Kenya - Multiple Indicator Cluster Survey - 2014

Publication date: 2014

Bungoma County, Kenya Multiple Indicator Cluster Survey 2013/14 Final Report February, 2016 Bungoma County MICS 2013/14 The Bungoma County Multiple Indicator Cluster Survey (MICS) was carried out in 2013/14 by the Population Studies and Research Institute, University of Nairobi, in collaboration with Kenya National Bureau of Statistics, as part of the global MICS programme. Technical support was provided by the United Nations Children’s Fund (UNICEF). UNICEF provided financial support. The global MICS programme was developed by UNICEF in the 1990s as an international household survey programme to support countries in the collection of internationally comparable data on a wide range of indicators on the situation of children and women. MICS surveys measure key indicators that allow countries to generate data for use in policies and programmes, and to monitor progress towards the Millennium Development Goals (MDGs) and other internationally agreed upon commitments. Suggested citation: Kenya National Bureau of Statistics, Population Studies and Research Institute and United Nations Children’s Fund. 2016. Bungoma County Multiple Indicator Cluster Survey 2013/14, Final Report. Nairobi, Kenya: Kenya National Bureau of Statistics, Population Studies and Research Institute and United Nations Children’s Fund. Bungoma County MICS 2013/14 P a g e | ii Summary Table of Survey Implementation and the Survey Population, Bungoma County MICS, 2013/14 Survey implementation Sample frame Updated National Sample Survey and Evaluation Programme V (NASSEP V) November 2013 Questionnaires Household Women (age 15-49) Children under-five Interviewer training October 2013 Fieldwork November 2013 to January 2014 Survey sample Households Sampled Occupied Interviewed Response rate (Percent) 1,500 1,316 1,246 94.7 Children under-five Eligible Mothers/caretakers interviewed Response rate (Percent) 874 846 96.8 Women Eligible for interviews Interviewed Response rate (Percent) 1,373 1,213 88.3 Survey population Average household size 4.8 Percentage of population living in Urban areas Rural areas 45.1 54.9 Percentage of population under: Age 5 Age 18 15.0 55.2 Percentage of women age 15-49 years with at least one live birth in the last 2 years 25.6 Housing characteristics Household or personal assets Percentage of households with Electricity Finished floor Finished roofing Finished walls 14.8 36.6 94.9 29.3 Percentage of households that own A television A refrigerator Agricultural land Farm animals/livestock 23.0 3.6 79.5 68.9 Mean number of persons per room used for sleeping 3.02 Percentage of households where at least a member has or owns a Mobile phone Car or truck 81.8 4.3 Bungoma County MICS 2013/14 P a g e | iii Summary Table of Findings1 Multiple Indicator Cluster Surveys (MICS) and Millennium Development Goals (MDG) Indicators, Bungoma County MICS, 2013/14 NUTRITION Breastfeeding and infant feeding MICS Indicator Indicator Description Value 2.5 Children ever breastfed Percentage of women with a live birth in the last 2 years who breastfed their last live-born child at any time 97.3 2.6 Early initiation of breastfeeding Percentage of women with a live birth in the last 2 years who put their last newborn to the breast within one hour of birth 50.8 2.7 Exclusive breastfeeding under 6 months Percentage of infants under 6 months of age who are exclusively breastfed 43.1 2.8 Predominant breastfeeding under 6 months Percentage of infants under 6 months of age who received breast milk as the predominant source of nourishment during the previous day 58.5 2.9 Continued breastfeeding at 1 year Percentage of children age 12-15 months who received breast milk during the previous day 75.3 2.10 Continued breastfeeding at 2 years Percentage of children age 20-23 months who received breast milk during the previous day 40.2 2.11 Median duration of breastfeeding The age in months when 50 percent of children age 0-35 months did not receive breast milk during the previous day 20.8 2.12 Age-appropriate breastfeeding Percentage of children age 0-23 months appropriately fed during the previous day 63.5 2.13 Introduction of solid, semi-solid or soft foods Percentage of infants age 6-8 months who received solid, semi-solid or soft foods during the previous day 81.4 2.14 Milk feeding frequency for non-breastfed children Percentage of non-breastfed children age 6-23 months who received at least 2 milk feedings during the previous day (25.2) 2.15 Minimum meal frequency Percentage of children age 6-23 months who received solid, semi-solid and soft foods (plus milk feeds for non- breastfed children) the minimum number of times or more during the previous day 49.2 2.16 Minimum dietary diversity Percentage of children age 6–23 months who received foods from 4 or more food groups during the previous day 41.8 2.17a 2.17b Minimum acceptable diet (a) Percentage of breastfed children age 6–23 months who had at least the minimum dietary diversity and the minimum meal frequency during the previous day (b) Percentage of non-breastfed children age 6–23 months who received at least 2 milk feedings and had at least the minimum dietary diversity not including milk feeds and the minimum meal frequency during the previous day 23.9 (16.3) 2.18 Bottle feeding Percentage of children age 0-23 months who were fed with a bottle during the previous day 15.6 Salt iodization 2.19 Iodized salt consumption Percentage of households with salt testing 15 parts per million or more of iodate 94.4 Low-birthweight 2.20 Low-birthweight infants Percentage of most recent live births in the last 2 years weighing below 2,500 grams at birth 5.3 1 See Appendix G for a detailed description of MICS indicators Bungoma County MICS 2013/14 P a g e | iv 2.21 Infants weighed at birth Percentage of most recent live births in the last 2 years who were weighed at birth 47.3 ( ) Figures that are based on 25-49 unweighted cases CHILD HEALTH Vaccinations MICS Indicator Indicator Description Value 3.1 Tuberculosis immunization coverage Percentage of children age 12-23 months who received BCG vaccine by their first birthday 95.7 3.2 Polio immunization coverage Percentage of children age 12-23 months who received the third dose of OPV vaccine (OPV3) by their first birthday 77.5 3.3 Diphtheria, pertussis and tetanus (DPT) immunization coverage Percentage of children age 12-23 months who received the third dose of DPT vaccine (DPT3) by their first birthday 87.7 3.4 MDG 4.3 Measles immunization coverage Percentage of children age 12-23 months who received measles vaccine by their first birthday 91.8 3.5 Hepatitis B immunization coverage Percentage of children age 12-23 months who received the third dose of Hepatitis B vaccine (HepB3) by their first birthday 81.1 3.6 Haemophilus influenzae type B (Hib) immunization coverage Percentage of children age 12-23 months who received the third dose of Hib vaccine (Hib3) by their first birthday 83.9 3.8 Full immunization coverage Percentage of children age 12-23 months who received all vaccinations recommended in the national immunization schedule by their first birthday 56.3 Tetanus toxoid 3.9 Neonatal tetanus protection Percentage of women age 15-49 years with a live birth in the last 2 years who were given at least two doses of tetanus toxoid vaccine within the appropriate interval prior to the most recent birth 53.8 Diarrhoea - Children with diarrhoea Percentage of children under age 5 with diarrhoea in the last 2 weeks 11.9 3.10 Care-seeking for diarrhoea Percentage of children under age 5 with diarrhoea in the last 2 weeks for whom advice or treatment was sought from a health facility or provider 46.2 3.11 Diarrhoea treatment with oral rehydration salts (ORS) and zinc Percentage of children under age 5 with diarrhoea in the last 2 weeks who received ORS and zinc 13.1 3.12 Diarrhoea treatment with oral rehydration therapy (ORT) and continued feeding Percentage of children under age 5 with diarrhoea in the last 2 weeks who received ORT (ORS packet, pre-packaged ORS fluid, recommended homemade fluid or increased fluids) and continued feeding during the episode of diarrhoea 67.6 Acute Respiratory Infection (ARI) symptoms - Children with ARI symptoms Percentage of children under age 5 with ARI symptoms in the last 2 weeks 3.8 3.13 Care-seeking for children with ARI symptoms Percentage of children under age 5 with ARI symptoms in the last 2 weeks for whom advice or treatment was sought from a health facility or provider (51.5) 3.14 Antibiotic treatment for children with ARI symptoms Percentage of children under age 5 with ARI symptoms in the last 2 weeks who received antibiotics (53.0) Bungoma County MICS 2013/14 P a g e | v Solid fuel use 3.15 Use of solid fuels for cooking Percentage of household members in households that use solid fuels as the primary source of domestic energy to cook 96.1 Malaria / Fever MICS Indicator Indicator Description Value - Children with fever Percentage of children under age 5 with fever in the last 2 weeks 19.8 3.16a 3.16b Household availability of insecticide-treated nets (ITNs) Percentage of households with (a) at least one ITN (b) at least one ITN for every two people 78.0 44.5 3.17a 3.17b Household vector control Percentage of households (a) with at least one ITN or that have been sprayed by IRS in the last 12 months (b) with at least one ITN for every two people or that have been sprayed by IRS in the last 12 months 78.4 45.4 3.18 MDG 6.7 Children under age 5 who slept under an ITN Percentage of children under age 5 who slept under an ITN the previous night 62.9 3.19 Population that slept under an ITN Percentage of household members who slept under an ITN the previous night 57.0 3.20 Care-seeking for fever Percentage of children under age 5 with fever in the last 2 weeks for whom advice or treatment was sought from a health facility or provider 53.8 3.21 Malaria diagnostics usage Percentage of children under age 5 with fever in the last 2 weeks who had a finger or heel stick for malaria testing 29.2 3.22 MDG 6.8 Anti-malarial treatment of children under age 5 Percentage of children under age 5 with fever in the last 2 weeks who received any antimalarial treatment 45.8 3.23 Treatment with Artemisinin-based Combination Therapy (ACT) among children who received anti- malarial treatment Percentage of children under age 5 with fever in the last 2 weeks who received ACT (or other first-line treatment according to national policy) 50.4 3.24 Pregnant women who slept under an ITN Percentage of pregnant women who slept under an ITN the previous night 70.3 3.25 Intermittent preventive treatment for malaria during pregnancy Percentage of women age 15-49 years who received three or more doses of SP/Fansidar, at least one of which was received during an ANC visit, to prevent malaria during their last pregnancy that led to a live birth in the last 2 years 22.9 WATER AND SANITATION MICS Indicator Indicator Description Value 4.1 MDG 7.8 Use of improved drinking water sources Percentage of household members using improved sources of drinking water 86.7 4.2 Water treatment Percentage of household members in households using unimproved drinking water who use an appropriate treatment method 68.9 4.3 MDG 7.9 Use of improved sanitation Percentage of household members using improved sanitation facilities which are not shared 49.7 4.4 Safe disposal of child’s faeces Percentage of children age 0-2 years whose last stools were disposed of safely 89.5 4.5 Place for handwashing Percentage of households with a specific place for hand washing where water and soap or other cleansing agent are present 5.4 Bungoma County MICS 2013/14 P a g e | vi WATER AND SANITATION MICS Indicator Indicator Description Value 4.6 Availability of soap or other cleansing agent Percentage of households with soap or other cleansing agent 70.5 REPRODUCTIVE HEALTH Contraception and unmet need MICS Indicator Indicator Description Value - Total fertility rate Total fertility rate for women age 15-49 years 4.5 5.1 MDG 5.4 Adolescent birth rate Age-specific fertility rate for women age 15-19 years 66 5.2 Early childbearing Percentage of women age 20-24 years who had at least one live birth before age 18 29.8 5.3 MDG 5.3 Contraceptive prevalence rate Percentage of women age 15-49 years currently married or in union who are using (or whose partner is using) a (modern or traditional) contraceptive method 54.4 5.4 MDG 5.6 Unmet need Percentage of women age 15-49 years who are currently married or in union who are fecund and want to space their births or limit the number of children they have and who are not currently using contraception 22.5 Maternal and newborn health 5.5a 5.5b MDG 5.5 MDG 5.5 Antenatal care coverage Percentage of women age 15-49 years with a live birth in the last 2 years who were attended during their last pregnancy that led to a live birth (a) at least once by skilled health personnel (b) at least four times by any provider 91.3 50.3 5.6 Content of antenatal care Percentage of women age 15-49 years with a live birth in the last 2 years who had their blood pressure measured and gave urine and blood samples during the last pregnancy that led to a live birth 80.0 5.7 MDG 5.2 Skilled attendant at delivery Percentage of women age 15-49 years with a live birth in the last 2 years who were attended by skilled health personnel during their most recent live birth 50.7 5.8 Institutional deliveries Percentage of women age 15-49 years with a live birth in the last 2 years whose most recent live birth was delivered in a health facility 46.3 5.9 Caesarean section Percentage of women age 15-49 years whose most recent live birth in the last 2 years was delivered by caesarean section 2.8 Post-natal health checks 5.10 Post-partum stay in health facility Percentage of women age 15-49 years who stayed in the health facility for 12 hours or more after the delivery of their most recent live birth in the last 2 years 67.9 5.11 Post-natal health check for the newborn Percentage of last live births in the last 2 years who received a health check while in facility or at home following delivery, or a post-natal care visit within 2 days after delivery 62.9 5.12 Post-natal health check for the mother Percentage of women age 15-49 years who received a health check while in facility or at home following delivery, or a post-natal care visit within 2 days after delivery of their most recent live birth in the last 2 years 60.4 Bungoma County MICS 2013/14 P a g e | vii CHILD DEVELOPMENT MICS Indicator Indicator Description Value 6.1 Attendance to early childhood education Percentage of children age 36-59 months who are attending an early childhood education programme 36.8 6.2 Support for learning Percentage of children age 36-59 months with whom an adult has engaged in four or more activities to promote learning and school readiness in the last 3 days 73.7 6.3 Father’s support for learning Percentage of children age 36-59 months whose biological father has engaged in four or more activities to promote learning and school readiness in the last 3 days 6.8 6.4 Mother’s support for learning Percentage of children age 36-59 months whose biological mother has engaged in four or more activities to promote learning and school readiness in the last 3 days 20.7 6.5 Availability of children’s books Percentage of children under age 5 who have three or more children’s books 4.4 6.6 Availability of playthings Percentage of children under age 5 who play with two or more types of playthings 54.9 6.7 Inadequate care Percentage of children under age 5 left alone or in the care of another child younger than 10 years of age for more than one hour at least once in the last week 44.2 6.8 Early child development index Percentage of children age 36-59 months who are developmentally on track in at least three of the following four domains: literacy-numeracy, physical, social- emotional, and learning 72.1 LITERACY AND EDUCATIONA MICS Indicator Indicator Description Value 7.1 MDG 2.3 Literacy rate among young women Percentage of young women age 15-24 years who are able to read a short simple statement about everyday life or who attended secondary or higher education 85.1 7.2 School readiness Percentage of children in first grade of primary school who attended pre-school during the previous school year 42.7 7.3 Net intake rate in primary education Percentage of children of school-entry age who enter the first grade of primary school 61.9 7.4 MDG 2.1 Primary school net attendance ratio (adjusted) Percentage of children of primary school age currently attending primary or secondary school 89.1 7.S1 Primary school net attendance ratio (adjusted) Percentage of children of primary school age currently attending primary (primary 1-8; national) or secondary school 90.7 7.5 Secondary school net attendance ratio (adjusted) Percentage of children of secondary school age currently attending secondary school or higher 57.5 7.S2 Secondary school net attendance ratio (adjusted) Percentage of children of secondary school age currently attending secondary school (national) or higher 31.8 7.6 MDG 2.2 Children reaching last grade of primary Percentage of children entering the first grade of primary school who eventually reach last grade 98.3 7.S3 Children reaching last grade of primary Percentage of children entering the first grade of primary school who eventually reach last grade (primary 8; national) 95.7 7.7 Primary completion rate Number of children attending the last grade of primary school (excluding repeaters) divided by number of children of primary school completion age (age appropriate to final grade of primary school) 132.2 Bungoma County MICS 2013/14 P a g e | viii 7.S4 Primary completion rate Number of children attending the last grade of primary school (excluding repeaters) divided by number of children of primary school completion age (age appropriate to final grade of primary school) (national) 107.8 7.8 Transition rate to secondary school Number of children attending the last grade of primary school during the previous school year who are in the first grade of secondary school during the current school year divided by number of children attending the last grade of primary school during the previous school year 94.4 7.S5 Transition rate to secondary school Number of children attending the last grade of primary school during the previous school year who are in the first grade of secondary school during the current school year divided by number of children attending the last grade of primary school during the previous school year (national) 51.9 7.9 MDG 3.1 Gender parity index (primary school) Primary school net attendance ratio (adjusted) for girls divided by primary school net attendance ratio (adjusted) for boys 0.99 7.S6 Gender parity index (primary school) Primary school net attendance ratio (adjusted) for girls divided by primary school net attendance ratio (adjusted) for boys (national) 1.00 7.10 MDG 3.1 Gender parity index (secondary school) Secondary school net attendance ratio (adjusted) for girls divided by secondary school net attendance ratio (adjusted) for boys 1.22 7.S7 Gender parity index (secondary school) Secondary school net attendance ratio (adjusted) for girls divided by secondary school net attendance ratio (adjusted) for boys (national) 1.22 A For Kenya, the International Standard Classification of Education (ISCED) 1997 classifies Primary 7 and 8 as Lower Secondary education. The indicators labelled ISCED calculates Primary School indicators based on Primary 1-6 only, whereas Primary 7 and 8 are included in Secondary School indicators. Those indicators labelled national and marked with S are based on the national education system, which includes Primary 7-8 in Primary School indicators. CHILD PROTECTION Birth registration MICS Indicator Indicator Description Value 8.1 Birth registration Percentage of children under age 5 whose births are reported registered 62.2 Child labour 8.2 Child labour Percentage of children age 5-17 years who are involved in child labour 54.4 Child discipline 8.3 Violent discipline Percentage of children age 1-14 years who experienced psychological aggression or physical punishment during the last one month 81.6 Early marriage and polygyny 8.4 Marriage before age 15 Percentage of women age 15-49 years who were first married or in union before age 15 5.2 8.5 Marriage before age 18 Percentage of women age 20-49 years who were first married or in union before age 18 30.1 8.6 Young people age 15-19 years currently married or in union Percentage of young women age 15-19 years who are married or in union 8.1 8.7 Polygyny Percentage of women age 15-49 years who are in a polygynous union 14.6 Bungoma County MICS 2013/14 P a g e | ix 8.8a 8.8b Spousal age difference Percentage of young women who are married or in union and whose spouse is 10 or more years older, (a) among women age 15-19 years, (b) among women age 20-24 years (*) 22.8 Female genital mutilation/cutting 8.9 Approval for female genital mutilation/cutting (FGM/C) Percentage of women age 15-49 years who state that FGM/C should be continued 1.7 8.10 Prevalence of FGM/C among women Percentage of women age 15-49 years who report to have undergone any form of FGM/C 2.1 8.11 Prevalence of FGM/C among girls Percentage of daughters age 0-14 years who have undergone any form of FGM/C, as reported by mothers age 15-49 years 0.0 Attitudes towards domestic violence 8.12 Attitudes towards domestic violence Percentage of women age 15-49 years who state that a husband is justified in hitting or beating his wife in at least one of the following circumstances: (1) she goes out without telling him, (2) she neglects the children, (3) she argues with him, (4) she refuses sex with him, (5) she burns the food 42.3 Children’s living arrangements 8.13 Children’s living arrangements Percentage of children age 0-17 years living with neither biological parent 16.5 8.14 Prevalence of children with one or both parents dead Percentage of children age 0-17 years with one or both biological parents dead 9.6 8.15 Children with at least one parent living abroad Percentage of children 0-17 years with at least one biological parent living abroad 0.2 (*) Figures that are based on less than 25 unweighted cases HIV/AIDS AND SEXUAL BEHAVIOUR HIV/AIDS knowledge and attitudes MICS Indicator Indicator Description Value - Have heard of AIDS Percentage of women age 15-49 years who have heard of AIDS 99.2 9.1 MDG 6.3 Knowledge about HIV prevention among young women Percentage of young women age 15-24 years who correctly identify ways of preventing the sexual transmission of HIV, and who reject major misconceptions about HIV transmission 48.5 9.2 Knowledge of mother- to-child transmission of HIV Percentage of women age 15-49 years who correctly identify all three means of mother-to-child transmission of HIV 48.7 9.3 Accepting attitudes towards women living with HIV Percentage of women age 15-49 years expressing accepting attitudes on all four questions toward women living with HIV 23.0 HIV testing 9.4 Women who know where to be tested for HIV Percentage of women age 15-49 years who state knowledge of a place to be tested for HIV 91.0 9.5 Women who have been tested for HIV and know the results Percentage of women age 15-49 years who have been tested for HIV in the last 12 months and who know their results 41.4 Bungoma County MICS 2013/14 P a g e | x 9.6 Sexually active young women who have been tested for HIV and know the results Percentage of young women age 15-24 years who have had sex in the last 12 months, who have been tested for HIV in the last 12 months and who know their results 48.0 9.7 HIV counselling during antenatal care Percentage of women age 15-49 years who had a live birth in the last 2 years and received antenatal care during the pregnancy of their most recent birth, reporting that they received counselling on HIV during antenatal care 75.8 9.8 HIV testing during antenatal care Percentage of women age 15-49 years who had a live birth in the last 2 years and received antenatal care during the pregnancy of their most recent birth, reporting that they were offered and accepted an HIV test during antenatal care and received their results 82.7 Sexual behaviour 9.9 Young women who have never had sex Percentage of never married young women age 15-24 years who have never had sex 69.0 9.10 Sex before age 15 among young women Percentage of young women age 15-24 years who had sexual intercourse before age 15 10.0 9.11 Age-mixing among sexual partners Percentage of women age 15-24 years who had sex in the last 12 months with a partner who was 10 or more years older 19.0 9.12 Multiple sexual partnerships Percentage of women age 15-49 years who had sexual intercourse with more than one partner in the last 12 months 2.3 9.13 Condom use at last sex among women with multiple sexual partnerships Percentage of women age 15-49 years who report having had more than one sexual partner in the last 12 months who also reported that a condom was used the last time they had sex (*) 9.14 Sex with non-regular partners Percentage of sexually active young women age 15-24 years who had sex with a non-marital, non-cohabitating partner in the last 12 months 13.9 9.15 MDG 6.2 Condom use with non- regular partners Percentage of young women age 15-24 years reporting the use of a condom during the last sexual intercourse with a non-marital, non-cohabiting sex partner in the last 12 months 55.1 (*) Figures that are based on less than 25 unweighted cases ACCESS TO MASS MEDIA AND ICT Access to mass media MICS Indicator Indicator Description Value 10.1 Exposure to mass media Percentage of women age 15-49 years who, at least once a week, read a newspaper or magazine, listen to the radio, and watch television 8.5 Use of information/communication technology 10.2 Use of computers Percentage of young women age 15-24 years who used a computer during the last 12 months 12.8 10.3 Use of internet Percentage of young women age 15-24 years who used the internet during the last 12 months 8.3 Bungoma County MICS 2013/14 P a g e | xi SUBJECTIVE WELL-BEING MICS Indicator Indicator Description Value 11.1 Life satisfaction Percentage of young women age 15-24 years who are very or somewhat satisfied with their life, overall 88.1 11.2 Happiness Percentage of young women age 15-24 years who are very or somewhat happy 90.3 11.3 Perception of a better life Percentage of young women age 15-24 years whose life improved during the last one year, and who expect that their life will be better after one year 71.5 TOBACCO AND ALCOHOL USE Tobacco use MICS Indicator Indicator Description Value 12.1 Tobacco use Percentage of women age 15-49 years who smoked cigarettes, or used smoked or smokeless tobacco products at any time during the last one month 0.3 12.2 Smoking before age 15 Percentage of women age 15-49 years who smoked a whole cigarette before age 15 0.1 Alcohol use 12.3 Use of alcohol Percentage of women age 15-49 years who had at least one alcoholic drink at any time during the last one month 10.5 12.4 Use of alcohol before age 15 Percentage of women age 15-49 years who had at least one alcoholic drink before age 15 7.7 Bungoma County MICS 2013/14 P a g e | xii Table of Contents Summary Table of Survey Implementation and the Survey Population, Bungoma County MICS, 2013/14 . ii Summary Table of Findings . iii Table of Contents. xii List of Tables . xv List of Figures . xix List of Abbreviations . xx Foreword . xxii Acknowledgements . xxiv Executive Summary . xxv 1. Introduction . 1 1.1 Background . 1 1.2 Survey Objectives. 3 2. Sample and Survey Methodology . 4 2.1 Sample Design . 4 2.2 Questionnaires . 4 2.3 Training and Fieldwork . 6 2.4 Data Processing . 6 3. Sample Coverage and the Characteristics of Households and Respondents. 7 3.1 Sample Coverage . 7 3.2 Characteristics of Households . 8 3.3 Characteristics of Female Respondents 15-49 Years of Age and Children Under-5 Years . 11 3.4 Housing characteristics, asset ownership, and wealth quintiles . 15 4. Nutrition. 19 4.1 Birth Weight. 19 4.2 Breastfeeding and Infant and Young Child Feeding . 21 4.3 Salt Iodization . 31 5. Child Health . 34 5.1 Vaccinations . 34 5.2 Neonatal Tetanus Protection . 40 5.3 Care of Illness . 41 Bungoma County MICS 2013/14 P a g e | xiii 5.3.1 Diarrhoea . 43 5.3.2 Acute Respiratory Infections (ARI) . 52 5.3.3 Solid Fuel Use . 53 5.3.4 Malaria/Fever . 56 6. Water and Sanitation . 72 6.1 Use of Improved Water Sources . 72 6.2 Use of Improved Sanitation . 78 6.3 Handwashing . 85 7. Reproductive Health . 90 7.1 Fertility . 90 7.2 Contraception . 95 7.3 Unmet Need . 98 7.4 Antenatal Care (ANC) . 100 7.5 Assistance at Delivery . 104 7.6 Place of Delivery . 108 7.7 Post-natal Health Checks (PNC) . 109 8. Early Childhood Development . 117 8.1 Early Childhood Care and Education . 117 8.2 Quality of Care . 118 8.3 Developmental Status of Children . 124 9. Literacy and Education . 127 9.1 Literacy among Young Women . 127 9.2 School Readiness . 128 9.3 Primary and Secondary School Participation . 129 10. Child Protection . 143 10.1 Birth Registration . 143 10.2 Child Labour . 146 10.3 Child Discipline. 151 10.4 Early Marriage and Polygyny . 155 10.5 Female Genital Mutilation/Cutting . 161 10.6 Attitudes toward Domestic Violence . 163 10.7 Children’s Living Arrangements . 165 11. HIV/AIDS and Sexual Behaviour . 168 11.1 Knowledge about HIV Transmission and Misconceptions about HIV . 168 11.2 Knowledge of mother-to-child HIV transmission (MTCT) . 172 11.3 Accepting Attitudes toward People Living with HIV . 174 Bungoma County MICS 2013/14 P a g e | xiv 11.4 Knowledge of a Place for HIV Counselling and Testing during Antenatal Care. 175 11.5 Sexual Behaviour Related to HIV Transmission . 178 11.6 HIV Indicators for Young Women . 180 11.7 Orphans . 186 12. Access to Mass Media and Use of Information and Communication Technology . 187 12.1 Access to Mass Media . 187 12.2 Use of Information and Communication Technology . 188 13. Subjective well-being . 190 14. Tobacco and Alcohol Use . 196 14.1 Tobacco Use . 196 14.2 Alcohol Use . 198 Appendix A. Documents Reviewed . 200 Appendix B. Education ISCED Tables . 205 Appendix C. Sample Design . 213 Appendix D. Estimates of Sampling Errors . 218 Appendix E. List of Personnel Involved in the Survey . 223 Appendix F. Data Quality Tables . 225 Appendix G. Bungoma County MICS5 Indicators: Numerators and Denominators . 240 Appendix H. Bungoma County MICS Questionnaires . 253 Bungoma County MICS 2013/14 P a g e | xv List of Tables Table HH.1: Results of household, women's and under-5 interviews . 7 Table HH.2: Household age distribution by sex . 8 Table HH.3: Household composition . 10 Table HH.4: Women's background characteristics . 12 Table HH.5: Under-5's background characteristics. 13 Table HH.6: Housing characteristics . 14 Table HH.7: Household and personal assets . 15 Table HH.8: Wealth quintiles . 16 Table NU.1: Low birth weight infants . 18 Table NU.2: Guiding Principles for Feeding children age 6-23 months . 20 Table NU.3: Initial breastfeeding . 20 Table NU.4: Breastfeeding . 23 Table NU.5: Duration of breastfeeding . 23 Table NU.6: Age-appropriate breastfeeding . 24 Table NU.7: Introduction of solid, semi-solid, or soft foods . 25 Table NU.8: Infant and young child feeding (IYCF) practices . 26 Table NU.9: Bottle feeding . 28 Table NU.10: Iodized salt consumption . 29 Table CH.1: Vaccinations in the first years of life . 34 Table CH.2: Vaccinations by background characteristics . 36 Table CH.3: Neonatal tetanus protection . 38 Table CH.4: Reported disease episodes . 39 Table CH.5: Care-seeking during diarrhoea . 41 Table CH.6: Feeding practices during diarrhoea . 42 Table CH.7: Oral rehydration solutions, recommended homemade fluids, and zinc . 44 Table CH.8: Oral rehydration therapy with continued feeding and other treatments . 46 Table CH.9: Source of ORS and zinc . 48 Table CH.10: Knowledge of the two danger signs of pneumonia . 49 Table CH.11: Solid fuel use . 51 Table CH.12: Solid fuel use by place of cooking . 52 Table CH.13: Household availability of insecticide treated nets and protection by a vector control method . 55 Table CH.14: Access to an insecticide treated net (ITN) - number of household members . 57 Table CH.15: Access to an insecticide treated net (ITN) - background characteristics . 57 Table CH.16: Use of ITNs . 58 Table CH.17: Children sleeping under mosquito nets . 59 Table CH.18: Use of mosquito nets by the household population. 60 Table CH.19: Care-seeking during fever . 61 Table CH.20: Treatment of children with fever . 62 Table CH.21: Diagnostics and anti-malarial treatment of children . 63 Table CH.22: Source of anti-malarial . 63 Table CH.23: Pregnant women sleeping under mosquito nets . 64 Table CH.24: Intermittent preventive treatment for malaria . 65 Table WS.1: Use of improved water sources . 68 Bungoma County MICS 2013/14 P a g e | xvi Table WS.2: Household water treatment . 70 Table WS.3: Time to source of drinking water . 71 Table WS.4: Person collecting water . 72 Table WS.5: Types of sanitation facilities . 73 Table WS.6: Use and sharing of sanitation facilities . 74 Table WS.7: Drinking water and sanitation ladders . 77 Table WS.8: Disposal of child's faeces . 79 Table WS.9: Water and soap at place for handwashing . 81 Table WS.10: Availability of soap or other cleansing agent . 83 Table RH.1: Fertility rates . 85 Table RH.2: Adolescent birth rate and total fertility rate . 86 Table RH.3: Early childbearing . 86 Table RH.4: Trends in early childbearing . 88 Table RH.5: Use of contraception . 90 Table RH.6: Unmet need for contraception . 93 Table RH.7: Antenatal care coverage . 95 Table RH.8: Number of antenatal care visits and timing of first visit . 96 Table RH.9: Content of antenatal care . 98 Table RH.10: Assistance during delivery and caesarean section . 100 Table RH.11: Place of delivery . 103 Table RH.12: Post-partum stay in health facility . 104 Table RH.13: Post-natal health checks for newborns . 105 Table RH.14: Post-natal health checks for mothers . 106 Table RH.15: Post-natal health checks for mothers and newborns . 107 Table CD.1: Early childhood education. 110 Table CD.2: Support for learning . 112 Table CD.3: Learning materials . 114 Table CD.4: Inadequate care . 115 Table CD.5: Early child development index . 117 Table ED.1: Literacy (young women). 119 Table ED.2: School readiness . 120 Table ED.3: Primary school entry . 121 Table ED.4: Primary school attendance and out of school children . 123 Table ED.5: Secondary school attendance and out of school children . 126 Table ED.6: Children reaching last grade of primary school . 129 Table ED.7: Primary school completion and transition to secondary school. 130 Table ED.8: Education gender parity . 131 Table ED.9: Out of school gender parity . 132 Table ED.10: Summary of education indicators (ISCED) . 134 Table CP.1: Birth registration . 137 Table CP.2: Children's involvement in economic activities . 139 Table CP.3: Children's involvement in household chores . 140 Table CP.4: Child labour . 141 Table CP.5: Child discipline . 144 Table CP.6: Attitudes toward physical punishment . 145 Table CP.7: Early marriage and polygyny (women) . 147 Table CP.8: Trends in early marriage (women) . 149 Bungoma County MICS 2013/14 P a g e | xvii Table CP.9: Spousal age difference . 150 Table CP.10: Female genital mutilation/cutting (FGM/C) among women . 152 Table CP.11: Approval of female genital mutilation/cutting (FGM/C) . 153 Table CP.12: Attitudes toward domestic violence (women) . 154 Table CP.13: Children's living arrangements and orphanhood . 156 Table CP.14: Children with parents living abroad . 157 Table HA.1: Knowledge about HIV transmission, misconceptions about HIV, and comprehensive knowledge about HIV transmission (women) . 160 Table HA.2: Knowledge of mother-to-child HIV transmission (women) . 163 Table HA.3: Accepting attitudes toward people living with HIV (women) . 164 Table HA.4: Knowledge of a place for HIV testing (women) . 166 Table HA.5: HIV counselling and testing during antenatal care . 167 Table HA.6: Sex with multiple partners (women) . 168 Table HA.7: Key HIV and AIDS indicators (young women) . 170 Table HA.8: Key sexual behaviour indicators (young women) . 173 Table MT.1: Exposure to mass media (women) . 176 Table MT.2: Use of computers and internet (women) . 178 Table SW.1: Domains of life satisfaction (women) . 180 Table SW.2: Overall life satisfaction and happiness (women) . 182 Table SW.3: Perception of a better life (women) . 183 Table TA.1: Current and ever use of tobacco (women) . 186 Table TA.2: Age at first use of cigarettes and frequency of use (women) . 187 Table TA.3: Use of alcohol (women) . 188 Appendices: Table ED.4: Primary school attendance and out of school children (ISCED). 194 Table ED.5: Secondary school attendance and out of school children (ISCED) . 196 Table ED.7: Primary school completion and transition to secondary school (ISCED) . 198 Table ED.8: Education gender parity ISCED) . 199 Table ED.9: Out of school gender parity (ISCED) . 200 Table SD.1: Allocation of Sample Clusters (Primary Sampling Units) to Sampling Strata . 203 Table SE.1: Indicators selected for sampling error calculations . 207 Table SE.2: Sampling errors: Total sample . 208 Table SE.3: Sampling errors: Urban . 209 Table SE.4: Sampling errors: Rural . 210 Table DQ.1: Age distribution of household population . 213 Table DQ.2: Age distribution of eligible and interviewed women . 214 Table DQ.4: Age distribution of children in household and under-5 questionnaires . 215 Table DQ.5: Birth date reporting: Household population . 215 Table DQ.6: Birth date and age reporting: Women . 216 Table DQ.8: Birth date and age reporting: Under-5s . 216 Table DQ.9: Birth date reporting: Children, adolescents and young people . 216 Table DQ.10: Birth date reporting: First and last births. 217 Bungoma County MICS 2013/14 P a g e | xviii Table DQ.11: Completeness of reporting . 217 Table DQ.12: Completeness of information for anthropometric indicators: Underweight . 218 Table DQ.13: Completeness of information for anthropometric indicators: Stunting . 218 Table DQ.14: Completeness of information for anthropometric indicators: Wasting . 219 Table DQ.15: Heaping in anthropometric measurements . 219 Table DQ.16: Observation of birth certificates . 220 Table DQ.17: Observation of vaccination cards . 221 Table DQ.18: Observation of women's health cards . 221 Table DQ.19: Observation of bednets and places for handwashing . 222 Table DQ.20: Presence of mother in the household and the person interviewed for the under-5 questionnaire . 222 Table DQ.21: Selection of children age 1-17 years for the child labour and child discipline modules . 223 Table DQ.22: School attendance by single age . 224 Table DQ.23: Sex ratio at birth among children ever born and living . 225 Table DQ.24: Births in years preceding the survey . 225 Table DQ.25: Reporting of age at death in days . 226 Table DQ.26: Reporting of age at death in months . 227 Bungoma County MICS 2013/14 P a g e | xix List of Figures Figure HH.1: Age and sex distribution of household population . 9 Figure NU.1: Initiation of breastfeeding . 22 Figure NU.2: Consumption of iodized salt . 30 Figure CH.1: Vaccinations by age 12 months . 35 Figure WS.1: Percent distribution of household members by source of drinking water . 69 Figure WS.2: Percent distribution of household members by use and sharing of sanitation facilities . 75 Figure WS.3: Use of improved drinking water sources and improved sanitation facilities by household members . 78 Figure WS.4: Use of improved water and sanitation in urban and rural areas . 78 Figure RH.1: Person assisting at delivery . 102 Figure RH.2: Place of delivery and post-natal health checks . 108 Figure ED.1: Education indicators by sex . 133 Figure CP.1: Children under-5 whose births are registered . 138 Figure CP.2: Child disciplining methods, children age 1-14 years . 145 Figure CP.3: Early marriage among women . 150 Figure HA.1: Women with comprehensive knowledge of HIV transmission . 162 Figure HA.2: Accepting attitudes toward people living with HIV/AIDS . 165 Figure HA.3: Sexual behaviour that increases the risk of HIV infection, young people age 15- 24 . 175 Appendix: Figure DQ.1: Number of household population by single ages . 214 Figure DQ.2: Weight and height/length measurements by digits reported for the decimal points. 220 Bungoma County MICS 2013/14 P a g e | xx List of Abbreviations ACRWC African Charter on the Rights and Welfare of the Child ACT Artemisinin-based Combination therapy AIDS Acquired Immune Deficiency Syndrome ANC Antenatal Care ARI Acute Respiratory Infection ART Anti‐retroviral Therapy ASFR Age-specific Fertility Rate BCC Behaviour Change Communication BCG Bacillus Calmette-Guérin (Tuberculosis) CARMMA Campaign on Accelerated Reduction of Maternal Mortality in Africa CBR Crude Birth Rate CEDAW Convention on the Elimination of all forms of Discrimination Against Women CRC Convention on the rights of the Child CSP Country Strategy Paper CSPro Census and Survey Processing System DOMC Division of Malaria Control DPT Diphtheria Pertussis Tetanus DVI Division of Vaccine and Immunisation EA Enumeration area ECD Early Childhood Development ECDE Early Childhood Development and Education ECDI Early Child Development Index EFA Education for All EHP Essential Health Package EMTCT Elimination of Mother-to-Child Transmission of HIV EPI Expanded Programme on Immunization FCTC Framework Convention on Tobacco Control FGM/C Female genital mutilation/cutting FNSP Food and Nutrition Security Policy GAPPD Global Action Plan for the Prevention and Control of Pneumonia and Diarrhoea GARPR Global AIDS Response Progress Reporting GFR General Fertility Rate GIPA Greater Involvement of People Living with HIV and AIDS GMAP Global Malaria Action Plan GPI Gender Parity Index GVAP Global Vaccine Action Plan HIV Human Immunodeficiency Virus ICPD International Conference on Population and Development ICT Information and Communications Technology IDD Iodine Deficiency Disorders ILO International Labour Organization IPT Intermittent Preventive Treatment IPTp Intermittent Preventive Treatment of Pregnant women IRS Indoor Residual Spraying ITN Insecticide Treated Net IUD Intrauterine Device JMP Joint Monitoring Programme Bungoma County MICS 2013/14 P a g e | xxi KASF Kenya AIDS Strategic Framework KCPE Kenya Certificate of Primary Education KCSE Kenya Certificate of Secondary Education KDHS Kenya Demographic and Health Survey KEBS Kenya Bureau of Standards KEPI Kenya Expanded Programme on Immunization KHPF Kenya Health Policy Framework KNASP Kenya National AIDS Strategic Plan KNBS Kenya National Bureau of Statistics LAM Lactational Amenorrhea Method MDG Millennium Development Goals MICS Multiple Indicator Cluster Survey MICS5 Fifth global round of Multiple Indicator Clusters Surveys programme MoH Ministry of Health MTP Medium Term Plans NAR Net Attendance Rate NASSEP V National Sample Survey and Evaluation Programme V NHSSP II National Health Sector Strategic Plan II NNAP National Nutrition Action Plan NTFIC National Tobacco Free Initiative Committee ORS Oral Rehydration Salts ORT Oral rehydration treatment PMI Presidents Malaria Initiative PMTC Prevention of Mother to Child Transmission PNC Post-natal Care PNHC Post-natal Health Checks PPM Parts Per Million PSRI Population Studies and Research Institute, University of Nairobi RHF Recommended Home Fluid SP Sulfadoxine-Pyrimethamine SPSS Statistical Package for Social Sciences STIs Sexually Transmitted Infections SUN Scaling Up Nutrition TFR Total Fertility Rate UNAIDS United Nations Programme on HIV/AIDS UNDP United Nations Development Programme UNFPA United Nations Population Fund UNGASS United Nations General Assembly Special Session on HIV/AIDS UNICEF United Nations Children’s Fund WFFC World Fit for Children WHO World Health Organization Bungoma County MICS 2013/14 P a g e | xxii Foreword The 2013/14 Multiple Indicator Cluster Survey (MICS5) covering Bungoma, Kakamega and Turkana Counties are part of the fifth global round of Multiple Indicator Cluster Survey series conducted worldwide to provide up-to-date information on the situation of children and women. This survey was conducted in collaboration with the Population Studies and Research Institute (PSRI) of the University of Nairobi, the Kenya National Bureau of Statistics (KNBS) and United Nations Children’s Fund (UNICEF). The results of this survey provide requisite baseline information that can be used to facilitate evidence-based planning, budgeting and programming by policymakers and stakeholders at the county levels. The reports will go a long way in encouraging increased demand for use of statistics by policy makers at devolved levels; ensure that resources at both county and national levels are used most effectively through well-planned projects/programmes that will benefit especially the women and children of the three counties. MICS5 was conducted at county level to provide comprehensive and disaggregated data to partly fill the existing data gaps at this level. This survey is the second of its kind to be conducted at the devolved level after the MICS4 was conducted in the six counties of the Nyanza region in 2011. MICS3 was conducted in all the 13 districts of the then Eastern Province in 2008. The MICS5 results are critical in gauging milestones achieved in the field of education, nutrition, child development, and health for women and children in the three counties and in evaluating the various health based policies that the Government has formulated over the years towards achieving the national welfare objectives. More specifically, the 2013/14 MICS5 data is critical in informing the future planning for the three counties, especially in view of the new constitutional dispensation and Vision 2030. It is anticipated that MICS5 will supplement the data collected during 2014 Kenya Demographic and Health Survey (KDHS). In addition, the information collected will inform strategic communication for social and behaviour change interventions by Government and partners including UNICEF. Furthermore, the data will contribute to the improvement of data and monitoring systems in the three counties. The survey laid emphasis on quality in every step of the process, right from the design of the tools, training of interviewers, monitoring of data collection, and the whole process of data processing. The MICS5 has much to offer to the health and family planning professionals, government planners, NGOs, researchers, and gender specialists. The potential users are numerous. It is, therefore, our appeal that the findings of MICS5 be put into good use so as to improve the well-being of people in the counties; to prepare reasonable and realistic objectives for county projects; to draw attention to critical problems and inequities; and to determine budgetary priorities. This report is a culmination of concerted efforts of various organizations and individuals. I have the greatest pleasure to give credit to the technical and financial assistance from UNICEF. I wish to appreciate the organizations, especially Population Studies and Research Institute of the University of Nairobi, that have contributed so much time, energy, and expertise to providing these findings and results. In addition I commend the hard work and dedication of Kenya National Bureau of Statistics (KNBS) staff in assisting to plan and implement this Survey. I thank the interviewers, editors, supervisors, who traversed the three counties, knocking on doors and spending hours talking to household respondents to generate the data. They faced a variety of challenges from occasional vehicle breakdowns, bad terrains, changing weather to basic accommodation. I wish to thank the Bungoma County MICS 2013/14 P a g e | xxiii respondents who generously and voluntarily provided the information. Without them, there would have been no report to talk about. Much gratitude goes to the data processing specialists and data editors for dedicating their time and expertise to put together quality data. All of them did a tremendous job. Zachary Mwangi Director General, Kenya National Bureau of Statistics Bungoma County MICS 2013/14 P a g e | xxiv Acknowledgements Kenya implemented the Multiple Indicator Cluster Survey (MICS5) in 2013/2014 in the three counties of Bungoma, Kakamega and Turkana as part of Global MICS round five. MICS is an international household survey programme developed by UNICEF. MICS provides up-to-date information on the situation of children and women and measures key indicators that allow countries to monitor progress towards the Millennium Development Goals (MDGs) and other internationally agreed upon commitments. In Kenya, this information is important to guide the planning and implementation of new development plans targeting the new administrative County-levels of governance. The successful implementation of the MICS5 was due to the great support and dedication of the partners. Kenya would like to thank the following collaborating organizations:  United Nations Children’s Fund  Kenya National Bureau of Statistics We do appreciate the financial support provided by the United Nations Children’s Fund. Special thanks go to the technical experts from the Kenya National Bureau of Statistics and Population Studies and Research Institute (PSRI) who ensured that the survey was implemented efficiently and effectively to produce quality results. These experts included officers from the collaborating institutions. They exhibited high degree of professionalism during the preparatory work prior and during the implementation stage as well as during the data analysis and report writing. We also thank the UNICEF Regional Office for East and Southern Africa and UNICEF Kenya Country Office for the technical support provided to Kenya during MICS5. We especially recognize and appreciate the support of Dr. Paul Mpuga, Dr. Monica Chizororo, Mr. Nicholas Oloo, Dr. Robert Ndugwa, Dr John Ndegwa Wagai and Dr. Nyasha Madzingira. Our deepest gratitude goes to the Kenyan Core Technical team responsible for implementing the MICS5. The team consisted of technical staff from the PSRI lead by Prof. Lawrence Ikamari supported by Mr. Ben Obonyo, Dr. Wanjiru, Dr. Samuel Wakibi, Dr Andew Mutuku and Dr. Odipo. The survey could not have been such a success without the guidance and expertise of the Kenya National Bureau of Statistics. In particular, the immeasurable support, advice and guidance of Mr. Zachary Mwangi – Director General, KNBS, Mr Macdonald Obutho – Director Population and Social Statistics, Mr. Robert Buluma, Mr. James Ng’ang’a and Bernard Obasi. This core team effectively implemented the entire MICS5 household survey. Finally, the most heartfelt gratitude goes to the County Statistical Officers in Bungoma, Kakamega and Turkana; Supervisors, KNBS enumerators, Research Assistants, the Village Elders and all the respondents who participated in the generation of data that made this survey successful. Prof. Murungaru Kimani Director Population Studies and Research Institute University of Nairobi Bungoma County MICS 2013/14 P a g e | xxv Executive Summary The Bungoma County Multiple Indicator Survey (MICS) is a representative sample survey designed to provide estimates for a large number of indicators on the situation of children and women at the county level, for urban and rural areas. The survey used two-stage stratified cluster sampling where the first stage selected 50 clusters from the KNBS fifth National Sample Survey and Evaluation Program (NASSEP V) household-based master sampling frame using equal probability selection method (EPSEM). The second stage randomly selected a uniform sample of 30 households in each cluster from a list of households in the cluster using systematic random sampling method. The survey was implemented by the University of Nairobi through Population studies and Research Institute in collaboration with Kenya National Bureau of Statistics (KNBS) with support from UNICEF Kenya. Information was collected from a total of 1,246 households representing 95 percent response rate. The composition of these households was 5,983 household members comprising 2,797 males and 3,186 females. The mean household size was 4.8 persons. About 48 percent of the sampled households’ population is below 15 years, 48 percent are between age 15-64 years and four percent are age 65 years and above. Due to data quality issues, data relating to mortality and anthropometric measures were not analyzed and reported. Anthropometric data suffered digit preference for both weight and height, while for mortality, deaths especially among children under-five years were under reported. KDHS 2014 had similar shortcomings. Nutrition Weight at birth is a good indicator not only of a mother's health and nutritional status but also the new-born’s chances for survival, growth, long-term health and psychosocial development. The survey findings show that 47 percent of the live births in the two years preceding the survey were weighed at birth, and approximately five percent of infants weighed less than 2,500 grams at birth. The prevalence of low birth weight varied slightly by urban-rural residence, birth order, and by mother’s education. Ninety-seven percent of the children were ever breastfed and 51 percent of babies were breastfed for the first time within one hour of birth. Approximately 43 percent of children age less than six months were exclusively breastfed. By age 12-15 months, 75 percent of children continued to be breastfed and by age 20-23 months, only 40 percent were still being breastfed. Among children under age 3 years, the median duration of any breastfeeding was 21 months. Percentage of children who were age appropriately breastfed during the previous day of the survey was 60 percent for 0-23 months. The overall assessment using the indicator of minimum acceptable diet revealed that only 22 percent were benefitting from a diet sufficient in both diversity and frequency (18 percent males and 26 percent females). Percentage of children age 0-23 months who were fed with a bottle with a nipple during the previous day of the survey were 16 percent and this practice was more prevalent for children 6-11 months old, residing in urban areas and whose mothers had attained secondary/higher education. More than 90 percent of households in both urban (96 percent) and rural areas (93 percent) were found to be using adequately iodized salt. Bungoma County MICS 2013/14 P a g e | xxvi Child Health Immunization plays a key part in reducing preventable child diseases and mortality. Percentage of children who were fully vaccinated by their first birthday was 56 percent. Overall, 64 percent of children age 12-23 months were fully immunized against vaccine preventable childhood diseases. The percentage of children fully vaccinated was higher for rural areas (71 percent) than for urban areas (59 percent). About 12 percent of children under five years of age were reported to have had diarrhoea in the two weeks preceding the survey, and a health facility or provider was seen in 46 percent of cases. Approximately 83 percent of children with diarrhoea received one or more of the recommended home treatments (i.e. were treated with ORS or any recommended homemade fluid), while 14 percent received zinc. In addition, 13 percent received ORS and zinc. Seventy-eight percent of households had at least one Insecticide-Treated Net (ITN) and 63 percent of children under-5 years slept under an ITN the night preceding the survey. Water and Sanitation Safe drinking water is a basic necessity for good health. Unsafe drinking water can be a significant determinant of diseases such as cholera, typhoid, and schistosomiasis. Drinking water can also be contaminated with chemical and physical contaminants with harmful effects on human health. In addition to preventing disease, improved access to drinking water may be particularly important for women and children, especially in rural areas, who bear the primary responsibility for carrying water, often for long distances. In Bungoma, 87 percent of the population uses an improved source of drinking water. Sixty-nine percent of household members in households using unimproved drinking water sources are using an appropriate water treatment method. In the majority of households (78 percent), an adult female usually collected drinking water when the source was not on the premises. Sixty-seven percent of the population are living in households using improved sanitation facilities. In 90 percent of the cases, children’s stool was disposed of safely. The percentage of households where a place for hand washing was observed is 15 percent. Eighty percent of the households had no specific place for hand washing in the dwelling, yard, or plot. Reproductive Health Empowering women and adolescent girls to exercise their sexual and reproductive health rights is a necessary condition for sustainable development. The findings show that age specific fertility rate and birth rate for the three years preceding the survey fertility is 66 births per 1,000 women among adolescents age 15-19 years. Fourteen percent of women age 15-19 years had begun childbearing, three percent were pregnant with their first child, and two percent have had a live birth before age 15. Four percent of women age 15-49 years have had a live birth before age 15. The proportion of women with a live birth before age 15 is four percent in urban areas and three percent in rural areas. Contraception by women currently married or in union is 54 percent and a third use injectables. Unmet need for family planning was 23 percent. Almost nine in ten mothers received ANC more than once and half of the mothers received ANC at least four times. Among those women who had a live birth during the last two years preceding the survey, 80 percent had blood pressure checked, urine and blood samples taken. Fifty-one percent of births occurring in the two years preceding the MICS were delivered by skilled personnel. About 46 percent of births were delivered in a health facility. Overall, 68 percent of women who gave birth in a health facility stayed 12 hours or more in the facility after delivery. Sixty-three percent of newborns received a health check following birth while in a health facility or at home and 60 percent of all mothers received a post-natal health check. Bungoma County MICS 2013/14 P a g e | xxvii Early Childhood Development In Bungoma County, about 37 percent of children age 36-59 months are attending an organised early childhood education programme. Seventy-four percent of children age 36-59 months have an adult household member engaged in four or more activities that promote learning and school readiness. The father’s involvement in such activities was low, with only seven percent of children age 36-59 months with fathers involved in four or more activities. Mother’s engagement in four or more activities that promote learning during the three days preceding the survey was higher at 21 percent. Availability of children’s books for those age 0-59 months was low, with only seven percent of children living in households where at least three children’s books were present. Fifty-five percent of children age 0-59 months had two or more types of playthings to play with in their homes. A total of 44 percent of children were left with inadequate care, either by being left alone or in the care of another child. Child development index is calculated as the percentage of children who are developmentally on target in at least three of the four component domains such as language-cognitive, physical, social- emotional, and approaches to learning. In Bungoma County, 72 percent of children age 36-59 months were developmentally on track. Literacy and Education Youth Literacy Rate as a measure of the effectiveness of the primary education system is often seen as a proxy measure of social progress and economic achievement. Forty-three percent of children who were attending the first grade of primary school at the time of the survey were attending pre-primary school the previous year. About 85 percent of young women age 15-24 were literate. Among those with primary school as their highest level of education, 75 percent were able to read the statement shown to them. Eight percent of children age 6-13 were out of school, with a low attendance rate of 70 percent for children age 6, who appeared to be starting late in school. Thirteen percent of the children of secondary school age were out of school. The majority of all children starting grade one were expected to reach grade 8 (96 percent). Only 52 percent of the children who were attending the last grade of primary school in the school year prior to the survey were found to be attending the first grade of secondary school at the time of the survey, suggesting a low transition rate from primary to secondary. The gender parity index (GPI) for primary school was 1.00, suggesting boys and girls of primary school age attended primary education at the same rate. The GPI for secondary education was 1.22, indicating a higher secondary school attendance rate among girls of secondary age than among boys of the same age. Child Protection In Bungoma County, the births of 40 percent of children under-five years are registered. Data shows that only 33 percent of the mothers/caretakers of the children under-five years of age whose births are not registered know how to register a child’s birth. Total child labour for Bungoma County is 54 percent (60 percent in rural areas and 47 percent in urban areas). Overall, the proportion of children working under hazardous conditions in Bungoma County is 44 percent (51 percent in rural areas and 36 percent in urban areas). Eighty-two percent of children age 1-14 years are subjected to at least one form of psychological aggression or physical punishment by household members. And 65 percent of respondents to the household questionnaire believe that physical punishment is a necessary part of child-rearing. Among women age 15-49 years, five percent are married before age 15 while among women age 20- 49 years, six percent are married before age 15 while 30 percent are married before age 18. Fifteen Bungoma County MICS 2013/14 P a g e | xxviii percent of women age 15-49 years are in polygamous unions. Eight percent of young women age 15- 19 years are currently married. Among currently married/in union women age 20-24 years, about one in five are married/in union with a man who is older by ten years or more (23 percent). The cases for women age 15-19 years currently married/in union were too few to be analysed by the age of the husband/partner. Two percent of women had some form of female genital mutilation. As to whether the practice should be continued or discontinued, two percent of women think it should be continued while 91 percent believe it should be discontinued. Overall, 42 percent of women in Bungoma County feel that a husband/partner is justified in hitting or beating his wife in at least one of the five situations (when a wife neglects the children, or if she demonstrates her autonomy, or arguing with him, or refuses to have sex with the husband, or burns the food). About 61 percent of children age 0-17 years in Bungoma County live with both their parents. Seventeen percent of children live with neither of their biological parents. Less than one percent of children age 0-17 have one or both parents living abroad. HIV/AIDS and Sexual Behaviour Almost all women age 15-49 years (99 percent) in Bungoma County have knowledge of AIDS. Seventy- one percent know of the two main ways of preventing HIV transmission, with 82 percent knowing having only one faithful uninfected partner and 81 percent know using a condom every time as main ways of preventing HIV transmission. Overall, 49 percent of women have comprehensive knowledge of HIV prevention methods and transmission which is higher in urban (54 percent) than rural areas (44 percent) and also varies with education and wealth status. In total, 64 percent of women rejected the two most common misconceptions that HIV can be transmitted through mosquito bites (82 percent), and by sharing food with someone with HIV (84 percent) and know that a healthy-looking person can be HIV-positive, and about 93 percent and 82 percent of women know that supernatural means and mosquito bites cannot transmit HIV, respectively. Ninety-three percent of women age 15-49 years know that HIV can be transmitted from mother to child by at least one of the three means; during pregnancy, delivery and breastfeeding while 49 percent of women know all three ways of mother-to- child transmission. Ninety-eight percent of women age 15-49 years who have heard of AIDS agreed with at least one accepting statement. The most common accepting attitude is willingness to care for a family member with AIDS in own home (93 percent). More educated women tend to have a more accepting attitude than those with no education. Ninety-one percent of women age 15-49 years know of a place where to be tested, while 74 percent have been tested. Forty-seven percent of women know the result of their most recent test. The proportion of women age 15-49 years that had been tested within the last 12 months preceding the survey is 48 percent, while those who had been tested within the last 12 months and know the result is 41 percent. Three quarters of women age 15-49 years with a live birth in the last two years preceding the survey received HIV counselling during ANC, 83 percent were offered an HIV test and were tested for HIV; and 76 percent received HIV counselling, offered an HIV test, accepted and received the results. Two percent of women 15-49 years of age reported that they had sex with more than one partner in the last 12 months with a mean number of lifetime sexual partners as 2.0. Forty- eight percent of young women have comprehensive knowledge. Young women who know of three Bungoma County MICS 2013/14 P a g e | xxix means of HIV transmission from mother-to-child are 44 percent and 86 percent have knowledge of a place to get tested. About 48 percent of young women age 15-24, who were sexually active, had been tested for HIV in the last 12 months and know the result. The proportion is high among young women with secondary/higher education (64 percent) compared with those with primary education (35 percent).Overall, 10 percent of young women age 15-24 years reported ever having sex before age 15. Further, two percent of young women had sex with more than one partner in the last 12 months. Only 55 percent of women used a condom the last time they had sex. About 19 percent of women age 15-24 years who had sex in the last 12 months, had sex with a man 10 or more years older. Access to Mass Media and Use of Information/Communication Technology About 17 percent of women age 15-49 years in Bungoma County read a newspaper or magazine, 71 percent listen to the radio, and 23 percent watch television at least once a week. Overall, 24 percent do not have regular exposure to any of the three media, while 76 percent are exposed to at least one, and nine percent to all the three types of media on a weekly basis. Women with higher education are four times more likely to have been exposed to all three types of media than women with primary education. Similarly, women from the richest households are more likely to have been exposed to all three types of media (28 percent) than women from the poorest households (1 percent). Overall, nine percent of young women age 15-24 years ever used the internet, while 8 percent used the internet during the last 12 months. The proportion of young women who used the internet more frequently, at least once a week during the last month, was smaller, at six percent. Both computer and internet use during the last 12 months were more widespread among women age 20-24 years compared to women age 15-19 years. Use of a computer and the internet is also strongly associated with education and wealth. Only about one percent of women with primary education reported using a computer during the last 12 months, while about a third of the women with higher education used a computer. Similarly, higher utilisation of the internet is observed among young women in the richest households (28 percent) compared the poorest households (3 percent). Subjective Well-being Young women are the most satisfied with their health (97 percent), the way they look (96 percent), and friendships and treatment by others (91 percent for each domain). The percentage of women age 15-24 years who are very or somewhat satisfied with school is 93 percent, with their job is 85 percent, and with their income is 73 percent. In Bungoma County, 88 percent of women age 15-24 years are satisfied with their life. The proportion of women who are satisfied with life is higher in urban areas (94 percent) than in rural areas (83 percent). The proportions do not vary much by marital status and educational level. About 90 percent of women age 15-24 years are very or somewhat happy. The percentage of women age 15-24 years who were very happy or somewhat happy is 93 percent for those age 15-19 years while it is 87 percent for those women age 20-24 years. The percentage for women in urban areas is 93 percent while it is 88 percent for those in rural areas. Women who had never married/in union are very happy or somewhat happy at 92 percent and those ever married/in union were at 86 percent. The proportion of women age 15-24 years who believe that their lives improved during the last one year and who expect that their lives would get better after one year, was 72 percent. There are no major differences among the various background characteristics. Bungoma County MICS 2013/14 P a g e | xxx Tobacco and Alcohol Use In Bungoma County, ever use of any tobacco products among women is two percent, while less than one percent smoked cigarettes, or used smoked or smokeless tobacco products on one or more days during the last one month preceding the survey. The results show that only about one woman age 15- 49 years in a thousand smoked a cigarette for the first time before age 15. About 11 percent of women age 15-49 years had at least one drink of alcohol on one or more days during the last month preceding the survey while eight percent have had at least one alcoholic drink before the age of 15 years. The proportion who had an alcoholic drink in the last month preceding the survey increased with age, ranging from five percent for the age group 15-19 to 19 percent for the age group 40-44, and decreasing to 12 percent for the 45-49 age group. A higher proportion of women in rural areas (12 percent) had at least one alcoholic drink before age 15 compared to those who resided in urban areas (3 percent). Similarly, women in rural areas (13 percent) were more likely than those in urban areas (8 percent) to have had at least one alcoholic drink at any time during the last one month preceding the survey. Bungoma County MICS 2013/14 P a g e | 1 1. Introduction Bungoma County is one of the 47 counties in Kenya. Bungoma County is located in the western part of the country and constitutes nine constituencies (Mt Elgon, Sirisia, Kabuchai, Bumula, Kanduyi, Webuye East, Webuye West, Kimilili and Tongaren). The county had an estimated population of 1,375,063 in 20132. 1.1 Background This report is based on the Bungoma County Multiple Indicator Cluster Survey (MICS), conducted in 2013/14 by the Population Studies and Research Institute, University of Nairobi, in collaboration with Kenya National Bureau of Statistics, as part of the global MICS programme. The survey provides statistically sound and internationally comparable data essential for developing evidence-based policies and programmes, and for monitoring progress toward national goals and global commitments. Among these global commitments are those emanating from the World Fit for Children Declaration and Plan of Action (2002)3, the goals of the United Nations General Assembly Special Session on HIV/AIDS (2001)4, the Education for All Declaration (2000)5 and the Millennium Development Goals (MDGs) 2000.6 A Commitment to Action: National and International Reporting Responsibilities The governments that signed the Millennium Declaration and the World Fit for Children Declaration and Plan of Action also committed themselves to monitoring progress towards the goals and objectives they contained: “We will monitor regularly at the national level and, where appropriate, at the regional level and assess progress towards the goals and targets of the present Plan of Action at the national, regional and global levels. Accordingly, we will strengthen our national statistical capacity to collect, analyse and disaggregate data, including by sex, age and other relevant factors that may lead to disparities, and support a wide range of child- focused research. We will enhance international cooperation to support statistical capacity-building efforts and build community capacity for monitoring, assessment and planning.” (A World Fit for Children, paragraph 60) “…We will conduct periodic reviews at the national and subnational levels of progress in order to address obstacles more effectively and accelerate actions.…” (A World Fit for Children, paragraph 61) The Plan of Action of the World Fit for Children (paragraph 61) also calls for the specific involvement of UNICEF in the preparation of periodic progress reports: “… As the world’s lead agency for children, the United Nations Children’s Fund is requested to continue to prepare and disseminate, in close collaboration with Governments, relevant funds, programmes and the specialized agencies of the United Nations system, and all other relevant actors, as appropriate, information on the progress made in the implementation of the Declaration and the Plan of Action.” 2Kenya National Bureau of Statistics, 2013. Statistical Abstract 2013. 3A World Fit for Children. Resolution adopted by the United Nations General Assembly 10 May 2002. 4United Nations General AssemblySpecial Session on HIV/AIDS 2001. Summary of the Declaration of Commitment on HIV/AIDS25-27 June 2001, New York 5http://www.unesco.org/new/en/education/themes/leading-the-international-agenda/education-for-all/ 6http://www.who.int/topics/millennium_development_goals/en/ http://www.unesco.org/new/en/education/themes/leading-the-international-agenda/education-for-all/ http://www.who.int/topics/millennium_development_goals/en/ Bungoma County MICS 2013/14 P a g e | 2 Similarly, the Millennium Declaration (paragraph 31) calls for periodic reporting on progress: “…We request the General Assembly to review on a regular basis the progress made in implementing the provisions of this Declaration, and ask the Secretary-General to issue periodic reports for consideration by the General Assembly and as a basis for further action.” Kenya’s GDP has grown by an annual average of 4 percent in the past five years. In 2013, Kenya adopted its second five-year Medium Term Plan (MTP II 2013-17) to implement its ‘Vision 2030’, which represents a solid strategic framework to transform Kenya into a newly industrializing, middle-income country by 2030.7 The African Development Bank’s Country Strategy Paper (CSP) 2014-18 for Kenya supports the country’s ambitions and addresses its main developmental challenges by promoting job creation as the overarching objective. The Bungoma County MICS results are expected to form part of the baseline data for the post-2015 agenda. The survey findings are also expected to contribute to the evidence base of several important initiatives, including Committing to Child Survival: A Promise Renewed7, a global movement to end child deaths from preventable causes, and the accountability framework proposed by the Commission on Information and Accountability for the Global Strategy for Women's and Children's Health.8 This final report presents the results of the indicators and topics covered in the survey. There are 14 chapters presented as follows: Chapter 1: An introductory note to the Bungoma County MICS Report; Chapter 2: Sample and survey methodology Chapter 3: Sample coverage and characteristics of households and respondents Chapter 4: Child nutrition Chapter 5: Child health Chapter 6: Water and sanitation Chapter 7: Reproductive health Chapter 8: Early childhood development Chapter 9: Literacy and education Chapter 10: Child protection Chapter 11: HIV, AIDS and sexual behaviour Chapter 12: Mass media and Information and Communication Technology (ICT) Chapter 13: Subjective well-being Chapter 14: Tobacco and alcohol use 7United Nations Children’s Fund (UNICEF), September 2014. Committing to Child Survival: A Promise Renewed - Progress Report 2014. 8WHO. 2014. Implementing the Commission on Information and Accountability Recommendations2014: Progress Report Accountability for Women’s and Children’s Health. http://www.apromiserenewed.org/ http://www.who.int/woman_child_accountability/en/ http://www.who.int/woman_child_accountability/en/ Bungoma County MICS 2013/14 P a g e | 3 1.2 Survey Objectives The 2013/14 Bungoma County MICS has as its primary objectives to:  Provide up-to-date information for assessing the situation of children and women in Bungoma County;  Generate data for the critical assessment of the progress made in various areas, and to put additional efforts in those areas that require more attention;  Furnish data needed for monitoring progress toward goals established in the Millennium Declaration, and other internationally agreed upon goals, as a basis for future action;  Collect disaggregated data for the identification of disparities, to allow for evidence based policy-making aimed at social inclusion of the most vulnerable;  Contribute to the generation of baseline data for the post-2015 agenda;  Validate data from other sources and the results of focused interventions; and  Contribute to the improvement of data and monitoring systems in Kenya and to strengthen technical expertise in the design, implementation, and analysis of such systems. Bungoma County MICS 2013/14 P a g e | 4 2. Sample and Survey Methodology Chapter Two presents the survey sample design and methodology, content for the three questionnaires used in the survey, the interviewer training process, fieldwork, and data management and processing. 2.1 Sample Design The sample for the Bungoma County MICS, 2013/14 was designed to provide estimates for a large number of indicators on the situation of children and women at the county level. The urban and rural areas within the county were the main sampling strata. The sample was selected in two stages: cluster and household. The survey utilized the fifth National Sample Survey and Evaluation Program (NASSEP V) household-based master sampling frame which is created and maintained by the Kenya National Bureau of Statistics (KNBS). The primary sampling unit for the frame is a cluster, which constitutes one or more EAs, with an average of 100 households. For the NASSEP V master sample the EAs were selected within each stratum using systematic sampling with probabilities proportion to size (PPS). For the MICS, within each stratum a specified number of clusters was selected from the master sample using an equal probability selection method (EPSEM). After a household listing was carried out within the selected clusters, a systematic sample of 30 households was drawn in each sampled cluster. In total, 50 clusters were selected for the survey in Bungoma County. The sample was stratified by urban and rural areas, and was not self-weighting. All selected clusters were visited during fieldwork. For reporting county level results, sample weights are used. A more detailed description of the sample design is provided in Appendix C. 2.2 Questionnaires A set of three questionnaires was used in the survey: 1) a household questionnaire which was administered to the household head or any other responsible member of the household; 2) a questionnaire for individual women administered in each household to all women age 15-49 years; 3) an under-5 questionnaire, administered to mothers (or caretakers) for all children under 5 years living in the household. The questionnaires included the following modules: The Household Questionnaire included the following modules:  List of Household Members  Education  Child Labour  Child Discipline  Household Characteristics  Insecticide Treated Nets  Indoor Residual Spraying  Water and Sanitation Bungoma County MICS 2013/14 P a g e | 5  Handwashing  Salt Iodization The Questionnaire for Individual Women age 15-49 years included the following modules:  Woman’s Background  Access to Mass Media and Use of Information/Communication Technology  Fertility/Birth History  Desire for Last Birth  Maternal and Newborn Health  Post-natal Health Checks  Illness Symptoms  Contraception  Unmet Need  Female Genital Mutilation/Cutting  Attitudes Toward Domestic Violence  Marriage/Union  Sexual Behaviour  HIV/AIDS  Tobacco and Alcohol Use  Life Satisfaction The Questionnaire for Children Under5 was administered to mothers (or caretakers) of children under 5 years of age9 living in the households. Normally, the questionnaire was administered to mothers of under-5 children; in cases when the mother was not listed in the household roster, a primary caretaker for the child was identified and interviewed. The questionnaire included the following modules:  Age  Birth Registration  Early Childhood Development  Immunization  Breastfeeding and Dietary Intake  Care of Illness  Anthropometry Due to data quality issues, data relating to mortality and anthropometric measures were not analyzed and reported. Anthropometric data suffered digit preference for both weight and height, while for mortality, deaths especially among children under-five years were under reported. The recommendation to remove the Mortality Chapter and the anthropometric measures section from the Nutrition Chapter was adopted at the final reports validation workshop organized by KNBS, PSRI and UNICEF. KDHS 2014 had similar shortcomings. The DQ tables are included in the report for reference. The MICS data set can be accessed and evaluated by researchers for further analysis. The survey team, KNBS and the Population Studies and Research Institute will review the data in detail to identify challenges encountered and to address them before the next round of surveys. 9 The terms “children under 5”, “children age 0-4 years”, and “children age 0-59 months” are used interchangeably in this report. Bungoma County MICS 2013/14 P a g e | 6 The questionnaires are based on the MICS5 model questionnaire.10 From the MICS5 model English version, the questionnaires were customised and translated into Kiswahili and Luhya sub dialect and were pre-tested in four clusters (rural and urban) in Trans Nzoia County. Based on the results of the pre-test, modifications were made to the wording and translation of the questionnaires. A copy of the Bungoma County MICS questionnaires is provided in Appendix F. In addition to administering of questionnaires, fieldwork teams tested the salt used for cooking in the households for iodine, observed the place for handwashing, and measured the weights and heights of children under-5 years of age. Details and findings of these observations and measurements are provided in the respective sections of the report. 2.3 Training and Fieldwork Training for the fieldwork was conducted in Kitale town for 14 days from 24th October to 6th November, 2013. Training included lectures on interviewing techniques and the contents of the questionnaires, and mock interviews between trainees to gain practice in asking questions. Facilitators used a variety of methods which included PowerPoint presentations, illustrations on flip charts, question and answer, case studies, group work and group discussions. Towards the end of the training period, trainees spent two days practising the research tools by interviewing respondents in selected urban and rural clusters in Trans Nzoia County. Fieldwork began in November 2013 and concluded in February 2014. The survey team was divided into two groups. Each group comprised of 5 interviewers, one driver, one editor, one measurer and a supervisor. 2.4 Data Processing CSPro software, Version 5.0 running on desktop computers was used for data entry. Data entry was done by a trained team of 14 data entry operators, one Archivist/System administrator and one data entry supervisor. For quality assurance purposes, all questionnaires were double-entered and internal consistency checks performed. Procedures and standard programs developed under the global MICS programme and adapted to the Bungoma County MICS questionnaire were used throughout. Data processing began simultaneously with data collection in November 2013 and was completed in February 2014. Data were analysed using the Statistical Package for Social Sciences (SPSS) software, Version 21. Model syntax and tabulation plans developed by UNICEF were customized and used for this purpose. 10 The model MICS5 questionnaires can be found at http://www.childinfo.org/mics5_questionnaire.html http://www.childinfo.org/mics5_questionnaire.html Bungoma County MICS 2013/14 P a g e | 7 3. Sample Coverage and the Characteristics of Households and Respondents This chapter presents results of the sample coverage; characteristics of households and female respondents age 15-49 years and children under-five years of age. The chapter also provides information on the housing characteristics, asset ownership and household wealth quintiles. 3.1 Sample Coverage Table HH1 shows the results of the households, women’s and under-five interviews. Of the 1,500 households selected for the sample, 1,316 were found to be occupied. Of these, 1,246 were successfully interviewed giving a household response rate of 95 percent. A total of 1,373 women age 15-49 years were eligible for interview out of whom 1,213 were successfully interviewed, yielding a response rate of 88 percent. There were 874 eligible children under age five years in the interviewed households out of whom 846 interviews were completed for them by their mothers/caretakers or giving a response rate of 97 percent. Overall response rates of 84 percent and 92 percent were calculated for the individual interviews of women and under-5s, respectively, as shown in Table HH.1 below. About 97 percent of households in rural areas were interviewed compared to 93 percent in urban areas. Similarly, the overall response rate was slightly higher for women in rural areas (85 percent) than for those in urban areas (82 percent). For children under-five years, the overall response rate was 95 percent in rural areas and 88 percent in urban areas. Table HH.1: Results of household, women's, and under-5 interviews Number of households, women, and children under-5 by interview results, and household, women's and under-5's response rates, Bungoma County MICS, 2013/14 Total Area Urban Rural Households Sampled 1,500 780 720 Occupied 1,316 671 645 Interviewed 1,246 623 623 Household response rate 94.7 92.8 96.6 Women Eligible 1,373 641 732 Interviewed 1,213 568 645 Women's response rate 88.3 88.6 88.1 Women's overall response rate 83.6 82.3 85.1 Children under 5 Eligible 874 392 482 Mothers/caretakers interviewed 846 372 474 Under-5's response rate 96.8 94.9 98.3 Under-5's overall response rate 91.6 88.1 95.0 Bungoma County MICS 2013/14 P a g e | 8 3.2 Characteristics of Households The weighted age and sex distribution of the survey population is provided in Table HH.2. The distribution has been used to generate the population pyramid in Figure HH.1. Data by single year age distribution of the population is in Appendix F, Table DQ.1. In the 1,246 households successfully interviewed in the survey, 5,983 household members were listed. Of these, 2,797 (47 percent) are males and 3,186 (53 percent) are females. About 48 percent of the population comprises of children below 15 years of age. The youth age 15-24 years account for 18 percent of the population. Table HH.2: Age distribution of household population by sex Percent and frequency distribution of the household population by five-year age groups, dependency age groups, and by child (age 0-17 years) and adult populations (age 18 or more), by sex, Bungoma County MICS, 2013/14 Total Males Females Number Percent Number Percent Number Percent Total 5,983 100.0 2,797 100.0 3,186 100.0 Age 0-4 898 15.0 443 15.8 456 14.3 5-9 1,074 18.0 517 18.5 557 17.5 10-14 890 14.9 417 14.9 473 14.9 15-19 662 11.1 297 10.6 365 11.5 20-24 402 6.7 170 6.1 232 7.3 25-29 430 7.2 176 6.3 254 8.0 30-34 311 5.2 143 5.1 169 5.3 35-39 292 4.9 146 5.2 146 4.6 40-44 223 3.7 105 3.7 119 3.7 45-49 183 3.1 85 3.0 99 3.1 50-54 145 2.4 75 2.7 70 2.2 55-59 136 2.3 62 2.2 74 2.3 60-64 106 1.8 2.2 45 1.4 65-69 87 1.5 38 1.3 49 1.5 70-74 63 1.1 25 0.9 38 1.2 75-79 33 0.6 15 0.5 18 0.6 80-84 27 0.4 14 0.5 13 0.4 85+ 19 0.3 10 0.3 9 0.3 Missing/DK 1 0.0 0 0.0 1 0.0 Dependency age groups 0-14 2,863 47.8 1,377 49.2 1,486 46.6 15-64 2,892 48.3 1,319 47.2 1,572 49.4 65+ 228 3.8 101 3.6 127 4.0 Missing/DK 1 0.0 0 0.0 1 0.0 Child and adult populations Children age 0-17 years 3,303 55.2 1,578 56.4 1,725 54.1 Adults age 18+ years 2,680 44.8 1,219 43.6 1,461 45.8 Missing/DK 1 0.0 0 0.0 1 0.0 Bungoma County MICS 2013/14 P a g e | 9 The population pyramid (Figure HH.1) for Bungoma County is broad based. However, the pattern exhibited is slightly different from the national population pyramid obtained during the 2009 Housing and Population Census. The national population pyramid from the 2009 census was smooth and showed a higher percentage of the population in the 0-4 year age group than in the 5-9 year age group, which is what is expected. On the contrary, the population pyramid from the MICS5 shows a notably smaller percentage of the population in the 0-4 year age group than in the 5-9 year age group. This may be attributed partly to interviewers’ bias (out transference) in order to reduce the number of under-five questionnaires to administer. There is also a noticeable drop in the age group 20-24 years, which may be an indication of out-migration of the population from the county to other areas either for further education or for employment opportunities. In the Bungoma County, forty-eight percent are in the 15 to 64 year age group while four percent are age 65 years and above (Table HH.2). Fifty-five percent of the population is under the age of 18. The percentage of males under the age of 18 years is 56 percent, compared to 54 percent of females. Figure HH.1: Age and sex d istr ibut ion of household populat ion , Bungoma Count y MICS, 2013/14 Tables HH.3, HH.4 and HH.5 provide basic information on the households, female respondents’ age 15-49 years, and children under-5 years. Both unweighted and weighted numbers are presented. Such information is essential for the interpretation of findings presented later in the report and provides background information on the representativeness of the survey sample. The rest of the tables in this report are presented only with weighted numbers.11 11 See Appendix C: Sample Design, for more details on sample weights. 10 8 6 4 2 0 2 4 6 8 10 12 0-4 5-9 10-14 15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59 60-64 65-69 70-74 75-79 80-84 85+ Percent Age Males Females Note: 1 household members with missing age and/or sex is excluded Bungoma County MICS 2013/14 P a g e | 10 Table HH.3 provides basic background information on the households, including the sex of the household head, area, number of household members, education of household head, and ethnicity of the household head. These background characteristics are used in subsequent tables in this report. The figures in the table are also intended to show the numbers of observations by major categories of analysis in the report. The weighted and unweighted total number of households are equal, since sample weights were normalized.11 The table shows the weighted mean household size of 4.8 persons estimated by the survey. Most households in Bungoma County are headed by males (68 percent) compared to only 32 percent of those headed by females. Forty-nine percent of the households are in an urban area, with 51 percent in rural areas. The results further indicate that most of the household heads have either primary education (45 percent) or secondary/higher education (44 percent). About a third of the households (29 percent) have household sizes of 4-5 persons, 22 percent have 2-3 persons, 22 percent have 6-7 persons, 12 percent have 1 person, 10 percent have 8-9 persons and five percent have 10 or more persons. Most of the heads of households (88 percent) comprises of the Luhya ethnic group. Bungoma County MICS 2013/14 P a g e | 11 Table HH.3: Household composition Percent and frequency distribution of households by selected characteristics, Bungoma County MICS, 2013/14 Weighted percent Number of households Weighted Unweighted Total 100.0 1,246 1,246 Sex of household head Male 68.0 847 860 Female 32.0 399 386 Area Urban 49.2 614 623 Rural 50.8 632 623 Number of household members 1 11.6 145 150 2 9.2 114 114 3 13.2 165 165 4 14.7 183 187 5 14.5 180 181 6 12.2 152 149 7 9.7 121 112 8 6.6 82 84 9 3.3 41 43 10+ 5.1 63 61 Education of household head None 9.9 123 114 Primary 45.3 565 564 Secondary+ 44.4 553 564 Missing/DK 0.4 5 4 Ethnicity of household head Luhya 87.6 1,091 1,022 Other ethnic group 12.4 154 223 Missing/DK12 0.0 0 1 Mean household size 4.8 1,246 1,246 3.3 Characteristics of Female Respondents 15-49 Years of Age and Children Under-5 Years Tables HH.4 and HH.5 provide information on the background characteristics of female respondents 15-49 years of age and children under-5 years respectively. In the two tables, the total numbers of weighted and unweighted observations are equal, since sample weights have been normalized (standardized).11 In addition to providing useful information on the background characteristics of women, and children under-5 years, the tables are also intended to show the numbers of observations in each background category. These categories are used in the subsequent tabulations of this report. Table HH.4 provides background characteristics of female respondents, age 15-49 years. The table 12 Since there is only 1 household and 1 child for whom information on ethnicity is missing, these cases will not be shown in subsequent tables (except HH5 and HH7). Bungoma County MICS 2013/14 P a g e | 12 includes information on the distribution of women according to area, age, marital/union status, motherhood status, births in last two years, education13, wealth index quintiles14, 15, and ethnicity of the household head. More than half of the women interviewed (54 percent) reside in rural areas while 46 percent are in urban areas. Disaggregation of the data by age of the woman shows that 24 percent of the women are age 15-19 years, 16 percent are age 20-24 years, and 18 percent are in the 25-29 years age category. The data further indicates that fifty-seven percent of the women interviewed are currently married/in union, while a third of the respondents (33 percent) have never married. Of all women age 15-49 years in Bungoma, 71 percent had ever given birth, including 26 percent who gave birth in the two years preceding the survey. A higher proportion of 45 percent of women had never given birth in the last two years. The majority of women have either primary education (55 percent) or secondary/higher education (43 percent). 13 Throughout this report, unless otherwise stated, “education” refers to highest educational level ever attended by the respondent when it is used as a background variable. 14 The wealth index is a composite indicator of wealth. To construct the wealth index, principal components analysis is performed by using information on the ownership of consumer goods, dwelling characteristics, water and sanitation, and other characteristics that are related to the household’s wealth, to generate weights (factor scores) for each of the items used. First, initial factor scores are calculated for the total sample. Then, separate factor scores are calculated for households in urban and rural areas. Finally, the urban and rural factor scores are regressed on the initial factor scores to obtain the combined, final factor scores for the total sample. This is carried out to minimize the urban bias in the wealth index values. Each household in the total sample is then assigned a wealth score based on the assets owned by that household and on the final factor scores obtained as described above. The survey household population is then ranked according to the wealth score of the household they are living in, and is finally divided into 5 equal parts (quintiles) from lowest (poorest) to highest (richest). In Bungoma County MICS, the following assets were used in these calculations: radio, television, non-mobile telephone, refrigerator, agricultural land, farm animals/livestock, watch, mobile telephone, bicycle, motorcycle or scooter, animal- drawn cart, car or truck, boat with a motor, and ownership of dwelling. The wealth index is assumed to capture the underlying long-term wealth through information on the household assets, and is intended to produce a ranking of households by wealth, from poorest to richest. The wealth index does not provide information on absolute poverty, current income or expenditure levels. The wealth scores calculated are applicable for only the particular data set they are based on. Further information on the construction of the wealth index can be found in Filmer, D and Pritchett, L. 2001. Estimating wealth effects without expenditure data – or tears: An application to educational enrolments in states of India. Demography 38(1): 115-132; Rutstein, SO and Johnson, K. 2004. The DHS Wealth Index. DHS Comparative Reports No. 6; and Rutstein, SO. 2008. The DHS Wealth Index: Approaches for Rural and Urban Areas. DHS Working Papers No. 60. 15 When describing survey results by wealth quintiles, appropriate terminology is used when referring to individual household members, such as for instance “women in the richest population quintile”, which is used interchangeably with “women in the wealthiest survey population”, “women living in households in the richest population wealth quintile”, and similar. Bungoma County MICS 2013/14 P a g e | 13 Table HH.4: Women's background characteristics Percent and frequency distribution of women age 15-49 years by selected background characteristics, Bungoma County MICS, 2013/14 Weighted percent Number of women Weighted Unweighted Total 100.0 1,213 1,213 Area Urban 46.4 563 568 Rural 53.6 650 645 Age 15-19 24.4 296 286 20-24 15.7 191 197 25-29 18.3 222 233 30-34 13.2 161 153 35-39 11.7 142 144 40-44 9.0 110 103 45-49 7.6 92 97 Marital/Union status Currently married/in union 57.2 694 698 Widowed 3.0 37 39 Divorced 2.2 27 26 Separated 4.2 51 48 Never married/in union 33.3 404 402 Motherhood and recent births Never gave birth 29.1 352 356 Ever gave birth 70.9 861 857 Gave birth in last two years 25.6 311 304 No birth in last two years 45.3 550 553 Education None 2.3 28 27 Primary 54.6 662 636 Secondary+ 43.0 522 550 Wealth index quintile Poorest 16.3 197 205 Second 18.7 227 192 Middle 19.7 240 225 Fourth 21.7 263 271 Richest 23.5 285 320 Ethnicity of household head Luhya 89.5 1,086 1,010 Other ethnic group 10.5 127 203 In households where there were children under the age of five years, the mothers/caretakers were interviewed. The background characteristics of children under-5 years are presented in Table HH.5. These include the distribution of children by several attributes: sex, area, age in months, respondent type, mother’s (or caretaker’s) education, wealth, and ethnicity. The proportion of male and female children under-5 years was almost the same (49 and 51 percent, respectively). Fifty-six percent of children under-5 years reside in rural areas, while 45 percent are in Bungoma County MICS 2013/14 P a g e | 14 urban areas. A quarter of the children are age 36-47 months. The women who responded to the questions about the child under-5 years (89 percent) are mothers of the children compared to only 11 percent of caretakers. Ninety-six percent of the women interviewed have either primary or secondary/higher education. About a quarter (24 percent) of the children are in the poorest wealth quintile. About 90 percent of households are headed by Luhyas. Table HH.5: Under-5's background characteristics Percent and frequency distribution of children under five years of age by selected characteristics, Bungoma County MICS, 2013/14 Weighted percent Number of under-5 children Weighted Unweighted Total 100.0 846 846 Sex Male 48.9 414 427 Female 51.1 432 419 Area Urban 44.5 376 372 Rural 55.5 470 474 Age 0-5 months 9.9 83 80 6-11 months 9.9 84 84 12-23 months 17.9 152 153 24-35 months 18.9 160 168 36-47 months 25.4 215 209 48-59 months 18.0 152 152 Respondent to the under-5 questionnaire Mother 89.2 754 751 Other primary caretaker 10.8 92 95 Mother’s educationa None 4.0 34 32 Primary 60.8 514 503 Secondary+ 35.2 298 311 Wealth index quintile Poorest 23.6 199 210 Second 21.8 184 163 Middle 19.2 162 146 Fourth 18.5 157 165 Richest 16.9 143 162 Ethnicity of household head Luhya 90.0 762 698 Other ethnic group 9.9 84 147 Missing/DK 0.1 0 1 a In this table and throughout the report, mother's education refers to educational attainment of mothers as well as caretakers of children under 5, who are the respondents to the under-5 questionnaire if the mother is deceased or is living elsewhere. Bungoma County MICS 2013/14 P a g e | 15 3.4 Housing characteristics, asset ownership, and wealth quintiles Tables HH.6, HH.7 and HH.8 provide results on household characteristics and assets in connection to household wealth. Table HH.6 presents characteristics of housing, disaggregated by area and region, distributed by whether the dwelling has electricity, the main materials of the flooring, roof, and exterior walls, as well as the number of rooms used for sleeping. Fifteen percent of the households have electricity (20 percent urban and 10 percent rural areas). Sixty- three percent have natural floors16, while 37 percent have a finished floor17. Ninety-five percent of the households have finished roofing.18 While 52 percent of households have rudimentary walls19, 18 percent have natural walls20 and 29 percent have finished walls.21 Data was also collected on the number of sleeping rooms and number of persons sleeping in one room. The mean number of persons per sleeping room is 3. 16 Natural flooring – earth/sand or dung 17 Finished floor - Parquet or polished wood, vinyl or asphalt strips, ceramic tiles, cement or carpet 18 Finished roofing - Metal/Tin, wood, calamine/cement fibre, ceramic tiles, cement, or roofing shingles 19 Rudimentary walls - Bamboo with mud, stone with mud, uncovered adobe, plywood, cardboard, or reused wood 20 Natural walls - No walls, cane /palm / trunks or dirt. 21 Finished walls – Cement, stone with lime / cement, bricks, cement blocks, covered adobe or wood planks / shingles. Additional definitions for housing characteristics (Table HH.6) are in Appendix G Bungoma County MICS 2013/14 P a g e | 16 Table HH.6: Housing characteristics Percent distribution of households by selected housing characteristics, according to area of residence and regions, Bungoma County MICS, 2013/14 Total Area Urban Rural Total 100.0 100.0 100.0 Electricity Yes 14.8 19.8 10.0 No 85.2 80.2 90.0 Flooring Natural floor 63.2 53.4 72.7 Rudimentary floor 0.1 0.0 0.1 Finished floor 36.6 46.4 27.1 Other 0.0 0.0 0.0 Missing/DK 0.1 0.2 0.0 Roof Natural roofing 5.0 1.2 8.7 Rudimentary roofing 0.0 0.0 0.1 Finished roofing 94.9 98.8 91.1 Other 0.1 0.0 0.1 Exterior walls Natural walls 18.4 18.6 18.2 Rudimentary walls 52.3 43.9 60.4 Finished walls 29.3 37.4 21.4 Other 0.1 0.1 0.1 Rooms used for sleeping 1 42.2 45.3 39.1 2 38.1 39.0 37.1 3 or more 14.6 11.9 17.1 Missing/DK 5.2 3.8 6.6 Number of households 1,246 614 632 Mean number of persons per room used for sleeping 3.02 2.83 3.21 In Table HH.7, households are distributed according to ownership of assets by households and by individual household members. This also includes ownership of dwelling unit. Seventy percent of the households own a radio (69 in urban areas and 71 in rural areas) while 23 percent own a television set. Eighty percent of households own agricultural land while 69 percent own farm animals/livestock. About eighty-two percent of household members own a mobile phone, 43 percent a bicycle, 38 percent a bank account, 22 percent own a watch. About three quarters (76 percent) of the dwelling units are owned by a household member. Ownership is higher in rural areas (87 percent) than urban areas (64 percent). Bungoma County MICS 2013/14 P a g e | 17 Table HH.7: Household and personal assets Percentage of households by ownership of selected household and personal assets, and percent distribution by ownership of dwelling, according to area of residence and regions, Bungoma County MICS, 2013/14 Total Area Urban Rural Total 100.0 100.0 100.0 Percentage of households that own a Radio 70.3 69.2 71.4 Television 23.0 26.0 20.1 Non-mobile phone 1.8 0.8 2.6 Refrigerator 3.6 3.8 3.3 Solar Panel 1.9 1.9 1.9 Chair 1.0 1.1 1.0 Sofa Set 1.5 1.5 1.5 Table 1.1 1.1 1.1 Cupboard 1.5 1.5 1.5 Bed 1.0 1.1 1.0 Clock 1.8 1.8 1.8 Camera 2.0 2.0 2.0 Computer 2.0 2.0 2.0 Percentage of households that own Agricultural land 79.5 72.7 86.1 Farm animals/Livestock 68.9 59.4 78.1 Percentage of households where at least one member owns or has a Watch 22.0 22.4 21.5 Mobile telephone 81.8 83.5 80.1 Bicycle 43.3 36.8 49.5 Motorcycle or scooter 8.7 7.9 9.5 Animal-drawn cart 2.3 1.4 3.1 Car or truck 4.3 3.4 5.2 Boat with a motor 0.0 0.0 0.0 Bank account 38.2 37.9 38.5 Ownership of dwelling Owned by a household member 75.7 63.7 87.4 Not owned 24.3 36.3 12.6 Rented 23.2 35.0 11.6 Other 1.1 1.3 0.9 Number of households 1,246 614 632 Table HH.8 shows how the household populations in urban and rural areas are distributed according to household wealth quintiles. Fewer households in urban areas (53 percent) are in the poorest to middle wealth quintiles compared to households in rural areas (66 percent). Bungoma County MICS 2013/14 P a g e | 18 Table HH.8: Wealth quintiles Percent distribution of the household population by wealth index quintile, according to area of residence and regions, Bungoma County MICS, 2013/14 Wealth index quintile Total Number of household members Poorest Second Middle Fourth Richest Total 20.0 20.0 19.9 20.0 20.0 100.0 5,983 Area Urban 18.7 16.6 17.7 22.1 24.8 100.0 2,697 Rural 21.0 22.8 21.7 18.4 16.1 100.0 3,286 Bungoma County MICS 2013/14 P a g e | 19 4. Nutrition About half of Kenya’s estimated 38.5 million people are poor, and some 7.5 million people live in extreme poverty, while over 10 million people suffer from chronic food insecurity and poor nutrition. Children are undernourished and micronutrient deficiencies are widespread.22, 23 The Government of Kenya is strongly committed to reducing hunger and malnutrition. Policies and strategies were developed to guide the nutrition interventions and activities in the country. These include the Food and Nutrition Security Policy (FNSP) 2011, National Nutrition Action Plan (NNAP) 2012-2017 and Kenya Health Strategic Plan 2008-2012. Most of these interventions were part of Scaling Up Nutrition (SUN) actions that were implemented globally to accelerate efforts towards achieving MDG 4 and 5. The NNAP is aligned to the government’s Medium Term Plans (MTPs) to enable mainstreaming of the nutrition budgeting process into national development plans, and facilitate allocation of resources to nutrition programmes. Chapter Four presents the results on birth weight; breastfeeding, and infant and young child feeding practices and use of iodized salt at household.24 4.1 Birth Weight Weight at birth is a good indicator not only of a mother's health and nutritional status but also the newborn's chances for survival, growth, long-term health and psychosocial development. Low birth weight (defined as less than 2,500 grams) carries a range of grave health risks for children. Babies who were undernourished in the womb face a greatly increased risk of dying during their early days, months and years. Those who survive may have impaired immune function and increased risk of disease; they are likely to remain undernourished, with reduced muscle strength, throughout their lives, and suffer a higher incidence of diabetes and heart disease in later life. Children born with low birth weight also risk a lower IQ and cognitive disabilities, affecting their performance in school and their job opportunities as adults. In the developing world, low birth weight stems primarily from the mother's poor health and nutrition. Three factors have most impact: the mother's poor nutritional status before conception, short stature (due mostly to under nutrition and infections during her childhood), and poor nutrition during pregnancy. Inadequate weight gain during pregnancy is particularly important since it accounts for a large proportion of foetal growth retardation. Moreover, diseases such as diarrhoea and malaria, which are common in many developing countries, can significantly impair foetal growth if the mother becomes infected while pregnant. In the industrialized world, cigarette smoking during pregnancy is the leading cause of low birth weight. In developed and developing countries alike, teenagers who give birth when their own bodies have yet to finish growing run a higher risk of bearing low birth weight babies. 22 Government of Kenya, 2011. National Food and Nutrition Security Policy. 23 The Partnership for Maternal, Newborn and Child Health, 2012. Maternal and Child Health: Kenya 24 A section on anthropometric indicators was excluded from the report due to data quality issues. Bungoma County MICS 2013/14 P a g e | 20 One of the major challenges in measuring the incidence of low birth weight is that more than half of infants in the developing world are not weighed at birth. In the past, most estimates of low birth weight for developing countries were based on data compiled from health facilities. However, these estimates are biased for most developing countries because the majority of newborns are not delivered in health facilities, and those who are, represent only a sample of all births. Since many infants are not weighed at birth and those who are weighed may be a biased sample of all births, the reported birth weights usually cannot be used to estimate the prevalence of low birth weight among all children. Therefore, the percentage of births weighing below 2,500 grams is estimated from two items in the questionnaire: the mother’s assessment of the child’s size at birth (i.e., very small, smaller than average, average, larger than average, very large) and the mother’s recall of the child’s weight or the weight as recorded on a health card if the child was weighed at birth.25 In Bungoma County, 47 percent of last the live-born births in the last two years preceding the survey were weighed at birth and approximately five percent of infants weighed less than 2,500 grams at birth (Table NU.1). The prevalence of low birth weight varied slightly by urban-rural residence, birth order, and by mother’s education. 25 For a detailed description of the methodology, see Boerma, JT et al. 1996. Data on Birth Weight in Developing Countries: Can Surveys Help? Bulletin of the World Health Organization 74(2): 209-16. Bungoma County MICS 2013/14 P a g e | 21 Table NU.1: Low birth weight infants Percentage of last live-born children in the last two years that are estimated to have weighed below 2,500 grams at birth and percentage of live births weighed at birth, Bungoma County MICS, 2013/14 Percent distribution of births by mother's assessment of size at birth Total Percentage of live births: Number of last live- born children in the last two years Very small Smaller than average Average Larger than average or very large DK Below 2,500 grams1 Weighed at birth2 Total 1.8 4.6 62.9 28.3 2.4 100.0 5.3 47.3 311 Mother's age at birth Less than 20 years (8.0) (0.0) (69.9) (19.5) (2.6) 100.0 (10.4) (39.7) 33 20-34 years 0.9 5.1 61.3 30.5 2.3 100.0 4.5 48.7 227 35-49 years (1.8) (5.6) (65.4) (24.4) (2.8) 100.0 (5.5) (45.9) 51 Birth order 1 3.6 2.9 60.2 31.1 2.3 100.0 6.8 55.1 74 2-3 0.5 3.3 65.2 29.3 1.7 100.0 3.7 48.3 91 4-5 0.6 10.2 61.7 23.9 3.6 100.0 5.4 50.5 76 6+ 2.9 2.2 64.1 28.7 2.1 100.0 5.9 34.0 69 Area Urban 2.3 6.6 56.2 31.1 3.8 100.0 6.3 62.5 137 Rural 1.4 3.1 68.2 26.1 1.3 100.0 4.6 35.3 174 Mother’s education None (*) (*) (*) (*) (*) 100.0 (*) (*) 5 Primary 2.9 4.1 60.5 30.5 1.9 100.0 6.4 38.1 189 Secondary+ 0.0 4.4 66.5 25.9 3.3 100.0 3.5 62.9 116 Wealth index quintile Poorest 3.6 7.0 68.9 19.4 1.2 100.0 7.6 30.3 68 Second 2.1 5.2 57.4 33.1 2.2 100.0 5.8 45.7 65 Middle 3.1 2.4 61.7 32.7 0.0 100.0 6.2 40.5 55 Fourth 0.0 2.0 60.0 33.6 4.3 100.0 2.9 43.7 56 Richest 0.0 5.6 65.6 24.6 4.1 100.0 3.8 74.1 68 Ethnicity of household head Luhya 1.4 4.6 65.3 27.0 1.8 100.0 4.9 45.0 272 Other ethnic group 4.4 5.1 46.5 37.7 6.3 100.0 8.4 63.4 39 1 MICS indicator 2.20 - Low-birthweight infants 2 MICS indicator 2.21 - Infants weighed at birth ( ) Figures that are based on 25-49 unweighted cases (*) Figures that are based on fewer than 25 unweighted cases 4.2 Breastfeeding and Infant and Young Child Feeding Proper feeding of infants and young children can increase their chances of survival; it can also promote optimal growth and development, especially in the critical window from birth to two years of age. Breastfeeding for the first two years of life protects children from infection, provides an ideal source of nutrients, and is economical and safe. However, many mothers do not start to breastfeed early enough, do not breastfeed exclusively for the recommended 6 months or stop breastfeeding too soon. There are often pressures to switch to infant formula, which can contribute to growth faltering and micronutrient deficiency. In addition, it can be unsafe if hygienic conditions, including safe drinking water are not readily available. Studies have shown that, in addition to continued breastfeeding, Bungoma County MICS 2013/14 P a g e | 22 consumption of appropriate, adequate and safe solid, semi-solid and soft foods from the age of 6 months onwards leads to better health and growth outcomes, with potential to reduce stunting during the first two years of life.26 UNICEF and WHO recommend that infants be initiated to breastfeeding within one hour of birth, breastfed exclusively for the first six months of life and continue to be breastfed up to two years of age and beyond.27 Starting at 6 months, breastfeeding should be combined with safe, age-appropriate feeding of solid, semi-solid and soft foods.28 A summary of key guiding principles29, 30 for feeding 6-23 month olds is provided in Table NU.2. A below along with proximate measures for these guidelines collected in this survey. The guiding principles for which proximate measures and indicators exist are: (i) continued breastfeeding; (ii) appropriate frequency of meals (but not energy density); and (iii) appropriate nutrient content of food. Feeding frequency is used as proxy for energy intake, requiring children to receive a minimum number of meals/snacks (and milk feeds for non-breastfed children) for their age. Dietary diversity is used to ascertain the adequacy of the nutrient content of the food (not including iron) consumed. For dietary diversity, seven food groups were created for which a child consuming at least four of these is considered to have a better quality diet. In most populations, consumption of at least four food groups means that the child has a high likelihood of consuming at least one animal-source food and at least one fruit or vegetable, in addition to a staple food (grain, root or tuber).31 These three dimensions of child feeding are combined into an assessment of the children who received appropriate feeding, using the indicator of “minimum acceptable diet”. To have a minimum acceptable diet in the previous day, a child must have received: (i) the appropriate number of meals/snacks/milk feeds; (ii) food items from at least 4 food groups; and (iii) breastmilk or at least 2 milk feeds (for non-breastfed children). Table NU.3 is based on mothers’ reports of what their last-born child, born in the last two years, was fed in the first few days of life. It indicates the proportion who were ever breastfed, those who were first breastfed within one hour and one day of birth, and those who received a prelacteal feed.32 26 Bhuta, Z. et al. 2013. Evidence-based interventions for improvement of maternal and child nutrition: what can be done and at what cost? The Lancet June 6, 2013. 27 WHO. 2003. Implementing the Global Strategy for Infant and Young Child Feeding. Meeting Report Geneva, 3-5 February, 2003. 28 WHO. 2003. Global Strategy for Infant and Young Child Feeding. 29 PAHO. 2003. Guiding principles for complementary feeding of the breastfed child. 30 WHO. 2005. Guiding principles for feeding non-breastfed children 6-24 months of age. 31 WHO. 2008. Indicators for assessing infant and young child feeding practices. Part 1: Definitions. 32 Prelacteal feed refers to the provision of any liquid or food, other than breastmilk, to a newborn during the period when breastmilk flow is generally being established (estimated here as the first 3 days of life). Bungoma County MICS 2013/14 P a g e | 23 Table NU.2: Guiding Principles for Feeding children age 6 – 23 months Guiding Principle (age 6-23 months) Proximate measures Table Continue frequent, on-demand breastfeeding for two years and beyond Breastfed in the last 24 hours NU.4 Appropriate frequency and energy density of meals Breastfed children Depending on age, two or three meals/snacks provided in the last 24 hours Non-breastfed children Four meals/snacks and/or milk feeds provided in the last 24 hours NU.6 Appropriate nutrient content of food Four food groups33 eaten in the last 24 hours NU.6 Appropriate amount of food No standard indicator exists na Appropriate consistency of food No standard indicator exists na Use of vitamin-mineral supplements or fortified products for infant and mother No standard indicator exists na Practice good hygiene and proper food handling While it was not possible to develop indicators to fully capture programme guidance, one standard indicator does cover part of the principle: Not feeding with a bottle with a nipple NU.9 Practice responsive feeding, applying the principles of psycho-social care No standard indicator exists na 33 Food groups used for assessment of this indicator are 1) Grains, roots and tubers, 2) legumes and nuts, 3) dairy products (milk, yogurt, cheese), 4) flesh foods (meat, fish, poultry and liver/organ meats), 5) eggs, 6) vitamin-A rich fruits and vegetables, and 7) other fruits and vegetables. Bungoma County MICS 2013/14 P a g e | 24 Table NU.3: Initial breastfeeding Percentage of last live-born children in the last two years who were ever breastfed, breastfed within one hour of birth, and within one day of birth, and percentage who received a prelacteal feed, Bungoma County MICS, 2013/14 Percentage who were ever breastfed1 Percentage who were first breastfed: Percentage who received a prelacteal feed Number of last live-born children in the last two years Within one hour of birth2 Within one day of birth Total 97.3 50.8 80.9 31.3 311 Area Urban 94.8 54.7 81.7 23.8 137 Rural 99.3 47.6 80.2 37.2 174 Months since last birth 0-11 months 98.4 56.9 79.8 35.1 161 12-23 months 96.1 44.1 82.1 27.2 150 Assistance at delivery Skilled attendant 97.9 55.4 82.4 26.9 154 Traditional birth attendant 100.0 52.2 86.5 37.7 78 Other (100.0) (44.6) (77.1) (41.1) 37 No one/Missing (88.0) (36.7) (68.3) (26.7) 42 Place of delivery Home 100.0 44.7 82.3 36.4 161 Health facility 97.7 59.7 82.5 26.5 144 Public 98.8 58.0 82.0 28.1 120 Private (92.2) (68.3) (85.0) (18.2) 24 Mother’s education None (*) (*) (*) (*) 5 Primary 98.8 49.2 80.3 35.6 189 Secondary+ 94.8 55.4 82.9 22.5 116 Wealth index quintile Poorest 97.1 42.8 78.7 26.5 68 Second 97.8 50.5 78.3 44.6 65 Middle 100.0 42.1 78.8 38.3 55 Fourth 97.5 60.9 88.2 19.6 56 Richest 94.8 57.7 81.1 27.1 68 Ethnicity of household head Luhya 98.1 51.2 81.5 33.1 272 Other ethnic group 91.8 47.7 76.3 18.8 39 1 MICS indicator 2.5 - Children ever breastfed 2 MICS indicator 2.6 - Early initiation of breastfeeding ( ) Figures that are based on 25-49 unweighted cases (*) Figures that are based on fewer than 25 unweighted cases Ninety-seven percent of the children were ever breastfed (Table NU.3). However, although a very important step in management of lactation and establishment of a physical and emotional relationship between the baby and the mother, 51 percent of babies were breastfed for the first time within one hour of birth and 81 percent of newborns in Bungoma County started breastfeeding within one day of birth. Fifty-five percent of children residing in urban areas in the last two years preceding the survey were breastfed within the hour of birth with 48 percent breastfed within the same timeframe in rural areas (Figure NU.1). Babies delivered by a skilled birth attendant were more likely to be breastfed within one hour of birth compared to those delivered by other attendants. Bungoma County MICS 2013/14 P a g e | 25 About one-third of the babies received prelacteal feed. Babies were more likely to receive prelacteal feed when delivered in a rural area, delivered by a traditional birth attendant, or delivered at home. Figure NU. 1: In i t iat ion of breastfeeding, Bungoma County MICS, 2013/14 The set of Infant and Young Child Feeding indicators reported in Tables NU.4 through NU.8 are based on the mother’s report of consumption of food and fluids during the day or night prior to being interviewed. Data are subject to a number of limitations, some related to the mother’s ability to provide a full report on the child’s liquid and food intake due to recall errors as well as lack of knowledge in cases where the child was fed by other individuals. In Table NU.4, breastfeeding status is presented for both Exclusively breastfed and Predominantly breastfed; referring to infants age less than 6 months who are breastfed, distinguished by the former only allowing vitamins, mineral supplements, and medicine and the latter allowing also plain water and non-milk liquids. The table also shows continued breastfeeding of children at 12-15 and 20-23 months of age. Approximately 43 percent of children age less than six months were exclusively breastfed (Table NU.4).34 With 59 percent predominantly breastfed, it is evident that a large proportion of mothers need to be informed about the benefits of exclusive breastfeeding. By age 12-15 months, 75 percent of children continued to be breastfed and by age 20-23 months, only 40 percent were still being breastfed. 34 Background characteristics variables are not included in Table NU.4 due to insufficient sample size. 82 80 81 55 48 51 0 20 40 60 80 100 Urban Rural Bungoma County P e rc e n t Within one day Within one hour Bungoma County MICS 2013/14 P a g e | 26 Table NU.4: Breastfeeding Percentage of living children according to breastfeeding status at selected age groups, Bungoma County MICS, 2013/14 Children age 0-5 months Children age 12-15 months Children age 20-23 months Percent exclusively breastfed1 Percent predominantly breastfed2 Number of children Percent breastfed (Continued breastfeeding at 1 year)3 Number of children Percent breastfed (Continued breastfeeding at 2 years)4 Number of children Total 43.1 58.5 83 75.3 52 40.2 50 1 MICS indicator 2.7 - Exclusive breastfeeding under 6 months 2 MICS indicator 2.8 - Predominant breastfeeding under 6 months 3 MICS indicator 2.9 - Continued breastfeeding at 1 year 4 MICS indicator 2.10 - Continued breastfeeding at 2 years Table NU.5 shows the median duration of breastfeeding according to selected background characteristics. Among children under 3 years of age, the median duration for ever breastfeeding is 21 months, two months for exclusive breastfeeding, and three months for predominant breastfeeding. Table NU.5: Duration of breastfeeding Median duration of any breastfeeding, exclusive breastfeeding, and predominant breastfeeding among children age 0-35 months, Bungoma County MICS, 2013/14 Median duration (in months) of: Number of children age 0-35 months Any breastfeeding1 Exclusive breastfeeding Predominant breastfeeding Median 20.8 2.1 3.4 479 Sex Male 20.5 1.9 2.3 237 Female 21.0 2.5 4.5 242 Area Urban 21.3 2.2 4.0 214 Rural 20.4 2.0 3.1 264 Mother’s education None (*) - - 12 Primary 20.0 1.3 3.6 288 Secondary+ 21.1 3.1 3.8 178 Wealth index quintile Poorest 20.5 0.7 2.3 115 Second 21.3 2.1 3.7 100 Middle 18.9 2.3 2.3 96 Fourth 21.5 2.8 4.7 82 Richest 20.9 4.0 4.5 85 Ethnicity of household head Luhya 20.7 1.9 3.2 428 Other ethnic group 21.6 3.2 4.0 51 Mean 20.2 2.9 4.1 479 1 MICS indicator 2.11 - Duration of breastfeeding (*) Figures that are based on fewer than 25 unweighted cases Bungoma County MICS 2013/14 P a g e | 27 The age-appropriateness of breastfeeding of children under age 24 months is provided in Table NU.6. Different criteria of feeding were used depending on the age of the child. For infants age 0-5 months, exclusive breastfeeding was considered as age-appropriate feeding, while children age 6-23 months were considered to be appropriately fed if they were receiving breastmilk and solid, semi-solid or soft food. As a result of feeding patterns in Bungoma County, only 71 percent of children age 6-23 months are being appropriately breastfed and age-appropriate breastfeeding among all children age 0-23 months drops to 64 percent. Variations by household wealth are evident, where the proportion of children age 0-23 months appropriately breastfed is 49 percent in the poorest households and 79 percent in the richest. Table NU.6: Age-appropriate breastfeeding Percentage of children age 0-23 months who were appropriately breastfed during the previous day, Bungoma County MICS, 2013/14 Children age 0-5 months Children age 6-23 months Children age 0-23 months Percent exclusively breastfed1 Number of children Percent currently breastfeeding and receiving solid, semi- solid or soft foods Number of children Percent appropriately breastfed2 Number of children Total 43.1 83 70.7 236 63.5 319 Sex Male (36.6) 42 70.2 117 61.4 159 Female (49.7) 42 71.2 118 65.6 160 Area Urban (40.7) 31 67.7 117 62.0 148 Rural (44.6) 52 73.7 119 64.8 171 Mother’s education None (*) 4 (*) 4 (*) 8 Primary (38.7) 47 69.6 141 61.9 188 Secondary+ (55.1) 32 73.2 90 68.4 123 Wealth index quintile Poorest (31.3) 29 (60.4) 45 48.9 74 Second (*) 18 (65.5) 51 57.2 68 Middle (*) 11 (78.0) 51 72.2 62 Fourth (*) 14 (67.5) 41 64.1 55 Richest (*) 12 80.9 48 79.1 60 Ethnicity of household head Luhya 40.5 73 69.5 210 62.0 284 Other ethnic group (*) 10 (80.7) 26 75.7 36 1 MICS indicator 2.7 - Exclusive breastfeeding under 6 months 2 MICS indicator 2.12 - Age-appropriate breastfeeding ( ) Figures that are based on 25-49 unweighted cases (*) Figures that are based on fewer than 25 unweighted cases Overall, 81 percent of infants age 6-8 months received solid, semi-solid, or soft foods at least once during the previous day (Table NU.7)35. The same percentage is noted among currently breastfeeding infants. 35 Descriptions by rural/urban areas and sex of child were not done due to small numbers of respondents in those categories. Bungoma County MICS 2013/14 P a g e | 28 Table NU.7: Introduction of solid, semi-solid, or soft foods Percentage of infants age 6-8 months who received solid, semi-solid, or soft foods during the previous day, Bungoma County MICS, 2013/14 Currently breastfeeding Currently not breastfeeding All Percent receiving solid, semi- solid or soft foods Number of children age 6-8 months Percent receiving solid, semi- solid or soft foods Number of children age 6-8 months Percent receiving solid, semi- solid or soft foods1 Number of children age 6-8 months Total 81.1 50 (*) 1 81.4 51 1 MICS indicator 2.13 - Introduction of solid, semi-solid or soft foods (*) Figures that are based on fewer than 25 unweighted cases Overall, about half of the children age 6-23 months were receiving solid, semi-solid and soft foods the minimum number of times (Table NU.8).36 The proportion of children receiving the minimum dietary diversity, or foods from at least four food groups, was much lower than that for the minimum meal frequency, indicating the need to focus on improving diet quality and nutrient intake among this vulnerable group. The overall assessment using the indicator of minimum acceptable diet revealed that only 22 percent were benefitting from a diet sufficient in both diversity and frequency (18 percent males and 26 percent females). 36 Note that a comparison between children 6-23 months currently breastfeeding and those currently not breastfeeding was removed from Table NU.8 because a high proportion of children were currently breastfeeding. Bungoma County MICS 2013/14 P a g e | 29 Table NU.8: Infant and young child feeding (IYCF) practices Percentage of children age 6-23 months who received appropriate liquids and solid, semi-solid, or soft foods the minimum number of times or more during the previous day, by breastfeeding status, Bungoma County MICS, 2013/14 Currently breastfeeding Currently not breastfeeding All Percent of children who received: Number of children age 6- 23 months Percent of children who received: Number of children age 6- 23 months Percent of children who received: Number of children age 6- 23 months Minimum dietary diversitya Minimum meal frequencyb Minimum acceptable diet1, c Minimum dietary diversitya Minimum meal frequencyb Minimum acceptable diet2, c At least 2 milk feeds3 Minimum dietary diversity4, a Minimum meal frequency5, b Minimum acceptable dietc Total 41.7 48.3 23.9 179 (41.1) (52.7) (16.3) (25.2) 50 41.8 49.2 22.2 236 Sex Male 40.1 45.9 20.3 89 (37.4) (70.8) (9.5) (15.8) 24 40.6 51.2 18.1 117 Female 43.3 50.5 27.4 91 (*) (*) (*) (*) 26 43.0 47.3 26.2 118 Age 6-8 months 19.5 50.2 7.3 50 (*) (*) (*) (*) 1 19.2 49.4 7.2 51 9-11 months (57.9) (33.0) (27.3) 32 (*) (*) (*) (*) 1 (55.9) (31.9) (26.3) 33 12-17 months 33.0 44.8 13.4 53 (*) (*) (*) (*) 15 29.1 43.6 11.8 70 18-23 months (65.2) (61.4) (52.7) 44 (54.0) (62.1) (22.0) (33.8) 33 60.8 61.7 39.6 82 Area Urban 44.6 46.7 26.6 84 (34.2) (52.6) (11.5) (16.6) 29 41.4 48.2 22.7 117 Rural 39.2 49.6 21.5 95 (*) (*) (*) (*) 21 42.1 50.2 21.7 119 Mother’s education None (*) (*) (*) 2 (*) (*) (*) (*) 2 (*) (*) (*) 4 Primary 35.4 41.1 16.1 108 (37.1) (54.5) (5.7) (18.5) 30 36.2 44.0 13.8 141 Secondary+ 50.5 60.0 36.6 70 (*) (*) (*) (*) 18 50.6 58.9 36.4 90 Wealth index quintile Poorest (42.9) (56.3) (33.5) 29 (*) (*) (*) (*) 12 (40.2) (50.1) (25.6) 45 Second (31.1) (44.7) (15.0) 37 (*) (*) (*) (*) 11 (26.4) (48.0) (11.7) 51 Middle (45.5) (41.4) (23.3) 41 (*) (*) (*) (*) 10 (47.6) (40.7) (18.8) 51 Fourth (42.9) (40.7) (23.0) 32 (*) (*) (*) (*) 10 (47.2) (48.5) (25.7) 41 Richest (45.9) (58.7) (26.5) 40 (*) (*) (*) (*) 8 48.7 59.4 30.5 48 Ethnicity of household head Bungoma County MICS 2013/14 P a g e | 30 Luhya 43.1 48.7 25.5 158 (38.5) (50.1) (14.9) (21.4) 47 42.3 49.0 23.0 210 Other ethnic group (31.2) (45.3) (12.7) 22 (*) (*) (*) (*) 4 (37.4) (51.0) (15.7) 26 1 MICS indicator 2.17a - Minimum acceptable diet (breastfed) 2 MICS indicator 2.17b - Minimum acceptable diet (non-breastfed) 3 MICS indicator 2.14 - Milk feeding frequency for non-breastfed children 4 MICS indicator 2.16 - Minimum dietary diversity 5 MICS indicator 2.15 - Minimum meal frequency a Minimum dietary diversity is defined as receiving foods from at least 4 of 7 food groups: 1) Grains, roots and tubers, 2) legumes and nuts, 3) dairy products (milk, yogurt, cheese), 4) flesh foods (meat, fish, poultry and liver/organ meats), 5) eggs, 6) vitamin-A rich fruits and vegetables, and 7) other fruits and vegetables. b Minimum meal frequency among currently breastfeeding children is defined as children who also received solid, semi-solid, or soft foods 2 times or more daily for children age 6-8 months and 3 times or more daily for children age 9-23 months. For non-breastfeeding children age 6-23 months it is defined as receiving solid, semi-solid or soft foods, or milk feeds, at least 4 times. c The minimum acceptable diet for breastfed children age 6-23 months is defined as receiving the minimum dietary diversity and the minimum meal frequency, while it for non-breastfed children further requires at least 2 milk feedings and that the minimum dietary diversity is achieved without counting milk feeds. ( ) Figures that are based on 25-49 unweighted cases (*) Figures that are based on fewer than 25 unweighted cases Bungoma County MICS 2013/14 P a g e | 31 The continued practice of bottle-feeding is a concern because of the possible contamination due to unsafe water and lack of hygiene in preparation. Table NU.9 shows that bottle-feeding is prevalent for children under two years of age in Bungoma County. About 16 percent of children under 6 months are fed using a bottle with a nipple. This practice is more prevalent in the following background categories: 6-11 months old, urban residency, children with mothers who attained secondary/higher education. Table NU.9: Bottle feeding Percentage of children age 0-23 months who were fed with a bottle with a nipple during the previous day, Bungoma County MICS, 2013/14 Percentage of children age 0-23 months fed with a bottle with a nipple1 Number of children age 0-23 months Total 15.6 319 Sex Male 15.8 159 Female 15.5 160 Age 0-5 months 13.2 83 6-11 months 23.1 84 12-23 months 12.8 152 Area Urban 18.8 148 Rural 12.9 171 Mother’s education None (*) 8 Primary 11.8 188 Secondary+ 22.5 123 Wealth index quintile Poorest 4.8 74 Second 11.9 68 Middle 22.3 62 Fourth 16.4 55 Richest 25.7 60 Ethnicity of household head Luhya 15.2 284 Other ethnic group 19.2 36 1 MICS indicator 2.18 - Bottle feeding (*) Figures that are based on fewer than 25 unweighted cases 4.3 Salt Iodization Iodine Deficiency Disorders (IDD) is the world’s leading cause of preventable mental retardation and impaired psychomotor development in young children. In its most extreme form, iodine deficiency causes cretinism. It also increases the risks of stillbirth and miscarriage in pregnant women. Iodine deficiency is most commonly and visibly associated with goitre. IDD takes its greatest toll in impaired mental growth and development, contributing in turn to poor school performance, reduced intellectual ability, and impaired work performance. The indicator is the percentage of households consuming adequately iodized salt (>15 parts per million). Bungoma County MICS 2013/14 P a g e | 32 The IDD legislation passed in Kenya in 1978 (revised in 1988) covers all salt produced for human consumption. Specifications for edible salt are reviewed regularly (latest revision was in September 2000) by the Kenya Bureau of Standards. Iodization of salt is mandatory. The mandated level of iodization is 168.5 mg/kg of salt, or 100ppm.37 The Ministry of Health monitors IDD in the country. In 92 percent of households in Bungoma, salt used for cooking was tested for iodine content by using salt test kits and testing for the presence of potassium iodate content. Table NU.10 shows that in five percent of households, there was no salt available. These households were included in the denominator of the indicator. In 94 percent of households, salt was found to contain at least 15 parts per million (ppm) or more of iodine. Table NU.10: Iodized salt consumption Percent distribution of households by consumption of iodized salt, Bungoma County MICS, 2013/14 Percentage of households in which salt was tested Number of households Percent of households with: Total Number of households in which salt was tested or with no salt No salt >0 and <15 PPM 15+ PPM1 Total 92.1 1,246 5.0 0.6 94.4 100.0 1,208 Area Urban 90.8 614 4.3 0.3 95.5 100.0 582 Rural 93.3 632 5.7 0.9 93.4 100.0 626 Wealth index quintile Poorest 89.7 246 9.0 0.0 91.0 100.0 243 Second 96.8 226 2.5 2.6 94.9 100.0 224 Middle 90.1 233 5.8 0.0 94.2 100.0 223 Fourth 91.2 256 3.9 0.2 96.0 100.0 243 Richest 92.9 285 3.8 0.4 95.8 100.0 275 1 MICS indicator 2.19 - Iodized salt consumption The consumption of adequately iodized salt is graphically presented in Figure NU.2 together with the percentage of salt containing less than 15 ppm. More than 90 percent of households in both urban (96 percent) and rural areas (93 percent) are using adequately iodized salt. There is no difference in use of iodized salt by household wealth. 37 http://www.tulane.edu/~internut/Countries/Kenya/kenyaiodine.html http://www.tulane.edu/~internut/Countries/Kenya/kenyaiodine.html Bungoma County MICS 2013/14 P a g e | 33 Figure NU. 2: Consumption of iodized sa lt , Bungoma Count y MICS, 2013/14 96 94 91 98 94 96 96 95 96 93 91 95 94 96 96 94 80 100 P e rc e n t Any iodine 15+ PPM of iodine Bungoma County MICS 2013/14 P a g e | 34 5. Child Health Kenya has acceded and ratified a number of major international and regional conventions some of which aim at ensuring child survival, growth and development. In 1990, Kenya ratified the United Nations Convention on the rights of the Child (CRC).38, 39 Article 6 of the CRC refers to the right to life, survival and development. The term ‘development’ in this context refers to physical, mental, emotional, cognitive, social and cultural development. Further, Article 24 states that ‘children have the right to good quality health care – the best health care possible – to safe drinking water, nutritious food, a clean and safe environment, and information to help them stay healthy’.40 The United Nations Millennium Declaration, signed in September 2000, commits world leaders to combat poverty, hunger, disease, illiteracy, environmental degradation, and discrimination against women. The objective of one of the Millennium Development Goals (MDGs) – MDG 4 - is to reduce child mortality by two thirds between 1990 and 2015. The Constitution of Kenya (2010) states that every person has the right to the highest attainable standard of health, which includes the right to health care services, including reproductive health care. This chapter presents the results on the following subtopics: vaccinations; neonatal tetanus protection; and care of illnesses (diarrhoea, acute respiratory infections, malaria/fever); and use of solid fuels. 5.1 Vaccinations Immunization plays a key part in reducing preventable child diseases and mortality. The Global Vaccine Action Plan (GVAP) was endorsed by the 194 Member States of the World Health Assembly in May 2012 to achieve the Decade of Vaccines vision by delivering universal access to immunization. Immunization has saved the lives of millions of children in the four decades since the launch of the Expanded Programme on Immunization (EPI) in 1974. Worldwide there are still millions of children not reached by routine immunization and as a result, vaccine-preventable diseases cause more than 2 million deaths every year. The WHO Recommended Routine Immunizations for Children41states that all children to be vaccinated against tuberculosis, diphtheria, pertussis, tetanus, polio, measles, hepatitis B, haemophilus influenzae type b, pneumonia/meningitis, rotavirus, and rubella. All doses in the primary series are recommended to be completed before the child’s first birthday, although depending on the epidemiology of disease in a country, the first doses of measles and rubella containing vaccines may be recommended at 12 months or later. The recommended number and timing of most other doses also vary slightly with local epidemiology and may include booster doses later in childhood. 38Kenya Human Rights Commission. 2010. Towards Equality and Anti-Discrimination: An Overview of International and Domestic Law an Anti-discrimination in Kenya. 39The Kenyan Section of the International Commission of Jurists. 2004. International Human Rights Standards: Reporting Obligations – The Convention of the Rights of the Child. 40The United Nations General Assembly. 1989. The Convention on the Rights of the Child. 41http://www.who.int/immunization/diseases/en. Table 2 includes recommendations for all children and additional antigens recommended only for children residing in certain regions of the world or living in certain high-risk population groups. http://www.who.int/immunization/diseases/en Bungoma County MICS 2013/14 P a g e | 35 The Kenya Expanded Programme on Immunization (KEPI) was established in 1980 and is integrated within the Department of Preventive and Promotive Health Services of the Ministry of Health as part of the Essential Health Package (EHP). KEPI is now known as the Division of Vaccine and Immunisation (DVI). The Kenya National Immunization Programme immunization schedule is shown below. All vaccines should be received during the first year of life except the second dose of measles given at 18 months. Yellow fever is given at 9 months to children in selected sub-counties in the former Rift Valley province.42 Child Immunization Schedule in Kenya43, 44 Vaccine Age Remarks BCG Vaccine: at birth Intra-dermal left forearm; BCG Scar checked Dose: (0.05mls) Below 1 year Dose: (0.1mls) Above 1 year Oral Polio Vaccine (OPV) 2 drops (orally) Birth dose: OPV 0 At birth or within 2 weeks 1st dose: OPV 1 At 6 weeks 2nd dose: OPV 2 At 10 weeks 3rd dose: OPV 3 At 14 weeks Diphtheria/Pertussis/Tetanus/Hepatitis B/haemophilus influenzae Type b 0.5mls (intra-muscular left outer thigh) 1st dose 6 weeks 2nd dose 10 weeks 3rd dose 14 weeks Pneumococcal Vaccine 0.5mls (intra-muscular right outer thigh) 1st dose 6 weeks 2nd dose 10 weeks 3rd dose 14 weeks Rota Virus (Rotarix) 1.5mls (orally) 1st dose 6 weeks 2nd dose 10 weeks Measles Vaccine at 6 months: in the event of measles outbreak or HIV exposed children (HEI) 6 months 0.5mls (Subcutaneously right upper arm) Measles Vaccine 9 months Measles Vaccine 18 months Yellow Fever 9 months 0.5mls (Intra-muscular left upper deltoid) Other Vaccines Other vaccines refer to those not in the usual KEPI schedule 42 MICS 2013/14 collected data on Yellow Fever but further analysis is required before the findings can be shared. 43Ministry of Health, 2013. Mother and Child Heath Booklet. Republic of Kenya 44Kenya is planning to carryout out a Measles-Rubella (MR) and IPV Campaign in 2016, and subsequently include MR in the child immunization schedule in 2017. Bungoma County MICS 2013/14 P a g e | 36 and may include MMR, Typhoid, etc. In Bungoma County, the MICS collected data on immunization coverage for all children under three years of age. All mothers or caretakers were asked to provide vaccination cards. If the immunization card for a child was available, interviewers copied vaccination information from the cards onto the MICS questionnaire. If no immunization card was available for the child, the interviewer proceeded to ask the mother to recall whether or not the child had received each of the vaccines as per the schedule. The final immunization coverage estimates are based on information obtained from the immunization card and/or the mother’s report. The percentage of children age 12-23 months and 24-35 months who had received each of the specific vaccines by source of information (immunization card and mother’s recall) is shown in Table CH.1 and Figure CH.1. The denominators for the table are comprised of children age 12-23 months and 24-35 months and only children who are in these age groups are counted. In the first three columns in each panel of the table, the numerator includes all children who were vaccinated at any time before the survey according to the immunization card or the mother’s report. In the last column in each panel, only those children who were fully immunized before their first birthday, as recommended, were included. The proportion of children immunized before the first birthday but without immunization card/record was assumed to be the same as for those with vaccination cards/records. Most children age 12-23 months had been vaccinated against BCG and measles by the age of 12 months (96 and 92 percent, respectively), and had received the first dose of DPT, HepB, and Hib vaccines (97 percent, 88 percent and 94 percent, respectively). The percentages declined for the second and third doses of DPT, HepB, and Hib. Similarly, 96 percent of children age 12-23 months had received Polio 1 by age 12 months and this declined to 78 percent by the third dose. As a result, the percentage of children 12-23 months of age who had been fully vaccinated by their first birthday was low at only 56 percent. The proportion of children fully vaccinated by 12 months of age was lower for children age 24-35 months (30 percent). The individual coverage figures for children age 24-35 months are generally lower to those age 12-23 months suggesting that immunization coverage has been on average improving in Bungoma County between 2011 and 2013. Bungoma County MICS 2013/14 P a g e | 37 Table CH.1: Vaccinations in the first years of life Percentage of children age 12-23 months and 24-35 months vaccinated against vaccine preventable childhood diseases at any time before the survey and by their first birthday, Bungoma County MICS, 2013/14 Children age 12-23 months: Children age 24-35 months: Vaccinated at any time before the survey according to: Vaccinated by 12 months of agea Vaccinated at any time before the survey according to: Vaccinated by 12 months of age Vaccination card Mother's report Either Vaccination card Mother's report Either Antigen BCG1 63.4 33.7 97.1 95.7 46.3 53.0 99.3 89.8 Polio At birth 59.5 25.7 85.2 82.9 43.4 39.8 83.1 79.5 1 63.4 34.3 97.8 96.4 46.2 52.7 99.0 88.7 2 63.4 33.0 96.4 95.0 46.7 50.4 97.1 87.1 32 62.5 15.8 78.4 77.5 45.7 27.0 72.7 63.6 DPT 1 63.6 34.9 98.6 97.2 46.5 52.7 99.2 88.9 2 63.6 31.2 94.8 93.5 47.0 47.0 94.0 84.3 33 62.8 25.9 88.7 87.7 46.0 44.8 90.8 79.5 HepB At birth 59.3 29.5 88.8 85.2 43.3 42.7 86.0 82.0 1 65.9 23.0 88.9 87.7 46.5 44.6 91.1 81.6 2 65.9 18.8 84.7 83.5 47.0 41.4 88.4 79.4 34 65.0 2.1 67.2 81.1 46.0 8.9 54.9 48.0 Hib 1 59.2 35.5 94.8 93.8 37.6 57.3 94.9 87.9 2 59.2 27.8 87.0 86.1 37.6 55.9 93.5 87.3 35 58.7 26.8 85.5 83.9 37.6 50.8 88.4 79.7 Measles (MCV1)7 59.5 38.9 98.3 91.8 44.7 52.1 96.7 79.0 Fully vaccinated8, b 64.0 0.0 64.0 56.3 47.0 3.8 50.8 30.2 No vaccinations 0.0 0.9 0.9 1.6 0.0 0.7 0.7 3.7 Number of children 152 152 152 152 160 160 160 160 1 MICS indicator 3.1 - Tuberculosis immunization coverage 2 MICS indicator 3.2 - Polio immunization coverage 3 MICS indicator 3.3 - Diphtheria, pertussis and tetanus (DPT) immunization coverage 4 MICS indicator 3.5 - Hepatitis B immunization coverage 5 MICS indicator 3.6 - Haemophilus influenzae type B (Hib) immunization coverage 6 MICS indicator 3.7 - Yellow fever immunization coverage45 7 MICS indicator 3.4; MDG indicator 4.3 - Measles immunization coverage 8 MICS indicator 3.8 - Full immunization coverage a All MICS indicators refer to results in this column b Includes: BCG, Polio3, DPT3, HepB3, Hib3, and Measles (MCV1) as per the vaccination schedule in Country 45 Yellow fever immunization coverage not included in analysis Bungoma County MICS 2013/14 P a g e | 38 Figure CH.1: Vacc inat ions by age 12 months Bungoma Count y MICS, 2013/14 Table CH.2 presents vaccination coverage estimates among children age 12-23 months by background characteristics. The figures indicate children receiving the vaccinations at any time up to the date of the survey, and are based on information from both the vaccination cards and mothers’/caretakers’ reports. Vaccination cards were seen by the interviewer for only 63 percent of children age 12-23 months. Overall, 64 percent of children age 12-23 months are fully immunized against vaccine preventable childhood diseases. The percentage of children fully vaccinated is higher for rural areas (71 percent) than for urban areas (59 percent). Children whose mothers had secondary or higher education had higher vaccination rates than those whose mothers had primary education. 96 83 96 95 78 97 94 88 92 85 88 84 81 94 86 84 56 2 BCG Polio at birth Polio1 Polio2 Polio3 DPT1 DPT2 DPT3 Measles HepB at birth HepB1 HepB2 HepB3 Hib1 Hib2 Hib3 Fully vaccinated No vaccinations Percent Children Age 12-23 months 90 80 89 87 64 89 84 80 79 82 82 79 48 88 87 80 30 4 BCG Polio at birth Polio1 Polio2 Polio3 DPT1 DPT2 DPT3 Measles HepB at birth HepB1 HepB2 HepB3 Hib1 Hib2 Hib3 Fully vaccinated No vaccinations Children Age 24-35 months Bungoma County MICS 2013/14 P a g e | 39 Table CH.2: Vaccinations by background characteristics Percentage of children age 12-23 months currently vaccinated against vaccine preventable childhood diseases, Bungoma County MICS, 2013/14 Percentage of children who received: Percentage with vaccination card seen Number of children age 12-23 months BCG Polio DPT HepB Hib Measles (MCV1) Fulla None At birth 1 2 3 1 2 3 At birth 1 2 3 1 2 3 Total 97.1 85.2 97.8 96.4 78.4 98.6 94.8 88.7 88.8 88.9 84.7 67.2 94.8 87.0 85.5 98.3 64.0 0.9 63.4 152 Sex Male 100.0 83.3 98.6 98.6 81.1 99.0 93.6 86.4 90.1 85.8 84.3 69.4 96.2 86.7 84.3 98.6 65.3 0.0 65.3 78 Female 94.0 87.3 96.8 94.0 75.5 98.1 96.1 91.1 87.3 92.3 85.1 64.7 93.2 87.4 86.8 98.0 62.6 1.9 61.4 74 Area Urban 98.3 78.4 97.3 95.6 78.9 98.3 91.7 82.8 87.3 85.0 80.9 60.1 92.3 80.5 79.7 98.3 58.5 1.7 58.5 86 Rural 95.4 94.2 98.4 97.4 77.8 98.9 98.9 96.4 90.8 94.4 90.0 77.1 98.1 96.0 93.5 98.4 71.4 0.0 69.8 66 Mother’s education None (*) (*) (*) (*) (*) (*) (*) (*) (*) (*) (*) (*) (*) (*) (*) (*) (*) (*) (*) 3 Primary 94.7 82.3 96.5 94.0 74.9 98.3 93.3 84.4 86.9 87.2 81.1 62.4 93.8 82.9 82.4 97.6 60.5 1.7 60.5 84 Secondary+ 100.0 88.2 99.3 99.3 83.0 100.0 97.8 95.0 91.1 90.9 89.2 73.3 96.4 92.4 90.7 99.3 69.3 0.0 69.3 64 a Includes: BCG, Polio3, DPT3, HepB3, Hib3, and Measles (MCV1) as per the vaccination schedule in Kenya (*) Figures that are based on fewer than 25 unweighted cases Bungoma County MICS 2013/14 P a g e | 40 5.2 Neonatal Tetanus Protection The goal of MDG 5 is to reduce by three quarters the maternal mortality ratio, with one strategy to eliminate maternal tetanus. Following on the 42nd and 44th World Health Assembly calls for elimination of neonatal tetanus, the global community continues to work to reduce the incidence of neonatal tetanus to less than one case per 1,000 live births in every district by 2015. The strategy for preventing maternal and neonatal tetanus is to ensure that all pregnant women receive at least two doses of tetanus toxoid vaccine. If a woman has not received at least two doses during a particular pregnancy, the mother and child are also considered to be protected against tetanus if the woman:  Received at least two doses of tetanus toxoid vaccine, the last within the previous 3 years;  Received at least 3 doses, the last within the previous 5 years;  Received at least 4 doses, the last within the previous 10 years;  Received 5 or more doses anytime during her life. To assess the status of tetanus vaccination coverage in Bungoma County, women who had a live birth during the two years before the survey were asked if they had received tetanus toxoid injections during the pregnancy for their most recent birth, and if so, how many. Women who did not receive two or more tetanus toxoid vaccinations during this recent pregnancy were then asked about tetanus toxoid vaccinations they may have previously received. Interviewers also asked women to present their vaccination card on which dates of tetanus toxoid are recorded and referred to information from the cards when available. Table CH.3 shows the protection status from tetanus of women age 15-49 years who have had a live birth within the last two years preceding the survey. In Bungoma County, 54 percent of these women were protected against neonatal tetanus. The proportion was higher in urban areas (64 percent) than in rural areas (46 percent), and higher for those with secondary or higher education (64 percent) compared to those with only primary education (47 percent). Bungoma County MICS 2013/14 P a g e | 41 Table CH.3: Neonatal tetanus protection Percentage of women age 15-49 years with a live birth in the last 2 years protected against neonatal tetanus, Bungoma County MICS, 2013/14 Percentage of women who received at least 2 doses during last pregnancy Percentage of women who did not receive two or more doses during last pregnancy but received: Protected against tetanus1 Number of women with a live birth in the last 2 years 2 doses, the last within prior 3 years 3 doses, the last within prior 5 years 4 doses, the last within prior 10 years 5 or more doses during lifetime Total 36.6 15.8 1.1 0.0 0.2 53.8 311 Area Urban 44.5 17.7 1.6 0.0 0.0 63.8 137 Rural 30.4 14.3 0.8 0.0 0.4 45.8 174 Education None (*) (*) (*) (*) (*) (*) 5 Primary 32.1 12.2 1.9 0.0 0.3 46.5 189 Secondary+ 43.8 22.3 0.0 0.0 0.0 66.1 116 Wealth index quintile Poorest 39.5 14.0 3.2 0.0 0.0 56.7 68 Second 30.9 14.9 0.0 0.0 0.0 45.8 65 Middle 39.8 22.5 0.8 0.0 1.2 64.3 55 Fourth 31.5 12.6 1.7 0.0 0.0 45.7 56 Richest 40.8 15.7 0.0 0.0 0.0 56.6 68 Ethnicity of household head Luhya 36.1 15.2 1.0 0.0 0.2 52.5 272 Other ethnic group 40.4 20.2 2.0 0.0 0.0 62.6 39 1 MICS indicator 3.9 - Neonatal tetanus protection (*) Figures that are based on fewer than 25 unweighted cases 5.3 Care of Illness A key strategy for accelerating progress toward MDG 4 is to tackle the diseases that are the leading causes of morbidity and mortality of children under-5 years. Diarrhoea and pneumonia are two such diseases. The Global Action Plan for the Prevention and Control of Pneumonia and Diarrhoea (GAPPD) aims to end preventable pneumonia and diarrhoea death by reducing mortality from pneumonia to three deaths per 1,000 live births and mortality from diarrhoea to one death per 1,000 live births by 2025. Malaria is also a major cause of mortality of children under-5 years, leading to about 1,200 deaths children every day, especially in sub-Saharan Africa.46 46UNICEF Fact sheet http://www.unicef.org/media/media_81674.html http://www.unicef.org/media/media_81674.html Bungoma County MICS 2013/14 P a g e | 42 Table CH.4 presents the percentage of children under-5 years of age who were reported to have had an episode of diarrhoea, symptoms of acute respiratory infection (ARI), or fever during the two weeks preceding the survey. These results measure period-prevalence of those illnesses over a two-week time window. The definition of a case of diarrhoea or fever, in this survey, was the mother’s or caretaker’s report that the child had such symptoms over the specified period; no other evidence was sought beside the opinion of the mother. A child was considered to have had an episode of ARI if the mother or caretaker reported that the child had, over the specified period, an illness with a cough with rapid or difficult breathing, and whose symptoms were perceived to be due to a problem in the chest or both a problem in the chest and a blocked nose. While this approach is reasonable in the context of a MICS, these basically simple case definitions must be kept in mind when interpreting the results, as well as the potential for reporting and recall biases. Further, diarrhoea, fever and ARI are not only seasonal but are also characterized by the often rapid spread of localized outbreaks from one area to another at different points in time. In Bungoma, 12 percent of children under five years of age were reported to have had diarrhoea in the two weeks preceding the survey, four percent symptoms of ARI, and 20 percent an episode of fever (Table CH.4). About 15 percent of children under-5 years in urban areas had experienced an episode of diarrhoea compared to 10 percent in rural areas. Reported episodes of fever were 24 percent in rural areas and 14 percent in urban areas. Bungoma County MICS 2013/14 P a g e | 43 Table CH.4: Reported disease episodes Percentage of children age 0-59 months for whom the mother/caretaker reported an episode of diarrhoea, symptoms of acute respiratory infection (ARI), and/or fever in the last two weeks, Bungoma County MICS, 2013/14 Percentage of children who in the last two weeks had: Number of children age 0-59 months An episode of diarrhoea Symptoms of ARI An episode of fever Total 11.9 3.8 19.8 846 Sex Male 13.2 4.1 20.2 414 Female 10.6 3.5 19.4 432 Area Urban 14.6 3.8 14.1 376 Rural 9.7 3.9 24.4 470 Age 0-11 months 16.7 3.9 25.3 167 12-23 months 20.9 3.6 20.0 152 24-35 months 13.9 4.5 16.7 160 36-47 months 6.7 4.0 19.0 215 48-59 months 2.7 3.1 18.2 152 Mother’s education None (3.5) (9.3) (12.0) 34 Primary 13.7 3.5 20.2 514 Secondary 9.7 3.8 20.2 298 Wealth index quintile Poorest 11.8 6.4 20.5 199 Second 15.0 3.2 22.0 184 Middle 8.7 2.0 14.6 162 Fourth 11.8 3.6 20.2 157 Richest 11.6 3.4 21.6 143 Ethnicity of household head Luhya 12.2 3.9 19.6 762 Other ethnic group 9.1 3.1 21.3 84 ( ) Figures that are based on 25-49 unweighted cases 5.3.1 Diarrhoea Diarrhoea is one of the leading causes of death among children under five worldwide47. Most diarrhoea- related deaths in children are due to dehydration from loss of large quantities of water and electrolytes from the body in liquid stools. Management of diarrhoea – either through oral rehydration salts (ORS) or a recommended home fluid (RHF) – can prevent many of these deaths. In addition, provision of zinc supplements has been shown to reduce the duration and severity of the illness as well as the risk of future 47WHO, 2013. Fact Sheet number 330. Bungoma County MICS 2013/14 P a g e | 44 episodes within the next two or three months. Preventing dehydration and malnutrition by increasing fluid intake and continuing to feed the child are also important strategies for managing diarrhoea. During the survey, mothers or caretakers were asked whether their child under five years had an episode of diarrhoea in the two weeks prior to the survey. In cases where mothers reported that the child had diarrhoea, a series of questions were asked about the treatment of the illness, including what the child had been given to drink and eat during the episode and whether this was more or less than what was usually given to the child. The overall period-prevalence of diarrhoea in children under-5 years of age is 12 percent (Table CH.4). The highest period-prevalence is seen among children age 12-23 months (21 percent). Table CH.5 shows the percentage of children with diarrhoea in the two weeks preceding the survey for whom advice or treatment was sought and where. Overall, a health facility or provider was seen in 46 percent of cases, predominantly in public health facilities (40 percent).48 Table CH.5: Care-seeking during diarrhoea Percentage of children age 0-59 months with diarrhoea in the last two weeks for whom advice or treatment was sought, by source of advice or treatment, Bungoma County MICS, 2013/14 Percentage of children with diarrhoea for whom: Number of children age 0- 59 months with diarrhoea in the last two weeks Advice or treatment was sought from: No advice or treatment sought Health facilities or providers Other source A health facility or provider1, b Public Private Community health providera Total 39.8 13.1 0.0 5.4 46.2 41.7 100 Area Urban 42.5 12.7 0.0 9.8 45.4 35.0 55 Rural (36.5) (13.6) (0.0) (0.0) (47.2) (49.8) 45 Mother’s education None (*) (*) (*) (*) (*) (*) 1 Primary 41.5 11.2 0.0 1.6 46.7 45.7 70 Secondary+ (37.3) (18.2) (0.0) (14.7) (46.8) (29.8) 29 Ethnicity of household head Luhya 43.1 11.3 0.0 5.8 48.5 39.9 93 Other ethnic group (*) (*) (*) (*) (*) (*) 8 1 MICS indicator 3.10 - Care-seeking for diarrhoea a Community health providers includes both public (Community health worker and Mobile/Outreach clinic) and private (Mobile clinic) health facilities b Includes all public and private health facilities and providers, but excludes private pharmacy ( ) Figures that are based on 25-49 unweighted cases (*) Figures that are based on fewer than 25 unweighted cases 48Most of the variables in Table CH.5 could not be analysed due to small number of cases reported. Bungoma County MICS 2013/14 P a g e | 45 Table CH.6 provides information on drinking and feeding practices during diarrhoea. Overall, about one in five of under five children who experienced an episode of diarrhoea in the last two weeks preceding the survey were given more than usual to drink while 44 percent were given about the same. About 25 percent were given somewhat less, but nine percent were given much less than usual. About four percent of children under five years of age who had an episode of diarrhoea in the last two weeks preceding the survey were given more to eat than usual while 45 percent were given about the same quantity of food. Twenty-eight percent were given somewhat less to eat and 16 percent were given much less during this period. Bungoma County MICS 2013/14 P a g e | 46 Table CH.6: Feeding practices during diarrhoea Percent distribution of children age 0-59 months with diarrhoea in the last two weeks by amount of liquids and food given during episode of diarrhoea, Bungoma County MICS, 2013/14 Drinking practices during diarrhoea Eating practices during diarrhoea Number of children age 0-59 months with diarrhoea in the last two weeks Child was given to drink: Total Child was given to eat: Total Much less Somewhat less About the same More Missing/DK Much less Somewhat less About the same More Nothing Total 9.1 24.7 43.7 19.5 3.0 100.0 15.9 28.2 45.3 3.7 6.9 100.0 100 Area Urban 9.9 30.7 41.7 17.7 0.0 100.0 17.0 31.9 44.1 0.0 7.0 100.0 55 Rural (8.2) (17.5) (46.0) (21.7) (6.6) 100.0 (14.6) (23.7) (46.8) (8.1) (6.7) 100.0 45 Mother’s education None (*) (*) (*) (*) (*) 100.0 (*) (*) (*) (*) (*) 100.0 1 Primary 12.2 17.8 46.0 19.8 4.3 100.0 15.1 27.9 46.9 5.3 4.9 100.0 70 Secondary+ (2.1) (42.6) (35.7) (19.6) (0.0) 100.0 (18.5) (26.1) (43.4) (0.0) (12.0) 100.0 29 Ethnicity of household head Luhya 7.6 24.6 44.5 20.0 3.2 100.0 15.4 28.3 45.7 3.5 7.0 100.0 93 Other ethnic group (*) (*) (*) (*) (*) 100.0 (*) (*) (*) (*) (*) 100.0 8 ( ) Figures that are based on 25-49 unweighted cases (*) Figures that are based on fewer than 25 unweighted cases Bungoma County MICS 2013/14 P a g e | 47 Table CH.7 shows the percentage of children age 0-59 months with diarrhoea in the last two weeks preceding the survey, who received oral rehydration salts (ORS), recommended homemade fluids, and zinc during an episode of diarrhoea. Since children may have been given more than one type of liquid, the percentages do not necessarily add to 100. About 40 percent received fluids from ORS packets or pre- packaged ORS fluids and 76 percent received recommended homemade fluids (cereal gruel – uji; fresh fruit juice; soups; fresh or fermented milk). Approximately 83 percent of children with diarrhoea received one or more of the recommended home treatments (i.e., were treated with ORS or any recommended homemade fluid), while 14 percent received zinc. In addition, 13 percent received ORS and zinc. Bungoma County MICS 2013/14 P a g e | 48 Table CH.7: Oral rehydration solutions, recommended homemade fluids, and zinc Percentage of children age 0-59 months with diarrhoea in the last two weeks, and treatment with oral rehydration salts (ORS), recommended homemade fluids, and zinc, Bungoma County MICS, 2013/14 Percentage of children with diarrhoea who received: Number of children age 0-59 months with diarrhoea in the last two weeks Oral rehydration salts (ORS) Recommended homemade fluids ORS or any recommended homemade fluid Zinc ORS and zinc1 Fluid from packet Pre- packaged fluid Any ORS Cereal Gruel(Uji) Fresh or Fermented Milk Fresh fruit juices Soups Any recommended homemade fluid Tablet Syrup Any zinc Total 34.7 15.5 40.3 46.6 20.1 13.9 49.6 75.5 82.5 12.7 2.3 14.4 13.1 100 Area Urban 36.0 14.4 39.9 61.1 20.6 16.2 46.2 84.1 91.4 15.9 1.8 17.7 17.7 55 Rural (33.1) (16.8) (40.7) (28.9) (19.5) (11.2) (53.8) (65.1) (71.7) (9.0) (2.8) (10.4) (7.6) 45 Ethnicity of household head Luhya 36.4 16.8 42.5 48.0 17.5 12.8 50.6 75.9 83.5 12.7 2.4 14.4 13.1 93 Other ethnic group (*) (*) (*) (*) (*) (*) (*) (*) (*) (*) (*) (*) (*) 8 1 MICS indicator 3.11 - Diarrhoea treatment with oral rehydration salts (ORS) and zinc ( ) Figures that are based on 25-49 unweighted cases (*) Figures that are based on fewer than 25 unweighted cases Bungoma County MICS 2013/14 P a g e | 49 Table CH.8 provides the proportion of children age 0-59 months with diarrhoea in the last two weeks preceding the survey who received oral rehydration therapy with continued feeding, and the percentage of children with diarrhoea who received other treatments. Overall, 49 percent of children with diarrhoea received ORS or increased fluids, 96 percent received ORT (ORS or recommended homemade fluids or increased fluids). Combining the information in Table CH.6 with that of Table CH.7 on oral rehydration therapy, it is observed that 75 percent of children received ORT and, at the same time, feeding was continued, as is recommended. Table CH.8 also shows the percentage of children having had diarrhoea in the two weeks preceding the survey who were given various forms of treatment, leaving 14 percent of them without any treatment or drug. Table CH.9 provides information on the source of ORS and zinc for children who benefitted from these treatments.49 49 Detailed description of table was not done due to the limited number of cases reported. Bungoma County MICS 2013/14 P a g e | 50 Table CH.8: Oral rehydration therapy with continued feeding and other treatments Percentage of children age 0-59 months with diarrhoea in the last two weeks who were given oral rehydration therapy with continued feeding and percentage who were given other treatments, Bungoma Count MICS, 2013/14 Children with diarrhoea who were given: Not given any treatment or drug Number of children age 0-59 months with diarrhoea in the last two weeks Zinc ORS or increased fluids ORT (ORS or recommended homemade fluids or increased fluids) ORT with continued feeding1 Other treatments Pill or syrup Injection Intra- venous Home remedy, herbal medicine Other Anti- biotic Anti- motility Other Unknown Anti- biotic Non- antibiotic Unknown Total 14.4 49.4 83.1 67.6 8.6 2.8 .9 2.6 3.3 0.0 0.0 1.1 2.1 9.6 14.2 100 Area Urban 17.7 48.0 92.5 69.3 10.6 5.1 1.6 3.9 1.1 0.0 0.0 1.9 3.0 7.0 6.1 55 Rural (10.4) (51.0) (71.7) (65.6) (6.1) (0.0) (0.0) (0.9) (5.9) (0.0) (0.0) (0.0) (1.0) (12.7) (24.1) 45 Ethnicity of household head Luhya 14.4 52.4 84.2 69.1 7.4 3.0 1.0 1.2 3.5 0.0 0.0 1.1 2.3 9.4 13.8 93 Other ethnic group (*) (*) (*) (*) (*) (*) (*) (*) (*) (*) (*) (*) (*) (*) (*) 8 1 MICS indicator 3.12 - Diarrhoea treatment with oral rehydration therapy (ORT) and continued feeding ( ) Figures that are based on 25-49 unweighted cases (*) Figures that are based on fewer than 25 unweighted cases Bungoma County MICS 2013/14 P a g e | 51 Table CH.9: Source of ORS and zinc Percentage of children age 0-59 months with diarrhoea in the last two weeks who were given ORS, and percentage given zinc, by the source of ORS and zinc, Bungoma County MICS, 2013/14 Percentage of children who were given as treatment for diarrhoea: Number of children age 0-59 months with diarrhoea in the last two weeks Percentage of children for whom the source of ORS was: Number of children age 0- 59 months who were given ORS as treatment for diarrhoea in the last two weeks Percentage of children for whom the source of zinc was: Number of children age 0-59 months who were given zinc as treatment for diarrhoea in the last two weeks Health facilities or providers A health facility or providerb Health facilities or providers A health facility or providerb ORS zinc Public Private Public Private Total 40.3 14.4 100 (88.2) (11.8) 100.0 40 (*) (*) 100.0 14 a Community health provider includes both public (Community health worker and Mobile/Outreach clinic) and private (Mobile clinic) health facilities50 b Includes all public and private health facilities and providers ( ) Figures that are based on 25-49 unweighted cases (*) Figures that are based on fewer than 25 unweighted cases 50Category for community health provider was removed due to small number of cases recorded Bungoma County MICS 2013/14 P a g e | 52 5.3.2 Acute Respiratory Infections (ARI) Symptoms of ARI were collected during the Bungoma County MICS to capture pneumonia disease, which is a leading cause of death in children under-5 years. Once diagnosed, pneumonia is treated effectively with antibiotics. Studies have shown a limitation in the survey approach of measuring pneumonia because many of the suspected cases identified through surveys are in fact, not true pneumonia.51 While this limitation does not affect the level and patterns of care-seeking for suspected pneumonia, it limits the validity of the level of treatment of pneumonia with antibiotics, as reported through household surveys. Mothers’ knowledge of danger signs is an important determinant of care-seeking behaviour. In the MICS, mothers or caretakers were asked to report symptoms that would cause them to take a child under-five years for care immediately at a health facility. Issues related to knowledge of danger signs of pneumonia are presented in Table CH.10. Overall, 46 percent of women know at least one of the two danger signs of pneumonia – fast and/or difficult breathing. The most commonly identified symptom for taking a child to a health facility is when the child develops a fever (90 percent): fast breathing (29 percent), and difficult breathing (33 percent). In urban areas, 51 percent of the mothers or caretakers of children under five years of age recognize at least one of the two danger signs of pneumonia. In rural areas, the percentage is 42. A higher percentage of mothers and caretakers (90 percent or more) indicated that they would take a child immediately to a health facility if the child developed a fever compared to the other symptoms. This was the case irrespective of area of residence and education level of the respondent. 51Campbell, H. et al. 2013.Measuring Coverage in MNCH: Challenges in Monitoring the Proportion of Young Children with Pneumonia Who Receive Antibiotic Treatment. PLoS Med 10(5): e1001421. doi:10.1371/journal.pmed.1001421 Bungoma County MICS 2013/14 P a g e | 53 Table CH.10: Knowledge of the two danger signs of pneumonia Percentage of women age 15-49 years who are mothers or caretakers of children under age 5 by symptoms that would cause them to take a child under age 5 immediately to a health facility, and percentage of mothers who recognize fast or difficult breathing as signs for seeking care immediately, Bungoma County MICS, 2013/14 Percentage of mothers/caretakers of children age 0-59 months who think that a child should be taken immediately to a health facility if the child: Mothers/caretakers who recognize at least one of the two danger signs of pneumonia (fast and/or difficult breathing) Number of women age 15-49 years who are mothers/caretakers of children under age 5 Is not able to drink or breastfeed Becomes sicker Develops a fever Has fast breathing Has difficult breathing Has blood in stool Is drinking poorly Has other symptoms Total 34.8 33.6 90.4 29.2 33.2 24.7 24.0 44.1 46.2 569 Area Urban 37.7 36.6 89.8 32.8 40.1 32.9 22.7 39.0 50.8 253 Rural 32.5 31.1 90.8 26.3 27.8 18.1 25.0 48.2 42.4 315 Education None (*) (*) (*) (*) (*) (*) (*) (*) (*) 11 Primary 32.4 34.4 89.8 31.9 32.8 25.2 24.3 42.3 47.7 340 Secondary+ 39.3 32.0 91.5 25.2 35.1 25.0 24.5 48.6 44.5 218 Wealth index quintile Poorest 31.5 31.3 92.1 30.7 29.8 23.5 25.5 48.3 45.5 114 Second 39.3 35.3 88.9 35.5 34.0 21.9 26.8 42.7 52.2 122 Middle 33.9 29.6 90.2 20.5 33.0 21.8 23.9 46.6 38.0 108 Fourth 34.5 37.1 90.5 35.7 31.2 23.8 21.6 38.7 49.7 107 Richest 34.4 34.5 90.2 23.3 37.9 32.3 21.8 44.0 44.9 117 Ethnicity of household head Luhya 34.4 33.0 90.3 29.1 32.5 24.5 23.4 44.1 46.1 506 Other ethnic group 38.1 37.8 90.8 29.9 39.6 26.1 28.5 44.1 47.1 63 ( ) Figures that are based on 25-49 unweighted cases (*) Figures that are based on fewer than 25 unweighted cases 5.3.3 Solid Fuel Use More than 3 billion people around the world rely on solid fuels for their basic energy needs, including cooking and heating. Solid fuels include biomass fuels, such as wood, charcoal, crops or other agricultural waste, dung, shrubs and straw, and coal. Cooking and heating with solid fuels leads to high levels of indoor smoke which contains a complex mix of health-damaging pollutants. The main problem with the use of solid fuels is their incomplete combustion, which produces toxic elements such as carbon monoxide, polyaromatic hydrocarbons, and sulphur dioxide (SO2), among others. Use of solid fuels increases the risks of incurring acute respiratory illness, pneumonia, chronic obstructive lung disease, cancer, and possibly tuberculosis, asthma, or cataracts, and may contribute to low birth weight of babies born to pregnant women exposed to smoke. The primary indicator for monitoring use of solid fuels is the proportion of the population using solid fuels as the primary source of domestic energy for cooking, shown in Table CH.11. Overall, the majority (96 percent) of the household population in Bungoma County uses solid fuels for cooking, consisting mainly of wood (77 percent). Use of solid fuels in urban areas (95 percent) is equally Bungoma County MICS 2013/14 P a g e | 54 high as in rural areas (97 percent). Likewise, no major differentials are noted when assessing use of solid fuels by the educational level of the household head (none, 99 percent; primary education, 98 percent; secondary or higher, 94 percent). With respect to household wealth, the use of solid fuels decreases from 100 percent for poorest households to 87 percent for those in the richest households. Bungoma County MICS 2013/14 P a g e | 55 Table CH.11: Solid fuel use Percent distribution of household members according to type of cooking fuel mainly used by the household, and percentage of household members living in households using solid fuels for cooking, Bungoma County MICS, 2013/14 Percentage of household members in households mainly using: Number of household members Electricity Liquefied Petroleum Gas (LPG) Natural Gas Biogas Kerosene Solid fuels Other fuel No food cooked in the household Total Solid fuels for cooking1 Coal/ Lignite Char- coal Wood Straw/ Shrubs/ Grass Agricultural crop residue Total 0.1 1.3 0.3 0.4 1.6 0.2 18.0 76.9 0.9 0.1 0.0 0.2 100.0 96.1 5,983 Area Urban 0.2 2.2 0.3 0.7 1.1 0.1 25.0 69.3 0.5 0.1 0.0 0.5 100.0 94.9 2,697 Rural 0.0 0.6 0.2 0.1 2.0 0.3 12.3 83.1 1.3 0.0 0.1 0.1 100.0 97.1 3,286 Education of household head None 0.0 0.1 0.0 0.0 0.7 0.0 14.4 83.8 0.5 0.0 0.0 0.5 100.0 98.7 466 Primary 0.0 0.1 0.1 0.0 1.7 0.4 12.7 83.5 1.0 0.1 0.1 0.2 100.0 97.7 2,815 Secondary+ 0.2 2.7 0.4 0.8 1.7 0.1 24.5 68.4 0.9 0.0 0.0 0.2 100.0 93.9 2,649 Missing/DK 0.0 0.0 0.0 0.0 0.0 0.0 15.0 85.0 0.0 0.0 0.0 0.0 100.0 100.0 53 Wealth index quintile Poorest 0.0 0.0 0.0 0.0 0.1 0.0 .2 98.3 1.4 0.0 0.0 0.0 100.0 99.8 1,196 Second 0.0 0.0 0.0 0.0 0.1 0.0 5.4 93.6 0.4 0.3 0.0 0.1 100.0 99.7 1,199 Middle 0.0 0.1 0.0 0.0 0.4 0.0 9.2 89.6 0.5 0.0 0.0 0.2 100.0 99.3 1,192 Fourth 0.0 0.0 0.0 0.0 4.7 0.9 22.0 69.6 2.1 0.0 0.2 0.5 100.0 94.6 1,199 Richest 0.5 6.3 1.3 1.9 2.6 0.2 53.4 33.3 0.2 0.0 0.0 0.4 100.0 87.0 1,198 Ethnicity of household head Luhya 0.1 0.8 0.3 0.3 1.5 0.2 15.8 79.8 1.0 0.0 0.0 0.2 100.0 96.8 5,394 Other ethnic group 0.2 6.1 0.1 0.6 2.9 0.1 38.9 49.7 0.0 0.6 0.0 0.8 100.0 89.3 587 1 MICS indicator 3.15 - Use of solid fuels for cooking Bungoma County MICS 2013/14 P a g e | 56 Solid fuel use by place of cooking is depicted in Table CH.12. The presence and extent of indoor pollution are dependent on cooking practices, places used for cooking, as well as types of fuel used. According to the Bungoma County MICS, 30 percent of the population living in households using solid fuels for cooking, cook food in a separate room that is used as a kitchen. The percentage that had food cooked in a separate room used as a kitchen within the dwelling unit is higher in urban (34 percent) than in rural areas (26 percent). Table CH.12: Solid fuel use by place of cooking Percent distribution of household members in households using solid fuels by place of cooking, Bungoma County MICS, 2013/14 Place of cooking: Number of household members in households using solid fuels for cooking In the house In a separate building Outdoors Total In a separate room used as kitchen Elsewhere in the house Total 29.9 16.5 49.8 3.8 100.0 5,750 Area Urban 34.2 22.1 38.5 5.3 100.0 2,561 Rural 26.4 12.0 58.9 2.6 100.0 3,189 Education of household head None 29.7 20.0 49.0 1.3 100.0 460 Primary 29.4 18.7 47.3 4.6 100.0 2,751 Secondary+ 30.7 13.6 52.2 3.5 100.0 2,486 Wealth index quintile Poorest 24.4 22.2 46.8 6.6 100.0 1,194 Second 28.8 12.8 56.0 2.4 100.0 1,196 Middle 23.0 15.0 57.5 4.5 100.0 1,183 Fourth 35.2 14.7 47.8 2.3 100.0 1,134 Richest 39.3 17.8 39.8 3.1 100.0 1,043 Ethnicity of household head Luhya 29.7 14.9 51.5 3.9 100.0 5,224 Other ethnic group 31.8 32.2 33.0 2.9 100.0 524 5.3.4 Malaria/Fever Malaria is a major cause of death of children under five years worldwide. In Kenya, malaria accounts for about 31 percent of outpatient consultations and five percent of hospital admissions.52The results of the Kenya Malaria Indicator Survey 2010 showed that children aged 5–14 years had the highest prevalence of malaria (13 percent). The prevalence in children below five years increased from four percent in 2007 to eight percent in 2010. Malaria prevalence was also nearly three times as high in rural areas (12 percent) 52 President’s Malaria Initiative – Kenya Malaria Operational Plan FY 2014 Bungoma County MICS 2013/14 P a g e | 57 as in urban areas (5 percent).53 Malaria transmission and infection risk in Kenya is determined largely by altitude, rainfall patterns and temperature. Preventive measures and treatment with an effective antimalarial can dramatically reduce malaria mortality rates among children. In areas where malaria is common, WHO recommends indoor residual spraying (IRS), use of insecticide treated bednets (ITNs) and prompt treatment of cases with recommended anti-malarial drugs. In 2010 the WHO issued a recommendation for universal use of diagnostic testing to confirm malaria infection and apply appropriate treatment based on the results. According to the guidelines, treatment solely on the basis of clinical suspicion should only be considered when a parasitological diagnosis is not accessible. This recommendation was based on studies that showed substantial reduction in the proportion of fever that are associated with malaria to a low level.54 This recommendation implies that the indicator on proportion of children with fever that received antimalarial treatment is no longer an acceptable indicator of the level of treatment of malaria in the population of children under age five. However, as it remains the MDG indicator and for purposes of comparisons, as well as assessment of patterns across socio-demographic characteristics, the indicator remains a standard MICS indicator. Children with severe malaria symptoms, such as fever and convulsions, should be taken to a health facility. Further, children recovering from malaria should be given extra liquids and food, and younger children should continue breastfeeding. In Kenya, the Division of Malaria Control (DOMC) and Presidents Malaria Initiative (PMI), have put in place the following interventions for malaria control and case management: indoor residual spraying (IRS); distribution of insecticide-treated nets; intermittent preventive treatment of pregnant women (IPTp): provision of prompt diagnosis and effective treatment at all levels of the health care system; advocacy, communication and social mobilisation through Behaviour Change Communication (BCC); monitoring and evaluation; and health systems strengthening and integration. The Malaria Control Programme is guided by the National Malaria Communication Strategy 2010 – 2013; Kenya National Malaria Strategy 2009 – 2017: Towards a Malaria-free Kenya; and the National Guidelines for the Diagnosis, Treatment and Prevention of Malaria in Kenya 2010. Insecticide-treated mosquito nets, or ITNs, if used properly, are very effective in offering protection against mosquitos and other insects. The use of ITNs is one of the main health interventions implemented to reduce malaria transmission in Kenya. The questionnaire incorporated questions on the availability and use of bed nets, both at household level and among children under five years of age and pregnant women. In addition, all households in Bungoma County were asked whether the interior dwelling walls were sprayed with an insecticide to kill or repel mosquitoes that spread malaria during the 12 months preceding the survey. 53Division of Malaria Control [Ministry of Public Health and Sanitation], Kenya National Bureau of Statistics, and ICF Macro. 2011. 2010 Kenya Malaria Indicator Survey. Nairobi, Kenya: DOMC, KNBS and ICF Macro. 54D'Acremont, V et al. 2010. Reduction in the proportion of fevers associated with Plasmodium falciparum parasitaemia in Africa: a systematic review. Malaria Journal 9(240). http://en.wikipedia.org/wiki/Mosquito http://en.wikipedia.org/wiki/Insect Bungoma County MICS 2013/14 P a g e | 58 In Bungoma County, the survey results indicate that 78 percent of households had at least one insecticide treated net (Table CH.13), and 45 percent had at least one ITN for every two household members. Further, one percent of households received indoor residual spraying during the last 12 months, and 78 percent had at least one ITN for every two household members and/or received IRS during the last 12 months. Bungoma County MICS 2013/14 P a g e | 59 Table CH.13: Household availability of insecticide treated nets and protection by a vector control method Percentage of households with at least one mosquito net, one insecticide treated net (ITN), and one long-lasting treated net, percentage of households with at least one mosquito net, one insecticide treated net (ITN) per two people, and one long-lasting treated net, percentage of households with at least one ITN and/or indoor residual spraying (IRS) in the last 12 months, and percentage of households with at least one ITN per two people and/or with indoor residual spraying (IRS) in the last 12 months, Bungoma County MICS, 2013/14 Percentage of households with at least one mosquito net: Percentage of households with at least one net for every two personsa: Percentage of households with IRS in the past 12 months Percentage of households with at least one ITN and/or IRS during the last 12 months3 Percentage of households with at least one ITN for every 2 persons and/or received IRS during the last 12 months4 Number of households Any mosquito net Insecticide treated mosquito net (ITN)1 Long-lasting insecticidal treated net (LLIN) Any mosquito net Insecticide treated mosquito net (ITN)2 Long-lasting insecticidal treated net (LLIN) Total 82.8 78.0 76.3 47.7 44.5 43.6 1.4 78.4 45.4 1,246 Area Urban 83.0 76.4 74.6 50.9 47.1 46.3 1.6 77.0 47.9 614 Rural 82.6 79.6 78.0 44.5 41.9 41.1 1.3 79.7 42.9 632 Education of household head None 70.7 67.1 61.8 47.2 44.9 42.5 0.4 67.1 44.9 123 Primary 79.4 73.5 71.9 37.7 33.2 32.2 1.8 74.1 34.7 565 Secondary+ 89.0 85.0 84.1 58.3 56.1 55.8 1.3 85.3 56.7 553 Wealth index quintile Poorest 73.6 69.3 68.6 30.0 28.7 28.2 0.8 69.9 29.6 246 Second 76.0 71.8 70.7 38.2 34.4 33.8 0.9 71.8 35.3 226 Middle 83.1 76.7 74.0 42.4 37.7 37.0 1.7 76.9 39.2 233 Fourth 86.0 81.4 79.1 52.2 49.2 47.7 2.2 82.4 50.6 256 Richest 93.1 88.4 86.9 70.6 67.3 66.5 1.4 88.5 67.5 285 Ethnicity of household head Luhya 82.9 77.9 76.2 46.4 42.9 42.1 1.1 78.2 43.6 1,091 Other ethnic group 82.3 78.5 77.3 57.0 55.4 54.7 3.9 80.3 58.4 154 1 MICS indicator 3.16a - Household availability of insecticide-treated nets (ITNs) - One+ 2 MICS indicator 3.16b - Household availability of insecticide-treated nets (ITNs) - One+ per 2 people 3 MICS indicator 3.17a - Households covered by vector control - One+ ITNs Bungoma County MICS 2013/14 P a g e | 60 4 MICS indicator 3.17b - Households covered by vector control - One+ ITNs per 2 people a The numerators are based on number of usual (de jure) household members and does not take into account whether household members stayed in the household last night. MICS does not collect information on visitors to the household Bungoma County MICS 2013/14 P a g e | 61 Tables CH.14 and CH.15 provide further insight on access to ITNs. Overall, 21 percent of individuals are estimated to have access to ITNs, i.e. they could sleep under an ITN if each ITN in the household was used by two people. Access is slightly higher in urban (23 percent) than in rural (20 percent) areas. Access to an ITN ranges from nine percent in the poorest households to 42 percent in the richest households. Table CH.14: Access to an insecticide treated net (ITN) - number of household members Percentage of household population with access to an ITN in the household, Bungoma County MICS, 2013/14 Number of ITNs owned by household: Total Percentage with access to an ITNa Number of household membersb 0 1 2 3 4 5 6 7 8 or more Total 22.0 22.3 25.3 22.6 5.1 1.3 1.2 0.1 0.2 100.0 21.1 5,983 Number of household members 1 33.2 60.2 4.6 1.0 0.5 0.0 0.5 0.0 0.0 100.0 66.8 145 2 16.6 35.2 39.9 8.2 0.0 0.0 0.0 0.0 0.0 100.0 48.2 229 3 29.7 29.9 18.7 18.4 3.4 0.0 0.0 0.0 0.0 100.0 40.5 495 4 22.0 16.4 37.4 19.3 4.9 0.0 0.0 0.0 0.0 100.0 24.3 731 5 18.2 12.8 31.8 29.8 6.1 1.1 0.2 0.0 0.0 100.0 37.2 901 6 16.1 8.7 29.9 35.3 5.7 2.1 2.2 0.0 0.0 100.0 9.9 910 7 18.1 14.0 24.0 30.4 10.0 0.0 3.5 0.0 0.0 100.0 13.5 850 8 or more 21.0 9.4 17.3 32.5 8.6 6.3 3.2 0.3 1.4 100.0 8.0 1,723 a Percentage of household population who could sleep under an ITN if each ITN in the household were used by up to two people b The denominator is number of usual (de jure) household members and does not take into account whether household members stayed in the household last night. MICS does not collect information on visitors to the household Bungoma County MICS 2013/14 P a g e | 62 Table CH.15: Access to an insecticide treated net (ITN) - background characteristics Percentage of household population with access to an ITN in the household, Bungoma County MICS, 2013/14 Percentage with access to an ITNa Number of household membersb Total 21.1 5,983 Area Urban 22.9 2,697 Rural 19.6 3,286 Wealth index quintile Poorest 8.7 1,196 Second 14.3 1,199 Middle 17.0 1,192 Fourth 23.8 1,199 Richest 41.8 1,198 Ethnicity of household head Luhya 20.3 5,394 Other ethnic group 29.1 587 a Percentage of household population who could sleep under an ITN if each ITN in the household were used by up to two people b The denominator is number of usual (de jure) household members and does not take into account whether household members stayed in the household last night. MICS does not collect information on visitors to the household Overall, 82 percent of ITNs were used during the night preceding the survey (Table CH.16). The percentage of ITNs used by anyone the night preceding the survey is slightly higher in rural areas (84 percent) than in urban areas (79 percent). Bungoma County MICS 2013/14 P a g e | 63 Table CH.16: Use of ITNs Percentage of insecticide treated nets (ITNs) that were used by anyone last night, Bungoma County MICS, 2013/14 Percentage of ITNs used last night Number of ITNs Total 81.8 2,207 Area Urban 79.2 1,046 Rural 84.2 1,161 Wealth index quintile Poorest 78.7 320 Second 81.8 340 Middle 84.5 411 Fourth 81.4 514 Richest 82.1 622 Ethnicity of household head Luhya 82.0 1,950 Other ethnic group 80.3 257 As for children under the age of five years, who constitute an important vulnerable group, 63 percent slept under an ITN the night preceding the survey (Table CH.17). This figure increased to 77 percent considering only children living in a household with at least one ITN. Disparities by sex in ITN use among children under five years are noted. The percentage of boys who slept under an ITN the night before the survey was higher than the percentage of girls (67 compared to 59 percent). Similarly, in households with at least one ITN, a higher proportion of boys (82 percent) slept under an ITN, compare to girls (73 percent). Some differences are also apparent in regard to the education level of the mother, and household wealth, with the proportion of children sleeping under an ITN being higher among children of mothers with secondary or higher education (74 percent) compared to children of mothers with primary education (58 percent), and among children in the richer households. A higher proportion of children age 0-11 months (74 percent) slept under an ITN the night before the survey, with lower proportions for children 12 months and older. Table CH.17: Children sleeping under mosquito nets Percentage of children age 0-59 months who slept under a mosquito net last night, by type of net, Bungoma County MICS, 2013/14 Percentage of children age 0-59 who spent last night in the interviewed households Number of children age 0-59 months Percentage of children under age five who the previous night slept under: Number of children age 0- 59 months who spent last night in the interviewed households Percentage of children 0-59 months who slept under an ITN last night in households with at least one ITN Number of children age 0-59 living in household s with at least one ITN Any mosquito net An insecticide treated net (ITN)1 A Long- lasting insecticida l treated net (LLIN) An ITN or in a dwelling sprayed with IRS in the past 12 months Total 98.9 846 68.1 62.9 61.6 63.3 837 77.3 681 Bungoma County MICS 2013/14 P a g e | 64 Sex Male 99.1 414 71.3 66.8 65.2 67.1 410 81.6 335 Female 98.7 432 64.9 59.3 58.1 59.6 427 73.2 346 Area Urban 98.8 376 68.0 61.1 59.4 61.4 372 77.2 294 Rural 98.9 470 68.2 64.4 63.4 64.7 465 77.4 387 Age 0-11 months 99.6 167 76.7 73.7 71.5 74.0 167 84.9 145 12-23 months 98.2 152 65.9 60.8 59.8 61.1 149 78.2 116 24-35 months 100.0 160 71.0 66.4 66.4 67.0 160 81.2 131 36-47 months 99.0 215 63.3 54.2 52.1 54.7 213 68.8 168 48-59 months 97.3 152 64.2 61.7 60.7 61.7 148 75.2 122 Mother's education None (100.0) 34 (*) (*) (*) (*) (*) (*) 20 Primary 98.8 514 64.7 58.3 57.3 58.5 508 72.8 406 Secondary+ 99.0 298 76.6 73.5 72.7 73.9 295 85.0 255 Wealth index quintile Poorest 99.8 199 56.2 51.7 51.7 52.4 199 72.1 143 Second 99.7 184 62.9 58.6 58.1 58.8 184 75.5 143 Middle 99.1 162 66.5 59.2 56.1 59.2 161 69.9 136 Fourth 96.0 157 80.6 77.7 75.5 78.3 151 87.7 133 Richest 99.5 143 79.8 72.9 71.5 72.9 143 82.5 126 Ethnicity of household head Luhya 98.8 762 68.5 63.0 61.6 63.1 753 77.2 614 Other ethnic group 99.5 84 64.0 63.1 61.6 65.1 83 78.9 67 1 MICS indicator 3.18; MDG indicator 6.7 - Children under age 5 sleeping under insecticide-treated nets (ITNs) ( ) Figures that are based on 25-49 unweighted cases (*) Figures that are based on fewer than 25 unweighted cases Table CH.18 gives further insight into the use of mosquito nets by household members of any age, 57 percent of whom slept under an ITN the night prior to the survey. This figure rises to 71 percent considering only household members living in a household with at least one ITN. Overall, 58 percent of household members slept under an ITN the previous night or in a dwelling which had IRS in the past 12 months. The percentage of household members who slept under an ITN the night prior to the survey is 44 percent in households where the household head had no education, 52 percent for those with primary education, the rate is 65 percent for those with secondary or higher education. Variations are noted by household wealth from 46 percent in poorest households, 56 percent for households in the middle wealth quintile, and 70 percent for those in the richest wealth quintile. Bungoma County MICS 2013/14 P a g e | 65 Table CH.18: Use of mosquito nets by the household population Percentage of household members who slept under a mosquito net last night, by type of net, Bungoma County MICS, 2013/14 Percentage of household members who the previous night slept under: Number of household members who spent the previous night in the interviewed households Percentage of household members who slept under an ITN last night in households with at least one ITN Number of household members in households with at least one ITN Any mosquito net An insecticide treated net (ITN)1 A Long- lasting insecticidal treated net (LLIN) An ITN or in a dwelling sprayed with IRS in the past 12 months Total 60.8 57.0 55.4 57.6 5,742 71.2 4,594 Sex Male 58.3 54.7 53.1 55.5 2,689 68.4 2,151 Female 63.1 59.0 57.4 59.5 3,053 73.7 2,443 Area Urban 62.2 56.5 54.6 57.2 2,610 72.6 2,031 Rural 59.7 57.4 56.0 57.9 3,132 70.1 2,563 Age 0-4a 68.6 63.4 62.1 63.8 879 77.8 718 5-14 52.7 49.5 47.9 50.2 1,907 62.6 1,508 15-34 56.6 53.3 51.9 53.9 1,678 66.0 1,356 35-49 74.2 69.6 67.6 70.4 682 84.9 559 50+ 72.2 67.1 65.0 67.7 595 88.1 453 Education of household head None 46.0 43.5 37.9 43.5 453 63.8 309 Primary 56.6 51.9 50.4 52.8 2,722 67.9 2,080 Secondary+ 68.3 65.0 64.0 65.4 2,519 75.7 2,162 Missing/DK 51.1 51.1 51.1 51.1 48 (56.7) 44 Wealth index quintile Poorest 48.4 45.5 45.4 46.7 1,151 63.5 825 Second 52.2 48.5 47.7 48.8 1,156 66.4 844 Middle 60.6 56.1 53.7 56.7 1,160 68.8 946 Fourth 68.4 64.8 62.4 65.6 1,156 75.6 990 Richest 75.0 70.4 68.1 70.6 1,118 79.6 989 Ethnicity of household head Luhya 60.6 56.6 54.9 56.9 5,167 70.5 4,147 Other ethnic group 62.7 61.0 59.8 64.1 572 78.2 447 1 MICS indicator 3.19 - Population that slept under an ITN a The results of the age group 0-4 years do not match those in Table CH.18, which is based on completed under-5 interviews only. The two tables are computed with different sample weights Table CH.19 provides information on care-seeking behaviour during an episode of fever in the last two weeks preceding the survey. As shown in Table CH.19, advice was sought from a health facility or a qualified health care provider for 54 percent of children with fever; these services were provided mainly by the public health facility (36 percent). However, no advice or treatment was sought in 33 percent of the cases. Differences are noted by urban and rural areas, 64 percent and 49 percent, respectively. Bungoma County MICS 2013/14 P a g e | 66 Table CH.19: Care-seeking during fever Percentage of children age 0-59 months with fever in the last two weeks for whom advice or treatment was sought, by source of advice or treatment, Bungoma County MICS, 2013/14 Percentage of children for whom: Number of children with fever in last two weeks Advice or treatment was sought from: No advice or treatment sought Health facilities or providers Other source A health facility or provider1, b Public Private Community health providera Total 35.5 16.5 0.4 16.8 53.8 33.0 168 Sex Male 39.6 16.8 0.7 9.7 52.7 33.9 84 Female 31.4 16.3 0.0 23.8 54.9 32.1 84 Area Urban 49.5 15.4 1.1 7.3 63.6 27.8 53 Rural 29.0 17.0 0.0 21.1 49.3 35.5 115 1 MICS indicator 3.20 - Care-seeking for fever a Community health providers include both public (Community health worker and Mobile/Outreach clinic) and private (Mobile clinic) health facilities b Includes all public and private health facilities and providers as well as shops Mothers were asked to report all of the medicines given to a child to treat the fever, including both medicines given at home and medicines given or prescribed at a health facility. Artemisinin-based Combination therapy (ACT) is the first line antimalarial recommended by the WHO and used in the country. In addition, confirmation of malaria is done on all fever cases through a malaria test. Table CH.20 presents the results of children age 0-59 months who had a fever in the last two weeks preceding the survey, by type of medicine given for the illness. Twenty-three percent of children with fever during this period were treated with an artemisinin-based combination therapy (ACT). Bungoma County MICS 2013/14 P a g e | 67 Table CH.20: Treatment of children with fever Percentage of children age 0-59 months who had a fever in the last two weeks, by type of medicine given for the illness, Bungoma County MICS, 2013/14 Children with a fever in the last two weeks who were given: Number of children with fever in last two weeks Anti-malarials Other medications Other Missing/DK SP/ Fansidar Chloroquine Amodia- quine Quinine Artemisinin- based Combination Therapy (ACT) Other anti- malarial Antibiotic pill or syrup Antibiotic injection Paracetamol/ Panadol/ Acetaminophen Aspirin Ibuprofen Total 5.2 0.5 1.0 3.9 23.1 14.5 48.2 0.4 60.0 1.9 4.6 15.9 0.8 168 Sex Male 2.6 0.0 0.7 5.8 15.2 16.4 52.6 0.0 58.9 2.0 4.4 24.9 1.6 84 Female 7.7 1.0 1.3 1.9 30.9 12.6 43.9 0.9 61.2 1.8 4.8 6.9 0.0 84 Area Urban 2.8 0.8 1.1 1.7 17.1 10.7 57.6 0.0 60.2 3.1 7.5 26.2 0.0 53 Rural 6.3 0.4 1.0 4.9 25.8 16.2 43.9 0.7 60.0 1.3 3.3 11.1 1.2 115 Bungoma County MICS 2013/14 P a g e | 68 Overall, 29 percent of children with a fever in the previous two weeks preceding the survey had blood taken from a finger or heel for testing (Table CH.21). Forty-six percent of children who had fever in the two weeks preceding the survey were treated with any antimalarial drug. Of these, half of them were treated with ACT. Table CH.21: Diagnostics and anti-malarial treatment of children Percentage of children age 0-59 months who had a fever in the last two weeks who had a finger or heel stick for malaria testing, who were given Artemisinin-combination Treatment (ACT) and any anti-malarial drugs, and percentage who were given A

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