Kenya - Multiple Indicator Cluster Survey - 2011

Publication date: 2011

Kenya, Nyanza Province Monitoring the situation of children and women Multiple Indicator Cluster Survey 2011 Kenya National Bureau of Statistics United Nations Children’s Fund Kenya, Nyanza Province Multiple Indicator Cluster Survey 2011 July, 2013 N N NyamiraHoma Bay Kisumu Siaya Kisii Migori The Nyanza province Multiple Indicator Cluster Survey (MICS) was carried out in 2011 by Kenya National Bureau of Statistics in collaboration with County and Provincial administration. The survey covered all the 6 constituent counties of Nyanza, namely: Siaya, Kisumu, Homa Bay, Migori, Kisii, and Nyamira. Financial and technical support was provided by the United Nations Children’s Fund (UNICEF). MICS is an international household survey programme developed by UNICEF. The Nyanza province MICS was conducted as part of the fourth global round of MICS surveys (MICS4). 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. Additional information on the global MICS project may be obtained from www. childinfo.org. In Kenya, this information is important to guide the planning and implementation of new development plans targeting the new administrative County -levels of governance. Suggested citation: Kenya National Bureau of Statistics. 2013. Nyanza Province Multiple Indicator Cluster Survey 2011, Final Report. Nairobi, Kenya: Kenya National Bureau of Statistics. Nyanza Province Multiple Indicator Cluster Survey 2011 Kenya National Bureau of Statistics and United Nations Children’s Fund July, 2013 iiiContents Table of Contents Table of Contents .iii List of Tables .v List of Figures .viii List of Abbreviations .ix Foreword .x Executive Summary .xi Summary Table of Findings .xv I. Introduction . 1 Background . 1 Survey Objectives . 2 II. Sample and Survey Methodology . 3 Sample Design . 3 Questionnaires . 3 Training and Fieldwork . 5 Data Processing . 5 III. Sample Coverage and the Characteristics of Households and Respondents . 6 Sample Coverage . 6 Characteristics of Households . 7 Characteristics of Female Respondents 15-49 Years of Age and Children Under-5 . 10 IV. Child Mortality . 14 Levels of Childhood Mortality . 14 V. Nutrition . 18 Nutritional Status . 18 Breastfeeding and Infant and Young Child Feeding . 21 Salt Iodization . 30 Children’s Vitamin A Supplementation . 32 Low Birth Weight . 34 VI. Child Health . 37 Vaccinations . 37 Neonatal Tetanus Protection . 41 Oral Rehydration Treatment . 42 Care Seeking and Antibiotic Treatment of Pneumonia . 49 Solid Fuel Use . 51 Malaria . 53 VII. Water and Sanitation . 60 Use of Improved Water Sources . 60 Use of Improved Sanitation Facilities . 69 Hand washing practices . 77 iv Contents VIII. Reproductive Health . 80 Fertility . 80 Contraception . 84 Antenatal Care . 86 Assistance at Delivery . 90 Place of Delivery . 92 Postnatal Care . 93 IX. Child Development . 95 Early Childhood Education and Learning . 95 Early Childhood Development . 100 X. Literacy and Education . 103 Literacy among Young Women . 103 School Readiness. 104 Primary and Secondary School Participation . 104 XI. Child Protection . 112 Birth Registration . 112 Child Labour . 113 Child Discipline . 115 Early Marriage and Polygyny . 117 Female Genital Mutilation/Cutting . 122 Attitudes toward Domestic Violence . 124 XII. HIV/AIDS, Sexual Behaviour, and Orphans . 126 Knowledge about HIV Transmission and Misconceptions about HIV/AIDS . 126 Knowledge of mother-to-child transmission of HIV/AIDS . 130 Accepting Attitudes toward People Living with HIV/AIDS . 131 Knowledge of a Place for HIV Testing, Counselling and Testing during Antenatal Care . 132 Sexual Behaviour Related to HIV Transmission . 135 Orphans . 142 List of References . 145 Appendix A. Sample Design . 146 Appendix B. List of Personnel Involved in the Survey . 150 Appendix C. Estimates of Sampling Errors . 153 Appendix D: Data Quality tables . 174 Appendix E: MICS4 Indicators - Numerators and Denominators . 190 Appendix F: Questionnaires . 198 vList of Tables List of Tables Table HH.1: Results of household, women’s and under-5 interviews . 6 Table HH.2: Household age distribution by sex . 7 Table HH.3: Household composition . 9 Table HH.4: Women’s background characteristics. 11 Table HH.5: Under-5’s background characteristics . 13 Table CM.1: Children ever born, children surviving and proportion dead . 15 Table CM.2: Child mortality . 16 Table NU.1: Nutritional status of children . 19 Table NU.2: Initial breastfeeding . 22 Table NU.3: Breastfeeding . 24 Table NU.4: Duration of breastfeeding . 26 Table NU.5: Age-appropriate breastfeeding . 27 Table NU.6: Introduction of solid, semi-solid or soft foods . 28 Table NU.7: Minimum meal frequency . 29 Table NU.8: Bottle feeding. 30 Table NU.9: Iodized salt consumption . 31 Table NU.10: Children’s vitamin A supplementation . 33 Table NU.11: Low birth weight infants. 35 Table CH.1: Vaccinations in first year of life . 38 Table CH.2: Vaccinations by background characteristics . 40 Table CH.3: Neonatal tetanus protection . 42 Table CH.4: Oral rehydration solutions and recommended homemade fluids . 44 Table CH.5: Feeding practices during diarrhoea . 46 Table CH.6: Oral rehydration therapy with continued feeding and other treatments . 48 Table CH.7: Care seeking for suspected pneumonia and antibiotic use during suspected pneumonia . 50 Table CH.9: Solid fuel use . 52 Table CH.10: Solid fuel use by place of cooking . 53 Table CH.11: Household availability of insecticide treated nets and protection by a vector control method . 54 Table CH.12: Children sleeping under mosquito nets . 55 Table CH.13: Pregnant women sleeping under mosquito nets . 56 Table CH.14: Anti-malarial treatment of children with anti-malarial drugs . 57 Table CH.16: Intermittent preventive treatment for malaria . 59 vi List of Tables Table WS.1: Use of improved water sources . 62 Table WS.2: Household water treatment . 64 Table WS.3: Time to source of drinking water . 66 Table WS.4: Person collecting water . 68 Table WS.5: Types of sanitation facilities . 70 Table WS.6: Use and sharing of sanitation facilities . 72 Table WS.7: Disposal of child’s faeces . 74 Table WS.8: Drinking water and sanitation ladders . 76 Table WS.9: Water and soap at place for handwashing . 78 Table WS.10: Availability of soap . 79 Table RH.1: Adolescent birth rate and total fertility rate . 80 Table RH.2: Early childbearing . 82 Table RH.3: Trends in early childbearing . 83 Table RH.4: Use of contraception . 85 Table RH.6: Antenatal care coverage . 87 Table RH.7: Number of antenatal care visits . 88 Table RH.8: Content of antenatal care . 89 Table RH.9: Assistance during delivery . 91 Table RH.10: Place of delivery. 92 Table RH.11a: Postnatal care provider . 94 Table CD.1: Early childhood education . 95 Table CD.2: Support for learning . 97 Table CD.3: Learning materials . 98 Table CD.4: Inadequate care . 100 Table CD.5: Early child development index . 102 Table ED.1: Literacy among young women . 103 Table ED.2: School readiness . 104 Table ED.3: Primary school entry . 105 Table ED.4: Primary school attendance . 106 Table ED.5: Secondary school attendance . 107 Table ED.6U: Children reaching last grade of primary school (unweighed with denominators) . 109 Table ED.7: Primary school completion and transition to secondary school . 110 Table ED.8: Education gender parity. 111 vii Table CP.1: Birth registration . 112 Table CP.2: Child labour. 114 Table CP.3: Child labour and school attendance . 115 Table CP.4: Child discipline. 116 Table CP.5: Early marriage and polygyny . 119 Table CP.6: Trends in early marriage . 120 Table CP.7: Spousal age difference . 121 Table CP.8: Female genital mutilation/cutting (FGM/C) among women . 123 Table CP.10: Approval of female genital mutilation/cutting (FGM/C) . 124 Table CP.11: Attitudes toward domestic violence . 125 Table HA.1: Knowledge about HIV transmission, misconceptions about HIV/AIDS, and comprehensive knowledge about HIV transmission . 127 Table HA.2: Knowledge about HIV transmission, misconceptions about HIV/AIDS, and comprehensive knowledge about HIV transmission among young women . 128 Table HA.3: Knowledge of mother-to-child HIV transmission . 130 Table HA.4: Accepting attitudes toward people living with HIV/AIDS . 132 Table HA.5: Knowledge of a place for HIV testing . 133 Table HA.6: Knowledge of a place for HIV testing among sexually active young women . 134 Table HA.7: HIV counselling and testing during antenatal care . 135 Table HA.8: Sexual behaviour that increases the risk of HIV infection . 136 Table HA.9: Sex with multiple partners . 138 Table HA.10: Sex with multiple partners among young women . 139 Table HA.11: Sex with non-regular partners . 141 Table HA.12: Children’s living arrangements and orphanhood . 143 Table HA.13: School attendance of orphans and non-orphans . 144 List of Tables viii List of Figures List of Figures Figure HH.1: Age and sex distribution of household population . 8 Figure CM.1: Under-5 mortality rates by background characteristics . 17 Figure NU.1: Percentage of children under age 5 who are underweight, stunted and wasted . 20 Figure NU.2: Percentage of mothers who started breastfeeding within one hour and within one day of birth . 23 Figure NU.3: Infant feeding patterns by age: Percentage distribution of children aged under 2 years by feeding pattern by age group . 25 Figure NU.4: Percentage of households consuming adequately iodized salt . 31 Figure NU.5: Percentage of infants weighing less than 2500 grams at birth . 36 Figure CH.1: Percentage of children aged 12-23 months who received the recommended vaccinations by 12 months . 39 Figure CH.3: Percentage of children under age 5 with diarrhoea who received oral rehydration treatment . 45 Figure CH.4: Percentage of children under age 5 with diarrhoea who received ORT or increased fluids and continued feeding. 47 Figure WS.1: Time to source of drinking water, Nyanza Province, Kenya, 2011 . 61 Figure HA.1: Percentage of women who have comprehensive knowledge of HIV/AIDS transmission . 129 Figure HA.2: Sexual behaviour that increases risk of HIV infection . 137 ixAbbreviations List of Abbreviations AIDS Acquired Immune Deficiency Syndrome ANC Antenatal Care BCG Bacillus Calmette Guerin (Tuberculosis) C-section Caesarian Section CSPro Census and Survey Processing System DPT Diphtheria Pertussis Tetanus DPT-HeB-Hib Diptheria Pertusis Tetanus Hepatitis B Haemophyllus Influenza B EA Enumeration Area ECDI Early Childhood Development Index EPI Expanded Programme on Immunization ERS Economic Recovery Strategy FGM/C Female Genital Mutilation/ Cutting GOK Government of Kenya GPI Gender Parity Index HIV Human Immunodeficiency Virus IDD Iodine Deficiency Disorders IPTp Intermittent Preventive Treatment of Malaria in Pregnancy IRS Indoor Residual Spraying ITN Insecticide Treated Net IUD Intrauterine Device IYCF Infant and Young Child Feeding Practices JMP Joint Monitoring Programme KAIS Kenya AIDS Indicator Survey KDHS Kenya Demographic Health Survey KEPI Kenya Expanded Programme on Immunization KESSP Kenya Education Sector Support Programme KNBS Kenya National Bureau of Statistics LAM Lactational Amenorrhea Method LLIN Long Lasting Insecticide Treated Nets MDG Millennium Development Goals MICS Multiple Indicator Cluster Survey MoH Ministry of Health MOMS Ministry of Medical Services MOPHS Ministry of Public Health and Sanitation NAR Net Attendance Rate NPA National Plan of Action ORT Oral Rehydration Therapy OVC Orphans and Vulnerable Children PMTCT Prevention of Mother to Child Transmission ppm Parts Per Million PRS Poverty Reduction Strategy PPS Probability proportional to size PSU Primary Sampling Units RHF Recommended Home Made Fluids SP Sulphadoxine- Pyrimethamine SPSS Statistical Package for Social Sciences STIs Sexually Transmitted Infections TBA Traditional Birth Attendant TFR Total Fertility Rate U5MR Under 5 mortality 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 VIP Ventilated Improved Latrine WFFC World Fit For Children WHO World Health Organization WSC World Summit for Children x Foreword Foreword The lives of children and women have improved significantly in the recent past, both at the global and national level. In spite of this, statistics and data presented at national levels often conceal disparities evident among the poor households in terms of access to basic services such as health care, education and protection. In addition, urban residents often present higher levels of achievement in most of the indicators compared to their rural counterparts. This may be attributed to their proximity to essential services ranging from infrastructure to provision of improved services like electricity and piped water. The Multiple Indicator Cluster Survey (MICS) 2011 was conducted to provide comprehensive and disaggregated data to fill the existing gap, particularly at the county level. The survey, which was the first of its kind to be conducted at the devolved level, was a follow-up to the MICS 2008 conducted in 13 districts in Eastern Province and the 2009 Mombasa Informal Settlement Survey. The objective of Nyanza MICS 2011 was to provide lower-level estimates relating to children and women residing in the six counties of the region. Particular emphasis was on reproductive health, child health and mortality, nutrition, child protection, childhood development, water and sanitation, hand washing practices, education, disability and HIV/AIDS, and orphanhood. The results of Nyanza MICS 2011 presented in this report will therefore provide requisite baseline information and facilitate evidence-based planning and programming by policymakers and stakeholders in the development sphere. This report is a culmination of concerted efforts of various organizations and individuals. I acknowledge the technical and financial assistance from the United Nations Children’s Fund (UNICEF). I sincerely applaud the UNICEF Kenya Country Office staff, lead by Dr. Robert Ndugwa- Research and Evaluation Specialist, for diligently managing and availing technical oversight of both the survey and report production. I also commend the hard work and dedication of Kenya National Bureau of Statistics (KNBS) staff, under the capable leadership of Mr. Macdonald Obudho – Director of Population and Social Statistics and Mr. James Gatungu- Director Production Statistics in the planning and implementation of the Survey. I remain indebted to households for generously and voluntarily responding to survey questions and allowing the survey teams to measure the weights and heights of children below 5 years of age. I urge all stakeholders to use the information presented in this report to impact positively on the lives of our people. Zachary Mwangi Director General Kenya National Bureau of Statistics xiExecutive Summary Executive Summary The Nyanza Province County-based MICS survey 2011 is a representative sample survey drawn using the 2009 Census Enumeration Areas (EAs) as the sampling frame. A stand-alone statistical frame for each of the Nyanza counties was constructed based on the 2009 census EAs for the purpose of this MICS survey. The 300 EAs were sampled using the probability proportional to size (PPS) sampling methodology, and information from a total of 6828 households were collected using structured questionnaires. The Nyanza Province County- based MICS survey is the first largest household sample surveys ever conducted with the inclusion of the County governance structures that came into effect as part of the Constitution of Kenya, 2010. The survey used a two stage design. In the first stage, EAs were selected and in the second stage households were selected systematically using a random start from the list of households1. The data was collected by twelve teams comprising of seven members each (one supervisor, one editor, one measurer and 4 interviewers). The survey was implemented by the Kenya National Bureau of Statistics (KNBS) with support from UNICEF. The summary findings from the survey are presented below. Child Mortality The mortality rates for children under five years were calculated using the birth history data collected during the survey. The under-five mortality rate is 91 deaths per 1,000 live births and the infant mortality rate is 60 deaths per 1,000 live births for the five year period preceeding the survey. The under five mortality rate within the counties ranges from 52 deaths per 1000 live births in Nyamira County to 167 deaths per 1000 live births in Siaya, whereas the infant mortality rate ranges from 43 in Kisii and Nyamira Counties to 112 deaths per 1000 live births in Siaya for the ten year period preceeding the survey. Nutritional Status and Breastfeeding Based on the new WHO standards, 15 per cent of children under five years old in Nyanza Province are severely or moderately underweight while 27 per cent were stunted. The prevalence of wasting is 4 per cent. Only 41 per cent of the children are timely breastfed (given breast milk within an hour of birth), and about a third of children age 0-5 months are exclusively breastfed. Overall, nearly half of all children aged 0-5 months (53 per cent) in Nyanza Province are appropriately breastfed for their age. Only three out of five (59 per cent) children under 5 years who live in Nyanza Province were reportedly weighed at the time of birth and the prevalence of low birth weight is at 5 per cent. In 88 per cent of the sampled households cooking salt was tested for its iodine content and among these, 87 per cent were found to have adequate iodine content (15ppm or more). Immunisation Seventy per cent of children age 12-23 months received full vaccination (BCG, 3 doses of Polio, 3 doses of DPT and measles) before reaching 12 monthsof age. BCG is given to 98 per cent of children age 12-23 months and the measles vaccine is received by 95 per cent. The dropout rate of DPT and polio vaccines from first dose to third dose is 6 and 13 per cent respectively. The yellow fever vaccination coverage among children age 12-23 months in Nyanza province is 85 per cent. Sixty four per cent of the mothers who gave birth in the last two years preceding the survey reportedly received adequate protection against tetanus (i.e., received two or more doses of TT injection during the two year period prior to delivery). 1 The household listing was carried out by 12 teams, each team comprised of a lister and mapper. xii Executive Summary Care of illness Reported incidence of diarrhoea during the last two weeks preceding the survey among children aged 0-59 months stood at 16 per cent. Of the reported diarrhoea cases, 35 per cent received oral rehydration therapy or recommended homemade fluid. About one in ten children less than five years reportedly had suspected pneumonia (acute respiratory infection (ARI) during the two weeks prior to the survey. About one in two (51 per cent) children who had suspected pneumonia reportedly sought appropriate treatment with 51 per cent reporting to have received antibiotic treatment. Malaria prevention In Nyanza Province, 93 per cent of the households have at least one mosquito net, and about 91 per cent have at least one treated net. Eighty one per cent of children below 5 years slept under any type of mosquito net while 78 per cent slept under an insecticide treated net the previous night. The proportion of pregnant women who reported sleeping under an insecticide treated net the previous night of the survey was 77 per cent. About one in five (22 per cent) children under five were reported to have had fever during the two weeks preceding the survey. Of those who had fever, only 47 per cent were given appropriate anti- malarial treatment. Sixty nine per cent of mothers who gave birth during two years preceding the survey received any medication to prevent malaria at an ANC visit during pregnancy, but only 27 per cent received SP/Fansidar two or more times during pregnancy. Water and sanitation Forty eight per cent of the population living in Nyanza Province use drinking water from an improved source – 62 per cent in urban areas and 46 per cent in rural areas. 60 per cent of household population that use an unimproved water source reportedly treat the drinking water. Only 36 per cent of the household population take less than 30 minutes round trip to fetch improved drinking water or have access to improved drinking water within their households. Among the household population who fetch water, in 79 per cent of cases an adult woman, in 12 per cent of cases an adult man and in 9 per cent of cases, a child below 15 years is the one responsible for collecting water. Thirty two per cent of the population is using improved sanitation toilet facilities, 22 per cent use a pit latrine with slab. Pit latrines without a slab and open pits are used by 53 per cent of the population who live in Nyanza province. In 73 per cent of cases, stool of children aged 0-2 years are disposed off safely. Only four per cent of the households in Nyanza Province were observed to have a designated place for hand washing. Among households where a designated place for handwashing was observed, 64 per cent had water and soap for handwashing. Reproductive health The total fertility rate (TFR) in Nyanza Province for the three year period preceding the survey is 4.9 children per woman. Teenage pregnancy, i.e., the proportion of women aged between 15 and 19 years who have began child bearing, is 34 per cent. About one in two (45 per cent) married or in union women aged 15-49 years who live in Nyanza Province use a modern contraceptive method and another three per cent use a traditional method of contraception. Ninety one per cent of mothers who gave birth in the past 2 years had an antenatal check-up and 46 per cent had four or more antenatal care visits. Fifty six per cent of the deliveries during the 2 year period preceding the survey were assisted by skilled personnel. About 22 per cent of births were delivered by traditional birth attendants, and this was more common in Kisumu, Migori and Homa Bay Counties where 30 to 33 per cent of all births were delivered by traditional birth attendants. xiii Childhood development In Nyanza Province, 44 per cent of children aged 36 - 59 months are currently attending early childhood development education. Thirty two per cent of children aged 36-59 months received support from a household member by being engaged in four or more activities that promote learning and school readiness during the three days preceding the survey. Sixty two per cent of children aged 0-59 months had 2 or more playthings to play with in their homes. About 55 per cent of children were left with inadequate care during the week preceding the survey, 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 Nyanza Province, 32 per cent of children aged 36- 59 months are developmentally on track. Education Seventy nine per cent of children in primary school going age in Nyanza province are attending primary school or secondary school. However, the adjusted secondary school net attendance ratio is only 25 per cent. The transition rate to secondary school is at 63 per cent. The gender parity index for primary school and for secondary school are 1.03 and 1.02 respectively. Female adult literacy rate in Nyanza Province is 86 per cent and literacy varies by place of residence (urban areas about 91 per cent versus 85 in rural areas). Child protection One out of two children (53 per cent) under five years in Nyanza Province has their births registered. Among the children from the poorest households, only 46 per cent are registered, compared to 71 among those from the richest households. Fifty one per cent of children aged 5-14 years in Nyanza Province are engaged in child labour. This proportion varies by counties and across age groups. For example, about 75 per cent of children in Siaya County aged 5-11 years are involved in child labour compared to 59 per cent for those living in Kisumu County. About three out of four children (65 per cent) aged 2-14 years received some form of psychological aggression during one month prior to the survey. More importantly, 88 per cent of children were subjected to any violent discipline method. In Nyanza Province 22 per cent of the women in the adolescent age group 15-19 years are married or in union. This proportion does not vary much between household wealth index levels (23 per cent in the poorest and 22 per cent among those from richest households), but varies by level of education (34 per cent among those with no education and 12 per cent among those with secondary or higher level of education). Among married women aged 20-24 years, nearly one in five (17 per cent) have partners who are 10 or more years older than their age. Female genital mutilation/cutting (FGM/C) and domestic violence Thirty seven per cent of women aged 15-49 years in Nyanza Province report to have undergone some form of female genital mutilation or cutting (FGM/C). The practice is more common in rural areas at 39 per cent versus 21 per cent in urban areas. Interestingly, within Nyanza there are two counties where the practice is very common i.e. Kisii and Nyamira counties with nearly 94 per cent of women reporting that they have had FGM. One in five (20 per cent) women believes that FGM/C should be continued while 69 per cent believe it should be discontinued. Women in Kisii and Nyamira counties are more likely to approve of the continuation of the practice of FGM/C than women in other counties. Sixty five per cent of women in Nyanza Province agree to wife beating under various circumstances. Executive Summary xiv For example, 50 per cent of women believe that a husband is justified to beat his wife if the wife neglected children while 38 per cent support wife beating if the wife argued with the husband. HIV and AIDS Almost all women aged 15-49 years (99.7 per cent) in Nyanza province have heard about HIV. However, only 53 per cent have comprehensive knowledge about HIV prevention. Knowledge about mother-to-child transmission of HIV is high in Nyanza Province, with 95 per cent reporting knowing that HIV can be transmitted from mother to child. Ninety five per cent of women age 15-49 years knew where to be tested, while 55 per cent reported having ever been tested. Ninety five per cent of women aged 15-24 years know where to get HIV tested and 42 per cent have been tested. Of those tested, 40 per cent received results of the HIV test. In Nyanza, 79 per cent of women aged 15-49 year who delivered a child in the 2 years preceding the survey received counselling on prevention of mother-to-child transmission of HIV and 78 per cent had the HIV test done during antenatal care visits. In Nyanza Province, 25 per cent of women aged 15- 24 years reportedly had sex before age 15. Among those who had sex during the past 12 months, 13 per cent reportedly had sex with a man who is 10 or more years older than them. Orphans and vulnerable children Eighteen per cent of all children aged between 0 and 17 years have been orphaned by one or both parents. Fifteen per cent of children in the same age group do not live with a biological parent and only 56 per cent are living with both parents. Executive Summary xvSummary Table of Findings Summary Table of Findings Multiple Indicator Cluster Surveys (MICS) and Millennium Development Goals (MDG) Indicators, Nyanza Province, Kenya, 2011 Topic MICS4 Indicator Number MDG Indicator Number Indicator Value and Units SAMPLE Households Households interviewed 6828 Number Women Number of women interview 5908 Number Children Number of children under-5 years with completed information 5045 Number CHILD MORTALITY Child mortality 1.1 4.1 Under-five mortality rate 91 per thousand 1.2 4.2 Infant mortality rate 60 per thousand NUTRITION Nutritional status Underweight prevalence 2.1a 1.8 Moderate and Severe (- 2 SD) 14.9 per cent 2.1b Severe (- 3 SD) 2.7 per cent Stunting prevalence 2.2a Moderate and Severe (- 2 SD) 27.1 per cent 2.2b Severe (- 3 SD) 10.6 per cent Wasting prevalence Moderate and Severe (- 2 SD) 3.9 per cent Severe (- 3 SD) 0.6 per cent Breastfeeding and infant feeding 2.4 Children ever breastfed 96.4 per cent 2.5 Early initiation of breastfeeding 41.2 per cent 2.6 Exclusive breastfeeding under 6 months 35.8 per cent 2.7 Continued breastfeeding at 1 year 82.2 per cent 2.8 Continued breastfeeding at 2 years 43.9 per cent 2.9 Predominant breastfeeding under 6 months 52.2 per cent 2.10 Duration of breastfeeding 20.5 Median (months) 2.11 Bottle feeding 11.7 per cent 2.12 Introduction of solid, semi-solid or soft foods 56.7 per cent 2.13 Minimum meal frequency 32.2 per cent 2.14 Age-appropriate breastfeeding 53.3 per cent Salt iodization 2.16 Iodized salt consumption 87.4 per cent xvi Summary Table of Findings Vitamin A 2.17 Vitamin A supplementation (children under age 5) 47.4 per cent Low birth weight 2.18 Low-birth weight infants 5.4 per cent 2.19 Infants weighed at birth 58.8 per cent CHILD HEALTH Vaccinations 3.1 Tuberculosis immunization coverage 97.6 per cent 3.2 Polio immunization coverage 84.4 per cent 3.3 Immunization coverage for diphtheria, pertussis and tetanus (DPT) 91.1 per cent 3.4 4.3 Measles immunization coverage 95.3 per cent 3.5 Hepatitis B immunization coverage 91.1 Per cent 3.6 Yellow fever immunization coverage 84.6 per cent Tetanus toxoid 3.7 Neonatal tetanus protection 64.0 per cent Care of illness 3.8 Oral rehydration therapy with continued feeding 43.2 per cent 3.9 Care seeking for suspected pneumonia 50.7 per cent 3.10 Antibiotic treatment of suspected pneumonia 50.6 per cent Solid fuel use 3.11 Solid fuels 97.0 per cent Malaria 3.12 Household availability of insecticide-treated nets (ITNs) 91.4 per cent 3.13 Households protected by a vector control method 93.5 per cent 3.14 Children under age 5 sleeping under any mosquito net 80.5 per cent 3.15 6.7 Children under age 5 sleeping under insecticide- treated nets (ITNs) 77.9 per cent 3.17 Antimalarial treatment of children under 5 the same or next day 32.9 per cent 3.18 6.8 Antimalarial treatment of children under age 5 47.1 per cent 3.19 Pregnant women sleeping under insecticide- treated nets (ITNs) 77.2 per cent 3.20 Intermittent preventive treatment for malaria 26.9 per cent WATER AND SANITATION Water and sanitation 4.1 7.8 Use of improved drinking water sources 48.3 per cent 4.2 Water treatment 60.2 per cent 4.3 7.9 Use of improved sanitation facilities 15.1 per cent 4.4 Safe disposal of child’s faeces 72.5 per cent 4.5 Place for hand-washing (water and soap are available) 63.6 per cent 4.6 Availability of soap (soap available, water not available) 85.2 per cent Topic MICS4 Indicator Number MDG Indicator Number Indicator Value and Units xvii REPRODUCTIVE HEALTH Contraception and unmet need 5.1 5.4 Adolescent birth rate 184 per 1,000 5.2 Early childbearing 39.9 per cent 5.3 5.3 Contraceptive prevalence rate 47.5 per cent Maternal and new- born health 5.5 Antenatal care coverage 5.5a At least once by skilled personnel 91.3 per cent 5.5b At least four times by any provider 46.0 per cent 5.6 Content of antenatal care 62.9 per cent 5.7 5.2 Skilled attendant at delivery 55.6 per cent 5.8 Institutional deliveries 52.7 per cent 5.9 Caesarean section 6.1 per cent CHILD DEVELOPMENT Child development 6.1 Support for learning 31.9 per cent 6.2 Father’s support for learning 30.5 per cent 6.3 Learning materials: children’s books 4.4 per cent 6.4 Learning materials: playthings 61.6 per cent 6.5 Inadequate care 55.3 per cent 6.6 Early child development index 31.8 per cent 6.7 Attendance to early childhood education 44.2 per cent EDUCATION Literacy and education 7.1 2.3 Literacy rate among young women 85.6 per cent 7.2 School readiness 76.8 per cent 7.3 Net intake rate in primary education 21.0 per cent 7.4 2.1 Primary school net attendance ratio (adjusted) 78.9 per cent 7.5 Secondary school net attendance ratio (adjusted) 25.3 per cent 7.6 2.2 Children reaching last grade of primary 89.1 per cent 7.7 Primary completion rate 76.5 per cent 7.8 Transition rate to secondary school 62.8 per cent 7.9 Gender parity index (primary school) 1.03 ratio 7.10 Gender parity index (secondary school) 1.02 ratio CHILD PROTECTION Birth registration 8.1 Birth registration 52.7 per cent Child labour 8.2 Child labour 50.7 per cent 8.3 School attendance among child labourers 96.6 per cent 8.4 Child labour among students 51.0 per cent Child discipline 8.5 Violent discipline 88.4 per cent Topic MICS4 Indicator Number MDG Indicator Number Indicator Value and Units Summary Table of Findings xviii Early marriage and polygyny 8.6 Marriage before age 15 12.5 per cent 8.7 Marriage before age 18 45.4 per cent 8.8 Young women age 15-19 currently married or in union 22.1 per cent 8.9 Polygyny 18.6 per cent Spousal age difference 8.10a Women age 15-19 16.9 per cent 8.10b Women age 20-24 17.1 per cent Female genital mutilation/cutting 8.11 Approval for female genital mutilation/cutting (FGM/C) 19.9 per cent 8.12 Prevalence of female genital mutilation/cutting (FGM/C) among women 36.5 per cent Domestic violence 8.14 Attitudes towards domestic violence 65.1 per cent HIV/AIDS, SEXUAL BEHAVIOUR, AND ORPHANED AND VULNERABLE CHILDREN HIV/AIDS knowledge and attitudes 9.1 Comprehensive knowledge about HIV prevention 53.0 per cent 9.2 6.3 Comprehensive knowledge about HIV prevention among young people 53.3 per cent 9.3 Knowledge of mother-to-child transmission of HIV 50.1 per cent 9.4 Accepting attitude towards people living with HIV 20.1 per cent 9.5 Women who know where to be tested for HIV 95.2 per cent 9.6 Women who have been tested for HIV and know the results 54.9 per cent 9.7 Sexually active young women who have been tested for HIV and know the results 39.8 per cent 9.8 HIV counselling during antenatal care 79.0 per cent 9.9 HIV testing during antenatal care 76.8 per cent Sexual behaviour 9.10 Young women who have never had sex 44.6 per cent 9.11 Sex before age 15 among young women 25.4 per cent 9.12 Age-mixing among sexual partners 13.2 per cent 9.13 Sex with multiple partners 2.4 per cent 9.14 Condom use during sex with multiple partners 43.1 per cent 9.15 Sex with non-regular partners 5.8 per cent 9.16 6.2 Condom use with non-regular partners 68.1 per cent Orphaned children 9.17 Children’s living arrangements 15.2 per cent 9.18 Prevalence of children with at least one parent dead 18.2 per cent 9.19 6.4 School attendance of orphans 95.5 per cent 9.20 6.4 School attendance of non-orphans 99.2 per cent Topic MICS4 Indicator Number MDG Indicator Number Indicator Value and Units Summary Table of Findings 1Introduction I. Introduction Background This report is based on the Nyanza province Multiple Indicator Cluster Survey, conducted in 2011 by the Kenya National Bureau of Statistics in collaboration with County and Provincial administration and UNICEF. The survey provides valuable information on the situation of children and women in Nyanza province and its 6 counties, and was based, in large part, on the needs to monitor progress towards goals and targets emanating from recent international agreements: the Millennium Declaration, adopted by all 191 United Nations Member States in September 2000, and the Plan of Action of A World Fit For Children, adopted by 189 Member States at the United Nations Special Session on Children in May 2002. Both of these commitments build upon promises made by the international community at the 1990 World Summit for Children. In signing these international agreements, governments committed themselves to improving conditions for their children and to monitoring progress towards that end. UNICEF was assigned a supporting role in this task (see box below). 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 (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.” 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.” 2 Introduction Presently, the Government’s Vision 2030 – which is the road map for Kenya’s political, economic and social development - commits to creating a better future for all children, and hence is very much in line with the achievement of the above mentioned goals. Specific policy responses and programmes exist such as the Free Primary Education, Free Day Secondary Schooling, and Cash Transfers for Orphans and Vulnerable Children2, and slum upgrading programmes and all these are geared towards challenging the current and future bottlenecks within all the social sectors. On the legal framework , there are enough local acts, several international statutes and policies that have been domesticated to obligate the Government, communities and families to take more action and efforts in ensuring and guaranteeing the well-being of all citizen and children in Kenya. The Kenya constitution 2010 is very elaborate and supportive on citizen’s empowerment and human rights. Providing timely data is therefore vital for monitoring the progress that the country is making using internationally existing benchmarks, goals and targets. This latest provincial level survey aims to increase the in-depth analysis of data at disaggregated levels, with a particular focus on areas with less available planning data as well as those exhibiting significant inequities. This approach is in line with the on- going devolution of power in Kenya with substantial powers for administration, governance and planning expected to move to the County levels. This final report presents the results of the indicators and topics covered in the survey. Survey Objectives The 2011 Nyanza Province Multiple Indicator Cluster Survey has as its primary objectives: • To provide up-to-date information for assessing the situation of children and women in Nyanza Province; • To 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; • To contribute to the improvement of data and monitoring systems in Nyanza province and to strengthen technical expertise in the design, implementation, and analysis of such systems. • To generate data on the situation of children and women, including the identification of vulnerable groups and of disparities, to inform policies and interventions. 2 Kenya Government Vision 2030 (Ministry of Planning and Vision 2030). 3Sample and Survey Methodology II. Sample and Survey Methodology Sample Design The sample for the Nyanza Province Multiple Indicator Cluster Survey (MICS) was designed to provide estimates for a large number of indicators on the situation of children and women at the provincial level, for urban and rural areas, and for counties: Siaya, Migori, Kisumu, Homa Bay, Kisii, and Nyamira. The urban and rural areas within each County were identified as the main sampling strata and the sample was selected in two stages. The primary sampling units (PSUs) for the survey were the recently created enumeration areas (EAs) based on the 2009 Kenya Population and Housing Census while the households were the ultimate sampling units. A stand-alone statistical frame for each of the Nyanza counties based on the 2009 census EAs was created for the purpose of MICS. Within each stratum, a specified number of census enumeration areas were selected systematically with probability proportional to size. A complete listing of all households in the selected EAs was undertaken by identifying and mapping all existing structures and households. The listing process ensured that the EAs had one measure of size (MOs). One MOs was defined as an EA having an average of 100 households. EA with less than 50 households was amalgamated with the most convenient adjoining EA. On the other hand, the EAs with more than 149 households were segmented during household listing and eventually one segment scientifically selected and developed into a cluster. After a household listing exercise within the selected enumeration areas, a systematic sample of 25 households was drawn from each of the sampled enumeration area. The sample was stratified by County, urban and rural areas, and is not self-weighting. For reporting provincial level results, sample weights are used. A more detailed description of the sample design can be found in Appendix A. Questionnaires Three sets of questionnaires were used in the survey: 1) a household questionnaire which was used to collect information on all de jure household members (usual residents), the household, and the dwelling; 2) a women’s questionnaire administered in each household to all women aged 15-49 years; and 3) an under-5 questionnaire, administered to mothers or caretakers for all children under 5 living in the household. The questionnaires included the following modules: The Household Questionnaire included the following modules: • Household Listing Form • Education • Water and Sanitation • Household Characteristics • Insecticide Treated Nets • Indoor Residual Spraying • Child Labour • Child Discipline • Handwashing • Salt Iodization • Orphaned and vulnerable children • Disability Findings from the disability module will be separately disseminated as a standalone report as part of wider focus on the status of disability in Kenya 2013. 4 Sample and Survey Methodology The Questionnaire for Individual Women was administered to all women aged 15-49 years living in the households, and included the following modules: • Women’s Background • Child Mortality • Maternal and Newborn Health • Illness Symptoms • Contraception • Female Genital Mutilation/Cutting • Attitudes Towards Domestic Violence • Marriage/Union • Sexual Behaviour • HIV/AIDS • Birth History • Tetanus Toxoid The Questionnaire for Children under Five was administered to mothers or caretakers of children under 5 years of age3 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 • Breastfeeding • Care of Illness • Malaria • Immunization • Anthropometry • Vitamin A The questionnaires are based on the MICS4 model questionnaire tested at the begining of the fourth round of MICS4. From the MICS4 model English version, the questionnaires were translated into Swahili, Luo, and Kisii languages and back-translated to ensure that the meaning of the translations remained the same. Based on the results of the back-translations, adjustments were made to the wording and translation of the questionnaires. A copy of the Nyanza Province MICS questionnaires is provided in Appendix F. In addition to the administration of questionnaires, fieldwork teams tested the salt used for cooking in the households for iodine content, observed the place for handwashing and measured the weights and heights of children age under 5 years. Salt samples were also collected and labelled in incidences where the testing kits were not available and testing undertaken within the local offices. Details and findings of these measurements are provided in the respective sections of the report. 3 The terms “children under 5”, “children age 0-4 years”, and “children aged 0-59 months” are used interchangeably in this report. 4 The model MICS4 questionnaires can be found at www.childinfo.org 5Sample and Survey Methodology Training and Fieldwork Training for the fieldwork was conducted for 19 days in August/September, 2011. Training included lectures on interviewing techniques and the contents of the questionnaires, and mock interviews between trainees to gain practice in asking questions. Towards the end of the training period, trainees spent 2 days in practice interviewing in Kisumu County within clusters that were not sampled for the main survey exercise. Data were collected by 12 teams; each was comprised of 5 interviewers, one driver, one editor, one measurer and a supervisor. Fieldwork began in October 2011 and was concluded in December 2011. Data Processing Data were entered using the CSPro software. The data were entered into microcomputers by 23 data entry operators and 4 data entry supervisors. In order to ensure quality control, all questionnaires were double entered and internal consistency checks were performed. Procedures and standard programs developed under the global MICS4 programme and adapted to the Nyanza Province questionnaire were used throughout. Data processing began three weeks after commencing data collection in October 2011 and was completed in January 2012. Data were analysed using the Statistical Package for Social Sciences (SPSS) software program, Version 18, and the model syntax and tabulation plans developed by UNICEF were used for this purpose. 6 Sample Coverage and the Characteristics of Households and Respondents III. Sample Coverage and the Characteristics of Households and Respondents Sample Coverage Of the 7500 households selected for the sample, 6994 were found to be occupied. Of these, 6828 were successfully interviewed for a household response rate of 97.6 per cent. In the interviewed households, 6581 women (age 15-49 years) were identified. Of these, 5908 were successfully interviewed, yielding a response rate of 89.8 per cent within interviewed households. In addition, 5157 children under age five were listed in the household questionnaire. Questionnaires were completed for 5045 of these children, which corresponds to a response rate of 97.8 per cent within interviewed households. Overall response rates of 87.6 and 95.5 are calculated for the women’s and under-5’s interviews respectively (Table HH.1). Table HH.1: Results of household, women’s, and under-5 interviews Number of households, women and children under 5 by results of the household, women’s and under-5’s interviews, and household, women’s and under-5’s response rates, Nyanza Province, Kenya, 2011 Area County TotalRural Urban Siaya Kisumu Homa Bay Migori Kisii Nyamira Households Sampled 6475 1025 1250 1250 1250 1250 1250 1250 7500 Households Occupied 6099 895 1190 1154 1182 1159 1191 1118 6994 Households Interviewed 5984 844 1181 1119 1164 1123 1161 1080 6828 Household response rate 98.1 94.3 99.2 97.0 98.5 96.9 97.5 96.6 97.6 Women Eligible 5747 834 992 1033 1117 1094 1223 1122 6581 Women Interviewed 5171 737 949 926 1033 952 1078 970 5908 Women’s response rate 90.0 88.4 95.7 89.6 92.5 87.0 88.1 86.5 89.8 Women’s overall response rate 88.3 83.3 94.9 86.9 91.1 84.3 85.9 83.5 87.6 Children under 5 Eligible 4608 549 805 771 926 1008 918 729 5157 Children under 5 Mother/ Caretaker Interviewed 4519 526 801 765 911 975 897 696 5045 Under-5’s response rate 98.1 95.8 99.5 99.2 98.4 96.7 97.7 95.5 97.8 Under-5’s overall response rate 96.2 90.4 98.8 96.2 96.9 93.7 95.3 92.2 95.5 There are some differentials in response rates by urban and rural areas. Overall household responses rates were 98 per cent for rural areas and 94 per cent for urban areas. The same trends was observed for overall women response rates and under-five overall response rates, in favour of rural areas. At the County levels, household response rates were all above 95 per cent, but differentials were observed for women response rates across counties. Overall women response rates were lowest in Nyamira County at 84 per cent and highest in Siaya at 95 per cent. Given the fact that Nyamira has response rates below 85 per cent, the results for this region or residence should be interpreted with some caution, as the response rate is low. Similarly overall under-five response rates were highest in Siaya County and lowest in Nyamira County. The reasons for the lower response rates for Nyamira County are not readily available, but a range of explanations for this lower performance include that a large section of the population who were not reachable on certain prayer days, in addition, heavy downpours affected availability of respondents during the whole day while working on farms. 7Sample Coverage and the Characteristics of Households and Respondents Characteristics of Households The weighted age and sex distribution of survey population is provided in Table HH.2. The distribution is also used to produce the population pyramid in Figure HH.1. In the 6828 households successfully interviewed in the survey, 30439 household members were listed. Of these, 14829 were males, and 15610 were females. Table HH.2: Household age distribution by sex Percentage 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, Nyanza Province, Kenya, 2011 Males Females Missing Total Number Per cent Number Per cent Number Per cent Number Per cent Age 0-4 2571 17.3 2502 16.0 0 0.0 5073 16.7 5-9 2446 16.5 2460 15.8 0 0.0 4907 16.1 10-14 2116 14.3 2208 14.1 1 14.6 4324 14.2 15-19 1783 12.0 1524 9.8 0 0.0 3307 10.9 20-24 1105 7.5 1343 8.6 0 0.0 2448 8.0 25-29 1012 6.8 1231 7.9 0 0.0 2243 7.4 30-34 778 5.2 794 5.1 0 0.0 1572 5.2 35-39 683 4.6 715 4.6 1 22.9 1399 4.6 40-44 448 3.0 498 3.2 0 0.0 946 3.1 45-49 395 2.7 462 3.0 0 0.0 857 2.8 50-54 377 2.5 536 3.4 0 0.0 913 3.0 55-59 341 2.3 417 2.7 0 0.0 759 2.5 60-64 268 1.8 301 1.9 0 0.0 569 1.9 65-69 159 1.1 198 1.3 0 0.0 358 1.2 70-74 141 0.9 175 1.1 0 0.0 316 1.0 75-79 100 0.7 94 0.6 2 42.1 196 0.6 80-84 54 0.4 95 0.6 0 0.0 149 0.5 85+ 38 0.3 48 0.3 0 0.0 86 0.3 Missing/DK 10 0.1 5 0.0 1 20.4 16 0.1 Dependency age groups 0-14 7133 48.1 7170 45.9 1 14.6 14304 47.0 15-64 7190 48.5 7821 50.1 1 22.9 15013 49.3 65+ 492 3.3 611 3.9 2 42.1 1105 3.6 Missing/DK 10 0.1 5 0.0 1 20.4 16 0.1 County Siaya 2378 16.0 2603 16.7 0 0.0 4981 16.4 Kisumu 2606 17.6 2652 17.0 2 43.3 5260 17.3 Homa Bay 2436 16.4 2574 16.5 1 14.6 5010 16.5 Migori 2621 17.7 2711 17.4 0 0.0 5333 17.5 Kisii 3301 22.3 3548 22.7 2 42.1 6851 22.5 Nyamira 1485 10.0 1519 9.7 0 0.0 3004 9.9 Children and adult populations Children age 0-17 years 8245 55.6 8133 52.1 1 14.6 16379 53.8 Adults age 18+ years 6571 44.3 7469 47.9 3 65.0 14043 46.1 Missing/DK 11 0.1 5 0.0 1 20.4 17 0.1 Total 14827 100 15607 100 5 100 30439 100 8 The population pyramid shows a high proportion of population in the younger dependency age groups, i.e., 0-14 years. The proportion of males in the age group 0-14 years is nearly balanced with females in the same group, but slightly different for the age group 20-24 i.e. 3.5 per cent for males and 4.5 per cent for females, respectively. A similar pattern is observed for, the proportion of males in 30-49 years age groups being slightly smaller than that of females, respectively. The low proportion of people in the potential working age groups clearly show the possibility of selective out-migration of young workers from this region to other areas within the country. Figure HH.1: Age and sex distribution of household population, Nyanza Province, Kenya, 2011 Table HH.3 - HH.5 provide basic information on the households, female respondents age 15-49, and children under-5 by presenting the unweighted, as well as the weighted numbers. Information on the basic characteristics of households, women and children under-5 interviewed in the survey is essential for the interpretation of findings presented later in the report and also can provide an indication of the representativeness of the survey. The remaining tables in this report are presented only with weighted numbers. See Appendix A for more details about the weighting. Table HH.3 provides basic background information on the households. Within households, the sex of the household head, region, residence, number of household members, and education of household head are shown. 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. 0 Males Females 2 24 46 6 88 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+ Sample Coverage and the Characteristics of Households and Respondents A g e g ro up s Percentage of population in age group. 9 Table HH.3: Household composition Percentage and frequency distribution of households by selected characteristics, Nyanza Province, Kenya, 2011 Weighted per cent Number of households Weighted Unweighted Sex of household head Male 66.2 4518 4566 Female 33.8 2308 2261 County Siaya 17.7 1209 1181 Kisumu 18.5 1261 1119 Homa Bay 16.0 1089 1164 Migori 16.5 1128 1123 Kisii 21.7 1483 1161 Nyamira 9.6 657 1080 Residence Rural 84.2 5751 5984 Urban 15.8 1077 844 Number of household members 1 11.2 762 724 2 10.3 702 671 3 14.8 1014 1020 4 17.5 1192 1203 5 15.4 1049 1053 6 12.5 856 881 7 8.3 565 572 8 5.1 348 354 9 2.5 171 177 10+ 2.5 168 173 Education of household head None 20.9 1430 1395 Primary 54.1 3691 3713 Secondary+ 24.6 1681 1696 Missing/Don’t know 0.4 26 24 Total 100.0 6828 6828 Households with at least One child age 0-4 years 50.3 6828 6828 One child age 0-17 years 80.0 6828 6828 One woman age 15-49 years 74.2 6828 6828 Mean household size 4.5 6828 6828 The weighted and unweighted numbers of total households are equal, since sample weights were normalized (See Appendix A). The table also shows the proportions of households with at least one child under 18, at least one child under 5, and at least one eligible woman age 15-49. The table also shows the weighted average household size estimated by the survey. In Nyanza, nearly 34 per cent of the households are female headed which is comparable to the rural national average of 36 per cent (KDHS, 2008/9). Fifty per cent of the households have at least one child below five years of age and 80 per cent of the households have at least one child below 18 years of age. Sample Coverage and the Characteristics of Households and Respondents 10 Sample Coverage and the Characteristics of Households and Respondents About three in four households (74 per cent) have at least one woman in the 15-49 years reproductive age group. It is also important to note that about one in ten households in Nyanza province is one-member households and about one in four households (25 per cent) have 2-3 persons. The mean household size in Nyanza is 4.5 persons. The distribution of the sampled households by educational level of the household head shows that, 54 per cent are educated up to primary level and another 25 per cent are educated up to secondary or higher levels. The remaining 21 per cent have no-education or have never been to school. Characteristics of Female Respondents 15-49 Years of Age and Children Under-5 Tables HH.4 and HH.5 provide information on the background characteristics of female respondents 15- 49 years of age and of children under age 5. In both tables, the total numbers of weighted and unweighted observations are equal, since sample weights have been normalized (standardized). In addition to providing useful information on the background characteristics of women and children, 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. 11Sample Coverage and the Characteristics of Households and Respondents Table HH.4: Women’s background characteristics Percentage and frequency distribution of women age 15-49 years by selected characteristics, Nyanza Province, Kenya, 2011 Weighted per cent Number of women Weighted Unweighted Area Rural 84.4 4985 5171 Urban 15.6 923 737 County Siaya 15.5 916 949 Kisumu 17.9 1057 926 Homa Bay 16.0 944 1033 Migori 16.3 963 952 Kisii 23.8 1404 1078 Nyamira 10.5 623 970 Age 15-19 20.6 1216 1215 20-24 20.2 1192 1175 25-29 19.6 1159 1166 30-34 12.6 747 745 35-39 11.4 675 689 40-44 8.1 478 479 45-49 7.4 440 439 Marital/Union status Currently married/in union 66.2 3912 3941 Widowed 7.3 431 434 Divorced 0.6 35 38 Separated 3.4 200 190 Never married/in union 22.5 1330 1305 Motherhood status Ever gave birth 80.5 4757 4778 Never gave birth 19.5 1151 1130 Births in last two years Had a birth in last two years 30.7 1812 1844 Had no birth in last two years 69.3 4096 4064 Education None 7.3 430 391 Primary 63.5 3752 3797 Secondary + 29.2 1725 1720 Wealth index quintiles Poorest 18.9 1115 1147 Second 19.4 1144 1151 Middle 19.5 1150 1199 Fourth 20.1 1188 1218 Richest 22.2 1311 1193 Total 100.0 5908 5908 12 Table HH.4 provides background characteristics of female respondents 15-49 years of age. The table includes information on the distribution of women according to residence, regions, age, marital status, motherhood status, births in last two years, education5, and wealth index quintiles6. Overall, 66 per cent of the women age 15-49 years in Nyanza province are currently married or in union and another 23 per cent have never married or been in union. Eighty one per cent have ever given birth while 7 per cent have no education and 29 per cent have secondary or higher level of education. The wealth index ranked 19 and 22 per cent of the women in the poorest and richest income categories respectively. The weighted and unweighted numbers in particular categories vary due to extensive over-sampling or under-sampling for some areas/counties. Some background characteristics of children under 5 are presented in Table HH.5. These include the distribution of children by several attributes: sex, region and residence, age, mother’s or caretaker’s education, and wealth quintiles. An almost equal proportion of male children under-five years (50.7 per cent) were found in the sample compared to female children (49.3 per cent). About 10 per cent of children below-five years belong to 0-5 months of age and another 10 per cent in 6-11 month category. Twenty three per cent of the children belong to mothers/care taker who have secondary or higher education, 70 per cent belong to mothers with primary education and 7 per cent belong to mothers or caretakers with no education. The distribution of children below 5 years by the wealth quintiles of the household show that, 23 per cent are from the poorest households, 20 per cent from middle wealth quintiles and 18 per cent from the richest households. These categories are mostly used in the subsequent tabulations of this report. There are considerable variations in the weighted and unweighted numbers in particular categories due to extensive over-sampling or under-sampling, and this is more evident with the County regions e.g. Nyamira County. 5 Unless otherwise stated, “education” refers to educational level attended by the respondent throughout this report when it is used as a background variable. 6 Principal components analysis was 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 assign weights (factor scores) to each of the household assets. Each household was then assigned a wealth score based on these weights and the assets owned by that household. The survey household population was then ranked according to the wealth score of the household they are living in, and was finally divided into 5 equal parts (quintiles) from lowest (poorest) to highest (richest). The assets used in these calculations were as follows: source of drinking water, type of sanitation, persons per sleeping room, type of floor, roof, wall, cooking fuel; possession of electricity, radio, black and white TV, color Tv, mobile phone, non-mobile phone, fridge, blender, water heater, animal-drawn cart, boat with motor, washing machine, computer, internet, watch, bicycle, car or truck, motorcycle, sewing machine, air conditioner, VCR VCD or DVD. 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. Gwatkin, D.R., Rutstein, S., Johnson, K. , Pande, R. and Wagstaff. A., 2000. Socio-Economic Differences in Health, Nutrition, and Population. HNP/Poverty Thematic Group, Washington, DC: World Bank. Rutstein, S.O. and Johnson, K., 2004. The DHS Wealth Index. DHS Comparative Reports No. 6. Calverton, Maryland: ORC Macro. Sample Coverage and the Characteristics of Households and Respondents 13 Table HH.5: Under-5’s background characteristics Percentage and frequency distribution of children under five years of age by selected characteristics, Nyanza Province, Kenya, 2011 Weighted per cent Number of children Weighted Unweighted Sex Male 50.7 2559 2561 Female 49.3 2486 2484 County Siaya 16.0 809 801 Kisumu 17.1 861 765 Homa Bay 17.2 868 911 Migori 18.4 930 975 Kisii 22.5 1135 897 Nyamira 8.8 442 696 Area Rural 87.8 4429 4519 Urban 12.2 616 526 Age 0-5 9.5 480 488 6-11 10.3 522 509 12-23 17.2 868 879 24-35 20.7 1047 1043 36-47 21.7 1094 1105 48-59 20.5 1034 1021 Mother’s education None 6.8 345 319 Primary 69.8 3523 3558 Secondary+ 23.3 1175 1166 Missing/Don’t know 0.1 3 2 Wealth index quintiles Poorest 23.2 1168 1191 Second 20.9 1054 1053 Middle 19.5 985 1025 Fourth 18.7 944 955 Richest 17.7 894 821 Total 100.0 5045 5045 Sample Coverage and the Characteristics of Households and Respondents 14 IV. Child Mortality One of the overarching goals of the Millennium Development Goals (MDGs) and the World Fit for Children (WFFC) is to reduce infant and under-five mortality. Specifically, the MDGs call for the reduction in under- five mortality by two-thirds between 1990 and 2015. Monitoring progress towards this goal is an important but difficult objective. Measuring childhood mortality may seem easy, but attempts using direct questions, such as “Has anyone in this household died in the last year?” give inaccurate results. However, the Nyanza province Survey utilised direct measures of child mortality from birth histories which is one of the best ways of obtaining this information. The birth history obtained from women aged 15-49 years includes number of children ever born and living by sex, and date of birth of each child born. If the child is not alive at the time of survey, information on age of the child at the time of death is also obtained. The Infant Mortality Rate (IMR) is the probability of dying before the first birthday. The Under-five Mortality Rate (U5MR) is the probability of dying before the fifth birthday. The neonatal mortality rate is the probability of dying before one month of life. Post neonatal mortality rate is the probability of dying between one month and one year of life. The child mortality rate refers to probability of dying between one and five year of life. All mortality rates mentioned above are expressed per 1,000 live births, except for child mortality rate, which is expressed per 1,000 children surviving up to 12 months of age. Though direct estimates of mortality obtained from birth histories are the best, the quality of these mortality estimates depend on the completeness of information obtained in the birth histories. In many cases women tend to avoid reporting their dead children and this tend to under estimate the mortality levels. Levels of Childhood Mortality Table CM.1 provides estimates of childhood mortality for the five year period preceding the survey for the Nyanza province. The infant mortality rate (IMR) is estimated at 60 per thousand live births, while the under-5 mortality rate (U5MR) is 91 per thousand live births. Child Mortality 15Child Mortality Table CM.1: Early childhood mortality rates Neonatal, post-neonatal, Infant, child and under-five mortality rates for five year periods preceding the survey, Nyanza Province, Kenya, 2011 Years preceding the survey Neonatal mortality rate [1] Post-neonatal mortality rate [2] Infant mortality rate [3] Child mortality rate [4] Under-five mortality rate [5] 0-4 25 35 60 33 91 5-9 27 57 84 48 128 10-14 27 68 95 62 151 15-19 35 77 112 80 183 [1] MICS indicator 1.3 [2] MICS indicator 1.4 [3] MICS indicator 1.2; MDG indicator 4.2 [4] MICS indicator 1.5 [5] MICS indicator 1.1; MDG indicator 4.1 Post-neonatal mortality rates are computed as the difference between the infant and neonatal mortality rates Table CM.2 provides estimates of child mortality by selected socio-economic and demographic background characteristics. To ensure a sufficient number of births to study mortality differentials across the population sub-groups, period-specific rates for Table CM.2 are presented for the 10-year period preceding the survey (approximately 2002 to 2011). The results in Table CM.2 indicate that the under-five mortality rate is 111 deaths per 1,000 live births in rural areas and 92 in urban areas. Within counties, under-five mortality rates ranges from 52 deaths per 1,000 live births in Nyamira County to 167 deaths per 1000 live births in Siaya county. The infant mortality rates ranges from 43 deaths per 1,000 live births in Nyamira and Kisii to 112 in Siaya County. Under-5 mortality rate is 117 per 1000 among males and 100 per 1000 among females in Nyanza. The infant mortality rate is 80 per 1000 live births for males and 63 per 1000 live birth for females. Under-5 mortality among children whose mothers have secondary or higher levels of education is 69 per 1000 live births, while for those with mothers having no education its 110 per 1000 live births. Further differentials in under-5 mortality rates by selected background characteristics are shown in Figure CM.2 16 Child Mortality Table CM.2: Early childhood mortality rates by socioeconomic characteristics Neonatal, post-neonatal, infant, child and under-five mortality rates for the ten year period preceding the survey, by socioeconomic characteristics, Nyanza Province, Kenya, 2011 Neonatal mortality rate [1] Post-neonatal mortality rate [2] Infant mortality rate [3] Child mortality rate [4] Under-five mortality rate [5] County Siaya 32 80 112 62 167 Kisumu 23 52 75 33 105 Homa Bay 26 51 77 57 130 Migori 27 49 76 50 123 Kisii 23 19 43 18 60 Nyamira 26 17 43 10 52 Residence Urban 20 39 59 35 92 Rural 27 47 74 41 111 Mother’s education None 20 33 53 61 110 Primary 27 52 79 45 120 Secondary+ 24 29 53 17 69 Wealth index quintile Poorest 24 43 67 40 104 Second 27 48 75 37 109 Middle 28 47 75 42 114 Fourth 25 54 78 49 123 Richest 26 37 64 30 92 Sex of child Male 29 51 80 41 117 Female 23 41 63 39 100 Total 26 47 73 41 110 [1] MICS indicator 1.3 [2] MICS indicator 1.4 [3] MICS indicator 1.2; MDG indicator 4.2 [4] MICS indicator 1.5 [5] MICS indicator 1.1; MDG indicator 4.1 17Child Mortality County Kisumu Migori Nyamira Siaya Homa Bay Kisii Residence Urban Rural Mother’s education None Primary Secondary + Wealth Index Quintiles Under five mortality rate Poorest 20% Richest 20% 20 105 167 130 123 60 52 92 111 110 120 69 104 92 40 80 100 120 140 160 180600 Figure CM.1 Under-5 mortality rates by background characteristics, Nyanza province, Kenya, 2011 18 Nutrition V. Nutrition Nutritional Status Children’s nutritional status is a reflection of their overall health. When children have access to an adequate food supply, are not exposed to repeated illness, and are well cared for, they reach their growth potential and are considered well nourished. Malnutrition is associated with more than half of all child deaths worldwide. Undernourished children are more likely to die from common childhood ailments, and for those who survive, have recurring sicknesses and faltering growth. Three-quarters of the children who die from causes related to malnutrition were only mildly or moderately malnourished – showing no outward sign of their vulnerability. The Millennium Development target is to reduce by half the proportion of people who suffer from hunger between 1990 and 2015. A reduction in the prevalence of malnutrition will also assist in the goal to reduce child mortality. In a well-nourished population, there is a reference distribution of height and weight for children under age five. Under-nourishment in a population can be gauged by comparing children to a reference population. The reference population used in this report is based on new WHO growth standards7. Each of the three nutritional status indicators can be expressed in standard deviation units (z-scores) from the median of the reference population. Weight-for-age is a measure of both acute and chronic malnutrition. Children whose weight-for-age is more than two standard deviations below the median of the reference population are considered moderately or severely underweight while those whose weight-for-age is more than three standard deviations below the median are classified as severely underweight. Height-for-age is a measure of linear growth. Children whose height-for-age is more than two standard deviations below the median of the reference population are considered short for their age and are classified as moderately or severely stunted. Those whose height-for-age is more than three standard deviations below the median are classified as severely stunted. Stunting is a reflection of chronic malnutrition as a result of failure to receive adequate nutrition over a long period and recurrent or chronic illness. Finally, children whose weight-for-height is more than two standard deviations below the median of the reference population are classified as moderately or severely wasted, while those who fall more than three standard deviations below the median are classified as severely wasted. Wasting is usually the result of a recent nutritional deficiency. The indicator may exhibit significant seasonal shifts associated with changes in the availability of food or disease prevalence. In Nyanza province MICS, weights and heights of all children under 5 years of age were measured using anthropometric equipment recommended by UNICEF (www.childinfo.org). Findings in this section are based on the results of these measurements. Table NU.1 shows percentages of children classified into each of these categories, based on the anthropometric measurements that were taken during fieldwork. Additionally, the table includes the percentage of children who are overweight, which takes into account those children whose weight for height is above 2 standard deviations from the median of the reference population, and mean z-scores for all three anthropometric indicators. 7 http://www.who.int/childgrowth/standards/second_set/technical_report_2.pdf 19Nutrition Ta b le N U .1 : N ut ri ti o na l s ta tu s o f ch ild re n P er ce nt ag e o f ch ild re n un d er a g e 5 b y nu tr it io na l s ta tu s ac co rd in g t o t hr ee a nt hr o p o m et ri c in d ic es : w ei g ht f o r ag e, h ei g ht f o r ag e, a nd w ei g ht f o r he ig ht , N ya nz a P ro vi nc e, K en ya , 2 01 1 W ei gh t fo r ag e H ei gh t fo r ag e W ei gh t fo r he ig ht U nd er w ei gh t S tu nt ed W as te d O ve rw ei gh t p er c en t b el ow M ea n Z -S co re N um b er o f c hi ld re n un d er a ge 5 p er c en t b el ow M ea n Z -S co re N um b er o f c hi ld re n un d er a ge 5 p er c en t b el ow p er c en t ab ov e M ea n Z -S co re N um b er o f c hi ld re n un d er a ge 5 - 2 S D [1 ] - 3 S D [2 ] (S D ) - 2 S D [3 ] - 3 S D [4 ] (S D ) - 2 S D [5 ] - 3 S D [6 ] + 2 S D (S D ) S ex M al e 15 .6 2. 9 -0 .9 24 76 28 .1 11 .5 -1 .3 24 76 4. 2 1. 0 3. 2 -0 .1 24 76 Fe m al e 14 .1 2. 5 -0 .7 23 95 26 .0 9. 6 -1 .1 23 95 3. 5 0. 3 3. 8 0. 0 23 95 C o un ty S ia ya 13 .6 3. 7 -0 .8 80 0 27 .7 10 .7 -1 .3 80 0 1. 4 0. 2 3. 2 0. 1 80 0 K is um u 14 .9 2. 4 -0 .7 82 3 23 .7 9. 4 -1 .0 82 3 4. 1 0. 5 4. 0 -0 .1 82 3 H om a B ay 15 .0 2. 2 -0 .7 83 6 26 .3 10 .7 -1 .1 83 6 4. 2 0. 8 2. 4 -0 .1 83 6 M ig or i 17 .1 2. 8 -0 .9 87 9 32 .3 13 .9 -1 .3 87 9 6. 4 1. 3 4. 8 -0 .1 87 9 K is ii 14 .7 2. 5 -0 .9 11 05 26 .3 9. 0 -1 .2 11 05 3. 4 0. 5 3. 4 -0 .1 11 05 N ya m ira 12 .9 2. 5 -0 .8 42 8 25 .0 9. 5 -1 .2 42 8 3. 4 0. 2 2. 9 -0 .1 42 8 R es id en ce U rb an 13 .6 1. 4 -0 .6 58 3 23 .2 9. 4 -1 .0 58 3 2. 9 0. 3 5. 8 0. 1 58 3 R ur al 15 .1 2. 9 -0 .8 42 88 27 .6 10 .7 -1 .2 42 88 4. 0 0. 7 3. 2 -0 .1 42 88 A g e 0- 5 m on th s 2. 1 .8 0. 4 43 7 2. 9 0. 6 -0 .1 43 7 5. 4 1. 7 9. 7 0. 4 43 7 6- 11 m on th s 14 .0 2. 8 -0 .6 51 4 13 .2 4. 3 -0 .6 51 4 7. 8 1. 1 5. 1 -0 .1 51 4 12 -2 3 m on th s 22 .2 4. 2 -1 .1 84 9 34 .7 12 .3 -1 .5 84 9 6. 9 1. 0 3. 6 -0 .3 84 9 24 -3 5 m on th s 18 .5 4. 3 -1 .0 10 33 31 .4 11 .8 -1 .3 10 33 2. 2 0. 4 2. 1 -0 .2 10 33 36 -4 7 m on th s 13 .8 1. 9 -0 .9 10 54 33 .4 13 .0 -1 .4 10 54 2. 2 0. 2 1. 7 -0 .1 10 54 48 -5 9 m on th s 12 .1 1. 3 -0 .9 98 3 27 .1 12 .8 -1 .3 98 3 2. 1 0. 3 3. 1 0. 0 98 3 M o th er ’s e d uc at io n N on e 10 .9 2. 6 -0 .6 31 9 17 .0 9. 6 -. 8 31 9 3. 2 0. 7 3. 4 0. 0 31 9 P rim ar y 16 .1 2. 9 -0 .9 34 05 29 .4 11 .2 -1 .3 34 05 4. 1 0. 7 3. 1 -0 .1 34 05 S ec on d ar y+ 12 .2 2. 0 -0 .7 11 45 22 .9 8. 7 -1 .0 11 45 3. 6 0. 3 4. 6 -0 .1 11 45 M is si ng /D K (* ) (* ) (* ) 3 (* ) (* ) (* ) 3 (* ) (* ) (* ) (* ) 3 W ea lt h in d ex q ui nt ile P oo re st 18 .6 4. 0 -1 .0 11 23 32 .7 13 .4 -1 .4 11 23 4. 8 0. 9 2. 7 -0 .2 11 23 S ec on d 16 .5 2. 9 -0 .9 10 24 28 .2 10 .2 -1 .3 10 24 4. 3 0. 8 3. 3 -0 .1 10 24 M id d le 13 .4 2. 3 -0 .8 96 3 26 .3 10 .5 -1 .2 96 3 3. 8 0. 5 3. 2 -0 .1 96 3 Fo ur th 14 .8 2. 4 -0 .8 91 5 26 .8 11 .1 -1 .2 91 5 3. 5 0. 7 2. 8 -0 .1 91 5 R ic he st 9. 9 1. 3 -0 .5 84 6 19 .3 6. 7 -0 .8 84 6 2. 6 0. 1 5. 8 0. 1 84 6 To ta l 14 .9 2. 7 -0 .8 48 71 27 .1 10 .6 -1 .2 48 71 3. 9 0. 6 3. 5 -0 .1 48 71 [1 ] M IC S in d ic at or 2 .1 a an d M D G in d ic at or 1 .8 , [2 ] M IC S in d ic at or 2 .1 b , [3 ] M IC S in d ic at or 2 .2 a, [ 4] M IC S in d ic at or 2 .2 b , [5 ] M IC S in d ic at or 2 .3 a, [ 6] M IC S in d ic at or 2 .3 b 20 Children whose full birth date (month and year) were not obtained, and children whose measurements are outside a plausible range are excluded from Table NU.1. Children are excluded from one or more of the anthropometric indicators when their weights and heights have not been measured, whichever applicable. For example if a child has been weighed but his/her height has not been measured, the child is included in underweight calculations, but not in the calculations for stunting and wasting. Percentages of children by age and reasons for exclusion are shown in the data quality tables DQ.6 and DQ.7. Overall 98% of children had both their weights and heights measured (Table DQ.6), with 2% and 2.3% of children being excluded due to weight and height measurements not being available or out of the acceptable ranges. Table DQ.7 shows that due to incomplete dates of birth, implausible measurements, and missing weight and/or height, 2.5 per cent of children have been excluded from calculations of the weight-for-age indicator, while the figures are 3.0% for the height-for-age indicator, and 2.8% for the weight-for-height indicator. About 15 per cent of children under age five in Nyanza province are moderately or severely underweight and 3% per cent are classified as severely underweight (Table NU.1). More than a quarter of children (27% per cent) are moderately or severely stunted or too short for their age and 4 per cent are moderately or severely wasted or too thin for their height. The prevalence of stunting is 26 per cent in female children and 28 per cent in male children whereas it is 23 per cent in children living in urban areas of Nyanza and 26 per cent in children living in the rural areas. It is also of interest to note that malnutrition levels decline with increasing levels of the wealth index. For example, 33 per cent of children from the poorest wealth index are moderately or severely stunted compared to 19 per cent among those from richest wealth index households. This pattern is also true for underweight indicators where 19% of children from the poorest wealth quintile are moderately or severely underweight compared to 10 per cent among those from the richest households. Figure NU.1: Percentage of children under age 5 who are underweight, stunted and wasted, Nyanza Province, Kenya, 2011 Nutrition Underweight Stunted Wasted P er c en t 0 0 6 12 18 24 30 36 42 48 54 60 5 10 15 20 25 30 35 40 Age in months 21Nutrition Among the 6 counties, the underweight prevalence ranged from 13 per cent to 17 per cent. The prevalance of stunting ranged from 24 to 32 per cent while wasting ranged from 1 per cent to 6 per cent. Moderate or severe underweight prevalence ranged from 11 and 12 per cent among children with mothers having no education and secondary education or higher to 16 per cent among those with mothers having primary level education. This pattern is expected and is related to the age at which many children cease to be breastfed and are exposed to contamination in water, food, and environment. Overweight prevalence is low across the entire province (3.5%), and ranged from 3% among children from the poorest households to 6 per cent among children from the richest households (Table NU.1). Breastfeeding and Infant and Young Child Feeding Breastfeeding for the first few years of life protects children from infection, provides an ideal source of nutrients, and is economical and safe. However, many mothers stop breastfeeding too soon and there are often pressures to switch to infant formula, which can contribute to growth faltering and micronutrient malnutrition and is unsafe if clean water is not readily available. The World Fit for Children goal states that children should be exclusively breastfed for 6 months and continue to be breastfed with safe, appropriate and adequate complementary feeding for up to 2 years of age and beyond. WHO/UNICEF have the following feeding recommendations: • Exclusive breastfeeding for first six months • Continued breastfeeding for two years or more • Safe, appropriate and adequate complementary foods beginning at 6 months • Frequency of complementary feeding: 2 times per day for 6-8 month olds; 3 times per day for 9-11 month olds It is also recommended that breastfeeding be initiated within one hour of birth. This is to ensure that the colostrum available in the first breast milk received by the child. The indicators related to recommended child feeding practices are as follows: • Early initiation of breastfeeding (within 1 hour of birth) • Exclusive breastfeeding rate (< 6 months) • Predominant breastfeeding (< 6 months) • Continued breastfeeding rate (at 1 year and at 2 years) • Duration of breastfeeding • Age-appropriate breastfeeding (0-23 months) • Introduction of solid, semi-solid and soft foods (6-8 months) • Minimum meal frequency (6-23 months) • Milk feeding frequency for non-breastfeeding children (6-23 months) • Bottle feeding (0-23 months) 22 Table NU.2: Initial breastfeeding Percentage of last-born children in the 2 years preceding the survey who were ever breastfed, percentage who were breastfed within one hour of birth and within one day of birth, Nyanza Province, Kenya, 2011 Percentage who were ever breastfed [1] Percentage who were first breastfed: Number of last-born children in the two years preceding the survey Within one hour of birth [2] Within one day of birth County Siaya 96.0 33.2 81.5 318 Kisumu 97.1 43.1 88.9 318 Homa Bay 97.7 41.3 89.0 316 Migori 96.2 39.6 87.6 326 Kisii 96.2 47.9 82.4 370 Nyamira 94.6 40.5 80.2 164 Residence Urban 96.3 49 88.5 240 Rural 96.4 40 84.8 1572 Months since birth 0-11 months 97.7 41.8 86.3 946 12-23 months 96.6 41.1 85.5 802 Assistance at delivery Skilled attendant 98.3 46.9 88.3 1008 Traditional birth attendant 97.8 35.5 86.9 400 Other 90.3 31.9 74.9 280 No attendant 90.5 33.4 78.9 124 Place of delivery Public sector health facility 98.5 49.0 88.8 711 Private sector health facility 98.4 42.5 86.6 244 Home 97.6 35.0 85.3 779 Other 59.6 27.2 49.1 78 Mother’s education None 94.8 41.7 83.9 89 Primary 96.8 39.5 85.5 1287 Secondary+ 95.7 46.0 85.0 436 Wealth index quintile Poorest 95.3 34.8 81.1 415 Second 96.2 35.8 84.6 355 Middle 99.3 43.6 88.7 354 Fourth 96.9 47.4 88.5 345 Richest 94.5 45.5 84.3 341 Total 96.4 41.2 85.3 1812 [1] MICS indicator 2.4 [2] MICS indicator 2.5 Nutrition 23Nutrition Table NU.2 provides the proportion of children born in the last two years who were ever breastfed, those who were first breastfed within one hour and one day of birth. Although a very important step in management of lactation and establishment of a physical and emotional relationship between the baby and the mother, only 41 per cent of babies were breastfed for the first time within one hour of birth, while 85 per cent of newborns in Nyanza province start breastfeeding within one day of birth. The proportion of newborns of mothers with secondary or higher level of education who receives first breast milk within one hour of birth is 46 per cent, while it is 42 per cent for those with mothers with no education. 84 per cent of mothers with no education and 85 per cent of mothers by secondary education or higher breast fed their newborn children within the first day of birth. Almost one in two mothers in urban areas breastfeed within an hour of birth (49 per cent) while the corresponding figure is 40 per cent for those from rural areas. At the regional level, breastfeeding within one hour ranges from 33 per cent in Siaya County to 48 per cent in Kisii County. Figure NU.2 Percentage of mothers who started breastfeeding within one hour and within one day of birth, Nyanza, Kenya, 2011 81.5 88.9 89.0 87.6 82.4 80.2 88.5 84.8 85.3 33.2 43.1 41.3 39.6 47.9 40.5 49 40 41.2 80 70 60 50 40 30 20 10 Within one day P er c en t Within one hour 0 Si ay a Ki su m u H om a B ay M ig or i Ki si i N ya m ira U rb an R ur al N ya nz a 90 100 In Table NU.3, breastfeeding status is based on the reports of mothers/caretakers of children’s consumption of food and fluids in the 24 hours prior to the interview. Exclusively breastfed refers to infants who received only breast milk (and vitamins, mineral supplements, or medicine). The table shows exclusive breastfeeding of infants during the first six months of life, as well as continued breastfeeding of children at 12-15 and 20-23 months of age. 24 Table NU.3: Breastfeeding Percentage of living children according to breastfeeding status at selected age groups, Nyanza Province, Kenya, 2011 Children age 0-5 months Children age 12-15 months Children age 20-23 months Per cent exclusively breastfed [1] Per cent predominantly breastfed [2] Number of children Per cent breastfed (Continued breastfeeding at 1 year) [3] Number of children Per cent breastfed (Continued breastfeeding at 2 years) [4] Number of children Sex Male 34.2 49.1 238 81.6 175 35.5 140 Female 37.4 55.2 242 83.0 133 52.3 140 County Siaya 28.7 42.9 100 (83.4) 45 (52.5) 50 Kisumu 38.5 58.1 84 (83.1) 50 (39.7) 46 Homa Bay 35.0 53.8 88 80.7 63 (36.8) 48 Migori 35.6 56.3 73 78.9 49 50.5 55 Kisii 41.6 55.6 88 83.4 72 (41.2) 54 Nyamira (37.1) (45.8) 47 (84.9) 30 (39.7) 27 Residence Urban (46.2) (57.1) 55 (63.9) 28 (48.6) 45 Rural 34.5 51.6 425 84.1 280 43.0 235 Mother’s education None (48.0) (55.7) 28 (*) 21 (*) 20 Primary 35.4 52.4 334 82.8 217 44.9 193 Secondary+ 34.2 50.7 118 82.5 70 37.6 67 Wealth index quintile Poorest 38.2 51.6 112 86.4 57 42.5 62 Second 28.0 41.0 80 89.4 77 41.1 53 Middle 35.1 57.9 100 79.5 65 40.6 54 Fourth 30.6 53.1 86 80.9 59 (40.1) 49 Richest 44.5 55.2 102 71.8 51 53.6 62 Total 35.8 52.2 480 82.2 309 43.9 280 [1] MICS indicator 2.6 [2] MICS indicator 2.9 [3] MICS indicator 2.7 [4] MICS indicator 2.8 (*) Not shown, based on less than 25 unweighted cases. ( ) Based on 25-49 unweighted cases Approximately 36 per cent of children aged less than six months are exclusively breastfed, a level considerably lower than recommended. By age 12-15 months, 82 per cent of children are still being breastfed and by age 20-23 months, 44 per cent are still breastfed. Continued breastfeeding at 2 years ranges from 36 per cent among boys to 52 per cent among girls (Table NU.3). Different criteria of adequate feeding are used depending on the age of the child. For infants aged 0-5 months, exclusive breastfeeding is considered as adequate feeding. Infants aged 6-8 months are considered to be adequately fed if they are receiving breast milk and complementary food at least two times per day, while infants aged 9-11 months are considered to be adequately fed if they are receiving breast milk and eating complementary food at least three times a day. Nutrition 25Nutrition Figure NU.3 shows the detailed pattern of breastfeeding by the child’s age in months. This figure is obtained by using data from Table NU.A1. Even at the earliest ages i.e before 6 months, the majority of children are receiving liquids or foods other than breast milk. By the end of the fourth month, the percentage of children exclusively breastfed is below 30 per cent. Only about 36 per cent of children are being breastfed by the age of 22-23 months. Figure NU.3 Infant feeding patterns by age: Percentage distribution of children aged under 2 years by feeding pattern by age group, Nyanza province, Kenya, 2011 Table NU.4 shows the median duration of breastfeeding by selected background characteristics. Among children under age 3, the median duration is 20.5 months for any breastfeeding, 1.3 months for exclusive breastfeeding, and 2.7 months for predominant breastfeeding. Median duration of exclusive breastfeeding is higher among women with no education (2.4 months) compared to those with secondary or higher education (0.6 months). In contrast, duration of any breastfeeding is comparable across all women irrespective of the education level. Median duration of any breastfeeding for women from rural areas is 20.4 while that for those from urban areas is 21.1 months. Age (in Months) P er c en t 0- 1 8- 9 16 -1 7 2- 3 10 -1 1 18 -1 9 4- 5 12 -1 3 20 -2 1 6- 7 14 -1 5 22 -2 3 0 10 20 30 40 50 60 70 80 90 100 Weaned (not breastfed) Breastfed and complementary food Breastfed and other milk/formula Breastfed and non-milk liquids Breastfed and plain water only Exclusively breastfed 26 Table NU.4: Duration of breastfeeding Median duration of any breastfeeding, exclusive breastfeeding, and predominant breastfeeding among children age 0-35 months, Nyanza Province, Kenya, 2011 Median duration (in months) of Number of children age 0-35 monthsAny breastfeeding [1] Exclusive breastfeeding Predominant breastfeeding Sex Male 19.2 1.4 2.5 1465 Female 21.3 1.1 3.0 1453 County Siaya 21.7 0.7 2.1 492 Kisumu 21.0 1.1 3.2 502 Homa Bay 19.5 1.8 2.9 512 Migori 21.0 1.6 3.3 522 Kisii 19.2 0.7 3.0 635 Nyamira 20.8 1.8 2.3 253 Residence Urban 21.1 1.9 3.4 369 Rural 20.4 1.2 2.6 2548 Mother’s education None 20.7 2.4 3.1 171 Primary 20.6 1.5 2.7 2033 Secondary+ 20.0 0.6 2.6 713 Wealth index quintile Poorest 18.8 1.7 2.6 677 Second 20.8 0.7 2.1 584 Middle 20.3 1.1 3.1 557 Fourth 20.7 0.9 2.8 561 Richest 21.5 1.9 3.1 537 Median 20.5 1.3 2.7 2917 Mean for all children (0-35 months) 20.0 2.2 3.6 2917 [1] MICS indicator 2.10 The adequacy of infant feeding in children under 24 months is provided in Table NU.5. Different criteria of adequate feeding are used depending on the age of the child. For infants age 0–5 months, exclusive breastfeeding is considered as adequate feeding, while infants age 6–23 months are considered to be adequately fed if they are receiving breastmilk and solid, semi-solid or soft food (breastfeeding is recommended to be continued up to 24 months of age or beyond). The results show that most children are not fed in the appropriate way. About one third of children less than six months (36 per cent) are exclusively breastfed. From six months of age, complementary feeding is to be introduced while breastfeeding continues. However, about 59 per cent of children of children 6–23 months were receiving complementary foods and breastmilk at the same time. Overall, only about 53 per cent of children of children 0–23 months are appropriately breastfeed. Appropriate breastfeeding of infants aged 0-23 months ranges from 42 per cent in Kisumu county to 61 per cent in Nyamira county. Nutrition 27Nutrition Table NU.5: Age-appropriate breastfeeding Percentage of children age 0-23 months who were appropriately breastfed during the previous day, Nyanza Province, Kenya, 2011 Children age 0-5 months Children age 6-23 months Children age 0-23 months Per cent exclusively breastfed [1] Number of children Per cent currently breastfeeding and receiving solid, semi-solid or soft foods Number of children Per cent appropriately breastfed [2] Number of children Sex Male 34.2 238 58.3 698 52.2 936 Female 37.4 242 60.4 692 54.4 934 County Siaya 28.7 100 64.7 240 54.1 340 Kisumu 38.5 84 42.9 237 41.7 320 Homa Bay 35.0 88 55.2 252 50.0 340 Migori 35.6 73 62.6 249 56.4 322 Kisii 41.6 88 64.5 297 59.2 385 Nyamira (37.1) 47 71.1 116 61.3 163 Residence Urban 46.2 55 52.2 174 50.7 230 Rural 34.5 425 60.4 1216 53.7 1641 Mother’s education None (48.0) 28 54.8 72 52.9 100 Primary 35.4 334 59.2 988 53.2 1322 Secondary+ 34.2 118 60.7 330 53.7 448 Wealth index quintile Poorest 38.2 112 57.5 324 52.5 436 Second 28.0 80 64.4 282 56.4 362 Middle 35.1 100 60.7 278 53.9 378 Fourth 30.6 86 59.1 265 52.1 351 Richest 44.5 102 54.7 242 51.7 343 Total 35.8 480 59.4 1390 53.3 1870 [1] MICS indicator 2.6 [2] MICS indicator 2.14 ( ) Based on 25-49 unweighted cases Adequate complementary feeding of children from 6 months to two years of age is particularly important for growth and development and the prevention of under-nutrition. Continued breastfeeding beyond six months should be accompanied by consumption of nutritionally adequate, safe and appropriate complementary foods that help meet nutritional requirements when breast milk is no longer sufficient. This requires that for breastfed children, two or more meals of solid, semi-solid or soft foods are needed if they are six to eight months old, and three or more meals if they are 9-23 months of age. For children 6-23 months and older who are not breastfed, four or more meals of solid, semi-solid or soft foods or milk feeds are needed. Overall, 57 per cent of infants age 6-8 months received solid, semi-solid, or soft foods during the previous day (Table NU.6). Among currently breastfeeding infants this percentage is 56 while only a few infants in this age-range were not currently breastfeeding. There are no major variations in the proportions of 6-8 months who received solid, semi-solid or soft foods during the previous day, by gender. 28 Table NU.6: 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, Nyanza Province, Kenya, 2011 Currently breastfeeding Currently not breastfeeding All Per cent receiving solid, semi-solid or soft foods Number of children age 6-8 months Per cent receiving solid, semi-solid or soft foods Number of children age 6-8 months Per cent receiving solid, semi-solid or soft foods [1] Number of children age 6-8 months Sex Male 54.7 127 (*) 4 56.3 132 Female 56.9 125 (*) 4 57.2 130 Residence Urban (38.8) 34 - 0 (38.8) 34 Rural 58.4 219 (*) 8 59.4 228 Total 55.8 253 (*) 8 56.7 262 [1] MICS indicator 2.12 (*) Not shown, based on less than 25 unweighted cases. ( ) Based on 25-49 unweighted cases Table NU.7 presents the proportion of children age 6-23 months who received semi-solid or soft foods the minimum number of times or more during the previous day according to breastfeeding status (see the note in Table NU.7 for a definition of minimum number of times for different age groups). Overall, about one-third of the children age 6-23 months (32 per cent) were receiving solid, semi-solid and soft foods the minimum number of times. The proportion of females enjoying the minimum meal frequency is 31 per cent while for males it is 33 per cent. The minimum meal frequency proportion ranges from in 18 per cent in Kisumu County - a more urbanized County- to 40 per cent in Nyamira and 43 per cent in Migori County. Nutrition 29Nutrition Table NU.7: Minimum meal frequency Percentage of children age 6-23 months who received solid, semi-solid, or soft foods (and milk feeds for non-breastfeeding children) the minimum number of times or more during the previous day, according to breastfeeding status, Nyanza Province, Kenya, 2011 Currently breastfeeding Currently not breastfeeding All Per cent receiving solid, semi- solid and soft foods the minimum number of times Number of children age 6-23 months Per cent receiving at least 2 milk feeds [1] Per cent receiving solid, semi- solid and soft foods or milk feeds 4 times or more Number of children age 6-23 months Per cent with minimum meal frequency [2] Number of children age 6-23 months County Siaya 34.1 188 25.6 35.9 52 34.5 240 Kisumu 19.8 181 13.5 10.4 56 17.6 237 Homa Bay 26.2 184 18.9 29.0 68 27.0 252 Migori 40.7 193 45.7 50.3 56 42.8 249 Kisii 32.9 219 26.1 38.4 78 34.4 297 Nyamira 38.9 86 (37.9) (45.0) 30 40.4 116 Sex Male 33.2 514 25.0 32.5 184 33.0 698 Female 30.1 538 28.9 36.0 154 31.4 692 Age 6-8 months 41.4 253 (*) (*) 9 41.8 262 9-11 months 28.2 242 (*) (*) 18 28.4 261 12-17 months 25.5 343 26.0 42.3 98 29.3 441 18-23 months 33.6 214 26.2 29.8 213 31.7 427 Area Rural 31.3 923 24.3 34.1 293 32.0 1216 Urban 33.7 129 (42.7) (33.6) 45 33.7 174 Mother’s education None (38.9) 49 (54.0) (45.7) 24 41.1 72 Primary 31.6 754 22.9 31.2 234 31.5 988 Secondary+ 30.1 249 30.0 39.1 81 32.3 330 Wealth index quintiles Poorest 26.9 240 15.0 28.2 84 27.3 324 Second 29.4 222 18.1 25.3 60 28.5 282 Middle 36.5 208 34.1 39.0 70 37.1 278 Fourth 32.6 205 31.6 49.0 60 36.3 265 Richest 33.9 177 37.8 30.7 65 33.0 242 Total 31.6 1052 26.8 34.1 339 32.2 1390 1] MICS indicator 2.15 [2] MICS indicator 2.13 (*) Not shown based on less than 25 unweighted case. ( ) Based on 25-49 unweighted cases 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.8 shows that bottle-feeding is still prevalent in Nyanza province. About one in ten children under 24 months are fed using a bottle with a nipple. 30 Table NU.8: Bottle feeding Percentage of children age 0-23 months who were fed with a bottle with a nipple during the previous day, Nyanza Province, Kenya, 2011 Percentage of children age 0-23 months fed with a bottle with a nipple [1] Number of children age 0-23 months County Siaya 10.5 340 Kisumu 11.8 320 Homa Bay 12.5 340 Migori 21.0 322 Kisii 5.1 385 Nyamira 9.0 163 Sex Male 11.4 936 Female 11.9 934 Age 0-5 months 13.7 480 6-11 months 14.5 522 12-23 months 8.8 868 Area Rural 11.4 1641 Urban 13.8 230 Mother’s education None 15.6 100 Primary 11.0 1322 Secondary+ 12.7 448 Wealth index quintiles Poorest 10.2 436 Second 9.6 362 Middle 12.5 378 Fourth 11.4 351 Richest 15.1 343 Total 11.7 1870 [1] MICS indicator 2.11 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 international goal is to achieve sustainable elimination of iodine deficiency by 2005. The indicator is the percentage of households consuming adequately iodized salt (>15 parts per million). In Kenya, the nutrition program in the Ministry of Public Health shares responsibility with the Kenya Bureau of Standards, for regulation of iodized salt and for managing the national salt iodization program. A national committee, headed by the MOPH, deals with iodine, iron, and vitamin A, and works with WHO, UNICEF, salt producers, and others. Recommendations by the MOPH for increasing compliance with the iodine contents include more training for district mid-level health officers and the operational staff, IEC for iodized salt, monitoring of salt for iodine content, and utilization of the national laboratory for urinary iodines. Nutrition 31Nutrition Table NU.9: Iodized salt consumption Percentage distribution of households by consumption of iodized salt, Nyanza Province, Kenya, 2011 Percentage of households in which salt was tested Number of households Percent of households with Number of households in which salt was tested or with no saltNo salt Salt test result Not iodized 0 PPM >0 and <15 PPM 15+ PPM [1] Total County Siaya 90.0 1209 9.1 0.2 3.4 87.3 100.0 1197 Kisumu 88.9 1261 8.6 0.2 1.0 90.3 100.0 1226 Homa Bay 82.0 1089 15.8 0.0 0.7 83.5 100.0 1061 Migori 92.4 1128 7.1 0.1 1.7 91.2 100.0 1121 Kisii 87.6 1483 10.7 0.6 1.0 87.6 100.0 1455 Nyamira 81.6 657 17.2 1.0 0.8 81.0 100.0 648 Residence Urban 89.6 1077 8.8 0.1 1.5 89.5 100.0 1059 Rural 87.2 5751 11.2 0.3 1.5 87.0 100.0 5649 Wealth index quintile Poorest 83.8 1347 14.7 0.2 1.5 83.6 100.0 1323 Second 86.9 1311 11.5 0.7 1.4 86.3 100.0 1288 Middle 88.2 1319 10.5 0.3 1.8 87.4 100.0 1300 Fourth 89.6 1340 8.6 0.2 1.3 90.0 100.0 1313 Richest 89.2 1510 9.2 0.2 1.4 89.3 100.0 1483 Total 87.6 6828 10.9 0.3 1.5 87.4 100.0 6708 [1] MICS indicator 2.16 During the 2011 Nyanza MICS survey, in about 88 per cent of households, the 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.9 shows that in about one out of ten households (11 per cent), there was no salt available. In 87 per cent of households, salt was found to contain 15 parts per million (ppm) or more of iodine. Use of iodized salt ranges from 81 per cent in Nyamira County and 84 per cent in Homa Bay County to 91 per cent in Migori County. A majority of households from both rural and urban areas were found to be using adequately iodized salt (90 per cent in urban households and 87 per cent in rural areas. Similarly, iodized salt consumption ranges from 84 per cent among poorest households to 90 and 89 per cent among households in the fourth and richest wealth quintiles, (Figure NU.4). Figure NU.4 Percentage of households consuming adequately iodized salt, Nyanza Province, Kenya, 2011 80 88 84 92 82 90 86 P er c en t RegionsWealth Total Po or es t Se co nd M id dl e Fo ur th R ic he st U rb an R ur al N ya nz a 83.6 86.3 87.4 90 89.3 89.5 87 87.4 32 Children’s Vitamin A Supplementation Vitamin A is essential for eye health and proper functioning of the immune system. It is found in foods such as milk, liver, eggs, red and orange fruits, red palm oil and green leafy vegetables, although the amount of vitamin A readily available to the body from these sources varies widely. In developing areas of the world, where vitamin A is largely consumed in the form of fruits and vegetables, daily per capita intake is often insufficient to meet dietary requirements. Inadequate intakes are further compromised by increased requirements for the vitamin as children grow or during periods of illness, as well as increased losses during common childhood infections. As a result, vitamin A deficiency is quite prevalent in the developing world and particularly in countries with the highest burden of under-five deaths. The 1990 World Summit for Children set the goal of virtual elimination of vitamin A deficiency and its consequences, including blindness, by the year 2000. This goal was also endorsed at the Policy Conference on Ending Hidden Hunger in 1991, the 1992 International Conference on Nutrition, and the UN General Assembly’s Special Session on Children in 2002. The critical role of vitamin A for child health and immune function also makes control of deficiency a primary component of child survival efforts, and therefore critical to the achievement of the fourth Millennium Development Goal: a two-thirds reduction in under-five mortality by the year 2015. For countries with vitamin A deficiency problems, current international recommendations call for high- dose vitamin A supplementation every four to six months, targeted to all children between the ages of six to 59 months living in affected areas. Providing young children with two high-dose vitamin A capsules a year is a safe, cost-effective, efficient strategy for eliminating vitamin A deficiency and improving child survival. Giving vitamin A to new mothers who are breastfeeding helps protect their children during the first months of life and helps to replenish the mother’s stores of vitamin A, which are depleted during pregnancy and lactation. For countries with vitamin A supplementation programs, the definition of the indicator is the per cent of children 6-59 months of age receiving at least one high dose vitamin A supplement in the last six months. Undernutrition is associated with widespread micronutrient deficiencies. Although recent data are not available, it is likely that iodine deficiency disorders are still prevalent. The national salt iodisation programme needs to be evaluated. Vitamin A deficiency and iron deficiency anaemia are both highly prevalent in the country. The implementation of supplementation in vitamin A and iron is still insufficient. More long-term strategies are needed such as fortification, dietary diversification and nutritional education. Based on UNICEF/WHO guidelines, the Kenya Ministry of Public Health recommends that children aged 6-11 months be given one high dose Vitamin A capsules and children aged 12-59 months given a vitamin A capsule every 6 months. In some parts of the country, Vitamin A capsules administration are linked to immunization services and are given when the child has contact with these services after six months of age. It is also recommended that mothers take a Vitamin A supplement within eight weeks of giving birth due to increased Vitamin A requirements during pregnancy and lactation. Table NU.10 shows children’s vitamin A supplementation by selected background characteristics such as sex and age of child, mother’s education, and household’s wealth index. Within the six months prior to the survey, 47 per cent of children aged 6-59 months received a high dose Vitamin A supplement. The proportion of female children receiving Vitamin A supplementation within last six months at 48 per cent is comparable with male children (47 per cent). There is a consistent decline in Vitamin A supplementation with the age of children within the 6 months window prior to the survey. For example, supplementation in the last six months declines from 74 per cent among children aged 6-11 months to 38 per cent among children aged 48-59 months. The differentials by household wealth index show no clear variation with Vitamin A supplementation coverage. For example, 46 per cent of children from poorest wealth index households received Vitamin A supplementation compared to 52 and 46 per cent among those from the Nutrition 33Nutrition fourth and richest wealth index households. At the county levels, Vitamin A supplementation coverage during the last 6 months ranges from 39 per cent in Nyamira County to 59 per cent in Siaya County. Table NU.10: Children’s vitamin A supplementation Per cent distribution of children age 6-59 months by receipt of a high dose vitamin A supplement in the last 6 and 12 months, Nyanza Province, Kenya, 2011 Percentage who received Vitamin A according to: Percentage of children who received Vitamin A during the last 6 months [1] Number of children age 6-59 months Child health book/ card/vaccination card in last 12 months Child health book/card/ vaccination card in last 6 months Mother’s report any time prior to 12 months Mother’s report less than 6 months County Siaya 7.2 5.7 69.0 58.1 58.6 710 Kisumu 7.2 4.2 53.3 43.2 43.6 777 Homa Bay 6.8 3.8 49.1 40.4 41.7 780 Migori 3.9 2.1 60.4 50.4 50.9 857 Kisii 6.6 4.2 55.4 46.4 46.9 1046 Nyamira 11.3 7.5 49.6 37.9 39.4 395 Sex Male 6.7 4.3 56.3 46.2 46.7 2321 Female 6.8 4.2 56.8 47.1 48.1 2244 Area Rural 6.5 4.1 56.5 46.8 47.5 4004 Urban 8.7 5.3 56.2 45.6 46.6 561 Age 6-11 17.5 16.5 77.2 72.8 74.1 522 12-23 15.4 7.6 71.6 52.0 53.8 868 24-35 4.6 2.5 52.1 42.8 43.6 1047 36-47 2.1 1.0 49.8 41.7 42.0 1094 48-59 1.1 0.6 44.9 38.0 38.1 1034 Mother’s education None 6.3 4.3 47.2 37.6 37.9 317 Primary 5.8 3.8 56.2 46.9 47.5 3189 Secondary+ 9.8 5.7 60.3 48.8 49.9 1056 Missing/DK (*) (*) (*) (*) (*) 3 Wealth index quintiles Poorest 5.6 3.6 54.1 44.9 45.7 1056 Second 5.6 3.9 55.0 46.2 47.1 974 Middle 6.2 2.9 56.9 46.9 47.2 885 Fourth 7.4 5.1 61.6 50.8 51.6 857 Richest 9.6 6.1 55.5 44.8 45.6 793 Total 6.7 4.3 56.5 46.6 47.4 4565 [1] MICS indicator 2.17 (*) Not shown based on less than 25 unweighted case. The mother’s level of education is also related to the likelihood of Vitamin A supplementation. The percentage receiving a supplement in the last six months [increases] from 38 per cent among children whose mothers have no education to 48 per cent of those whose mothers have primary education and 50 per cent among children of mothers with secondary or higher education. 34 Low Birth Weight 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. Low birth weight (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 months and years. Those who survive 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 underweight also tend to have 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 the 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 the risk of bearing underweight babies. One of the major challenges in measuring the incidence of low birth weight is the fact that more than half of infants in the developing world are not weighed. 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 new-borns are not delivered in facilities, and those who are represent only a selected sample of all births. Because 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 2500 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 birth8. Table NU.11 shows the incidence of low birth weight infants by County, residence, the education level of mother, and household wealth index. Overall, 59 per cent of births were weighed at birth and 5.4 per cent of infants weighed less than 2500 grams at birth. A higher proportion of children born to mothers who reside in urban areas were weighed at birth (80 per cent) compared with those born to mothers from rural areas (56 per cent). There is a noticeable increasing trend in the proportion of children weighed at birth with increase in the wealth index. For example, 42 per cent of the children from the poorest wealth index category were weighed at birth, compared to 77 per cent among those from the richest household wealth index category (Table NU.11). 8 For a detailed description of the methodology, see Boerma, J. T., Weinstein, K. I., Rutstein, S.O., and Sommerfelt, A. E. , 1996. Data on Birth Weight in Developing Countries: Can Surveys Help? Bulletin of the World Health Organization, 74(2), 209-16. NutritionNutrition 35 Table NU.11: Low birth weight infants Percentage of last-born children in the 2 years preceding the survey that are estimated to have weighed below 2500 grams at birth and percentage of live births weighed at birth, Nyanza Province, Kenya, 2011 Percentage of live births: Number of live births in the last 2 yearsBelow 2500 grams [1] Weighed at birth [2] County Siaya 5.6 53.8 318 Kisumu 6.4 71.5 318 Homa Bay 5.1 45.8 316 Migori 4.4 57.1 326 Kisii 4.7 59.3 370 Nyamira 7.2 71.0 164 Residence Urban 6.1 80.2 240 Rural 5.3 55.5 1572 Mother’s education None 6.1 72.3 89 Primary 5.3 52.6 1287 Secondary+ 5.6 74.2 436 Wealth index quintile Poorest 5.4 42.4 415 Second 4.4 52.7 355 Middle 5.1 59.8 354 Fourth 5.7 65.8 345 Richest 6.4 76.8 341 Total 5.4 58.8 1812 [1] MICS indicator 2.18 [2] MICS indicator 2.19 There was significant variation in the proportions of live births weighed at birth by County regions, as well as the proportions of those who weighed below 2500 grams at birth. In Kisumu and Nyamira counties, more than 70 per cent of children were weighed at birth, compared to only 46 per cent and 54 per cent in Homa Bay and Siaya counties. 36 Nutrition Figure NU.5 Percentage of infants weighing less than 2500 grams at birth, Nyanza Province, Kenya, 2011 .0 4.0 2.0 6.0 7.0 8.0 1.0 5.0 3.0 P er c en t County Total Si ay a Ki su m u H om a B ay M ig or i Ki si i N ya m ira N ya nz a 5.6 6.4 5.1 4.4 4.7 7.2 5.4 37 VI. Child Health Vaccinations The fourth Millennium Development Goal (MDG) is to reduce child mortality by two thirds between 1990 and 2015. Immunization plays a key part in this goal. Immunizations have saved the lives of millions of children in the three decades since the launch of the Expanded Programme on Immunization (EPI) in 1974. Worldwide there are still 27 million children overlooked by routine immunization and as a result, vaccine-preventable diseases cause more than 2 million deaths every year. A World Fit for Children goal is to ensure full immunization of children under one year of age at 90 per cent nationally, with at least 80 per cent coverage in every district or equivalent administrative unit. The Kenya Expanded Programme on Immunizations (KEPI) and the Malezi Bora campaigns are playing key roles in this regard. The Kenya National Expanded Programme on Immunization (KEPI) recommends that a child should receive a BCG vaccination to protect against tuberculosis, three doses of DPT-HeB-Hib (Pentavalent) vaccine to protect against diphtheria, pertussis, tetanus, Hepatitis B and invasive Hemophilus influenzae type B disease, four doses of polio vaccine and a single dose of measles vaccine by the age of 9 months. In the Nyanza province MICS Survey, mothers or care givers of children below five years of age were asked to provide vaccination cards and interviewers copied vaccination information from the cards onto the questionnaire. However, information about children with no immunization card was obtained using a set of structured direct questions on immunization. The immunization coverage shown in this report includes information from card as well as re-call, unless mentioned other-wise. Overall, 77 per cent of children 12-23 months had health cards (Table CH.2). If the child did not have a card, the mother was asked to recall whether or not the child had received each of the vaccinations and, for DPT and Polio, how many times. The percentage of children age 12 to 23 months who received each of the vaccinations is shown in Table CH.1. The denominator for the table is children age 12- 23 months so that only children who are old enough to be fully vaccinated are counted. In the first three columns, the numerator includes all children who were vaccinated at any time before the survey according to the vaccination card or the mother’s report. In the last column, only those who were vaccinated before their first birthday, as recommended, are included. For children without vaccination cards, the proportion of vaccinations given before the first birthday is assumed to be the same as for children with vaccination cards. Child Health 38 Table CH.1: Vaccinations in first year of life Percentage of children age 12-23 months immunized against childhood diseases at any time before the survey and before the first birthday, Nyanza Province, Kenya, 2011 Vaccinated at any time before the survey according to Vaccinated by 12 months of ageVaccination card Mother’s report Either BCG [1] 76.5 21.1 97.6 97.2 Polio At birth 73.8 17.2 91.0 90.7 1 76.3 20.4 96.7 96.2 2 76.1 15.8 91.8 91.4 3 [2] 74.3 10.1 84.4 83.3 DPT 1 76.9 20.2 97.1 96.0 2 76.9 18.3 95.2 94.5 3 [3] 76.9 14.2 91.1 90.0 Measles [4] 75.9 19.4 95.3 89.1 All vaccinations 77.2 1.2 78.3 70.3 No vaccinations 0.0 1.6 1.6 1.6 Yellow fever [6] 76.9 7.7 84.6 79.1 Number of children age 12-23 months 868 868 868 868 [1] MICS indicator 3.1; [2] MICS indicator 3.2; [3] MICS indicator 3.3; [4] MICS indicator 3.4; MDG indicator 4.3; [6] MICS indicator 3.6 Approximately 97 per cent of children age 12-23 months received a BCG vaccination by the age of 12 months and the first dose of DPT was given to 96 per cent. The percentage declines for subsequent doses of DPT to 95 per cent for the second dose, and 90 per cent for the third dose (Figure CH.1). Similarly, 96 per cent of children received Polio 1 by age 12 months and this declines to 83 per cent by the third dose. The coverage for measles vaccine by 12 months was at 89 per cent. This is primarily because, although 95 per cent of children received the vaccine, a good number don’t receive it by their first birthday. As a result, the percentage of children who had all the recommended vaccinations by their first birthday is low at only 70 per cent. The proportion of children receiving yellow fever vaccination in Nyanza is 79 per cent. The proportion of children who received all vaccines at age 12 months is 70 % whereas the proportion of children who did not receive any type of vaccination is only 2 per cent. Child Health 39 Table CH.2 shows vaccination coverage rates among children 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. 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. The coverage of BCG, DPT1 and Polio1 is all above 95% in Nyanza province as a whole. However, the coverage of DPT3 and Polio3 by 12 months of age drops by 6 per cent and 12 percentage points respectively. The measles vaccination was received by 95 per cent of children age 12-23 months. Overall, 78 per cent of children aged 12-23 months are fully vaccinated. That is, they had received BCG, 3 doses of DPT, 3 doses of Polio and measles vaccines. The immunization coverage across gender is similary distributed between girls and boys. Vaccination coverage ranges from 70 per cent in urban areas to 78 per cent in rural areas. The good coverage for rural areas is likely due to the fact that around the period of the survey, there was an on-going targeted and mop-up vaccination campaign on polio and other vaccines in majority of the rural areas visited. Similarly, the proportion of children receiving all vaccination across counties ranges from 69 per cent in Homa Bay County to 84 per cent in Migori County. Overall, the proportion of children not receiving any vaccinations is less than 2 per cent and does not vary much by any of the background characteristics considered. 0 80 40 20 100 60 P er c en t BCG DPT1 DPT2 DPT3 Polio 1 Polio 2 Polio 3 Measles All 97.2 96.0 94.5 90.0 96.2 91.4 83.3 89.1 70.3 Child Health Figure CH.1 Percentage of children aged 12-23 months who received the recommended vaccinations by 12 months, Nyanza Province, Kenya, 2011 40 Ta b le C H .2 : V ac ci na ti o ns b y b ac kg ro un d c ha ra ct er is ti cs P er ce nt ag e o f ch ild re n ag e 12 -2 3 m o nt hs c ur re nt ly v ac ci na te d a g ai ns t ch ild ho o d d is ea se s, N ya nz a P ro vi nc e, K en ya , 2 01 1 P er ce nt ag e of c hi ld re n w ho r ec ei ve d : P er ce nt ag e w ith v ac ci na tio n ca rd s ee n N um b er o f ch ild re n ag e 12 -2 3 m on th s B C G P ol io D P T M ea sl es Ye llo w fe ve r N on e A ll A t b irt h 1 2 3 1 2 3 S ex M al e 98 .7 91 .3 95 .5 91 .8 83 .9 97 .5 95 .0 91 .7 95 .8 84 .9 1. 1 78 .2 77 .5 44 3 Fe m al e 96 .4 90 .8 97 .9 91 .9 85 .0 96 .7 95 .3 90 .6 94 .7 84 .3 2. 1 78 .5 76 .0 42 5 C o un ty S ia ya 96 .5 87 .3 96 .4 93 .9 85 .7 95 .9 95 .1 89 .6 93 .8 83 .0 2. 4 78 .3 74 .0 13 7 K is um u 99 .3 91 .3 94 .9 85 .2 79 .1 97 .7 94 .4 87 .5 96 .1 83 .4 0. 7 74 .0 73 .7 14 7 H om a B ay 94 .8 85 .4 97 .2 89 .4 75 .6 95 .6 92 .2 86 .7 91 .5 78 .5 2. 8 68 .5 66 .6 16 5 M ig or i 96 .6 93 .1 96 .4 92 .9 87 .5 97 .7 96 .6 94 .0 96 .4 89 .0 2. 3 84 .3 82 .9 15 2 K is ii 10 0. 0 96 .3 98 .2 95 .2 91 .0 98 .2 96 .6 95 .0 96 .8 87 .1 0. 0 83 .6 82 .1 18 7 N ya m ira 98 .3 92 .2 96 .6 95 .7 89 .2 97 .4 96 .8 94 .8 98 .2 87 .6 1. 7 82 .9 83 .8 80 A re a U rb an 10 0. 0 94 .8 95 .8 87 .4 81 .9 96 .1 93 .2 89 .6 92 .9 82 .7 0. 0 71 .6 69 .5 10 7 R ur al 97 .2 90 .5 96 .8 92 .5 84 .8 97 .3 95 .5 91 .3 95 .6 84 .8 1. 8 79 .3 77 .8 76 2 M o th er ’s e d uc at io n N on e 95 .1 92 .3 93 .9 89 .6 82 .2 95 .1 91 .7 91 .7 95 .1 82 .1 4. 9 71 .4 68 .3 52 P rim ar y 97 .3 90 .4 96 .6 92 .2 84 .9 97 .0 95 .1 91 .1 94 .4 83 .5 1. 8 78 .4 77 .0 61 3 S ec on d ar y+ 98 .9 92 .5 97 .7 91 .3 83 .6 98 .1 96 .4 91 .1 98 .0 88 .3 0. 2 80 .0 78 .2 20 3 W ea lt h in d ex q ui nt ile P oo re st 95 .4 88 .2 95 .6 92 .2 85 .3 95 .5 93 .2 88 .6 92 .1 83 .3 3. 5 79 .4 79 .1 19 5 S ec on d 96 .3 91 .3 96 .0 91 .2 87 .0 97 .3 96 .1 93 .1 96 .7 86 .8 2. 2 82 .2 80 .2 18 1 M id d le 98 .4 90 .7 98 .0 95 .5 84 .7 97 .4 96 .2 90 .6 95 .1 86 .9 1. 1 80 .0 78 .0 17 7 Fo ur th 99 .1 91 .2 98 .5 90 .6 85 .0 99 .1 98 .0 93 .7 98 .4 85 .5 0. 0 78 .8 76 .9 15 9 R ic he st 99 .3 94 .3 95 .8 89 .3 79 .5 96 .6 92 .5 90 .0 94 .5 80 .1 0. 7 70 .2 68 .2 15 6 To ta l 97 .6 91 .0 96 .7 91 .8 84 .4 97 .1 95 .2 91 .1 95 .3 84 .6 1. 6 78 .3 76 .8 86 8 Child Health 41 Neonatal Tetanus Protection One of the MDGs is to reduce by three quarters the Maternal Mortality Ratio (MMR), with one strategy being to eliminate maternal tetanus. The other goal related to this indicator is to reduce the incidence of neonatal tetanus to less than 1 case of neonatal tetanus per 1,000 live births. A World Fit for Children goal is to eliminate maternal and neonatal tetanus by 2005. Prevention of maternal and neonatal tetanus requires that all pregnant women receive at least two doses of tetanus toxoid vaccine. However, if women have not received two doses of the vaccine during the pregnancy, they (and their new-born) are also considered to be protected if the following conditions are met: • Received at least two doses of tetanus toxoid vaccine, the last within the prior 3 years; • Received at least 3 doses, the last within the prior 5 years; • Received at least 4 doses, the last within 10 years; • Received at least 5 doses during lifetime. Table CH.3 shows the protection status from tetanus of women who have had a live birth within the last 2 years. In Nyanza Province, 64 per cent of women who had a live birth during two year preceding the survey had adequate protection against tetanus. The differentials in the neonatal tetanus protection coverage by background characteristics are also shown in Table CH.3. The women in Homa Bay were more likely to receive neonatal tetanus protection compared to their counterparts in Nyamira and Migori. The differentials by wealth index of the household show some variations, with a wider gap between women from the poorest and the richest wealth index households. Child Health 42 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, Nyanza Province, Kenya, 2011 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 tetanus [1] 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 County Siaya 48.0 13.0 0.0 0.0 0.0 61.0 318 Kisumu 55.6 9.0 0.0 0.0 0.0 64.5 318 Homa Bay 54.6 19.7 0.0 0.0 0.0 74.2 316 Migori 48.4 6.3 0.0 0.0 0.3 55.1 326 Kisii 45.6 21.4 0.0 0.0 0.0 67.0 370 Nyamira 48.7 10.6 0.0 0.0 0.3 59.7 164 Area Urban 60.5 8.2 0.0 0.0 0.0 68.7 240 Rural 48.5 14.6 0.0 0.0 0.1 63.2 1572 Education None 48.8 14.7 0.0 0.0 0.0 63.5 89 Primary 48.0 13.6 0.0 0.0 0.1 61.7 1287 Secondary+ 56.6 14.1 0.0 0.0 0.0 70.7 436 Wealth index quintile Poorest 43.1 13.8 0.0 0.0 0.2 57.1 415 Second 48.4 16.3 0.0 0.0 0.2 64.9 355 Middle 50.9 13.9 0.0 0.0 0.0 64.8 354 Fourth 50.7 13.6 0.0 0.0 0.0 64.3 345 Richest 58.9 11.2 0.0 0.0 0.0 70.1 341 Total 50.1 13.8 0.0 0.0 0.1 64.0 1812 [1] MICS indicator 3.7 Oral Rehydration Treatment Diarrhoea is the second leading cause of death among children under five worldwide. 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. Preventing dehydration and malnutrition by increasing fluid intake and continuing to feed the child are also important strategies for managing diarrhoea. The goals are to: 1) reduce by one half death due to diarrhoea among children under five by 2010 compared to 2000 (A World Fit for Children); and 2) reduce by two thirds the mortality rate among children under five by 2015 compared to 1990 (Millennium Development Goals). In addition, the World Fit for Children calls for a reduction in the incidence of diarrhoea by 25 per cent. Child Health 43 The indicators are: • Prevalence of diarrhoea • Oral rehydration therapy (ORT) • Home management of diarrhoea • ORT with continued feeding In the MICS questionnaire, mothers (or caretakers) were asked to report whether their child had had diarrhoea in the two weeks prior to the survey. If so, the mother was asked a series of questions about what the child had to drink and eat during the episode and whether this was more or less than the child usually ate and drank. Overall, 16 per cent of under five children had diarrhoea in the two weeks preceding the survey (Table CH.4). Diarrhoea prevalence was highest in Siaya and Kisumu Counties. The peak of diarrhoea prevalence occurs in the weaning period, among children age 12-23 months. Table CH.4 also shows the percentage of children receiving various types of recommended liquids during the episode of diarrhoea. Since mothers were able to name more than one type of liquid, the percentages do not necessarily add to 100. About one in four children (25 per cent) received fluids from ORS packets or pre-packaged ORS fluids and 35 per cent received ORS or recommended homemade fluids (Figure CH.3). Approximately 12 per cent of children with diarrhoea received one or more of the recommended home treatments (i.e., were treated with sugar and salt solution). The proportion taking ORS or any recommended homemade fluid was highest in Siaya County (50%). Child Health 44 Ta b le C H .4 : O ra l r eh yd ra ti o n so lu ti o ns a nd r ec o m m en d ed h o m em ad e fl ui d s P er ce nt ag e o f ch ild re n ag e 0- 59 m o nt hs w it h d ia rr ho ea in t he la st t w o w ee ks , a nd t re at m en t w it h o ra l r eh yd ra ti o n so lu ti o ns a nd r ec o m m en d ed h o m em ad e fl ui d s, N ya nz a P ro vi nc e, K en ya , 2 01 1 H ad d ia rr ho ea in la st t w o w ee ks N um b er o f ch ild re n ag ed 0- 59 m on th s O R S (F lu id fr om O R S p ac ka ge or p re -p ac ka ge d O R S fl ui d ) A ny R ec om m en d ed H om em ad e Fl ui d O R S o r an y re co m m en d ed ho m em ad e flu id N um b er o f c hi ld re n ag ed 0 -5 9 m on th s w ith d ia rr he a S ex M al e 17 .8 25 59 25 .6 12 .1 35 .5 45 5 Fe m al e 13 .6 24 86 24 .5 12 .6 33 .8 33 9 C o un ty S ia ya 19 .5 80 9 35 .7 18 .9 50 .1 15 8 K is um u 18 .2 86 1 27 .7 12 .0 39 .7 15 6 H om a B ay 15 .6 86 8 31 .5 11 .4 36 .7 13 6 M ig or i 12 .9 93 0 19 .5 6. 3 25 .0 12 0 K is ii 14 .6 11 35 12 .1 10 .8 21 .6 16 5 N ya m ira 13 .2 44 2 23 .4 13 .9 33 .6 58 A re a R ur al 15 .3 44 29 25 .2 13 .1 35 .4 67 6 U rb an 19 .2 61 6 24 .8 7. 3 31 .3 11 8 A g e 0- 11 21 .2 10 02 24 .3 17 .2 37 .8 21 3 12 -2 3 25 .4 86 8 29 .9 12 .1 39 .7 22 1 24 -3 5 16 .5 10 47 26 .3 8. 8 32 .0 17 2 36 -4 7 9. 2 10 94 21 .5 11 .9 31 .0 10 1 48 -5 9 8. 4 10 34 17 .2 7. 8 25 .0 87 M o th er ’s ed uc at io n N on e 12 .3 34 5 (2 8. 6) (8 .0 ) (3 6. 6) 42 P rim ar y 17 .0 35 23 24 .6 11 .9 33 .8 59 8 S ec on d ar y+ 13 .0 11 78 26 .3 14 .9 38 .1 15 3 W ea lt h in d ex q ui nt ile s P oo re st 15 .8 11 68 17 .3 13 .6 29 .5 18 4 S ec on d 16 .2 10 54 25 .9 9. 6 34 .3 17 1 M id d le 15 .5 98 5 30 .7 16 .9 41 .9 15 2 Fo ur th 14 .6 94 4 25 .1 13 .4 35 .2 13 8 R ic he st 16 .5 89 4 28 .3 7. 9 34 .2 14 8 To ta l 15 .7 50 45 25 .1 12 .3 34 .8 79 4 ( ) B as ed o n 25 -4 9 un w ei gh te d c as es . Child Health 45 Figure CH.3 Percentage of children under age 5 with diarrhoea who received oral rehydration solution, Nyanza Province, 2011 0 20.0 10.0 30.0 35.0 40.0 5.0 25.0 15.0 P er c en t 36 32 28 19 12 23 25 County Total Si ay a Ki su m u H om a B ay M ig or i Ki si i N ya m ira N ya nz a One in four (25 per cent) of under five children with diarrhoea drank more than usual while, 38 per cent drank the same or somewhat less, and 36 per cent were given much less to drink (Table CH.5). About 17, 26 and 2 per cent ate somewhat less, same or were given more (continued feeding) respectively, while 42 and 14 per cent ate much less or ate almost none. Child Health 46 Ta b le C H .5 : F ee d in g p ra ct ic es d ur in g d ia rr ho ea P er ce nt ag e d is tr ib ut io n o f ch ild re n ag e 0- 59 m o nt hs w it h d ia rr ho ea in t he la st t w o w ee ks b y am o un t o f liq ui d s an d f o o d g iv en d ur in g e p is o d e o f d ia rr ho ea , N ya nz a P ro vi nc e, K en ya , 2 01 1 H ad d ia r- rh oe a in la st t w o w ee ks N um b er of c hi ld re n ag e 0- 59 m on th s D rin ki ng p ra ct ic es d ur in g d ia rr ho ea : E at in g p ra ct ic es d ur in g d ia rr ho ea : N um b er of c hi ld re n ag ed 0 -5 9 m on th s w ith d ia rr ho ea G iv en m uc h le ss t o d rin k G iv en a b ou t th e sa m e (o r so m ew ha t le ss ) G iv en m or e to d rin k M is si ng / D K To ta l G iv en no ne to e at G iv en m uc h le ss t o ea t G iv en so m ew ha t le ss t o ea t G iv en ab ou t th e sa m e to ea t G iv en m or e to ea t M is si ng / D K To ta l S ex M al e 17 .8 25 59 36 .0 37 .7 25 .5 0. 8 10 0. 0 13 .8 41 .9 17 .0 24 .2 2. 4 0. 7 10 0. 0 45 5 Fe m al e 13 .6 24 86 35 .9 39 .1 25 .0 0. 0 10 0. 0 13 .5 41 .0 15 .9 27 .7 1. 7 0. 3 10 0. 0 33 9 C o un ty S ia ya 19 .5 80 9 48 .8 26 .5 24 .7 0. 0 10 0. 0 19 .0 46 .0 11 .9 18 .1 4. 3 0. 7 10 0. 0 15 8 K is um u 18 .2 86 1 37 .0 37 .8 24 .4 0. 8 10 0. 0 13 .6 41 .6 12 .3 31 .7 0. 0 0. 8 10 0. 0 15 6 H om a B ay 15 .6 86 8 40 .1 31 .9 27 .3 0. 8 10 0. 0 13 .5 46 .6 12 .7 24 .4 1. 2 1. 5 10 0. 0 13 6 M ig or i 12 .9 93 0 24 .5 33 .4 42 .0 0. 0 10 0. 0 8. 0 45 .6 19 .8 25 .6 1. 1 0. 0 10 0. 0 12 0 K is ii 14 .6 11 35 28 .5 51 .7 18 .8 0. 9 10 0. 0 16 .2 30 .2 27 .1 23 .2 3. 3 0. 0 10 0. 0 16 5 N ya m ira 13 .2 44 2 33 .3 58 .6 8. 1 0. 0 10 0. 0 3. 8 41 .1 12 .6 40 .1 2. 3 0. 0 10 0. 0 58 A re a R ur al 15 .3 44 29 36 .4 39 .9 23 .1 0. 6 10 0. 0 13 .8 40 .8 16 .4 26 .3 2. 1 0. 6 10 0. 0 67 6 U rb an 19 .2 61 6 33 .2 29 .0 37 .8 0. 0 10 0. 0 13 .0 45 .7 17 .3 22 .1 1. 9 0. 0 10 0. 0 11 8 A re a 0- 11 21 .2 10 02 42 .1 43 .0 13 .7 1. 2 10 0. 0 32 .9 31 .1 14 .0 20 .4 0. 6 0. 9 10 0. 0 21 3 12 -2 3 25 .4 86 8 34 .7 35 .1 29 .6 0. 6 10 0. 0 10 .2 43 .6 17 .4 25 .5 2. 2 1. 0 10 0. 0 22 1 24 -3 5 16 .5 10 47 33 .6 38 .0 28 .4 0. 0 10 0. 0 6. 8 45 .5 14 .8 29 .5 3. 4 0. 0 10 0. 0 17 2 36 -4 7 9. 2 10 94 35 .6 34 .8 29 .6 0. 0 10 0. 0 2. 4 49 .7 23 .0 23 .2 1. 8 0. 0 10 0. 0 10 1 48 -5 9 8. 4 10 34 29 .0 39 .9 31 .1 0. 0 10 0. 0 2. 1 44 .5 16 .3 34 .0 3. 1 0. 0 10 0. 0 87 M o th er ’s ed uc at io n N on e 12 .3 34 5 33 .1 36 .7 30 .2 0. 0 10 0. 0 (1 2. 9) (4 3. 5) (2 6. 7) (1 4. 4) (0 .0 ) (2 .4 ) 10 0. 0 42 P rim ar y 17 .0 35 23 35 .8 40 .0 23 .8 0. 4 10 0. 0 12 .7 42 .3 15 .2 26 .9 2. 4 0. 5 10 0. 0 59 8 S ec on d ar y+ 13 .0 11 78 37 .4 32 .2 29 .4 1. 0 10 0. 0 17 .6 38 .1 19 .1 23 .8 1. 4 0. 0 10 0. 0 15 3 W ea lt h in d ex q ui nt ile s P oo re st 15 .8 11 68 38 .1 40 .1 21 .0 0. 8 10 0. 0 16 .0 38 .9 18 .0 24 .4 2. 1 0. 5 10 0. 0 18 4 S ec on d 16 .2 10 54 40 .0 34 .9 25 .2 0. 0 10 0. 0 11 .8 45 .9 15 .4 22 .6 4. 3 0. 0 10 0. 0 17 1 M id d le 15 .5 98 5 36 .1 41 .2 22 .8 0. 0 10 0. 0 15 .5 42 .1 16 .0 25 .7 0. 6 0. 0 10 0. 0 15 2 Fo ur th 14 .6 94 4 27 .7 46 .0 25 .4 0. 9 10 0. 0 9. 7 29 .3 20 .3 38 .2 1. 5 0. 9 10 0. 0 13 8 R ic he st 16 .5 89 4 36 .2 30 .0 33 .1 0. 7 10 0. 0 14 .6 50 .5 13 .0 19 .0 1. 5 1. 4 10 0. 0 14 8 To ta l 15 .7 50 45 36 .0 38 .3 25 .3 0. 5 10 0. 0 13 .7 41 .5 16 .5 25 .7 2. 1 0. 5 10 0. 0 79 4 ( ) B as ed o n 25 -4 9 un w ei gh te d c as es . Child Health 47 Table CH.6 provides the proportion of children age 0-59 months with diarrhoea in the last two weeks who received oral rehydration therapy with continued feeding, and percentage of children with diarrhoea who received other treatments. Overall, 35 per cent of children with diarrhoea received ORS or increased fluids, 70 per cent received ORT (ORS or recommended homemade fluids or increased fluids). Combining the information in Table CH.5 with those in Table CH.4 on oral rehydration therapy, it is observed that 43 per cent of children received ORT and, at the same time, feeding was continued, as is the recommendation. There are variations in the home management of diarrhoea by background characteristics. In urban areas, 47 per cent of children received ORT and continued feeding, while the figure is 43 per cent in rural areas. Figure CH.4 Percentage of children under age 5 with diarrhoea who received ORS fluids, Nyanza Province, Kenya 2011 0 40 20 60 70 10 50 30 P er c en t 46.3 37.8 46.7 58.9 34 35.6 47.1 42.5 43.2 Si ay a Ki su m u H om a B ay M ig or i Ki si i N ya m ira R ur al U rb an N ya nz a Child Health County Area 48 Child Health Ta b le C H .6 : O ra l r eh yd ra ti o n th er ap y w it h co nt in ue d f ee d in g a nd o th er t re at m en ts P er ce nt ag e o f ch ild re n ag e 0- 59 m o nt hs w it h d ia rr ho ea in t he la st t w o w ee ks w ho r ec ei ve d o ra l r eh yd ra ti o n th er ap y w it h co nt in ue d f ee d in g , a nd p er ce nt ag e o f ch ild re n w it h d ia rr ho ea w ho r ec ei ve d o th er t re at m en ts , N ya nz a P ro vi nc e, K en ya , 2 01 1 C hi ld re n w ith d ia rr ho ea w ho r e- ce iv ed : O th er t re at m en t: N ot g iv en an y tr ea t- m en t or d ru g N um b er of c hi ld re n ag ed 0 -5 9 m on th s w ith d ia r- rh oe a O R S o r in cr ea se d flu id s O R T (O R S or r ec om - m en d ed ho m em ad e flu id s or in cr ea se d flu id s) O R T w ith co nt in - ue d fe ed - in g [1 ] P ill o r sy ru p : A nt ib io tic P ill o r sy ru p : A nt m ot ili ty P ill o r sy ru p : Z in c P ill o r sy ru p : O th er P ill o r sy ru p : U nk no w n In je ct io n: A nt ib io tic In je ct io n: N on -a nt i- b io tic In je ct io n: U nk no w n In tr a- ve no us H om e re m - ed y/ H er b al m ed i- ci ne O th er S ex M al e 35 .6 69 .7 41 .0 20 .3 2. 1 2. 2 0. 9 5. 3 3. 6 0. 0 1. 1 0. 0 13 .5 6. 3 30 .3 45 5 Fe m al e 33 .1 70 .0 46 .3 24 .6 1. 8 2. 9 0. 0 3. 6 2. 4 0. 3 1. 1 1. 0 13 .0 6. 1 30 .0 33 9 C o un ty S ia ya 48 .9 88 .7 46 .3 29 .0 0. 0 1. 3 0. 6 3. 4 4. 3 0. 0 0. 5 0. 0 16 .6 6. 3 11 .3 15 8 K is um u 38 .3 64 .8 37 .8 21 .8 1. 6 1. 5 0. 8 2. 8 0. 8 0. 0 0. 7 0. 0 9. 8 2. 2 35 .2 15 6 H om a B ay 34 .8 78 .8 46 .7 22 .8 3. 8 1. 9 1. 3 3. 1 2. 8 0. 0 2. 1 0. 0 12 .7 16 .2 21 .2 13 6 M ig or i 26 .0 72 .7 58 .9 30 .4 3. 7 10 .2 0. 0 6. 1 9. 6 0. 7 2. 7 2. 9 13 .6 4. 8 27 .3 12 0 K is ii 22 .7 52 .8 34 .0 14 .8 1. 6 0. 0 0. 0 8. 0 0. 7 0. 0 0. 4 0. 0 12 .4 3. 6 47 .2 16 5 N ya m ira 35 .9 53 .4 35 .6 6. 7 1. 1 1. 1 0. 6 2. 9 0. 0 0. 0 0. 0 0. 0 16 .7 4. 0 46 .6 58 A re a R ur al 34 .9 69 .6 42 .5 19 .8 2. 1 2. 1 0. 3 4. 9 2. 0 0. 1 1. 3 0. 3 14 .3 6. 3 30 .4 67 6 U rb an 32 .4 71 .2 47 .1 35 .5 1. 2 4. 9 1. 7 2. 6 9. 5 0. 0 0. 0 1. 0 7. 2 6. 2 28 .8 11 8 A g e 0- 11 37 .1 69 .2 37 .3 18 .6 2. 8 2. 8 0. 8 4. 7 1. 7 0. 0 0. 4 0. 0 13 .9 5. 9 30 .8 21 3 12 -2 3 39 .4 70 .3 44 .5 25 .9 0. 7 3. 2 0. 2 4. 1 2. 6 0. 4 0. 9 0. 5 13 .9 4. 5 29 .7 22 1 24 -3 5 33 .5 68 .7 44 .5 19 .7 2. 4 1. 7 0. 7 4. 6 4. 9 0. 0 2. 0 0. 8 12 .0 5. 1 31 .3 17 2 36 -4 7 30 .1 76 .7 48 .9 26 .5 2. 4 3. 4 0. 9 7. 5 2. 3 0. 0 0. 0 0. 9 11 .7 9. 2 23 .3 10 1 48 -5 9 23 .0 64 .0 45 .6 21 .4 1. 4 0. 4 0. 0 1. 8 5. 1 0. 0 2. 6 0. 0 14 .7 10 .5 36 .0 87 M o th er ’s ed uc at io n N on e (3 2. 0) (8 2. 3) (6 0. 2) (3 3. 1) (0 .0 ) (3 .0 ) (5 .4 ) (1 3. 3) (8 .1 ) (0 .0 ) (0 .0 ) (0 .0 ) (1 5. 3) (3 .9 ) (1 7. 7) 42 P rim ar y 33 .9 68 .7 42 .4 20 .1 2. 0 2. 6 0. 3 4. 1 2. 8 0. 1 1. 3 0. 6 13 .7 6. 2 31 .3 59 8 S ec on d ar y+ 37 .6 70 .8 41 .8 26 .9 2. 1 2. 0 0. 0 3. 9 2. 9 0. 0 0. 5 0. 0 11 .1 7. 1 29 .2 15 3 W ea lt h in d ex q ui nt ile s P oo re st 29 .5 68 .2 38 .1 21 .5 2. 4 1. 5 0. 3 4. 7 1. 3 0. 5 2. 0 0. 8 20 .9 7. 1 31 .8 18 4 S ec on d 35 .5 63 .0 39 .0 15 .2 0. 4 2. 4 0. 2 3. 6 1. 6 0. 0 0. 7 0. 5 10 .6 6. 1 37 .0 17 1 M id d le 39 .4 74 .0 46 .5 19 .7 3. 0 4. 2 0. 0 5. 9 4. 0 0. 0 2. 0 0. 0 11 .7 4. 4 26 .0 15 2 Fo ur th 35 .5 70 .9 50 .7 25 .6 2. 3 1. 4 0. 9 6. 1 1. 9 0. 0 0. 5 0. 0 8. 6 6. 6 29 .1 13 8 R ic he st 33 .8 74 .3 44 .1 30 .3 1. 7 3. 1 1. 3 2. 8 7. 3 0. 0 0. 0 0. 8 12 .9 7. 1 25 .7 14 8 To ta l 34 .5 69 .8 43 .2 22 .1 1. 9 2. 5 0. 5 4. 6 3. 1 0. 1 1. 1 0. 4 13 .3 6. 3 30 .2 79 4 [1 ] M IC S in d ic at or 3 .8 ( ) B as ed o n 25 -4 9 un w ei gh te d c as es . 49 Care Seeking and Antibiotic Treatment of Pneumonia Pneumonia is the leading cause of death in children and the use of antibiotics in under-5s with suspected pneumonia is a key intervention. A World Fit for Children goal is to reduce by one-third the deaths due to acute respiratory infections. Children with suspected pneumonia are those who had an illness with a cough accompanied by rapid or difficult breathing and whose symptoms were NOT due to a problem in the chest and a blocked nose. The indicators are: • Prevalence of suspected pneumonia • Care seeking for suspected pneumonia • Antibiotic treatment for suspected pneumonia • Knowledge of the danger signs of pneumonia Table CH.7 presents the prevalence of suspected pneumonia and, if care was sought outside the home, the site of care. About 9 per cent of children aged 0-59 months were reported to have had symptoms of pneumonia during the two weeks preceding the survey. Of these children, 51 per cent were taken to an appropriate provider. Appropriate care was mostly sought from government dispensaries and health centres. Many government hospitals are found in urban areas; hence it is not surprising that about 30 per cent of those in urban areas sought appropriate care form the government hospitals compared to only 7 per cent in rural areas. The differentials in the prevalence of suspected pneumonia by background characteristics such as levels of mother’s education and household wealth index are presented in Table CH.7. For example, 8 per cent of the children with mothers with no education had suspected pneumonia compared with 10 and 6 per cent among those educated up to primary and secondary or higher levels, respectively. Table CH.7 also presents the use of antibiotics for the treatment of suspected pneumonia in under-5s by sex, age, region, residence, age, and socioeconomic factors. In Nyanza, 51 per cent of under-5 children with suspected pneumonia had received an antibiotic during the two weeks prior to the survey. The percentage was higher in urban areas (61 per cent) compared to rural areas (49 per cent). At the regional level, 63 per cent of children in Kisumu with suspected pneumonia received antibiotics in the last two weeks compared to only 31 per cent for those resident in Nyamira County. The table also shows that antibiotic treatment of suspected pneumonia is lower among the three lower wealth index households. In Nyanza, the use of antibiotics does not seem to rise with the age of the child Child Health 50 Ta b le C H .7 : C ar e se ek in g f o r su sp ec te d p ne um o ni a an d a nt ib io ti c us e d ur in g s us p ec te d p ne um o ni a P er ce nt ag e o f ch ild re n ag e 0- 59 m o nt hs w it h su sp ec te d p ne um o ni a in t he l as t tw o w ee ks w ho w er e ta ke n to a h ea lt h p ro vi d er a nd p er ce nt ag e o f ch ild re n w ho w er e g iv en an ti b io ti cs , H ad s us - p ec te d p ne um o- ni a in t he la st t w o w ee ks N um - b er o f ch ild re n ag e 0- 59 m on th s C hi ld re n w ith s us p ec te d p ne um on ia w ho w er e ta ke n to : A ny a p - p ro p ria te p ro vi d er [1 ] P er ce nt ag e of ch ild re n w ith su sp ec te d p ne um on ia w ho re ce iv ed a nt ib i- ot ic s in t he la st tw o w ee ks [2 ] N um b er o f ch ild re n ag e 0- 59 m on th s w ith s us p ec te d p ne um on ia in th e la st t w o w ee ks P ub lic se ct or : G ov er n- m en t ho sp ita l P ub lic se ct or : G ov er n- m en t he al th ce nt re P ub lic se ct or : G ov er n- m en t d is p en - sa ry O th er p ub lic P riv at e: M is si on ho sp ita l P riv at e ho sp ita l / cl in ic N ur si ng / m at er ni ty ho m e P riv at e p ha r- m ac y O th er p riv at e m ed i- ca l M ob ile cl in ic C om m u- ni ty h ea lth w or ke r S ho p Tr ad i- tio na l p ra ct i- tio ne r O th er S ex M al e 9. 6 25 59 10 .5 12 .4 17 .6 0. 4 2. 4 5. 8 0. 0 8. 2 0. 9 0. 0 0. 5 0. 0 0. 0 0. 0 49 .9 50 .2 24 6 Fe m al e 7. 8 24 86 7. 5 9. 8 24 .5 0. 0 3. 6 4. 9 0. 0 9. 5 1. 2 0. 8 0. 5 0. 0 0. 0 0. 0 51 .9 51 .2 19 3 C o un ty S ia ya 13 .2 80 9 12 .9 14 .9 18 .6 0. 0 5. 6 2. 8 0. 0 16 .6 0. 0 1. 4 0. 0 0. 0 0. 0 0. 0 54 .8 56 .0 10 7 K is um u 6. 2 86 1 9. 3 19 .8 9. 9 0. 0 1. 3 7. 1 0. 0 6. 0 1. 9 0. 0 2. 1 0. 0 0. 0 0. 0 51 .5 63 .0 53 H om a B ay 8. 7 86 8 7. 1 11 .9 14 .7 1. 1 6. 0 10 .6 0. 0 14 .5 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 50 .0 60 .8 76 M ig or i 7. 6 93 0 8. 2 11 .3 21 .5 0. 0 0. 4 5. 0 0. 0 6. 9 1. 5 0. 0 1. 3 0. 0 0. 0 0. 0 49 .2 47 .3 70 K is ii 8. 0 11 35 7. 0 2. 3 31 .4 0. 0 1. 5 2. 4 0. 0 1. 4 2. 7 0. 0 0. 0 0. 0 0. 0 0. 0 47 .4 40 .3 91 N ya m ira 9. 7 44 2 9. 8 9. 3 25 .2 0. 0 0. 0 7. 8 0. 0 1. 1 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 50 .8 31 .4 43 A re a R ur al 9. 0 44 29 7. 0 11 .5 22 .5 0. 2 3. 0 5. 8 0. 0 8. 3 1. 1 0. 4 0. 5 0. 0 0. 0 0. 0 51 .5 49 .6 39 7 U rb an 6. 8 61 6 (2 9. 8) (8 .9 ) (3 .5 ) (0 .0 ) (2 .4 ) (1 .6 ) (0 .0 ) (1 3. 4) (0 .0 ) (0 .0 ) (0 .0 ) (0 .0 ) (0 .0 ) (0 .0 ) (4 3. 6) (6 0. 6) 42 A g e 0- 11 9. 6 10 02 10 .5 10 .5 25 .0 0. 0 7. 8 4. 5 0. 0 7. 1 1. 3 1. 5 0. 0 0. 0 0. 0 0. 0 59 .1 55 .9 96 12 -2 3 8. 4 86 8 12 .8 10 .7 21 .0 0. 0 0. 0 5. 7 0. 0 10 .8 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 50 .2 44 .6 73 24 -3 5 8. 8 10 47 8. 6 7. 9 17 .6 0. 0 1. 2 6. 6 0. 0 7. 6 2. 4 0. 0 0. 0 0. 0 0. 0 0. 0 44 .4 52 .7 92 36 -4 7 8. 1 10 94 9. 7 12 .0 17 .6 0. 0 3. 6 8. 1 0. 0 4. 7 1. 2 0. 0 1. 0 0. 0 0. 0 0. 0 53 .1 50 .2 88 48 -5 9 8. 7 10 34 4. 9 15 .3 21 .7 1. 0 1. 2 2. 4 0. 0 14 .0 0. 0 0. 0 1. 2 0. 0 0. 0 0. 0 46 .5 48 .3 90 M o th er ’s e d uc at io n N on e 8. 2 34 5 (7 .3 ) (1 0. 1) (1 5. 9) (0 .0 ) (7 .4 ) (8 .8 ) (0 .0 ) (1 1. 5) (3 .6 ) (0 .0 ) (0 .0 ) (0 .0 ) (0 .0 ) (0 .0 ) (5 3. 0) (5 4. 5) 28 P rim ar y 9. 7 35 23 8. 5 10 .6 20 .7 0. 3 2. 8 5. 9 0. 0 9. 7 0. 7 0. 4 0. 3 0. 0 0. 0 0. 0 49 .6 49 .4 34 1 S ec on d ar y+ 6. 0 11 78 13 .4 14 .8 22 .3 0. 0 1. 6 1. 6 0. 0 2. 9 1. 7 0. 0 1. 6 0. 0 0. 0 0. 0 55 .3 55 .2 70 W ea lt h in d ex q ui nt ile s P oo re st 9. 8 11 68 3. 4 12 .0 25 .7 0. 0 2. 2 4. 4 0. 0 7. 3 2. 2 0. 0 0. 0 0. 0 0. 0 0. 0 49 .8 44 .2 11 5 S ec on d 9. 6 10 54 8. 0 11 .7 24 .4 0. 0 3. 9 7. 5 0. 0 7. 2 0. 0 0. 0 0. 9 0. 0 0. 0 0. 0 56 .5 51 .0 10 1 M id d le 7. 6 98 5 3. 7 7. 1 23 .8 1. 2 3. 3 3. 8 0. 0 10 .0 0. 0 0. 0 1. 5 0. 0 0. 0 0. 0 44 .3 42 .3 75 Fo ur th 8. 3 94 4 10 .9 15 .6 14 .4 0. 0 3. 6 6. 5 0. 0 15 .0 0. 0 1. 9 0. 0 0. 0 0. 0 0. 0 50 .2 56 .7 78 R ic he st 7. 8 89 4 24 .3 9. 1 10 .5 0. 0 1. 6 4. 6 0. 0 5. 2 3. 0 0. 0 0. 0 0. 0 0. 0 0. 0 51 .4 62 .9 70 To ta l 8. 7 50 45 9. 2 11 .3 20 .6 0. 2 2. 9 5. 4 0. 0 8. 8 1. 0 0. 3 0. 5 0. 0 0. 0 0. 0 50 .7 50 .6 43 9 [1 ] M IC S in d ic at or 3 .9 ; [ 2] M IC S in d ic at or 3 .1 0; ; ( ) B as ed o n 25 -4 9 un w ei gh te d c as es Child Health 51 Solid Fuel Use More than 3 billion people around the world rely on solid fuels (biomass and coal) for their basic energy needs, including cooking and heating. Cooking and heating with solid fuels leads to high levels of indoor smoke, a complex mix of health-damaging pollutants. The main problem with the use of solid fuels is products of incomplete combustion, including CO, polyaromatic hydrocarbons, SO2, and other toxic elements. Use of solid fuels increases the risks of acute respiratory illness, pneumonia, chronic obstructive lung disease, cancer, and possibly tuberculosis, low birth weight, cataracts, and asthma. The primary indicator is the proportion of the population using solid fuels as the primary source of domestic energy for cooking. Information regarding solid fuel use by background characteristics such as education level of the household head, wealth index and counties are shown in Table CH.9. Ninety seven per cent of the households in Nyanza use solid fuels for cooking. Seventy five per cent of the households use wood for cooking followed by charcoal (15 per cent). Differentials with respect to household wealth index show that 53 per cent of the richest households use charcoal, while wood is predominantly prevalent among the poor households. A similar pattern is observed among urban and rural households. For example, 65 per cent of households from the urban areas use charcoal compared to only 7 per cent among those from rural areas, while the use of wood is 84 per cent among rural areas versus 19 per cent in urban areas. The findings show that use of solid fuels is very common among households in the predominantly rural counties (all except Kisumu), and among the richest households. In Siaya, many households rely on straw/shrubs and grass. The table also clearly shows that the overall percentage is high due to high level of use wood for cooking purposes. Child Health 52 Ta b le C H .9 : S o lid f ue l u se P er ce nt ag e d is tr ib ut io n o f ho us eh o ld m em b er s ac co rd in g t o t yp e o f co o ki ng f ue l u se d b y th e ho us eh o ld , a nd p er ce nt ag e o f ho us eh o ld m em b er s liv in g in h o us eh o ld s us in g s o lid f ue ls f o r co o ki ng , N ya nz a P ro vi nc e, K en ya , 2 01 1 P er ce nt ag e of h ou se ho ld m em b er s in h ou se ho ld s us in g: S ol id fu el s fo r co ok in g [1 ] N um b er o f ho us eh ol d m em b er s E le ct ric ity Li q ui d p ro p an e ga s (L P G ) N at ur al ga s B io ga s K er os en e C oa l/ lig ni te C ha rc oa l W oo d S tr aw / sh ru b s/ gr as s A ni m al d un g A gr ic ul tu ra l cr op re si d ue O th er M is si ng To ta l C o un ty S ia ya 0. 0 0. 3 0. 0 0. 0 0. 6 0. 0 13 .9 46 .7 38 .2 0. 0 0. 0 0. 0 0. 3 10 0. 0 98 .8 49 81 K is um u 0. 2 4. 1 0. 7 0. 0 3. 5 0. 0 25 .8 65 .2 0. 3 0. 0 0. 0 0. 1 0. 2 10 0. 0 91 .2 52 60 H om a B ay 0. 0 0. 3 0. 5 0. 0 0. 6 0. 0 12 .2 85 .4 0. 7 0. 0 0. 1 0. 0 0. 2 10 0. 0 98 .4 50 10 M ig or i 0. 0 0. 0 0. 8 0. 2 0. 6 0. 0 18 .0 79 .5 0. 0 0. 0 0. 6 0. 0 0. 2 10 0. 0 98 .2 53 33 K is ii 0. 6 0. 6 0. 2 0. 0 0. 4 0. 0 9. 1 87 .3 0. 4 0. 1 0. 7 0. 4 0. 1 10 0. 0 97 .7 68 51 N ya m ira 0. 0 0. 8 0. 3 0. 1 0. 7 0. 1 6. 5 86 .0 4. 9 0. 0 0. 4 0. 2 0. 0 10 0. 0 97 .9 30 04 A re a R ur al 0. 0 0. 3 0. 2 0. 0 0. 3 0. 0 6. 8 83 .7 7. 9 0. 0 0. 4 0. 1 0. 2 10 0. 0 98 .8 26 37 9 U rb an 1. 2 5. 4 1. 6 0. 3 5. 9 0. 0 65 .1 18 .8 1. 2 0. 0 0. 0 0. 2 0. 2 10 0. 0 85 .2 40 60 E d uc at io n o f ho us eh o ld h ea d N on e 0. 2 4. 2 1. 8 0. 3 1. 5 0. 0 18 .1 67 .1 6. 0 0. 0 0. 6 0. 0 0. 2 10 0. 0 91 .8 52 41 P rim ar y 0. 2 0. 0 0. 1 0. 0 0. 7 0. 0 10 .4 79 .8 8. 0 0. 0 0. 4 0. 1 0. 2 10 0. 0 98 .7 17 17 5 S ec on d ar y + 0. 1 1. 0 0. 2 0. 1 1. 6 0. 0 21 .6 69 .7 5. 4 0. 0 0. 0 0. 2 0. 1 10 0. 0 96 .7 79 00 M is si ng /D K 0. 0 2. 9 0. 0 0. 0 0. 0 0. 0 3. 4 91 .3 2. 4 0. 0 0. 0 0. 0 0. 0 10 0. 0 97 .1 12 3 W ea lt h in d ex q ui nt ile s P oo re st 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 96 .6 2. 7 0. 1 0. 6 0. 0 0. 0 10 0. 0 10 0. 0 60 84 S ec on d 0. 0 0. 0 0. 0 0. 0 0. 0 0. 1 0. 1 92 .8 6. 7 0. 0 0. 2 0. 1 0. 1 10 0. 0 99 .8 60 92 M id d le 0. 0 0. 0 0. 0 0. 0 0. 1 0. 0 2. 3 82 .6 13 .5 0. 0 0. 7 0. 4 0. 4 10 0. 0 99 .2 60 87 Fo ur th 0. 0 0. 0 0. 0 0. 0 1. 1 0. 0 17 .4 72 .7 8. 4 0. 0 0. 1 0. 1 0. 2 10 0. 0 98 .6 60 89 R ic he st 0. 8 5. 0 2. 0 0. 3 4. 2 0. 0 53 .1 30 .6 3. 6 0. 0 0. 0 0. 1 0. 2 10 0. 0 87 .3 60 88 To ta l 0. 2 1. 0 0. 4 0. 1 1. 1 0. 0 14 .6 75 .0 7. 0 0. 0 0. 3 0. 1 0. 2 10 0. 0 97 .0 30 43 9 [1 ] M IC S in d ic at or 3 .1 1 Child Health 53 Solid fuel use alone is a poor proxy for indoor air pollution, since the concentration of the pollutants is different when the same fuel is burnt in different stoves or fires. Use of closed stoves with chimneys minimizes indoor pollution, while open stove or fire with no chimney or hood means that there is no protection from the harmful effects of solid fuels. Solid fuel use by place of cooking is depicted in Table CH.10. In Nyanza, about 23 per cent of households cook in the same room used for living/sleeping, 26 per cent cook in a separate room used as a kitchen, while 42 per cent use a separate building used a kitchen. Table CH.10: Solid fuel use by place of cooking Percentage distribution of household members in households using solid fuels by place of cooking, Nyanza Province, Kenya, 2011 Place of cooking: Number of household members in households using solid fuels for cooking In a room used for living/ sleeping In a separate room used as kitchen In a separate building used as kitchen Outdoors Others Missing Total County Siaya 23.0 19.1 41.5 16.0 0.0 0.4 100.0 4920 Kisumu 34.1 37.9 18.1 9.6 0.0 0.3 100.0 4798 Homa Bay 26.7 24.2 34.4 14.2 0.1 0.5 100.0 4930 Migori 22.1 23.8 44.4 8.8 0.0 0.9 100.0 5234 Kisii 14.5 25.4 56.4 3.7 0.0 0.0 100.0 6694 Nyamira 20.8 22.1 52.9 3.8 0.0 0.4 100.0 2941 Area Rural 20.6 23.8 45.7 9.6 0.0 0.3 100.0 26060 Urban 42.2 39.1 10.5 7.4 0.0 0.8 100.0 3458 Education of household head None 18.0 35.2 41.0 5.5 0.0 0.2 100.0 4812 Primary 24.3 22.8 41.7 10.7 0.0 0.5 100.0 16947 Secondary + 23.4 25.8 41.5 8.9 0.0 0.3 100.0 7639 Missing/DK 39.2 11.2 42.8 6.7 0.0 0.0 100.0 119 Wealth index quintiles Poorest 32.5 21.9 35.1 10.1 0.0 0.4 100.0 6082 Second 19.3 19.6 50.8 10.0 0.0 0.3 100.0 6079 Middle 18.8 19.8 49.2 11.9 0.0 0.3 100.0 6035 Fourth 18.3 25.7 45.8 9.8 0.0 0.3 100.0 6004 Richest 27.2 43.0 24.8 4.4 0.0 0.7 100.0 5317 Total 23.1 25.6 41.5 9.4 0.0 0.4 100.0 29518 Malaria Malaria is a leading cause of death of children under age five in Kenya, and more so in the Nyanza province where transmission occurs throughout the year. It also contributes to anaemia in children and is a common cause of school absenteeism. Preventive measures, especially the use of mosquito nets treated with insecticide (ITNs), can dramatically reduce malaria mortality rates among children. In areas where malaria is common, international recommendations suggest treating any fever in children as if it were malaria and immediately giving the child a full course of recommended anti-malarial tablets. Children with severe malaria symptoms, such as fever or convulsions, should be taken to a health facility. Also, children recovering from malaria should be given extra liquids and food and, for younger children, should continue breastfeeding. Child Health 54 Table CH.11: Household availability of insecticide treated nets and protection by a vector control methods Percentage of households with at least one mosquito net, percentage of households with at least one long- lasting treated net, percentage of households with at least one insecticide treated net (ITN) and percentage of households which either have at least one ITN or have received spraying through an indoor residual spraying (IRS) campaign in the last 12 months, Nyanza Province, Kenya, 2011 Percentage of households with at least one mosquito net Percentage of households with at least one long- lasting treated net Percentage of households with at least one ITN [1] Percentage of households with at least one ITN or received IRS during the last 12 months [2] Number of households County Siaya 94.6 89.7 92.7 92.8 1209 Kisumu 92.0 84.1 88.9 92.5 1261 Homa Bay 94.0 90.4 92.3 94.4 1089 Migori 89.9 87.1 89.5 94.9 1128 Kisii 94.0 91.3 92.7 93.2 1483 Nyamira 92.6 91.7 92.1 93.0 657 Area Rural 93.7 90.2 92.2 94.4 5751 Urban 88.7 82.1 86.8 88.6 1077 Education of household head None 91.4 88.3 90.0 92.0 1430 Primary 92.3 88.4 90.7 93.1 3691 Secondary + 95.6 90.8 94.1 95.6 1681 Missing/DK (95.4) (74.6) (79.0) (91.4) 26 Wealth index quintiles Poorest 90.4 87.6 89.3 92.1 1347 Second 93.4 89.4 91.4 93.8 1311 Middle 94.0 90.3 92.5 94.8 1319 Fourth 93.3 89.8 92.3 94.0 1340 Richest 93.6 87.6 91.3 92.7 1510 92.9 88.9 91.4 93.5 6828 [1] MICS indicator 3.12, [2] MICS indicator 3.13 ( ) Based on 25-49 unweighted cases. The Nyanza Province MICS survey incorporated questions on the availability and use of bed nets, both at household level and among children under five years of age, as well as anti-malarial treatment, intermittent preventive therapy for malaria and indoor residual spraying of households. Availability of Insecticide Treated Nets (ITN) by selected household characteristics is shown in Table CH.11. In Nyanza province the survey results indicate that 91 per cent of households have at least one insecticide treated net (Table CH.11). ITN ownership is equally high in all households irrespective of the household wealth index. The differentials across other background characteristics are largely comparable. Results indicate that 81 per cent of children under the age of five slept under any mosquito net the night prior to the survey and 78 per cent slept under an insecticide treated net (Table CH.12). There were no significant gender disparities in ITN use among children under five. The proportion of children sleeping under an ITN drops with increasing age of the child, and increases with improving levels of household wealth index. Child Health 55 Table CH.12: Children sleeping under mosquito nets Percentage of children age 0-59 months who slept under a mosquito net during the previous night, by type of net, Nyanza Province, Kenya, 2011 Percentage of children age 0-59 who stayed in the household the previous night Number of children age 0-59 months Percentage of children who: Slept under any mosquito net [1] Percentage of children who: Slept under an insecticide treated net [2] Number of children age 0-59 months who slept in the household the previous night Percentage of children who slept under an ITN living in households with at least one ITN Number of children age 0-59 living in households with at least one ITN Sex Male 100.0 2559 80.6 77.4 2559 82.2 2409 Female 100.0 2486 80.4 78.5 2486 82.6 2362 County Siaya 100.0 809 83.1 79.6 809 82.6 780 Kisumu 100.0 861 83.6 77.8 861 84.1 796 Homa Bay 100.0 868 78.8 76.8 868 82.2 810 Migori 100.0 930 77.5 76.7 930 81.5 875 Kisii 100.0 1135 80.3 78.6 1135 81.9 1088 Nyamira 100.0 442 80.1 78.2 442 81.9 422 Area Rural 100.0 4429 80.5 77.9 4429 82.2 4198 Urban 100.0 616 80.7 77.9 616 83.7 573 Age 0-11 100.0 1002 84.2 82.3 1002 86.1 959 12-23 100.0 868 86.3 84.4 868 88.2 830 24-35 100.0 1047 81.5 78.6 1047 83.3 988 36-47 100.0 1094 76.9 73.8 1094 78.9 1024 48-59 100.0 1034 74.9 71.8 1034 76.5 971 Mother’s education None 100.0 345 78.9 75.1 345 80.4 322 Primary 100.0 3523 79.5 77.4 3523 81.9 3329 Secondary+ 100.0 1178 84.2 80.5 1178 84.6 1120 Wealth index quintiles Poorest 100.0 1168 73.0 71.6 1168 77.1 1085 Second 100.0 1054 81.0 77.5 1054 82.6 988 Middle 100.0 985 82.5 79.8 985 83.3 944 Fourth 100.0 944 83.3 80.8 944 84.5 902 Richest 100.0 894 84.7 81.4 894 85.5 851 100.0 5045 80.5 77.9 5045 82.4 4771 [1] MICS indicator 3.14 [2] MICS indicator 3.15; MDG indicator 6.7 Table CH.13 presents the proportion of pregnant women who slept under a mosquito net during the previous night by selected characteristics. About 81 per cent of pregnant women slept under any mosquito net the night prior to the survey and 77 per cent slept under an insecticide treated net. Surprisingly, the proportion of women sleeping under mosquito net does not increase with their level of education, but it increases with increasing levels of wealth index of the household. Child Health 56 Table CH.13: Pregnant women sleeping under mosquito nets Percentage of pregnant women who slept under a mosquito net during the previous night, by type of net, Nyanza Province, Kenya, 2011 Percentage of pregnant women who stayed in the household the previous night Number of pregnant women Percentage of pregnant women who: Slept under any mosquito net Percentage of pregnant women who: Slept under an insecticide treated net [1] Number of pregnant women who slept in the household the previous night Percentage of pregnant women who slept under an ITN, living in households with at least one ITN Number of pregnant women living in households with at least one ITN County Siaya 100.0 62 83.1 81.5 62 84.5 60 Kisumu 100.0 68 90.3 82.6 68 86.5 65 Homa Bay 100.0 57 76.7 74.2 57 83.9 51 Migori 100.0 62 81.2 79.1 62 88.4 56 Kisii 100.0 95 75.6 71.1 95 74.3 91 Nyamira 100.0 37 82.6 77.0 37 87.8 33 Area Rural 100.0 332 82.1 78.0 332 83.7 309 Urban (100.0) 50 (74.9) (72.0) 50 (78.6) 45 Age 15-19 100.0 68 61.0 57.2 68 61.8 63 20-24 100.0 126 88.3 83.6 126 88.8 119 25-29 100.0 102 83.8 78.3 102 85.8 93 30-34 100.0 49 82.2 82.2 49 (91.8) 44 35-39 (*) 24 (*) (*) 24 (*) 23 40-44 (*) 13 (*) (*) 13 (*) 13 Education None (*) 22 (*) (*) 22 (*) 20 Primary 100.0 255 78.9 75.9 255 82.4 235 Secondary + 100.0 104 84.0 78.5 104 82.5 99 Wealth index quintiles Poorest 100.0 92 75.3 73.3 92 78.3 86 Second 100.0 68 75.3 65.0 68 73.1 60 Middle 100.0 76 88.1 85.9 76 89.2 74 Fourth 100.0 75 80.6 77.4 75 84.8 69 Richest 100.0 70 87.5 84.4 70 89.8 66 Total 100.0 381 81.2 77.2 381 83.1 354 [1] MICS indicator 3.19 (*) Not shown based on less than 25 unweighted cases. ( ) Based on 25-49 unweighted cases. Table CH.14 shows information on malaria treatment of children with anti-malarial drugs. Questions on the prevalence and treatment of fever were asked for all children under age five. About one in five (22 per cent) of under five children were ill with fever in the two weeks prior to the survey (Table CH.14). There are regional differences in fever prevalence ranging from 29 per cent in Siaya County to 14 and 13 per cent in Kisii and Nyamira counties, respectively. However, no variations in fever prevalence are observed across gender, while the prevalences were 18 per cent for urban areas and 22 per cent for rural areas. Child Health 57 Ta b le C H .1 4: A nt i- m al ar ia l t re at m en t o f ch ild re n w it h an ti -m al ar ia l d ru g s P er ce nt ag e o f ch ild re n ag e 0- 59 m o nt hs w ho h ad f ev er in t he la st t w o w ee ks w ho r ec ei ve d a nt i- m al ar ia l d ru g s, N ya nz a P ro vi nc e, K en ya , 2 01 1 H ad a fe ve r in la st tw o w ee ks N um - b er o f ch ild re n ag e 0- 59 m on th s C hi ld re n w it h a fe ve r in t he la st t w o w ee ks w ho w er e tr ea te d w it h: N um b er of c hi l- d re n w ith fe ve r in la st t w o w ee ks A nt i- m al ar ia ls : S P / Fa ns id ar A nt i- m al ar ia ls : C hl or o- q ui ne A nt i- m al ar i- al s: A rm od i- aq ui ne A nt i- m al ar ia ls : Q ui ni ne A nt i- m al ar ia ls : A rt em is in in b as ed c om - b in at io ns A nt i- m al ar ia ls : O th er A nt i- m al ar ia l A nt i- m al ar ia ls : A ny a nt i- m al ar ia l d ru g [1 ] O th er m ed ic at io ns : P ar ac et am ol / P an ad ol / A ce ta m in o- p ha n O th er m ed - ic at io ns : A sp iri n O th er m ed - ic at io ns : Ib up ro fe n O th er m ed ic a- tio ns : O th er D on ’t kn ow P er ce nt ag e w ho t oo k an an ti- m al ar ia l d ru g sa m e or ne xt d ay [2 ] S ex M al e 21 .9 25 59 2. 8 1. 1 3. 8 3. 2 31 .3 5. 6 45 .9 58 .3 1. 5 5. 6 17 .3 3. 0 33 .0 56 0 Fe m al e 21 .3 24 86 4. 3 1. 8 3. 2 4. 1 35 .9 3. 1 48 .3 58 .3 3. 6 5. 8 17 .1 3. 9 32 .8 53 0 C o un ty S ia ya 29 .2 80 9 2. 5 1. 1 2. 1 3. 7 48 .3 0. 8 54 .8 61 .1 1. 6 5. 7 20 .8 0. 8 40 .0 23 6 K is um u 25 .6 86 1 4. 8 0. 5 1. 4 2. 5 38 .5 5. 6 51 .7 53 .5 2. 2 3. 0 11 .6 4. 5 36 .7 22 0 H om a B ay 27 .9 86 8 5. 0 1. 6 6. 3 2. 7 31 .8 6. 4 49 .8 57 .2 2. 4 5. 2 20 .4 3. 2 31 .6 24 2 M ig or i 19 .5 93 0 1. 2 3. 9 3. 5 6. 0 39 .8 3. 4 53 .4 70 .0 3. 2 7. 8 8. 8 2. 0 43 .1 18 2 K is ii 12 .9 11 35 3. 8 0. 0 2. 6 4. 5 11 .4 6. 2 27 .1 53 .7 2. 6 8. 6 23 .8 2. 6 14 .3 14 6 N ya m ira 14 .4 44 2 4. 0 1. 9 7. 2 2. 0 0. 8 4. 8 19 .7 45 .9 5. 5 4. 7 19 .8 16 .6 12 .6 64 A re a R ur al 22 .1 44 29 3. 5 1. 5 3. 7 3. 5 32 .9 4. 4 46 .5 57 .9 2. 7 5. 7 17 .4 3. 6 32 .3 97 9 U rb an 18 .0 61 6 3. 9 0. 8 1. 7 4. 6 38 .7 4. 3 51 .8 62 .4 0. 9 5. 8 15 .4 1. 8 38 .7 11 1 A g e 0- 11 17 .8 10 02 3. 6 1. 9 1. 6 4. 2 21 .3 5. 3 33 .8 63 .4 0. 7 4. 1 20 .2 5. 3 22 .6 17 9 12 -2 3 24 .8 86 8 3. 6 2. 2 3. 7 4. 9 31 .7 3. 7 47 .6 58 .3 3. 7 9. 7 17 .2 3. 2 34 .8 21 5 24 -3 5 21 .9 10 47 2. 1 0. 9 4. 2 3. 5 33 .5 6. 3 47 .4 56 .6 3. 7 3. 8 14 .2 2. 6 31 .3 23 0 36 -4 7 23 .2 10 94 2. 9 1. 6 4. 0 3. 2 42 .7 2. 9 54 .0 59 .5 2. 6 5. 7 20 .1 2. 5 40 .2 25 4 48 -5 9 20 .6 10 34 5. 9 0. 7 3. 6 2. 5 34 .7 4. 1 49 .1 54 .5 1. 4 5. 3 14 .4 4. 2 32 .7 21 3 M o th er ’s ed uc at io n N on e 18 .5 34 5 3. 7 2. 5 0. 0 3. 8 47 .4 4. 9 57 .6 58 .9 1. 1 6. 4 10 .3 8. 0 41 .4 64 P rim ar y 23 .2 35 23 3. 3 1. 4 4. 0 3. 7 35 .0 4. 3 48 .5 57 .8 2. 6 5. 3 15 .7 3. 4 34 .7 81 7 S ec on d ar y+ 17 .8 11 78 4. 4 1. 4 2. 8 3. 2 23 .5 4. 7 38 .4 60 .1 2. 8 7. 1 25 .0 2. 2 23 .7 20 9 W ea lt h in d ex q ui nt ile s P oo re st 20 .1 11 68 3. 6 1. 6 0. 6 3. 0 27 .4 1. 6 36 .9 56 .4 2. 1 8. 4 13 .8 4. 1 25 .6 23 5 S ec on d 23 .8 10 54 3. 7 2. 0 4. 4 2. 4 31 .7 5. 2 46 .3 57 .1 3. 2 6. 9 15 .7 3. 9 30 .2 25 1 M id d le 24 .2 98 5 3. 5 1. 5 4. 4 5. 2 36 .9 5. 8 53 .2 57 .5 3. 0 4. 3 15 .4 3. 7 33 .9 23 9 Fo ur th 21 .3 94 4 4. 6 0. 8 3. 6 3. 0 32 .2 6. 9 47 .2 60 .1 2. 0 3. 5 25 .7 2. 8 34 .7 20 1 R ic he st 18 .4 89 4 2. 0 1. 1 4. 8 4. 7 41 .7 2. 0 53 .7 61 .9 2. 0 4. 9 16 .4 2. 3 43 .9 16 5 To ta l 21 .6 50 45 3. 6 1. 5 3. 5 3. 6 33 .5 4. 4 47 .1 58 .3 2. 5 5. 7 17 .2 3. 4 32 .9 10 90 [1 ] M IC S in d ic at or 3 .1 8; M D G in d ic at or 6 .8 [2 ] M IC S in d ic at or 3 .1 7 Child Health 58 Further, all mothers with a child below five years who had fever during the two weeks prior to the survey and sought treatment were asked to report all of the medicines given to a child to treat the fever, this included both medicines given at home and medicines given or prescribed at a health facility. Overall, 47 per cent of children with fever in the last two weeks prior to the survey were treated with any anti- malarial drug and 33 per cent received anti-malarial drugs on the same day or the next day after onset of symptoms. “Appropriate” anti-malarial drugs include chloroquine, SP (sulfadoxine-pyrimethamine), artimisinin combination drugs, etc. (see table Ch.14). In Nyanza province, less than 2 per cent of children with fever were given chloroquine, and less than 4 per cent were given SP. Only 34 per cent received artemisinin combination therapy which is the currently recommended national therapy. A large proportion of children (over 60 per cent) were given other types of medicines that are not anti-malarials, including anti-pyretics such as paracetemol, aspirin, or ibuprofen. Overall, children with fever in Nyamira and Kisii counties, where malaria is also known to be prevalent, are less likely to have received any anti-malarial drug while those in Siaya, Kisumu, Migori and Homa Bay counties were more likely to receive any anti-malarial drug. The proportion receiving any anti-malarial drugs was 46 per cent among boys and 48 per cent among girls, while the proportion ranges from 58 per cent among children whose mothers have no education to 38 per cent for those with secondary or higher education levels. Pregnant women living in places where malaria is highly prevalent are four times more likely than other adults to get malaria and twice as likely to die of the disease. Once infected, pregnant women risk anaemia, premature delivery and stillbirth. Their babies are likely to be of low birth weight, which makes them unlikely to survive their first year of life. For this reason, steps are taken to protect pregnant women by distributing insecticide-treated mosquito nets and treatment during antenatal check-ups with drugs that prevent malaria infection (Intermittent preventive treatment or IPT). In Nyanza MICS, women were asked of the medicines they had received in their last pregnancy during the 2 years preceding the survey. Women are considered to have received intermittent preventive therapy if they received at least 2 doses of SP/Fansidar during the pregnancy. Details of Intermittent preventive treatment for malaria in pregnant women who gave birth in the two years preceding the survey is presented in Table CH.16. Nearly 70 per cent of mothers who delivered a child during the two year period preceding the survey received medicine to prevent malaria during pregnancy. Forty two per cent received SP/Fansidar at least once while 27 per cent received the same two or more times. About 65 per cent of mothers from the poorest wealth index households used medicine to prevent malaria during any ANC visit while pregnant, while the corresponding figure for those from the richest wealth index households is 72 per cent. Child Health 59 Table CH.16: Intermittent preventive treatment for malaria Percentage of women age 15-49 years who had a live birth during the two years preceding the survey and who received intermittent preventive treatment (IPT) for malaria during pregnancy at any antenatal care visit, Nyanza Province, Kenya, 2011 Percentage of women who received antenatal care (ANC) Number of women who gave birth in the preceding two years Percentage of pregnant women who took: Number of women who had a live birth in the last two years and who received antenatal care Any medicine to prevent malaria at any ANC visit during pregnancy SP/Fansidar at least once SP/Fansidar two or more times [1] County Siaya 91.2 318 68.2 42.5 26.7 290 Kisumu 95.1 318 71.6 26.8 18.5 302 Homa Bay 92.6 316 64.7 44.1 24.9 293 Migori 87.1 326 70.7 45.0 32.7 284 Kisii 89.6 370 70.4 55.7 37.9 331 Nyamira 94.2 164 69.1 27.1 13.5 154 Area Rural 90.8 1572 68.4 41.5 26.9 1427 Urban 95.0 240 74.0 42.1 27.0 228 Education None 87.6 89 71.4 50.2 26.0 78 Primary 90.8 1287 68.0 40.5 25.7 1169 Secondary + 93.6 436 72.1 42.9 30.7 408 Wealth index quintiles Poorest 85.9 415 65.1 42.3 27.7 357 Second 92.5 355 73.3 44.8 30.3 329 Middle 92.8 354 67.1 39.0 22.6 329 Fourth 92.3 345 68.7 40.3 26.3 319 Richest 94.2 341 72.0 41.4 27.7 322 91.3 1812 69.2 41.6 26.9 1655 [1] MICS indicator 3.20 Child Health 60 VII. Water and Sanitation Safe drinking water is a basic necessity for good health. Unsafe drinking water can be a significant carrier of diseases such as trachoma, cholera, typhoid, and schistosomiasis (or snail fever). Drinking water can also be polluted by chemical, physical, and radiological contaminants with harmful effects on human health. In addition to its association with disease, access to drinking water may be particularly important for women and children, especially in rural areas, who bear the primary responsibility of carrying water, often over long distances. The MDG goal is to reduce by half, between 1990 and 2015, the proportion of people without sustainable access to safe drinking water and basic sanitation. The World Fit for Children goal calls for a reduction in the proportion of households without access to hygienic sanitation facilities and affordable and safe drinking water by at least one-third. The list of indicators used in MICS is as follows: Water • Use of improved drinking water sources • Use of adequate water treatment method • Time to source of drinking water • Person collecting drinking water Sanitation • Use of improved sanitation facilities • Sanitary disposal of child’s faeces For more details on water and sanitation and to access some reference documents, please visit the UNICEF childinfo website http://www.childinfo.org/wes.html. Use of Improved Water Sources The distribution of the population by source of drinking water is shown in Table WS.1 and Figure WS.1. The population using improved sources of drinking water are those using any of the following types of supply: piped water (into dwelling, compound, yard or plot, piped to neighbourhood, piped to kiosk, public tap/ standpipe), tube well/borehole, protected well, protected spring, and rainwater collection. Bottled water is considered as an improved water source only if the household is using an improved water source for other purposes, such as handwashing and cooking. Water and Sanitation 61 Overall, 48 per cent of the population is using an improved source of drinking water – 62 per cent in urban areas and 46 per cent in rural areas. The source of drinking water for the population varies strongly by counties (Table WS.1). The situation in in Migori and Homa Bay counties is considerably worse than in other counties; less than 35 per cent of the population in these counties gets its drinking water from an improved source. In Kisumu, use of piped water is more common than in all other counties. In Kisii and Nyamira, the most important source of drinking water is protect springs while in Homa Bay and Migori counties, more households reportedly use surface water (an unimproved source) as their main source of drinking water. The differentials by wealth index of the household are in the expected direction with respect to the proportion of population using an improved source of drinking water. Among the richest households, 64 per cent are using an improved source of drinking water, compared to 38 among the poorest households. Water and Sanitation Unimproved water sources. Water on premises 1.2% 0.5% Improved water sources. Water on premises Unimproved water sources. Less than 30 minutes Improved water sources. Less than 30 minutes Unimproved water sources. 30 minutes or more Improved water sources. 30 minutes or more Missing/DK Missing/DK 22.8% 22.2% 13.2% 22.5% 17.6% Figure WS.1 Time to source of drinking water, Nyanza Province, Kenya, 2011 62 Water and Sanitation Ta b le W S .1 : U se o f im p ro ve d w at er s o ur ce s P er ce nt ag e d is tr ib ut io n o f ho us eh o ld p o p ul at io n ac co rd in g t o m ai n so ur ce o f d ri nk in g w at er a nd p er ce nt ag e o f ho us eh o ld p o p ul at io n us in g im p ro ve d d ri nk in g w at er s o ur ce s, N ya nz a P ro vi nc e, 20 11 M ai n so ur ce o f d rin ki ng w at er To ta l P er ce nt - ag e us in g im p ro ve d so ur ce s of d rin ki ng w at er [1 ] N um b er o f ho us eh ol d m em b er s Im p ro ve d s ou rc es U ni m p ro ve d s ou rc es P ip ed w at er Tu b e- w el l/ b or e- ho le P ro te ct - ed w el l P ro te ct ed sp rin g R ai n- w at er co lle c- tio n B ot tle d w at er * P ip ed in to d w el l- in g P ip ed in to co m - p ou nd , ya rd o r p lo t P ip ed t o ne ig hb or P ip ed to w at er ki os k P ub lic ta p / st an d p ip e U np ro - te ct ed w el l U np ro - te ct ed sp rin g Ta nk er tr uc k C ar t w ith ta nk / d ru m S ur fa ce w at er B ot tle d w at er * O th er C o un ty S ia ya 0. 6 2. 9 4. 8 7. 5 5. 0 10 .0 6. 8 15 .3 3. 9 0. 0 7. 8 6. 0 0. 2 0. 0 29 .2 0. 0 0. 0 10 0. 0 51 .7 49 81 K is um u 6. 3 5. 0 10 .8 6. 7 13 .8 2. 8 7. 6 1. 3 7. 8 0. 2 10 .9 1. 2 0. 2 1. 5 23 .9 0. 0 0. 1 10 0. 0 48 .4 52 60 H om a B ay 0. 8 1. 5 2. 3 1. 6 7. 2 7. 2 12 .8 3. 1 5. 3 0. 0 7. 6 3. 9 0. 0 0. 2 46 .4 0. 0 0. 0 10 0. 0 34 .7 50 10 M ig or i 0. 4 1. 2 0. 9 1. 6 0. 5 9. 0 6. 7 4. 1 7. 7 0. 0 13 .7 11 .2 0. 0 0. 0 42 .5 0. 1 0. 0 10 0. 0 31 .7 53 33 K is ii 0. 5 0. 6 0. 3 0. 0 1. 7 0. 0 2. 6 53 .5 4. 0 0. 0 2. 2 25 .8 0. 0 0. 0 8. 8 0. 0 0. 0 10 0. 0 61 .5 68 51 N ya m ira 1. 2 4. 0 0. 3 0. 5 3. 9 0. 3 3. 9 49 .1 5. 4 0. 0 3. 5 22 .7 0. 0 0. 0 5. 1 0. 0 0. 2 10 0. 0 64 .6 30 04 R es id en ce R ur al 0. 4 1. 2 2. 3 1. 7 4. 0 4. 9 7. 1 22 .9 5. 7 0. 0 8. 0 12 .9 0. 0 0. 1 28 .7 0. 0 0. 0 10 0. 0 46 .2 26 37 9 U rb an 9. 7 9. 5 9. 4 11 .5 13 .0 4. 9 3. 7 7. 4 5. 5 0. 3 5. 4 5. 0 0. 3 1. 6 12 .0 0. 1 0. 1 10 0. 0 62 .0 40 60 E d uc at io n o f ho us eh o ld h ea d N on e 5. 4 3. 4 3. 6 2. 1 4. 5 5. 4 6. 2 21 .3 7. 4 0. 2 7. 4 7. 7 0. 2 0. 7 24 .4 0. 0 0. 1 10 0. 0 54 .9 52 41 P rim ar y 0. 3 1. 4 3. 2 3. 1 5. 3 5. 0 7. 3 19 .2 4. 3 0. 0 8. 5 12 .0 0. 0 0. 2 30 .2 0. 0 0. 0 10 0. 0 43 .8 17 17 5 S ec on d ar y+ 1. 8 3. 5 3. 4 3. 5 5. 5 4. 4 5. 6 24 .1 7. 2 0. 0 6. 1 13 .9 0. 0 0. 3 20 .1 0. 1 0. 1 10 0. 0 53 .7 79 00 M is si ng /D K 2. 9 10 .3 0. 0 0. 0 4. 5 10 .7 13 .9 13 .7 0. 0 8. 0 4. 7 25 .9 0. 0 0. 0 37 .5 0. 0 0. 0 10 0. 0 56 .0 12 3 W ea lt h in d ex q ui nt ile P oo re st 0. 0 0. 0 0. 8 0. 1 1. 4 3. 6 6. 2 27 .5 0. 3 0. 0 6. 8 15 .8 0. 0 .0 37 .5 0. 0 0. 0 10 0. 0 38 .4 60 84 S ec on d 0. 0 0. 0 1. 8 1. 0 3. 0 4. 6 6. 4 28 .6 2. 5 0. 0 7. 5 16 .6 0. 0 0. 0 28 .0 0. 0 0. 1 10 0. 0 44 .8 60 92 M id d le 0. 0 0. 6 3. 2 2. 5 6. 3 4. 6 7. 8 21 .9 5. 2 0. 0 9. 5 11 .2 0. 0 0. 0 27 .3 0. 0 0. 0 10 0. 0 45 .8 60 87 Fo ur th 0. 4 1. 9 5. 1 4. 2 6. 7 6. 3 7. 7 16 .7 6. 6 0. 0 9. 0 8. 4 0. 1 0. 5 26 .3 0. 0 0. 0 10 0. 0 49 .0 60 89 R ic he st 7. 6 9. 2 5. 5 7. 1 8. 7 5. 5 5. 3 9. 4 13 .6 0. 3 5. 5 7. 1 0. 3 1. 0 13 .4 0. 1 0. 1 10 0. 0 63 .5 60 88 To ta l 1. 6 2. 3 3. 3 3. 0 5. 2 4. 9 6. 7 20 .8 5. 6 0. 1 7. 7 11 .8 0. 1 0. 3 26 .5 0. 0 0. 0 10 0. 0 48 .3 30 43 9 [1 ] M IC S in d ic at or 4 .1 ; M D G in d ic at or 7 .8 *H ou se ho ld s us in g b ot tle d w at er a s th e m ai n so ur ce o f d rin ki ng w at er a re c la ss ifi ed in to im p ro ve d o r un im p ro ve d d rin ki ng w at er u se rs a cc or d in g to t he w at er s ou rc e us ed fo r ot he r p ur p os es s uc h as c oo ki ng a nd h an d w as hi ng 63 Table 7.2 presents use of in-house water treatment by selected characteristics in Nyanza province. The table shows water treatment by all households and the percentage of household members living in households using unimproved water sources but using appropriate water treatment methods. Households were asked of ways they may be treating water at home to make it safer to drink were boiling, adding bleach or chlorine, using a water filter, and using solar disinfection are considered as proper treatment of drinking water. Water and Sanitation 64 Ta b le W S .2 : H o us eh o ld w at er t re at m en t P er ce nt ag e o f ho us eh o ld p o p ul at io n b y d ri nk in g w at er t re at m en t m et ho d u se d i n th e ho us eh o ld , an d f o r ho us eh o ld m em b er s liv in g i n ho us eh o ld s w he re a n un im p ro ve d d ri nk in g w at er s o ur ce is u se d , t he p er ce nt ag e w ho a re u si ng a n ap p ro p ri at e tr ea tm en t m et ho d , N ya nz a P ro vi nc e, K en ya , 2 01 1 W at er t re at m en t m et ho d u se d in t he h ou se ho ld N on e B oi l A d d b le ac h / ch lo rin e S tr ai n th ro ug h a cl ot h U se w at er fil te r S ol ar d is in fe ct io n Le t it st an d an d se tt le O th er D on ’t kn ow N um b er o f ho us eh ol d m em b er s P er ce nt ag e of h ou se ho ld m em b er s in h ou se ho ld s us in g un im p ro ve d d rin ki ng w at er s ou rc es a nd u si ng a n ap p ro p ria te w at er t re at m en t m et ho d [1 ] N um b er o f h ou se ho ld m em b er s in ho us eh ol d s us in g un im p ro ve d d rin ki ng w at er s ou rc es C o un ty S ia ya 27 .8 16 .7 61 .4 6. 0 0. 5 0. 5 0. 5 0. 3 0. 0 49 81 76 .2 21 59 K is um u 27 .2 23 .4 54 .2 2. 8 1. 0 0. 0 2. 0 3. 3 0. 0 52 60 71 .1 19 89 H om a B ay 27 .4 16 .3 58 .4 3. 8 0. 7 0. 3 1. 5 0. 4 0. 0 50 10 72 .5 29 14 M ig or i 41 .1 25 .7 42 .8 5. 9 1. 4 0. 2 5. 3 0. 4 0. 0 53 33 55 .8 36 18 K is ii 66 .9 26 .7 8. 1 1. 0 0. 0 0. 0 0. 1 0. 6 0. 0 68 51 31 .9 25 24 N ya m ira 45 .4 46 .7 9. 6 .8 0. 9 0. 0 3. 3 0. 4 0. 2 30 04 55 .0 94 6 A re a R ur al 41 .7 24 .2 38 .4 3. 5 0. 6 0. 2 1. 9 0. 8 0. 0 26 37 9 59 .9 13 13 3 U rb an 32 .5 27 .5 44 .8 3. 0 1. 3 0. 0 2. 1 1. 5 0. 0 40 60 64 .3 10 17 E d uc at io n o f ho us eh o ld h ea d N on e 37 .0 30 .5 36 .5 5. 0 1. 0 0. 1 2. 0 0. 8 0. 0 52 41 62 .3 21 27 P rim ar y 43 .3 20 .2 40 .1 3. 3 0. 6 0. 3 1. 9 0. 9 0. 0 17 17 5 57 .9 87 51 S ec on d ar y + 36 .7 30 .6 39 .3 2. 6 0. 6 0. 1 2. 1 1. 1 0. 0 79 00 65 .3 32 28 M is si ng /D K 42 .9 7. 1 40 .9 9. 1 0. 0 0. 0 0. 0 0. 0 0. 0 12 3 (* ) 44 W ea lt h in d ex q ui nt ile s P oo re st 54 .5 17 .1 30 .1 2. 9 0. 4 0. 4 2. 1 0. 7 0. 0 60 84 51 .8 36 57 S ec on d 46 .2 23 .3 33 .6 3. 6 0. 6 0. 0 1. 5 0. 8 0. 0 60 92 55 .2 31 81 M id d le 42 .6 21 .0 40 .2 3. 8 0. 5 0. 1 2. 4 0. 8 0. 1 60 87 61 .4 29 18 Fo ur th 34 .1 26 .4 45 .4 3. 6 0. 6 0. 2 1. 6 1. 4 0. 0 60 89 66 .4 26 99 R ic he st 25 .2 35 .2 47 .2 3. 4 1. 3 0. 1 2. 2 1. 0 0. 0 60 88 75 .6 16 95 To ta l 40 .5 24 .6 39 .3 3. 5 0. 7 0. 2 2. 0 0. 9 0. 0 30 43 9 60 .2 14 15 0 [1 ] M IC S in d ic at or 4 .2 Water and Sanitation 65 Roughly, three out of five individuals are using unimproved drinking water in Nyanza Province drink appropriately treated water. The proportion of household members treating the water increases with household wealth. For example, 76 per cent of household population from the richest quintile use unimproved drinking water sources and apply an appropriate water treatment method, compared to only 52 per cent among those from the poorest wealth quintile. Adding bleach chlorine is the most common water treatment method reported at 39 per cent and another 25 per cent of the household population boil the water. The proportion of household population using bleach/chlorine as a means for water treatment increases with improving wealth and with the level of education of the head of the household. The amount of time it takes to obtain water is presented in Table WS.3 and the person who usually collected the water in Table WS.4. Note that these results refer to one roundtrip from home to drinking water source. Information on the number of trips made in one day was not collected. Table WS.3 shows that for about 14 per cent of households, the drinking water source is on the premises and this consists mostly of improved drinking water sources. For a about 23 per cent of all households, it takes less than 30 minutes to get to an improved water source and bring water , with an almost equal proportion taking the same time to collect water from an unimproved water source. About 18 and 22 per cent of households spend 30 minutes or more for this purpose on collecting from an improved and unimproved water sources, respectively. In rural areas more households spend time in collecting water compared to those in urban areas. Poor households spend more time collecting water, and this is mostly from unimproved drinking water sources. A lower percentage of households population from Kisumu County (25 per cent) spend more than 30 minutes to go to the source of drinking water, than in all other counties (Homa Bay- 50 per cent; Nyamira- 49 per cent). Water and Sanitation 66 Ta b le W S .3 : T im e to s o ur ce o f d ri nk in g w at er P er ce nt ag e d is tr ib ut io n o f ho us eh o ld p o p ul at io n ac co rd in g t o t im e to g o t o s o ur ce o f d ri nk in g w at er , g et w at er a nd r et ur n, f o r us er s o f im p ro ve d a nd u ni m p ro ve d d ri nk in g w at er s o ur ce s, N ya nz a P ro vi nc e, K en ya , 2 01 1 Ti m e to s ou rc e of d rin ki ng w at er To ta l N um b er o f ho us eh ol d m em b er s U se rs o f i m p ro ve d d rin ki ng w at er s ou rc es U se rs o f u ni m p ro ve d d rin ki ng w at er s ou rc es W at er o n p re m is es Le ss t ha n 30 m in ut es 30 m in ut es or m or e M is si ng / D K W at er o n p re m is es Le ss t ha n 30 m in ut es 30 m in ut es o r m or e M is si ng / D K C o un ty S ia ya 12 .1 25 .5 18 .9 0. 2 0. 1 20 .1 22 .9 0. 2 10 0. 0 49 81 K is um u 28 .2 23 .0 10 .3 0. 6 1. 3 21 .7 14 .3 0. 4 10 0. 0 52 60 H om a B ay 11 .2 13 .0 17 .3 0. 3 1. 1 24 .2 32 .5 0. 4 10 0. 0 50 10 M ig or i 13 .1 13 .8 5. 3 0. 0 2. 8 34 .3 30 .1 0. 6 10 0. 0 53 33 K is ii 4. 6 32 .9 25 .5 0. 1 0. 9 19 .0 16 .8 0. 1 10 0. 0 68 51 N ya m ira 11 .5 24 .3 32 .6 0. 1 0. 9 14 .7 15 .9 0. 0 10 0. 0 30 04 A re a R ur al 9. 5 21 .3 19 .2 0. 2 0. 9 24 .2 24 .5 0. 2 10 0. 0 26 37 9 U rb an 37 .1 30 .2 7. 5 0. 2 3. 0 13 .7 7. 5 0. 9 10 0. 0 40 60 E d uc at io n o f ho us eh o ld h ea d N on e 21 .1 21 .0 16 .9 0. 4 1. 1 20 .9 18 .2 0. 4 10 0. 0 52 41 P rim ar y 9. 2 21 .7 18 .0 0. 2 1. 2 24 .0 25 .7 0. 1 10 0. 0 17 17 5 S ec on d ar y + 16 .4 25 .3 17 .2 0. 2 1. 3 21 .4 17 .5 0. 7 10 0. 0 79 00 M is si ng /D K 24 .7 19 .8 19 .5 0. 0 0. 0 22 .0 14 .1 0. 0 10 0. 0 12 3 W ea lt h in d ex q ui nt ile s P oo re st 1. 5 19 .8 18 .5 0. 2 0. 5 26 .9 32 .7 0. 1 10 0. 0 60 84 S ec on d 3. 9 23 .2 20 .5 0. 2 0. 7 24 .0 27 .5 0. 0 10 0. 0 60 92 M id d le 8. 1 21 .8 21 .8 0. 4 0. 7 24 .2 22 .7 0. 3 10 0. 0 60 87 Fo ur th 14 .5 23 .7 17 .2 0. 2 1. 4 22 .8 19 .8 0. 3 10 0. 0 60 89 R ic he st 37 .7 24 .1 10 .2 0. 2 2. 7 15 .9 8. 5 0. 8 10 0. 0 60 88 To ta l 13 .2 22 .5 17 .6 0. 2 1. 2 22 .8 22 .2 0. 3 10 0. 0 30 43 9 (* ) N ot s ho w n b as ed o n le ss t ha n 25 u nw ei gh te d c as es Water and Sanitation 67 Details on the person who usually collected the water are presented in Table WS.4. In most households, an adult female (79 per cent) is usually the person collecting the water, when the source of drinking water is not on the premises. Adult men collect water in only 12 per cent of cases, while for the rest of the households, female or male children under age 15 collect water (9 per cent). The proportion of households where an adult women collects water drops with increasing levels of households wealth index, and this proportion is lower in urban than in rural areas. At the County levels, an adult woman is likely to be responsible for collecting water if she resides in Homa Bay or Migori counties, when compared to other counties. Water and Sanitation 68 Ta b le W S .4 : P er so n co lle ct in g w at er P er ce nt ag e o f ho us eh o ld s w it ho ut d ri nk in g w at er o n p re m is es , a nd p er ce nt ag e d is tr ib ut io n o f ho us eh o ld s w it ho ut d ri nk in g w at er o n p re m is es a cc o rd in g t o t he p er so n us ua lly c o lle ct in g d ri nk in g w at er u se d in t he h o us eh o ld , N ya nz a P ro vi nc e, K en ya , 2 01 1 P er ce nt ag e of ho us eh ol d s w ith ou t d rin ki ng w at er o n p re m is es N um b er o f ho us eh ol d s P er so n us ua lly c ol le ct in g d rin ki ng w at er N um b er o f h ou se ho ld s w ith ou t d rin ki ng w at er on p re m is es A d ul t w om an A d ul t m an Fe m al e ch ild (u nd er 1 5) M al e ch ild (u nd er 1 5) D K M is si ng To ta l C o un ty S ia ya 91 .5 12 09 74 .2 18 .1 4. 6 2. 9 0. 0 0. 2 10 0. 0 11 62 K is um u 81 .5 12 61 74 .0 20 .3 4. 1 1. 6 0. 1 0. 0 10 0. 0 11 23 H om a B ay 88 .6 10 89 84 .5 7. 7 5. 5 2. 0 0. 1 0. 2 10 0. 0 10 59 M ig or i 83 .4 11 28 87 .8 6. 9 3. 7 1. 1 0. 0 0. 6 10 0. 0 11 13 K is ii 93 .8 14 83 78 .2 10 .0 9. 1 2. 5 0. 1 0. 1 10 0. 0 14 65 N ya m ira 86 .3 65 7 74 .3 9. 5 11 .5 4. 4 0. 1 0. 2 10 0. 0 61 9 A re a R ur al 91 .2 57 51 80 .2 10 .5 6. 6 2. 5 0. 1 0. 1 10 0. 0 56 48 U rb an 69 .8 10 77 69 .7 25 .3 3. 3 1. 2 0. 0 0. 6 10 0. 0 89 3 E d uc at io n o f ho us eh o ld h ea d N on e 82 .3 14 30 69 .9 16 .4 9. 5 4. 0 0. 1 0. 0 10 0. 0 13 15 P rim ar y 91 .8 36 91 81 .5 10 .7 5. 6 2. 0 0. 1 0. 1 10 0. 0 36 18 S ec on d ar y + 84 .1 16 81 80 .2 13 .0 4. 8 1. 5 0. 0 0. 5 10 0. 0 15 85 M is si ng /D K (* ) 24 (* ) (* ) (* ) (* ) (* ) (* ) (* ) 23 W ea lt h in d ex q ui nt ile s P oo re st 98 .9 13 47 82 .3 6. 1 8. 6 2. 9 0. 0 0. 1 10 0. 0 13 47 S ec on d 96 .3 13 11 82 .6 6. 9 7. 7 2. 6 0. 1 0. 1 10 0. 0 13 11 M id d le 92 .8 13 19 79 .0 12 .4 5. 6 2. 5 0. 1 0. 3 10 0. 0 13 13 Fo ur th 89 .3 13 40 78 .8 14 .7 4. 6 2. 0 0. 0 0. 0 10 0. 0 13 10 R ic he st 65 .0 15 10 69 .6 24 .9 3. 7 1. 1 0. 1 0. 4 10 0. 0 12 62 To ta l 87 .8 68 28 78 .9 12 .4 6. 2 2. 3 0. 1 0. 2 10 0. 0 65 41 (* ) N ot s ho w n, b as ed o n le ss t ha n 25 u nw ei gh te d c as es Water and Sanitation 69 Use of Improved Sanitation Facilities Inadequate disposal of human excreta and personal hygiene is associated with a range of diseases including diarrhoeal diseases and polio. An improved sanitation facility is defined as one that hygienically separates human excreta from human contact. Improved sanitation can reduce diarrheal disease by more than a third, and can significantly lessen the adverse health impacts of other disorders responsible for death and disease among millions of children in developing countries. Improved sanitation facilities for excreta disposal include flush or pour flush to a piped sewer system, septic tank, or latrine; ventilated improved pit latrine, pit latrine with slab, and composting toilet. Information regarding sanitation by education of the household head, wealth index and counties is shown in Table WS.5. About 32 per cent of households in Nyanza Province use improved sanitation facilities. Use of improved sanitation facilities is strongly correlated with urban rural residence and household wealth index. For example, 64 per cent of households living in urban areas use improved sanitation compared with 28 per cent for rural households. Similarly, 74 per cent of households from the richest household wealth quintile use improved sanitation facilities, compared to less than 4 per cent among those from the poorest wealth quintile. Pit latrines with slab are the most commonly used facility among the improved facilities with 22 per cent of the population in Nyanza Province using them. However, majority of household members use pit latrines without slab or an open pit (53 per cent). In rural areas, 20 per cent of the population use a pit latrine with a slab which is an improved sanitation facility, while 56 per cent of the population use pit latrines without slabs/open pit which is an unimproved form of sanitation facility. In rural areas 16 per cent of the population have no sanitation facilities or use the bush/field. In urban areas, about one third (34 per cent) of the population use pit latrine with slab, with a comparable proportion (32 per cent) using pit latrine without slab/open pit. Across counties, the proportion of population without facilities is highest in Homabay (34 per cent) and Migori (26 per cent) counties. Water and Sanitation 70 Ta b le W S .5 : T yp es o f sa ni ta ti o n fa ci lit ie s P er ce nt ag e d is tr ib ut io n o f ho us eh o ld p o p ul at io n ac co rd in g t o t yp e o f to ile t fa ci lit y us ed b y th e ho us eh o ld , N ya nz a P ro vi nc e, K en ya , 2 01 1 Im p ro ve d s an ita tio n fa ci lit y U ni m p ro ve d s an ita tio n fa ci lit y N o fa ci lit ie s or b us h or fi el d or o ce an To ta l N um b er o f ho us eh ol d m em b er s Fl us h to p ip ed se w er sy st em Fl us h to se p tic ta nk Fl us h to p it (la tr in e) Fl us h to so m e- w he re el se Fl us h to un kn ow n p la ce /n ot su re /D K w he re Ve nt ila te d Im p ro ve d P it la tr in e (V IP ) P it la tr in e w ith sl ab C om - p os tin g to ile t P it la tr in e w ith ou t sl ab / op en p it B uc ke t H an gi ng to ile t/ ha ng in g la tr in e O th er M is si ng C o un ty S ia ya 0. 0 0. 3 0. 0 0. 0 0. 0 7. 7 25 .7 0. 0 50 .4 0. 0 0. 0 0. 0 0. 0 15 .8 10 0. 0 49 81 K is um u 4. 2 3. 7 1. 3 1. 2 0. 0 6. 6 33 .3 4. 5 35 .4 0. 1 0. 0 0. 1 0. 1 9. 3 10 0. 0 52 60 H om a B ay 0. 9 0. 4 0. 9 0. 0 0. 2 5. 7 29 .3 0. 1 27 .6 0. 0 0. 3 0. 4 0. 2 33 .9 10 0. 0 50 10 M ig or i 0. 2 0. 3 0. 0 0. 0 0. 0 4. 9 15 .3 1. 2 51 .6 0. 0 0. 0 0. 1 0. 3 26 .1 10 0. 0 53 33 K is ii 0. 6 0. 4 0. 2 0. 2 0. 0 8. 0 9. 5 0. 0 80 .4 0. 0 0. 0 0. 3 0. 0 0. 4 10 0. 0 68 51 N ya m ira 0. 4 1. 0 0. 3 0. 1 0. 0 10 .9 20 .2 0. 2 65 .8 0. 0 0. 1 0. 1 0. 0 0. 8 10 0. 0 30 04 A re a R ur al 0. 0 0. 3 0. 3 0. 0 0. 0 6. 1 19 .6 1. 1 55 .7 0. 0 0. 1 0. 2 0. 1 16 .4 10 0. 0 26 37 9 U rb an 7. 9 5. 3 1. 6 2. 0 0. 3 13 .5 34 .4 0. 6 32 .2 0. 0 0. 0 0. 1 0. 0 2. 0 10 0. 0 40 60 E d uc at io n o f ho us eh o ld h ea d N on e 4. 2 3. 5 0. 3 0. 7 0. 0 11 .8 20 .4 1. 3 45 .1 0. 0 0. 0 0. 2 0. 0 12 .3 10 0. 0 52 41 P rim ar y 0. 1 0. 1 0. 4 0. 0 0. 1 4. 3 20 .6 1. 2 54 .4 0. 0 0. 1 0. 2 0. 2 18 .3 10 0. 0 17 17 5 S ec on d ar y + 1. 2 1. 2 0. 7 0. 4 0. 0 10 .1 24 .7 0. 5 53 .1 0. 0 0. 0 0. 1 0. 0 7. 8 10 0. 0 79 00 M is si ng /D K 0. 0 2. 9 0. 0 0. 0 2. 4 1. 8 14 .6 0. 0 68 .2 0. 0 0. 0 0. 0 0. 0 10 .1 10 0. 0 12 3 W ea lt h in d ex q ui nt ile s P oo re st 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 1. 5 1. 6 67 .1 0. 0 0. 0 0. 2 0. 1 29 .4 10 0. 0 60 84 S ec on d 0. 0 0. 0 0. 1 0. 0 0. 0 0. 3 8. 9 1. 0 70 .9 0. 0 0. 2 0. 2 0. 2 18 .4 10 0. 0 60 92 M id d le 0. 0 0. 0 0. 1 0. 0 0. 0 2. 8 26 .9 1. 3 54 .5 0. 1 0. 0 0. 1 0. 1 14 .0 10 0. 0 60 87 Fo ur th 0. 0 0. 0 0. 9 0. 0 0. 0 7. 7 32 .9 1. 2 48 .0 0. 0 0. 1 0. 3 0. 0 8. 8 10 0. 0 60 89 R ic he st 5. 4 4. 9 1. 2 1. 3 0. 1 24 .6 37 .8 0. 0 22 .3 0. 0 0. 1 0. 0 0. 1 2. 0 10 0. 0 60 88 To ta l 1. 1 1. 0 0. 5 0. 3 0. 0 7. 1 21 .6 1. 0 52 .6 0. 0 0. 1 0. 2 0. 1 14 .5 10 0. 0 30 43 9 (* ) N ot s ho w n, b as ed o n le ss t ha n 25 u nw ei gh te d c as es Water and Sanitation 71 Access to safe drinking-water and to basic sanitation is measured by the proportion of population using an improved sanitation facility. MDGs and WHO / UNICEF Joint Monitoring Programme (JMP) for Water Supply and Sanitation classify households as using an unimproved sanitation facility if they are using otherwise acceptable sanitation facilities but sharing a facility between two or more households or using a public toilet facility. As shown in Table WS.6, 32 per cent of the household population is using an improved sanitation facility. Use of a shared facility is more common among households using an unimproved facility. Only 15 per cent of households use an improved toilet facility that is not shared with other households. One in five household populations in urban areas use an improved not shared sanitation facility (22 per cent), while the corresponding figure is 14 per cent for rural areas. At the County level, use of improved sanitation facilities that is not shared is highest in Kisumu County (25 per cent) and Nyamira County (22 per cent). The population using an improved sanitation facility that is not shared increases with improving levels of the household wealth index. For example, 35 per cent among those from the richest household wealth index category use improved sanitation facility that is not shared while the proportion is less than 2 per cent among those from the poorest households. Water and Sanitation 72 Ta b le W S .6 : U se a nd s ha ri ng o f sa ni ta ti o n fa ci lit ie s P er ce nt ag e d is tr ib ut io n o f ho us eh o ld p o p ul at io n b y us e o f p ri va te a nd p ub lic s an it at io n fa ci lit ie s an d u se o f sh ar ed f ac ili ti es , b y us er s o f im p ro ve d a nd un im p ro ve d s an it at io n fa ci lit ie s, N ya nz a P ro vi nc e, K en ya , 2 01 1 U se rs o f i m p ro ve d s an ita tio n fa ci lit ie s U se rs o f u ni m p ro ve d s an ita tio n fa ci lit ie s O p en d ef ec at io n (n o fa ci lit y, b us h fie ld ) To ta l N um b er o f ho us eh ol d m em b er s N ot sh ar ed [1 ] P ub lic fa ci lit y S ha re d b y: 5 ho us eh ol d s or le ss S ha re d b y: M or e th an 5 ho us eh ol d s M is si ng / D K N ot sh ar ed P ub lic fa ci lit y S ha re d b y: 5 ho us eh ol d s or le ss S ha re d b y: M or e th an 5 ho us eh ol d s M is si ng / D K C o un ty S ia ya 9. 6 3. 7 17 .2 3. 1 0. 2 17 .0 3. 5 26 .3 3. 5 0. 2 15 .8 10 0. 0 49 81 K is um u 25 .0 4. 0 17 .3 8. 7 0. 0 14 .2 1. 9 15 .9 3. 6 0. 1 9. 3 10 0. 0 52 60 H om a B ay 14 .6 1. 2 16 .7 4. 7 0. 4 13 .2 1. 3 12 .6 1. 2 0. 2 33 .9 10 0. 0 50 10 M ig or i 10 .0 0. 9 7. 5 3. 5 0. 0 20 .9 1. 7 22 .6 6. 7 0. 1 26 .1 10 0. 0 53 33 K is ii 12 .7 1. 1 3. 2 1. 7 0. 2 60 .1 2. 1 16 .0 2. 3 0. 1 0. 4 10 0. 0 68 51 N ya m ira 21 .9 0. 2 8. 1 2. 6 0. 4 51 .0 0. 6 12 .8 1. 3 0. 3 0. 8 10 0. 0 30 04 A re a R ur al 14 .0 1. 4 10 .3 1. 6 0. 2 33 .2 1. 6 19 .0 2. 1 0. 2 16 .4 10 0. 0 26 37 9 U rb an 21 .8 5. 4 18 .4 19 .8 0. 2 6. 6 4. 0 11 .5 10 .3 0. 0 2. 0 10 0. 0 40 60 E d uc at io n o f ho us eh o ld h ea d N on e 24 .2 2. 1 12 .5 3. 4 0. 2 24 .7 1. 7 16 .9 2. 0 0. 1 12 .3 10 0. 0 52 41 P rim ar y 10 .3 1. 7 10 .7 3. 9 0. 1 30 .0 1. 9 19 .7 3. 1 0. 2 18 .3 10 0. 0 17 17 5 S ec on d ar y + 19 .4 2. 2 12 .2 4. 7 0. 3 31 .8 2. 1 15 .0 4. 2 0. 1 7. 8 10 0. 0 79 00 M is si ng /D K 8. 4 1. 8 9. 1 2. 4 0. 0 40 .7 3. 4 13 .6 10 .6 0. 0 10 .1 10 0. 0 12 3 W ea lt h in d ex q ui nt ile s P oo re st 1. 8 0. 1 1. 3 0. 0 0. 0 40 .8 1. 6 22 .9 2. 0 0. 1 29 .4 10 0. 0 60 84 S ec on d 5. 0 0. 2 4. 4 0. 6 0. 0 45 .5 1. 6 21 .2 2. 8 0. 3 18 .4 10 0. 0 60 92 M id d le 14 .2 2. 4 12 .9 1. 5 0. 1 29 .7 1. 8 19 .9 3. 3 0. 1 14 .0 10 0. 0 60 87 Fo ur th 19 .3 3. 3 15 .7 4. 0 0. 3 24 .9 2. 2 17 .5 3. 7 0. 3 8. 8 10 0. 0 60 89 R ic he st 34 .9 3. 7 22 .5 13 .9 0. 4 7. 2 2. 6 8. 4 4. 2 0. 0 2. 0 10 0. 0 60 88 To ta l 15 .1 1. 9 11 .4 4. 0 0. 2 29 .6 1. 9 18 .0 3. 2 0. 2 14 .5 10 0. 0 30 43 9 [1 ] M IC S in d ic at or 4 .3 ; M D G in d ic at or 7 .9 (* ) N ot s ho w n, b as ed o n le ss t ha n 25 u nw ei gh te d c as es Water and Sanitation 73 Safe disposal of a child’s faeces is disposing of the stool, by the child using a toilet or by rinsing the stool into a toilet or latrine. Disposal of faeces of children 0-2 years of age is presented in Table WS.7. In 73 per cent of the cases, the stool of children age 0-2 years are disposed safely and with the majority of caretakers reportedly putting the stool in the toilet/latrine as the mode of disposal. As expected, the proportion of households practicing safe disposal of children waste disposal increases with improving levels of household wealth index. Similarly safe disposal is 87 per cent among urban households, and 70 per cent in rural households. Water and Sanitation 74 T ab le W S .7 : D is p o sa l o f ch ild ’s f ae ce s P er ce nt ag e d is tr ib ut io n o f ch ild re n ag e 0- 2 ye ar s ac co rd in g t o p la ce o f d is p o sa l o f ch ild ’s f ae ce s, a nd t he p er ce nt ag e o f ch ild re n ag e 0- 2 ye ar s w ho se s to o ls w er e d is p o se d o f sa fe ly t he la st t im e th e ch ild p as se d s to o ls , N ya nz a P ro vi nc e, K en ya , 2 01 1 P la ce o f d is p os al o f c hi ld ’s fa ec es To ta l P er ce nt ag e of ch ild re n w ho se st oo ls w er e d is p os ed o f sa fe ly [1 ] N um b er o f ch ild re n ag e 0- 2 ye ar s C hi ld us ed to ile t/ la tr in e P ut / rin se d in to t oi le t or la tr in e P ut / rin se d in to d ra in or d itc h Th ro w n in to ga rb ag e (s ol id w as te ) B ur ie d Le ft in t he op en O th er D K M is si ng Ty p e o f sa ni ta to n fa ci lit y in d w el lin g Im p ro ve d 2. 3 83 .2 3. 5 2. 5 2. 4 2. 8 1. 2 0. 2 1. 9 10 0. 0 85 .5 90 2 U ni m p ro ve d 3. 6 81 .9 5. 6 2. 7 2. 0 1. 3 1. 5 0. 2 1. 3 10 0. 0 85 .5 15 14 O p en d ef ec at io n 0. 0 8. 1 11 .7 17 .6 33 .8 21 .3 4. 9 0. 3 2. 2 10 0. 0 8. 1 48 5 C o un ty S ia ya 0. 4 70 .9 6. 8 3. 5 8. 0 6. 7 0. 9 0. 2 2. 5 10 0. 0 71 .3 49 0 K is um u 0. 9 77 .4 6. 8 4. 8 5. 4 2. 1 2. 2 0. 2 0. 2 10 0. 0 78 .3 49 9 H om a B ay 2. 1 50 .8 4. 3 7. 3 15 .2 15 .3 1. 5 0. 6 2. 9 10 0. 0 52 .9 50 7 M ig or i 2. 6 56 .6 6. 4 11 .5 12 .7 4. 1 2. 9 0. 1 3. 0 10 0. 0 59 .2 52 1 K is ii 4. 5 84 .0 6. 7 1. 1 0. 6 0. 4 2. 6 0. 0 0. 1 10 0. 0 88 .5 63 3 N ya m ira 6. 3 84 .7 2. 9 1. 6 0. 9 1. 0 0. 9 0. 3 1. 4 10 0. 0 90 .9 25 1 A re a R ur al 2. 7 67 .7 6. 2 5. 3 8. 4 5. 7 2. 1 0. 3 1. 6 10 0. 0 70 .4 25 34 U rb an 1. 4 85 .8 4. 2 4. 1 0. 6 1. 1 0. 8 0. 0 1. 9 10 0. 0 87 .3 36 7 M o th er ’s e d uc at io n N on e 2. 2 81 .9 1. 8 5. 0 2. 5 1. 8 4. 0 0. 0 0. 8 10 0. 0 84 .1 17 1 P rim ar y 2. 0 64 .7 6. 9 6. 2 9. 4 6. 4 2. 0 0. 2 2. 1 10 0. 0 66 .7 20 21 S ec on d ar y+ 4. 3 82 .1 4. 3 2. 0 2. 9 2. 1 1. 3 0. 3 0. 7 10 0. 0 86 .4 70 9 W ea lt h in d ex q ui nt ile s P oo re st 2. 1 58 .6 7. 4 7. 5 11 .3 8. 7 3. 1 0. 1 1. 2 10 0. 0 60 .7 67 6 S ec on d 3. 0 64 .4 6. 7 6. 0 9. 1 6. 0 2. 6 0. 3 1. 8 10 0. 0 67 .5 58 3 M id d le 2. 4 67 .3 6. 7 5. 9 9. 2 4. 9 1. 7 0. 4 1. 6 10 0. 0 69 .7 54 9 Fo ur th 3. 1 75 .4 5. 4 3. 2 5. 8 3. 8 1. 6 0. 2 1. 4 10 0. 0 78 .6 55 8 R ic he st 2. 3 87 .4 3. 0 2. 5 0. 7 1. 1 0. 5 0. 2 2. 3 10 0. 0 89 .7 53 4 To ta l 2. 6 70 .0 5. 9 5. 1 7. 4 5. 1 2. 0 0. 2 1. 7 10 0. 0 72 .5 29 01 [1 ] M IC S in d ic at or 4 . Water and Sanitation 75 In its 2008 report9, the JMP developed a new way of presenting the access figures, by disaggregating and refining the data on drinking-water and sanitation and reflecting them in “ladder” format. This ladder allows a disaggregated analysis of trends in a three rung ladder for drinking-water and a four-rung ladder for sanitation. For sanitation, this gives an understanding of the proportion of population with no sanitation facilities at all, of those reliant on technologies defined by JMP as “unimproved,” of those sharing sanitation facilities of otherwise acceptable technology, and those using “improved” sanitation facilities. Table WS.8 presents the percentages of household population by drinking water and sanitation ladders. The table also shows the percentage of household members using improved sources of drinking water and sanitary means of excreta disposal. As shown in Table WS.8, the percentage share of households using improved sources of drinking water and sanitary means of excreta disposal is 9 per cent. This proportion is positively associated with the household wealth index. For example, less than one per cent of household population living in the poorest households are using improved sources of drinking water and improved sanitation as opposed to 25 per cent in case of those who live in the richest households. The combined use of improved drinking water and improved sanitation in households is 8 per cent in rural areas and 18 per cent in urban areas of Nyanza Province. 9 WHO/UNICEF JMP (2008), MDG assessment report - http://www.wssinfo.org/download?id_document=1279 Water and Sanitation 76 Ta b le W S .8 : D ri nk in g w at er a nd s an it at io n la d d er s P er ce nt ag e o f ho us eh o ld p o p ul at io n b y d ri nk in g w at er a nd

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