Kenya - Demographic and Health Survey - 2004

Publication date: 2004

Demographic and Health Survey Kenya 2003 K enya 2003 D em ographic and H ealth Sur vey Kenya Demographic and Health Survey 2003 Central Bureau of Statistics Nairobi, Kenya Ministry of Health Nairobi, Kenya Kenya Medical Research Institute Nairobi, Kenya National Council for Population and Development Nairobi, Kenya ORC Macro Calverton, Maryland, USA Centers for Disease Control and Prevention Nairobi, Kenya July 2004 British Department for International Development United Nations Population Fund Centres for Disease Control and Prevention United Nations Development Programme ORC Macro U.S. Agency for International Development United Nations Children’s Fund Japan International Cooperation Agency This report summarises the findings of the 2003 Kenya Demographic and Health Survey (2003 KDHS) carried out by Central Bureau of Statistics in partnership with the Ministry of Health and the National Council for Population and Development. ORC Macro provided financial and technical assistance for the survey through the USAID-funded MEASURE DHS+ programme, which is designed to assist developing countries to collect data on fertility, family planning, and maternal and child health. The Centres for Disease Control and Prevention (CDC) provided technical and financial support on the HIV component of the survey. Additional funding for the KDHS was received from the United Nations Population Fund (UNFPA), the Department for International Development (DFID/U.K.), the Government of Japan through a fund managed by United Nations Development Programme (UNDP), and the United Nations Children’s Fund (UNICEF). The opinions expressed in this report are those of the authors and do not necessarily reflect the views of the donor organisations. Additional information about the survey may be obtained from Central Bureau of Statistics (CBS), P.O. Box 30266, Nairobi (Telephone: 254.20.340.929; Fax: 254.20.333.030; Email: director@cbs.go.ke). Additional information about the DHS programme may be obtained from MEASURE DHS+, ORC Macro, 11785 Beltsville Drive, Suite 300, Calverton, MD 20705, U.S.A. (Telephone: 301.572.0200; Fax: 301.572.0999; Email: reports@macroint.com). Recommended citation: Central Bureau of Statistics (CBS) [Kenya], Ministry of Health (MOH) [Kenya], and ORC Macro. 2004. Kenya Demographic and Health Survey 2003. Calverton, Maryland: CBS, MOH, and ORC Macro. Contents | iii CONTENTS Page Tables and Figures . ix Foreword. xvii Summary of Findings . xix Map of Kenya . xxiv CHAPTER 1 INTRODUCTION Fredrick Otieno and Silas Opiyo 1.1 Geography, History, and the Economy.1 1.2 Population.2 1.3 Population and Family Planning Policies and Programmes .3 1.4 Health Priorities and Programmes.4 1.5 Strategic Framework to Combat the HIV/AIDS Epidemic.5 1.6 Objectives and Organisation of the Survey.6 1.7 Survey Organisation.7 1.8 Sample Design.7 1.9 Questionnaires .7 1.10 HIV Testing.9 1.11 Training .9 1.12 Fieldwork .10 1.13 Data Processing .11 1.14 Response Rates.11 CHAPTER 2 HOUSEHOLD POPULATION AND HOUSING CHARACTERISTICS Francis M. Munene 2.1 Household Population by Age and Sex .13 2.2 Household Composition .15 2.3 Educational Attainment of Household Members .16 2.4 Housing Characteristics.21 2.5 Household Durable Goods .25 CHAPTER 3 CHARACTERISTICS OF RESPONDENTS AND WOMEN’S STATUS Godfrey K. Ndeng’e 3.1 Background Characteristics of Respondents .27 3.2 Educational Attainment and Literacy.27 3.3 Access to Mass Media .32 3.4 Employment .35 iv | Contents 3.4.1 Employment Status .35 3.4.2 Occupation .37 3.4.3 Type of Employer, Form of Earnings, and Continuity of Employment .39 3.4.4 Control Over Earnings and Women’s Contribution to Household Expenditures.40 3.5 Women’s Empowerment .42 3.5.1 Women’s Participation in Decisionmaking.42 3.5.2 Women’s Attitudes Towards Wife-Beating .44 3.5.3 Attitudes Towards Refusing Sex with Husband.47 CHAPTER 4 FERTILITY LEVELS, TRENDS, AND DIFFERENTIALS Collins Opiyo 4.1 Introduction .51 4.2 Current Fertility .51 4.3 Fertility Trends.54 4.4 Children Ever Born and Children Surviving .57 4.5 Birth Intervals .58 4.6 Age at First Birth .59 4.7 Teenage Fertility .60 CHAPTER 5 FAMILY PLANNING Samuel Ogola and Salome Adala 5.1 Knowledge of Contraceptive Methods .63 5.2 Ever Use of Contraception .65 5.3 Current Use of Contraceptive Methods.66 5.4 Trends in Contraceptive Use.68 5.5 Differentials in Contraceptive Use By Background Characteristics .70 5.6 Current Use of Contraceptives by Women’s Status .72 5.7 Timing of First Use of Contraception.73 5.8 Use of Femiplan Social Marketing Pill Brand .74 5.9 Knowledge of the Fertile Period.74 5.10 Source of Contraception.75 5.11 Informed Choice .76 5.12 Contraceptive Discontinuation.78 5.13 Future Use of Contraception.79 5.14 Reasons for Not Intending to Use.80 5.15 Preferred Method for Future Use .80 5.16 Exposure to Family Planning Messages.81 5.17 Contact of Nonusers with Family Planning Providers.84 5.18 Discussion of Family Planning between Couples .85 5.19 Attitudes of Respondents Towards Family Planning.85 Contents | v CHAPTER 6 OTHER PROXIMATE DETERMINANTS OF FERTILITY Alfred Agwanda 6.1 Introduction .89 6.2 Marital Status.89 6.3 Polygyny.90 6.4 Age at First Marriage .92 6.5 Age at First Sexual Intercourse .94 6.6 Recent Sexual Activity.96 6.7 Postpartum Amenorrhoea, Abstinence, and Insusceptibility .99 6.8 Termination of Exposure to Pregnancy. 101 CHAPTER 7 FERTILITY PREFERENCES Murungaru Kimani 7.1 Desire for More Children. 103 7.2 Need for Family Planning Services . 105 7.3 Ideal Family Size. 107 7.4 Wanted and Unwanted Fertility. 109 7.5 Ideal Family Size and Unmet Need by Women’s Status . 111 CHAPTER 8 INFANT AND CHILD MORTALITY Fredrick Otieno and Christopher Omolo 8.1 Levels and Trends in Infant and Child Mortality . 114 8.2 Socioeconomic Differentials in Infant and Child Mortality. 115 8.3 Demographic Differentials in Infant and Child Mortality . 117 8.4 Differentials in Infant and Child Mortality by Women’s Status. 118 8.5 Perinatal Mortality . 119 8.6 High-Risk Fertility Behaviour. 121 CHAPTER 9 MATERNAL AND CHILD HEALTH George Kichamu, Jones N. Abisi, and Lydia Karimurio 9.1 Antenatal Care. 123 9.2 Delivery Care . 129 9.3 Postnatal Care . 134 9.4 Reproductive Health Care and Women’s Status. 135 9.5 Vaccination of Children . 136 9.6 Acute Respiratory Infection and Fever. 140 9.7 Diarrhoeal Disease . 142 9.8 Child Health Indicators and Women’s Status . 147 9.9 Birth Registration . 148 9.10 Knowledge of Signs of Illness . 149 9.11 Smoking and Alcohol Use. 150 vi | Contents CHAPTER 10 NUTRITION John O. Owuor and John G. Mburu 10.1 Breastfeeding and Supplementation. 153 10.2 Micronutrient Intake. 159 10.3 Nutritional Status of Children Under Five. 163 10.4 Nutritional Status of Women . 168 CHAPTER 11 MALARIA Kiambo Njagi and Eric Were 11.1 Malaria Control and Prevention Strategies in Kenya . 171 11.2 Household Ownership of Mosquito Nets . 171 11.3 Use of Mosquito Nets . 173 11.4 Intermittent Preventive Treatment of Malaria in Pregnancy . 175 11.5 Malaria Case Management among Children. 178 CHAPTER 12 HIV/AIDS RELATED KNOWLEDGE, ATTITUDES, AND BEHAVIOUR James N. Muttunga, Robert C. B. Buluma, and Boaz K. Cheluget 12.1 Introduction . 183 12.2 Knowledge of AIDS and HIV Transmission. 184 12.3 Stigma Towards HIV-Infected People. 191 12.4 Perceived Risk of Getting AIDS . 193 12.5 Multiple Sexual Partnerships . 196 12.6 Testing and Counselling for HIV. 197 12.7 Attitudes Towards Negotiating Safer Sex . 199 12.8 Condom Use at Higher-Risk Sex . 200 12.9 Paid Sex and Condom Use . 202 12.10 Attitudes Towards Condoms . 203 12.11 Condom Brands . 205 12.12 Self-Reporting of Sexually Transmitted Infections . 205 12.13 Male Circumcision. 207 12.14 Age at First Sex Among Youth . 209 12.15 Knowledge of Condom Sources Among Youth . 210 12.16 Condom Use at First Sex Among Youth. 211 12.17 Premarital Sex . 212 12.18 Higher-Risk Sex and Condom Use Among Youth . 214 12.19 Age-Mixing in Sexual Relationships . 215 12.20 Orphanhood and Children’s Living Arrangements. 215 CHAPTER 13 HIV PREVALENCE AND ASSOCIATED FACTORS Lawrence Marum, James N. Muttunga, Francis M. Munene, and Boaz K. Cheluget 13.1 Coverage of HIV Testing . 220 13.2 HIV Prevalence. 223 Contents | vii 13.3 Distribution of the HIV Burden in Kenya. 232 CHAPTER 14 ADULT AND MATERNAL MORTALITY Christopher Omolo and Paul Kizito 14.1 Data . 233 14.2 Estimates of Adult Mortality . 234 14.3 Estimates of Maternal Mortality . 236 CHAPTER 15 GENDER VIOLENCE Betty Khasakhala-Mwenesi, Robert C.B. Buluma, Rosemary U. Kong’ani, and Vivian M. Nyarunda 15.1 Introduction . 239 15.2 Data Collection. 239 15.3 Violence Since Age 15 . 241 15.4 Marital Violence . 243 15.5 Frequency of Spousal Violence . 245 15.6 Onset of Spousal Violence Against Women. 246 15.7 Physical Consequences of Spousal Violence. 247 15.8 Violence Initiated by Women against Husbands . 248 15.9 Violence by Spousal Characteristics and Women’s Status Indicators. 248 15.10 Female Genital Cutting . 250 REFERENCES . 253 APPENDIX A SAMPLE IMPLEMENTATION . 257 APPENDIX B ESTIMATES OF SAMPLING ERRORS . 263 APPENDIX C DATA QUALITY TABLES. 279 APPENDIX D PERSONS INVOLVED IN THE 2003 KENYA DEMOGRAPHIC AND HEALTH SURVEY. 285 APPENDIX E QUESTIONNAIRES . 289 Tables and Figures | ix TABLES AND FIGURES Page CHAPTER 1 INTRODUCTION Table 1.1 Basic demographic indicators. 3 Table 1.2 Results of the household and individual interviews . 12 CHAPTER 2 HOUSEHOLD POPULATION AND HOUSING CHARACTERISTICS Table 2.1 Household population by age, sex, and residence . 14 Table 2.2 Household composition. 15 Table 2.3.1 Educational attainment of household population: females . 16 Table 2.3.2 Educational attainment of household population: males . 17 Table 2.4 School attendance . 18 Table 2.5 School attendance ratios. 20 Table 2.6 Housing characteristics . 22 Table 2.7 Household durable goods. 25 Figure 2.1 Population pyramid . 14 Figure 2.2 Percentage of males and females currently attending school, by age . 19 CHAPTER 3 CHARACTERISTICS OF SURVEY RESPONDENTS Table 3.1 Background characteristics of respondents . 28 Table 3.2.1 Educational attainment by background characteristics: women. 29 Table 3.2.2 Educational attainment by background characteristics: men. 30 Table 3.3.1 Literacy: women. 31 Table 3.3.2 Literacy: men . 32 Table 3.4.1 Exposure to mass media: women. 33 Table 3.4.2 Exposure to mass media: men . 34 Table 3.5 Employment status. 36 Table 3.6.1 Occupation: women. 37 Table 3.6.2 Occupation: men . 38 Table 3.7.1 Type of employment: women. 39 Table 3.7.2 Type of employment: men . 39 Table 3.8 Decision on use of earnings and contribution of earnings to household expenditures. 40 Table 3.9 Women’s control over earnings . 41 Table 3.10 Women’s participation in decisionmaking . 42 Table 3.11 Women’s participation in decisionmaking by background characteristics: women . 43 Table 3.12.1 Women’s attitude towards wife-beating. 45 Table 3.12.2 Men’s attitude towards wife-beating . 46 Table 3.13.1 Women’s attitude towards refusing sex with husband . 48 Table 3.13.2 Men’s attitude towards wife refusing sex with husband . 49 x | Tables and Figures Table 3.14 Men’s attitudes towards justifiable actions if wife refuses sex. 50 Figure 3.1 Access to mass media . 35 CHAPTER 4 FERTILITY Table 4.1 Current fertility . 52 Table 4.2 Fertility by background characteristics. 53 Table 4.3 Trends in fertility. 55 Table 4.4 Trends in fertility by background characteristics . 56 Table 4.5 Trends in age-specific fertility rates . 56 Table 4.6 Children ever born and living. 57 Table 4.7 Birth intervals. 58 Table 4.8 Age at first birth . 59 Table 4.9 Median age at first birth by background characteristics. 60 Table 4.10 Teenage pregnancy and motherhood . 62 Figure 4.1 Total fertility rate, by background characteristics . 54 Figure 4.2 Total fertility rates, Kenya 1975-2003 . 55 CHAPTER 5 FAMILY PLANNING Table 5.1.1 Knowledge of contraceptive methods: women . 64 Table 5.1.2 Knowledge of contraceptive methods: men . 65 Table 5.2 Ever use of contraception . 66 Table 5.3 Current use of contraception . 67 Table 5.4 Trends in current use of contraception. 68 Table 5.5 Current use of contraception by background characteristics . 71 Table 5.6 Current use of contraception by women’s status . 73 Table 5.7 Number of children at first use of contraception . 74 Table 5.8 Use of social marketing brand pills. 74 Table 5.9 Knowledge of fertile period. 75 Table 5.10 Source of contraception. 76 Table 5.11 Informed choice . 77 Table 5.12 First-year contraceptive discontinuation rates. 78 Table 5.13 Reasons for discontinuation . 79 Table 5.14 Future use of contraception . 80 Table 5.15 Reasons for not intending to use contraception. 80 Table 5.16 Preferred method of contraception for future use . 81 Table 5.17 Exposure to condom messages. 82 Table 5.18 Acceptability of media messages about condoms . 83 Table 5.19 Exposure of men to family planning messages . 84 Table 5.20 Discussion of family planning with husband. 85 Table 5.21 Attitudes towards family planning: married women . 86 Table 5.22 Attitudes towards family planning: all men. 87 Table 5.23 Men’s attitudes towards contraception. 88 Figure 5.1 Contraceptive use among currently married women, Kenya 1984-2003 . 69 Figure 5.2 Trends in current use of specific contraceptive methods among currently married women age 15-49, Kenya 1993-2003. 69 Figure 5.3 Current use of family planning among currently married women age 15-49, selected countries in east Africa and southern Africa . 70 Tables and Figures | xi Figure 5.4 Current use of any contraceptive method among currently married women age 15-49, by background characteristics . 72 CHAPTER 6 OTHER PROXIMATE DETERMINANTS OF FERTILITY Table 6.1 Current marital status. 90 Table 6.2 Polygyny. 91 Table 6.3 Age at first marriage . 93 Table 6.4 Median age at first marriage. 94 Table 6.5 Age at first sexual intercourse. 95 Table 6.6 Median age at first intercourse . 96 Table 6.7.1 Recent sexual activity: women. 91 Table 6.7.2 Recent sexual activity: men . 98 Table 6.8 Postpartum amenorrhoea, abstinence, and insusceptibility . 99 Table 6.9 Median duration of postpartum insusceptibility by background characteristics . 100 Table 6.10 Menopause . 101 Figure 6.1 Percentage of currently married women whose husbands have at least one other wife . 92 CHAPTER 7 FERTILITY PREFERENCES Table 7.1 Fertility preferences by number of living children. 104 Table 7.2 Desire to limit childbearing. 105 Table 7.3 Need for family planning among currently married women. 106 Table 7.4 Ideal number of children . 108 Table 7.5 Mean ideal number of children. 109 Table 7.6 Fertility planning status . 110 Table 7.7 Wanted fertility rates . 111 Table 7.8 Ideal number of children and unmet need by women’s status. 112 Figure 7.1 Fertility preferences among currently married women age 15-49 . 104 CHAPTER 8 INFANT AND CHILD MORTALITY Table 8.1 Early childhood mortality rates. 114 Table 8.2 Early childhood mortality rates by socioeconomic characteristics . 116 Table 8.3 Early childhood mortality rates by demographic characteristics . 118 Table 8.4 Early childhood mortality rates by women’s status. 119 Table 8.5 Perinatal mortality . 120 Table 8.6 High-risk fertility behaviour. 122 Figure 8.1 Trends in infant and under-five mortality, 1988 KDHS and 2003 KDHS. 115 Figure 8.2 Under-five mortality by background characteristics . 116 CHAPTER 9 MATERNAL AND CHILD HEALTH Table 9.1 Antenatal care . 124 Table 9.2 Source of antenatal care . 125 Table 9.3 Number of antenatal care visits and timing of first visit . 126 Table 9.4 Components of antenatal care . 127 xii | Tables and Figures Table 9.5 Tetanus toxoid injections . 129 Table 9.6 Place of delivery . 130 Table 9.7 Assistance during delivery . 132 Table 9.8 Delivery characteristics . 133 Table 9.9 Postnatal care by background characteristics. 135 Table 9.10 Reproductive health care by women’s status. 136 Table 9.11 Vaccinations by source of information . 137 Table 9.12 Vaccinations by background characteristics. 139 Table 9.13 Prevalence and treatment of symptoms of ARI and fever. 141 Table 9.14 Disposal of children’s stools . 143 Table 9.15 Prevalence of diarrhoea . 144 Table 9.16 Knowledge of ORS packets . 145 Table 9.17 Diarrhoea treatment . 146 Table 9.18 Feeding practices during diarrhoea . 147 Table 9.19 Children’s health care by women’s status. 148 Table 9.20 Birth registration . 149 Table 9.21 Knowledge of illness signs . 150 Table 9.22 Use of tobacco among men . 151 Table 9.23 Use of alcohol . 152 Figure 9.1 Antenatal care, tetanus vaccinations, place of delivery, and delivery assistance. 131 Figure 9.2 Percentage of children age 12-23 months with specific vaccinations according to health cards and mother’s reports . 138 CHAPTER 10 NUTRITION Table 10.1 Initial breastfeeding .154 Table 10.2 Breastfeeding status by child’s age .155 Table 10.3 Median duration and frequency of breastfeeding.157 Table 10.4 Foods consumed by children in the day or night preceding the interview .158 Table 10.5 Micronutrient intake among children .160 Table 10.6 Micronutrient intake among mothers .162 Table 10.7 Nutritional status of children.165 Table 10.8 Trends in nutritional status of children .167 Table 10.9 Nutritional status of women by background characteristics.169 Figure 10.1 Breastfeeding practices by age . 156 Figure 10.2 Frequency of meals consumed by children under 36 months of age living with their mother. 159 CHAPTER 11 MALARIA Table 11.1 Ownership of mosquito nets. 172 Table 11.2 Use of mosquito nets by children. 173 Table 11.3 Use of mosquito nets by pregnant women . 174 Table 11.4 Use of antimalarial drugs among pregnant women. 176 Table 11.5 Use of SP for intermittent treatment. 177 Table 11.6 Prevalence and prompt treatment of fever/convulsions . 179 Table 11.7 Standard treatment of fever . 180 Table 11.8 Other interventions for treatment of fever and/or convulsions . 181 Tables and Figures | xiii CHAPTER 12 HIV/AIDS-RELATED KNOWLEDGE, ATTITUDES, AND BEHAVIOUR Table 12.1 Knowledge of AIDS. 185 Table 12.2 Knowledge of HIV prevention methods . 186 Table 12.3 Knowledge of prevention of mother-to-child transmission of HIV. 188 Table 12.4.1 Beliefs about AIDS: women . 189 Table 12.4.2 Beliefs about AIDS: men. 190 Table 12.5.1 Accepting attitudes towards those living with HIV: women . 192 Table 12.5.2 Accepting attitudes towards those living with HIV: men . 193 Table 12.6 Perception of risk of getting AIDS. 194 Table 12.7 Reasons for perception of small/no risk of getting AIDS . 195 Table 12.8 Reasons for perception of moderate/great risk of getting AIDS . 195 Table 12.9 Multiple sex partnerships among women and men . 196 Table 12.10 Population who had an HIV test and received test results . 198 Table 12.11 Attitudes towards negotiating safer sex with husband . 200 Table 12.12 Higher-risk sex and condom use at last higher-risk sex . 201 Table 12.13 Paid sex in last year and condom use at last paid sex . 203 Table 12.14 Attitude towards condoms . 204 Table 12.15 Condom brands. 205 Table 12.16 Self-reporting of a sexually transmitted infection (STI) and STI symptoms . 206 Table 12.17 Women and men seeking treatment for sexually transmitted infections. 207 Table 12.18 Male circumcision . 208 Table 12.19 Age at first sex among young women and men . 209 Table 12.20 Knowledge of a source for condoms among young people. 210 Table 12.21 Condom use at first sex among young women and men . 211 Table 12.22 Premarital sex and condom use among youth. 213 Table 12.23 Higher-risk sex and condom use among young women and men. 214 Table 12.24 Children’s living arrangements and orphanhood . 216 Figure 12.1 Reason for getting HIV test among women and men age 15-49 who have ever been tested . 199 Figure 12.2 Abstinence, being faithful, and using condoms among young women and men. 212 CHAPTER 13 HIV PREVALENCE AND ASSOCIATED FACTORS Table 13.1 Coverage of HIV testing by sex and urban-rural residence. 218 Table 13.2 Coverage of HIV testing by age, education, and wealth quintile . 220 Table 13.3 HIV prevalence by age. 222 Table 13.4 HIV prevalence by selected socioeconomic characteristics. 223 Table 13.5 HIV prevalence by selected sociodemographic characteristics. 224 Table 13.6 HIV prevalence by sexual behaviour characteristics . 226 Table 13.7 HIV prevalence by selected other characteristics. 227 Table 13.8 HIV prevalence by prior HIV testing. 228 Table 13.9 HIV prevalence by male circumcision . 229 Table 13.10 HIV prevalence among couples . 231 CHAPTER 14 ADULT AND MATERNAL MORTALITY Table 14.1 Data on siblings . 234 Table 14.2 Adult mortality rates . 235 Table 14.3 Maternal mortality . 237 xiv | Tables and Figures Figure 14.1 Trends in adult mortality, Kenya 1991-1997 and 1996-2002. 236 CHAPTER 15 GENDER VIOLENCE Table 15.1 Experience of physical mistreatment . 242 Table 15.2 Perpetrators of violence . 243 Table 15.3 Marital violence. 244 Table 15.4 Frequency of spousal violence . 246 Table 15.5 Onset of spousal violence . 247 Table 15.6 Physical consequences of spousal violence . 248 Table 15.7 Spousal violence, women’s status, and husband’s characteristics. 249 Table 15.8 Female circumcision . 251 Figure 15.1 Percentage of women who have experienced different forms of spousal violence ever (since age 15) and in the 12 months preceding the survey. 245 APPENDIX A SAMPLE IMPLEMENTATION Table A.1 Sample implementation: women . 257 Table A.2 Sample implementation: men. 258 Table A.3 Coverage of HIV testing among interviewed women by socio- demographic characteristics. 259 Table A.4 Coverage of HIV testing among interviewed men by socio- demographic characteristics. 260 Table A.5 Coverage of HIV testing among women who ever had sex by risk status variables . 261 Table A.6 Coverage of HIV testing among men who ever had sex by risk status variables . 262 APPENDIX B ESTIMATES OF SAMPLING ERRORS Table B.1 List of selected variables for sampling errors . 266 Table B.2 Sampling errors for national sample . 267 Table B.3 Sampling errors for urban sample. 268 Table B.4 Sampling errors for rural sample. 269 Table B.5 Sampling errors for Nairobi sample . 270 Table B.6 Sampling errors for Central sample . 271 Table B.7 Sampling errors for Coast sample . 272 Table B.8 Sampling errors for Eastern sample. 273 Table B.9 Sampling errors for Nyanza sample . 274 Table B.10 Sampling errors for Rift Valley sample . 275 Table B.11 Sampling errors for Western sample. 276 Table B.12 Sampling errors for North Eastern sample. 277 Tables and Figures | xv APPENDIX C DATA QUALITY TABLES Table C.1 Household age distribution. 279 Table C.2 Age distribution of eligible and interviewed women and men . 280 Table C.3 Completeness of reporting . 281 Table C.4 Births by calendar years . 281 Table C.5 Reporting of age at death in days . 282 Table C.6 Reporting of age at death in months . 283 Foreword | xvii FOREWORD This detailed report presents the major findings of the 2003 Kenya Demographic and Health Sur- vey (2003 KDHS). The 2003 KDHS is the fourth survey of its kind to be undertaken in Kenya, others being in 1989, 1993, and 1998. The 2003 KDHS differed in two aspects from the previous KDHS sur- veys: it included a module on HIV prevalence from blood samples, and it covered all parts of the country, including the arid and semi-arid districts that had previously been omitted from the KDHS. The 2003 KDHS was implemented by the Central Bureau of Statistics. Fieldwork was carried out between April and September 2003. The primary objective of the 2003 KDHS was to provide up-to-date information for policymak- ers, planners, researchers, and programme managers, which would allow guidance in the planning, im- plementation, monitoring and evaluation of population and health programmes in Kenya. Specifically, the 2003 KDHS collected information on fertility levels, marriage, sexual activity, fertility preferences, awareness and use of family planning methods, breastfeeding practices, nutritional status of women and young children, childhood and maternal mortality, maternal and child health, and awareness and behav- iour regarding HIV/AIDS and other sexually transmitted infections (STIs). In addition, it collected infor- mation on malaria and use of mosquito nets, domestic violence among women, and HIV prevalence of adults. The 2003 KDHS results present evidence of lower than expected HIV prevalence in the country, stagnation in fertility levels, only a very modest increase in use of family planning methods since 1998, continued increase in infant and under-five mortality rates, and overall decline in indicators of maternal and child health in the country. There is a disparity between knowledge and use of family planning meth- ods. There is also a large disparity between knowledge and behaviour regarding HIV/AIDS and other STIs. Some of the critical findings from this survey, like the stagnation in fertility rates and the declining trend in maternal and child health, need to be addressed without delay. I would like to acknowledge the efforts of a number of organisations that contributed immensely to the success of the survey. First, I would like to acknowledge financial assistance from the Government of Kenya, the United States Agency for International Development (USAID), the United Kingdom De- partment for International Development (DFID), the United Nations Population Fund (UNFPA), the Ja- pan International Co-operation Agency (JICA), the United Nations Development Programme (UNDP), the United Nations Children’s Fund (UNICEF), and the Centers for Disease Control and Prevention (CDC). Second, in the area of technical backstopping, I would like to acknowledge ORC Macro, CDC, the National AIDS and STIs Control programme (NASCOP), the Kenya Medical Research Institute (KEMRI), and the National Council of Population and Development (NCPD). Special thanks go to the staff of the Central Bureau of Statistics and the Ministry of Health who coordinated all aspects of the sur- vey. Finally, I am grateful to the survey data collection personnel and, more importantly, to the survey respondents, who generously gave their time to provide the information and blood spots that form the ba- sis of this report. Anthony K. M. Kilele Acting Director of Statistics Summary of Findings | xix SUMMARY OF FINDINGS The 2003 Kenya Demographic and Health Survey (2003 KDHS) is a nationally representa- tive sample survey of 8,195 women age 15 to 49 and 3,578 men age 15 to 54 selected from 400 sample points (clusters) throughout Kenya. It is designed to provide data to monitor the population and health situation in Kenya as a follow-up of the 1989, 1993 and 1998 KDHS surveys. The survey utilised a two-stage sample based on the 1999 Population and Housing Census and was designed to produce separate estimates for key indicators for each of the eight provinces in Kenya. Unlike prior KDHS surveys, the 2003 KDHS covered the northern half of Kenya. Data collection took place over a five-month period, from 18 April to 15 September 2003. The survey obtained detailed information on fertility levels, marriage, sexual activity, fertility preferences, awareness and use of family planning methods, breastfeeding practices, nutritional status of women and young children, childhood and ma- ternal mortality, maternal and child health, aware- ness and behaviour regarding HIV/AIDS, and other sexually transmitted infections (STIs). New features of the 2003 KDHS include the collection of information on malaria and use of mosquito nets, domestic violence, and HIV testing of adults. The 2003 KDHS was implemented by the Central Bureau of Statistics (CBS) in collabora- tion with the Ministry of Health (including the National AIDS and STIs Control Programme- NASCOP and the Kenya Medical Research Insti- tute-KEMRI), and the National Council for Popu- lation and Development (NCPD). Technical assis- tance was provided through the MEASURE/DHS programme, in collaboration with the U.S. Centers for Disease Control and Prevention (CDC). Fi- nancial support for the survey was provided by the Government of Kenya and a consortium of do- nors, including: the U. S. Agency for International Development (USAID), the United Nations Popu- lation Fund (UNFPA), Japan International Coop- eration Agency (JICA)/United Nations Develop- ment Programme (UNDP), the United Nations Children’s Fund (UNICEF), the British Depart- ment for International Development (DFID), and the Centers for Disease Control and Prevention (CDC). FERTILITY Fertility Levels and Trends. One of the most surprising findings from the 2003 KDHS is that the previously documented decline in fertility appears to have stalled. The total fertility rate of 4.9 children per woman for the three-year period preceding the survey (mid-2000 to mid-2003) is almost identical to the rate of 5.0 derived from the 1999 Population and Housing Census. Comparison with the 1998 KDHS requires restricting analysis to the southern parts of the country that were sampled in both surveys; this comparison shows a slight increase in fertility from 4.7 children per woman between 1995 and 1998 to 4.8 between 2000 and 2003. Given the dramatic decline in fertility from the late 1970s to the mid-1990s (from 8.1 to 4.7), this plateau in fertility is worrisome. Fertility Differentials. There are substantial dif- ferences in fertility levels in Kenya. The total fertility rate is considerably higher in the rural areas (5.4 chil- dren per woman) than urban areas (3.3 children per woman). Regional differences are also marked. Fertil- ity is lowest in Nairobi Province (2.7 children per woman) and highest in North Eastern Province (7.0 children per woman). Fertility in Central Province is also relatively low (3.4), compared with Nyanza (5.6), Rift Valley (5.8) and Western (5.8) Provinces. In accordance with expectations, education of women is strongly associated with lower fertility. The total fertility rate (TFR) decreases dramatically from 6.7 for women with no education to 3.2 for women with at least some secondary education. In terms of trends over time, fertility has actually increased among women with no education and has only de- clined among those with some secondary education. Unplanned Fertility. Despite a relatively high level of contraceptive use, the 2003 KDHS data indi- cate that unplanned pregnancies are common in Kenya. Overall, 20 percent of births in Kenya are un- wanted, while 25 percent are mistimed (wanted later). Overall, the proportion of births considered mistimed or unwanted has changed little, compared with the xx | Summary of Findings 1998 KDHS; however, the trends show a sizeable increase in the percentage of births that are un- wanted and a comparable reduction in those that are mistimed. Fertility Preferences. The desire to have more children has increased since 1998 among both women and men. For example, the propor- tion of married women who want another child has increased from 40 to 45 percent (excluding the northern districts in order to be comparable). Na- tionally, 47 percent of married women want to have another child—29 percent later and 16 per- cent soon (within two years). There has been little change in the ideal number of children. In 2003, among women, the mean ideal family size is 3.9 children. FAMILY PLANNING Knowledge of Contraception. Knowledge of family planning is nearly universal, with 94 percent of all women age 15 to 49 and 97 percent of men age 15 to 54 knowing at least one modern method of family planning. Among all women, the most widely known methods of family plan- ning are the male condom (91 percent), pills (90 percent), and injectables (89 percent). Three- quarters of all women have heard of female ster- ilisation, while about two-thirds have heard of the IUD, implants, and periodic abstinence. Trends in contraceptive knowledge since the 1998 KDHS are mixed. Although it appears as if there has been a slight drop in knowledge since 1998, it is mostly due to the inclusion of the northern areas of Kenya in 2003. When these ar- eas are excluded, there has been no change in overall levels of knowledge of any method or any modern method. Nevertheless, the level of knowl- edge of several methods has declined slightly since 1998. For example, among all women (ex- cluding the northern districts), the percentages who know of female sterilisation, the pill, the IUD, and periodic abstinence have declined slightly since 1998. On the other hand, the per- centages who know of male sterilisation, male condoms, injectables, implants and withdrawal have increased slightly. Use of Contraception. Almost four in ten married women (39 percent) in Kenya are using a method of family planning. Most are using a modern method (32 percent of married women), while 8 per- cent use a traditional method. Injectables, pills, and periodic abstinence are the most commonly used con- traceptive methods, used by 14 percent, 8 percent, and 6 percent of married women, respectively. Trends in Contraceptive Use. Contraceptive use has increased slightly since 1998, from 39 to 41 percent of married women (excluding the northern part of the country so as to be comparable to 1998). This is far less than the 6 percentage point rise in the five years between 1993 and 1998. Nevertheless, the 2003 KDHS corroborates trends in method mix, namely, a continuing increase in use of injectables and decrease in use of the pill as was the case in earlier KDHS surveys. Differentials in Contraceptive Use. As ex- pected, contraceptive use increases with level of edu- cation. Use of modern methods increases from 8 per- cent among married women with no education to 52 percent among women with at least some secondary education. Use of modern contraception among women with no education dropped from 16 percent in 1998 to 11 percent in 2003 (excluding the northern areas). Source of Modern Methods. In Kenya, public (government) facilities provide contraceptives to slightly more than half (53 percent) of modern method users, while 41 percent are supplied through private medical sources, 5 percent through other private sources (e.g. shops) and only 1 percent through com- munity-based distribution. Discontinuation Rates. Overall, almost four in ten women (38 percent) discontinue use within 12 months of adopting a method. The 12-month discon- tinuation rate for injectables (32 percent) and periodic abstinence (33 percent) are lower than for the pill (46 percent) and male condom (59 percent). Discontinua- tion rates have increased since 1998, from 33 percent to 38 percent of users. This seems to be due to higher discontinuation rates for the pill and injectables, while rates for condoms and periodic abstinence have re- mained stable. Unmet Need for Family Planning. One-quarter of currently married women in Kenya have an unmet need for family planning, unchanged since 1998. Three-fifths of unmet need is comprised of women who want to wait two or more years before having Summary of Findings | xxi their next child (spacers), while two-fifths is com- prised of women who want no more children (lim- iters). MATERNAL HEALTH Antenatal Care. The 2003 KDHS data indi- cate that 88 percent of women in Kenya receive antenatal care from a medical professional, either from doctors (18 percent) or nurses or midwives (70 percent). A small fraction (2 percent) receives antenatal care from traditional birth attendants, while 10 percent do not receive any antenatal care. The 2003 data indicate a slight decline since 1998 in medical antenatal care coverage. Just over half of women (52 percent) re- ceived two or more tetanus toxoid injections dur- ing pregnancy for their most recent birth in the five years preceding the survey, while 34 percent received one dose. There has been little change since 1998 in the proportion of women receiving tetanus toxoid injections during pregnancy. With regard to anti-malarial indicators, the 2003 KDHS data shows that only 4 percent of pregnant women slept under an insecticide-treated mosquito net the night before the survey and 4 percent received intermittent preventive treatment with anti-malarial medication during antenatal care visits. Delivery Care. Proper medical attention and hygienic conditions during delivery can re- duce the risk of serious illness among mothers and their babies. The 2003 KDHS found that two out of five births (40 percent) are delivered in a health facility, while 59 percent are delivered at home. There has been no change since 1998 in the pro- portion of births occurring at home. Similarly, 42 percent of births in Kenya are delivered under the supervision of a health profes- sional, mainly a nurse or midwife. Traditional birth attendants continue to play a vital role in delivery, assisting with 28 percent of births. Rela- tives and friends assist in 22 percent of births. The proportion of births assisted by medically trained personnel has remained constant since 1998. Only 4 percent of births are delivered by Caesarean sec- tion, a slight decline since 1998. Maternal Mortality. Data on the survival of respondents’ sisters were used to calculate a ma- ternal mortality ratio for the 10-year period before the survey, which was estimated as 414 maternal deaths per 100,000 live births. This represents a decline from the rate of 590 maternal deaths per 100,000 live births for the ten-year period prior to the 1998 KDHS; how- ever, the sampling errors around each of the estimates are large and consequently, the two estimates are not significantly different. Thus, it is impossible to say with confidence that maternal mortality has declined. However, a comparison of data from the 1998 and 2003 KDHS surveys indicates a substantial increase in overall adult mortality rates for both males and fe- males at all ages, with the exception of age group 15 to 19 among men. CHILD HEALTH Childhood Mortality. Data from the 2003 KDHS show that child mortality levels have been more or less stable over the recent few years. For the most recent five-year period preceding the survey, infant mortality is 77 deaths per 1,000 live births and under-five mortality is 115 deaths per 1,000 live births. This means that one in every nine children born in Kenya dies before attaining their fifth birthday. Childhood Vaccination Coverage. In the 2003 KDHS, mothers were able to show a health card with immunisation data for only 60 percent of children age 12-23 months. Accordingly, estimates of coverage are based on both data from health cards and mothers’ recall. The data show that 57 percent of children 12- 23 months are fully vaccinated against the major childhood illnesses. This represents a deterioration in immunisation coverage for children. Seven percent of children 12-23 months have not received any of the recommended immunisations. Child Illness and Treatment. Among children under five years of age, 18 percent were reported to have had symptoms of acute respiratory illness in the two weeks preceding the survey, while 41 percent had a fever in the two weeks preceding the survey and 16 percent had diarrhoea. Forty-six percent of children with symptoms of ARI and/or fever were taken to a health facility or provider for treatment. Thirty percent of children with diarrhoea were taken to a facility for treatment, while half were given either a solution pre- pared from oral rehydration salt (ORS) packets or in- creased fluids. Among children with fever in the two weeks preceding the survey, 11 percent were given the recommended medicine, sulfadoxine-pyrimethamine or SP, although only 6 percent of children received SP within a day of the onset of the fever. Survey data also xxii | Summary of Findings indicate that only 5 percent of children under five slept under an insecticide-treated mosquito net the night before the survey. NUTRITION Breastfeeding Practices. Breastfeeding is nearly universal in Kenya; 97 percent of children are breastfed. The median duration of breastfeed- ing is 20 months, similar to the duration docu- mented in the 1993 and 1998 KDHSs. The 2003 KDHS data indicate that supplementary feeding of children begins early. For example, among new- borns less than two months of age, 45 percent are receiving supplementary foods or liquids other than water. The median duration of exclusive breastfeeding is estimated at less than one month. Bottle-feeding is common in Kenya; 27 per- cent of children under 6 months are fed with bot- tles with teats. Nevertheless, use of infant formula milk is minimal; only 5 percent of children below six months receive commercially produced infant formula. Intake of Vitamin A. Ensuring that children between six months and 59 months receive enough vitamin A may be the single most effec- tive child survival intervention, since deficiencies in this micronutrient can cause blindness and can increase the severity of infections, such as measles and diarrhoea. Overall, 62 percent of children un- der age three years consume vitamin A-rich foods and 33 percent of children age 6-59 months re- ceived a vitamin A supplement in the six months preceding the survey. Nutritional Status of Children. Survey data show that the nutritional status of children under five has improved only slightly in the past few years. At the national level, 30 percent of children under five are stunted (low height-for- age), while 6 percent of children are wasted (low weight-for-height) and 20 percent are underweight (low weight-for-age). Children in Coast Province are most likely to be stunted, while those in North Eastern Province are most likely to be wasted and underweight. Nutritional Status of Women. The mean body mass index (BMI) for women age 15-49 has increased very slightly since 1998 and is now 23. HIV/AIDS Awareness of AIDS. Almost all (99 percent) of Kenyan women and men have heard of AIDS. More than 4 in 5 respondents (81 percent of women and 89 percent of men) indicate that the chances of getting the AIDS virus can be reduced by limiting sex to one faithful partner. Similarly, 61 percent of women and 72 percent of men know that condoms can reduce the risk of contracting the HIV virus during sexual inter- course. As expected, the proportion of both women and men who know that abstaining from sex reduces the chances of getting the AIDS virus is high—79 percent among women and 89 percent among men. Almost three-quarters of women (72 percent) and two-thirds of men (68 percent) know that HIV can be transmitted by breastfeeding; however, only one-third of women (33 percent) and 38 percent of men know that the risk of maternal to child transmission can be reduced by the mother taking certain drugs during pregnancy. Eighty-five percent of women and 90 per- cent of men are aware that a healthy-looking person can have the AIDS virus. Attitudes Towards HIV-Infected People. Large majorities of Kenyan women and men (84 and 88 percent, respectively) express a willingness to care for a relative sick with AIDS in their own household, while far fewer (60 and 74 percent, respectively) say they would be willing to buy fresh vegetables from a vendor who has the AIDS virus. Survey results further indicate that only 57 and 60 percent of women and men, respectively, believe that a female teacher who has the AIDS virus should be allowed to continue teaching in school. Finally, 59 percent of women and 72 percent of men say that if a member of their family got infected with the virus that causes AIDS, they would not necessarily want it to remain a secret. HIV-Related Behavioural Indicators. Com- parison of data from the 2003 KDHS with similar data from the 1998 KDHS indicates that there has been an increase in the age at first sexual experience. The me- dian age at first sex among women age 20 to 49 has increased from 16.7 to 17.8, even when the northern areas of Kenya are excluded to make the data more comparable. Since the most important mechanism of HIV transmission is sexual intercourse, it is important to know the extent of multiple sexual partners. The 2003 KDHS data show that only 2 percent of women and 12 percent of men report having had more than one sexual partner in the 12 months prior to the sur- vey. Summary of Findings | xxiii HIV Prevalence. In the one-half of the households selected for the man’s survey, all women and men who were interviewed were asked to voluntarily provide some drops of blood for HIV testing in the laboratory. Results indicate that 7 percent of Kenyan adults are infected with HIV. HIV prevalence is nearly 9 percent among women age 15 to 49 and under 5 percent among men 15 to 54. The female-to-male ratio is higher than that found in most population-based studies in Africa and is due to the fact that young women are particularly vulnerable to HIV infection com- pared to young men. The peak prevalence among women is at age 25 to 29 (13 percent), while prevalence rises gradually with age among men to peak at age 40 to 44 (9 percent). Only in the 45 to 49 year age group is HIV prevalence among men higher than that for women. Patterns of HIV Prevalence. Urban resi- dents have a significantly higher risk of HIV in- fection (10 percent) than rural residents (6 per- cent). The HIV epidemic also shows regional het- erogeneity. Nyanza Province has an overall preva- lence of 15 percent, followed by Nairobi with 10 percent. All other provinces have levels between 4 percent and 6 percent overall, except North East- ern Province where no respondent tested positive. Women and men who are widowed have signifi- cantly higher rates than married respondents. Sur- vey findings indicate that there is a strong rela- tionship between HIV prevalence and male cir- cumcision; 13 percent of men who are uncircum- cised are HIV infected, compared with 3 percent of those who are circumcised. Among couples who are married or living together, 7 percent are discordant, with one partner infected and the other uninfected. GENDER-RELATED VIOLENCE Violence Since Age 15. Not only has domes- tic violence against women been acknowledged worldwide as a violation of the basic human rights of women, but an increasing amount of research highlights the health burdens, intergenerational effects, and demographic consequences of such violence. In the 2003 KDHS, women were asked if they had experienced violence since age 15. The data show that half of women have experienced violence since they were 15 and one in four reported experienc- ing violence in the 12 months preceding the survey. The main perpetrators are husbands, and to a lesser extent, teachers, mothers, fathers and brothers. Marital Violence. Twenty-six percent of ever- married women report having experienced emotional violence by husbands, 40 percent report physical vio- lence and 16 percent report sexual violence. Almost half (47 percent) of ever-married women report suffer- ing emotional, physical or sexual violence, while 8 percent have experienced all three forms of violence by their current or most recent husband. Two in three women who have experienced physical or sexual vio- lence by their husbands have experienced such vio- lence in the 12 months preceding the survey. One- quarter of ever-abused women (26 percent) have ex- perienced spousal violence three or more times in the last 12 months. The factor most strongly related to marital violence is husband’s alcohol and/or drug use; violence is 2-3 times more prevalent among women who say their husbands get drunk or take illegal drugs very often compared to those whose husbands do not drink or take illegal drugs. Attitudes Towards Marital Violence. To gauge the acceptability of domestic violence, women and men interviewed in the 2003 KDHS were asked whether they thought a husband would be justified in hitting or beating his wife in each of the following five situations: if she burns the food; if she argues with him; if she goes out without telling him; if she neglects the children; and if she refuses to have sexual relations with him. Results show that two-thirds of Kenyan women and men agree that at least one of these factors is sufficient justification for wife beating. Female Genital Cutting. Survey data show that 32 percent of Kenyan women are circumcised. This represents a decline from the level recorded in the 1998 KDHS (from 38 to 31 percent, excluding the northern districts so as to be comparable). Sudan Ethiopia Uganda Somalia NORTH EASTERN EASTERN COAST CCCENTRALC NANA ROBIROBNAIROBNAIROBAIROAIROB Tanzania NYANZAN W NRNWESTERNWESTERN RIFT VALLEY I N D I A N OCEAN L a k e T u rk a n a Laakea Victooriaooriaoria KENYA xxiv | Map of Kenya Introduction | 1 INTRODUCTION 1 Fredrick Otieno and Silas Opiyo 1.1 GEOGRAPHY, HISTORY, AND THE ECONOMY Geography Kenya is situated in the eastern part of the African continent. The country lies between 5 degrees north and 5 degrees south latitude and between 24 and 31 degrees east longitude. It is almost bisected by the equator. Tanzania borders it to the south, Uganda to the west, Ethiopia and Sudan to the north, Soma- lia to the northeast, and the Indian Ocean to the southeast. The coastline and the port in Mombasa enable the country to trade easily with other countries. The country is divided into 8 provinces and 72 districts. It has a total area of 582,646 square kilo- metres of which 571,466 square kilometres form the land area. Approximately 80 percent of the land area of the country is arid or semiarid, and only 20 percent is arable. The country has diverse physical features, including the Great Rift Valley, which runs from north to south; Mount Kenya, the second highest mountain in Africa; Lake Victoria, the largest freshwater lake on the continent; Lake Nakuru, a major tourist attraction because of its flamingos; Lake Magadi, famous for its soda ash; and a number of rivers, including Tana, Athi, Yala, Nzoia, and Mara. The country falls into two regions: lowlands, including coastal and lake basin lowlands, and high- lands, which extend on both sides of the Great Rift Valley. Rainfall and temperatures are influenced by altitude and proximity to lakes or the ocean. There are four seasons in a year: a dry period from January to March, the long rainy season from March to May, followed by a long dry spell from May to October, and then the short rains between October and December. History Kenya is a former British colony. The independence process was met with resistance and an armed struggle. The Mau Mau rebellion in the 1950s paved the way for constitutional reform and political development in the following years. The country achieved self-rule in June 1963 and gained independ- ence (Uhuru) on December 12, 1963. Exactly one year later, Kenya became a republic. The country has had a stable government and political tranquility since becoming independent. The country was a multi- party state until 1981, when the relevant parts of the constitution were amended to create a one-party state. However, in the early 1990s, the country reverted to a multiparty state. From the start of its ind- pendence until December 2002, the country was ruled by the Kenya African National Union. During the 2002 general elections, the National Alliance of Rainbow Coalition ascended to power through a land- slide victory. The country has about 42 ethnic groups which are distributed throughout the country. Major tribes include Kikuyu, Luo, Kalenjin, Luhya, Kamba, Kisii, Mijikenda, Somali, and Meru. In Kenya, English is the official language while Kiswahili is the national language. Main religions in the country are Christianity and Islam. 2 | Introduction Economy The Kenyan economy is predominantly agricultural with a strong industrial base. The agriculture sector contributes 25 percent of the gross domestic product (GDP). Coffee, tea, and horticulture (flowers, fruits, and vegetables) are the main agricultural export commodities; in 2002, the three commodities jointly accounted for 53 percent of the total export earnings (Central Bureau of Statistics, 2003a). The manufacturing sector contributes about 13 percent of the total GDP and contributes significantly to export earnings, especially from the Common Market for Eastern and Southern Africa (COMESA) region. De- spite recent declines, the tourism sector has also contributed to improving the living standards of Ken- yans. The economy has undergone a structural transformation since 1964. There has been gradual decline in the share of the GDP attributed to agriculture, from over 30 percent during the period 1964-1979 to 25 percent in 2000-2002. The manufacturing sector has expanded from about 10 percent of the GDP in the period 1964-1973 to 13 percent in 2000-2002. The performance of the Kenyan economy since the country became independent has been mixed. In the first decade after the country’s independence, the economy grew by about 7 percent per annum, attributed to expansion in the manufacturing sector and an increase in agricultural production. Since then, there has been a consistent decline in the economy, reaching the lowest GDP growth level of about 2 per- cent between 1996 and 2002. The consistent poor growth performance has failed to keep pace with popu- lation growth. The weak performance has been due to external shocks and internal structural problems, including the drought of the 1980s, low commodity prices, world recession, bad weather, and poor infra- structure. The poor growth of the economy has contributed to a deterioration in the overall welfare of the Kenyan population. Similarly, the economy has been unable to create jobs at a rate to match the rising labour force. Poverty has increased, such that about 56 percent of the population live in poverty and over half live below the absolute poverty level (Central Bureau of Statistics, 2003a). The number of poor peo- ple is estimated to have risen from 11 million in 1990 to 17 million in 2001. The worsening living stan- dard is shown by rising child mortality rates, increasing rates of illiteracy, and rising unemployment lev- els. The HIV/AIDS pandemic has also had a devastating impact on all sectors of the economy, through loss of production and labour force. Against this background, the government of Kenya in 2003 launched the Economic Recovery Strategy for Wealth and Employment Creation, aimed at restoring economic growth, generating employment opportunities, and reducing poverty levels (Ministry of Planning and Na- tional Development, 2003). The government is convinced that employment creation is the most effective strategy for halting the increasing poverty. 1.2 POPULATION The population of Kenya increased from 10.9 million in 1969 to 28.7 million in 1999 (Central Bureau of Statistics, 1994, 2001a) (see Table 1.1). The results of the previous censuses indicate that the annual population growth rate was 2.9 percent per annum during the 1989-1999 period, down from 3.4 percent reported for both the 1969-1979 and 1979-1989 inter-censal periods. The decline in population growth is a realisation of the efforts contained in the National Population Policy for Sustainable Devel- opment (National Council for Population and Development, 2000) and is a result of the decline in fertility rates since the mid-1980s. In contrast, mortality rates have risen since the 1980s, presumably due to in- creased deaths from the HIV/AIDS epidemic, deterioration of health services, and widespread poverty (National Council for Population and Development, 2000). As a result of changing population dynamics, the total population of Kenya was projected to be 32.2 million by 2003 (Central Bureau of Statistics, 2002d). Introduction | 3 The crude birth rate increased from 50 per 1,000 in 1969 to 54 per 1,000 in 1979, but has declined to 48 and 41 per 1,000 in 1989 and 1999, respectively. After a long decline, the crude death rate has in- creased from 11 per 1,000 in 1979-1989 to 12 per 1,000 for the 1989-1999 period. Similarly, the infant mortality rate decreased from 119 deaths per 1,000 live births in 1969, to 88 per 1,000 in 1979, and to 66 per 1,000 in 1989, but has since increased to 77 per 1,000 in 1999. As a result of the high fertility and de- clining mortality in the past, the country is characterised by a youthful population, with almost 44 percent younger than 15 years and only 4 percent age 65 and older. The proportion of the population that resides in rural areas is still higher than the proportion in the urban areas. The urban population has increased from 10 percent in 1969 to 19 percent in 1999. Increased urbanisation levels have mainly resulted from rural-urban migration. 1.3 POPULATION AND FAMILY PLANNING POLICIES AND PROGRAMMES In 2000, the Government of Kenya launched the National Population Policy for Sustainable De- velopment (National Council for Population and Development, 2000). This sessional paper builds on the strength of Sessional Paper No. 4 of 1984. The current policy outlines ways of implementing the pro- gramme of action developed at the 1994 International Conference on Population and Development in Cairo. The implementation of this policy is being guided by the national and district plans of action for- mulated by the National Council for Population and Development (NCPD). The policy also addresses the issues of environment, gender, and poverty, as well as problems facing certain segments of the Kenyan population, such as the youth. The goals and objectives include full integration of population concerns into the development process; motivating and encouraging Kenyans to adhere to responsible parenthood; empowerment of women; and integration of the youth, elderly, and per- sons with disabilities into mainstream and national development. The overriding concern of the policy is the implementation of appropriate policies, strategies, and programmes that will shape the population growth to fit the available national resources over time, in order to improve the well-being and quality of life of individuals, the family, and the nation as a whole. The goals of the population policy include the following: • Improvement of the standard of living and quality of life; Table 1.1 Basic demographic indicators Selected demographic indicators for Kenya, 1969, 1979, 1989, 1999 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Indicator 1969 1979 1989 1999 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Population (millions) 10.9 16.2 23.2 28.7 Density (pop./km2) 19.0 27.0 37.0 49.0 Percent urban 9.9 15.1 18.1 19.4 Crude birth rate 50.0 54.0 48.0 41.3 Crude death rate 17.0 14.0 11.0 11.7 Inter-censal growth rate 3.3 3.8 3.4 2.9 Total fertility rate 7.6 7.8 6.7 5.0 Infant mortality rate (per 1,000 births) 119 88 66 77.3 Life expectancy at birth 50 54 60 56.6 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Source: CBS, 1970; CBS, 1981; CBS, 1994; CBS, 2002a 4 | Introduction • Improvement of the health and welfare of the people through provision of information and education on how to prevent premature deaths and illness among risk groups, especially among mothers and children; • Sustenance of the ongoing demographic transition to further reduce fertility and mortality, especially infant and child mortality; • Continuing motivation and encouragement of Kenyans to adhere to responsible parenthood • Promotion of stability of the family, taking into account equality of opportunity for family members, especially the rights of women and children; • Empowerment of women and the improvement of their status in all spheres of life and elimi- nation of all forms of discrimination, especially against the girl child; • Sustainability of the population programme; • Elimination of retrogressive sociocultural practices through education. The policy has the following set targets: • Reduction of the infant mortality rate per 1,000 live births from 71 in 1998, to 67 by 2005, and to 63 by 2010; • Reduction of the under-five mortality rate per 1,000 live births from 112 in 1998, to 104 by 2005, and to 98 by 2010; • Reduction of the maternal mortality rate per 100,000 births from 590 in 1998, to 230 by 2005, and to 170 by 2010; • Maintenance of the crude death rate per 1,000 population at 12 up to the year 2000 and reduc- ing it to 10 by 2005 and to 9 by 2010; • Minimisation of the decline in life expectancy at birth for both sexes from 58 in 1995 to 53 by 2010; • Stabilisation of the population growth rate at 2.1 percent per annum by 2010. 1.4 HEALTH PRIORITIES AND PROGRAMMES On behalf of the Government of Kenya, the Ministry of Health launched a National Health Sector Strategic Plan covering the period 1999-2004 (Ministry of Health, 1999b). The current strategic plan op- erationalises Kenya’s Health Policy Framework Paper approved and launched in 1994. The strategic plan was prepared with an aim of reforming the entire health sector. These reforms are part of the larger economic reforms contained in the Economic Recovery Strategy for Employment and Wealth Creation of 2003-2007. The strategic plan sets out a number of objectives and interventions, which seek to address this situation in the context of the ongoing health sector reforms over the five-year period. The objectives of the plan are to: • Ensure equitable allocation of government resources to reduce disparities in health resources; • Increase the cost-effectiveness and the cost-efficiency of resource allocation and use; • Continue to manage population growth; • Enhance the regulatory role of the government in all aspects of health care provision; • Create an enabling environment for increased private sector and community involvement for increased private sector provision and finance; • Increase and diversify per capita financial flows to the health sector. Introduction | 5 The vision of the Ministry of Health is to create an enabling environment for the provision of sustain- able quality health care that is acceptable, affordable, and accessible for all Kenyans. Within the frame- work of the vision, the strategic plan focuses on the critical areas in the health sector development agenda. To monitor the implementation of the strategic plan, the government has set various national health tar- gets: • Reduce iron deficiency anaemia in pregnant women by 30 percent; • Achieve 90 percent childhood immunisation coverage with all antigens in 85 percent of dis- tricts (from 63 percent of districts); • Reduce measles morbidity by 95 percent and mortality by 90 percent; • Reduce the incidence of neonatal tetanus to less than 1 death per 1,000 live births with a 100 percent reporting rate; • Eliminate vitamin A deficiency in children under five years; • Reduce malnutrition by 30 percent among children under five years; • Eradicate poliomyelitis by 2000 and reach certification by 2005; • Increase areas with family planning services from the current 60 percent of health care facili- ties to 75 percent; • Reduce malaria morbidity and mortality ratios by 30 percent; • Reduce the HIV prevalence rate from the current 13 to 14 percent by 10 percent and sexually transmitted infection prevalence by 50 percent; • Reduce the proportion of under-five morbidity and mortality rates attributable to measles, pneumonia, diarrhoea, malaria, and malnutrition from 70 to 40 percent; • Increase provision of safe water and improve sanitation in rural areas by 30 percent. 1.5 STRATEGIC FRAMEWORK TO COMBAT THE HIV/AIDS EPIDEMIC To meet the challenge of the HIV/AIDS epidemic in the country, the Government of Kenya ap- proved, in September 1997, Sessional Paper No. 4 on AIDS in Kenya (Ministry of Health, 1997). This was a clear intent of the government to support effective programmes to control the spread of AIDS, to protect the human rights of those with HIV or AIDS, and to provide care for those infected and affected by HIV/AIDS. The goal of the sessional paper is to “provide a policy framework within which AIDS pre- vention and control efforts will be undertaken for the next 15 years and beyond.” Specifically, it has the following objectives: • Give direction on how to handle controversial issues while taking into account prevailing cir- cumstances and the sociocultural environment. • Enable the government to play the leadership role in AIDS prevention and control activities. Challenges posed by AIDS call for a multisectoral approach, necessitating involvement from a diversity of actors. • Recommend an appropriate institutional framework for effective management and coordina- tion of HIV/AIDS programme activities. The sessional paper recognises that responding effectively to the HIV/AIDS crisis will require a strong political commitment at the highest level; implementation of a multisectoral prevention and control strategy with priority focus on young people; mobilisation of resources for financing HIV prevention, care, and support; and establishment of a National AIDS Control Council to provide leadership at the highest level possible. 6 | Introduction 1.6 OBJECTIVES AND ORGANISATION OF THE SURVEY The 2003 Kenya Demographic and Health Survey (KDHS) is the latest in a series of national level population and health surveys to be carried out in Kenya in the last three decades. The 2003 KDHS is designed to provide data to monitor the population and health situation in Kenya and to be a follow-up to the 1989, 1993, and 1998 KDHS surveys. The survey obtained detailed information on fertility levels; marriage; sexual activity; fertility preferences; awareness and use of family planning methods; breastfeeding practices; nutritional status of women and young children; childhood and maternal mortality; maternal and child health; and awareness and behaviour regarding HIV/AIDS and other sexually transmitted infections. New features of the 2003 KDHS include the collection of information on malaria and the use of mosquito nets, domestic violence, and HIV testing of adults. More specifically, the objectives of the 2003 KDHS were to: • At the national and provincial level, provide data that allow the derivation of demographic rates, particularly fertility and childhood mortality rates, which can be used to evaluate the achievements of the current national population policy for sustainable development; • Measure changes in fertility and contraceptive prevalence use and at the same time study the factors that affect these changes, such as marriage patterns, desire for children, availability of contraception, breastfeeding habits, and important social and economic factors; • Examine the basic indicators of maternal and child health in Kenya, including nutritional status, use of antenatal and maternity services, treatment of recent episodes of childhood ill- ness, use of immunisation services, use of mosquito nets, and treatment of children and preg- nant women for malaria; • Describe the patterns of knowledge and behaviour related to the transmission of HIV/AIDS and other sexually transmitted infections; • Estimate adult and maternal mortality ratios at the national level; • Ascertain the extent and pattern of domestic violence and female genital cutting in the coun- try; • Estimate the prevalence of HIV in the country at the national and provincial level and use the data to corroborate the rates from the sentinel surveillance system. The 2003 KDHS information is intended to provide data to assist policymakers and programme implementers to monitor and evaluate existing programmes and to design new strategies for demographic, social, and health policies in Kenya. The survey also provides data to monitor the country’s achievement of the Millenium Development Goals, as well as the Economic Recovery Strategy objectives. The 2003 KDHS was the first survey in the Demographic and Health Surveys (DHS) programme to cover the entire country, including North Eastern Province and other northern districts that had been excluded from the prior surveys (Turkana and Samburu in Rift Valley Province and Isiolo, Marsabit, and Moyale in Eastern Province). The survey collected information on demographic and health issues from a sample of women in the reproductive ages (15-49) and from men age 15-54 years in the one-in-two sub- sample of households selected for the male survey. Introduction | 7 1.7 SURVEY ORGANISATION The 2003 KDHS was implemented by the Central Bureau of Statistics (CBS) in collaboration with the Ministry of Health (including the National AIDS and STIs Control Programme [NASCOP] and the Kenya Medical Research Institute [KEMRI]) and NCPD. Technical assistance was provided through the MEASURE/ DHS+ programme, a project sponsored by the United States Agency for International Development (USAID) to carry out population and health surveys in developing countries. The Centers for Disease Control and Prevention (CDC) assisted in training the health field workers, supported the vol- untary counselling and testing of respondents who wanted to know their HIV status, and implemented the HIV testing in the laboratory. Financial support for the survey was provided by the Government of Kenya and a consortium of donors, namely, USAID, the United Nations Population Fund (UNFPA), Japan International Cooperation Agency (JICA)/United Nations Development Programme (UNDP), the United Nations Children’s Fund (UNICEF), the British Department for International Development (DFID), and CDC. 1.8 SAMPLE DESIGN The sample for the 2003 KDHS covered the population residing in households in the country. A representative probability sample of almost 10,000 households was selected for the KDHS sample. This sample was constructed to allow for separate estimates for key indicators for each of the eight provinces in Kenya, as well as for urban and rural areas separately. Given the difficulties in traveling and interview- ing in the sparsely populated and largely nomadic areas in the North Eastern Province, a smaller number of households was selected in this province. Urban areas were oversampled. As a result of these differing sample proportions, the KDHS sample is not self-weighting at the national level; consequently, all tables except those concerning response rates are based on weighted data. The survey utilised a two-stage sample design. The first stage involved selecting sample points (“clusters”) from a national master sample maintained by CBS (the fourth National Sample Survey and Evaluation Programme [NASSEP IV]). The list of enumeration areas covered in the 1999 population cen- sus constituted the frame for the NASSEP IV sample selection and thus for the KDHS sample as well. A total of 400 clusters, 129 urban and 271 rural, were selected from the master frame. The second stage of selection involved the systematic sampling of households from a list of all households that had been pre- pared for NASSEP IV in 2002. The household listing was updated in May and June 2003 in 50 selected clusters in the largest cities because of the high rate of change in structures and household occupancy in the urban areas. All women age 15-49 years who were either usual residents of the households in the sample or visitors present in the household on the night before the survey were eligible to be interviewed in the sur- vey. In addition, in every second household selected for the survey, all men age 15-54 years were eligible to be interviewed if they were either permanent residents or visitors present in the household on the night before the survey. All women and men living in the households selected for the Men’s Questionnaire and eligible for the individual interview were asked to voluntarily give a few drops of blood for HIV testing. 1.9 QUESTIONNAIRES Three questionnaires were used in the survey: the Household Questionnaire, the Women’s Ques- tionnaire and the Men’s Questionnaire. The contents of these questionnaires were based on model ques- tionnaires developed by the MEASURE DHS+ programme. 8 | Introduction In consultation with a broad spectrum of technical institutions, government agencies, and local and international organisations, CBS modified the DHS model questionnaires to reflect relevant issues in population, family planning, HIV/AIDS, and other health issues in Kenya. A number of thematic ques- tionnaire design committees were organised by CBS. Periodic meetings of each of the thematic commit- tees, as well as the final meeting, were also arranged by CBS. The inputs generated in these meetings were used to finalise survey questionnaires. These questionnaires were then translated from English into Kiswahili and 11 other local languages (Embu, Kalenjin, Kamba, Kikuyu, Kisii, Luhya, Luo, Maasai, Meru, Mijikenda, and Somali). The questionnaires were further refined after the pretest and training of the field staff. The Household Questionnaire was used to list all of the usual members and visitors in the se- lected households. Some basic information was collected on the characteristics of each person listed, in- cluding age, sex, education, and relationship to the head of the household. The main purpose of the Household Questionnaire was to identify women and men who were eligible for the individual interview. The Household Questionnaire also collected information on characteristics of the household’s dwelling unit, such as the source of water, type of toilet facilities, materials used for the floor and roof of the house, ownership of various durable goods, and ownership and use of mosquito nets. In addition, this question- naire was used to record height and weight measurements of women age 15-49 years and children under the age of 5 years, households eligible for collection of blood samples, and the respondents’ consent to voluntarily give blood samples. The HIV testing procedures are described in detail in the next section. The Women’s Questionnaire was used to collect information from all women age 15-49 years and covered the following topics: • Background characteristics (e.g., education, residential history, media exposure) • Reproductive history • Knowledge and use of family planning methods • Fertility preferences • Antenatal and delivery care • Breastfeeding • Vaccinations and childhood illnesses • Marriage and sexual activity • Woman’s work and husband’s background characteristics • Infant and child feeding practices • Childhood mortality • Awareness and behaviour about AIDS and other sexually transmitted diseases • Adult mortality including maternal mortality. The Women’s Questionnaire also included a series of questions to obtain information on women’s experience of domestic violence. These questions were administered to one woman per house- hold. In households with two or more eligible women, special procedures were followed, which ensured that there was random selection of the woman to be interviewed. The Men’s Questionnaire was administered to all men age 15-54 years living in every second household in the sample. The Men’s Questionnaire collected similar information contained in the Women’s Questionnaire, but was shorter because it did not contain questions on reproductive history, maternal and child health, nutrition, maternal mortality, and domestic violence. All aspects of the KDHS data collection were pretested in November and December 2002. Thir- teen teams (one for each language) were formed, each with one female interviewer, one male interviewer, and one health worker. The 39 team members were trained for two weeks and then proceeded to conduct Introduction | 9 interviews in the various districts in which their language was spoken. In total, 260 households were cov- ered in the pretest. The lessons learnt from the pretest were used to finalise the survey instruments and logistical arrangements for the survey. The pretest underscored the desirability of inluding voluntary counselling and testing (VCT) for HIV/AIDS as an integral part of the survey, since many respondents during the pretest wanted to know their HIV status. 1.10 HIV TESTING In all households selected for the Men’s Questionnaire, all eligible women and men who were in- terviewed were asked to voluntarily provide some drops of blood for HIV testing. The protocol for the blood specimen collection and analysis was based on the anonymous linked protocol developed by the DHS programme and approved by ORC Macro’s Institutional Review Board. This protocol was revised and enhanced by KEMRI and CDC. It was reviewed and approved by the Scientific and Ethical Review Committees of KEMRI and by the Institutional Review Board and Director of CDC in Atlanta, Georgia. The protocol allowed for the linking of the HIV results to the sociodemographic data collected in the in- dividual questionnaires, provided that the information that could potentially identify an individual was destroyed before the linking took place. This required that identification codes be deleted from the data file and that the back page of the Household Questionnaire, containing the barcode labels and names of respondents, be destroyed prior to merging the HIV results with the individual data file. For the purposes of blood sample collection, a health worker was included in each of the 17 field teams. The health workers were recruited with the assistance of the Ministry of Health. To obtain in- formed consent for taking blood for HIV testing, the health worker explained the procedures, the confi- dentiality of the data, and the fact that test results could not be traced back to or made available to the sub- ject; the health worker also provided respondents with information about how they could obtain their HIV status through VCT services. If consent was granted, the health worker then collected a dried blood spot (DBS) sample on a filter paper card from a finger prick, using a single-use, spring-loaded, sterile lancet. Each DBS sample was given a barcode label, with a duplicate label attached to the Household Question- naire on the line showing consent for that respondent. The health worker affixed a third copy of the same barcode label to a Blood Sample Transmittal Form in order to track the blood samples from the field to the laboratory. Filter papers were dried overnight in a plastic drying box, after which the health worker packed them in individual Ziploc bags with desiccant and a humidity indicator card and placed them in a larger Ziploc bag with other blood spots for that particular sample point. Blood samples were periodically collected in the field along with the completed questionnaires and transported to CBS headquarters in Nairobi for logging in, after which they were taken to the CDC laboratory at KEMRI headquarters in Nai- robi for HIV testing. At the laboratory, the DBS samples were each assigned a laboratory number and kept frozen until testing was started in early September. After the samples were allowed to attain room temperature, scis- sors were used to cut a circle at least 6.3 mm in diameter. The blots were placed in cryo-vials that con- tained 200 µl of elution buffer and were labeled with the lab number. The vials were left to elute over- night at 4oC, then they were centrifuged at 2,500 rpm for 10 minutes. These eluates were then tested with an Enzygnost Anti-HIV-1/2 Plus enzyme-linked immunosorbent assay (ELISA) test kit (DADE Behring HIV-1/2) for verification purposes. All positive samples and 10 percent of negative samples were then tested with a Vironostika HIV-1 MicroELISA System (Organon Teknika). Finally, 29 discrepant samples were tested by an INN-OLIA HIV confirmation Western blot kit (Innogenetics, Belgium). 1.11 TRAINING In February and early March 2003, CBS staff responsible for the survey spent considerable effort in recruiting people with the requisite skills to work as field staff. Most of those recruited were university 10 | Introduction graduates, and many had experience either with a previous KDHS or similar surveys, such as the Behav- ioural Surveillance Survey or the DHS-type survey that was conducted in Nairobi slum areas by the Afri- can Population and Health Research Centre. CBS then organized a three-week training course from March 17 to April 5, 2003, at the Izaak Walton Inn in Embu. A total of 146 field personnel were trained as interviewers, supervisors, health workers and data processing staff. Because of the large number involved, trainees were divided into three groups and trained separately on questionnaire administration. They came together in plenary sessions for special lectures. Four trainers were assigned to each group. The trainers were officers of CBS and NCPD as well as staff from ORC Macro. In addition to the 12 main trainers, guest lecturers gave presentations in ple- nary sessions on specialised topics, such as family planning; Kenya’s Program on Integrated Management of Childhood Illnesses; nutrition and anthropometric measurements; HIV/AIDS; and Kenya’s VCT pro- gramme for HIV/AIDS. All participants were trained on interviewing techniques and the contents of the KDHS question- naires. The training was conducted following the standard DHS training procedures, including class pres- entations, mock interviews, and four written tests. All of the participants were trained on how to complete the Women’s Questionnaire and how to take anthropometric measurements. Late in the second week of training, the health workers were split off from the other three groups to form a fourth group. Staff from KEMRI, CDC/Kenya, and ORC Macro trained the health workers on informed consent procedures, taking blood spots for HIV testing, and procedures for minimising risks in handling blood products (“universal precautions”). Meanwhile, the other trainees practiced interviewing in their local languages. During the final week, the whole group visited households in two sites close to the training center for practical interviews. Towards the end of the training programme, some trainees were selected as su- pervisors and field editors. This group was further trained on how to supervise fieldwork and editing of the questionnaires in the field. 1.12 FIELDWORK Data collection took place over a five-month period, from April 18 to September 15, 2003. Sev- enteen interviewing teams were involved in the exercise. Each team consisted of one supervisor, one field editor, four female interviewers, one male interviewer, one health worker, and one driver. The Maasai- speaking team and the two Somali-speaking teams had fewer female interviewers. Five senior staff from CBS coordinated and supervised fieldwork activities. ORC Macro participated in field supervision for interviews, weight and height measurements, and blood sample collection. To ensure that respondents could learn their HIV status, CDC/Kenya (in collaboration with KEMRI and NASCOP) organised a parallel team of two VCT counselors to work with each of the data collection teams (except in Nairobi, where VCT is accessible through many fixed sites). These mobile VCT teams followed the same protocol applied in fixed VCT sites according to the National Guidelines for Voluntary Counselling and Testing for HIV (Ministry of Health, 2003). This includes discussing the clients’ reasons for coming for counselling and testing, their risk factors, and implications of test out- comes, followed by anonymous testing for HIV for those requesting the service. A finger prick was per- formed to collect several drops of blood for simultaneous (parallel) testing performed with two simple, rapid HIV test kits (Abbott Determine HIV 1/2 and Trinity Biotech Uni-Gold); for quality control, a dried blood spot filter paper was collected on every fifth client for testing in the laboratory. During the 15 min- utes while the test was developing, prevention counselling was provided. If the two test results were dis- Introduction | 11 crepant, a third test (Instascreen) was performed as a “tiebreaker.” Post-test counselling was then pro- vided. In the field, the team supervisors and counsellors worked with local officials to locate suitable places within or adjacent to the cluster in which the counsellors could provide VCT services that were accessible and allowed privacy for testing and counselling. The plan was for the two VCT counsellors to “leapfrog” each other, with one staying behind for one or two days after the interviewing team left the area and the other moving ahead of the team to set up services in advance. In practice, this was not always possible because of transport logistics problems. CDC/Kenya also printed a brochure on HIV/AIDS and VCT for the team’s health workers to provide all households and survey respondents. Similarly, numbered vouchers were printed and left with eligible respondents. The vouchers were to be given to the mobile VCT teams or the fixed VCT site when the eligible respondents went for VCT. NASCOP and CDC/Kenya also made arrangements with the few fixed VCT sites charging for services, so that they would provide free services to KDHS clients and send the vouchers back to CDC for reimbursement. Finally, although the VCT teams were to give priority to clients presenting the KDHS vouchers, they also accepted any other clients from the sampled communi- ties. Over 10,600 clients, both respondents and other community members, sought and received free VCT services through the KDHS. 1.13 DATA PROCESSING The processing of the 2003 KDHS results began shortly after the fieldwork commenced. Com- pleted questionnaires were returned periodically from the field to CBS offices in Nairobi, where they were edited and entered by data processing personnel specially trained for this task. Data were entered using CSPro. All data were entered twice (100 percent verification). The concurrent processing of the data was a distinct advantage for data quality, since CBS was able to advise field teams of errors detected during data entry. The data entry and editing phase of the survey was completed in October 2003. 1.14 RESPONSE RATES Table 1.2 shows response rates for the survey. A total of 9,865 households were selected in the sample, of which 8,889 were occupied and therefore eligible for interviews. The shortfall was largely due to structures that were found to be vacant or destroyed. Of the 8,889 existing households, 8,561 were suc- cessfully interviewed, yielding a household response rate of 96 percent. In the households interviewed in the survey, 8,717 eligible women were identified; interviews were completed with 8,195 of these women, yielding a response rate of 94 percent. With regard to the male survey results, 4,183 eligible men were identified in the subsample of households selected for the male survey, of whom 3,578 were successfully interviewed, yielding a response rate of 86 percent. The response rates are higher in rural areas, as compared with urban areas both for males and females. More detailed tables on response rates for women and men are given in Appendix A. The principal reason for nonresponse among both eligible men and women was the failure to find individuals despite repeated visits to the household and even sometimes the work place. The substantially lower response rate for men reflects the more frequent and longer absences of men from the household. Response rates for the HIV testing component were lower than those for the interviews. Details of the HIV testing response rates are discussed in Chapter 13. 12 | Introduction Table 1.2 Results of the household and individual interviews Number of households, number of interviews, and response rates, accord- ing to residence, Kenya 2003 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Residence ––––––––––––––––– Result Urban Rural Total ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Household interviews Households selected 3,423 6,442 9,865 Households occupied 3,068 5,821 8,889 Households interviewed 2,893 5,668 8,561 Household response rate 94.3 97.4 96.3 Interviews with women Number of eligible women 3,019 5,698 8,717 Number of eligible women interviewed 2,751 5,444 8,195 Eligible woman response rate 91.1 95.5 94.0 Household interviews for male subsample Households selected 1,680 3,188 4,868 Households occupied 1,505 2,891 4,396 Households interviewed 1,420 2,814 4,234 Household response rate for male subsample 94.4 97.3 96.3 Interviews with men Number of eligible men 1,466 2,717 4,183 Number of eligible men interviewed 1,150 2,428 3,578 Eligible man response rate 78.4 89.4 85.5 Household Population and Housing Characteristics | 13 HOUSEHOLD POPULATION AND HOUSING CHARACTERISTICS 2 Francis M. Munene This chapter presents information on the social, economic, and demographic characteristics of the household population, focusing mainly on such background characteristics as age, sex, educational atten- dance and attainment, place of residence, and socio-economic conditions of households. The information provided is intended to facilitate interpretation of the key demographic, socioeconomic, and health indi- ces. It is further intended to assist in the assessment of the representativeness of the survey. One of the background characteristics used throughout this report is an index of socioeconomic status. The economic index used here was recently developed and tested in a large number of countries in relation to inequities in household income, use of health services, and health outcomes (Rutstein et al., 2000). It is an indicator of the level of wealth that is consistent with expenditure and income measures (Rutstein, 1999). The economic index was constructed using household asset data with principal compo- nents analysis. The asset information was collected through the Household Questionnaire of the 2003 KDHS and covers information on household ownership of a number of consumer items ranging from a television to a bicycle or car, as well as dwelling characteristics, such as source of drinking water, sanita- tion facilities, and type of material used for flooring. Each asset was assigned a weight (factor score) generated through principal components analysis, and the resulting asset scores were standardised in relation to a normal distribution with a mean of zero and standard deviation of one (Gwatkin et al., 2000). Each household was then assigned a score for each asset, and the scores were summed for each household; individuals were ranked according to the total score of the household in which they resided. The sample was then divided into quintiles from one (low- est) to five (highest). A single asset index was developed for the whole sample; separate indices were not prepared for the urban and rural population separately. 2.1 HOUSEHOLD POPULATION BY AGE AND SEX The 2003 KDHS Household Questionnaire solicited information on key demographic and socio- economic characteristics; parental survivorship and residence for people age 15 years and under; educa- tional attendance/attainment; and housing characteristics. A household was defined as a person or group of people, related or unrelated to each other, who live together in the same dwelling unit and share a com- mon source of food. Table 2.1 presents the distribution of the 2003 KDHS household population by five-year age groups, according to sex and urban-rural residence. The household population constitutes 37,128 persons, of which 49 percent are males and 51 percent are females. There are more persons in the younger age groups than in the older groups for both sexes. Figure 2.1 shows the age-sex structure of the Kenyan population. The household population age- sex structure is still wide based, as depicted by the population pyramid, despite evidence that the percent- age share of the younger population has been falling while the percentage of those age 15-64 has been increasing. The KDHS household population has a median age of 17.5, a slight increase from the previous 14 | Household Population and Housing Characteristics Figure 2.1 Population Pyramid 80+ 75-79 70-74 65-69 60-64 55-59 50-54 45-49 40-44 35-39 30-34 25-29 20-24 15-19 10-14 5-9 0-4 0246810 0 2 4 6 8 10 KDHS 2003 Age Male Percent Female Table 2.1 Household population by age, sex, and residence Percent distribution of the de facto household population by five-year age groups, according to sex and resi- dence, Kenya 2003 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Urban Rural Total ––––––––––––––––––––––– –––––––––––––––––––––– ––––––––––––––––––––––– Age Male Female Total Male Female Total Male Female Total ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– <5 14.6 13.9 14.2 16.6 16.1 16.4 16.2 15.7 15.9 5-9 10.9 11.2 11.0 15.7 14.7 15.2 14.7 14.0 14.4 10-14 9.6 10.4 10.0 16.3 14.4 15.4 15.0 13.6 14.3 15-19 9.2 11.2 10.2 12.0 10.3 11.1 11.4 10.5 10.9 20-24 12.5 15.1 13.8 7.8 8.2 8.0 8.7 9.5 9.1 25-29 11.9 11.2 11.5 5.8 6.9 6.4 7.0 7.8 7.4 30-34 8.6 8.3 8.5 5.1 5.6 5.3 5.8 6.2 6.0 35-39 7.0 6.0 6.5 4.0 4.6 4.3 4.6 4.9 4.7 40-44 4.9 4.4 4.6 3.9 4.5 4.2 4.1 4.4 4.3 45-49 3.7 2.9 3.3 2.6 2.9 2.8 2.9 2.9 2.9 50-54 2.9 2.3 2.6 2.5 3.3 2.9 2.6 3.1 2.9 55-59 1.9 1.3 1.6 2.1 2.4 2.2 2.0 2.2 2.1 60-64 1.0 0.9 1.0 1.7 1.8 1.8 1.6 1.6 1.6 65-69 0.6 0.3 0.4 1.2 1.3 1.2 1.0 1.1 1.1 70-74 0.4 0.2 0.3 1.1 1.3 1.2 1.0 1.1 1.0 75-79 0.1 0.3 0.2 0.7 0.6 0.7 0.6 0.6 0.6 80+ 0.2 0.1 0.2 0.8 0.9 0.9 0.7 0.8 0.7 Don't know/missing 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Number 3,663 3,680 7,344 14,627 15,157 29,784 18,291 18,837 37,128 Household Population and Housing Characteristics | 15 observed population samples (15.3 in 1993 and 16.9 in 1998). This is an indication that the Kenyan popu- lation is aging, most probably because of the decline in fertility in the 1980s and 1990s. The share of the Kenyan population under 15 years of age is 45 percent, those age 15-64 constitute 52 percent, and those age 65 years and above make up 3 percent of the total Kenyan household population. This means that the age dependency ratio in Kenya has declined from 127 in 1989, to 98 in 1998, and to 92 in 2003.1 2.2 HOUSEHOLD COMPOSITION Table 2.2 shows the distribution of households by sex of the head of household and by household size, according to rural-urban residence and province. At the national level, women head 32 percent of Kenyan households, a pattern that has remained more or less constant since the 1993 KDHS but is lower than the 37 percent from the 1999 population census (Central Bureau of Statistics, 2002g :11). There are modest differences in female-headed households between urban (26 percent) and rural areas (34 percent). Regional differentials are relatively modest, with Western, Nyanza, and Eastern provinces registering the highest proportions of female-headed households (38, 37, and 36 percent, respectively), while Nairobi Province has the lowest (20 percent). Table 2.2 also shows that the mean size of a Kenyan household is 4.4 persons, identical to the mean household size of 4.4 found in the 1999 population census (Central Bureau of Statistics, 2002g: 15). When the northern areas of Kenya are excluded for comparison with previous surveys, the mean house- hold size is 4.3 in 2003, a drop from the 4.8 persons per household reported in the 1993 KDHS, but iden- tical to the 1998 KDHS level of 4.3. 1 The dependency ratio is defined as the sum of all persons under 15 years or over 64 years of age, divided by the number of persons age 15-64, multiplied by 100. Table 2.2 Household composition Percent distribution of households by sex of head of household and by household size, according to residence and province, Kenya 2003 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Residence Province ––––––––––––– ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Rift North Characteristic Urban Rural Nairobi Central Coast Eastern Nyanza Valley Western Eastern Total ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Sex of head of household Male 74.4 66.2 79.9 65.8 71.9 64.2 63.4 72.4 62.2 70.2 68.3 Female 25.6 33.8 20.1 34.2 28.1 35.8 36.6 27.6 37.8 29.8 31.7 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Number of usual members 1 22.6 11.1 22.0 18.0 16.2 11.3 12.0 11.9 12.4 3.7 14.0 2 18.1 9.9 20.2 12.6 12.9 10.6 11.7 10.8 8.7 8.3 12.0 3 16.3 13.8 17.2 17.5 14.6 13.1 14.4 12.9 13.5 10.0 14.4 4 14.9 15.7 15.0 18.4 13.5 15.0 15.9 13.9 17.1 10.8 15.5 5 11.2 15.3 11.3 15.4 11.2 13.9 14.4 15.9 14.4 14.1 14.3 6 7.0 12.4 6.7 8.1 10.5 12.0 12.4 12.4 12.7 16.0 11.1 7 4.4 9.4 4.3 5.2 6.7 10.6 8.9 9.3 9.1 14.5 8.2 8 2.5 5.7 1.6 2.6 5.4 5.7 4.7 6.5 5.9 9.6 4.9 9+ 3.0 6.6 1.7 2.2 8.9 7.8 5.6 6.4 6.4 13.1 5.7 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Number of households 2,136 6,405 837 1,350 683 1,313 1,278 1,927 966 187 8,542 Mean size 3.5 4.7 3.3 3.8 4.4 4.7 4.5 4.6 4.6 5.7 4.4 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Note: Table is based on de jure members, i.e., usual residents. 16 | Household Population and Housing Characteristics As expected, urban households have, on average, much smaller household sizes (3.5 persons) than rural households (4.7 persons). Wide variations in the average household sizes are also observed across provinces, with the largest household sizes occurring in North Eastern Province (5.7 persons) and the smallest in Nairobi (3.3 persons). 2.3 EDUCATIONAL ATTAINMENT OF HOUSEHOLD MEMBERS Tables 2.3.1 and 2.3.2 show the percent distribution of the female and male household population age six years and over by highest level of education attended, according to background characteristics. Twenty-three percent of females and 16 percent of males have no education at all, while about three in five women and men have some primary education or complete primary only. Among males, 22 percent have attained at least some secondary education, compared with only 17 percent of females. Table 2.3.1 Educational attainment of household population: females Percent distribution of the de facto female household population age six and over by highest level of education attended or completed, accord- ing to background characteristics, Kenya 2003 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Don’t Median Background No Primary Primary Secondary Secondary More than know/ number characteristic education incomplete complete1 incomplete complete2 secondary missing Total Number of years –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Age 6-9 41.8 57.9 0.0 0.0 0.0 0.0 0.3 100.0 2,166 0.0 10-14 9.6 88.1 1.2 0.8 0.0 0.0 0.2 100.0 2,566 3.1 15-19 7.8 51.9 18.5 16.7 4.5 0.6 0.0 100.0 1,981 6.5 20-24 8.1 27.4 30.9 9.6 17.4 6.4 0.2 100.0 1,797 7.5 25-29 10.3 29.4 28.6 7.6 14.6 9.2 0.2 100.0 1,462 7.4 30-34 13.0 32.0 22.9 9.2 14.4 7.9 0.5 100.0 1,159 7.2 35-39 14.7 25.3 26.4 11.3 14.3 7.3 0.7 100.0 915 6.5 40-44 25.7 24.5 20.1 9.6 12.0 7.8 0.3 100.0 837 5.9 45-49 33.2 27.5 18.0 7.4 8.1 4.9 0.8 100.0 543 4.0 50-54 40.6 29.4 18.1 2.5 4.5 3.7 1.2 100.0 587 2.4 55-59 57.8 26.5 8.6 1.1 1.5 2.6 1.9 100.0 414 0.0 60-64 73.9 20.9 3.7 0.3 0.5 0.5 0.3 100.0 305 0.0 65+ 80.5 16.2 1.8 0.3 0.0 0.2 1.0 100.0 665 0.0 Residence Urban 13.9 30.3 20.3 9.0 15.2 10.7 0.5 100.0 3,099 7.1 Rural 25.2 48.2 13.6 5.7 5.0 1.7 0.4 100.0 12,316 3.5 Province Nairobi 10.0 22.9 20.4 8.9 21.8 15.4 0.6 100.0 1,157 7.8 Central 12.0 43.1 20.5 8.2 10.8 5.0 0.5 100.0 2,234 6.1 Coast 37.8 36.7 13.0 3.5 5.8 2.7 0.5 100.0 1,222 2.0 Eastern 21.2 49.2 17.1 4.5 5.6 2.3 0.2 100.0 2,632 3.9 Nyanza 18.3 54.9 12.2 8.7 4.0 1.8 0.2 100.0 2,393 4.0 Rift Valley 28.6 43.4 13.8 5.3 5.8 2.6 0.4 100.0 3,594 3.5 Western 18.2 55.1 12.1 7.9 4.2 1.6 1.0 100.0 1,794 4.0 North Eastern 86.8 11.9 0.5 0.3 0.1 0.2 0.2 100.0 389 0.0 Wealth quintile Lowest 43.7 44.9 7.6 2.2 1.0 0.1 0.5 100.0 2,833 0.6 Second 25.9 52.5 12.9 5.6 2.3 0.3 0.4 100.0 3,085 3.2 Middle 22.8 51.3 14.5 6.3 4.3 0.5 0.3 100.0 3,205 3.6 Fourth 14.7 45.0 18.6 8.0 9.9 3.2 0.5 100.0 3,161 5.6 Highest 9.5 29.3 20.5 9.5 17.3 13.3 0.6 100.0 3,131 7.4 Total 22.9 44.6 15.0 6.4 7.1 3.5 0.4 100.0 15,415 4.3 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Note: Total includes 16 women whose age was not stated. 1 Completed grade 8 at the primary level 2 Completed form 4 at the secondary level Household Population and Housing Characteristics | 17 There has been a slight increase in the proportion of children and young adults who have never attended school between the 1998 KDHS and the 2003 KDHS, most notably among those age 6-9 years. Differences are diminished, however, when the northern areas of the country are excluded from the 2003 data so as to be comparable to the preceding surveys. Differences in the youngest age group (6-9) may be due to the addition of a code “0” in the 2003 survey to allow for preschool, such as nursery school and kindergarten. It is possible that children in Standard 1 were erroneously coded as having reached only level “0,” instead of level “1” for primary school. The proportion of the household population age six years and above who have attended school is higher for males than females in most age groups. However, the gender gap in the proportions with no education is narrower in 2003 than in 1998. Whereas about 95 percent of children of both sexes have at least some schooling, only 25 to 30 percent of young adults are able to complete secondary school. Table 2.3.2 Educational attainment of household population: males Percent distribution of the de facto male household population age six and over by highest level of education attended or completed, according to background characteristics, Kenya 2003 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Don’t Median Background No Primary Primary Secondary Secondary More than know/ number characteristic education incomplete complete1 incomplete complete2 secondary missing Total Number of years –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Age 6-9 45.2 54.3 0.0 0.0 0.0 0.0 0.4 100.0 2,195 0.0 10-14 8.6 89.8 1.0 0.6 0.0 0.0 0.1 100.0 2,741 2.8 15-19 5.7 61.9 13.0 14.9 3.8 0.1 0.6 100.0 2,084 6.0 20-24 5.1 29.3 25.4 10.6 21.4 7.4 0.8 100.0 1,594 7.6 25-29 5.8 26.5 27.2 7.0 22.3 10.9 0.3 100.0 1,287 7.7 30-34 5.8 24.8 24.8 7.8 25.0 11.7 0.2 100.0 1,055 7.9 35-39 8.3 12.7 33.3 11.0 21.8 12.4 0.5 100.0 843 7.6 40-44 11.7 18.1 27.6 6.5 24.8 10.7 0.6 100.0 749 6.8 45-49 14.6 21.3 23.2 8.3 17.8 14.0 0.9 100.0 523 6.7 50-54 17.6 24.2 25.8 8.2 12.0 11.8 0.5 100.0 471 6.4 55-59 18.2 25.5 28.2 9.2 9.7 7.8 1.4 100.0 369 6.3 60-64 34.6 26.6 17.6 5.7 7.2 6.6 1.7 100.0 287 3.0 65+ 47.9 34.6 9.9 2.8 2.1 1.6 1.1 100.0 611 0.3 Residence Urban 9.6 28.4 18.4 9.0 21.7 12.3 0.6 100.0 3,051 7.5 Rural 17.4 50.9 14.4 5.8 7.6 3.2 0.5 100.0 11,774 4.2 Province Nairobi 7.3 21.2 16.0 9.4 28.9 16.4 0.7 100.0 1,212 9.2 Central 6.8 44.6 20.8 8.3 12.4 6.4 0.6 100.0 2,123 6.4 Coast 23.5 39.4 17.9 5.3 10.2 3.0 0.7 100.0 1,190 4.0 Eastern 14.3 53.9 15.7 4.8 7.2 3.6 0.4 100.0 2,484 4.0 Nyanza 10.3 55.0 13.3 8.5 8.9 3.7 0.4 100.0 2,236 4.9 Rift Valley 22.7 44.4 14.4 4.6 9.1 4.3 0.5 100.0 3,465 4.2 Western 11.4 56.8 12.6 7.6 7.2 3.5 1.0 100.0 1,705 4.3 North Eastern 65.2 28.3 2.5 1.1 2.3 0.8 0.0 100.0 410 0.0 Wealth quintile Lowest 33.6 49.9 10.1 3.0 2.8 0.4 0.3 100.0 2,781 1.7 Second 16.9 56.4 14.1 5.4 5.2 1.3 0.7 100.0 2,900 3.7 Middle 14.5 53.8 15.5 6.9 7.3 1.4 0.5 100.0 2,910 4.5 Fourth 8.8 46.4 18.4 7.3 12.7 5.8 0.6 100.0 3,084 6.1 Highest 7.3 26.8 17.5 9.1 23.1 15.4 0.7 100.0 3,149 7.8 Total 15.8 46.3 15.2 6.5 10.5 5.1 0.6 100.0 14,825 5.0 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Note: Total includes 15 men whose age was not stated. 1 Completed grade 8 at the primary level 2 Completed form 4 at the secondary level 18 | Household Population and Housing Characteristics The median number of years of schooling completed by sex has increased slightly between 1998 and 2003 for both sexes when the northern areas of the country are excluded. Educational attainment is higher in urban areas than in rural areas. The median number of years of education is highest in Nairobi for both sexes and lowest in North Eastern Province. Almost two-thirds of males and 87 percent of fe- males age six and over in North Eastern Province have no education. Table 2.4 shows the percentage of the household population age 6-24 who are currently attending school, by age, sex, and residence. Eighty-nine percent of those age 6-15 are in school, with rural atten- dance identical to urban attendance and male attendance negligibly higher than female attendance (90 and 89 percent, respectively). However, at age group 16-20, attendance levels have dropped in half, and they are noticeably higher in rural than in urban areas and also considerably higher for males than females. A comparison of data from the 2003 KDHS and the 1998 KDHS shows that there is some im- provement in school attendance at all ages from 6 to 24 years. Excluding the north, the proportion of chil- dren age 6-15 attending school increased from 85 percent in 1998 to 93 percent in 2003. Figure 2.2 shows that attendance rates for both males and females are at par (89 percent) at age group 6-10. However, girls tend to drop out of school earlier than boys, such that at age group 11-15, 90 percent of boys and 88 percent of girls are attending school. After age 11-15, the gender gap begins to widen, such that by age 21-24, only 11 percent of males and 4 percent of females are in school. The larg- est drop in attendance for both sexes occurs at age 16-20 (51 and 37 percent for males and females, re- spectively). Table 2.4 School attendance Percentage of the de facto household population age 6-24 years currently attending school, by age, sex, and residence, Kenya 2003 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Male Female Total ––––––––––––––––––––––– –––––––––––––––––––––– ––––––––––––––––––––––– Age Urban Rural Total Urban Rural Total Urban Rural Total ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– 6-10 89.7 89.3 89.4 93.3 88.4 89.2 91.6 88.9 89.3 11-15 91.7 90.2 90.4 82.5 89.4 88.3 87.0 89.8 89.4 6-15 90.6 89.7 89.9 88.3 88.9 88.8 89.4 89.3 89.3 16-20 35.5 55.1 51.3 23.0 41.5 36.9 28.6 48.5 44.1 21-24 13.6 9.4 10.6 4.8 3.4 3.8 8.7 6.2 6.9 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Note: Table includes children attending kindergarten/pre-school. Household Population and Housing Characteristics | 19 Figure 2.2 Percentage of Males and Females Currently Attending School, by Age KDHS 2003 , , , , # # # # 6-10 11-15 16-20 21-24 Age in years 0 20 40 60 80 100 Male Female# , Table 2.5 presents net attendance ratios (NARs) and gross attendance ratios (GARs) for the household population by level of schooling and sex, according to background characteristics. The NAR for primary school measures the proportion of children of primary school age who are attending primary school, while the GAR represents the total number of primary school students of any age from 5 to 24 as a percentage of children of primary school age. In the Kenyan context, the levels refer to 6 to 13 years for primary and 14 to 17 years for secondary. The GAR is usually higher than the NAR because the GAR includes participation of those who may be older or younger than the official age range for that level. Stu- dents who are over age for a given level of school may have started school late, may have repeated one or more grades in school, or may have dropped out of school and later returned. The NAR indicates that 79 percent of children of primary school age are attending primary school. There is no gender gap among the children who are attending primary school; the NAR is 79 per- cent for both boys and girls. NARs for primary school are higher in urban (83 percent) than in rural areas (78 percent) and are highest in the Central (91 percent), Western (86 percent), Nairobi (85 percent) and Eastern (85 percent) provinces. Ratios are lowest in North Eastern Province (36 percent). The GAR indi- cates that there are children in primary school who are not of primary school age, with ratios of 113 for males and 106 for females. As expected, both the NAR and GAR are lower at the secondary school level. The NAR indicates that only 13 percent of the secondary school age population are attending secondary school. Net secon- dary school attendance is higher for females (NAR of 13) than for males (NAR of 12). Nairobi, Central, and Nyanza provinces have the highest NARs at the secondary level of 32, 19, and 14 percent respec- tively, while North Eastern Province has the lowest (2 percent). The GAR shows that there are many sec- ondary school students who are not of secondary school age. In fact, discrepancies between the NAR and GAR indicate that there are almost as many secondary school students who are either over age or under age as there are students of secondary school age. 20 | Household Population and Housing Characteristics Table 2.5 School attendance ratios Net attendance ratios (NAR) and gross attendance ratios (GAR) for the de jure household population by level of schooling and sex, according to background characteristics, Kenya 2003 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Net attendance ratio1 Gross attendance ratio2 Gender Background –––––––––––––––––––––––––– ––––––––––––––––––––––––– parity characteristic Male Female Total Male Female Total index3 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– PRIMARY SCHOOL ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Residence Urban 82.4 82.5 82.5 103.2 99.9 101.5 0.97 Rural 78.0 78.1 78.0 114.2 107.2 110.8 0.94 Province Nairobi 85.9 84.1 85.0 101.4 97.0 99.2 0.96 Central 90.6 91.1 90.8 121.9 119.4 120.7 0.98 Coast 71.9 67.2 69.7 98.8 86.0 92.8 0.87 Eastern 85.2 84.2 84.7 125.6 117.4 121.5 0.93 Nyanza 78.5 81.7 80.1 122.3 111.4 116.9 0.91 Rift Valley 70.9 73.9 72.4 101.6 98.3 99.9 0.97 Western 86.5 86.1 86.3 123.4 123.4 123.4 1.00 North Eastern 44.6 26.5 36.3 66.6 34.1 51.7 0.51 Wealth quintile Lowest 63.0 59.4 61.3 95.5 84.1 90.1 0.88 Second 79.0 81.0 79.9 116.5 112.2 114.4 0.96 Middle 83.5 84.1 83.8 122.7 116.0 119.3 0.94 Fourth 88.4 87.9 88.1 126.3 119.4 123.0 0.95 Highest 85.5 86.4 86.0 103.0 99.8 101.4 0.97 Total 78.6 78.8 78.7 112.7 106.1 109.5 0.94 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– SECONDARY SCHOOL ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Residence Urban 26.8 21.8 24.2 42.1 29.9 35.7 0.71 Rural 9.1 11.6 10.3 20.9 19.6 20.3 0.94 Province Nairobi 35.5 28.9 32.1 52.6 37.7 44.8 0.72 Central 19.0 19.4 19.2 31.2 29.6 30.4 0.95 Coast 8.4 11.0 9.7 17.6 12.7 15.1 0.72 Eastern 5.9 8.1 6.9 15.1 12.8 14.0 0.85 Nyanza 12.2 16.5 14.2 31.2 28.9 30.2 0.93 Rift Valley 10.6 8.6 9.7 18.0 14.6 16.4 0.81 Western 9.8 15.9 12.9 28.6 28.8 28.7 1.00 North Eastern 2.8 1.4 2.2 6.6 1.6 4.4 0.25 Wealth quintile Lowest 2.7 5.4 4.0 9.1 8.6 8.9 0.94 Second 6.7 7.9 7.3 20.9 17.3 19.2 0.83 Middle 11.1 11.6 11.4 23.9 19.4 21.8 0.81 Fourth 13.6 19.1 16.2 26.9 29.4 28.1 1.09 Highest 31.9 25.0 28.2 48.1 34.2 40.8 0.71 Total 11.7 13.4 12.5 24.0 21.4 22.7 0.89 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– 1 The NAR for primary school is the percentage of the primary-school-age (6-13 years) population that is attending primary school. The NAR for secondary school is the percentage of the secondary-school-age (14-17 years) popula- tion that is attending secondary school. By definition the NAR cannot exceed 100 percent. 2 The GAR for primary school is the total number of primary school students, expressed as a percentage of the offi- cial primary-school-age population. The GAR for secondary school is the total number of secondary school students, expressed as a percentage of the official secondary-school-age population. If there are significant numbers of over- age and underage students at a given level of schooling, the GAR can exceed 100 percent. 3 The Gender Parity Index for primary school is the ratio of the primary school GAR for females to the GAR for males. The Gender Parity Index for secondary school is the ratio of the secondary school GAR for females to the GAR for males. Household Population and Housing Characteristics | 21 The gender parity index shows the ratio of the female to male GARs. For the primary school level, the gender parity index is close to one (indicating parity between the sexes) for all groups except North East- ern Province, where the GAR for females is half that for males. For the secondary school level, the gender parity index is generally lower, especially for North Eastern Province. 2.4 HOUSING CHARACTERISTICS Given that there is a strong relationship between household economic conditions and exposure to diseases, information on housing characteristics, such as access to electricity, source of drinking water, sanitary facilities, and flooring and roofing materials, is key to explaining the interrelationships between the social and economic conditions of the household and likely exposure to and prevalence of diseases. Table 2.6 presents the percent distribution of households by housing characteristics, according to resi- dence and province. The table shows that only 16 percent of Kenyan households have electricity, with large discrep- ancies by urban-rural residence. Half of urban households have electricity, compared with only 5 percent of rural households. Wide regional variations in the supply of electricity are evident, with Nairobi Prov- ince registering the highest proportion of households (71 percent) connected to electricity supply. Western Province is least supplied, with only 2 percent of households having electricity. The predominant flooring materials used by Kenyan households are earth, mud, dung, and sand, with a share of 62 percent. Cement is the next most common flooring material, with a share of 34 percent. Seventy-one percent of urban households use cement for flooring their houses, while 77 percent of rural households use packed earth. These proportions are almost identical to those from the 1999 population census (Central Bureau of Statistics, 2002g: 30). About two-thirds of Kenyan households (69 percent) live in dwellings with corrugated iron (ma- bati) roofs, while almost all of the rest (22 percent) have grass or thatched roofs. Urban-rural differences in roofing material are not as strong as those for some of the other housing characteristics, with 73 percent of urban households having corrugated iron roofs, compared with 67 percent of rural households. Data from the 1999 population census show a slightly larger proportion of households with grass or thatched roofs (28 percent) and fewer with iron sheet roofs (64 percent), as compared with the 2003 KDHS (Cen- tral Bureau of Statistics, 2002g: 25). The 2003 KDHS collected data on the number of rooms used by members of the households for sleeping. This information provides a rough measure of the degree and severity of household crowding. Most households in Kenya (77 percent) have 1 to 2 persons sleeping together in a single room, and the mean is 2.6. For cooking fuel, two-thirds of Kenyan households depend on firewood. Urban households mostly use kerosene (51 percent) or charcoal (26 percent), while 85 percent of rural households use fire- wood. The 2003 KDHS collected information on the source of drinking water (Table 2.6). Almost one in four (24 percent) Kenyan households draws its drinking water from either rivers or streams; 21 percent have piped water connected to their dwelling, compound, or plot; and 11 percent use a public tap. Almost one in five households uses wells as a source of drinking water, the majority of which are covered or pro- tected wells. Less than 5 percent of households use other types of water supply sources. A majority of households (53 percent) are within 15 minutes of their water source. 22 | Household Population and Housing Characteristics Table 2.6 Housing characteristics Percent distribution of households by housing characteristics, according to residence and province, Kenya 2003 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Residence Province ––––––––––––– ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Housing Rift North characteristic Urban Rural Nairobi Central Coast Eastern Nyanza Valley Western Eastern Total ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Electricity Yes 50.2 4.6 71.4 19.2 19.3 6.9 5.1 10.5 1.6 3.2 16.0 No 49.8 95.2 28.5 80.4 80.5 93.1 94.9 89.5 98.2 95.9 83.9 Missing 0.0 0.2 0.1 0.4 0.2 0.0 0.0 0.1 0.2 1.0 0.1 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Flooring material Earth, mud, dung, sand 18.8 76.5 10.9 60.7 54.7 62.5 73.8 66.3 83.1 93.7 62.1 Wood planks 0.9 0.3 1.7 0.3 0.0 0.5 0.0 0.7 0.0 0.0 0.5 Palm, bamboo 0.0 0.1 0.0 0.0 0.0 0.0 0.0 0.2 0.0 0.0 0.1 Parquet, polished wood 1.2 0.1 3.0 0.1 0.1 0.0 0.0 0.1 0.0 0.0 0.4 Vinyl, asphalt strips 1.4 0.1 2.3 0.7 0.1 0.1 0.0 0.2 0.1 0.0 0.4 Ceramic tiles 2.1 0.3 4.4 0.8 0.4 0.1 0.3 0.5 0.1 0.1 0.8 Cement 71.4 22.1 70.7 36.2 41.8 35.6 25.8 31.4 16.5 6.0 34.4 Carpet 2.9 0.3 4.1 0.8 2.7 0.3 0.0 0.6 0.1 0.1 0.9 Other 1.2 0.0 2.7 0.0 0.1 0.3 0.0 0.0 0.0 0.0 0.3 Missing 0.2 0.2 0.1 0.3 0.1 0.6 0.0 0.0 0.1 0.0 0.2 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Roofing material Grass, thatch, makuti 4.0 28.4 0.1 2.7 39.4 18.4 30.0 24.7 34.1 89.6 22.3 Tin cans 0.3 0.4 0.7 1.1 0.3 0.2 0.0 0.3 0.0 0.0 0.4 Corrugated iron (mabati) 73.3 67.1 56.2 92.0 52.3 78.1 68.2 64.7 65.2 9.8 68.6 Asbestos sheets 3.4 0.7 4.2 0.7 2.8 2.2 0.5 0.5 0.5 0.2 1.3 Concrete 12.6 0.6 26.2 1.0 4.0 0.3 0.3 2.0 0.0 0.2 3.6 Tiles 5.9 0.6 12.2 2.2 1.3 0.3 0.7 0.4 0.0 0.1 1.9 Other 0.5 2.1 0.2 0.0 0.0 0.2 0.2 7.3 0.0 0.0 1.7 Missing 0.2 0.2 0.1 0.3 0.1 0.5 0.0 0.1 0.2 0.0 0.2 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Persons per sleeping room 1-2 persons 64.1 60.8 65.7 80.4 60.0 67.3 63.4 46.0 62.7 16.1 61.6 3-4 persons 27.3 26.4 26.9 15.6 28.8 24.5 28.4 31.9 29.9 28.7 26.6 5-6 persons 6.9 8.6 6.2 3.3 8.1 5.5 6.3 14.9 5.9 27.9 8.2 7+ persons 1.7 4.2 1.1 0.8 3.1 2.6 2.0 7.1 1.6 27.3 3.6 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Mean number 2.4 2.7 2.3 1.9 2.6 2.4 2.5 3.2 2.5 5.0 2.6 Type of cooking fuel Electricity 1.0 0.1 1.8 0.2 0.4 0.4 0.1 0.1 0.0 0.0 0.3 LPG, natural gas 10.8 1.1 19.8 4.3 2.4 0.7 1.0 1.5 0.9 0.0 3.5 Biogas 0.3 0.0 0.6 0.0 0.3 0.0 0.0 0.1 0.1 0.0 0.1 Kerosene 50.8 2.8 68.3 14.5 22.5 6.8 4.2 8.8 3.3 0.4 14.8 Coal, lignite 0.2 0.0 0.3 0.0 0.1 0.0 0.0 0.0 0.0 0.0 0.0 Charcoal 25.9 10.2 7.4 14.8 19.1 8.2 15.6 19.7 11.7 9.1 14.2 Firewood, straw 9.4 85.2 0.1 65.1 53.9 83.5 79.0 68.9 83.5 90.2 66.2 Dung 1.6 0.4 1.7 0.8 1.2 0.4 0.1 0.9 0.4 0.2 0.7 Other 0.1 0.1 0.1 0.4 0.1 0.0 0.0 0.0 0.1 0.0 0.1 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Continued… Household Population and Housing Characteristics | 23 Table 2.6—Continued ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Residence Province ––––––––––––– ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Housing Rift North characteristic Urban Rural Nairobi Central Coast Eastern Nyanza Valley Western Eastern Total ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Source of drinking water Piped into dwelling 19.2 3.8 33.2 11.8 8.1 4.1 0.6 4.5 1.3 0.6 7.6 Piped into compound/plot 30.2 7.8 43.4 19.3 9.7 18.4 2.3 8.2 2.6 1.6 13.4 Public tap 21.8 6.8 15.0 3.5 40.1 9.1 11.7 7.8 3.9 0.1 10.6 Open well in compound/plot 1.8 1.7 0.2 2.2 1.3 0.6 0.7 3.3 2.3 3.8 1.7 Open public well 4.1 6.0 0.1 3.5 9.7 6.6 5.5 6.3 3.5 25.0 5.5 Covered well in compound/plot 3.3 5.9 0.3 8.3 0.9 1.6 1.2 13.0 4.1 1.4 5.3 Covered public well 2.6 7.5 0.1 4.5 1.8 8.1 9.4 4.8 13.5 6.1 6.3 Spring 1.7 16.9 0.0 6.2 0.9 11.5 33.4 3.2 40.3 0.0 13.1 River, stream 2.5 31.1 0.0 24.8 11.7 29.9 25.0 32.4 26.2 21.1 23.9 Pond, lake 0.0 2.2 0.0 0.1 1.7 0.3 7.6 1.2 0.2 0.4 1.6 Dam 0.7 4.1 0.1 1.7 9.6 4.6 0.3 3.3 0.0 34.1 3.3 Rainwater 0.7 2.5 0.1 7.5 0.4 0.9 1.7 1.3 0.9 1.7 2.1 Bottled water 0.7 0.0 1.3 0.0 0.2 0.0 0.1 0.0 0.2 0.0 0.2 Other 10.6 3.5 6.2 6.4 3.9 4.4 0.5 10.7 1.0 4.1 5.3 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Time to water source Percentage <15 minutes 83.8 43.1 95.9 70.9 63.6 38.7 31.6 50.5 44.6 22.1 53.2 Median time to source 0.0 14.9 0.0 0.7 5.0 24.7 19.7 10.0 14.4 u 9.7 Water availability Usually available 70.0 82.0 64.8 85.7 77.3 77.0 90.7 67.7 95.3 67.1 79.0 Several hours per day 10.1 1.6 14.0 1.2 6.7 4.6 3.4 1.2 0.8 2.5 3.7 Once or twice per week 10.0 3.1 12.8 2.7 4.0 8.6 1.9 4.9 0.9 2.8 4.9 Infrequent 9.1 13.1 7.0 10.2 11.7 9.6 3.8 26.2 2.5 27.2 12.1 Drinks bottled water 0.7 0.0 1.3 0.0 0.2 0.0 0.1 0.0 0.2 0.0 0.2 Missing 0.1 0.2 0.2 0.3 0.1 0.3 0.0 0.0 0.3 0.4 0.2 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Sanitation facility Flush toilet 39.0 1.7 66.5 9.5 12.3 4.9 2.1 3.4 1.9 0.3 11.0 Traditional pit toilet 44.2 70.3 26.5 84.3 39.2 74.2 66.1 58.8 87.3 14.3 63.8 Ventilated improved pit latrine 11.7 7.3 2.2 5.5 14.6 8.9 5.6 13.2 7.9 1.4 8.4 No facility, bush, field 3.7 20.4 2.7 0.2 33.5 11.8 26.2 24.1 2.8 80.9 16.2 Other 1.2 0.1 1.6 0.2 0.4 0.1 0.1 0.4 0.0 2.7 0.4 Missing 0.2 0.2 0.4 0.3 0.0 0.2 0.0 0.1 0.1 0.4 0.2 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Share toilet with other households No facilities 3.7 20.4 2.7 0.2 33.5 11.8 26.2 24.1 2.8 80.9 16.2 No 28.0 47.4 32.8 59.5 27.1 55.3 35.5 36.9 48.2 7.8 42.5 Yes 68.3 32.1 64.4 40.1 39.4 32.9 38.3 39.1 48.9 11.3 41.2 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Wealth quintile Lowest 1.3 21.2 0.0 0.9 22.7 12.3 23.7 22.1 20.3 71.6 16.3 Second 1.4 23.3 0.0 12.7 10.6 20.7 29.6 16.5 30.2 10.8 17.9 Middle 2.6 24.9 0.0 27.7 13.6 27.3 20.1 14.6 27.6 9.3 19.3 Fourth 12.2 22.8 2.9 36.0 15.7 27.2 12.9 22.7 14.2 4.6 20.2 Highest 82.5 7.7 97.1 22.7 37.4 12.4 13.6 24.1 7.7 3.7 26.4 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Continued… 24 | Household Population and Housing Characteristics There are marked provincial differentials in the source of drinking water. More than three- quarters of the households in Nairobi have piped water in their dwelling, compound, or plot compared with only 2 to 4 percent of households in Western, Nyanza, and North Eastern provinces. About 83 percent of the households in Kenya have access to some type of sanitary facility. Two- thirds of households in Kenya have traditional pit toilets, while only 11 percent have flush toilets. Sixteen percent of households have no toilet facilities. As expected, flush toilets are more widely used in urban areas and in Nairobi, although pit toilets are also very common. Traditional pit toilets are the predominant type of toilet in all the provinces, with the exception of Nairobi, where flush toilets are more common, and North Eastern Province, where toilet facilities are rare. The proportion of households with private toilets is almost identical to the proportion with shared toilets. Table 2.6—Continued ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Residence Province ––––––––––––– ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Housing Rift North characteristic Urban Rural Nairobi Central Coast Eastern Nyanza Valley Western Eastern Total ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Household owns structure Owns 19.3 87.6 10.4 73.3 63.8 85.3 84.6 66.4 89.6 87.3 70.5 Pays rent, lease 76.2 6.7 84.7 20.4 29.5 9.9 14.2 24.7 7.8 4.4 24.1 No rent, with consent of owner 4.3 4.9 4.6 5.7 5.9 4.8 1.2 7.1 2.2 6.3 4.7 No rent, squatting 0.1 0.7 0.1 0.3 0.8 0.1 0.0 1.7 0.1 1.9 0.6 Missing 0.1 0.1 0.2 0.3 0.1 0.0 0.0 0.1 0.1 0.0 0.1 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Household owns land on which structure sits Owns 15.6 80.5 8.3 58.1 54.5 78.6 83.9 60.0 89.3 75.8 64.3 Pays rent, lease 58.4 5.3 49.5 18.7 27.4 9.9 12.1 19.4 6.5 4.4 18.5 No rent with consent of owner 25.4 12.7 42.0 21.5 15.6 11.2 3.9 18.2 3.9 10.7 15.9 No rent, squatting 0.5 1.4 0.1 1.3 2.4 0.1 0.1 2.3 0.2 9.1 1.2 Missing 0.1 0.2 0.1 0.3 0.1 0.2 0.0 0.1 0.2 0.0 0.1 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 State of repair of dwelling Completely dilapidated, shack 2.1 2.1 3.2 0.2 9.1 1.2 1.4 2.0 0.5 4.6 2.1 Needs major repairs 17.3 22.4 17.8 13.9 17.6 19.7 25.5 28.2 13.6 48.1 21.2 Needs no or minor repairs 79.5 72.9 78.7 85.3 69.4 74.3 70.3 67.8 84.9 43.7 74.5 Being repaired 0.5 0.5 0.3 0.1 1.8 0.4 0.4 0.3 0.0 3.6 0.5 Under construction 0.4 2.0 0.1 0.2 1.8 3.8 2.5 1.6 0.7 0.0 1.6 Missing 0.3 0.2 0.1 0.3 0.4 0.6 0.0 0.0 0.2 0.0 0.2 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 How household disposes of kitchen waste and trash Regular collection by gov’t. 2.5 0.2 2.9 0.3 2.3 0.2 0.4 0.6 0.1 0.0 0.8 Infrequent collection by gov’t. 2.4 0.0 2.8 0.3 1.1 0.3 0.1 0.4 0.2 0.1 0.6 Pays for private collection 23.6 0.4 51.7 1.6 7.8 0.3 0.1 0.7 0.3 0.0 6.2 Composted 12.3 30.5 1.7 48.2 8.8 41.9 24.3 12.6 38.9 6.3 26.0 Dumps, buries, burns in compound 29.1 55.3 10.0 37.5 59.1 42.1 59.0 64.3 56.5 42.6 48.8 Dumps in street, empty plot 24.9 8.3 22.0 7.1 18.6 1.8 15.6 15.6 3.8 49.3 12.4 Other 4.9 5.0 8.4 4.7 2.2 12.7 0.4 5.5 0.0 0.2 5.0 Missing 0.4 0.3 0.5 0.5 0.1 0.6 0.0 0.3 0.2 1.5 0.3 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Number of households 2,138 6,423 837 1,351 684 1,316 1,282 1,937 967 187 8,561 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– u = Unknown (not available) Household Population and Housing Characteristics | 25 Interpretation of trends in housing and household characteristics over time is made slightly more difficult by the inclusion of areas in the northern part of Kenya in the 2003 KDHS. Excluding these areas shows that electricity coverage has increased from 15 percent of households in 1998 to 17 percent in 2003. The proportion of households with piped water has remained stable, as have the types of toilets that households have. There are also few notable differences in the types of flooring materials used in Kenya since the 1998 KDHS. Table 2.6 provides information about household ownership of the structure and the land. Overall, 71 percent of Kenyan households own their own home, while 24 percent pay rent. As expected, in urban areas, renting is more common, with 76 percent of households renting. A similar pattern holds for owner- ship of the land. The table also shows that most homes in Kenya need only minor repairs or no repairs at all. With regard to trash disposal, almost half of Kenyan households bury or burn their trash themselves, while about one-quarter compost their trash. Urban households are almost equally likely to bury or burn their trash themselves, dump their trash in the street or an empty plot, or pay for private collection. 2.5 HOUSEHOLD DURABLE GOODS Table 2.7 shows the percentage of households possessing various durable goods by urban-rural residence. This indicator provides a rough measure of the socioeconomic status of households. Of the ten selected durable household goods, radio, bicycle, and television stand out as the three most commonly owned by a household. Seventy-four percent of Kenyan households own a radio, 29 percent own a bicy- cle, and 19 percent own a television. There is noticeable urban-rural variation in the proportion of households owning durable goods. Eighty-one percent of households in urban areas have a radio, compared with 71 percent of rural house- holds. Similarly, 33 percent of urban households have a telephone, as opposed to 6 percent of rural households. Overall, 15 percent of urban households and 24 percent of rural households have none of the selected durable goods. There has been an increase in the percentage of households owning radios, bicycles, and televi- sions since the 1998 KDHS. Those owning radios went up from 63 percent in 1998 to 76 percent in 2003 (excluding the northern parts of Kenya), while those owning television sets increased from 13 percent in 1998 to 20 percent in 2003. The percentage of households owning bicycles went up from 24 to 30 percent between the 1993 KDHS and the 2003 KDHS. Table 2.7 Household durable goods Percentage of households possessing various durable consumer goods, by residence, Kenya 2003 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Residence ––––––––––––––––– Durable consumer goods Urban Rural Total –––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Radio 80.6 71.3 73.6 Television 40.6 12.4 19.4 Telephone/mobile 32.7 6.2 12.8 Refrigerator 13.4 1.2 4.3 Bicycle 17.7 33.1 29.3 Motorcycle 0.9 0.6 0.7 Car/truck 9.6 3.3 4.9 Solar power 1.1 4.0 3.3 None of the above 15.3 24.3 22.1 Number of households 2,138 6,423 8,561 Characteristics of Survey Respondents | 27 CHARACTERISTICS OF SURVEY RESPONDENTS 3 Godfrey Kyalo Ndeng’e 3.1 BACKGROUND CHARACTERISTICS OF RESPONDENTS Information on the basic characteristics of women and men interviewed in the survey is essential for the interpretation of findings presented later in the report. Background characteristics of the 8,195 women and 3,578 men interviewed in the Kenya Demographic and Health Survey (KDHS) are presented in Table 3.1. The distribution of respondents according to age shows a similar pattern for both genders. The proportion of respondents in each age group declines as age increases, reflecting the comparatively young age structure of the population. The distribution of sampled population by age and sex closely re- sembles that of the 1999 Population and Housing Census1 and indicates that there is no substantial selec- tion bias in the sample. In terms of rural and urban dichotomy, three-quarters of both males and females are rural respon- dents. The distribution of respondents by province shows that Rift Valley and Eastern provinces have the largest proportion of respondents, while North Eastern and Coast provinces have the least proportions. Sixty percent of female respondents are currently married or living with a man, compared with 51 percent of males. The never-married females account for slightly less than a third of all women, while 45 percent of males have never married. The proportion of female respondents who have never been to school is twice that of their male counterparts (13 versus 6 percent). Male respondents are much more likely to reach secondary school (37 percent) than females (29 percent), while only 10 percent of men and 6 percent of women manage to go beyond a secondary level of education. While the percentage of women with secondary education and above remained constant, that of men shows a downward trend since 1998. The tabulation of respondents by religion indicates that nine in ten women and men are Chris- tian (about 25 percent are Roman Catholic, and 60 to 65 percent are Protestant), while only 6 to 8 percent are Muslim. Males (7 percent) are more likely than females (2 percent) to have no religion. In terms of ethnic affiliation, Kikuyu respondents (both sexes) account for 23 percent of the total and are followed approximately in order of size by Luhya, Luo, Kamba, and Kalenjin. 3.2 EDUCATIONAL ATTAINMENT AND LITERACY Tables 3.2.1 and 3.2.2 present the distributions of female and male respondents, respectively, by the highest level of education attended according to age, urban-rural residence, province, and wealth in- dex. The large majority of respondents have not gone beyond the primary level of education. Generally, younger persons have reached higher levels of school than older people, as have urban residents. For 1 The distribution of the 2003 KDHS sample population of males and females by age matches that of the 1999 Popu- lation and Housing Census, where for males, 44 and 28 percent were age 15-24 and 25-34 years, respectively, while 29 percent were age 35-54. Similarly, for women, the pattern closely follows that of the census, where 47 percent of women were age 15-24, 29 percent were age 25-34, and 24 percent were age 35-49 years. 28 | Characteristics of Survey Respondents Table 3.1 Background characteristics of respondents Percent distribution of women and men by background characteristics, Kenya 2003 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Number of women Number of men ––––––––––––––––––––– ––––––––––––––––––––––– Background Weighted Un- Weighted Un- characteristic percent Weighted weighted percent Weighted weighted –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Age 15-19 22.6 1,856 1,820 23.9 856 829 20-24 20.6 1,691 1,710 19.0 681 674 25-29 16.9 1,382 1,400 14.2 509 514 30-34 13.3 1,086 1,116 11.6 415 421 35-39 10.6 871 859 11.1 396 390 40-44 9.6 788 780 8.7 310 314 45-49 6.4 521 510 5.5 196 206 50-54 na na na 6.0 215 230 Marital status Never married 29.8 2,443 2,466 45.0 1,611 1,584 Married 54.5 4,462 4,449 49.9 1,786 1,829 Living together 5.6 457 427 0.9 31 26 Divorced/separated 5.9 488 516 3.5 126 116 Widowed 4.2 346 337 0.7 23 23 Residence Urban 25.1 2,056 2,751 25.4 907 1,150 Rural 74.9 6,139 5,444 74.6 2,671 2,428 Province Nairobi 10.2 835 1,169 11.1 397 493 Central 14.4 1,181 1,314 15.5 554 621 Coast 8.1 667 938 7.0 252 375 Eastern 16.2 1,325 993 16.4 588 468 Nyanza 14.9 1,222 1,025 13.4 481 434 Rift Valley 22.8 1,872 1,328 23.6 846 586 Western 11.3 927 991 11.1 396 435 North Eastern 2.0 168 437 1.8 65 166 Education No education 12.7 1,039 1,291 6.4 228 296 Primary incomplete 32.8 2,685 2,409 33.8 1,210 1,110 Primary complete 25.2 2,069 1,939 22.9 820 813 Secondary incomplete 11.2 914 902 11.0 392 392 Secondary complete 12.3 1,009 1,073 15.7 562 581 More than secondary 5.9 480 581 10.2 366 386 Religion Roman Catholic 25.2 2,067 1,919 26.6 953 913 Protestant/other Christian 64.9 5,322 5,045 60.3 2,156 2,055 Muslim 7.6 619 1,025 6.4 231 381 No religion 1.9 156 167 6.5 232 219 Other 0.3 22 29 0.1 5 9 Missing 0.1 10 10 0.0 1 1 Ethnicity Embu 1.6 129 101 1.7 60 46 Kalenjin 10.1 831 643 11.8 423 324 Kamba 11.4 938 786 11.7 420 371 Kikuyu 23.0 1,886 1,977 22.6 808 845 Kisii 5.7 466 454 5.6 202 208 Luhya 15.0 1,230 1,229 14.7 527 520 Luo 12.0 984 853 11.9 427 390 Maasai 2.3 189 162 2.4 87 68 Meru 5.6 460 386 5.7 203 172 Mijikenda/Swahili 5.0 407 566 4.1 147 214 Somali 3.6 298 602 3.1 111 223 Taita/Taveta 1.2 101 135 1.0 36 51 Turkana 1.4 116 121 1.5 53 51 Kuria 0.6 49 47 0.7 26 27 Other 1.4 111 133 1.4 50 68 Wealth quintile Lowest 16.6 1,364 1,376 15.3 548 540 Second 18.0 1,475 1,306 17.0 609 556 Middle 18.3 1,503 1,381 18.1 648 615 Fourth 20.9 1,711 1,568 22.2 794 752 Highest 26.1 2,141 2,564 27.4 979 1,115 Total 100.0 8,195 8,195 100.0 3,578. 3,578 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Note: Education categories refer to the highest level of education attended, whether or not that level was completed. na = Not applicable Characteristics of Survey Respondents | 29 example, 48 percent of females in urban areas have attended at least some secondary school, compared with 23 percent of rural women. Among the provinces, Nairobi and Central have the largest proportion of women and men who have attended secondary school and above. The educational level of women in North Eastern Province is worrying, as 93 percent of women reported that they did not attend school at all, and less than 1 percent had any secondary education. As expected, the level of education increases with the wealth index. For example, among males in the lowest quintile, only 14 percent have at least some secondary education, compared with 63 percent of those in the highest quintile. Table 3.2.1 Educational attainment by background characteristics: women Percent distribution of women by highest level of schooling attended or completed, and median number of years of schooling,, according to background characteristics, Kenya 2003 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Educational attainment –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– More Number Median Background No Primary Primary Secondary Secondary than of years of characteristic education incomplete complete1 incomplete complete2 secondary Total women schooling ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Age 15-19 6.8 49.6 20.8 17.3 4.9 0.6 100.0 1,856 6.7 20-24 7.3 27.7 30.8 10.0 17.7 6.5 100.0 1,691 7.5 25-29 9.4 29.0 30.4 7.6 14.8 8.7 100.0 1,382 7.4 30-34 12.9 31.7 22.1 9.5 15.2 8.5 100.0 1,086 7.3 35-39 15.7 25.0 28.3 11.1 12.6 7.3 100.0 871 6.4 40-44 26.3 24.4 19.3 10.4 12.7 6.9 100.0 788 5.9 45-49 33.5 27.0 19.7 7.0 7.5 5.3 100.0 521 3.9 Residence Urban 7.8 16.9 27.2 13.1 21.0 14.1 100.0 2,056 7.9 Rural 14.3 38.1 24.6 10.5 9.4 3.1 100.0 6,139 6.5 Province Nairobi 5.6 12.5 25.6 11.7 26.1 18.6 100.0 835 9.4 Central 2.6 22.3 33.6 15.2 18.3 8.1 100.0 1,181 7.6 Coast 29.6 28.6 21.9 5.8 9.9 4.3 100.0 667 5.5 Eastern 8.4 37.8 31.6 7.8 10.4 3.9 100.0 1,325 6.9 Nyanza 7.1 44.9 21.7 15.6 7.2 3.4 100.0 1,222 6.6 Rift Valley 17.4 33.6 23.9 9.4 11.3 4.4 100.0 1,872 6.6 Western 9.0 47.6 19.3 13.8 7.7 2.7 100.0 927 6.4 North Eastern 93.4 4.0 1.8 0.1 0.3 0.4 100.0 168 0.0 Wealth quintile Lowest 34.5 44.0 15.1 3.9 2.4 0.1 100.0 1,364 3.9 Second 13.5 45.1 25.5 10.7 4.6 0.7 100.0 1,475 6.3 Middle 10.3 40.6 27.1 12.7 8.1 1.1 100.0 1,503 6.6 Fourth 6.3 27.8 29.8 13.6 17.4 5.0 100.0 1,711 7.4 Highest 5.0 15.5 26.6 13.1 22.8 17.1 100.0 2,141 8.7 Total 12.7 32.8 25.2 11.2 12.3 5.9 100.0 8,195 7.0 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– 1 Completed grade 8 at the primary level 2 Completed form 4 at the secondary level 30 | Characteristics of Survey Respondents Unlike previous KDHS surveys in which respondents were asked if they could read, the 2003 KDHS interviewers asked respondents to read a simple, short sentence to establish literacy. The sentences were written not only in English and Kiswahili but also in the same 11 local vernaculars in which the questionnaires were translated. Tables 3.3.1 and 3.3.2 show the percent distribution of female and male respondents, respectively, by level of literacy and percent literate according to background characteristics. The data show that illiteracy among females is almost twice (21 percent) that of males (12 per- cent). The difference is almost entirely due to the gender gap at older ages; for younger respondents, there is much less difference in illiteracy between the sexes. The urban-rural differential also displays the expected pattern, such that more rural respondents are illiterate than their urban counterparts. North Eastern Province has, by far, the highest illiteracy rates (94 percent among females and 71 percent among males), and illiteracy is lowest in Nairobi and Central provinces for both sexes. Table 3.2.2 Educational attainment by background characteristics: men Percent distribution of men by highest level of schooling attended or completed, and median number of years of schooling,, ac- cording to background characteristics, Kenya 2003 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Educational attainment –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– More Number Median Background No Primary Primary Secondary Secondary than of years of characteristic education incomplete complete1 incomplete complete2 secondary Total women schooling ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Age 15-19 3.9 58.7 14.7 17.4 4.7 0.7 100.0 856 6.4 20-24 3.0 28.2 25.4 8.8 24.2 10.3 100.0 681 7.8 25-29 6.1 30.9 25.5 7.7 16.2 13.6 100.0 509 7.5 30-34 3.8 26.8 24.6 9.0 22.5 13.2 100.0 415 7.9 35-39 7.6 16.5 27.0 12.7 19.9 16.4 100.0 396 8.0 40-44 10.8 22.7 27.1 7.9 17.5 14.0 100.0 310 6.8 45-49 13.5 25.1 24.5 8.3 14.3 14.3 100.0 196 6.5 50-54 17.0 28.6 23.7 7.3 9.2 14.1 100.0 215 6.2 Residence Urban 4.3 17.1 20.9 13.3 23.1 21.3 100.0 907 9.3 Rural 7.1 39.5 23.6 10.2 13.2 6.5 100.0 2,671 6.8 Province Nairobi 4.9 10.8 16.9 13.9 25.9 27.5 100.0 397 10.6 Central 1.5 24.2 33.2 10.8 18.4 11.9 100.0 554 7.6 Coast 10.0 28.5 30.4 9.3 16.8 4.9 100.0 252 7.2 Eastern 3.5 47.4 19.0 9.9 12.4 7.9 100.0 588 6.7 Nyanza 1.8 43.3 21.0 14.3 13.3 6.3 100.0 481 6.8 Rift Valley 10.2 34.6 22.9 7.9 15.3 9.0 100.0 846 7.0 Western 3.4 44.0 20.4 14.9 11.0 6.3 100.0 396 6.9 North Eastern 71.1 10.9 7.8 2.7 7.0 0.6 100.0 65 0.0 Wealth quintile Lowest 17.9 51.6 17.0 5.2 6.3 2.0 100.0 548 5.1 Second 6.2 46.8 24.6 9.4 9.6 3.4 100.0 609 6.4 Middle 4.5 40.8 27.1 12.2 12.8 2.6 100.0 648 6.9 Fourth 2.9 30.3 26.8 12.2 18.3 9.5 100.0 794 7.5 Highest 4.0 13.9 19.3 13.4 24.6 24.8 100.0 979 10.1 Total 6.4 33.8 22.9 11.0 15.7 10.2 100.0 3,578 7.2 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– 1 Completed grade 8 at the primary level 2 Completed form 4 at the secondary level Characteristics of Survey Respondents | 31 Illiteracy decreases as wealth increases. As expected, the poorest women have the highest rate of illiteracy (47 percent), while the richest women are least likely to be illiterate (9 percent). This pattern also holds for men. Table 3.3.1 Literacy: women Percent distribution of women by level of schooling attended and by level of literacy, and percent literate, according to background characteristics, Kenya 2003 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– No schooling or primary school –––––––––––––––––––––––––––––––––––––––– Secondary Can read Can read Cannot Number Background school or a whole part of a read of Percent characteristic higher sentence sentence at all Missing Total women literate1 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Age 15-19 22.8 56.7 6.1 14.0 0.4 100.0 1,856 85.5 20-24 34.2 46.0 5.6 13.9 0.2 100.0 1,691 85.9 25-29 31.1 45.8 7.3 15.6 0.2 100.0 1,382 84.2 30-34 33.3 38.5 7.5 20.4 0.3 100.0 1,086 79.3 35-39 31.0 32.2 9.3 27.1 0.4 100.0 871 72.5 40-44 30.0 22.3 8.9 38.7 0.1 100.0 788 61.2 45-49 19.8 21.6 7.8 50.8 0.0 100.0 521 49.2 Residence Urban 48.2 36.5 3.8 11.3 0.2 100.0 2,056 88.5 Rural 23.0 44.0 8.2 24.5 0.3 100.0 6,139 75.2 Province Nairobi 56.4 32.0 3.5 7.8 0.3 100.0 835 91.8 Central 41.6 42.0 7.5 8.8 0.0 100.0 1,181 91.1 Coast 19.9 40.4 5.2 34.3 0.1 100.0 667 65.6 Eastern 22.2 49.0 10.4 17.9 0.5 100.0 1,325 81.6 Nyanza 26.2 47.6 6.0 19.7 0.5 100.0 1,222 79.8 Rift Valley 25.0 40.0 8.2 26.5 0.2 100.0 1,872 73.2 Western 24.2 46.5 6.7 22.5 0.1 100.0 927 77.4 North Eastern 0.8 4.4 1.1 93.6 0.0 100.0 168 6.4 Wealth quintile Lowest 6.4 37.2 9.0 47.0 0.5 100.0 1,364 52.5 Second 15.9 48.0 9.8 26.2 0.1 100.0 1,475 73.7 Middle 21.9 48.2 8.6 20.9 0.3 100.0 1,503 78.7 Fourth 36.1 45.2 6.0 12.5 0.2 100.0 1,711 87.3 Highest 52.9 34.4 3.8 8.5 0.3 100.0 2,141 91.2 Total 29.3 42.1 7.1 21.2 0.3 100.0 8,195 78.5 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– 1 Refers to women who attended secondary school or higher and women who can read a whole sentence or part of a sentence 32 | Characteristics of Survey Respondents 3.3 ACCESS TO MASS MEDIA Information access is essential in increasing people’s knowledge and awareness of what is taking place around them, which may eventually affect their perceptions and behaviour. In the survey, exposure to media was assessed by asking respondents how often they read a newspaper, watched television, or listened to a radio. It is important to know the types of persons who are more or less likely to be reached by the media for purposes of planning programmes intended to spread information about health and fam- ily planning. Tables 3.4.1 and 3.4.2 show the percentage of male and female respondents, respectively, exposed to different types of mass communication media by age, place of residence, province, education and wealth index. Table 3.3.2 Literacy: men Percent distribution of men by level of schooling attended and by level of literacy, and percent literate, according to background characteristics, Kenya 2003 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– No schooling or primary school –––––––––––––––––––––––––––––––––––––––– Secondary Can read Can read Cannot Number Background school or a whole part of a read of Percent characteristic higher sentence sentence at all Missing Total men literate1 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Age 15-19 22.7 60.4 6.2 10.6 0.1 100.0 856 89.3 20-24 43.3 42.4 5.4 8.9 0.0 100.0 681 91.1 25-29 37.5 46.9 4.3 10.9 0.3 100.0 509 88.7 30-34 44.7 42.1 5.5 7.5 0.2 100.0 415 92.3 35-39 49.0 35.3 5.1 10.5 0.0 100.0 396 89.5 40-44 39.4 39.0 7.6 14.0 0.0 100.0 310 86.0 45-49 36.9 32.0 7.0 24.0 0.0 100.0 196 76.0 50-54 30.7 36.9 8.1 23.8 0.5 100.0 215 75.7 Residence Urban 57.7 33.3 2.7 6.3 0.0 100.0 907 93.7 Rural 29.9 49.4 6.9 13.6 0.1 100.0 2,671 86.2 Province Nairobi 67.4 25.0 1.9 5.8 0.0 100.0 397 94.2 Central 41.1 49.0 4.3 5.5 0.0 100.0 554 94.4 Coast 31.1 52.5 4.5 11.8 0.0 100.0 252 88.2 Eastern 30.2 53.6 7.9 8.3 0.0 100.0 588 91.7 Nyanza 34.0 51.2 4.3 10.4 0.2 100.0 481 89.4 Rift Valley 32.2 42.9 8.9 15.8 0.1 100.0 846 83.9 Western 32.2 46.9 5.7 15.0 0.2 100.0 396 84.8 North Eastern 10.3 16.7 2.6 70.5 0.0 100.0 65 29.5 Wealth quintile Lowest 13.5 51.3 9.4 25.7 0.0 100.0 548 74.3 Second 22.3 56.6 6.7 14.0 0.1 100.0 609 85.6 Middle 27.6 53.2 7.7 11.5 0.0 100.0 648 88.5 Fourth 39.9 46.4 5.5 7.8 0.2 100.0 794 91.9 Highest 62.8 28.9 2.4 5.9 0.0 100.0 979 94.1 Total 36.9 45.4 5.8 11.8 0.1 100.0 3,578 88.1 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– 1 Refers to men who attended secondary school or higher and men who can read a whole sentence or part of a sentence Characteristics of Survey Respondents | 33 Table 3.4.1 Exposure to mass media: women Percentage of women who usually read a newspaper at least once a week, watch television at least once a week, and listen to the radio at least once a week, by background characteristics, Kenya 2003 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Reads a Watches Listens to newspaper television the radio at least at least at least Number Background once once once All three No of characteristic a week a week a week media media women –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Age 15-19 23.4 28.2 74.0 11.3 22.6 1,856 20-24 27.4 32.8 79.5 16.7 17.2 1,691 25-29 24.7 29.6 77.6 14.2 19.2 1,382 30-34 22.7 28.5 74.2 14.7 23.4 1,086 35-39 18.7 26.3 74.8 12.0 22.8 871 40-44 16.4 24.4 69.4 10.1 27.0 788 45-49 13.1 27.3 68.7 9.6 28.1 521 Residence Urban 42.4 57.3 84.3 29.7 9.7 2,056 Rural 15.9 19.3 72.0 7.7 25.9 6,139 Province Nairobi 49.7 72.1 89.4 40.7 5.4 835 Central 25.7 35.5 84.5 15.5 11.5 1,181 Coast 21.0 26.2 64.7 11.1 30.4 667 Eastern 16.4 25.4 72.0 9.9 25.7 1,325 Nyanza 14.8 15.7 74.0 5.6 23.6 1,222 Rift Valley 23.6 26.7 71.3 12.7 25.6 1,872 Western 15.8 14.2 82.3 5.2 16.1 927 North Eastern 1.3 1.8 12.6 0.3 86.8 168 Education No education 0.4 8.2 39.0 0.2 59.8 1,039 Primary incomplete 7.5 16.0 71.0 2.7 26.7 2,685 Primary complete 21.0 27.8 82.2 9.7 14.4 2,069 Secondary+ 50.3 52.9 89.1 33.7 6.3 2,403 Wealth quintile Lowest 5.7 2.8 44.4 0.5 53.9 1,364 Second 8.2 6.4 71.5 1.6 27.1 1,475 Middle 12.1 14.2 77.3 3.9 20.7 1,503 Fourth 25.8 35.2 85.2 13.3 12.1 1,711 Highest 47.9 65.9 87.4 35.8 6.3 2,141 Total 22.5 28.8 75.1 13.2 21.8 8,195 34 | Characteristics of Survey Respondents In general, women are less likely than men to have access to mass media; this is true for all types of media (Figure 3.1). Twenty-three percent of women and 44 percent of men read newspapers at least once a week, 29 percent of women and 40 percent of men watch television at least once a week, and 75 percent of women and 90 percent of men listen to the radio once a week. Only 13 percent of women and 27 percent of men are exposed to all three of these media sources. Twenty-two percent of women and 8 percent of men have no access to mass media. Since 1998, the proportions of both women and men who reported reading newspapers weekly have declined, and the proportion watching television has increased slightly for women and declined for men. At least some of these apparent changes in media exposure could be due to a change in the way the questions were worded between the two surveys. Also, in 1988, the question on radio listenership referred to daily listening, further confounding trend analysis. Table 3.4.2 Exposure to mass media: men Percentage of men who usually read a newspaper at least once a week, watch television at least once a week, and listen to the radio at least once a week, by background characteristics, Kenya 2003 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Reads a Watches Listens to newspaper television the radio at least at least at least Number Background once once once All three No of characteristic a week a week a week media media men –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Age 15-19 32.4 34.6 86.5 17.6 10.9 856 20-24 49.8 44.8 93.6 31.6 4.7 681 25-29 49.3 44.3 91.0 31.3 7.8 509 30-34 51.1 43.9 93.6 30.8 4.4 415 35-39 52.0 43.2 91.7 33.5 6.2 396 40-44 43.0 34.8 89.0 25.1 9.6 310 45-49 41.3 33.1 85.0 23.9 13.0 196 50-54 42.4 35.4 87.0 27.4 12.7 215 Residence Urban 72.0 65.8 95.2 52.3 2.3 907 Rural 35.1 31.1 88.3 18.5 10.1 2,671 Province Nairobi 74.4 71.9 93.8 56.8 2.5 397 Central 55.9 51.9 96.8 35.9 1.8 554 Coast 45.9 39.0 93.3 29.8 5.4 252 Eastern 26.3 26.0 86.4 15.0 11.9 588 Nyanza 40.3 24.8 87.7 15.1 9.9 481 Rift Valley 44.9 41.4 87.1 27.9 11.4 846 Western 33.2 32.6 94.6 17.5 4.4 396 North Eastern 15.5 9.8 58.8 6.1 39.2 65 Education No education 1.4 13.8 62.1 0.3 37.5 228 Primary incomplete 20.9 26.7 85.0 10.0 12.8 1,210 Primary complete 40.4 33.0 95.0 20.3 4.1 820 Secondary+ 76.0 60.9 96.4 51.6 1.2 1,320 Wealth quintile Lowest 19.6 13.2 71.8 7.4 26.1 548 Second 27.7 19.2 89.3 9.6 8.1 609 Middle 32.8 30.2 92.2 16.3 7.3 648 Fourth 50.3 47.4 94.9 30.6 4.3 794 Highest 71.7 68.2 95.4 53.3 1.7 979 Total 44.4 39.9 90.1 27.1 8.1 3,578 Characteristics of Survey Respondents | 35 23 75 29 13 44 90 40 27 Reads newspapers weekly Listens to radio weekly Watches television weekly All three media 0 20 40 60 80 100 Percent Women Men Figure 3.1 Access to Mass Media KDHS 2003 Nairobi and Central provinces have the highest proportion of women and men who have access to all three media, while the least access to media is reported in North Eastern Province. The data also show that urban residents are more likely to have access to mass media than rural residents. Exposure to media is positively associated with educational attainment; the proportion with ac- cess to all three media outlets increases with increasing education level of respondents. Similarly, access to all three media outlets increases as wealth increases for both sexes. 3.4 EMPLOYMENT 3.4.1 Employment Status The KDHS asked respondents whether they were employed at the time of the survey and, if not, whether they were employed in the 12 months preceding the survey. Table 3.5 shows that 58 percent of women and 72 percent of men are currently employed. The proportion currently employed generally in- creases with age and number of living children. Women who are divorced, separated, or widowed are most likely to be employed (76 percent), followed by those who are married (65 percent). In contrast, married men are somewhat more likely to be employed than divorced, separated, or widowed men. There are notable regional variations in the proportion currently employed. Women in Nyanza (70 percent), Western (64 percent) and Central (63 percent) provinces are the most likely to be employed, while women in North Eastern Province are least likely to be employed. Among men, Central, Rift Val- ley, and Coast provinces have the highest employment levels. Only about 20 percent of women and 30 percent of men in North Eastern Province are currently employed. Current employment shows a mixed pattern by education, generally increasing with education among women, but not among men. The pro- portion currently employed generally increases as wealth status of the respondent increases, though the relationship is not strong. 36 | Characteristics of Survey Respondents Table 3.5 Employment status Percent distribution of women and men by employment status, according to background characteristics, Kenya 2003 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Women Men –––––––––––––––––––––––––––––––––––––––––––––––– ––––––––––––––––––––––––––––––––––––––––––––––– Employed Employed in the 12 months Not in the 12 months Not preceding the survey employed preceding the survey employed ––––––––––––––––– in the –––––––––––––––– in the Not 12 months Don’t Number Not 12 months Don’t Number Background Currently currently preceding know/ of Currently currently preceding know/ of characteristic employed employed the survey missing Total women employed employed the survey missing Total men ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Age 15-19 28.6 3.1 68.4 0.0 100.0 1,856 25.5 3.0 70.4 1.1 100.0 856 20-24 54.1 5.1 40.8 0.0 100.0 1,691 69.9 8.8 21.1 0.1 100.0 681 25-29 65.4 4.1 30.1 0.4 100.0 1,382 87.3 7.5 4.7 0.5 100.0 509 30-34 73.0 4.1 22.7 0.2 100.0 1,086 92.3 4.1 3.7 0.0 100.0 415 35-39 76.7 1.4 21.5 0.3 100.0 871 96.0 1.9 2.1 0.0 100.0 396 40-44 75.0 3.3 21.5 0.2 100.0 788 94.8 2.4 2.8 0.0 100.0 310 45-49 73.3 1.6 25.2 0.0 100.0 521 91.7 3.9 4.4 0.0 100.0 196 50-54 na na na na na na 92.2 2.5 5.4 0.0 100.0 215 Marital status Never married 39.4 3.1 57.4 0.2 100.0 2,443 45.9 6.1 47.2 0.8 100.0 1,611 Married or living together 64.9 3.7 31.3 0.2 100.0 4,919 93.7 3.1 3.1 0.0 100.0 1,818 Divorced/separated/ widowed 75.6 4.3 20.0 0.2 100.0 833 87.6 9.4 3.1 0.0 100.0 149 Number of living children 0 36.5 3.7 59.8 0.1 100.0 2,399 48.4 6.1 44.8 0.7 100.0 1,704 1-2 62.7 4.8 32.4 0.2 100.0 2,427 92.3 4.5 3.3 0.0 100.0 721 3-4 71.4 2.5 26.0 0.1 100.0 1,752 95.5 1.8 2.8 0.0 100.0 544 5+ 70.2 2.7 26.8 0.3 100.0 1,616 92.8 3.7 3.5 0.0 100.0 609 Residence Urban 58.0 5.9 35.8 0.3 100.0 2,056 74.7 6.5 18.0 0.8 100.0 907 Rural 58.5 2.8 38.7 0.1 100.0 6,139 71.0 4.1 24.7 0.2 100.0 2,671 Province Nairobi 56.6 5.1 38.1 0.1 100.0 835 68.6 9.1 21.9 0.4 100.0 397 Central 63.4 2.0 34.4 0.2 100.0 1,181 80.2 0.3 19.2 0.2 100.0 554 Coast 49.7 7.3 42.8 0.2 100.0 667 75.9 4.1 20.0 0.0 100.0 252 Eastern 48.3 3.0 48.6 0.1 100.0 1,325 71.0 4.5 24.3 0.2 100.0 588 Nyanza 69.6 3.6 26.7 0.1 100.0 1,222 68.1 4.0 27.2 0.7 100.0 481 Rift Valley 59.8 4.1 36.0 0.2 100.0 1,872 76.1 6.3 16.9 0.6 100.0 846 Western 63.5 1.2 35.3 0.0 100.0 927 65.0 4.8 30.1 0.0 100.0 396 North Eastern 19.5 2.7 77.4 0.4 100.0 168 29.8 4.2 66.0 0.0 100.0 65 Education No education 50.0 3.2 46.6 0.3 100.0 1,039 70.3 9.7 20.0 0.0 100.0 228 Primary incomplete 55.7 3.2 41.0 0.1 100.0 2,685 63.3 4.1 32.4 0.2 100.0 1,210 Primary complete 63.6 3.6 32.6 0.1 100.0 2,069 85.1 3.4 10.9 0.5 100.0 820 Secondary+ 60.4 4.1 35.4 0.2 100.0 2,403 71.9 5.2 22.4 0.4 100.0 1,320 Wealth quintile Lowest 55.6 2.0 42.2 0.1 100.0 1,364 62.0 6.9 30.7 0.4 100.0 548 Second 58.7 3.7 37.5 0.1 100.0 1,475 69.5 3.6 26.9 0.0 100.0 609 Middle 60.0 2.6 37.3 0.1 100.0 1,503 68.7 4.1 27.0 0.2 100.0 648 Fourth 56.4 3.4 40.0 0.2 100.0 1,711 76.5 3.1 20.0 0.4 100.0 794 Highest 60.3 5.2 34.3 0.2 100.0 2,141 77.5 6.0 16.0 0.5 100.0 979 Total 58.4 3.6 37.9 0.2 100.0 8,195 71.9 4.7 23.0 0.3 100.0 3,578 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– na = Not applicable Characteristics of Survey Respondents | 37 3.4.2 Occupation The distributions of women and men employed in the 12 months preceding the survey, by occu- pation and other background characteristics, are shown in Tables 3.6.1 and 3.6.2, respectively. Forty-nine percent of working women and 42 percent of working men are engaged in agricultural occupations. Among women, the next most common occupation is in the sales and services sector (26 percent), while for men, it is unskilled manual occupations (22 percent). For men, the sales and service sector is the third major occupation category, engaging 17 percent of working men. Nine percent of employed Kenyan women do domestic work, while only 7 percent work in professional, technical, or managerial fields. The proportion of women employed in agricultural activities has remained the same since 1998. Table 3.6.1 Occupation: women Percent distribution of women employed in the 12 months preceding the survey by occupation, according to background charac- teristics, Kenya 2003 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Professional/ Sales Un- Number Background technical/ and Skilled skilled Domestic Agri- of characteristic managerial Clerical services manual manual service culture Missing Total women –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Age 15-19 1.9 0.1 20.1 0.0 6.5 24.6 46.6 0.1 100.0 587 20-24 4.1 1.6 25.9 0.0 11.2 12.7 44.3 0.2 100.0 1,001 25-29 7.4 2.8 26.0 0.1 8.9 8.2 46.4 0.2 100.0 960 30-34 7.4 2.5 31.0 0.2 5.8 4.7 48.2 0.0 100.0 838 35-39 7.7 2.6 28.7 0.1 6.7 3.8 49.9 0.5 100.0 681 40-44 9.6 3.2 26.3 0.1 4.9 1.9 54.1 0.0 100.0 617 45-49 8.3 2.7 24.0 0.5 4.4 1.5 58.6 0.0 100.0 390 Marital status Never married 7.3 3.2 22.1 0.0 12.3 26.2 28.4 0.4 100.0 1,036 Married or living together 7.2 2.0 25.8 0.1 5.8 3.2 55.8 0.1 100.0 3,371 Divorced/separated/ widowed 1.5 1.8 35.8 0.1 8.3 8.4 44.0 0.0 100.0 665 Number of living children 0 7.9 3.2 21.4 0.1 11.6 24.2 31.3 0.3 100.0 964 1-2 6.8 2.6 29.9 0.2 9.3 8.9 42.2 0.1 100.0 1,638 3-4 7.1 2.1 26.6 0.0 5.0 3.1 55.9 0.1 100.0 1,293 5+ 4.2 1.0 25.3 0.2 4.2 1.1 63.9 0.2 100.0 1,179 Residence Urban 11.4 5.6 41.0 0.4 11.4 19.4 10.7 0.1 100.0 1,314 Rural 4.8 1.0 21.3 0.0 6.1 4.7 61.9 0.2 100.0 3,759 Province Nairobi 15.5 7.2 37.2 0.7 13.0 23.9 2.2 0.2 100.0 515 Central 7.5 2.5 19.3 0.0 7.4 7.3 56.1 0.0 100.0 772 Coast 4.9 1.7 39.8 0.2 14.5 8.1 30.6 0.2 100.0 380 Eastern 7.1 1.4 26.0 0.2 10.3 12.4 42.5 0.0 100.0 679 Nyanza 3.4 1.3 26.6 0.0 5.1 3.6 59.9 0.0 100.0 895 Rift Valley 5.3 1.9 23.5 0.0 5.2 6.9 56.8 0.5 100.0 1,195 Western 4.9 1.0 21.1 0.0 3.5 3.7 65.8 0.0 100.0 600 North Eastern 0.0 1.9 64.1 0.0 2.7 1.6 27.8 1.9 100.0 37 Education No education 0.3 0.0 30.3 0.0 3.6 3.2 62.4 0.1 100.0 552 Primary incomplete 0.4 0.0 21.7 0.0 3.7 8.5 65.7 0.0 100.0 1,580 Primary complete 1.0 0.2 27.7 0.1 11.5 12.2 47.1 0.1 100.0 1,391 Secondary+ 19.9 7.0 28.5 0.3 9.0 7.2 27.8 0.4 100.0 1,549 Wealth quintile Lowest 0.8 0.0 20.6 0.0 4.3 1.7 72.3 0.4 100.0 786 Second 2.1 0.0 19.6 0.0 6.7 2.7 68.9 0.0 100.0 920 Middle 3.5 0.4 20.7 0.0 7.4 3.3 64.7 0.0 100.0 942 Fourth 7.2 1.6 27.1 0.2 5.9 6.6 51.2 0.3 100.0 1,023 Highest 14.1 6.5 37.3 0.3 10.9 21.1 9.5 0.2 100.0 1,402 Total 6.5 2.2 26.4 0.1 7.5 8.5 48.7 0.2 100.0 5,073 38 | Characteristics of Survey Respondents Table 3.6.2 Occupation: men Percent distribution of men employed in the 12 months preceding the survey by occupation, according to background characteris- tics, Kenya 2003 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Professional/ Sales Un- Number Background technical/ and Skilled skilled Domestic Agri- of characteristic managerial Clerical services manual manual service culture Missing Total men –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Age 15-19 0.6 1.1 9.3 4.9 17.1 7.5 58.6 0.7 100.0 244 20-24 4.7 1.7 21.9 4.1 23.9 5.0 37.2 1.6 100.0 537 25-29 8.0 1.1 22.6 5.6 21.1 3.1 38.4 0.0 100.0 482 30-34 10.6 0.9 17.3 4.9 21.8 3.2 40.9 0.4 100.0 400 35-39 10.8 0.9 16.5 6.3 27.2 0.9 37.4 0.0 100.0 388 40-44 18.4 2.4 13.8 5.3 21.5 0.8 37.8 0.1 100.0 301 45-49 13.6 0.8 13.1 1.4 16.1 1.7 53.3 0.0 100.0 188 50-54 16.9 1.6 14.1 3.4 14.9 1.4 47.3 0.3 100.0 204 Marital status Never married 5.3 1.4 16.5 4.0 19.7 6.7 45.2 1.2 100.0 837 Married or living together 12.0 1.4 18.0 5.0 21.7 1.4 40.4 0.1 100.0 1,761 Divorced/separated/ widowed 6.6 0.0 15.8 6.3 29.1 3.0 39.2 0.0 100.0 145 Number of living children 0 5.7 1.5 17.6 4.3 19.5 6.0 44.3 1.0 100.0 928 1-2 9.9 1.0 21.8 6.4 23.2 1.9 35.5 0.4 100.0 698 3-4 14.6 1.2 17.0 4.5 25.3 1.1 36.2 0.1 100.0 529 5+ 11.2 1.6 12.1 3.8 19.2 1.7 50.4 0.1 100.0 588 Residence Urban 14.1 2.9 30.3 10.5 33.7 1.9 6.3 0.2 100.0 736 Rural 8.0 0.7 12.7 2.6 17.0 3.6 54.8 0.6 100.0 2,006 Province Nairobi 18.1 4.2 30.3 12.9 31.2 1.6 1.4 0.3 100.0 308 Central 6.7 1.6 15.2 4.5 19.7 1.8 50.4 0.2 100.0 446 Coast 8.3 1.1 31.0 6.3 28.3 2.5 21.7 0.8 100.0 201 Eastern 9.2 0.7 14.1 2.1 20.0 9.4 44.3 0.3 100.0 444 Nyanza 10.0 1.1 12.4 5.4 22.6 0.8 47.4 0.3 100.0 347 Rift Valley 8.7 0.5 15.5 2.4 19.0 2.3 51.0 0.6 100.0 698 Western 8.1 1.0 12.6 4.5 17.0 2.5 53.1 1.2 100.0 277 North Eastern 16.6 2.9 23.8 0.0 11.4 0.0 45.3 0.0 100.0 22 Education No education 0.9 0.0 18.0 0.9 11.6 1.9 66.7 0.0 100.0 183 Primary incomplete 0.7 0.1 13.7 2.9 23.5 5.5 53.0 0.6 100.0 816 Primary complete 2.2 0.2 17.0 5.2 25.6 3.2 46.3 0.3 100.0 726 Secondary+ 23.8 3.3 20.6 6.5 18.8 1.3 25.1 0.6 100.0 1,018 Wealth quintile Lowest 0.8 1.4 9.9 2.6 15.2 0.7 69.0 0.5 100.0 378 Second 5.5 0.0 10.5 1.9 19.7 1.3 60.9 0.1 100.0 445 Middle 5.2 0.6 12.0 3.4 18.7 3.7 55.9 0.5 100.0 472 Fourth 10.5 1.0 13.5 3.0 21.9 4.9 44.4 0.7 100.0 632 Highest 18.0 2.6 30.7 9.4 26.8 3.4 8.6 0.5 100.0 817 Total 9.7 1.3 17.4 4.7 21.5 3.1 41.8 0.5 100.0 2,743 Characteristics of Survey Respondents | 39 Table 3.7.1 Type of employment: women Percent distribution of women employed in the 12 months preceding the survey by type of earnings, type of employer, and continuity of employment, according to type of employment (agricultural or nonagricultural), Kenya 2003 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Employment Agricultural Nonagricultural characteristic work work Total –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Type of earnings Cash only 25.2 84.1 55.4 Cash and in-kind 30.3 8.9 19.3 In-kind only 13.4 0.7 6.8 Not paid 31.1 6.3 18.3 Total 100.0 100.0 100.0 Type of employer Employed by family member 15.8 5.7 10.6 Employed by nonfamily member 11.8 41.6 27.1 Self-employed 72.4 52.5 62.2 Total 100.0 100.0 100.0 Continuity of employment All year 54.6 74.1 64.5 Seasonal 39.3 17.7 28.2 Occasional 6.0 8.2 7.1 Total 100.0 100.0 100.0 Number of women 2,468 2,596 5,073 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Note: Total includes 8 women with missing information on type of employ- ment, who are not shown separately. Table 3.7.2 Type of employment: men Percent distribution of men employed in the 12 months preceding the survey by type of earnings, according to type of employment (agricultural or nonagri- cultural, Kenya 2003 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Agricultural Nonagricultural Type of earnings work work Total –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Cash only 49.2 93.4 74.6 Cash and in-kind 23.6 3.9 12.1 In-kind only 5.8 0.3 2.6 Not paid 21.4 2.4 10.3 Missing 0.0 0.1 0.4 Total 100.0 100.0 100.0 Number of men 1,146 1,583 2,743 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Note: Total includes 13 men with missing information on type of employ- ment, who are not shown separately. Differences by background characteristics show that, as expected, rural women and men are more likely to be employed in agricultural jobs than urban residents. Among women, domestic service is par- ticularly high among never-married and younger respondents, as well as those who live in urban areas, in Nairobi, and in wealthier households. The latter finding could be due to the fact that the wealth index is derived from household-based information; to the extent that female domestic workers live in the house- holds in which they work, they take on the characteristics of that household. 3.4.3 Type of Employer, Form of Earnings, and Continuity of Employment Tables 3.7.1 and 3.7.2 present the percent distribution of employed women and men, respectively, by type of earnings and employment character- istics, according to type of employment (agricultural or nonagricultural). Sev- enty-five percent of women receive cash for their work, while almost one in five is unpaid. Women are more likely to be paid in kind or not paid at all if they are employed in agricultural activities. Men are more likely than women to be paid in cash for their work (87 percent); men engaged in nonagricultural work are almost all (93 percent) paid cash only. Three in five working women are self-employed, with only 27 per- cent employed by a nonfamily mem- ber. Women are more likely to be self- employed if they are doing agricultural work than if they are engaged in non- agricultural work. Women are more prone to seasonal and occasional work if they are employed in agricultural activities (45 percent) than if they are in nonagricultural occupations (26 percent) and, conversely, conti- nuity of employment is more assured for women who are engaged in nonagricultural work. 40 | Characteristics of Survey Respondents 3.4.4 Control Over Earnings and Women’s Contribution to Household Expenditures Women who were working and receiving cash earnings were asked to state who decides how their earnings are used. In addition, they were asked what proportion of household expenditures is met by their earnings. Table 3.8 shows that two in three working women decide by themselves how their earnings are used, while 23 percent make the decision jointly with someone else. Only about one in ten women Table 3.8 Decision on use of earnings and contribution of earnings to household expenditures Percent distribution of women employed in the 12 months preceding the survey receiving cash earnings by person who decides how earnings are to be used and by proportion of household expenditures met by earnings, according to background characteristics, Kenya 2003 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Person who decides Proportion of household how earnings are used expenditures met by earnings ––––––––––––––––––––––––––––––– ––––––––––––––––––––––––––––––––––––––––– Someone Almost Less Number Background Self else none/ than Over of characteristic only Jointly1 only2 Missing Total none half half All Missing Total women –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Age 15-19 62.4 12.7 24.8 0.0 100.0 33.6 20.6 35.4 10.4 0.0 100.0 363 20-24 71.4 15.7 13.0 0.0 100.0 15.2 31.5 41.1 12.2 0.0 100.0 755 25-29 63.8 26.5 9.7 0.0 100.0 8.0 25.3 50.6 16.1 0.0 100.0 705 30-34 59.6 31.7 8.8 0.0 100.0 4.0 25.3 50.6 20.1 0.0 100.0 654 35-39 66.8 25.6 7.5 0.2 100.0 4.1 24.6 51.6 19.5 0.2 100.0 521 40-44 70.5 22.1 7.1 0.3 100.0 3.5 24.4 47.9 23.9 0.3 100.0 494 45-49 70.6 20.4 9.0 0.0 100.0 1.3 25.8 47.1 25.8 0.0 100.0 298 Marital status Never married 85.5 2.9 11.6 0.0 100.0 29.5 23.7 33.9 12.9 0.0 100.0 786 Married or living together 53.3 33.7 12.9 0.1 100.0 3.8 28.2 51.7 16.2 0.1 100.0 2,458 Divorced/separated/ widowed 96.8 2.0 1.1 0.1 100.0 6.4 18.9 43.2 31.3 0.1 100.0 546 Number of living children 0 75.9 9.6 14.5 0.0 100.0 29.3 24.8 34.4 11.5 0.0 100.0 705 1-2 65.9 24.1 10.0 0.0 100.0 7.3 26.9 50.2 15.6 0.0 100.0 1,255 3-4 60.6 29.6 9.7 0.1 100.0 3.1 24.2 52.0 20.7 0.1 100.0 984 5+ 65.3 23.8 10.8 0.2 100.0 3.9 27.4 45.9 22.7 0.2 100.0 846 Residence Urban 75.4 17.1 7.5 0.1 100.0 13.2 22.2 46.9 17.7 0.1 100.0 1,182 Rural 62.1 25.3 12.5 0.1 100.0 7.9 27.6 46.7 17.7 0.1 100.0 2,608 Province Nairobi 80.6 14.0 5.3 0.0 100.0 16.0 20.7 43.1 20.2 0.0 100.0 482 Central 63.3 29.3 7.3 0.1 100.0 12.0 22.6 47.2 18.1 0.1 100.0 565 Coast 69.3 19.9 10.8 0.0 100.0 7.1 23.4 54.7 14.8 0.0 100.0 281 Eastern 67.2 22.3 10.4 0.0 100.0 13.3 30.2 46.1 10.4 0.0 100.0 601 Nyanza 63.5 23.0 13.6 0.0 100.0 3.4 31.6 51.1 14.0 0.0 100.0 639 Rift Valley 59.4 27.3 13.2 0.1 100.0 9.2 22.2 44.6 23.9 0.1 100.0 847 Western 68.7 16.6 14.4 0.2 100.0 5.1 29.8 43.6 21.2 0.2 100.0 349 North Eastern 67.3 11.3 21.5 0.0 100.0 0.0 53.1 40.0 6.9 0.0 100.0 26 Education No education 76.0 12.4 11.2 0.5 100.0 6.9 24.1 43.5 25.0 0.5 100.0 337 Primary incomplete 65.2 20.1 14.7 0.0 100.0 8.5 27.9 44.0 19.5 0.0 100.0 1,092 Primary complete 65.3 21.9 12.7 0.0 100.0 12.1 26.4 44.5 17.0 0.0 100.0 1,061 Secondary+ 65.4 28.3 6.3 0.0 100.0 9.0 24.3 51.7 14.9 0.0 100.0 1,300 Wealth quintile Lowest 62.6 22.0 15.4 0.0 100.0 5.1 33.1 43.9 18.0 0.0 100.0 486 Second 63.1 22.8 13.8 0.3 100.0 5.4 29.9 45.0 19.4 0.3 100.0 613 Middle 63.9 25.1 11.0 0.0 100.0 5.0 26.4 49.5 19.1 0.0 100.0 636 Fourth 60.2 25.9 13.8 0.0 100.0 10.2 26.3 48.2 15.3 0.0 100.0 774 Highest 74.0 19.9 6.1 0.0 100.0 15.1 20.9 46.4 17.5 0.0 100.0 1,281 Total 66.3 22.8 10.9 0.1 100.0 9.5 25.9 46.8 17.7 0.1 100.0 3,791 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– 1 With husband or someone else 2 Includes husband Characteristics of Survey Respondents | 41 report that the decision on how to use their earnings is made by some else only. The proportion of women who say that they decide by themselves how their earnings are used increased from 55 percent in 1998 to 66 percent in 2003.2 Table 3.8 also shows how the respondent’s degree of control over her earnings varies by back- ground characteristics. Irrespective of age, most respondents make their own decisions on how their cash earnings are used. Unmarried women tend to make their own decisions about the use of their earnings, while married women, compared with unmarried women, are more likely to involve another person in making the decision. Urban women are more independent in making their own decisions than rural women (75 and 62 percent, respectively). In rural areas, 25 and 13 percent of the decisions on the use of women’s earnings are made either jointly or by someone else, respectively. There are regional variations in the way decisions are made on how women’s earnings are used. The percentage of women who make decisions on their earnings by themselves ranges from 81 percent in Nairobi Province to 59 percent in Rift Valley Province. There are no clear patterns by education and pov- erty status. Regarding the proportion of household expenditures met by their earnings, 18 percent of working women reported that their earnings supported all household expenditures, while 47 percent reported that their earnings constitute over half of household expenditures. Older women; women who are widowed, divorced, or separated; and less educated women are more likely to support their households financially. Table 3.9 shows information on how decisions on use of women’s earnings are related to the pro- portional contribution of these earnings to the household expenditures, according to marital status. The analysis indicates that independence in decisionmaking is slightly inversely related to the proportion of women’s contribution to the household expenses. For instance, 75 percent of women whose contribution to household expenditures is minimal decide for themselves how their earnings are used. On the other hand, only 57 percent of women who support all of their household’s expenses decide by themselves how their earnings are used, while 30 percent share the decision with their husband and 14 percent say that their husband alone makes decisions. Almost all unmarried women (between 87 and 96 percent) make their own decisions regarding their earnings, regardless of their contribution to the household expendi- tures. 2 The figure is 66 percent for the entire sample, as well as for the sample excluding the northern districts. Table 3.9 Women’s control over earnings Percent distribution of women who received cash earnings for work in the past 12 months by person who decides how earnings are used, according to marital status, and the proportion of household expenditures met by earnings, Kenya 2003 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Currently married or living together Not married1 ––––––––––––––––––––––––––––––––––––––––––– –––––––––––––––––––––––––––– Jointly Jointly Some- Jointly Some- Contribution with with Hus- one Number with one Number to household Self hus- someone band else of Self someone else of expenditures only band else only only Total women only else only Total women –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Almost none/none 75.3 19.9 0.0 4.8 0.0 100.0 94 89.0 3.2 7.9 100.0 267 Less than half 59.1 29.5 0.5 10.5 0.4 100.0 693 87.4 3.3 9.2 100.0 290 Over half 47.5 37.8 0.3 14.0 0.4 100.0 1,270 89.3 1.9 8.8 100.0 502 All 56.8 29.7 0.0 13.5 0.0 100.0 399 96.1 2.1 1.8 100.0 273 Total 53.3 33.4 0.3 12.6 0.3 100.0 2,458 90.2 2.5 7.3 100.0 1,332 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– 1 Never-married, divorced, separated, or widowed women 42 | Characteristics of Survey Respondents 3.5 WOMEN’S EMPOWERMENT In addition to information on women’s education, employment status, and control over earnings, the 2003 KDHS collected information from both women and men on other measures of women’s auton- omy and status. In particular, questions were asked about women’s roles in making household decisions, on acceptance of wife beating, and on their opinions about when a wife should be able to deny sex to her husband. Such information provides insight into women’s control over their environment and their atti- tudes towards gender roles, both of which are relevant to understanding women’s demographic and health behaviour. 3.5.1 Women’s Participation in Decisionmaking To assess women’s decisionmaking autonomy, the 2003 KDHS sought information on women’s participation in five different types of household decisions: on the respondents’ own health care; on mak- ing large household purchases; on making household purchase for daily needs; on visits to family or rela- tives; and on what food should be cooked each day. Table 3.10 shows the percent distribution of women according to who in the household usually has the final say on each aspect. The autonomy of women in this case would be gauged by either their independently making such decisions or jointly deciding on such issues. Among currently married women, independence in making decisions ranges from 81 percent on what food to cook daily to only 12 percent on making large household purchases. Although 40 percent of married women make decisions on their own health care by themselves, 43 percent of women say that their husbands make such decisions alone. Husbands are more likely to decide on making large purchases (61 percent) and visits to family or relatives (39 percent). Among unmarried women, decisions on their own health care are made by the respondents (42 percent) or someone else (55 percent). The other decisions are made mostly by either the respondents themselves or by someone else, possibly because the majority are younger women who still live with their guardians or parents. Table 3.11 shows that although one in four women have a say in all five areas of decisionmaking, another one in four have no say at all in any of the specified areas. Generally, women’s participation in making all of the specified decisions increases with age, from 3 percent among women age 15-19 to 50 Table 3.10 Women’s participation in decisionmaking Percent distribution of women by person who has the final say in making specific decisions, according to current marital status and type of deci- sion, Kenya 2003 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Currently married or living together Not married1 ––––––––––––––––––––––––––––––––––––––––––––––––– –––––––––––––––––––––––––––––––––– Decision Decision not not Jointly made/ Jointly made/ Jointly with Some- not with Some- not with some- Hus- one appli- Number some- one appli- Number Self hus- one band else cable/ of Self one else cable/ of Decision only band else only only missing Total women only else only missing Total women ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Own health care 39.8 14.3 0.3 42.9 2.3 0.4 100.0 4,919 41.6 2.9 54.7 0.8 100.0 3,276 Large household purchases 11.8 24.2 0.2 61.3 2.3 0.2 100.0 4,919 24.4 2.5 70.4 2.7 100.0 3,276 Daily household purchases 40.5 19.2 0.5 37.3 2.2 0.3 100.0 4,919 25.6 3.5 68.3 2.4 100.0 3,276 Visits to family or relatives 22.9 35.1 0.4 39.4 1.7 0.5 100.0 4,919 32.7 6.1 59.2 1.9 100.0 3,276 What food to cook each day 81.2 5.0 1.1 10.0 2.4 0.1 100.0 4,919 28.0 5.2 64.9 1.9 100.0 3,276 ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– 1 Never-married, divorced, separated, or widowed women Characteristics of Survey Respondents | 43 percent among those age 45-49. Women who have never married, have no children, have incomplete pri- mary education, and who are not employed are the least likely to participate in decisionmaking in the household. About four in ten women (38 percent) who are employed for cash participate in making all decisions, compared with 20 percent who are employed but do not earn cash and 12 percent of unem- ployed women. This implies that cash employment increases women’s decisionmaking power. Table 3.11 Women’s participation in decisionmaking by background characteristics Percentage of women who say that they alone or jointly have the final say in specific decisions, by background charac- teristics, Kenya 2003 –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Alone or jointly has final say in: ––––––––––––––––––––––––––––––––––––––––––––––– What None Own Making Making Visits to food All of the Number Background health large daily family or to cook specified specified of characteristic care purchases purchases relatives each day decisions decisions women –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Age 15-19 20.8 5.5 8.5 15.7 17.3 3.2 65.7 1,856 20-24 47.2 20.1 36.1 44.3 59.3 14.6 24.1 1,691 25-29 56.2 35.8 55.5 56.0 78.9 25.1 11.2 1,382 30-34 64.0 44.8 65.9 65.9 87.7 34.6 5.9 1,086 35-39 64.6 51.2 73.2 69.5 92.5 39.8 4.2 871 40-44 69.7 59.2 78.8 74.6 92.8 47.2 4.8 788 45-49 70.2 62.6 77.6 80.7 92.4 49.9 3.9 521 Marital status Never married 32.0 11.5 13.5 24.5 18.0 9.6 59.1 2,443 Married or living together 54.4 36.2 60.2 58.4 87.4 24.5 8.1 4,919 Divorced/separated/ widowed 81.0 72.2 75.1 80.7 77.8 68.2 11.9 833 Number of living children 0 28.9 10.9 15.0 24.4 22.6 8.4 57.4 2,399 1-2 57.2 34.3 52.6 56.7 74.6 25.7 14.5 2,427 3-4 60.0 43.8 66.2 63.9 88.9 32.9 6.5 1,752 5+ 61.8 49.6 69.1 65.8 91.3 37.3 5.8 1,616 Residence Urban 61.4 40.4 53.1 59.9 69.5 32.6 17.3 2,056 Rural 46.8 29.8 46.0 47.5 64.5 21.8 25.8 6,139 Province Nairobi 62.6 40.6 55.0 63.6 68.9 33.7 16.2 835 Central 63.8 36.5 51.1 63.6 67.2 30.0 20.5 1,181 Coast 42.6 35.1 41.7 48.8 61.5 27.3 28.8 667 Eastern 60.6 35.5 46.2 50.9 63.5 26.8 21.6 1,325 Nyanza 31.3 27.9 51.6 42.0 61.2 18.4 30.2 1,222 Rift Valley 57.6 32.0 48.5 52.9 72.0 24.1 18.3 1,872 Western 29.0 21.0 38.4 31.2 59.6 13.3 35.8 927 North Eastern 24.0 32.3 40.5 42.4 71.3 20.2 24.1 168 Education No education 48.1 40.3 52.9 52.6 79.8 30.3 15.4 1,039 Primary incomplete 42.4 27.3 42.1 42.8 59.5 19.6 31.1 2,685 Primary complete 52.5 31.2 47.9 52.6 67.4 22.2 19.4 2,069 Secondary+ 58.7 36.1 51.7 56.7 65.1 29.4 22.6 2,403 Employment Not employed 36.0 17.7 26.4 33.8 48.1 12.3 41.2 3,397 Employed for cash 65.6 48.2 67.9 66.7 80.4 37.6 8.7 3,561 Employed not for cash 46.7 28.2 49

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