1 DIETARY DIVERSITY, NUTRIENT INTAKE AND NUTRITIONAL STATUS AMONG PREGNANT WOMEN IN LAIKIPIA COUNTY, KENYA KIBOI WILLY KAHANYA (BSc.) H60/27145/2013 A RESEARCH THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE AWARD OF THE DEGREE OF MASTER OF SCIENCE (FOOD, NUTRITION AND DIETETICS) IN THE SCHOOL OF APPLIED HUMAN SCIENCES OF KENYATTA UNIVERSITY JUNE, 2016 ii DECLARATION This thesis is my original work and has not been presented for a degree in any other university or any other award. Signature........................................ Date..................................................... Kiboi Willy Kahanya (BSc) H60/27145/2013 SUPERVISORS: We confirm that the work reported in this thesis was carried out by the candidate under our supervision. Signature................................. Date.................................... Prof. Judith Kimiywe (PhD) Department of Food, Nutrition and Dietetics Kenyatta University Nairobi, Kenya Signature................................. Date.................................... Peter M. Chege (PhD) Department of Food, Nutrition and Dietetics Kenyatta University Nairobi, Kenya iii DEDICATION I am privileged to dedicate this piece of work to my wife Esther, my mum Mrs. Jenifer Wanjiku Kiboi and my late dad Mr. Sammy Kiboi Kahanya for their love, encouragement and unwavering support. iv ACKNOWLEDGEMENT I would like to give all glory to the Almighty God for His mercies and grace which has seen me this far. There are many people to whom I am deeply grateful to. I acknowledge the support of my supervisors, Prof. Judith Kimiywe and Dr. Peter Chege for their sagacious guidance and support throughout the whole research process. I also extend my sincere gratitude to Kenyatta University for giving me an opportunity to pursue a Master of Science in Food, Nutrition and Dietetics. Special thanks to the Medical Superintendent and members of staff of Nanyuki Teaching and Referral Hospital for the support they accorded me during the study period. My appreciation also goes to my research assistants and participants without whom the research could not have succeeded. My heartfelt gratitude’s also extended to my sisters, Jedidah, Phyllis and Ann for their unequivocal support and earnest prayers throughout my studies. God bless you all. v TABLE OF CONTENTS DECLARATION............................................................................................................... ii DEDICATION.................................................................................................................. iii ACKNOWLEDGEMENT ............................................................................................... iv TABLE OF CONTENTS ................................................................................................. v LIST OF TABLES ............................................................................................................ x LIST OF FIGURES ......................................................................................................... xi OPERATIONAL DEFINITION OF TERMS .............................................................. xii ABBREVIATIONS AND ACRONYMS ...................................................................... xiii ABSTRACT .................................................................................................................... xiv CHAPTER ONE: INTRODUCTION ............................................................................. 1 1.1 Background of the Study ............................................................................................... 1 1.2 Problem Statement ........................................................................................................ 3 1.3 Purpose of the Study ..................................................................................................... 4 1.4 Objectives of the Study ................................................................................................. 4 1.5 Hypotheses of the Study ............................................................................................... 5 1.6 Significance of the Study .............................................................................................. 6 1.7 Delimitation of the Study .............................................................................................. 6 1.8 Limitations of the Study ................................................................................................ 6 1.9 Conceptual Framework ................................................................................................. 6 CHAPTER TWO: LITERATURE REVIEW ................................................................ 8 2.1 Nutrient Needs during Pregnancy ................................................................................. 8 2.2 Dietary Diversity and Pregnancy .................................................................................. 9 2.2.1 Measurement of Dietary Diversity........................................................................... 11 2.3 Nutrient Intake and Individual Dietary Diversity during Pregnancy .......................... 11 vi 2.4 Factors Influencing Dietary Diversity and Nutrient intake ......................................... 12 2.4.1 Socio-economic Factors ........................................................................................... 12 2.4.2 Demographic Factors ............................................................................................... 13 2.4.3 Morbidity Patterns ................................................................................................... 13 2.5 Maternal Nutritional Status during Pregnancy ........................................................... 14 2.6 Summary of Literature Review ................................................................................... 15 CHAPTER THREE: METHODOLOGY .................................................................... 17 3.1 Research Design.......................................................................................................... 17 3.2 Research Variables...................................................................................................... 17 3.2.1 Independent Variables ............................................................................................. 17 3.2.2 Dependent Variables ................................................................................................ 17 3.3 Study Area .................................................................................................................. 17 3.4. Target Population ....................................................................................................... 18 3.4.1 Accessible Population .............................................................................................. 18 3.4.2 Inclusion Criteria ..................................................................................................... 18 3.4.3 Exclusion Criteria .................................................................................................... 18 3.5 Sampling Technique ................................................................................................... 19 3.6 Sample Size Determination......................................................................................... 19 3.7 Research Instruments .................................................................................................. 19 3.8 Pretesting of Data Collection Tools ............................................................................ 20 3.8.1 Validity of the Tools ................................................................................................ 20 3.8.2 Reliability of the Tools ............................................................................................ 21 3.9 Training of Research Assistants.................................................................................. 21 3.10 Data Collection Procedures ....................................................................................... 21 3.10.1 Demographic, Socio-Economic and Morbidity Data ............................................. 22 vii 3.10.2 Dietary Diversity and Nutrient Intake.................................................................... 22 3.10.3 Nutritional Status of the Respondents.................................................................... 23 3.10.4 Qualitative Data ..................................................................................................... 24 3.11 Data Analyses ........................................................................................................... 24 3.12 Logistical and Ethical Considerations ...................................................................... 26 CHAPTER FOUR: RESULTS ...................................................................................... 27 4.0 Introduction ................................................................................................................. 27 4.1 Description of the Study Population ........................................................................... 27 4.1.1 Demographic Characteristics. .................................................................................. 27 4.1.2 Socio-economic Characteristics of the Study Population ........................................ 30 4.2 Individual Dietary Diversity Score ............................................................................. 38 4.2.1 Consumption of Foods by Respondents Based on Food Groups ............................. 39 4.2.2 Maternal Perception towards Dietary Diversity based on Qualitative data from FGDs ................................................................................................................................. 41 4.2.3 Findings of Key Informant Interviews (KII) on Dietary Diversity among Pregnant Women .............................................................................................................................. 43 4.3 Dietary Intake of Selected Nutrients among the Pregnant Women ............................ 43 4.4 Maternal Health Profile............................................................................................... 45 4.4.1 Antenatal Clinic Attendance among the Pregnant Women ..................................... 45 4.4.2 Micronutrient Supplementation among the Mothers ............................................... 45 4.4.3 Maternal Morbidity Pattern...................................................................................... 47 4.5 Nutritional Status of the Respondents......................................................................... 48 4.5.1 Nutritional Status Based on MUAC ........................................................................ 48 4.5.2 Nutrition Status Based on Haemoglobin Values ..................................................... 49 4.6 Relationship between Study dependent and Independent Variables .......................... 50 4.6.1 Relationship between Dietary Diversity and Maternal Demographic Factors ........ 50 viii 4.6.2 Relationship between Dietary Diversity and Maternal Socio-Economic Characteristics ................................................................................................................... 51 4.6.3 Relationship between Dietary Diversity and Respondents Nutrient Intake ............. 53 4.6.4 Relationship between Dietary Diversity and Respondents Morbidity Patterns ....... 54 4.6.5 Relationship between Dietary Diversity and Respondents Nutritional Status......... 55 CHAPTER FIVE: DISCUSSION .................................................................................. 57 5.1 Introduction ................................................................................................................. 57 5.2 Demographic and Socio-Economic Characteristics of the Respondents .................... 57 5.3 Dietary Diversity of the Mothers ................................................................................ 58 5.4 Nutrient Intake of the Pregnant Women ..................................................................... 59 5.5 Maternal Health Profile............................................................................................... 60 5.5.1 ANC Attendance ...................................................................................................... 60 5.5.2 Micronutrient Supplementation among the Women ................................................ 61 5.5.3 Maternal Morbidity Patterns .................................................................................... 61 5.6 Nutritional Status of the Mothers ................................................................................ 62 5.7 Relationship between Dietary Diversity and Demographic and Socio-Economic Factors among the Pregnant Women ................................................................................ 63 5.8 Relationship between Maternal Dietary Diversity and Nutrient Intake ...................... 65 5.9 Relationship between Maternal Dietary Diversity and Morbidity Pattern ................. 66 5.10 Relationship between Dietary Diversity and Nutritional Status of the Women ....... 66 CHAPTER SIX: SUMMARY, CONCLUSION AND RECOMMENDATIONS ..... 68 6.0 Introduction ................................................................................................................. 68 6.1 Summary of the Findings ............................................................................................ 68 6.2 Conclusion of the Study .............................................................................................. 69 6.3 Recommendations of the Study .................................................................................. 70 6.3.1 Recommendation for Policy .................................................................................... 70 ix 6.3.2 Recommendation for Practice .................................................................................. 71 6.3.3 Recommendation for Further Research ................................................................... 71 REFERENCES ................................................................................................................ 73 APPENDICES ................................................................................................................. 84 APPENDIX A: LETTER OF INTRODUCTION AND CONSENT ............................... 84 APPENDIX B: RESEARCHER ADMINISTERED QUESTIONNAIRE ....................... 90 APPENDIX C: KEY INFORMANT INTERVIEW SCHEDULE ................................. 113 APPENDIX D: FOCUS GROUP DISCUSSION GUIDE ............................................. 114 APPENDIX E: MAP OF LAIKIPIA COUNTY, KENYA ............................................ 116 APPENDIX F: RESEARCH PERMIT AND AUTHORIZATION ............................... 117 x LIST OF TABLES Table 4.1: Demographic characteristics of the respondents ............................................. 28 Table 4.2: Respondents education and occupation ........................................................... 30 Table 4.3: Major sources of income and decision maker on income use among the respondents households .................................................................................................... 33 Table 4.4: Respondents household livestock ownership .................................................. 35 Table 4.5: Land size, ownership status and main source of family food of the respondents ....................................................................................................................... 36 Table 4.6: Housing, lighting, fuel and source of water among the respondents households ........................................................................................................................................... 38 Table 4.7: Number of respondents who consumed each food group ................................ 41 Table 4.8: Nutrient intake of selected nutrients among the respondents ......................... 44 Table 4.9: Micronutrient supplementation intake among the respondents ...................... 46 Table 4.10: Maternal morbidity of the respondents in the past two weeks ...................... 47 Table 4.11: Nutritional status by MUAC of respondents ................................................. 48 Table 4.12: Nutritional status (MUAC) by age of respondents ........................................ 49 Table 4.13: Nutritional status by haemoglobin levels of the respondents ........................ 49 Table 4.14: Nutritional status (Hb) by age of respondents ............................................... 50 Table 4.15: Relationship between dietary diversity and demographic factors of the respondents ....................................................................................................................... 51 Table 4.16: Association between dietary diversity and socio-economic characteristic of the respondents.................................................................................................................. 52 Table 4.17: Relationship between dietary diversity and respondents nutrient intake ....... 54 Table 4.18: DDS mean difference by nutritional status (MUAC) of the respondents ...... 55 Table 4.19: DDS mean difference by nutritional status (Hb) of respondents ................... 56 xi LIST OF FIGURES Figure 1.1: Conceptual framework on factors influencing maternal dietary diversity, nutrient intake and nutritional status. .................................................................................. 7 Figure 3.1 Flow chart on the sampling procedure ............................................................ 19 Figure 4.1 Respondents household monthly income ........................................................ 32 Figure 4.2 Household assets of the respondents ............................................................... 34 Figure 4.3 Individual dietary diversity score terciles........................................................ 39 Figure 4.4 Consumption of foods by respondents based on food groups ......................... 40 Figure 4.5 Antenatal clinic attendance of the respondents ............................................... 45 xii OPERATIONAL DEFINITION OF TERMS Dietary diversity: the number of different foods or food groups consumed over a given reference period which in this study was 24 hours. Dietary diversity score: the sum total of the number of food groups consumed over a reference period of 24 hour by an individual relative to a scale of 14 food groups (Cereals, vitamin A rich vegetables and tubers, dark green leafy vegetables, other vegetables, white roots and tubers, vitamin A rich fruits, other fruits, flesh meat, organ meat, eggs, fish, pulses/legumes, nuts and seeds, milk and milk products, oils and fats) which were used in the study (FAO, 2008). Morbidity Pattern: In this study was presence of illness/disorder and its duration among the pregnant women two weeks prior to the day of interview. Nutrient intake: the intake of energy, macronutrients and micronutrients (carbohydrates, protein, fat, zinc, iron, folate, calcium, vitamin C and A). Nutrient adequacy: The ability of a diet to meet the recommended nutrient intakes Nutritional status: In this study nutritional status was assessed by mid upper arm circumference (MUAC) and haemoglobin level (Hb) as influenced by nutrient intake. xiii ABBREVIATIONS AND ACRONYMS ASAL : Arid and Semi Arid Land ANC : Antenatal Clinic ANOVA : Analysis of Variance BMI : Body Mass Index CSPRO : Census and Survey Processing DDS : Dietary Diversity Score FAO : Food and Agriculture Organization FGD : Focus Group Discussion HB : Haemoglobin GOK : Government of Kenya IDDS : Individual Dietary Diversity Score KDHS : Kenya Demographic and Health Survey KNBS : Kenya National Bureau of Statistics MOH : Ministry of Health MUAC : Mid Upper Arm Circumference RNI : Recommended Nutrient Intake SES : Socio-Economic Status SPSS : Statistical Package for Social Sciences SD : Standard Deviation UNICEF : United Nations Children’s Fund WHO : World Health Organization xiv ABSTRACT Pregnancy is a critical period during which adequate nutrition is considered an important factor that affects birth outcome and the health of the mother. Research has clearly shown that a diverse diet is strongly associated with nutrient adequacy. In Kenya, there is paucity of scientific data on dietary diversity and nutrient intake among pregnant women and the relationship to their nutritional status. This study therefore aimed at determining dietary diversity, nutrient intake and nutritional status of pregnant women in Laikipia County. The study adopted a cross-sectional analytical design. A researcher-administered questionnaire was used to collect information on demographic, socio-economic, dietary diversity, nutrient intake, morbidity and nutritional status for a total of 254 pregnant women attending antenatal clinic at Nanyuki Teaching and Referral Hospital. Anthropometric data (mid upper arm circumference) and haemoglobin levels were used to assess the women nutritional status. Data from the 24 hour dietary recall was analyzed using Nutri-survey software to determine the amount of each nutrient consumed. Dietary diversity score (DDS) was used to assess diversity of the diet consumed by each respondent. Census and Survey Processing system software (CSPro) was used to enter and verify data while Statistical Package for Social Sciences version 20.0 software was used to analyse the data for both descriptive and inferential statistics. Regression analyses were carried out to determine the contribution of dietary diversity to nutrient intake and nutritional status. A p-value of <0.05 was considered significant in all the analyses. The mean age of the women was 26.81 ± 5.64 years with most being between the ages of 20- 24 years. Majority (54.3%) of the respondents were in the second trimester and with a mean gestational age of 27 ± 6.99 weeks at the time of examination. Out of the possible 14 food groups the mean DDS was 6.84 ± 1.46, with cereals being the most (99.2%) commonly consumed food group. The mean intake of all selected nutrient was inadequate except for vitamin A and C. The mean energy intake (1890.59 ± 898.18) was also below the recommended nutrient intake of 2300 kilocalories. Morbidity burden was high with 57.5% of the respondents being ill two weeks prior to the date of interviews. In respect to nutritional status, 19.3% of the respondents were undernourished based on MUAC while 16.9% were found to be anaemic based on haemoglobin levels. Chi-square test showed that DDS was significantly associated with socioeconomic factors (education level (P<0.001), occupation (P=0.002), monthly income (P<0.001) and household assets ownership (P=0.009). Chi-square test further showed significant relationship between DDS and morbidity incidence (P=0.01) and nutritional status of the respondents (MUAC; P<0.001, Hb; P=0.033). Additionally, regression analysis revealed that DDS was a significant predictor of both MUAC (P<0.001) and Hb levels (P= 0.016). Dietary diversity is therefore crucial in improving nutrient intake and ensuring adequate nutritional status. The researcher recommends that policy makers should enact and support policies on investments geared towards improving the living standard of every household particularly among the poor population. Further, the ministry of health should initiate, support and monitor existing community based programmes promoting dietary diversity especially among vulnerable groups such as pregnant women. 1 CHAPTER ONE: INTRODUCTION 1.1 Background of the Study Good nutrition is considered as a paramount component of health and development (Vakili et al., 2013). Moreover, the growth and prosperity of a nation is highly dependent on the nutritional status of women of the reproductive age since they influence growth of the remaining population (Choudhary et al., 2010). In that view, pregnancy has over time been considered as a critical period during which good maternal nutrition is a key determinant of the health of both child and mother (Popa et al., 2013; Sajjad & Khan, 2012). According to World Health Organization (2012), good nutrition during pregnancy is related to proper infant growth, maternal and child health, healthier pregnancy and delivery and lower risk of chronic diseases. Cheng et al. (2009) have argued that maternal nutrition has a critical role in foetal development and therefore adequate nutrient intake during pregnancy is needed to ensure satisfactory birth outcomes. Maternal diets during pregnancy therefore needs to provide energy and nutrients not only for the mother but also for the growing foetus. The essential importance of diet quality during pregnancy is progressively becoming implicit (Torjusen et al., 2012). According to Zainal-Badari et al. (2012), adequate nutrient intake necessary for good nutrition has often been associated with food variety and diet quality of individuals. Consumption of a wide variety of foods, an integral component of diet quality is thus needed to ensure adequate intake of essential nutrients particularly during pregnancy. 2 Dietary diversity refers to the number of different foods or food groups consumed over a given reference period (Swindale & Bilinsky, 2006). The value of a diverse diet has long been recognized and is considered as a key element of high quality diet (Arimond & Ruel, 2004; Jayawardena et al., 2013). Kennedy et al. (2009) argues that a sufficiently diverse diet reflects nutrient adequacy since no single food contains all the required nutrients for optimal health. In this regard, Labadarios et al. (2011) noted that the more food groups included in a person’s daily diet the greater the likelihood of meeting their nutrient requirements. A variety of foods in the diet is therefore considered imperative in ensuring an adequate intake of essential nutrients (Drimie et al., 2013). In most developing countries micronutrients malnutrition is still a major problem of public health attention due to intake of monotonous, cereal-based diets that lack diversity (Kennedy et al., 2007; Ruel, 2003). Most diets in developing countries lack vegetables, fruits and animal source foods (Daniels, 2009). According to Arimond et al. (2010) women of reproductive age are the most vulnerable to suffer from these deficiencies particularly those from resource poor settings. Pregnant women specially are at a higher risk due to their increased nutrient needs (Lee et al., 2013). As observed by Black et al. (2008) deficiencies in micronutrients such as folate , zinc, iron, vitamin A, B6, B12, C, E and riboflavin are highly prevalent and may occur concurrently among pregnant women. While these deficiencies can have a number of causes not necessarily related to nutrition, a high proportion results from nutritional inadequacies (Kennedy et al., 2010). Notably, iron deficiency anaemia during pregnancy 3 has been reported to be a major problem throughout the world, particularly the developing countries (Alene & Dohe, 2014; Rodriguez-Bernal et al., 2012; Vivek et al., 2012). Similarly, more than 7.2 million pregnant women have been reported to be suffering from vitamin A deficiency (Abebe et al., 2014). In Kenya, according to the 1999 National Micronutrient Survey Report, 55.1 percent of pregnant women are anaemic due to iron deficiency (GOK, 1999; WHO, 2016). To overcome nutritional problems resulting from inadequate intake of micronutrients, food based strategies such as dietary diversification have been recommended (Kennedy, 2009). In Kenya, just as in most developing countries information about dietary diversity is scanty. This study therefore sought to investigate dietary diversity, nutrient intake and nutritional status of pregnant women in Laikipia County. The study also focused on the factors influencing dietary diversity and nutrient intake among the pregnant women. 1.2 Problem Statement Adequate nutrient intakes among women of reproductive age are important determinants of maternal and child health outcomes (Nguyen et al., 2013). According to Black et al. (2008), deficiencies in micronutrients such as folate, zinc, iron, vitamin A, B6, B12, C, E and riboflavin are highly prevalent and may occur concurrently among pregnant women. Further, micronutrient deficiencies are said to be widely spread among women and children in developing countries (Allen, 2014). This may be due to poor dietary habits. Dietary diversity is associated with a good nutritional status. In Kenya, 12.3% of women of reproductive age are said to have a Body Mass Index (BMI) of less than 18.5kg/m2. 4 During pregnancy, this under nutrition has resulted to one in ten new born in Kenya being a low birth weight (<2500g) infant (Kenya National Bureau of Statistics (KNBS) and ICF Macro, 2010). Despite the importance of dietary diversity being well acknowledged, there is paucity of scientific data in Kenya on dietary diversity, nutrient intake and nutritional status of pregnant women in arid and semi-arid land (ASAL) areas and more so in Laikipia County. Laikipia County is an ASAL in Kenya, with frequent drought which increases vulnerability of the resident pregnant women. Furthermore, as rightly noted by Rashid et al. (2011), most studies have been focusing on dietary quantity at the expense of dietary quality. Dietary diversity, a component of dietary quality has received little attention and therefore merits further research especially in developing countries where dietary diversity is rarely reported. To address this gap, this study aimed at determining dietary diversity, nutrient intake and nutritional status among pregnant women in Laikipia County. 1.3 Purpose of the Study The purpose of this study was to assess dietary diversity, nutrient intake and nutritional status among pregnant women in Laikipia County. 1.4 Objectives of the Study The specific objectives of this study were to; 1. Determine demographic and socio-economic characteristics among pregnant women in Laikipia County. 5 2. Assess dietary diversity and nutrient intake among pregnant women in Laikipia County. 3. Assess the morbidity patterns among pregnant women in Laikipia County. 4. Assess the nutritional status among pregnant women in Laikipia County. 5. Establish the relationship between dietary diversity and maternal demographic factors, socioeconomic characteristics, nutrient intake and nutritional status among pregnant women in Laikipia County. 1.5 Hypotheses of the Study This study tested the following hypotheses; H01: There is no significant relationship between maternal demographic factors, socio- economic status and dietary diversity of the pregnant women. H02: There is no significant relationship between dietary diversity and nutrient intake of the pregnant women. H03: There is no significant relationship between dietary diversity and maternal morbidity patterns of the pregnant women. H04: There is no significant relationship between dietary diversity and the nutritional status of the pregnant women. 6 1.6 Significance of the Study The findings of this study are useful to the Ministry of Health (MOH) and other stakeholders by providing important information needed in designing appropriate interventions to improve maternal nutrition. This study also makes an important empirical contribution to the growing body of literature on dietary diversity, nutrient intake and their associated factors among pregnant women and its influence to their nutritional status. 1.7 Delimitation of the Study Since the study was conducted in one county, generalization to other counties, country or region should be made with utmost caution due to demographic and ecological variations. 1.8 Limitations of the Study The data was collected from a cross-sectional study and therefore may not reveal whether the reported Dietary Diversity Score (DDS) values varies over time (Gibson, 2005). To minimise this limitation, Focus Group Discussions (FGDs) were used to solicit information on dietary consumptions at different times of the year. 1.9 Conceptual Framework This study’s conceptual framework was adopted and modified from the UNICEF’s conceptual framework on maternal and new born health (UNICEF, 2009) (Figure 1.1). 7 Figure 1.1: Conceptual framework of factors influencing maternal dietary diversity, nutrient intake and nutritional status. Source: Adapted and modified from UNICEF (2009). Figure 1.1 illustrates the various factors that influence maternal nutrient intake and nutritional status. Nutrient intake is an important factor that determines the nutritional status of a person. During pregnancy, a good nutritional status is strongly associated with healthy birth outcomes. Dietary diversity affects nutrient intake (Figure 1.1) since a diversified diet is positively correlated with nutrient adequacy. However, nutritional status, dietary diversity and nutrient intake may be directly affected by individual health factors such as morbidity patterns. Illness affects food intake, absorption and utilization of nutrients. Similarly, dietary diversity is also influenced by demographic factors such as maternal age, gender, household size and parity. Socio-economic factors such as income, occupation and education are also known to influence dietary diversity as shown in figure 1.1. Maternal Nutritional Status Nutrient Intake Dietary Diversity Socioeconomic Status - Income - Occupation - Education Demographic Factors - Marital status - Gender - Age - Parity - Household size Morbidity Patterns - Type, signs, symptoms and duration of illness 8 CHAPTER TWO: LITERATURE REVIEW 2.1 Nutrient Needs during Pregnancy Adequate nutrient intake is needed to ensure healthy birth outcomes (Saaka, 2013). Compelling evidence suggest that nutrient intake during pregnancy has a critical role in foetal development and therefore maternal diets needs to provide nutrients for both the mother and the foetus (Cheng et al., 2009). Macro and micronutrients such as carbohydrates, protein, fat, zinc, iron, folate, calcium, vitamin C and A are some of the nutrient which are stated to be of specific concern during pregnancy (Black et al., 2008). Pregnant women are vulnerable to nutritional inadequacies due to their elevated nutrient needs (Lee et al., 2013). According to Arimond et al. (2010), the high nutrient demand during pregnancy has put women in developing countries at a high risk since poor dietary intakes have been reported. Poor nutrient intake during pregnancy have been associated with adverse birth outcomes such as permanent damage to the foetus, pre-term delivery, poor infant survival and increased risk of chronic diseases in later life (Ahmed & Tseng, 2013; Blumfield et al., 2012; Imdad & Bhutta, 2011; Sullivan et al., 2009). Additionally, some micronutrient deficiencies in pregnancy, such as iron and calcium deficiencies have been cited to cause substantial maternal deaths ( Black et al., 2013). According to Lartey (2008) maternal malnutrition has been shown to be a major predisposing factor for maternal morbidity and mortality. This according to Ajani (2013) is caused by inadequate food intake, poor diet quality and infections. Ojofeitimi et al. (2008) have demonstrated that maternal malnutrition is known to worsen the other causes 9 of maternal morbidity and mortality such as anaemia, obstructed labour, postpartum haemorrhage and infections among others. Also, limited availability of high quality food and poor dietary habits in developing and developed countries respectively have been associated with these problems (Radlowski & Johnson, 2013). Despite the evidence on the relationship between maternal nutrient intake and birth outcomes, there is limited data on nutrient intake among pregnant women in Kenya and more so in ASAL areas. This study therefore sought to establish the nutrient intake among pregnant women in Laikipia County. 2.2 Dietary Diversity and Pregnancy Dietary diversity is defined as the number of different food groups or foods that are consumed over a specific reference period (Ruel, 2002). The value of a diverse diet has over time been recognized (Kadiyala & Rawat, 2013; Rathnayak et al., 2012), since it can provide a wide range of nutrients which enhances the nutritional quality of the diet (Fujita et al., 2012). All people therefore need a variety of foods to meet requirements for essential nutrients (Drimie et al., 2013; Hoddinott & Yohannes, 2002). High dietary diversity is highly recommended since it is positively associated with nutrient adequacy (Jayawardena et al., 2013). Several studies have demonstrated this positive association between dietary diversity and nutrient adequacy of the diet (Kennedy et al., 2009; Mirmiran et al., 2006). In 2003, five out of seven studies reviewed by Ruel revealed a positive association between DDS and nutrient adequacy (Ruel, 2003). Similarly, a positive relationship between intake from a diversified diet and nutrient 10 adequacy was observed in a research on women of reproductive age living in Mali, Mozambique, Bangladesh, Burkina Faso, and the Philippines (Arimond et al., 2010). In their study, Acham et al. (2012) also noted a strong relationship between dietary diversity and micronutrient intake among women in an informal settlement of South Africa. Based on the above arguments, a diverse diet is therefore paramount in meeting the nutrient requirements of a person and more so to those considered vulnerable to nutrient deficiencies such as the pregnant women. Ruel (2003) noted that in developing countries lack of dietary diversity is a major problem since the diet is predominantly cereal based. The diets are considered monotonous and are comprised of little or no animal products, fruits and vegetables (Kennedy et al., 2007; Leyna et al., 2010). Voster et al., (2011) have argued that the dependency on available and affordable staple foods and energy dense but poor nutrient foods, snacks and beverages have aided to the increased vulnerability to the nutrition transition in Africa. Notably, changing from a monotonous diet to a diet with varied range of food has been shown to increase energy and micronutrient intakes in developing countries (Kennedy et al., 2007). Based on this, consuming a diversified diet has been recommended by virtually all national and global food-based dietary guidelines (Clausen et al., 2005; Kennedy, 2009; Rathnayake et al., 2012; WHO, 1998). In Kenya information on dietary diversity among pregnant women is minimal and thus this study sought to assess dietary diversity among pregnant women in Laikipia County. 11 2.2.1 Measurement of Dietary Diversity Dietary diversity is measured by summing up the number of foods or food groups consumed over a reference period (Vakili et al., 2013; Ruel, 2002). Dietary diversity score has been defined as the total count of different food groups irrespective of the amounts consumed by individuals over a specific period of time (Jayawardena et al., 2013). According to Taruvinga et al. (2013), a reference period of one to three days is usually used though a period of seven days has often been used (FAO, 2011). In some instances, a period of up to 15 days has also been reported (Drewnowski et al., 1997). Notably, dietary diversity instruments (dietary diversity score or food variety score) have become the most preferred method of assessing dietary adequacy in developing countries (Hooshmand and Udipi, 2013). Moreover, single food or food group count have been the most popular methods for measuring dietary diversity (Pellegrini & Tasciotti, 2014). This is because the measurements are simple to collect and easily adopted in different settings (Daniels et al., 2009). 2.3 Nutrient Intake and Individual Dietary Diversity during Pregnancy Adequate nutrient intake prior and during pregnancy has been recognized as a major contributor to healthy birth outcomes. Adequate food intake and dietary diversity has been found to be positively associated (Msaki & Hendriks, 2013). Studies have similarly revealed a positive correlation between dietary diversity and nutrient intakes (Acham et al., 2012; Torheim et al., 2004). According to Krishna et al. (2012), increased dietary diversity is therefore important in ensuring adequate intake of essential foods and nutrients. Notably, micronutrient deficiencies in pregnancy is cited to cause substantial 12 maternal deaths (Black et al., 2013). Adequate nutrient intake among pregnant women is therefore important for maternal and child health (Lee et al., 2013). This study sought to establish the relationship between dietary diversity and nutrient intake among pregnant women in Kenya. 2.4 Factors Influencing Dietary Diversity and Nutrient intake 2.4.1 Socio-economic Factors A number of studies have shown that dietary diversity is associated with socio-economic status (SES) (Savy et al., 2005; Torheim et al., 2004). Rashid et al. (2011) and Thorne- Lyman et al. (2010) found that dietary diversity is strongly associated with SES of a household. Similarly, Brinkman et al. (2010) in their study discussed that families with more income and resources had a more diversified diet. A study in Burkina Faso on women also found that those who were wealthier and with higher education had a higher DDS (Savy et al., 2008). Literature furthermore suggests that individuals with lower incomes and less education have been reported to be more likely to have poorer diets than those individuals with more income and education (Silk et al., 2008). This could be because a healthy diet which consist of a diversified diet is said to be more expensive than a less healthy diet (Morris et al., 2014). Food insecurity which is an outcome measure of dietary diversity has been associated with low purchasing power leading to inadequate dietary intake (Ihab et al., 2012). Expensive food groups such as the high quality animal source foods, fruits and vegetables are also reported to have a decreased intake (Dachner et al., 2010). In Kenya, Kimiywe et 13 al. (2007) revealed that consumption of varied vegetables was influenced by occupation and income levels. According to Ihab et al. (2012), availability and access to food is prohibited by high food prices and scarce resources resulting in inadequate quantity and poor quality diets in the household. Nonetheless, there is paucity of data on the relationship between socio-economic factors and dietary diversity among pregnant women living in ASAL. 2.4.2 Demographic Factors Factors such as age, parity, household size, marital status, gender among others have been found to influence dietary diversity. A study in Botswana showed that older adults consume a diet low in variety with inadequate animal products, fruits and vegetables (Clausen et al., 2005). Age therefore is a determining factor of nutrient intake. According to Taruvinga et al. (2013), female-headed households have a higher probability of achieving a high dietary diversity than the male-headed households. This is in agreement with a study in 1996 by Rogers which noted that female headed households spent more on higher quality foods. In 2003, Thiele and Weiss in Germany also reported that age, sex, household size, employment status and level of education were the strongest determinants of dietary diversity. The association between dietary diversity and demographic characteristics is still less documented. 2.4.3 Morbidity Patterns Illness affects dietary diversity and nutrient intake since they cause decreased food intake as a result of loss of appetite associated with the condition (Scrimshaw, 2003). UNICEF 14 (1998) described morbidity as being one of the immediate causes of malnutrition in individuals. It affects food intake, absorption and utilization of nutrients resulting in poor nutritional status. According to Pieters et al. (2013), an individual’s health affects their ability to absorb nutrients. Antenatal care (ANC) has been cited as one of the best strategies in early detection of complications that might affect pregnancy. Antenatal care is said to serve as a key entry point for implementing nutrition and health interventions that would improve maternal and child nutrition (Perumal et al., 2013). This study sought to establish the relationship between morbidity pattern and nutritional status of pregnant women in Laikipia County. 2.5 Maternal Nutritional Status during Pregnancy Nutritional status can be termed as an outcome of the process of acquiring, consuming and utilizing food (Rajapaksa et al., 2011). In their study, Ey et al. (2012) indicate that a diversified diet is associated with a good nutritional status. Compelling evidence of the relationship between maternal nutritional status during pregnancy and the future health of the child is now substantial. The evidence suggests that the nutritional status of the mother pre and during pregnancy has a crucial role in the growth and development of the foetus (Imdad & Bhutta, 2011). Yakoob et al. (2009), Han et al. (2011) and Hambidge et al. (2014) in their studies have argued that poor nutritional status during pregnancy has been reported to cause delivery of low birth weight babies and is a significant contributor to maternal morbidity. 15 According to Bhutta et al. (2013) maternal under-nutrition contributes to 800,000 neonatal deaths globally annually through small for gestational age births. This maternal under-nutrition has also been stated to increase disease risk in the offspring even in later life (Ferreira et al., 2009; Ahmed & Tseng, 2013). Literature furthermore indicates that the effects of pre-pregnancy Body Mass Index (BMI) on pregnancy outcome have continued to gain widespread attention (Yu et al., 2013). In Kenya, there is paucity of scientific information on the relationship between dietary diversity and the nutritional status of pregnant women and more so among those living in ASAL. In assessing pregnant women nutritional status, methods such as the use of anthropometrics, biochemical methods, clinical methods and dietary intake assessments has been used (Gibson, 2005). According to De et al (2009) anthropometric measurements are the most frequently used methods. The methods are considered effective and most appropriate in the promotion of women’s health. In developing countries the use of BMI in assessing nutritional status among pregnant women has been restrained since most women attend their antenatal clinic late and thus their pre- pregnancy BMI may remain unknown (Kruger, 2005). In this study, mid upper arm circumference (MUAC) and haemoglobin levels (Hb) were used. 2.6 Summary of Literature Review Diverse literature reveals that dietary diversity is indeed strongly associated with nutrient adequacy. Discussed literature further reveals that micronutrient deficiencies among pregnant women remain a major public health concern in developing countries. Despite 16 the relationship between dietary diversity and nutrient adequacy being clearly documented there exist limited information on dietary diversity, nutrient intake and their association with nutritional status among pregnant women. This study therefore sought to determine dietary diversity, nutrient intake and the nutritional status among pregnant women in Laikipia County. 17 CHAPTER THREE: METHODOLOGY 3.1 Research Design The study adopted a cross-sectional analytical design. The design is effective in collecting both qualitative and quantitative data (Mugenda & Mugenda, 2003). The design was also appropriate as it enabled gathering of information at one point in time and identification of associations between the various variables. 3.2 Research Variables 3.2.1 Independent Variables Socio-economic status, demographic factors, morbidity patterns and dietary diversity were the independent variables for this study. 3.2.2 Dependent Variables The dependent variables for this study were nutrient intake and maternal nutritional status (MUAC and Hb). 3.3 Study Area The study was undertaken in Laikipia-East Sub County, Laikipia County; Kenya. The County is an ASAL which is experiencing a worsening food security situation (GOK, 2014). This situation makes pregnant women in the area very vulnerable due to their increased nutrient needs. Laikipia County is one of the 47 counties in the Republic of Kenya which covers an area of 9,462 km2. According to the 2009 Kenya Population and 18 Housing Census, the population for the county stood at 399,227 people. The approximate population of Laikipia-East Sub County is 116,562 people. 3.4. Target Population The study target population comprised of all pregnant women in Laikipia County. 3.4.1 Accessible Population The accessible population included all the pregnant women attending the antenatal clinic at Nanyuki Teaching and Referral Hospital at the time of data collection. 3.4.2 Inclusion Criteria All pregnant women who consented to participate in the study and who had been residents of Laikipia County for at least one year prior to the period of the study were included. One year was appropriate as it covered the whole food security cycle. 3.4.3 Exclusion Criteria Pregnant women with chronic diseases such as cancer and diabetes were excluded from the study. This was because these conditions are known to impact on the nutritional status of an individual. This health information was obtained from the respondents, clinical notes in the mother child booklet and from the hospital records. 19 3.5 Sampling Technique Nanyuki Teaching and Referral Hospital had been purposively selected since it is the referral and main hospital in the area. Comprehensive sampling was used to select the respondents as they arrived in the hospital for their antenatal clinic (Figure 3.1). 3.6 Sample Size Determination Nanyuki Teaching and Referral Hospital records indicated that antenatal clinic attendance was by an average of 237 pregnant women per month. Based on this, a comprehensive sample (100%) in a period of one month was used. A comprehensive sample is used when the number of units are small (Ary et al., 2013). One month was appropriate since ANC attendance in the hospital was on monthly basis. 3.7 Research Instruments A researcher administered questionnaire (Appendix B) was used to collect data on socio- economic and demographic characteristics, nutrient intake, dietary diversity, morbidity Figure 3.1: Flow chart on the sampling procedure Laikipia County (Purposive sampling) Nanyuki Teaching and Referral Hospital (Purposive sampling) Study sample (Comprehensive sampling) 20 patterns and nutritional status. Key informant interviews schedules (Appendix C) and Focused group discussion guides (Appendix D) were used to solicit qualitative data on maternal nutrition perceptions. The socio-economic and demographic data collected was; age, marital status, level of education, occupation, income level, parity, trimester, household head, household sex and household size. Dietary diversity data was collected using a modified individual dietary diversity questionnaire as recommended by FAO 2008. 3.8 Pretesting of Data Collection Tools The tools were pre-tested before the study on 24 respondents (10% of the expected sample size) to establish whether the tools could generate the information needed and with precision. This was done to check the length, content, wording and language of the tools. The pre-test was conducted at Nanyuki Teaching and Referral Hospital. The respondents who were used in the pretesting were not sampled for the actual data collection. After the pre-test, adjustments were done accordingly to enhance reliability and validity of the tools. 3.8.1 Validity of the Tools The tools were tested and validated by a panel of nutrition experts including the university supervisors to ensure that the questions solicited the information intended. 21 3.8.2 Reliability of the Tools The test-retest method was used to test the consistency of the data collection tools within a span of one week between the interviews. The test retest was done on 24 respondents which was 10% of the expected sample size. Correlation coefficient was determined between the two sets of results and a correlation coefficient of 0.92 was obtained. According to Cronbach and Shavelson (2004) a coefficient correlation of above 0.70 is considered as an acceptable threshold. Respondents were also allowed to make comments and give suggestions concerning the tools. 3.9 Training of Research Assistants Five research assistants with a minimum of a diploma in nutrition were recruited and trained as research assistants for four days. They were extensively trained on ethical issues, purpose and objective of the study. In addition, they were trained on how to use the data collection research tools, taking anthropometric measurements, interviewing skills and expectations from each question. 3.10 Data Collection Procedures Respondents were recruited at the hospital (Nanyuki Teaching and Referral Hospital) and followed to their households for the face to face interviews. The respondents were recruited after they had received their usual ANC services. 22 3.10.1 Demographic, Socio-Economic and Morbidity Data A semi-structured questionnaire (Appendix B) was used for collecting data on demographic and socio-economic characteristics of the study subjects. A two week recall period was used to gather information on morbidity pattern and experience among the study respondents. 3.10.2 Dietary Diversity and Nutrient Intake Nutrient intake information was generated using 24 hour recall dietary assessment. The 24-hour dietary recall was done to capture detailed and comprehensive information about all foods and beverages the respondent consumed. Food models, pictures, household utensils and other visual aids were used to help respondents judge and report on portion sizes. The time of food consumption was also recorded. A reference period of 24 hour was used in this study as it minimized the recall bias thus improving on accuracy. The 24 hour dietary recall involved asking the respondents to enumerate all the foods and beverages consumed in previous day from the time they woke up in the morning, throughout the day to the time they went to sleep at night indicating clearly the time the food was consumed. Thorough probing was done to ensure that no food consumed was forgotten. The 24-hour dietary recall was considered to be useful in determining the average intake of energy and nutrients for the respondents. Using the information collected from the 24-hour recall the DDS for the respondents was derived using the 2008 FAO guideline for measuring household and individual dietary 23 diversity (FAO, 2008). In assessing dietary diversity, a scale of sixteen food groups; cereals, vitamin A rich vegetables and tubers, dark green leafy vegetables, other vegetables, white roots and tubers, vitamin A rich fruits, other fruits, flesh meat, organ meat, eggs, fish, pulses/legumes, nuts and seeds, milk and milk products, oils and fats, sweets and sugar and condiments and spices was used. 3.10.3 Nutritional Status of the Respondents. Anthropometric measurements mid upper arm circumference (MUAC) were taken to assess the subject nutritional status. A standard adult MUAC tape was used and the measurements were taken on the less active arm with no clothing. Measurements were taken and recorded to the nearest 0.1 cm. For accuracy purposes, the measurements were taken twice and the average calculated. Additionally, respondent’s nutritional status was also assessed using haemoglobin (Hb) values. Haemoglobin tests were done following standard operating procedures by a qualified laboratory technologist on the same days of the interviews. The process of Hb test involved drawing blood into the microcuvette thorough a finger prick. The microcuvette was then placed into the HemoCue photometer for Hb analysis. The Hb value reading was recorded immediately in the questionnaire and the cuvette was hygienically disposed. Notably, in this study BMI for pregnancy was not used since it is documented that pregnant women in developing countries start to attend their antenatal clinic late in pregnancy and thus their pre-pregnancy BMI may be unknown (Kruger, 2005). 24 3.10.4 Qualitative Data Key informant interviews were conducted using the interview schedule (Appendix C). The respondents included doctors, nurses and nutritionists. Information on maternal knowledge and attitude during pregnancy, nutritional problems faced in pregnancy and possible solutions was solicited. Focus group discussions (FGDs) (Appendix D) were also administered to elicit information on maternal nutrition perceptions. Four focused group discussions were conducted and each FGD comprised of 8-12 respondents who were randomly selected. 3.11 Data Analyses Data on dietary intake from the 24 hour recall was entered and analysed using the Nutri- survey software. The nutrient intakes among the respondents were compared to the Recommended Nutrient Intakes (RNIs) to establish the percentage meeting the RNIs. To determine the DDS of the respondents, a point was awarded to each food group consumed over the reference period and a sum of all points was computed as recommended by FAO (2008). A scale of sixteen food groups (Cereals, vitamin A rich vegetables and tubers, dark green leafy vegetables, other vegetables, white roots and tubers, vitamin A rich fruits, other fruits, flesh meat, organ meat, eggs, fish, pulses/legumes, nuts and seeds, milk and milk products, oils and fats, sweets and sugar and condiments and spices was used. Since the food groups considered in the Individual Dietary Diversity Score (IDDS) put more emphasis on micronutrients, a scale of fourteen food groups (excluding the last two: 25 sweets and sugar and condiments and spices) was used for analysis purposes (FAO, 2008). According to FAO (2008), those two food groups may be used for additional analysis and considerations of bioavailability of micronutrients but not part of the IDDS. The dietary diversity was assessed based on the number of food groups consumed over the immediate past 24 hours. Using the fourteen food groups, dietary diversity terciles were established namely; low diversity tercile (≤ 3 food groups); medium diversity tercile (4 to 5 food groups) and high diversity tercile (≥6 food groups) (FAO, 2006; 2011). The respondent DDS was then assessed based on their position on the scale. Nutritional status was assessed using MUAC and Hb values. A MUAC value of less than 23cm was considered as under nutrition while that above 23 cm was considered normal for pregnant women (UNICEF, 2009; Ververs et al., 2013). Similarly pregnant women with Hb values of below 11.0 g/dl were considered anemic (UNICEF, 2001) while those above it were considered as having adequate nutritional status. Data was entered and verified using Census and Survey Processing system (CSPro) software version 6.1 and later exported to Statistical Package for Social Sciences (SPSS) version 20.0 software for analyses. Descriptive statistics such as means, frequencies, percentages, standard deviations and ranges were computed to describe the study population. Pearson’s product moment was used to determine the relationship and the strength between DDS and nutritional status. Chi-square tests were used to test for 26 association between dietary diversity, demographic and socio-economic status of the respondents. Moreover, T-test and Analysis of Variance (ANOVA) were used to test for significant differences in the mean DDS on different groups based on demographic and socioeconomic characteristics. Regression analyses were further carried out to determine the contribution of dietary diversity to nutrient intake and nutritional status. Qualitative data from key informant interviews and FGDs were transcribed and coded to show the emerging themes. Conclusions were drawn which were then triangulated with data from the questionnaire. A p-value of <0.05 was considered significant in all the analyses. 3.12 Logistical and Ethical Considerations Approval to conduct the research was sought from Kenyatta University graduate school. Ethical clearance was obtained from Ethical Review Committee of Kenyatta University while permit to conduct the research was obtained from the National Council for Science, Technology and Innovation (NACOSTI) (Appendix E). Permission was similarly sought from the area of study local administration and the hospital medical superintendent. Further, after being briefed and offered an opportunity to ask questions about the study, a signed consent was sought from the respondents before administering the questionnaire. To ensure confidentiality, names and other means of identity were not used in this study. Confidentiality and privacy of the data collected was also assured and maintained during and after the study. 27 CHAPTER FOUR: RESULTS 4.0 Introduction This chapter presents the study findings. Data on a comprehensive sample of 254 respondents was collected and reported. The results are organized as per the specific objectives of the study namely; demographic and socio-economic characteristics of the respondents, dietary diversity and nutrient intake among the respondents, morbidity patterns and nutritional status of the respondents. The results on the association between dietary diversity and demographic factors, socio-economic status, nutrient intake and nutritional status among the study respondents are also presented. 4.1 Description of the Study Population 4.1.1 Demographic Characteristics. 4.1.1.1 Age Distribution of the Respondents Table 4.1 displays the demographic characteristics of the study respondents. The mean age of the pregnant women was 26.81 ± 5.64 years with the youngest and the oldest mothers being 16 and 49 years respectively. Most of the women (33.9%) were between the ages of 20-24 years while the age bracket of 45-49 years had the least number of respondents (0.8%). 4.1.1.2 Marital Status of the Respondents The study revealed that majority (88.6%) of the population were married whilst the rest were either single (10.6 %) or widowed (0.8%). 28 Table 4.1: Demographic characteristics of the respondents Category (n=254) n % Age group(Years) 16-19 20-24 25-29 30-34 35-39 40-44 45-49 Mean age 26.81 ± 5.64 Marital status Married Widowed Single Parity of the respondents 1 2 3 >3 Mean parity 2 ± 2 Trimester of the respondents First Second Third Household characteristic Sex of the household head Male Female Household head Respondent Husband Relative Others (Not related) Household size 1 2 3 >3 Mean size of household 3.02 ± 1.27 14 86 78 48 23 3 2 225 2 27 84 89 51 30 13 138 103 225 29 19 219 12 4 13 86 81 74 5.5 33.9* 30.7 18.9 9.1 1.2 0.8 88.6* 0.8 10.6 33.1 35.0* 20.1 11.8 5.1 54.3* 40.6 88.6* 11.4 7.5 86.2* 4.7 1.6 5.1 33.9* 31.9 29.1 *:Majority of the respondents 29 4.1.1.3 Parity of the Respondents The mean parity of the study population was 2 ± 2. Most mothers were primiparous (35%) followed closely by 33.1%, being primigravida. The rest of the study participants were multiparous (Table 4.1). 4.1.1.4 Gestation of the Women in Weeks The mean gestational age at the time of examination was 27 ± 6.99 weeks. The gestation age ranged from 8 to 39 weeks. Slightly more than half of the respondents (54.3%) representing the majority were in their second trimester. Notably, only around 5.1% of the participants reported being in their first trimester. 4.1.1.5 Household Characteristics Information on key aspects of the composition of households, such as the sex of the household head and the size of the household, is presented in Table 4.1. This information is crucial since it is associated with the welfare of the household. The average size of the household was 3.02 ± 1.27. The smallest household had one member while the largest household had 10 members. Most of the household (33.9%) had 2 members. Household with 7, 8, and 10 members were least reported at 0.4% each. Majority (86.2%) of the respondents reported their husbands as being the household heads. Around, 7.5% of the participants indicated to be the heads of their households while 4.7% reported their relatives as being the household heads. Additionally, majority of the households were male headed (88.6%). For those household whose respondent 30 were not the household head the mean age of the head was 32.66 ± 6.87 years and ranging from 21 to 65 years. 4.1.2 Socio-economic Characteristics of the Study Population 4.1.2.1 Education Level and Occupation of the Respondent Education level is a key determinant of the type of employment one gets which in turn is likely to influence the income level of an individual. Moreover, education attainment has a strong effect on the health behaviour and attitude of a person. Table 4.2: Respondents education and occupation Characteristic N=254 n % Respondent education No formal education 10 3.9 Primary 62 24.4 Secondary 131 51.6* Tertiary 51 20.1 Total 254 100 Occupation of respondents Farming Casual labour Employed (salaried) Business Housewife Total Occupation of household head (excluding those respondents who were household heads)(n=19) 11 21 50 67 105 254 4.3 8.3 19.7 26.4 41.3* 100 Unemployed Farming Casual labour Employed(salaried) Business Total 4 16 57 95 63 235 1.7 6.8 24.3 40.4* 26.8 100 *: Majority of the respondents 31 The study results showed that slightly more than half (51.6%) of the respondents had secondary education whilst about 24.4% followed with primary education. Only 20.1% of the total respondents reported to have had formal education up to the tertiary level. Occupation is not only the source of income for an individual but also determines the social class that one enjoys in the society. Examinations of the respondent occupation distribution revealed that most (41.3%) of the women were housewives while those in business followed closely at 26.4%. Additionally, Table 4.2 further shows that about 19.7% of the study participants indicated that they were employed (salaried). For the households where the respondents were not the household heads, most (40.4%) of the household head were in formal salaried employment. Notably, 1.7% among this group was also not in any gainful employment. 4.1.2.2 Household Monthly Income The household wealth index is a background characteristic used as a proxy measure of the standard of living of a household. Household income explains the purchasing power and status of the household. In this study, household income was assessed as a combined income for all the household members. Descriptive analysis revealed that most (28.3%) of the households had a monthly income of between Ksh 10,000 to Ksh 20,000. They were followed by about 21.7% who declared that their household monthly income was between Ksh 8,000 to Ksh 10,000. Worthwhile noting, the findings further revealed that 13.3% of the participants had their household monthly income below Ksh 6,000. 32 Figure 4.1: Respondents household monthly income 4.1.2.3 Major Sources of Household Income and Decision maker on Income use Less than half of the participants (44.5%) highlighted formal employment as their major source of income. The results further show that 24.8%, 23.6%, 5.5% and 1.6% cited business, casual labour, agricultural farm produce and donations as their major source of household income respectively (Table 4.3). In regard to who determines how the income will be used, a huge majority (78.0%) indicated their husbands were the major decision makers. Additionally, a notable proportion (16.1%) of the respondents acknowledged that they were in command of how the income will be used as reflected in Table 4.3. 3.5 9.8 16.5 21.7 28.3 11.4 4.3 3.5 0.8 0 5 10 15 20 25 30 < Ksh 4000 Ksh 4001-6000 Ksh 6001-8000 Ksh 8001-10000 Ksh 10001-20000 Ksh 20001-30000 Ksh 30001-40000 Ksh 40001-50000 Ksh >50000 Percentage In co m e L ev el Household Monthly Income 33 Table 4.3: Major sources of income and decision maker on income use among the respondents households Variable N % Major sources of household income Agricultural farm produce Business Formal employment Casual labour Donations Total Income use decision maker Respondent Husband Relative Total 14 63 113 60 4 254 41 198 15 254 5.5 24.8 44.5* 23.6 1.6 100 16.1 78.0* 5.9 100 *: Majority of the respondents 4.1.2.4 Household Assets and Livestock Ownership 4.1.2.4.1 Household Assets The availability of durable consumer goods is a useful indicator of a household’s socio- economic status. The respondents were asked to state whether they own any of the following items; vehicle, motorcycle, bicycle, wheelbarrow, tractor, sofa set, computer, landline, mobile phone, radio, television, refrigerator, oven/gas cooker and solar pane. Most of the households did not own valuable items associated with high socio-economic status such as vehicle, computer and refrigerator. Only one household reported to have none of all the asked assets while the highest number of assets owned was 11 out of the possible 13. The mean asset ownership out of the possible 13 was 5.28 ± 1.86. From the results most owned asset was mobile phone (96.9%) followed by radio (93.3%) while the least owned 34 asset was a land line telephone (1.2%). Ownership of certain assets such as radio (93.3%), mobile phone (96.9%) and television (78.3%) could be a sign of improved awareness on various nutrition and health related issues since they are good channels of communication through which nutrition messages can be conveyed. Figure 4.2: Household assets of the respondents 4.1.2.4.2 Household Livestock ownership Household livestock ownership has the potential to improve the nutritional status of household members either directly as good sources of proteins through milk, meat and eggs or indirectly by boosting household income which can be used for food expenditure. Slightly more than half (51.2%) of the total respondents confirmed owning some 96.9 93.3 91.7 78.3 58.3 23.2 21.3 14.2 14.2 13.8 11 10.2 1.2 0 20 40 60 80 100 120 P er ce n ta g e Household Items Household Items Owned Owned 35 livestock. As shown in Table 4.4 the most commonly owned animals were chicken, which were owned by 44.1% of all the households. Table 4.4: Respondents household livestock ownership Variable <5 animals 5-10 animals 10-20 animals >20 animals (n=254) Livestock ownership (%) Yes (51.2) No (48.8) percent Percent percent Percent Cattle Yes (25.2) 84.4 14.1 1.6 0 Goat Yes (16.5) 47.6 42.9 7.1 2.4 Sheep Yes (13) 57.6 27.3 6.1 9.1 Donkey Yes (1.6) 100 0 0 0 Chicken Yes (44.1) 18.8 43.8 27.7 9.8 Pigs Yes (2) 100 0 0 0 Ducks Yes (3.9) 50 50 0 0 Rabbit Yes (5.1) 46.2 53.8 0 0 4.1.2.5 Land Size, Ownership Status and Main Source of Family Food. Strengthening household access to land and productive resources improves food and nutritional security. Access to land increases food production and raises income to improve wellbeing of household’s members. More than half (60.6%) of the study respondents reported to own a piece of land. However, the pieces of land were very small with most (31.8%) of the households owning between a half and one acre piece of land. The researcher observed that out of 254 respondents, 100 respondents representing 39.4% of the study population did not own any land (Table 4.5). 36 Table 4.5: Land size, ownership status and main source of family food of the respondents Characteristic N=254 n % Land ownership Yes 154 60.6* No 100 39.4 Total 254 100 Land size < 1/4 acre 6 3.9 1/4-1/2 acre 39 25.3 >1/2- 1 acres 49 31.8* >1-3 acres 46 29.9 >3-5 acres 11 7.1 >5 acres 3 1.9 Total 154 100 Land ownership status Self owned 146 94.8* Hired 4 2.6 Public land 4 2.5 Total 154 100 Main source of family food Home production 46 18.1 Purchase 206 81.1* Donation 2 0.8 Total 254 100 *: Majority of the respondents For those who reported owning land, a significant proportion (94.8%) said the land was self owned. A small fraction 2.6% and 2.5% pointed out that their land was either hired or public land respectively. In respect to the main source of family food, the highest percentage (81.1%) of the respondents purchased food as opposed to 18.1% who had 37 produced their own food. Only a small fraction (0.8%) mentioned donations as their major source of family food. 4.1.2.6 Housing, Lighting, Fuel and Source of Water Socio-economic profile of a household can also be reflected by the household’s type of house, lighting source and cooking fuel used. The present study results revealed that more than half (64.2%) of the participants rented their houses. The rest of the participants (35.8%) reported living in their own houses. In terms of source of household lighting, 78.3% of the respondents indicated to be using electricity. Use of kerosene lamp and solar panel followed at 12.2% and 7.9% respectively. The study showed variations in the type of cooking fuel used. Most (44.9%) of the households had charcoal as their main source of cooking fuel followed by use of gas at 32.7%. In reference to the source of water, Table 4.6 shows that about 82.3% of the respondents had water piped into their homestead while 6.7% of the respondent got their water for domestic use from rivers. The rest of the participant had rain water (4.7%), communal well (3.1%) or communal tap (3.1%) as their source of water. Access to safe water plays an indispensable role in realizing good health and other human rights such as the right to food and livelihood. 38 Table 4.6: Housing, lighting, fuel and source of water among the respondents households Variable N=254 Frequency Percentage Type of housing Own house 91 35.8 Rented 163 64.2* Source of lighting Electricity 199 78.3* Solar panel 20 12.9 Kerosene lamp 31 12.2 Pressure lamp 4 1.6 Type of fuel Kerosene 15 5.9 Gas 83 32.7 Firewood 42 16.5 Charcoal 114 44.9* Source of water Piped into house 209 82.3* Communal Tap 8 3.1 Communal well 8 3.1 Rain tanks 12 4.7 River 17 6.7 *: Majority of the respondents 4.2 Individual Dietary Diversity Score Out of the possible fourteen food groups, the mean DDS was 6.84 ± 1.46 with scores ranging from 3-10 food groups. The DDS of most respondents was in the high tercile (60.6%) (≥6 food groups) and medium tercile (37.0%) (4 to 5 food groups). Only 2.4% of the study subjects were found to be in the lower tercile (≤ 3 food groups). 39 Figure 4.3: Respondents individual dietary diversity score terciles 4.2.1 Consumption of Foods by Respondents Based on Food Groups In general, the most commonly consumed foods were cereals (99.2%), oils and fats (93.3%), other vegetable (92.9%) and milk and milk products (91.7%). White root and tubers were also highly consumed by the participants (Figure 4.4). Dark green leafy vegetables, legumes and other fruits were consumed in moderation by slightly above half of the respondents at 58.3%, 54.3% and 51.2% respectively. Notably, foods of animal origin were least consumed. Only 1.6% of the total respondents reported to have consumed fish and sea food. Similarly, only about 3.9%, 9.4% and 23.6% of the study participants had consumed organ meat, eggs and flesh meat respectively. 2.4 37 60.6 0 10 20 30 40 50 60 70 Low Dietary Diversity Medium Dietary Diversity High Dietary Diversity P er ce n ta g e Dietary Diversity Terciles Dietary Diversity Score 40 Figure 4.4: Consumption of foods by respondents based on food groups The study also showed that Vitamin A rich vegetables and tubers were consumed by approximately one third (32.3%) of the participants. In regard to vitamin A rich fruits, the researcher noted that only 5.1% of the respondents had consumed foods from this food group. There was consensus among the women that cereals was the most consumed food group as was underscored by the FGD statement “In this area most of us feed on Ugali and Githeri as a culture and also since the food is not very expensive”. In regard to meats one of the women said “the cost of buying meat is prohibitive and thus we opt for cheaper foods or we buy when we have extra cash or in important occasions” (FGD, Pregnant Women, 2015). 99.2 93.3 92.9 91.7 68.1 58.3 54.3 51.2 32.3 23.6 9.4 5.1 3.9 1.6 0 20 40 60 80 100 120 Cereals Oils and fats Other vegetables Milk and milk products White root and tubers Dark green leafy vegetables Legumes, nuts and seeds Other fruits Vitamin A rich vegetables and tubers Flesh meats Eggs Vitamin A rich fruits Organ meat Fish and sea food Percentage F o o d g ro u p Food Group Consumption Percentage 41 Table 4.7: Number of respondents who consumed each food group Food group n=254 Percentage Cereals 252 99.2 Oils and fats 237 93.3 Other vegetables 236 92.9 Milk and milk products 233 91.7 White root and tubers 173 68.1 Dark green leafy vegetables 148 58.3 Legumes, nuts and seeds 138 54.3 Other fruits 130 51.2 Vitamin A rich vegetables and tubers 82 32.3 Flesh meats 60 23.6 Eggs 24 9.4 Vitamin A rich fruits 13 5.1 Organ meat 10 3.9 Fish and sea food 4 1.6 Notably, in respect to food intake frequency, the majority (82. 7%) of the study respondents had a meal frequency of 3 times and above per day. Approximately 17.3% of the study subjects were noted to have a meal frequency of below 3 times per day. Both meals and snacks were considered as reported by the respondents. 4.2.2 Maternal Perception towards Dietary Diversity based on Qualitative data from FGDs Majority of the mothers had a good understanding of the benefits of consuming a diversified diet. One of the mothers who acknowledged consuming a diversified diet said, “Consuming different foods is important during pregnancy so that the foetus can get all the nutrients it requires for growth”. Despite majority of the mothers having a good attitude toward dietary diversity some had a contrary opinion. One of the women said, 42 “Consuming many foods is not good since it will make the baby big which will lead to birth through caesarean section”. In respect to the question of whether they belief that what they ate influenced on the health of the infant, majority said it had some influence. For instance one of the mothers stated that, “if you don’t take enough food then you might get a preterm baby or a very small baby”. In respect to frequency of consuming the different food groups, there was agreement among all mothers that the most consumed food group was cereals. A mother said, “Most of us consume Githeri (mixture of boiled maize and beans) almost on daily basis, Githeri is our cultural food. Sometimes Githeri is replaced with Ugali or rice”. When asked on what dictates what and how much they consume during pregnancy, majority said the household income influences what they eat. Others said that their health status influenced the type and quantity of the food they consumed. One of the mothers who reported eating very little quantities of food said, “During pregnancy, I lose appetite to foods, other times the increased heartburn makes me avoid food completely”. On the question of whether what they eat changes during pregnancy, majority of the mother said their diet does not change. One of the few mothers who acknowledged change of diet during pregnancy said, “During pregnancy, I have to eat a lot of fruits since I think they are good for the health of my baby”. In regard to food seasonality, there was consensus among the mothers that food seasonality also affected what they eat. One of the mothers stated, “In some months during the year, we have plenty of food all over 43 which makes them cheaper for us to buy. In other months the food is not readily available and what is available is very expensive”. 4.2.3 Findings of Key Informant Interviews (KII) on Dietary Diversity among Pregnant Women The health care providers (doctors, nurses and nutritionists) were interviewed on factors affecting dietary intake among pregnant women. There was agreement among the three cadres that morbidity and pregnancy disorders affected dietary intake of most of the pregnant women. The nutritionist in charge said, “Most of the mothers complain of heartburn, loss of appetite and vomiting”. When asked about whether they think poor dietary intake is a problem among the pregnant women, all of them considered it a potential problem. One of the nurses said, “There is an increase in pregnancy anaemia in this area which we highly attribute to poor dietary intake among our pregnant women. In regard to maternal knowledge on dietary diversity, the doctors, nurses and nutritionist all stated that majority of the women knew the importance of a diversified diet. “Many mothers have knowledge on the importance of dietary diversity but that does not necessarily translate to practice” said one of the doctors attending the maternity wing. 4.3 Dietary Intake of Selected Nutrients among the Pregnant Women Estimates of nutrient intake are necessary in monitoring the nutritional status of an individual. Table 4.8 presents the nutrient intake of some selected food nutrients in this study. The mean energy intake (1890.59 ± 898.19) of the respondents was below the recommended nutrient intake. When the body does not get enough energy for basal 44 metabolism and daily activities it responds by depleting the reserves and breaking other substances to meet the deficit resulting to poor nutritional status. Notably, the mean contribution of macronutrients (protein, fat and carbohydrate) in the diet to the total energy intake was found to be adequate except for fats 18.72% against the recommended 20-30%. Further, the study showed that the mean intake of vitamin A and C were adequate. The mean intake of all the other selected nutrients was found to be inadequate (Table 4.8). Table 4.8: Nutrient intake of selected nutrients among the respondents Nutrient Mean intake (SD) Reference values % contribution to total energy intake % of respondents meeting the RNI's Energy (kcal) 1890.59 ± 898.19 2300 28 Protein (g) 57.17 ± 29.96 74 (10-15%) 11.15 46.5 Fat (g) 43.54 ± 25.41 94(20-30%) 18.72 8.7 Carbohydrate (g) 415.98 ± 311.67 175(55-75%) 70.17 75.6 Vitamin A (µg) 1595.81 ± 3874.73 800 46.5 Vitamin C (mg) 96.38 ± 68.21 55 70.5 Calcium (mg) 475.52 ± 308.54 800 a 18.1 Folic Acid (µg) 178.97 ± 103.99 600 8.3 Iron (mg) 28.48 ± 48.33 30 b 16.9 Zinc (mg) 4.48 ± 2.82 20 c 5.1 FAO/WHO 1981; FAO/WHO 2001; WHO/FAO 2004 a Based on a low animal protein intake. b Based on a 10% bioavailability level. c Based on a low bioavailability level. 45 4.4 Maternal Health Profile 4.4.1 Antenatal Clinic Attendance among the Pregnant Women Antenatal clinic attendance is considered important in ensuring maternal and child health. As presented in Figure 4.5, though at different gestational ages, most (30.3%) women had attended their antenatal clinic thrice. Approximately 23.2% reported to have attended the antenatal clinic twice whereas around 24% were in their first antenatal visit. Furthermore, only 22.4% indicated to have attended the antenatal clinic more than thrice. Figure 4.5: Antenatal clinic attendance of the respondents 4.4.2 Micronutrient Supplementation among the Mothers The Table 4.9 reveals that vast majority (70.1%) of the women were having micronutrient supplementation. Out of the 70.1% who reported having micronutrient supplementation, most (98.9%) women indicated to be using iron and folic acid supplements. 61 59 77 57 0 20 40 60 80 100 Once Twice Thrice More than thrice N u m b er o f R es p o n d en ts Number of Times Antenatal Clinic Attendance 46 Table 4.9: Micronutrient supplementation intake among the respondents Variable Frequency (n) % Micronutrient supplementation Yes 178 70.1* No Total 76 254 29.9 100 Type of supplements Iron and Folic acid Multiple micronutrient Total Source of supplement Health facility Bought from shops Friends Total Reason for lack of supplementation First ANC visit Not available at ANC clinic Don’t see their need They make me sick Ran out Unaware of them Total 176 2 178 168 9 1 178 32 14 4 19 4 3 76 98.9* 1.1 100 94.4* 5.1 0.5 100 42.1* 18.4 5.3 25 5.3 3.9 100 *: Majority of the respondents In regard to the source of the supplements, health facility had the highest percentage of 94.4%. For those not having any micronutrient supplementation, 42.1% said it was their first ANC visit and thus had not started taking them as the reason of not taking the supplements. Additionally, 25% said the supplements were making them sick and thus could not take them. In the same line, 18.4% reported that the supplements were not available at the ANC clinic while 5.3% said they did not see the need to take the supplements. The study further revealed that another 5.3% of those not taking the supplements indicated their supplements had run out and had not secured more. About 47 3.9 % of the respondents not taking the supplements indicated that they were unaware of the supplements. 4.4.3 Maternal Morbidity Pattern Since illness affects food intake, absorption and utilization of nutrients of an individual, this study determined the morbidity patterns of the study participants. More than half (57.5%) of the women involved in this study reported to be unwell in the immediate two weeks preceding the day of the interviews. The main disorders reported by the women were heartburn (42.9%) and anorexia (15.4%) as shown in the Table 4.10. Out of all those who reported being sick, only 40.4% who sought medical attention. Government hospital was most preferred by those who sought medical treatment (78%) in comparison with 16.9% who sought attention from the private hospitals. About 5.1% of the sick respondents reported that they used traditional medicine to cure their ailments. Table 4.10: Maternal morbidity of the respondents in the past two weeks N=254 Type of illness/disorder n Prevalence (%) Highest frequency of duration Heartburn 109 42.9 >7 days Anorexia 39 15.4 >7 days Vomiting 36 14.2 > 7days Constipation 29 11.4 2 days Fever 14 5.5 7 days Abdominal pains 10 3.9 6 days Upper respiratory infection 6 2.4 5 days Diarrhoea 5 2 1 day Headache 3 1.2 5 days Sick= 146, Not sick=108, Total=254 Multiple responses 48 4.5 Nutritional Status of the Respondents 4.5.1 Nutritional Status Based on MUAC The average MUAC of the respondents was 26.72 cm ± 3.66 with the measurements ranging from 19.5 cm to 40.2 cm. The study results revealed that 19.3% of the study subjects were undernourished (MUAC <23cm) while about 80.7% of the participants had adequate nutritional status. Table 4.11: Nutritional status by MUAC of respondents N=254 MUAC in cm Frequency Percentage <23.0 cm 49 19.3 23.0 cm and above 205 80.7 Total 254 100 UNICEF, 2009; Ververs et al., 2013; WHO, 1995 Chi-square test showed a significant relationship between mother’s age and their respective nutritional status based on MUAC (Likelihood ratio; 20.210, df=6, P=0.003). Moreover, Pearson’s correlation coefficient revealed a significant positive relationship (r=0.217, P<0.001) between the mothers MUAC and age suggesting that MUAC increased with increase in age. Notably, when MUAC of the women was correlated with their gestational age in weeks, a negative relationship was revealed showing that MUAC readings decreased with increase in gestational age (r=-0.174, P=0.005). This could be explained by the fact that the foetal nutritional needs increase with gestational age and if the mother is not able to meet the requirements, body stores are depleted resulting in deterioration of the nutritional status 49 of the expectant woman. Cross tabulation of women age category and their respective nutritional status (MUAC) revealed that most of the women who were under nourished were in the age category of between 20-29 years as reflected in the Table 4.12. Table 4.12: Nutritional status (MUAC) by age of respondents N=254 MUAC status Age category Under Nourished (n) (%) Normal (n) (%) Total (n) (%) 16-19 9(3.5) 5(2.0) 14(5.5) 20-24 15(5.9) 71(28.0) 86(33.9) 25-29 15(5.9) 63(24.8) 78(30.7) 30-34 7(1.4) 41(16.1) 48(18.9) 35-39 1(0.4) 22(8.7) 23(9.1) 40-44 1(0.4) 2(0.8) 3(1.2) 45-49 1(0.4) 1(0.4) 2(0.8) Total 49(19.3) 205(80.7) 254(100) 4.5.2 Nutrition Status Based on Haemoglobin Values The respondent’s blood was tested for haemoglobin levels. In this study, pregnant women with haemoglobin of less than 11g/dl were considered to be anemic (UNICEF, 2001). The mean haemoglobin level of the respondents was 12.52 g/dl ± 1.61. About 16.9% of the respondents were found to be anemic. Table 4.13: Nutritional status by haemoglobin levels of the respondents N=254 Hb in g/dl Frequency Percentage <11.0 g/dl 43 16.9 11.0 g/dl and above 211 83.1 Total 254 100 UNICEF, UNU, WHO, 2001 50 Table 4.14: Nutritional status (Hb) by age of respondents N=254 MUAC status Age category Anemic (n) (%) Normal (n) (%) Total (n) (%) 16-19 4(1.6) 10(3.9) 14(5.5) 20-24 15(5.9) 71(28.0) 86(33.9) 25-29 17(6.7) 61(24.0) 78(30.7) 30-34 3(1.2) 45(17.7) 48(18.9) 35-39 3(1.2) 20(7.9) 23(9.1) 40-44 1(0.4) 2(0.9) 3(1.2) 45-49 0(0) 2(0.9) 2(0.8) Total 43(16.9) 211(83.1) 254(100) Cross-tabulation between women age category and nutritional status based on Hb showed that the age category of 25-29 years had the highest number of women who were anemic. Additionally, since dietary iron is important in formation of blood, Chi-square test was carried out to test for association between iron intake and anemia and the results showed no significant relationship (χ2=0.103, df=1, p=0.748). 4.6 Relationship between Study dependent and Independent Variables The study established the association between the dependent and the independent variables. 4.6.1 Relationship between Dietary Diversity and Maternal Demographic Factors Table 4.15 shows that there was no statistically significant relationship between dietary diversity and maternal demographic factors (age category, marital status, trimester of the pregnancy, house headship and household size of the respondents) assessed in this study. 51 Table 4.15: Relationship between dietary diversity and demographic factors of the respondents Variables χ2/Likelihood ratio P value DDS vs. Age category 10.096 0.608 Marital status 1.261 0.868 Parity 6.296 0.900 Trimester 1.299 0.862 Household headship 3.109 0.211 Household size 12.426 0.714 Likelihood ratio used for cells with less than 5 counts. 4.6.2 Relationship between Dietary Diversity and Maternal Socio-Economic Characteristics The study results established that there was significant relationship between dietary diversity and the respondent education levels (P<0.001), occupation of the respondents (P=0.002), monthly income level (P<0.001), land ownership (P=0.041), total number of household assets (P=0.009) and source of household lighting (P=0.017) (Table 4.16). When post hoc analysis of variance (ANOVA) was done, it was established that as the level of education increased, the level of dietary diversity score also increased. These results suggest that the more educated the respondents were the more they were likely to attain a high dietary diversity. Despite this positive relationship, it was noted that the mean diversity score of the various education levels was not significantly different (P=0.10). Similar trend was observed in respect to household monthly incomes. The 52 finding suggested that high income is associated with increased probability of having high dietary diversity. Table 4.16: Association between dietary diversity and socio-economic characteristic of the respondents Variables χ2/Likelihood ratio df P value DDS vs. Education level 43.409 14 <0.001* Occupation of the respondents 31.101 12 0.002* Occupation of the household head 11.197 10 0.342 Source of income 15.285 8 0.540 Monthly income 43.307 16 < 0.001* Income use determiner 8.180 6 0.225 Land ownership 6.382 2 0.041* Land size 11.142 10 0.347 Main source of food 0.348 4 0.987 Livestock ownership 2.196 2 0.334 Total number of household assets 40.587 22 0.009* House ownership 2.665 4 0.615 Source of lighting 18.633 8 0.017* Type of cooking fuel 8.805 6 0.185 Source of water 6.854 8 0.552 *: significant (P< 0.05) Likelihood ratio used for cells with less than 5 counts. With regard to the occupation of the respondents, those who reported to be employed (salaried) had the highest mean score of dietary diversity (7.04) while those in casual labour had the lowest mean score (5.90). The differences in dietary diversity mean score amongst the different employment status categories were significantly different (ANOVA; P=0.031). 53 A paired sample t-test was done to establish any significant differences in the dietary diversity mean score among those who reported owning land against those who did not. A significant difference (P=0.024) in the means was revealed with those who reported owning land having a higher mean score (7.01±1.48) than those who did not (6.59±1.39). A significant positive relationship was also established when Pearson’s correlation test was done between DDS and the total household assets (r=0.244, P<0.001). This implies that an increase in household assets is associated with an increase in the DDS. This could be explained by the fact that increased household assets are associated with a better socio-economic status. Since total household assets was found to be a predictor of DDS (P<0.001) a prediction equation of dietary diversity based on total household assets was developed. DDS= 5.835(constant) + 0.191(total household assets) 4.6.3 Relationship between Dietary Diversity and Respondents Nutrient Intake When Pearson’s correlations were done between DDS and nutrient intake of selected nutrients, positive correlations were noted in all the nutrients. This means that as dietary diversity increased, the nutrient intake of the respondents also increased. This indicates that increased dietary diversity is needed in ensuring adequate intake of essential nutrients. However, in this study the correlations were only statistically significant to some of the selected nutrients (protein and calcium) (Table 4.17). 54 Table 4.17: Relationship between dietary diversity and respondents nutrient intake Variables r P value DDS vs. Energy 0.041 0.518 Protein 0.134 0.031* Fat 0.074 0.238 Carbohydrate 0.118 0.061 Vitamin A 0.085 0.176 Total folic 0.031 0.618 Vitamin C 0.058 0.354 Calcium 0.143 0.023* Iron 0.021 0.740 Zinc 0.048 0.446 *: significant (P<0.05) 4.6.4 Relationship between Dietary Diversity and Respondents Morbidity Patterns Illness affects dietary diversity and nutrient intake since they cause decreased food intake. The decreased food intake is as a result of loss of appetite associated with the illness. A paired t-test showed that there were significant differences (P=0.01) in the mean DDS among those who had reported being sick two weeks prior to the day of the interviews and those who had not fallen ill in the same period. Those who had not reported any illness had a higher mean score (7.19±1.33) than their ill counterparts (6.59±1.50). This study finding confirms that illness can affect dietary diversity. There was however no significant relationship between morbidity pattern and the nutritional status of the respondents based on both MUAC (χ2=0.348, P=0.555, df=1) values and Hb levels (χ2=0.059, P=0.808, df=1). 55 4.6.5 Relationship between Dietary Diversity and Respondents Nutritional Status 4.6.5. 1 Relationship between Dietary Diversity and MUAC of the Respondents A positive linear relationship between dietary diversity and the pregnant women MUAC was revealed by the study results (r= 0.362, P<0.001). From a statistical standpoint, DDS stood out as an important predictor of the respondent nutritional status (MUAC) (P<0.001). In light of the present study finding, the following regression equation was formulated to enable prediction of MUAC based on DDS; MUAC= 20.504(constant) + 0.909(DDS) Similarly, when a Chi-square test was done between dietary diversity and the respondent nutritional status, a significant relationship was established (χ2= 16.003, df=2, P<0.001). Furthermore, a paired t-test revealed a significant difference on the mean dietary diversity score, with those with poor nutritional status having a lower mean DDS as compared with those who had a normal nutritional status (Table 4.18). From these findings, it is therefore evident that a diversified diet is associated with a good nutritional status. Table 4.18: DDS mean difference by nutritional status (MUAC) of the respondents MUAC STATUS N Mean DDS SD Std. Error Mean df Sig. (2 tailed) DDS Undernourished 49 5.9 1.48 0.211 252 <0.001 Normal 205 7.07 1.36 0.095 56 4.6.5. 2 Relationship between Dietary Diversity and Hb of the Respondents Haemoglobin levels was positively correlated with high dietary diversity and negatively correlated with low dietary diversity (r= 0.152, P=0.016). Regression equation was also developed to predict haemoglobin levels based on DDS Hb= 11.375(constant) + 0.167(DDS) Additionally, t-test analysis showed significant differences between the DDS means of those found anemic as compared to those who had normal Hb levels as shown in the Table 4.19 Table 4.19: DDS mean difference by nutritional status (Hb) of respondents Hb levels N Mean DDS SD Std. Error Mean df Sig. (2 tailed) DDS Anemic 43 6.30 1.389 0.212 252 0.007 Normal 211 6.95 1.450 0.100 These results infer that increased DDS is positively associated with increased haemoglobin levels. 57 CHAPTER FIVE: DISCUSSION 5.1 Introduction The aim of this study was to assess dietary diversity, nutrient intake and nutritional status of pregnant women in Laikipia County. This chapter discusses the study findings in relation to the study objectives as well as how the results compare with other research findings. 5.2 Demographic and Socio-Economic Characteristics of the Respondents Most of the pregnant women were young (20-24 years). Age consideration in pregnancy is very important because pregnancy complications may occur if the mothers are too young or at advanced age. The majority of the women had some formal education with only 3.9% being reported to have no education. This figure is lower than the national figure which reported that 7.5% of the women had no education (KNBS and ICF Macro, 2010). The mean household size of this study was also slightly lower than the national figure (4.2) reported by the Kenya National Bureau of Statistics (2010). Large household sizes may affect household and individual dietary diversity since economic resources tend to be constrained in large households as compared to households with few members. Most of the respondent in this study were married. Marital status affects the provision of basic needs and the general well being of the household. Further, According to Dyer (2007) marriage in the African society has been considered an important milestone in one’s life and the starting point of getting children who will carry the family name to 58 posterity. Most of the mothers had only completed secondary education. Education level affects food choices, type of occupation and ultimately the level of income one gets. 5.3 Dietary Diversity of the Mothers The value of a diverse diet has over time been recognized and is highly recommended since it is strongly and positively associated with nutrient adequacy (Jayawardena et al., 2013; Kadiyala & Rathnayak et al., 2012). Majority of the women in this study had a high dietary diversity with a mean of 6.84 ± 1.46. The findings of this study compare with those of studies done by Vakili et al. (2013) and Saaka (2012) where a mean DDS of 6.81 and 9.1 were reported respectively. It is important to note that the compared study of Saaka (2012) considered 12 food groups in a reference period of 7 days unlike this study which considered 14 food groups in a reference period of 24 hours. The high DDS score observed in this study could be explained by the fact that the study was conducted in the season of plenty. The high consumption of food items from the grains and grains product by almost all respondents (99.2%) confirms that diets of the pregnant women were predominantly based on starchy staples. The findings agree with those of other studies that most diet in developing countries are predominantly cereal based (Ekesa et al., 2011; Kennedy et al., 2007; Ruel, 2003). Notably, as stated by Daniels (2009) diets in developing countries have also been reported to be lacking or having little animal source foods which were confirmed by this study since only 27.5% of the total respondent had consumed animal source foods based on the 24 hour dietary recall. With regard to food intake frequency, the majority of the respondents had attained 59 the minimum meal frequency of 3 meals per day. Frequency of eating during pregnancy is a component of maternal nutrition relevant to pregnancy outcome. 5.4 Nutrient Intake of the Pregnant Women Saaka (2013) has argued that adequate nutrient intake is needed to ensure satisfactory birth outcomes since the nutrients have a critical role in the foetal development. Lee et al. (2013) have also demonstrated explicitly that pregnant women are vulnerable to nutritional inadequacies due to their increased nutrient needs. Despite the fairly high dietary diversity reported in this study most of the women had inadequate intake of some of the selected nutrients. In the present study, only the mean intake of vitamin A and C were adequate and this would be attributed to the high consumption of green leafy vegetables and other vegetables reported in the study. This study finding of inadequate nutrient intake during pregnancy are comparable with those of a study conducted by Black et al. (2008) where it was noted that deficiencies in micronutrients such as vitamin A, C, zinc, iron and folate are highly prevalent and may occur concurrently among pregnant women. Similar findings are also documented in a study conducted among pregnant women in Nakuru-Kenya (Kamau-Mbuthia, 2007). Moreover, a study in Deep South of Thailand reported nutrient inadequacies of key macro and micro nutrients among pregnant women (Sukchan et al., 2010). A possible reason for the inadequacies established in this study would be the low quantities of food that the women consumed. This could also be further explained by the fact that majority of the respondents had reported being sick in the two weeks prior to the period of data 60 collection and literature has clearly shown that sickness affect food intake, absorption and utilization of nutrients. 5.5 Maternal Health Profile 5.5.1 ANC Attendance The objective of ANC care during pregnancy is to identify and treat maternal health problems such as anaemia and infections (KNBS and ICF Macro, 2010). It is attested as one of the best strategies in early detection of maternal complications that might affect the pregnancy. Furthermore, according to Perumal et al. (2013) antenatal care is said to serve as a key entry point for implementing nutrition and health interventions that would improve maternal and child nutrition. Pregnant women should attend ANC clinic at least four times in the entire period of the pregnancy. Though the women were at different gestational ages, the study revealed that only a small number had attended their antenatal clinic more than thrice by the time of data collection. In respect to the gestational age, most women sought there first ANC visit in their second trimester. The study results are in agreement with those of Kenya National Bureau of Statistics and ICF Macro (2010) which indicate that most women seek their first ANC attendance either in their second and third trimester. KNBS and ICF Macro (2010) findings reported that only 15% of pregnant women seek antenatal care in their first trimester. ANC visit from the first trimester are very crucial for both the mother and the unborn child. This is because early visits can enable timely detection and treatment of any complication that might otherwise cause maternal and infant mortality 61 5.5.2 Micronutrient Supplementation among the Women Iron deficiency anaemia is still very common in developing countries. To overcome this deficiency iron supplements are usually prescribed to pregnant women (Shaw et al., 2011). In this study, majority of the respondents reported to be taking iron folate supplements or multiple micronutrient supplements. Due to the enormous prevalence of micronutrient deficiencies in developing countries which may adversely affect pregnancy, supplementation with iron and folate supplements have been shown to be of potential benefit to both the mother and the foetus. Anemia during pregnancy increases the chances of maternal mortality especially during delivery. 5.5.3 Maternal Morbidity Patterns Morbidity in an individual affects dietary diversity and ultimately nutrient intake. This is because it affects food intake due to the loss of appetite associated with the illness. According to UNICEF (1998) morbidity affects food intake, absorption and utilization of nutrients resulting in a poor nutritional status. As it emerged in this study a notably high proportion of the respondents reported being unwell two weeks prior to the date of data collection. Findings of this study are consistent with those of a study carried out in India which found that most women had reported being sick during antenatal period (Singh et al., 2013). The present study results pinpointed gastrointestinal disorders such as heartburn, anorexia constipation, abdominal pains, vomiting and diarrhoea as the most common type of illnesses and disorders among the pregnant women. This finding was further supported 62 by two of the key informant participants (nursing officer and nutritionist) who said that most of the pregnant women complained of heartburn and lack of appetite. The nutritionist in charge said, “Most of the mothers complain of heartburn, loss of appetite and vomiting” (KII, Health Care Provider, 2015). These findings compare well with those of studies done by Patel et al. (2013) and Singh et al. (2013) which reported abdominal pains and gastrointestinal disorders as the most common disorders among pregnant women. 5.6 Nutritional Status of the Mothers Several studies have documented that poor nutritional status during pregnancy have been reported to cause delivery of low birth weight babies and is also a significant contributor to maternal morbidity (Hambidge et al., 2014; Han et al., 2011; Yakoob et al., 2009). Additionally, available evidence suggests that maternal nutritional status prior and during pregnancy influences the birth outcome (Imdad & Bhutta, 2011). Based on both MUAC (19.3%) and Hb (16.9%) a considerable number of respondents in this study had a poor nutritional status. The poor nutritional status may be due to the inadequate intake of both macro and micronutrients as witnessed in this study. In comparison with this study findings, a study in South Eastern Nigeria among pregnant women reported 40.4% of the respondents as being anemic (Dim & Onah, 2007). Equally, a study in Nairobi by Nduhiu-Githiji (2013) reported 36.2% of the study participant as being anemic. The results of this study were comparable with a study conducted in Ethiopia which revealed that 21.3% of the participants were anemic (Hailu- 63 Alemayehu, 2013). The relatively low level of malnutrition detected in this study could be explained by the high dietary diversity reported by the pregnant women. Similarly, despite the inadequate dietary intake of iron revealed in this study the relatively lower cases of anemia in this study may be attributed to the high number of respondents who were taking iron-folate supplements. 5.7 Relationship between Dietary Diversity and Demographic and Socio-Economic Factors among the Pregnant Women The association between dietary diversity and maternal demographic and economic factors was established. In this study, the selected maternal demographic factors were not significantly associated with dietary diversity. Similar findings were also documented by a study done by Ali et al. (2014) in Pakistan among pregnant women. Contrary to the finding of this study, Taruvinga et al. (2013) reported a significant association between house headship and dietary diversity. The study found that female headed households were more likely to achieve high dietary diversity. Likewise, since age was not a determining factor of dietary diversity in this study, this study finding is therefore in disagreement with another study done in Botswana by Clausen et al. (2005) which reported that older adults consumed a diet low in variety. In regard to association between dietary diversity and socio-economic status, this study found compelling evidence that dietary diversity is indeed strongly associated with the socioeconomic status of the respondent households. Those women with higher education had a higher DDS. This could be so because women with a higher education might have 64 acquired essential information on appropriate feeding practices. Additionally, those households with higher income had better DDS. The possible reason is that higher income is associated with increased purchasing power which can help in promoting dietary diversity. In respect to occupation, those who reported being employed and salaried had the highest dietary diversity. This could be so because irregular family income contributes to low DDS as evidenced by this FGD participant statement “Since I have no consistent monthly income it becomes difficult for me to change my regular diet” (FGD, Pregnant Women, 2015). Significant association between dietary diversity and land ownership were shown in this study. Those who reported owning land had a higher DDS than those who did not own land and the difference was significant. This could be explained by the fact that those who had land were able to engage in food production which enhanced their dietary diversity. This was confirmed by the FGD finding where a mother said “I grow some food in my small piece of land which complements the food I obtain through buying” (FGD, Young Mother, 2015). Moreover, household assets and source of lighting were also significantly associated with DDS. This would be possible since household assets and source of lighting have been associated and used as a proxy indicator of the socioeconomic status of a household. Findings of this study are consistent with findings of several studies which have reported that dietary diversity is associated with socio-economic status (Rashid et al., 2011; Savy et al., 2008; Torheim et al., 2004). In unison with this study, a study conducted by 65 Kimiywe et al. (2007) in Nairobi revealed that dietary diversity was influenced by occupation and income levels. Moreover, in agreement with this study, a study by Vakili et al. (2013) in Ahvaz-Iran showed a significant relationship between DDS and the economic situation of the respective respondents. It is evidently clear that high DDS is accompanied by a greater cost and thus poor families may not access a highly diversified diet. In respect to this revelation that dietary diversity was indeed associated with the socioeconomic status of the respondents, the stated hypothesis that there is no significant relationship between maternal demographic and socio-economic factors is therefore rejected. 5.8 Relationship between Maternal Dietary Diversity and Nutrient Intake In this study, positive correlations were noted between dietary diversity and some of the selected nutrients. This finding suggests that nutrient intake increases with increase in dietary diversity. In light of this observation, improved dietary diversity therefore enhances the chances of nutrient adequacy in an individual. In comparison with other studies, a positive relationship between consumption of a varied diet and nutrient adequacy was noted in a study done on women in Tehran (Mirmiran et al., 2006). A strong relationship between dietary diversity and micronutrient intake was also found by Acham et al. (2012) among women in an informal settlement in South Africa. Moreover, a study in Brazil by Bezerra and Sichieri in 2011 demonstrated a direct association between dietary diversity and energy intake. A high dietary diversity should therefore be widely recommended and the importance of consuming a diversified diet should be captured in all food based dietary guidelines. Since relationships have been found 66 between dietary diversity and nutrient intake, the postulated hypothesis that dietary diversity is not associated with nutrient intake of the respondents is therefore rejected. 5.9 Relationship between Maternal Dietary Diversity and Morbidity Pattern The majority of the study participant reported being sick two weeks prior to the date of the interview. Significant differences were also found in the mean DDS among the sick and those not sick. This finding therefore supports evidence that illness affects dietary diversity of an individual. These observations are supported by a study by George et al (2014) who observed that high diet quality was found to be less associated with illness and side effects of medications. Moreover, a study by Young in 1997 concurs with this study that dietary intake is worsened by illness. Additionally, Morton et al (2014) have argued comprehensively that diseases affect dietary intake of a person. Since these findings reveal a significant relationship between morbidity pattern and dietary diversity, this study hypothesis that stated that there is no significant relationship between maternal morbidity pattern and dietary diversity is thus rejected. 5.10 Relationship between Dietary Diversity and Nutritional Status of the Women Significant relationship between dietary diversity and the respondent nutritional status based on both MUAC and Hb were observed in this study. These findings add evidence to the existing literature that dietary diversity is indeed associated with nutritional status of an individual. Findings from this study are in agreement with those observed by Ey et al. (2012) in their study who found a significant relationship between dietary diversity and nutritional status of the respondents. Based on the findings of this study, the 67 hypotheses that there is no significant relationship between dietary diversity and nutritional status of pregnant women in Laikipia County is therefore rejected. 68 CHAPTER SIX: SUMMARY, CONCLUSION AND RECOMMENDATIONS 6.0 Introduction This chapter provides a summary of the study, conclusions and recommendations. The study aimed at determining dietary diversity, nutrient intake and nutritional status of pregnant women in Laikipia County. 6.1 Summary of the Findings Most of the respondents were young and in the age category of 20-24 years. The highest percentages of the respondents were married and were in the third trimester of the pregnancy. The majority of the household were male headed and with a mean household size of 2 members. The results further showed that most of the pregnant women had only completed their secondary education. In regard to their occupation, most of the pregnant women reported being housewives. Overall, most of the households reported their monthly income as being between Ksh 10,000 to 20,000. Additionally, despite majority reporting owning some land, most of the households purchased their food. Dietary diversity of the respondents was generally good with a mean of 6.84. In respect to food groups, the highest consumed food group was cereals by almost all (99.2%) of the respondents while the least consumed food group was fish and sea food. The majority of the respondents had inadequate intake of both macro and micronutrients except for vitamin A and C. With regard to morbidity, the morbidity incidence was high with majority of the respondents being ill two weeks prior to the day of data collection. Results further revealed that maternal malnutrition was high with 19.3% and 16.9% of 69 the respondents having poor nutritional status based on both MUAC and Hb levels respectively. Moreover, the present study revealed statistically significant association between dietary diversity and the socio economic status of the respondent but found no significant association between dietary diversity and demographic factors of the respondents. Dietary diversity was also positively related to some of the selected nutrients. Similarly, morbidity and nutritional status were also found to be significantly associated with dietary diversity. 6.2 Conclusion of the Study The study has demonstrated that dietary diversity of the pregnant women was generally good. However, the diets of respondents were noted to be predominantly cereal based. Despite the good dietary diversity reported most of the respondent did not meet the recommended nutrient intakes of most of the selected nutrients. The inadequate intake of both macro and micronutrient was attributed to the low quantities of foods that were being consumed by the respondents. Morbidity incidence among the pregnant women was noted to be high. In regard to nutritional status, the majority of the respondents had a good nutritional status but a significant proportion of the respondents had a poor nutritional status. The discussed results also highlighted the critical role of education, occupation, monthly household income, lighting source, household assets and land ownership in the 70 attainment of high dietary diversity. Additionally, positive associations between dietary diversity and nutrient intake underscored the importance of dietary diversity in meeting nutrient requirements among pregnant women. Further, this study finding that morbidity negatively influenced dietary diversity strengthens the growing evidence that improved dietary diversity is associated with reduced likelihood of morbidity. In respect to nutritional status, the study confirmed that dietary diversity is indeed associated with nutritional status. This finding suggested that pregnant women with a diversified diet were more likely to have a better nutritional status. 6.3 Recommendations of the Study This study has the following recommendations; 6.3.1 Recommendation for Policy Results have demonstrated that factors such as level of education, occupation, monthly income, household assets and land ownership are important determinants of dietary diversity. Based on this finding, policy makers should enact new and support existing policies on investments geared towards improving the living standards of every household. This support would play a significant role in enhancing household dietary diversity and ultimately maternal dietary diversity and nutrient intake for better pregnancy outcomes particularly among the poor population. Further, policies to enhance women education and policies to ensure access and proper utilization of health facilities in the context of women general reproductive health are recommended. 71 6.3.2 Recommendation for Practice Since the study has revealed that illness influences dietary diversity and nutrient intake, it is therefore paramount that the government through the ministry of health and other relevant stakeholders launch public health awareness campaigns to make the public and more so the pregnant women aware of the importance of early identification and timely treatment of diseases. Moreover, nutritionists and dieticians have a critical role in educating pregnant women on the importance of diversified diets in improving nutrient intake for a healthy present and future generation. Nutrition education could be disseminated during pregnant women ANC visits. The ministry of agriculture should also scale up training on some practical skills of how they can achieve high dietary diversity through methods such as the use of kitchen gardening and through production of a variety of high yielding nutritious crops. Furthermore, the ministry of health should initiate and monitor existing community based programmes promoting dietary diversity especially among vulnerable groups such as pregnant women. 6.3.3 Recommendation for Further Research The study was undertaken in one season of the food security cycle. It is therefore recommended that similar studies be done during other seasons so that it can better explain the true dietary diversity of the study population. Moreover, despite high dietary diversity being reported it would be worthwhile studying further the whole array of factors involved in the inadequate food consumption reported by the pregnant women. 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This study will help inform the government on possible strategies of enhancing maternal nutrition. I will explain to you about the research and you may thereafter decide to participate in the research or decline. Procedure to be followed I and my research assistants would like to ask you some questions about yourself and your household. In addition, we will also take your anthropometric measurement mid upper arm circumference (MUAC). Though your views are very important, you have the right to refuse participation in the study. You will get the same care and treatment whether you agree to join the study or not. The questionnaire will take about 1 hour and your cooperation is highly appreciated. Possible benefits The benefits from this study may not be directly anticipated but the findings may be useful to the relevant stakeholder in initiating interventions geared toward improving maternal and young child health. You will also benefit from understanding your current dietary and nutritional status and if found to have a problem, advice on appropriate action will be provided. 85 Possible Risks/Discomfort There are no foreseen risks associated with the study; however some questions to be asked might make you uncomfortable. If this happens you may refuse to answer the questions and you are at liberty to stop the interview at any time. Compensation Your participation to the study is voluntary and thus you are not entitled to any form of payment. Community consideration All those respondents with poor nutritional status will be given appropriate advice. Moreover, on completion of the study, the result finding will be disseminated to the relevant community stakeholders for appropriate actions. Care and protection of the study participants The research procedure will adequately be explained to the participants. This will assure them that no risk is associated with the study. They will also be informed of their right to withdraw from the study at any time without penalty. Confidentiality Whatever information you provide will be treated with utmost confidentiality and will not be used for any other purpose other than the purpose of the study. 86 If you have any questions you may contact; Willy Kiboi or Kenyatta University P.O BOX 43844 P.O BOX 43844 Nairobi, Kenya Nairobi, Kenya Tel: +254 722653111 Tel: +254 20 8710901 Respondent’s statement The above information regarding my participation in the study is clear to me and I voluntarily agree to participate. Respondent Signature/ Thumb print------------------------------------------ Date: ---------------------------------------------- Interviewer’s statement I certify that, I the undersigned have explained the purpose and procedure, the potential benefits and possible risks associated with participating in this study to the above individual. Interviewer Name ----------------------------------------------------------------------------- Signature------------------------------------------ Date: ---------------------------------------------- 87 APPENDIX A: BARUA YA UTANGULIZI NA IDHINI Mpendwa Mshiriki, Jina langu ni WILLY KAHANYA KIBOI kutoka Chuo Kikuu cha Kenyatta, idara ya chakula na lishe bora. Mimi nafanya utafiti juu ya malazi tofauti, ulaji madini, na hali ya lishe ya wanawake wajawazito katika kata ya Laikipia. Utafiti huu utasaidia kujulisha serikali kuhusu mikakati ya uwezekano wa kuimarisha lishe ya wajawazito. Nitakuelezea kuhusu utafiti huu na baada ya hapo unaweza kuamua kushiriki katika utafiti au kukataa. Utaratibu utakao fuatwa Mimi na wasaidizi wa utafiti wangu tungependa kukuliza baadhi ya maswali kuhusu wewe mwenyewe na kaya yako. Aidha, tutachukua kipimo cha (MUAC) itakayochukuliwa katika mzingo wa katikati juu ya mkononi chini ya kazi. Ingawa maoni yako ni muhimu sana, una haki ya kukataa kushiriki katika utafiti. Wewe utapata huduma na matibabu sawa kama utakubaliana kujiunga na utafiti au la. Dodoso itachukua takribani saa moja, na ushirikiano wako utapewa shukra sana. Faida zinazoweza kupatikana Faida kutokana na utafiti huu huwenda si wa moja kwa moja, lakini matokeo inaweza kuwa na manufaa muhimu kwa wadau katika kuanzisha hatua zinazolenga kuboresha uzazi na afya ya mtoto. Wewe pia utafaidika na kuelewa hali yako ya sasa ya malazi na lishe na kama kutapatikana kuwa na tatizo , ushauri juu ya hatua sahihi utatolewa. 88 Hatari / usumbufu unaowezekana hakuna hatari linaonekana kuhusishwa na utafiti huu; Hata hivyo baadhi ya maswali ya kuulizwa yanaweza kukupa wasiwasi. Kama hali hii itatokea, unaweza kukataa kujibu maswali hayo na uko na uhuru wa kusimamisha mahojiano wakati wowote. Fidia Ushiriki wako kwa utafiti huu ni wa hiari na hivyo hakuna aina yoyote ya malipo. Masuala ya Jamii Wale watakaohojiwa na kupatikana na lishe duni watapewa ushauri sahihi. Aidha, utafiti utakapokamilika, matokeo itasambazwa kwa wadau husika katika jamii kwa ajili ya kuchukua hatua zinazofaa Huduma na ulinzi wa washiriki wa utafiti Utaratibu wa utafiti utaelezewa vya kutosha kwa washiriki. Hii itawahakikishia kwamba hakuna hatari inayohusishwa na utafiti huu. Pia watajulishwa kuhusu haki yao ya kujiondoa katika utafiti wakati wowote bila adhabu Usiri Habari yoyote utakayotoa itabebwa na usiri mkumbwa na haitatumika kwa madhumuni mengine yoyote zaidi ya madhumuni ya utafiti. 89 Kama una maswali yoyote unaweza kuwasiliana na; Willy Kiboi ama Chuo Kikuu cha Kenyata SLP 43844 SLP 43844 Nairobi, Kenya Nairobi, Kenya Simu +254 722653111 Simu: +254 20 8710901 Taarifa ya Mshiriki Habari iliyopo hapo juu kuhusu ushiriki wangu katika utafiti ni wazi na mimi kwa hiari yangu nakubali kushiriki. Saini ama alama ya dole gumba-------------------------------------------------------- Tarehe ------------------------------------------------------- Taarifa ya Mhoji Ninathibitisha kwamba, mimi niliyetia sahihi hapa nilielezea mshiriki madhumuni, utaratibu, faida na uwezekano wa hatari zinazohusiana na kushiriki katika utafiti huu. Jina La Mhoji ------------------------------------------------- Saini -------------------------------------------------------- Tarehe ---------------------------------------------------------------------------------- 90 APPENDIX B: RESEARCHER ADMINISTERED QUESTIONNAIRE Dietary diversity, nutrient intake and nutritional status of pregnant women in Laikipia County MODULES 1. MD 1: Demographic and socio-economic characteristics 2. MD 2: Health information 3. MD 3: Dietary diversity and Dietary intake 4. MD 4: Anthropometric measurement Checked by: --------------------------------------------------------- 91 Administrative Details County ______________________ Location ______________________ Questionnaire Number |___||___||___||___| Date of Interview |___|___|/|___|___|/|___|___| MD 1: Demographic and socio-economic status Interviewer’s name________________________________________________________ Part A: Respondent Details 1.1 Respondent Code ______________________________________________________ 1.2 Age of the mother in completed year’s (confirm from ANC card) _____________ 1.3 Parity_____________ 1.4 Gestation in weeks_____________ 1.5 Marital status_____________ 1= Married 2 = Divorced/Separated 3 = Widow/Widowed 4 = Single 1.6 What is the highest level of education reached? (Respondent) _____________ 1 = Pre-school 2 = Primary incomplete 3 = Primary complete 4 = Secondary incomplete 5 = Secondary complete 6= College (certificate) 7 = College (Diploma) 8= University (degree) 9= Adult education 10= none 1.7 What is the Occupation of the respondent? 1= Farming 2=Casual labour 3=Employed (salaried) 4=Business 5= Housewife 6=Unemployed 7= Others (Specify) __________ Part B: Household composition and characteristics 1.8 How many people live in your *household? _____________ *Household= Members living together and sharing the same pot. 92 1.9 Who is the household head? 1=respondent 2=Husband 3=Child 4=Others (specify) 1.9.1 Sex of household head (skip if the respondent is the household head) 1=Male 2=Female 1.10 Occupation of household head (skip if the respondent is the household head) 1= Farming 2=Casual labour 3=Employed (salaried) 4=Business 5= Housewife 6=Unemployed 7= Others (Specify) __________ 1.11 What is the relationship between the household head and the respondent (skip if the respondent is the household head) 1. Husband 2. Child 3. Relatives 4. house help 1.12 What is the age of the household head? (skip if the respondent is the household head) 1.13 How many children do you have…………….. 1.14 How many children are below 5 years of age…………….. Part C: Household Wealth ranking 1.15 Please indicate the sources of income earned by the household ________________ 1= Agricultural farm produce 2= Business 3= Formal employment 4= Casual labour 5= Donations (Specify source) ___________ 6= any other specify ________________ 1.16 Please indicate the level of income earned by the household in last one month. 1. ≤2000 7. 20001- 30000 2. 2001- 4000 8. 30001- 40000 3. 4001- 6000 9. 40001- 50000 4. 6001- 8000 10. 50001- 100000 5. 8001- 10000 11. >100001 6. 10001- 20000 1.17 Who determines how family income will be used? 1=Respondent 2=Husband/Partner 3=Relative 4=Friend 5=Other (Specify) --------------- 93 Land status 1.18 Does the household have land? ______________ 1. Yes 2. No 1.19 If yes indicate the size of the land _______________acres 1.20 If yes, indicate the ownership status______________________ 1= Self owned 2. Hired=3. Public=land 4. Any other (specify) ___________________ 1.21 Where do you mainly get the food that you feed your family on? (One response only) ____________ 1= Home grown 2= Purchase 3= Farm Livestock 4= Donation 5= Other sources (specify) 1.212 Have you in the last 1 yr been a beneficiary of any food program? 1=Yes 2= No If yes, list the food program(s) i. -------------------------------- ii. -------------------------------- iii -------------------------------- 1.22 Are there any groups, association or clubs within your location? 1=yes 2=no 1.23 If yes, list them; tick if any are specifically for women and if the respondent belongs to any (tick) Name Any for women Any for respondent 1 2 3 4 5 6 94 Household Livestock, Assets and Communication 1.24 Does the household own any livestock? 1. Yes 2. No 1.25 If yes, what is the number of livestock owned in the household? 0= None 1=<5 2=5-10 3=>10-20 4=>20 Livestock Code Livestock Code Cattle Pigs Goats Ducks Sheep Rabbits Donkey Other (specify) chicken 1.26 Does the household own any of the following household items? Item 1=Yes 2=No Item 1=Yes 2=No Item 1=Yes 2=No Vehicle Sofa set Television Motorcycle Computer Refrigerator Bicycle Landline Oven/cooker/meko Wheel barrow Mobile phone Solar panel Tractor Radio Other (specify) 1.27 How many times in a week do you access the following No of times in a week Code Item No of times in a week code Mobile phone (call) News paper Mobile phone(text) Social worker Radio Barazas(community gatherings) Television Church/Mosque Internet 0=None 1=Once 2= twice 3= Thrice 4= more than three times 5=None 1.28 Where do you live? 1=Rented house 2=Own house 95 1.29 Materials used to make the house 1.30 Please indicate the materials the house is made up of a) Walls _____________ 1=Mud 2=Wood 3=Bricks 4=Iron sheets 5=Any other specify ___ b) Roof_______________ 1=Iron sheets 2=Grass 3=Concrete 4=Tiles 5= Any other specify __________ c) Floor _____________________ 1=Mud 2=Wood 3=Concrete 4=Tiles 5=Any other specify __________ 1.31 What is your main source of water? _________________ 1= Piped into the house 2=Piped to a tap on property outside the house 3= Rain tanks on property 4:=Communal tap 5=Communal well 7= River 1.32 Please indicate your main source of cooking fuel 1=Firewood 2=Charcoal 3=Kerosene 4=Gas 5=Any other (specify) _______________ 1.33 Please indicate your main source of lighting 1=Electricity 2= Pressure lamp 3=Kerosene lamp 4= Any other (specify) ____ MD 2: Health Information (Morbidity patterns) 2.1 Have you suffered from any disease for the last two weeks?________ 1 = yes 2 =No 2.2 If yes, state the illness and its duration. Type of illness Duration of illness 1=Anorexia 2=Vomiting 3=Fever 4=Constipation 5=Malaria 6=Diarrhoea 7=Anaemia 8=STI 9=Any other (specify) 2.3 Did you seek medical attention? 1= yes 2= no 96 2.4 If yes where? 1=government hospital 2=private hospital 3= traditional medicine 4=others (specify) -------- 2.5 How many times have you attended the antenatal clinic? 0=None 1=once 2=twice 3=thrice 4= more than three times Micronutrient supplementation 2.6 Are you taking any micronutrient supplements currently? 1=Yes 2=No 2.7 If yes, which ones? 1= Folic acid supplements 2=Multiple micronutrient supplement 3= others (Specify) ------------ 2.8 If yes, where did you get them from? 1=Health facility 2=Bought from the shops 2.9 If no, why not? 1=don’t see their need 2=not available at ANC 3=they make me sick 4=any other (specify) -------------------- MD3: Dietary Intake/Diversity 3.1 Recording form for 24hr recall of foods and drinks consumed by the respondent Establish the drink/foods the respondent consumed in the previous day starting from the time she woke up to the time she went to sleep whether at home or outside the home. Establish the meals taken per day, ingredients and the amount in the meals, the volume of the food cooked the volume of the food taken and calculate the amount of ingredients consumed in grams by the respondent? 3.1.1 Confirm if the day was usual or unusual 1= usual day 2= unusual 3.2.2 If unusual, explain why 1=Celebration 2=Religious activity 3=Little food in household 4=Other (specify) 97 24-Hour dietary recall Official use Time/ Meal Type of the dish/Food name Ingredients HH measure Amt in Grams Vol cooked Vol served Vol taken Amt taken gms Breakfast Snack 1 Lunch 98 Snack 2 Supper Snack 3 99 3.2 DIETARY DIVERSITY QUESTIONNAIRE Fill in the food groups based on the 24 hour recall information recorded above. For any food groups not mentioned, ask the respondent if a food item from this group was consumed. Question number Food group Examples YES=1 NO=0 1 CEREALS corn/maize, rice, wheat, sorghum, millet or any other grains or foods made from these (e.g. bread, noodles, porridge or other grain products) + insert local foods e.g. ugali, nshima, porridge or pastes 2 WHITE ROOTS AND TUBERS white potatoes, white yam, white cassava, or other foods made from roots 3 VITAMIN A RICH VEGETABLES AND TUBERS pumpkin, carrot, squash, or sweet potato that are orange inside + other locally available vitamin A rich vegetables (e.g. red sweet pepper) 4 DARK GREEN LEAFY VEGETABLES dark green/leafy vegetables, including wild forms + locally available vitamin A rich leaves such as amaranth, cassava leaves, kale, spinach 5 OTHER VEGETABLES other vegetables (e.g. tomato, onion, eggplant) + other locally available vegetables 6 VITAMIN A RICH FRUITS ripe mango, cantaloupe, apricot (fresh or dried), ripe papaya, dried peach, and 100% fruit juice made from these + other locally available vitamin A rich fruits 7 OTHER FRUITS other fruits, including wild fruits and 100% fruit juice made from these 8 ORGAN MEAT liver, kidney, heart or other organ meats or blood-based foods 9 FLESH MEATS beef, pork, lamb, goat, rabbit, game, chicken, duck, other birds, insects 10 EGGS eggs from chicken, duck, guinea fowl or any other egg 11 FISH AND SEAFOOD fresh or dried fish or shellfish 12 LEGUMES, NUTS AND SEEDS dried beans, dried peas, lentils, nuts, seeds or foods made from these (e.g. hummus, peanut butter) 13 MILK AND MILK PRODUCTS milk, cheese, yogurt or other milk products 14 OILS AND FATS oil, fats or butter added to food or used for cooking 15 SWEETS sugar, honey, sweetened soda or sweetened juice drinks, sugary foods such as chocolates, candies, cookies and cakes 16 SPICES, CONDIMENTS, BEVERAGES spices (black pepper, salt), condiments (soy sauce, hot sauce), coffee, tea, alcoholic beverages Individual level Did you eat anything (meal or snack) OUTSIDE the home yesterday? 100 MD 4: Nutritional status: Anthropometric Measurement 4.1 MUAC of the respondent in centimeters (to the nearest 0.1cm). First reading Second reading Average MUAC 4.2 Hb of the respondents in g/dl.............. 101 APPENDIX B: DODOSO LINALOSIMAMIWA NA MTAFITI Malazi tofauti, ulaji madini na hali ya lishe ya wanawake wajawazito katika kata ya Laikipia. MODULI 1. MD 1: Demografia na hali ya jamii ya kiuchumi 2. MD 2: Habari za afya 3. MD 3: Malazi tofauti na ulaji 4. MD 4: Vipimo Imeangaliwa na: ------------------------------- 102 Maelezo ya Tawala Kata ______________________ Eneo ______________________ Nambari ya dodoso |___||___||___||___|Tarehe ya mahojiano |___|___|/|___|___|/|___|___| MD 1: Demographia na hali ya kiuchumi ya jamii Jina la mhoji________________________________________________________ Sehemu A: Maelezo ya mshiriki 1.1 Nambari ya utambulisho ya mshiriki _____________________________________ 1.2 Umri wa mama katika miaka iliyokamilika (Thibitisha kutoka kwa kadi ya ANC) _____________ 1.2 Idadi ya mimba ya mama_____________ 1.4 Umri wa Ujauzito (katika kipindi cha wiki )_____________ 1.5 Hali ya ndoa_____________ 1= Oleka 2 = Talikiwa/Tengana 3 = Mjane 4 = Asiyeoleka kamwe 1.6 Je, ni kiwango kipi cha juu cha elimu kufikiwa ? ( Mhojiwa )_____________ 1 = Kabla ya shule ya msingi 2 = Shule ya msingi isiyomaliziwa 3 = Shule ya msingi iliyomaliziwa 4 = Shule ya sekondari isiyomaliziwa 5 = Shule ya sekondari iliyomaliziwa 6= Chuo (cheti) 7 = Chuo (Stashahada) 8= Chuo kikuu (shahada) 9= Elimu ya watu wazima 10= Hakuna elimu yoyote 1.7 Kazi ya mhojiwa? 1= Kilimo 2=Kazi ya kawaida 3=Ajira (mshahara) 4=Biashara 5= Mama wa nyumba 6=Mkosa ajira 7= Nyingine yeyote (Taja) __________ Sehemu B: Utungaji na sifa za kaya 1.8 Watu wangapi wanaishi katika * kaya yako? _____________ *Kaya = Wanaoishi pamoja na kushirikiana sufuria moja ya chakula 1.9 Jinsia ya mkuu wa kaya (ruka kama mhojiwa ni mkuu wa kaya ) 1 = Kiume 2 = Kike 1.10 Kazi ya mkuu wa kaya (ruka kama mhojiwa ni mkuu wa kaya) 103 1= Kilimo 2=Kazi ya kawaida 3=Ajira (mshahara) 4=Biashara 5= Mama wa nyumba 6=mkosa ajira 7= Nyingine yeyote (Taja) __________ 1.11 uhusiano kati ya kaya kichwa na mhojiwa (ruka kama mhojiwa ni mkuu wa kaya ) 1. Mume 2. Mtoto 3. Jamaa 4. msaadisi wa nyumba 1.12 Umri wa mkuu wa kaya? (ruka kama mhojiwa ni mkuu wa kaya) 1.13 una watoto wangapi? …………….. 1.14 Una watoto wangapi walio chini ya miaka tano?…………….. Sehemu C: Mali ya kaya 1.15 Tafadhali onyesha vyanzo vya mapato ya kaya ________________ 1= Uzalishaji wa shamba 2= Biashara 3= Ajira rasmi 4= Kazi ya kawainda 5=Michango (Taja Chanzo) ___________ 6= Nyingine yoyote (Taja) ________________ 1.16 Tafadhali onyesha kiwango cha mapato ya kaya katika mwisho wa mwezi mmoja uliopita. 7. <2000 7. 20001- 30000 8. 2001- 4000 8. 30001- 40000 9. 4001- 6000 9. 40001- 50000 10. 6001- 8000 10. 50001- 100000 11. 8001- 10000 11. >100001 12. 10001- 20000 1.17 Nani huamua jinsi mapato ya familia zitatumika? 1=Mhojiwa 2=Mume 3=Jamaa 4=Rafiki 5=Nyingine (Taja) ------------ Hali ya shamba 1.18 Je, kaya inamiliki shamba? ______________ 1. Ndiyo 2. La 1.19 Kama ndiyo onesha ukubwa _______________(katika ekari) 1.20 Kama ndiyo, onyesha hali ya umiliki______________________ 1= inayomilikiwa kibinafsi 2. Iliyokodiwa =3. Inayomilikiwa na umma 4. Nyingine yeyote (Taja) ___________________ 1.21 Wapi hasa unapopata chakula cha kulisha familia yako? (Jibu moja pekee) ____________ 1= Kukuza nyumbani 2= Ununuzi 3= Mifugo wa shamba 4= Mchango 5= Nyingine yeyote (Taja) 104 1.212 Je, kwa wakati wa mwaka moja uliopita umelengwa na mpango wowote wa chakula? 1=Ndiyo 2= Hapana Kama ndiyo, orodhesha i. -------------------------------- ii. -------------------------------- iii -------------------------------- 1.22 Je, kuna makundi, chama au klabu ndani ya eneo lako?? 1=Ndiyo 2=Hakuna 1.23 Kama ndiyo, orodha yao; onyesha kama yoyote mahsusi ni kwa ajiili ya wanawake na kama mhojiwa ako kwa yoyote? Name Any for women Any for respondent 1 2 3 4 5 6 Mifugo, mali na mawasiliano ya kaya 1.24 Je, kaya inamiliki mifugo yoyoye ? 1. Ndiyo 2. Hakuna 1.25 Kama ndiyo, ni nini idadi ya mifugo inayomilikiwa katika kaya? 1=<5 2=5-10 3=>10-20 4=>20 Livestock Code Livestock Code Ngombe Nguruwe Mbuzi Mbata Kondoo Sungura Punda Nyingine (Taja) Kuku 105 1.26 Kaya inamiliki vitu vifuatazo? Bidhaa 1=Ndiyo 2=Hapana Bidhaa 1=Ndiyo 2=Hapana Bidhaa 1=Ndiyo 2=Hapana Gari Kiti cha sofa Televisheni Motorcycle Kompyuta Jokovu Baiskeli Simu ya mezani Tanuri/Jiko/gesi Toroli Simu ya rukono Jopo nishati ya jua Trekta Radio Nyingine(Taja) 1.27 Ni mara ngapi kwa wiki wewe hutumia zifuatazo? Mara katika wiki (code) bidhaa Mara katika wiki (code) Simu ya mkononi (wito) Gazeti Mobile phone(Ujumbe wa mandishi) Mfanyi kazi wa kijamii Radio Mabaraza(mkusanyiko wa jamii) Televisheni Kanisa/Msikiti Mtandao 1=Mara moja 2= Mara mbili 3= Mara tatu 4= Zaidi ya mara tatu 5=Hakuna 1.28 Je unaishi wapi? 1=Nyumba ya kukodiwa 2=Nyumba ya kibinafsi 1.29 Vifaa vilivyotumika kujenga nyumba 1.30 Tafadhali onyesha vifaa vilivyotumika kujenga nyumba a) Ukuta_____________ 1=Matope 2=Mbao 3=Matofali 4=Mabati 6=Nyingine yoyote (taja) ___ b) Paa_______________ 1=Mabati 2=Nyasi 3=Saruji 4=Tiles 5= Nyingine yoyote (taja)__________ c) Sakafu _____________________ 1=Matope 2=Mbao 3=Saruji 4=Tiles 5=Nyingine yoyote (taja) __________ 106 1.31 Nini nyenzo yako kuu ya maji? _________________ 1= Mboba ndani ya nyumba 2=mboba nje ya nyumba 3= Mizinga ya mvua 4:=mboba ya jumuiya 5=Kisima cha jumuiya 7= Mto 1.32 Tafadhali onyesha nyenzo kuu ya nishati ya upishi 1=Kuni 2=Makaa 3=Mafuta ya taa 4=Gesi 5=Nyingine yoyote (Taja) _______________ 1.33 Tafadhali onyesha nyezo yako kuu ya mwangaza? 1=Umeme 2= Taa la shinikizo 3=Taa ya mafuta 4=Nyingine yoyote (Taja) ____ MD 2: Habari za afya (Chati cha maradhi) 2.1 Je, umepata ugojwa wowote kwa wiki mbili zilizopita?________ 1 = Ndiyo 2 =Hapana 2.2 Kama ndiyo, taja ugojwa na muda uliochukua. Aina ya ugojwa Muda wa ugojwa 1=Kukosa hamu 2=Kutapika 3=Homa 4=Kuvimbiwa 5=Malaria 6=Kuhara 7=Anemia 8=Magojwa ya zinaa 9=Nyingine yoyote (taja) 2.3 Je, ulitafuta matibabu? 1= Ndiyo 2= La 2.4 Kama ndiyo, wapi? 1=hospitali ya serikali 2=hospitali binafsi 3= dawa za jadi 4=Nyingine yoyote (Taja) -------- 2.5 Ni mara ngapi umehudhuria kliniki ya wajawazito? 1=mara moja 2=mara mbili 3=mara tatu 4= zaidi ya mara tatu Matone ya kuongeza lishe 2.6 Je, wewe unachukua virutubisho lishe yoyote kwa sasa? 1=Ndiyo 2=La 2.7 Kama ndiyo, gani,? 1= Virutubisho vya folic 2=Virutubisho nyingi za matone 3= Nyingine yoyote (Taja) ------------ 107 2.8 Kama ndiyo, ulizipata kutoka wapi? 1=Kituo cha afya 2=Kununuliwa kutoka kwa maduka 2.9 Kama hakuna, Kwa nini? 1=Sioni haja yazo 2=Haipatikani katika ANC 3=zinanifanya mgojwa 4=Nyingine yoyote (Taja) -------------------- MD3: Malazi tofauti na ulaji 3.1 Fomu ya kurekodi vyakula na vinywanji vilivyotumiwa masaa 24 iliyopita na mhojiwa. Uliza vyakula na vinywanji mhojiwa alizotumia siku iliyopita kuanzia alipoamka asubuhi hadi alipolala usiku kwa nyumba yake au nje ya nyumba yake. Uliza chakula iliyotumiwa kwa siku, viungo na kiasi katika milo, kiasi cha chakula kupikwa, kiasi cha chakula kilicholiwa na uhesabu kiasi cha viungo zilizotumiwa katika gramu na mhojiwa? 3.1.1 Thibitisha kama siku ilikuwa ya kawaida au siyo ya kawaida 1= siku ya kawaida 2= siku isiyo ya kawaida 3.2.2 Kama si ya kawaida, elezea kwa nini? 1=Sherehe 2=Shughuli ya kidini 3=Chakula kidogo katika kaya 4=Nyingine (Taja) 108 Masaa 24 malazi kumbuka Matumizi rasmi Wakati/ Chakula Aina ya chakula/Jin a ya chakula Viungo Kipimo cha kaya Kiasi katika gramu Kiasi kupikwa Kiasi pakuliwa Kiasi kuliwa Kiasi kuliwa katika gramu Kifungua kinywa Kitafunio 1 Chakula cha 109 mchana Kitafunio 2 Karamu Kitafunio 3 110 3.2 DODOSO LA MALAZI TOFAUTI Jaza makundi ya chakula kulingana na taarifa ya malazi kumbuka iliyoandikwa hapo juu. Kwa makundi yoyote ya chakula yenye haikutajwa, uliza mhojiwa kama kuna bidhaa ya chakula kutoka kundi hilo alikula. Nambari ya swali Kundi la chakula Mifano Ndiyo=1 La=0 1 NAFAKA mkate, tambi (supagetti), biskuti, mandazi, samosa au vyakula vingine vyovyote vilivyotengenezwa kutoka kwa mtama, wimbi, mahindi, mchele au ngano, kwa mfano: ugali, uji n.k. 2 VIAZI VYEUPE NA VYAKULA VYA MIZIZI viazi vya mboga, viazi vitamu vyeupe, nduma, mhogo au vyakula vilivyo tengenezwa kutokana na mizizi 3 MBOGA NA VIAZI VILIVYO NAWINGI WA VITAMINI A matango, karoti, viazi tamu vya manjano + vyakula vingine vipatikanvyo vyenye wingi wa vitamini A 4 MBOGA ZA MAJANI ZENYE WINGI WA RANGI YA KIJANI KIBICHI Sukuma wiki, mchicha, mnavu, mkunde, kigwada, bwere, mchunga, mchicha, mzungi, majani ya matango + mboga zingine zozote za majani yenye wingi wa rangi ya kijani kibichi 5 MBOGA ZINGINE nyanya, kitunguu maji, hoho, biringanya, kabichi, tunguja, pilipili, mamumunye, n.k. 6 MATUNDA YENYE WINGI WA VITAMINI A maembe yaliyoiva, paipai n.k. 7 MATUNDA MENGINE machungwa, ndimu, ndizi, mapera, nanasi, matikiti, passion, kunazi, pepeta, vitoria, mkwaju, chenza, madafu, matunda ya damu (tree tomato), zabibu, avocado (parachichi) n.k. 8 NYAMA YA VIUNGO ini, figo, moyo au nyama ya chombo nyingine au vyakula damu 111 9 NYAMA nyama ya ng'ombe, nguruwe, kondoo, mbuzi, sungura, nyama ya mwituni, nyama ya kuku au bata au ndege wengine, nyama ya wadudu kama kumbikumbi, panzi, nyama ya mamba n.k. 10 MAYAI Mayai ya kuku, bata, ndege n.k. 11 SAMAKI NA DAGAA samaki asiyekaushwa au aliyekaushwa, omena, papa, simu, kamba, ngege, mbuta, kweza, kaa n.k. 12 BOROHOA, NJUGU AU KOROSHO NA MBEGU maharagwe, ufuta, mbaazi, kunde, ndengu, pojo, soya, njugu mawe, minji, njahi, au vyakula vingine vitokanavyo na hivi vilivyotajwa 13 MAZIWA NA VYAKULA VYOTE VINAVYOTOKA KWA MAZIWA maziwa, maziwa lala, cheese, yogurt n.k. 14 MAFUTA mafuta ya kupikia, mafuta ya samaki, mafuta ya nguruwe, siagi, mafuta ya nasi n.k. 15 VYAKULA VYA SUKARI sukari, asali, soda yenye sukari, sukari nguru, kaimati, miwa, chokoleti, peremende, icecream, barafu (ice) 16 VIUNGO, CHAI AU KAHAWA NA VILEO viungo kama vile tangawizi, mdalasini, binzari, dhania, kitunguu saumu, karafuu, iliki n.k.; kahawa, chai; vileo kama chang'aa, mnazi, matingasi/busaa, mukoma n.k. Ngazi ya kibinafsi Je, ulikula kitu chochote (mlo au vitafunio) nje ya nyumba jana? 112 MD 4: Hali ya lishe: Vipimo 4.1 MUAC ya mhojiwa katika sentimita (kwa karibu zaidi ya 0.1sentimita). Kwanza kusoma Pili kusoma Wastani MUAC 4.2 Kipimo cha Himoglobini g/dl.................... 113 APPENDIX C: KEY INFORMANT INTERVIEW SCHEDULE Dietary diversity, nutrient intake and nutritional status of pregnant women in Laikipia County Information obtained from the participant(s) will be treated with utmost confidentiality and will only be used for the purpose of this study. Doctor/Nurse/Nutritionist Respondent Code _______________________________Position___________________ Date of Interview ________________________________________________________ 1. Do you believe that poor diet is a problem among pregnant women in this area? Yes ( ) No ( ) 2. What nutritional services are available to the pregnant women in this area? 3. a) What are the most common types of complications among pregnant women in this area? b) Do these complications among pregnant women affect their dietary intake? 4. What do you think are the best solution to solve malnutrition among pregnant women? 5. a) Would it be possible for policy makers in this area to help address the problem of pregnancy malnutrition in this area? b) If yes, how do you think they could help? Thank you for taking the time to participate in this interview 114 APPENDIX D: FOCUS GROUP DISCUSSION GUIDE Dietary diversity, nutrient intake and nutritional status of pregnant women in Laikipia County Date of discussion ________________________________________________________ 1. What foods are mostly consumed in this area? 2. Does what you eat change when you are pregnant? Yes/No - If yes, how? 3. What are some of the nutrition messages you get during pregnancy? - State the sources of the information 4. Do you belief that what you eat have an influence on the health of the infant? Yes/No - If yes how? 5. What foods should be avoided during pregnancy? Give reasons 6. Are there specific foods that must be taken during pregnancy? If yes, state them 7. What determines your choice of food during pregnancy? 8. Do we have food seasonality in this area? If yes describe the seasons and state if they affect your food consumption patterns? 9. Suggest ways that can be adopted to promote dietary diversity among pregnant women in this area? Thank you for taking the time to participate in this discussion. 115 APPENDIX D: MWONGOZO WA MAJANDILIANO (FGD) Malazi tofauti, ulaji madini na hali ya lishe ya wanawake wajawazito katika kata ya Laikipia. Tarehe ya majandiliano ____________________________________________________ 1. Ni aina gani ya vyakula zinazotumiwa zaidi katika eneo hili? 2. Je, kunamabadiliko ya unacho kula unapokuwa majamzito? Ndiyo/La - Kama ndiyo, ni jinsi gani? 3. Je, ni baadhi ya unjumbe mgani wa lishe wewe hupata wakati waujauzito - Taja chenzo cha habari hizo? 4. Unaamini kwamba unachokula kina ushawishi zidi ya afya ya mtoto mchanga? Ndiyo/La - Kama ndiyo, jinsi gani? 5. Ni aina gani ya vyakula vinafaa kuepukwa wakati wa ujauzito? Toa sababu 6. Je, kuna vyakula maalum ambazo lazima zichukuliwe wakati wa ujauzito? Kama ndiyo, taja ni gani 7. Nini huamua uchaguzi wako wa chakula wakati wa ujauzito? 8. Je, kuna majira ya chakula katika eneo hili? Kama ndiyo elezea majira hayo na taja kama yanaathiri uchaguzi wako wa chakula? 9. Pendekeza njia zinazoweza kuchukuliwa kukuza ulaji wa malazi tofauti kati ya wanawake wajawazito katika eneo hili? Asante kwa kuchukua muda wa kushiriki katika mjadala huu. 116 APPENDIX E: MAP OF LAIKIPIA COUNTY, KENYA Source: Map data (2015) by Google 117 APPENDIX F: RESEARCH PERMIT AND AUTHORIZATION 118 119