant association. There are also other factors like immunization status, availability of laterine and attendance of ANC whose data shows their influence either positively or negetively but the statistical analysis reported no association. Wasted (measured by weight-for-height) is another indicator of nutritional status of under-five children. About 18.30% of the study area children were wasted. Similar assessments done in Adami Tulu showed a wasted nutritional status of 18.10% while that of Borena reported 9.90% which is almost halve of the others. The facters influencing wasted nutritional status were child age and sex. Contrary to stunting an increase in child age increases the status of wasted malnutrition though the increase is not uniform. The statistical analysis depicts that both factors have significant association. There are steal other factors like frequency of feeding, immunization status, monthly income and household size whose data indicates existance of a clear influence but the statistical analysis revealed no significant association. Wasting affects more female children than male. From the factors in this study two of them need attention. The first one is age of mothers at their first merriage. The lowest age at which a mother merried was reported as 11 years which is very low. The result of key informants’ interview indicates that this age of first marriage goes even below the above figure.This activity has its own consequence particularly on maternal health. Thus, there is a need for government intervention in creating awarness and exercise the regulations towards the protection of the right of children. The second facter which still needs attention is age of the mother at first delivery. In this study the data obtained on the age of mothers on their first delivery was 14 years. This factor is highly dependent on the age of this mother’s first marriage. Thus, government intervention is highly needed inorder to improve both situations. In general, as discussed above the prevalence of under-five children malnutrition is found to be high compared to other similar nutrition assessments at different locations and time. The ECSA 2011 can be looked in to so as to compare it to the country malnutrition status which is 46%, 30% and 10% for stunted, underweight and wasted respectively. Using statistical analysis the determining factors were identified. 35

Accordingly, household size, monthly income of the household and child age are found strongly associated with stunted. Mothers’ education status, monthly income of the household and use of birth control are strongly associated with underweight. Additionally, the analysis identifies that child age and child sex are the only factors strongly associated with wasted. Though other factors don’t have association with these malnutrition cases particularly the data of some of the factors shows some influence to the dependent variable. Hence, it is advisable for any intervention in Arsi Negele Woreda to consider these six factors (household size, monthly income, mothers’ education status, use of birth control, child age and sex). With change of time new assessments have to be conducted to get up-to-date information.

5.2 Recommendations

The study was conducted in one of the largest region’s Woreda in Arsi Negele. The woreda is known by its fertile arable land and vegetation cover particularly in its Woina Dega and Dega agro climatic areas. It is also one of the densely populated Woredas. It has a better infrastructure like all-weather road, electric power access, drinking water availability, health facilities, schools, etc. All these are indicators of good opportunity to facilitate social and economic development activities. Having said this, the researcher recommends the following action points. A. There should be a well-coordinated targeted nutrition program in which responsibility, accountability and clear objectives are set. There is a supplementary nutrition program which run in the Woreda since 2012. In its implementation a clear gap between the two main implementing government sectors (Disaster Prevention & Preparedness and health offices) was clearly observed. Thus, this recommendation is forwarded to aware the two sectors and other concerned ones to revisit the activities and drawbacks and devise a well-coordinated and effective program. B. A program that aims to create awareness and empower women to make them decision makers on issues influencing them and their family should be prepared. Almost all respondents don’t know what their husband’s plan, what they have and do not have, they even can’t tell their husband’s age, etc. There is a need to aware or/and educate them. This can be done through creation of adult education type mechanism targeted for women and/or to assess and discuss on how to use the current one-to-five team work, etc. 36

C. To increase the number of women who use contraceptives, the family planning program should be strengthened. There is family planning service in every health facility at this moment. According to the information obtained from Health Extension Workers (HEWs) the service is available, there is no shortage of medicine but only a problem of awareness and decision making. As reported by HEWs most of the women who started contraceptive withdraw. The issue of using contraceptive can’t be easily discussed with their partner. As most of the community members are Islam religion followers, it also have its own pressure according to the key informant’s response. Thus, Woreda health and women’s affairs offices should think of these issues and work in coordination. D. Targeted income generating schemes should be planned and implemented by Disaster Prevention & Preparedness office, Agricultural Development office, NGOs, and other stakeholders. E. Health Posts (HPs) and Health Centers should be strengthened with necessary basic materials and services such as electric power, clean water, refrigerator, living quarter/ rooms for HEWs, etc. and refresher trainings. Finally, since repeated assessments have to be conducted to reach to a better generalization, further investigation on these similar and/or additional factors influencing the increase of malnutrition cases in the Woreda should be conducted.

References

Abera Hunde (1996). Factors Influencing Children’s Nutritional Status in Adami Tulu Woreda. Unpublished master’s thesis, Addis Abeba University, Addis Abeba, Ethiopia. Action Against Hunger International (ACF), (2010). Taking Action: Nutrition for Survival, Growth and Development. London, UK. Arsi Negele Woreda Health Office (ANWHO), (2014). Quarter nutritional screening report. Arsi Negele Woreda Health Office, Arsi Negele, Ethiopia. Belay Zeleke. (2011). The Role of Targeted Supplementary Feeding (TSF) on Child Nutrition under the Age of Five in South Nations and Nationalities People Region: The Case of Mareko Woreda. Unpublished Master’s Thesis, Addis Abeba University, Addis Abeba, Ethiopia. Department for International Development (DFID). (2010). The Neglected Crisis of Undernutrition: DFID’s Strategy. London, UK. Disaster Prevention and Preparedness Commission (DPPC). (2002). Guideline on Emergency Nutrition Assessment. Addis Abeba, Ethiopia. Disaster Prevention and Preparedness Office (DPPO) of Arsi Negele Woreda. (2015). Annual Performance Report. Arsi Negele, Ethiopia. Ethiopian Central Statistical Agency (ECSA). (2012). Ethiopian Demographic and Health Survey. Addis Abeba, Ethiopia Federal Ministry of Health (2008). Program Implementation Manual of National Nutrition Program (NNP)-I July 2008-June 2013. Addis Ababa. Ferew Lemma, Teweldebirhan Daniel, Habtamu Fekadu, & Mates, E. (2012). CMAM Role out in Ethiopia: The ‘way in’ to Scale Up Nutrition. Emergency Nutrition Network, 43, 15-20. Food and Agricultural Organization (FAO) of the United Nations. (1997). Human Nutrition in the Developing World: Food and Nutrition Series. Rome, Italy. Helen Young, Annalies Barrel, Diane Holland, Peter Salama, (2004). Public health in complex emergencies. Lancent 2004, 364: 1899-1909. International Food Policy Research Institute (IFPRI). (2000). Explaining Child Malnutrition in Developing Countries: A Cross-Country Analysis. Washington, D.C.

International Institute for Sustainable Development (IISD). (2014). Summary of the Second International Conference on Nutrition. International Conference on Nutrition Bulletin, 226 number 1, P1-30. Mahgoub, S.E.O., Nnyepi, M., & Bandeke, T. (2006). Factors Affecting Prevalence of Malnutrition Among Children Under Three years of Age in Botswana. African Journal of Food Agriculture, Nutrition and Development (AJFAND), 6 (1), 1-15. Measure DHS-Program. (2001). Nutrition of Young Children and Mother’s in Zimbabwe: African Nutrition Chart books. ORC Macro International Inc., Calverton, Maryland, U.S.A. Medecine Sans Frontieres (MSF). (1995). Nutrition Guidelines. Paris, France. Mekonnin W/Yesus (2011). Household food security, constraints and strategies among Borena pastoral communities of Ethiopia, unpublished master’s thesis, AAU, Addis Abeba, Ethiopia. UNICEF (2009). Tracking progress on child and maternal nutrition. UNICEF, NewYork, USA. UNICEF (2013). Improving child nutrition. UNICEF, NewYork, USA. UNICEF (2013). Some 35m More Child Under Five at Risk if Child Mortality Goal Not Met. Retrieved February 2, 2014, from http://www.unicef.org. United Nations Children’s Fund, World Health Organization, The World Bank. (2012). UNICEF-WHO-World Bank Joint Child Malnutrition Estimate. UNICEF, New York; WHO, Geneva; The World Bank, Washington, DC. United Nations Country Program Ethiopia. (2012). Assessing Progress Towards the Millennium Development Goals. FDRE and UNCT, Addis Abeba, Ethiopia. World Food Program (WFP). (2000). Food and Nutrition Handbook. Rome, Italy. World Food Program (WFP). (2005). A Manual: Measuring and Interpreting Malnutrition and Mortality. Rome, Italy.

Annexes

Annex 1: KII Checklist

Date ______, _2015

Kebele ______

Village/cluster ______

KII number ______

Enumerator Name ______

A. General Information: 1. How many people live in this village? ______2. How many HHs are living in this village? ______3. What is the ecological zoning of the cluster? ______4. Which rains are you dependent on? ______

B. Agriculture, income and market: 5. In a normal year for an average family in this cluster, what are the three main sources of income for HHs? List in order of importance (if possible what proportion?)

1st ______2nd ______3rd ______4th ______5th ______

6. How do HHs obtain most of their food? List in order of importance.

1st ______2nd ______3rd ______7. Has there been a normal harvest this year? ______

8. On average, how many quintals of food are harvested per average HH at a normal time? ______9. If there is a change from a normal year, what are the reasons? ______10. How long does it take to walk from the centre of the cluster to the major market? ______11. Why do you sell green maize? ______12. What foods are available at the local (nearest) market? Select up to 8 main foods.

1. ______2. ______3. ______4. ______5. ______6. ______7. ______8. ______13. What are the trends of food prices at the local (nearest) market? Select up to 8 main foods.

1. ______2. ______3. ______4. ______5. ______6. ______7. ______8. ______14. Do HHs have access to animal health care? ______15. Have livestock been sold during the last six months? ______16. What are the trends for livestock prices at the local (nearest) market? Select up to 4 livestock’s.

1. ______

2. ______

3. ______

4. ______

17. What is the wage level for unskilled casual labour? Select up to 4 types of labour.

1. ______2. ______3. ______4. ______

C. Health

18. Where do most HHs go for health treatment? ______19. How long does it take to walk to the nearest HP/HC? ______Minutes. 20. What are the main diseases affecting the population in the last three months? 1. ______2. ______3. ______4. ______21. What have been the three main shocks that have affected people in the village in the past 2 years? 1. ______2. ______3. ______22. Which population groups face the most problems with access to food and income? ______23. Which food items are avoided from under-five children feeding? ______

24. At what age should a child start complementary feeding? ______25. Up to what age should a child breastfed? ______

26. How do you comment the strength of family planning service? ______27. What is the main source of water for the cluster? ______28. How many under-five children died in this cluster in the last three months? ______29. If there are deaths what were the main causes for these deaths? ______

Annex 2: Questioner

QUESTIONNAIRE FOR NUTRITIONAL ASSESSMENT OF UNDERFIVE CHILDREN IN ARSI NEGELE WOREDA, WEST ARSI ZONE OF OROMIA REGIONAL STATE

Date: Day ______Month ______Year ______

I. Questioner identification number: ______II. House number: ______III. Village/cluster name: ______

IV. Respondent’s availability:

1. First visit □

2. Second Visit □

V. Result:

1. Filled out □

2. Not available □

3. Unwilling □

4. Others, specify ______VI. Interviewee’s name and signature: ______VII. Supervisor’s name and signature: ______

A. Socio Demographic Indicators

1. Number of children 6 to 59 months of age in the household ______

2. Name of head of the household ______age ______

3. Marital status:-

1. Married & in union 2.Married & not in union 3. Single 4.Widow 5. Separated

4. Name of mother ______age ______

5. Education level:-

1. Illiterate 2. Read and write 3. Formal education

Father ______

Mother ______

6. Occupation of father:

1. Farmer 2.Merchant 3. Daily laborer 4. Civil servant 5. Fisher 6. Others ______

7. Occupation of mother:

1. Farmer 2.Merchant 3. Daily laborer 4. Civil servant 5. Fisher 6. Others ______

8. Ethnic and tribal origin:

1. Oromo 2. Amhara 3. Gurage 4. Kembata 5. Hadia 6. Wolita 7. Others ______

9. Religion:

1. Christian (Orthodox--Protestant-- Catholic--) 2. Muslim 3. Other _____

10. How many people currently live in the house (Family size)?

1. Less than 5 2. 6 -10 3. > 11

11. How many of these children are under-five years of age? ______

B. Economic Indicators:

12. Housing condition:

Roof: - 1. Corrugated 2. Thatched

Floor: - 1. Muddy 2. Cemented 3. Tiles 4. Other

Window: - 1. Yes 2. No If yes, how many 1. One 2.≥ two

Room: - 1. One 2. Two 3. Greater than two

Kitchen: - 1. Separate 2. In the living room

Barrack: - 1. Separate 2. In the living room

13. Do you have domestic animal? 1. Yes 2. No

If yes, how many do you have of the following?

Cattle ____ (oxen ____), Sheep ____, Goat ____, Horse ____, Donkey ____, Mule _____, Poultry _____, Others ______

14. Does the household have its own farm land? 1. Yes 2. No

If yes, how many quintals do you harvest in a year on average? ______

15. What are your cash crops?

1. Vegetables ____ 2. Teff ____ 3. Bean ____ 4. Pepper ____ 5. Wheat ____

6. Maize _____ 7. Barley ______8. Others, specify ______

16. What is the source of income of the household?

1. Salary 2. Daily wage 3. House rent 4. Land rent 5. Livestock/crop/ forest product 6. Gift 7. Others, specify ______

17. Estimated monthly income in Birr ______

1. >50 2. 50-149 3. 150-249 4. 250-349 5. 350-449 6. >500

18. What is your staple food?

1. Teff 2. Maize 3. Barley 4.Sorghum 5. Wheat 6. Bean 7. Others

19. How do you get it?

1. Production 2. Bought from market 3. Donated 4. Other, specify _____

20. Do you grow vegetables around the house?

1. Yes 2. No

If no, how often do you buy?

1. Daily 2. Weekly 3. Occasionally

21. How accessible is the market?

1. Half hour walk 2. One hour walk 3.Two hour walk 4. Greater than two hour walk

22. Does the household have radio? 1. Yes 2. No

23. Does the household have TV? 1. Yes 2. No

24. Does the household have means of communication?

1. Telephone 2. Cell phone 3. No

25. Does the household have its own vehicle? 1. Yes 2. No

C. Child health indicators:

26. Age of mother at first marriage ______

27. Age of mother at first delivery ______

28. Number of pregnancies ______

29. Number of children alive: Male ______Female ______

If there is death, specify the cause?

Diarrhea ____, Cough ____, Fever and chills ____, Accidents ____, Others ____

If there is abortion, how many times? ______

30. Have you ever used birth control method?

1. Yes 2.No

If yes, what type?

1. Pills 2. Injection 3. Condom 4. Others

31. Have you attended antenatal care (ANC) during your pregnancies of the index child? 1. Yes 2. No

If yes, how many times? 1. <3 2. 3-6 3. >6

32. Who attended your index child delivery?

1. Health facility 2. Traditional Birth Attendant (TBA) 3. House

33. How many years’ differences are there between the last two of your children?

1. < 24 months 2. 24 – 48 months 3. > 48 months

34. Have you moved from your usual residence in the last one year?

1. Yes 2. No

35. If yes, what is the reason?

1. Famine 2. Clashes between tribes 3. Others, specify ______

36. Do you usually work out-side home?

1. Yes 2.No

37. Have you got enough time to prepare food?

1. Yes 2.No

38. How do you usually prepare food for children under five year of age?

1. Together with adult food 2. Separately for them

39. In which order is food served to the members of the household?

(First = 1, second = 2, all together = 3)

Husband _____, Husband and wife ____, Children ____, Mother and children _____, All together _____.

40. Do you usually take your child to health institution when sick?

1. Yes 2.No

If no, where do you prefer to take? ______

41. Name of the index child: ______, Age ___, Sex __, Birth order ___.

42. General appearance: 1. Normal 2. Deformed

43. Source of water supply:

1. Pipe (Tape) 2. Protected well 3.Unprotected well 4. Spring 5. River 6. Lake 7. Other, specify ______.

44. Do you wash your hand whenever you feed your child?

1. Yes 2. No

45. Do you have a latrine? 1. Yes 2. No

If yes, which type of latrine do you have? 1. Pit 2. VIP

If no, do you use open field? 1. Yes 2. No

46. What do you use for refuse disposal? 1. Pit 2. Open field

47. Immunization status:

1. Not vaccinated 2.Partially vaccinated 3. Fully vaccinated 4. Don’t know

48. Types of vaccine the child received?

1. BCG only

2. BCG, DPT 1 and Polio 1

3. BCG, DPT 2 and Polio 2

4. BCG, DPT 3 and Polio 3

5. BCG, DPT 3, Polio 3 and Measles.

49. If no vaccine, why?

1. Lack of knowledge,

2. Lack of time to the mother,

3. Inaccessibility of service,

4. Unavailability of service,

5. Fear of side effect,

6. Others, specify ______.

50. Did your child receive vitamin A supplement and deworming tablets?

1. Yes 2. No

51. If no, why?

1. Lack of knowledge,

2. Lack of time to the mother,

3. Inaccessibility of service,

4. Unavailability of service,

5. Fear of side effect,

6. Others, specify ______.

52. History of illness in the last one week:-

a. Difficulty to swallow 1. Yes ____ 2. No _____ b. Refuse to feed 1. Yes _____ 2. No ______c. Cough and difficulty in breathing? 1. Yes ______2. No ______d. Fever with rash 1. Yes ______2. No _____ e. Fever with chills 1. Yes _____ 2. No ______f. Worm expelled 1. Yes _____ 2. No ______g. Diarrhea 1.Yes ______2. No ______h. Vomiting 1. Yes _____ 2. No ______i. Diarrhea with vomiting 1. Yes _____ 2. No ______j. Diarrhea With blood 1. Yes ______2. No ______k. Number of liquid stool on worst day: 1. Two ____ 2. Three ____ 3. Four _____ 4. >Four times ______l. Number of vomits on worst day: 1. Two ___, 2. Three ___, 3. Four _____ 4. >Four times _____.

53. Severity of illness:

a. Did the child stay in bed? 1. Yes 2. No If yes, for how long? ______(in days).

b. Did the illness subside by itself? 1. Yes 2. No If no, did you took him/her to health institution? 1. Yes 2. No

54. Have you breastfed the child? 1. Yes 2. No

If yes, when do you first put your index child on breastfeeding?

1. Within the first hour of delivery. 2. Within the first 8 hours of delivery. 3. After 2-3 days. 4. Don’t remember. If no, why don’t breastfed the child?

1. Due to illness. 2. Child refuses to suck. 3. Time constraint of mother. 4. Others, specify ______55. Do the child breast feed now? 1. Yes 2. No

If yes, when is breastfeed given?

1. When the child cry 2. Based on prefixed time 3. Based on mothers feeling 4. Other, specify ______.

56. For how many months did you breastfed your child?

1. Less than six months 2. 6-12 months 3. 1-2 years 4. More than 2 years 5. Don’t know

57. At what age is the child given supplementary feeding?

1. Before 6 months 2. Immediately after 6 months 3. 6 to 12 months 4. After 12 months

58. What was the first supplementary food given to the child?

1. Milk 2. Pourage 3. Soup 4. Adult food 5. Butter 6. Water & sugar 7. Other, specify ______.

59. If not breastfed, at which age discontinued breastfeeding?

1. < 6 months 2. 6 to 9 months 3. 9 to 12 months 4. 12 to 24 months

5. after 24 months.

60. At his age, how frequent should the child eat?

1. Less than 3 times 2. 3-4 times, 3. Greater than 4 times, 4. I don’t know

61. At his age, what type of food or drink is not allowed to be taken by the child?

1. Raw meat 2. Alcohol 3. Coffee 4. Egg 5. Fish 6. Others, specify __

62. Are you feeding your child vegetables?

1. Yes, once a week 2. Yes, less frequently 3. No

63. Are you feeding your child fruits?

1. Yes, once a week 2. Yes, less frequently 3. No

64. What kind of food did you feed your child yesterday?

1. Breast milk only 2. Breast milk and cow’s milk 3. Cow’s milk 4. Cereals and legumes 5. Meat and egg 6. Vegetables 7. Others, specify

65. How frequent do you feed your child the following foods?

Daily, Weekly, Occasionally, Never a. Injera k. Meat wot b. Bread l. Milk c. Kita m. Roasted meat d. Kolo n. Ayib e. Nifro o. Egg f. Genfo p. Butter g. Kinche q. Fish h. Chechebsa r. Oil i. Shiro wot s. Beverage j. Vegetable wot t. Tea

DECLARATION I the undersigned, declare that this thesis is my original work, has not been presented for a degree in any other University and that all sources of material used for the thesis has been duly acknowledged.

Declared by: Confirmed by:

Candidat Advisor