Kenya - Demographic and Health Survey - 1994

Publication date: 1994

Demographic and Health Survey 1993 ~ ~. Republic of Kenya National Council for Population and Development Central Bureau of Statistics Office of the Vice President and Ministry of Planning at~d National Development ~DHS Demographic and Health Surveys Macro International Inc. i Kenya Demographic and Health Survey 1993 National Council for Population and Development Central Bureau of Statistics Office of the Vice President and Ministry of Planning and National Development Nairobi, Kenya Macro International Inc. Calverton, Maryland USA May 1994 This report summarises the findings of the 1993 Kenya Demographic and Health Survey (KDHS) conducted by the National Council for Population and Development and the Central B areau of Statistics. Macro International Inc. provided technical assistance. Funding was provided by the U.S. Agency for International Development (USAID) and the Government of Kenya. The KDHS is part of the worldwide Demographic and Health Surveys (DHS) program, which is designed to collect data on fertility, family planning, and maternal and child health. Additional information about the Kenya survey may be obtained from the National Council for Population and Development, P.O. Box 30478, Nairobi. Kenya (Telephone: 228-411; Fax: 213-642). Additional information about the DHS program may be obtained by writing to: DHS, Macro International Inc., 11785 Beltsville Drive, Calve~on, MD 20705 (Telephone: 301-572-0200; Fax: 301-572- 0999). Recommended citation: National Council for Population and Development (NCPD), Central Bureau of Statistics (CBS) (Office of the Vice President and Ministry of Planning and National Development [Kenya]), and Macro International Inc. (MI). 1994. Kenya Demographic and Health Survey 1993. Calverton, Maryland: NCPD, CBS, and MI. CONTENTS Page List of tables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . vi i List of f igures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xiii Foreword . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xv Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xvii Executive summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xix Map of Kenya . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xxiv CHAPTER 1 1.1 1.2 1.4 1.5 1.6 INTRODUCTION Geography, History, and Economy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 Population . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Health Priorities and Programmes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Objectives of the 1993 Kenya Demographic and Health Survey . . . . . . . . . . . . . . 4 Survey Organisation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 CHAPTER 2 2.1 2.2 2.3 CHARACTERIST ICS OF HOUSEHOLDS AND RESPONDENTS Characteristics of the Household Population . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 Housing Characteristics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 Background Characteristics of Women Respondents . . . . . . . . . . . . . . . . . . . . . 16 CHAPTER 3 3.1 3.2 3.3 3.4 3.5 3.6 3.7 3.8 FERT IL ITY Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21 Fertility Levels . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21 Fertility Differentials . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23 Fertility Trends . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24 Children Ever Bom . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27 Birth Intervals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28 Age at First Birth . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30 Teenage Fertility . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31 CHAPTER 4 4.1 4.2 4.3 4.4 4.5 4.6 4.7 FERT IL ITY REGULAT ION Knowledge of Contraception . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35 Ever Use of Contraception . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38 Current Use of Contraception . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39 Number of Children at First Use . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46 Knowledge of Fertile Period . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46 T iming of Sterilisation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47 Source of Supply . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48 i i i 4.8 4.9 4.10 4.11 4.12 4.13 Page Future Use . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50 Nonuse of Family Planning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52 Exposure to Media Programmes on Family Planning . . . . . . . . . . . . . . . . . . . . 53 Attitudes towards Family Planning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54 Source of Family Planning Information . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57 Community-Based Distribution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58 CHAPTER 5 5.1 5.2 5.3 5.5 5.6 5.7 5.8 OTHER PROXIMATE DETERMINANTS OF FERTILITY Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61 Marital Status . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61 Polygyny . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62 Age ~t First Sexual Intercourse . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66 Recent Sexual Activity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67 Postpartum Amenorrhoea and Insusceptibility . . . . . . . . . . . . . . . . . . . . . . . . . 69 Termination of Exposure to Pregnancy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71 CHAPTER 6 6.1 6.2 6.3 FERT IHTY PREFERENCES Desire for More Children . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73 Demand for Family Planning Services . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77 Ideal Family Size . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78 CHAPTER 7 7.1 7.2 7.3 7A 7.5 INFANT AND CHILD MORTAL ITY Assessment of Data Quality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83 Levels and Trends in Infant and Child Mortality . . . . . . . . . . . . . . . . . . . . . . . 84 Socioeconomic Differentials in Infant and Child Mortality . . . . . . . . . . . . . . . . 85 Demographic Differentials in Infant and Child Mortality . . . . . . . . . . . . . . . . . . 87 High-Risk Fertility Behaviour . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89 CHAPTER 8 8.1 8.2 8.3 8.4 MATERNAL AND CHILD HEALTH Antenatal Cam . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93 Delivery Care . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 97 Childhood Vaccination . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 101 Childhood Illness and Treatment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 106 CHAPTER 9 9.1 9.2 9.3 INFANT FEEDING AND CHILDHOOD AND MATERNAL NUTRITION Breastfeeding and Supplementation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 115 Nutritional Status of Children . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 120 Nutritional Status of Mothers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 124 iv CHAPTER 10 10.1 10.2 10.3 10.4 10.5 10.6 Page KNOWLEDGE OF AIDS AIDS Awareness and Knowledge . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 127 Sources of Information . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 129 Misconceptions About AIDS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 130 AIDS Prevention . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 131 Personal Acquaintance With AIDS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 132 Number of Sexual Partners and Condom Use . . . . . . . . . . . . . . . . . . . . . . . . . 133 CHAPTER 11 11.1 11.2 11.3 11.4 11.5 RESULTS OF THE MALE SURVEY Background Characteristics of the Male Survey Respondents . . . . . . . . . . . . . . 139 Fertility Regulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 142 Nuptiality and Sexual Intercourse . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 154 Fertility Preferences . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 157 Couples . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 159 CHAPTER 12 12.1 12.2 12.3 LOCAL AVAILABIL ITY OF FAMILY PLANNING AND HEALTH SERVICES Service Availability Questionnaire . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 165 Availability of Family Planning Services . . . . . . . . . . . . . . . . . . . . . . . . . . . . 166 Availability of Maternal and Child Health (MCH) Services . . . . . . . . . . . . . . . 170 REFERENCES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 175 APPENDIX A A.I A.2 A.3 APPENDIX B APPENDIX C APPENDIX D APPENDIX E SURVEY DES IGN . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 177 Questionnaires . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 179 Sample Design and Implementation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 180 Training and Fieldwork . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 183 EST IMATES OF SAMPL ING ERRORS . . . . . . . . . . . . . . . . . . . . . . . . . . 185 DATA QUAL ITY TABLES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 207 PERSONS INVOLVED IN THE 1993 KENYA DHS . . . . . . . . . . . . . . . . . 215 QUEST IONNAIRES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 219 LIST OF TABLES Table 1.2 Table 2.1 Table 2.2 Table 2.3 Table 2.4.1 Table 2.4.2 Table 2.5 Table 2.6 Table 2.7 Table 2.8 Table 2.9 Table 2.10 Table 3.1 Table 3.2 Table 3.3 Table 3.4 Table 3.5 Table 3.6 Table 3.7 Table 3.8 Table 3.10 Table 3.11 Table 3.12 Table 3.13 Table 3.14 Table 4.1 Table 42 Table 4.3 Table 4A Table 4.5 Page Results of the household and individual interviews . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Household population by age, residence and sex . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 Population by age from selected sources . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 Household composition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 Educational level of the male household population . . . . . . . . . . . . . . . . . . . . . . . . . 11 Educational level of the female household population . . . . . . . . . . . . . . . . . . . . . . . . 12 School enrolment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 Housing characteristics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 Household durable goods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16 Background characteristics of respondents . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17 Level of education . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18 Access to mass media . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 Current fertility . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22 Fertility by background characteristics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23 Trends in current fertility rates . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25 Trends in fertility by province . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25 Percent pregnant . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26 Age-specif ic fertility rates . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26 Fertility by marital duration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27 Children ever born and living . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28 Birth intervals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29 Age ~t fi~st birth . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30 Median age at first birth . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31 Teenage pregnancy and motherhood . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32 Children bom to teenagers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33 Knowledge of contraceptive methods and source for methods . . . . . . . . . . . . . . . . . . 36 Trends in knowledge of family planning methods and sources . . . . . . . . . . . . . . . . . 37 Knowledge of modem contraceptive methods and source for methods . . . . . . . . . . . 38 Ever use of contraception . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39 Trends in ever use of family planning methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40 vii Table 4,6 Table 4,7 Table 4.8 Table 4.9 Table 4.10 Table 4,11 Table 4.12 Table 4.13 Table 4.14 Table 4.15 Table 4.16 Table 4.17 Table 4,18 Table 4.19 Table 4.20 Table 4,21 Table 4.22 Table 4,23 Table 4.24 Table 5, I Table 5.2 Table 5.3 Table 5.4 Table 5.5 Table 5.6 Table 5.7 Table 5.8 Table 5.9 Table 5.10 Table 5.11 Table 5.12 Table 6.1 Page Current use of contraception . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40 Trends in current use of family planning methods . . . . . . . . . . . . . . . . . . . . . . . . . . . 41 Current use of family planning by method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43 Current use of contraception by district . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45 Number of children at first use of contraception . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46 Knowledge of fertile period . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47 T iming of sterilisation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48 Source of supply for modem contraceptive methods . . . . . . . . . . . . . . . . . . . . . . . . . 49 T ime to source of supply for modem contraceptive methods . . . . . . . . . . . . . . . . . . . 50 Future use of contraception . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51 Reasons for not using contraception . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52 Preferred method of contraception for future use . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53 Heard family planning on radio . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54 Attitudes about family planning for youth . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55 Discussion of family planning by couples . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56 Attitudes of couples toward family planning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56 First source of family planning information . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57 Main source of family planning information . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58 Community-based distribution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59 Current marital ~tatus . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61 Trends in proportion never married . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62 Polygyny . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63 Number of co-wives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64 Age at first marriage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65 Median age at first marriage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65 Age at first sexual intercourse . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66 Median age at first sexual intercourse . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67 Recent sexual activity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68 Postpartum amenorrhoea, abstinence and insusceptibility . . . . . . . . . . . . . . . . . . . . . 69 Median duration of postpartum insusceptibility by background characteristics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 70 Termination of exposure to the risk of pregnancy . . . . . . . . . . . . . . . . . . . . . . . . . . . 71 Fertility preference by number of l iving children . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73 viii Table 6.2 Table 6.3 Table 6.4 Table 6.5 Table 6.6 Table 6.7 Table 6.8 Table 7.1 Table 7.2 Table 7.3 Table 7.4 Table 8.1 Table 8.2 Table 8.3 Table 8.4 Table 8.5 Table 8.6 Table 8.7 Table 8.8 Table 8.9 Table 8.10 Table 8.11 Table 8.12 Table 8.13 Table 8.14 Table 8.15 Table 9.1 Table 9.2 Table 9.3 Table 9.4 Table 9.5 Table 9.6 Table 9.7 Page Fertility preferences by age . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75 Desire to limit (stop) childbearing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76 Need for family planning services . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78 Ideal number of children . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79 Mean ideal number of children by background characteristics . . . . . . . . . . . . . . . . . . 80 Fertility planning status . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81 Wanted fertility rates . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82 Infant and child mortality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84 Infant and child mortality by background characteristics . . . . . . . . . . . . . . . . . . . . . . 86 Infant and child mortality by demographic characteristics . . . . . . . . . . . . . . . . . . . . . 88 High-risk fertility behaviour . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 90 Antenatal care . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 94 Number of antenatal care visits and stage of pregnancy . . . . . . . . . . . . . . . . . . . . . . . 95 Tetanus toxoid vaccination . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 96 Place of delivery . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 98 Assistance during delivery . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100 Characteristics of delivery . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 101 Vaccinations by source of information . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 103 Vaccinations by background characteristics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 104 Vaccinations in the first year of life . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 106 Prevalence and treatment of acute respiratory infection . . . . . . . . . . . . . . . . . . . . . . 108 Prevalence and treatment of fever . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 109 Prevalence of diarrhoea . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 110 Knowledge and use of ORS packets . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 111 Treatment of diarrhoea . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 113 Feeding practices during diarrhoea . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 114 Initial breastfeeding . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 116 Breastfceding status . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 117 Breastfeeding and supplementation by age . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 118 Median duration and frequency of breastfeeding . . . . . . . . . . . . . . . . . . . . . . . . . . . 119 Nutritional status by demographic and background characteristics . . . . . . . . . . . . . 122 Anthropometric indicators of maternal nutritional status . . . . . . . . . . . . . . . . . . . . . 124 Differentials in matcmal anthropometric indicators . . . . . . . . . . . . . . . . . . . . . . . . . 125 ix Table 10.1 Table 10.2 Table 10.3 Table 10.4 Table 10.5 Table 10.6 Table 10.7.1 Table 10.7.2 Table 10.8.1 Table 10.8.2 Table 10.9 Table 11.1 Table 11.2 Table 11.3 Table 11.4 Table 11.5 Table 11.6 Table 11.7 Table 11.8 Table 11.9 Table 11.10 Table 11.11 Table 11.12 Table 11.13 Table 11.14 Table 11.15 Table 11.16 Table 11.17 Table 11.18 Table 11.19 Table 11.20 Table 11.21 Table 11.22 Page Knowledge of AIDS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 128 Sources of AIDS information . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 129 AIDS transmission . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 130 Protection against AIDS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 131 Personal knowledge of AIDS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 132 Personal risk of acquiring AIDS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 133 Number of recent sexual partners - male respondents . . . . . . . . . . . . . . . . . . . . . . . 134 Number of recent sexual partners - female respondents . . . . . . . . . . . . . . . . . . . . . . 135 Number of l ifetime sexual partners - male respondents . . . . . . . . . . . . . . . . . . . . . . 136 Number of l ifetime sexual partners - female respondents . . . . . . . . . . . . . . . . . . . . . 137 Condom use . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 138 Background characteristics of respondents . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 139 Level of education . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 141 Access to mass media . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 142 Knowledge of contraceptive methods and source for methods . . . . . . . . . . . . . . . . . 143 Knowledge of modem contraceptive methods and source for methods . . . . . . . . . . 145 Ever use of contraception . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 146 Current use of contraception . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 147 Current use of family planning by background characteristics . . . . . . . . . . . . . . . . . 148 Source of supply for modem contraceptive methods . . . . . . . . . . . . . . . . . . . . . . . . 149 Future use of contraception . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 150 Reasons for not using contraception . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 151 Preferred method of contraception for future use . . . . . . . . . . . . . . . . . . . . . . . . . . . 151 Heard family planning on radio . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 152 Discussion of family planning with wife . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 152 Attitudes of couples towards family planning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 153 Current marital status by age . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 154 Polygyny . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 155 Age at first marriage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 155 Age at first sexual intercourse . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 156 Fertility preference by number of l iving children . . . . . . . . . . . . . . . . . . . . . . . . . . . 157 Fertility preferences by age . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 158 Ideal number of children . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 158 X Table 11.23 Table 11.24 Table 11.25 Table 11.26 Table 11.27 Table 11.28 Table 11.29 Table 12.1 Table 12.2 Table 12.3 Table 12.4 Table 12.5 Table 12.6 Table 12.7 Table A. 1.1 Table A. 1.1 Table B. 1 Table B.2 Table B.3 Table B.4 Table B.5 Table B.6 Table B.7 Table B.8 Table B.9 Table B.10 Table B.11 Table B. 12 Page Background characteristics of husbands . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 159 Age difference between spouses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 160 Knowledge of methods among married couples . . . . . . . . . . . . . . . . . . . . . . . . . . . . 161 Attitudes of couples towards family planning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 161 Spouse's perception of other spouse's approval of family planning . . . . . . . . . . . . 162 Desire for more children among couples by number of living children . . . . . . . . . . 163 Spouse's agreement on ideal number of children . . . . . . . . . . . . . . . . . . . . . . . . . . . 164 Distance and time to nearest facility providing family planning services according to type of facility and residence . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 167 Distance to nearest family planning method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 168 Distance to nearest facility providing family planning services for users/nonusers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 169 Distance and time to nearest facility providing antenatal care according to type of facility and province . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 170 Distance and time to nearest facility providing delivery care according to type of facility and province . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 171 Distance and time to nearest facility providing child immunisation services according to type of facility and province . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 172 Distance to nearest maternal and child health services for children . . . . . . . . . . . . . 173 Sample implementation: Women . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 181 Sample implementation: Men . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 182 List of selected variables for sampling errors, Kenya 1993 . . . . . . . . . . . . . . . . . . . 189 Sampling errors - National sample, Kenya 1993 . . . . . . . . . . . . . . . . . . . . . . . . . . . 190 Sampling errors - Urban sample, Kenya 1993 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 191 Sampling errors - Rural sample, Kenya 1993 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 192 Sampling errors - Nairobi, Kenya 1993 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 193 Sampling errors - Central Province, Kenya 1993 . . . . . . . . . . . . . . . . . . . . . . . . . . . 194 Sampling errors - Coast Province, Kenya 1993 . . . . . . . . . . . . . . . . . . . . . . . . . . . . 195 Sampling errors - Eastem Province, Kenya 1993 . . . . . . . . . . . . . . . . . . . . . . . . . . . 196 Sampling errors - Nyanza Province, Kenya 1993 . . . . . . . . . . . . . . . . . . . . . . . . . . . 197 Sampling errors - Rift Valley Province, Kenya 1993 . . . . . . . . . . . . . . . . . . . . . . . . 198 Sampling errors - Western Province, Kenya 1993 . . . . . . . . . . . . . . . . . . . . . . . . . . 199 Sampling errors - Mombasa City, Murangja rural and Nyeri rural, Kenya 1993 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 200 xi Table B. 13 Table B. 14 Table B.15 Table B.16 Table B.17 Table C.1 Table C.2 Table C.3 Table C.4 Table C.5 Table C.6 Page Sampling errors - Kilifi rural, Taita Taveta rural and Machakos rural, Kenya 1993 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 201 Sampling errors - Meru rural, Kisi i /Nyamira rural and Siaya rural, Kenya 1993 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 202 Sampling errors - South Nyanza rural, Kericho rural and Nakuru rural, Kenya 1993 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 203 Sampling errors - Nandi rural, Uasin Gishu rural and Bungoma rural, Kenya 1993 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 204 Sampling errors - Kakamegea rural, Kenya 1993 . . . . . . . . . . . . . . . . . . . . . . . . . . . 205 Household age distribution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 209 Age distribution of eligible and interviewed women . . . . . . . . . . . . . . . . . . . . . . . . 210 Completeness of reporting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 211 Births by calendar year since birth . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 212 Reporting of age at death in days . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 213 Reporting of age at death in months . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 214 xii LIST OF FIGURES Figure 2.1 Figure2.2 Figure2.3 Figure 3.1 Figure 3.2 Figure 3.3 Figure 4.1 Figure 4.2 Figure 4.3 Figure 4.4 Figure 6.1 Figure 6.2 Figure 6.3 Figure7.1 Figure7.2 Figure 7.3 Figure8.1 Figure8.2 Figure 8.3 Figure 8.4 Figure 9.1 Figure 11.1 Figure 11.2 Figure 11.3 Page Population pyramid, Kenya 1993 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 Distribution of de facto household population by single year of age and sex . . . . . . . . . . . 9 Percentage of males and females who have completed primary education by age group . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 Age-specific fertility rates by urban-rural residence . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22 Total fertility rate by selected background characteristics . . . . . . . . . . . . . . . . . . . . . . . . 24 Age-specific fertility rates, 1977/78 KFS, 1989 KDHS and 1993 KDHS . . . . . . . . . . . . . 25 Trends in contraceptive use, currently married women 15-49, KDHS 1989 and KDHS 1993 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42 Current use of contraception by selected background characteristics . . . . . . . . . . . . . . . . 44 Current use of modem contraceptive methods by district, KDHS 1989 and KDHS 1993 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45 Percent distribution of current users of modern methods by most recent source of supply . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49 Fertility preferences of currently married women 15-49 . . . . . . . . . . . . . . . . . . . . . . . . . . 74 Fertility preferences of married women by number of living children . . . . . . . . . . . . . . . 75 Percentage of currently married women who want no more children by background characteristics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77 Trends in infant and child mortaltiy, Kenya, 1978-1993 . . . . . . . . . . . . . . . . . . . . . . . . . . 85 Under-five mortality by selected background characteristics . . . . . . . . . . . . . . . . . . . . . . 87 Under-five mortaltiy by selected demographic characteristics . . . . . . . . . . . . . . . . . . . . . 89 Percent distribution of births by number of antenatal care visits and timing of first visit . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95 Percent distribution of births in the five years preceding the survey by place of delivery . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 99 Vaccination coverage among children age 12-23 months . . . . . . . . . . . . . . . . . . . . . . . . 103 Percentage of children under 5 who received various treatments for diarrhoea in the two weeks preceding the survey . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 114 Nutritional status of children under five years, mean Z-scores by age in months . . . . . . 123 Level of education attained by men age 20-54 and women age 15-49 . . . . . . . . . . . . . . 140 Knowledge of contraceptive methods among currently married men 20-54 and women 15-49 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 144 Current use of contraceptive methods among currently married men 20-54 and women 15-49 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 147 xiii FOREWORD The 1993 Kenya Demographic and Health Survey (KDHS) is the second survey of its kind to be carried out in the country; the first one was conducted in 1989. Information on fertility, infant and child mortality, knowledge and practice of family planning, maternal and child health and AIDS awareness was collected. The survey therefore provides a complete set of relevant data for evaluation of population, health and family planning programmes, and necessary information for assessing the overall demographic situation in the country since 1989 and for development of future strategies. We hope that policymakers, health project implementers, social scientists and researchers will make optimal use of the survey data. The 1993 KDHS reinforces evidence of a major decline in fertility which was first revealed by the findings of the 1989 KDHS. Fertility continues to decline and family planning use has increased. However, the disparity between knowledge and use of family planning remains quite wide. There are indications that infant and under five child mortality rates are increasing, which in part might be attributed to the increase in AIDS prevalence. These are some of the critical issues that need to be addressed without delay. Finally, I would like to acknowledge assistance by both the Washington, D.C. and Kenya offices of the United States Agency for International Development (USAID) for financial support, Macro International Inc. of Calverton, Maryland, USA for technical support, and the Central Bureau of Statistics and the National Council for Population and Development for making the 1993 KDHS a success. S.B.A. Bullut, Director, National Council for Population and Development XV ACKNOWLEDGMENTS This report was written by: Anne Cross, Peter Thumbi, Timothy Takona, P.N. Kagwe, Jane Kariuki, John Kekovole, K. Kioga, P. M. L. Kizito, Jenipher Liku, M. K. Mbayah, Muchira Muraguri, Vane Nyonga, Helen Odido, John Owuor, and Tulshi Saha. The authors would like to acknowledge the contribution of Han Raggers for producing the tabulations and to thank the following reviewers: George Bicego, Kate Colson, Cara Egan, John Kekovole, Estelle Mallinoff, Mickey Marckwardt, Beatrice Michoma, Sidney Moore, Han Raggers, and Tulshi Saha. xvii EXECUTIVE SUMMARY The 1993 Kenya Demographic and Health Survey (KDHS) was a nationally representative survey of 7,540 women age 15-49 and 2,336 men age 20-54. The KDHS was designed to provide information on levels and trends of fertility, infant and child mortality, family planning knowledge and use, maternal and child health, and knowledge of AIDS. In addition, the male survey obtained data on men's knowledge and attitudes towards family planning and awareness of AIDS. The data are intended for use by programme managers and policymakers to evaluate and improve family planning and matemal and child health programmes. Fieldwork for the KDHS took place from mid-February until mid-August 1993. All areas of Kenya were covered by the survey, except for seven northem districts which together contain less than four percent of the country's population. The KDHS was conducted by the National Council for Population and Development (NCPD) and the Central Bureau of Statistics of the Government of Kenya. Macro International Inc. provided financial and technical assistance to the project through the intemational Demographic and Health Surveys (DHS) contract with the U.S. Agency for International Development. Fertility. Survey results show that fertility has declined precipitously in Kenya over the last 5-10 years. At current fertility levels, a Kenyan woman will give birth to an average of 5.4 children during her reproductive years. Although this is stin high, it is far lower than the level of 6.7 births per women reported for the late 1980s. A rural woman can expect to have an average of 5.8 children, over two children more than an urban women (3.4 children). Fertility rates are much higher in Western Province (6.4 children per wom an) than in Nairobi and Central Province (3.4 and 3.9, respectively). Childbearing begins earlyin Kenya. Oneinf iveteenagewomen(age 15-19) hasbegunchildbearing (either given birth or is pregnant with her first child). By the time they reach age 19, over 40 percent of women have begun childbearing. Births that occur too soon after a previous birth face higher risks of illness and early death. The KDHS shows that one-quarter of births in Kenya take place less than two years after a prior birth. Marr iage. There has been a steady increase over the past two decades in the age at which Kenyan women first marry. The median age at marriage among women age 25-29 is 19.5, compared to 18.1 among women age 45-49. Women with secondary education generally marry three years later (21.5) than women with no education (17.0). Women in Coast and Nyanza Provinces have the lowest median age at first marriage (17.4). Twenty percent of currently married women are in polygynous unions. Polygyny occurs in all provinces and age groups. It is most common among uneducated women (33 percent). The median age at first sexual intercourse is about 17 years for women. Fertility Preferences. Over half of married women in Kenya either do not want to have any more children or have been sterilised. Another one quarter of women want to wait two years or longer before having their next child. Thus, 78 percent of all married women in Kenya either want to space or to limit their births. xix When asked how many children they would like to have if they could live their lives over and choose exactly, women report an average ideal family size of 3,7 children. There has been a large decline in ideal family size over the past decade, from a mean of 5.8 children reported in a 1984 survey to 4.4 reported in the 1989 KDHS, to 3.7 in 1993. Results from the survey indicate that if unwanted births were eliminated, the fertility rate in Kenya would be 3.4 births per woman or 2 children fewer than the actual fertility rate of 5.4. Men want slightly more children than women. Regardless of the number of children they already have, a higher percentage of men than women say they want to have another child. The average ideal number of children among is 3.8 among men and 3.7 for women. Family Planning. Knowledge of some family planning method is virtually universal among both men and women. Among currently married respondents, 97 percent of women and men know at least one modem contraceptive method. The pill, injection, female sterilisation and condom are the most widely known methods. Moreover, almost all women and men who know a method, also know of a place to obtain it. One third of married women are currently using a contraceptive method. The level of use has almost doubled in the past decade, from 17 percent of married women in 1984 to 33 percent in 1993. Use of modern methods has increased even faster--from 10 to 27 percent of married women. Over 80 percent of women users employ modem methods, principally the pill (10 percent o f married women), injection (7 percent) and female sterilisation (6 percent). Use of the pill and injection has risen particularly rapidly over the last five years. Among both men and women, contraceptive use is higher in urban than in rural areas. The differential in use by education level is particularly striking: 20 percent of married women with no education are using family planning, compared to 52 percent of those with some secondary education. Contraceptive use also varies greatly by province. Women in Central Province have the highest prevalence rate (56 percent), compared to Coast Province with the lowest (20 percent). The government is the most important provider of family planning services, supplying over two- thirds of the women who use modem methods. Over one third of currently married women in Kenya have an unmet need for family planning. This group comprises women who are not using any family planning methods but either want to wait two years or more before their next birth (22 percent) or do not want any more children (15 percent). Combined with the 33 percent of married women who are currently using a contraceptive method, the total potential demand for family planning comprises almost 70 percent of married women in Kenya. Child Mortal ity. KDHS findings indicate that one in ten Kenyan children dies before reaching his/her fifth birthday. For the most recent five-year period (1988-93), under-five mortality was 96 per 1,000 live births and infant mortality 62 per 1,000 live births. There has apparently been no change in childhood mortality over the past decade, according to the birth histories recorded from women interviewed in the survey. Further evidence that the previous rapid decline in childhood mortality has stagnated comes from a comparison of the childhood mortality data from the 1989 and 1993 KDHSs, which also show no real change. XX Differences in mortality by province are quite marked. Childhood mortality is exceptionally high in Nyanza Province, where almost one in five children do not live to see their fifth birthdays. The infant mortality rate in Nyanza Province (128) is almost twice that of the second highest rate (Coast Province--68). KDHS data indicate that spacing births can potentially reduce childhood mortality levels; a child born less than 24 months after a preceding child is almost twice as likely to die before his first birthday than a child born after an interval of four or more years. Risks are also greater for children whose birth order is greater than seven and those born to mothers under age 20. Maternal Health. Utilisation of antenatal services is high. In the five years prior to the survey, mothers received antenatal care for 95 percent of births. The median number of antenatal care visits is 4.7. Mothers reported receiving at least one tetanus toxoid injection for about 90 percent of births in the five years preceding the survey. Over half (55 percent) of births take place at home. Forty-five percent of deliveries are assisted by medically trained personnel, while almost one quarter are assisted by relatives; ten percent of women deliver without assistance. Child Health. The KDHS found that 79 percent of children aged 12-23 months were fully vacci- nated and only 3 percent had not received any vaccinations at all. Seventy-one percent of children had received all the recommended vaccinations during the first year of life. Children of lower birth orders (1-3) are more likely to be fully vaccinated than children of higher birth orders. Coverage levels are higher for children in Central Province and Nairobi and lower for children in Nyanza and Westem Provinces. During the two weeks before the survey, 18 percent of children under age five experienced symptoms of acute respiratory infection (ARl)--cough with short, rapid breathing. Half of these children were taken to a health facility or doctor for treatment. Four in ten children under five (42 percent) were reported to have had fever in the two weeks preceding the survey; half of these children were taken to a health facility for treatment. Many of the children with fever who were taken to a health facility received antimalarial medicine. Fourteen percent of children under five had diarrhoea during the two weeks preceding the survey. About 40 percent of these children were taken to a health facility for treatment. Among children with diarrhoea, one-third were given a solution prepared from ORS packets and almost half received increased fluids to drink. Nutrition. Almost all children born in the five years before the survey (97 percent) were breastfed for someperiod of time. Themediandurationofbreastfeedingis21 months. InKenya, the introduction of supplementary liquids and foods in addition to breast milk occurs far too early in life; over half of children under the age of two months are given some form of supplemental feeding. Use of infant formula is not widespread in Kenya. Bottlefeeding, however, is more common; one in six infants under the age of 4 months is fed with a bottle. One in three children under the age of five is short for his/her age (stunted), which reflects chronic undemutrition. This proportion is 14 times the level expected in a healthy, well-nourished population. Twelve percent of the children were severely stunted. x×i Six percent of children under five are wasted (i.e., low weight low in relation to height). Wasting generally indicates acute undemutrition in recent months and may be related to illness or shortage of food. Women whose height is ! 50 centimetres or less and whose mean body mass index (BMI) falls below 18.5 are considered to be at greater risk of being undernourished than other women. Height and weight measurements were obtained in the KDHS for mothers of children under age five. These data show that less than six percent of mothers are shorter than 150 centimetres. The mean weight was 55.8 kilogrammes; 9 percent of mothers have a BMI below 18.5. Knowledge of AIDS. All but a tiny fraction of respondents reported they had heard about AIDS. Almost all (96 percent of men and 90 percent of women mentioned sexual intercourse as a mode of trans- mission of the AIDS virus. About 90 percent of respondents say it is possible for a mother with the AIDS virus to pass it along to her child at birth. A large majority of men and women said it is possible to protect against getting AIDS. About 40 percent of men and women know someone who either has AIDS or who died of AIDS. And two-thirds of men and almost half of women say they themselves can get AIDS. Misconceptions regarding modes of transmission of the AIDS virus are common. About one-quarter of men and women interviewed said they believed it was possible to get AIDS from sharing clothes or eating utensils with someone who has AIDS; one-third of respondents said it is possible to get AIDS from kissing somone who has AIDS, and over half say it is possible to get AIDS from insect bites. One-third of men and less than 5 percent of women said they had had two or more sexual panners in the six months prior to the survey. Twenty percent of men and 6 percent of women said they had used a condom in the six months before the survey. Condom use was much higher among those who reported having more sexual partners. Availability of Health and Family Planning Services. KDHS data indicate that about half of women (48 percen0 live in communities served by community-based distributors (CBDs) of family planning methods. Of these, half (23 percent of all women) are covered by government-sponsored CBDs and half by CBDs sponsored by non-governmental organisations. At least some method of family planning is readily available in Kenya. Two-thirds of married women live within 5 kilometres of a source of family planning services. Health services are somewhat less proximate. Half of women live within 5 kilometres of a facility that provides antenatal care and only one- third live within 5 kilometres of a facility that provides delivery services. Conclusions. Fertility and family planning behaviour in Kenya have changed dramatically over the past decade. Fertility levels have fallen sharply and use of family planning has "almost doubled. Use of modem contraceptive methods has almost tripled since 1984. Today, virtually all married women and men have heard of at least one family planning method, well over half have used a method at some time, and one- third of married women are currently using a method. The KDHS data also indicate that family planning methods are easily accessible to the vast majority of women, although, of course, not all methods are equally available. Moreover, attitudes towards contraceptive use are generally favourable. Despite these successes of the family planning programme in Kenya, there are a number of continuing challenges. One is that the level of unwanted fertility remains high; one in six recent births was xxii unwanted and one in three was mistimed. KDHS data indicate that the fertility rate in Kenya would be substantially lower if all unwanted births could be avoided. Another challenge is to reduce regional disparities in fertility, fertility preferences and family planning use. For example, fertility in Coast Province has hardly declined at all, no doubt because women there have the highest mean ideal family size, the lowest proportion who want no more children, and the lowest proportions who approve of and use family planning. Thus efforts in Coast Province should concentrate on education and motivation activities. In Western Province, both fertility and unmet need are highest. The results from the KDHS indicate that Kenya has made remarkable progress in the delivery of key child survival interventions: use of antenatal care is high; tetanus toxoid coverage among pregnant women is high; almost half of women deliver with the assistance of medical professionals; childhood immunisation coverage is high; there is a fairly high level of utilisation of curative services for diarrhoea and acute respiratory infections; one-third of children with diarrhoea are given oral rehydration salts. Yet, one in ten Kenyan children dies before reaching his/her fifth birthday. Moreover, declines in childhood mortality have stagnated recently. Poor nutrition may play a role; one-third of children under five are stunted. Spacing births at longer intervals can also reduce the level of childhood mortality. KDHS data show substantially lower infant mortality among children bom four years or more after a prior birth compared to those born two years or less after a sibling. Mortality among children under five is particularly high in Nyanza Province. The AIDS epidemic poses a major threat for the health of adults and children in Kenya. Data on knowledge of AIDS among adult men and women show that AIDS awareness is high, but that the quality of knowledge on AIDS can still be improved. More importantly, the survey results on sexual bebaviour indicate that having multiple partners is common and condom use is not widespread. xxiii KENYA RIF~ UGI _IA RN WE E: MAP KEY 21 Nairobi EASTERN PROVINCE RIFTVALLEY PROVINCE 27 Embu 15 Baringo CENTRAL PROVINCE 37 Isiolo 3 Elgeyo Marakwet 22 Kiambu 29 Kitui 20 Kajiado 26 Kidnyaga 28 Machakos* 14 Kericho* 23 Murang'a 39 Marsabit 16 Laikipia 17 Nyandarua 25 Meru* 18 Nakuru 24 Nyed NORTHEASTERN PROVINCE 9 Nandi 19 Narok COAST PROVINCE 36 Garissa 38 Samburu 33 Kllffl 41 Mandera 4 Trans Nzola 31 Kwale 40 Wajir 1 Turkana 35 Lamu NYANZA PROVINCE 10 Uasin Gishu 32 Mombasa 30 Taita 13 Kisii* 2 West Pokot 34 Tana River 11 Kisumu WESTERN PROVINCE 7 Siaya 5 Bungoma 12 South Nyanza* 6 Susie 8 Kakamega* • Note: Each of the six districts marked with an astedsk was recently subdivided into two or more districts The former boundaries are shown here since they were used in this survey, xxiv CHAPTER 1 INTRODUCTION 1.1 Geography, History, and Economy Geography Kenya covers an area of 582,000 square kilometres. It borders Ethiopia in the north, Sudan in the northwest, Uganda on the west, Tanzania in the south and Somalia in the east. It has 400 kilometres of Indian ocean shoreline. Lying between 3 degrees north and 5 degrees south latitude and between 34 and 41 degrees east longitude, it is entirely within the equatorial zone. The country is almost bisected by the equator. The country falls into two distinct regions, i.e., lowland and highland (upland) Kenya. This distinction affects the climate, patterns of human settlement and agricultural activities. Kenya has an unusually diversified physical environment--savannah, tropical, equatorial volcanic and tectonic. Approximately 80 percent of Kenya's land is arid and semi-arid and only 20 percent is arable. A large part of the arid and semi-arid zones have been set aside for wildlife conservation. The main climatic feature is the long rainy season from March to May. This is followed by a long dry spell from May to October. Short rains come between October and December. In the area around Lake Victoria in the west, rains are well distributed throughout the year. Kenya is divided into 8 provinces, which are sub-divided into districts. In all there are 48 districts, seven of which were recently delineated. History Kenya became a nation independent from British rule on December 12, 1963. It was a multi-party state until 1982, when the constitution was amended to make it a one-party state. In November 1991, in line with political changes taking place the world over, Parliament repealed the section of the constitution which made Kenya a one-party state. A multi-party election was held in December 1992. There are 43 ethno-linguistic groups in Kenya. The major groups are Kikuyu, Luo, Luhya, Kamba, Kalenjin, Mijikenda, Meru, Embu, and Kisii. Kikuyus primarily live in Central Province, Luos inhabit the westem part of Nyanza Province, Luhyas live in Western Province, Kambas in the soutbem part of Eastem Province, Kalenjins in Rift Valley Province, Mijikendas in Coast Province, Merus in the northern part of Eastern Province and Kisiis in the eastern part of Nyanza Province. Christianity and Islam are the major religions. Economy Agriculture is the mainstay of Kenya's economy, accounting for about 25 percent of the gross domestic product (GDP); manufacturing accounts lbr about 13 percent of the GDP. Coffee, tea and tourism are the main foreign exchange earners. Since its independence in 1963, the country has gone through several economic phases. In the first 10 years of independence, the country enjoyed low inllation, high employment creation, and a relatively stable balance of payments position. GDP growth rates averaged 6.5 percent per annum. The second phase (1973-1980) saw the record growth upset by three major shocks. The first was the sharp rise in oil prices in 1973, which created considerable internal and external economic imbalances. In 1977-78, the prices of coffee and tea rose significantly, which immediately improved the balance of payments position, but subsequently created internal imbalances. The third shock was experienced when oil prices rose again in 1979. Despite these setbacks, Kenya enjoyed an average growth rate in GDP of 5.2 percent per annum, reflecting a moderate reduction in the high growth rates achieved in the first 10 years of independence. The third phase (1980-1985) was characterised by slow growth in GDP (2.5 percent). This economic decline resulted from several confounding factors, including high cost ofoil, a global recession in 1980-1982, as well as a drought in 1984. Phase Four started at the end of 1986, when the government implemented adjustment programmes in agriculture, trade and industry. Supported with an adequate external resources flow, principally from the World Bank and the International Monetary Fund, the adjustment program accelerated the growth in GDP to an average of 5.8 percent per annum. Phase Five of the Kenyan economy began in 1990 when GDP growth fell to 4.3 percent. It fell further to 2.2 percent in 1991 and 0.4 percent in 1992. This declining growth is attributed to a decline in external resources and poor performance of Kenya's main exports. 1.2 Population On the basis of census statistics, Kenya's population increased from 5.4 million in 1948 to 15.3 million in 1979 and to 21.4 million in 1989 (CBS, 1994) (see Table 1.1). Results of the 1989 census indicate that the intercensal population growth rate for Kenya is 3.4 percent per annum. This represents a modest decline from the growth rate of 3.8 percent per annum estimated from the 1979 population census. If the population contin- ues to grow at this rate the population of Kenya will increase to 30 million by the year 2000 (Re- public of Kenya, 1994). The crude birth rate increased from 50 per thousand in 1948 to 52 per thousand in 1979, whereas the crude death rate decreased from 17 to 14 per thousand in the same period. The infant mortality rate decreased from 119 deaths per thou- sand births in 1969 to 104 in 1979 and further to about 69 deaths per thousand births in 1989. As a result of high fertility and declining mortality, Kenya is cbaracterised by a young population. Over 50 percent of Kenya's population is less than 15 years of age. Table 1.1 Demographic indicators r Kenya~ 1969 r 1979 r and 1989 Population census Indicator 1969 1979 1989 Population (millions) 10.9 15.3 21.4 Density (pop./sq.km.) 19 27 37 Percent urban 9.9 15.1 17.5" Crude birth rate 50 52 NA Crude death rate 17 14 NA Total fertility rate 7.6 7.9 6.7 b Infant mortality rate (per 1000) 119 104 69 ° Life expectancy at birth 50 54 59 c NA = Not available "Provisional figure bProm 1989 KDHS CFrom World Bank Sources: 1969--CBS. 1970, p.12, 16, 38, 43, 56. 1979--CBS. 1981b, p.4, 5, 87, 88, 103. 1989--CBS. 1994; CBS. 1991a, p.31; NCPD. 1989, p.18; and World Bank. 1991, p.35l. The 1984 Kenya Contraceptive Prevalence Survey (KCPS) showed some evidence of a possible decline in fertility, from a total fertility rate of 8.1 children per woman in 1977/78 (CBS, 1980) to 7.7 in 1984 (CBS, 1984). This evidence was confirmed by the findings of the 1989 KDHS which showed that the total fertility rate had actually dropped to 6.7 children per woman (NCPD, 1989). According to results of the 1989 census, 19 percent of Kenya's population lived in urban areas (CBS, 1991a) and the intercensal growth rate of the urban population was 4.8 percent per annum. This rate is above the national growth rate. The population of the capital city, Nairobi, has increased from 827,775 in 1979 to an estimated 1,324,570 in 1989 (CBS, 1994). This increase can be attributed in large extent to rural-urban migration. 1.3 Population and Family Planning Policies and Programmes The Government of Kenya became concerned about the high rate of population growth after the 1962 population census which showed that population was growing at the rate of 3.3 percent. The Family Planning Association of Kenya (FPAK) was established by private individuals in 1957, but it was not until 1967 that the official national family planning programme was launched. Family planning was integrated into the matemal and child health division of the Ministry of Health. At first, due to lack of an effective health infrastructure and adequate skilled manpower, the Ministry of Health relied mainly on FPAK and expatriate staff for service delivery. After the 1969 census provided evidence of a high level of fertility, the government decided to launch a five-year (1974-1978) family planning programme. The specific goals of the programme were to reduce the high annual rate of natural population increase from 3.3 percent (in 1975) to 3.0 percent (in 1979) and to improve the health of mothers and their children under the age of five. Initially, however, the family planning component of the Matemal and Child Health Programme had limited success. The 1979 census results indicated a population growth rate of 3.8 percent per armum, which was higher than the projected growth rate of 3.0 percent. This failure to achieve the targetted population growth rate could be attributed to shortfalls in the assumptions used to arrive at the target. The plan to reduce the growth rate concentrated on the supply side of family planning services instead of putting emphasis on programmes aimed at changing family size norms. It was with the realisation of the need to improve on the earlier weaknesses of the family planning programme that the Government of Kenya approved the establishment of the National Council for Population and Development (NCPD) in 1982. The Council's mandate is to formulate population policies and strategies and to co-ordinate the activities of govemment ministries, non-govemmental organisations, and donors involved in population, integrated rural health, and family planning programmes. 1.4 Health Priorities and Programmes The 1994-1996 Kenya Development Plan underscores the achievement of "Health For All by the Year 2000" as stipulated in the "Alma Ata Declaration" to be the long-term objective of the health sector. This long-term objective will be achieved through the following policies: • Increasing coverage and accessibility of health services with active community participation; Consolidating maternal and child health and family planning services in order to reduce morbidity and fertility; 3 • Increasing inter-sectoral collaboration with other ministries involved in the improvement of health status; and Encouraging the non-governmental organisations to take a greater role in the delivery and financing of health care services. Use of Community-Based Health Workers (CBHWs) and Community-Based Distributors (CBDs) to provide services is being emphasised. It is estimated that there are slightly over 10,000 CBDs employed by government and non-governmental agencies to provide non-clinical family planning methods (Lewis et al., 1992). In 1981, the Ministry of Health started a major programme in preventive health, the Kenya Expanded Programme on Immunisation (KEPI). Several other government programmes aimed at the reduction of diseases, improvement of nutrition, and provision of maternal and child health services have also been launched. However, budgetary constraints have adversely affected provision of health services in the country. 1.5 Objectives of the 1993 Kenya Demographic and Health Survey The KDHS is intended to serve as a source of population and health data for policymakers and the research community. It was designed as a follow-on to the 1989 KDHS, a national-level survey of similar size that was implemented by the same organisations. In general, the objectives of KDHS are to: assess the overall demographic situation in Kenya, assist in the evaluation of the population and health programmes in Kenya, advance survey methodology, and assist the NCPD to strengthen and improve its technical skills to conduct demographic and health surveys. The KDHS was specifically designed to: provide data on the family planning and fertility behaviour of the Kenyan population to enable the NCPD to evaluate and enhance the National Family Planning Programme, measure changes in fertility and contraceptive prevalence and at the same time study the factors which affect these changes, such as marriage patterns, urban/rural residence, availability of contraception, breastfeeding habits and other socioeconomic factors, and • examine the basic indicators of maternal and child health in Kenya. 1.6 Survey Organisation The 1993 KDHS is a national survey that was carded out by the NCPD in collaboration with the Central Bureau of Statistics (CBS). Macro International Inc. of Calverton, Maryland (USA) provided technical and financial assistance through its contract with the U.S. Agency for International Development (USAID). Sample Design The 1993 KDHS sample is national in scope, with the exclusion of all three districts in North Eastern Province and four other northern districts (Samburu and Turkana in Rift Valley Province and Isiolo and 4 Marsabit in Eastern Province). Together the excluded areas account for less than 4 percent of Kenya's population. The KDHS utilised a two-stage, stratified sample consisting of 536 sample units (clusters). Details of the sample design appear in Appendix A. Despite the emphasis on obtaining district-level data for planning purposes, it was decided that reliable estimates could not be produced from the KDHS for all 48 districts, unless the sample were expanded to an unmanageable size. However, it was felt that reliable estimates of certain variables could be produced for the rural areas in 15 districts: Bungoma, Kakamega, Kericho, Kilifi, Kisii, Macbakos, Meru, Murang'a, Nakuru, Nandi, Nyeri, Siaya, South Nyanza, Taita-Taveta, and Uasin Gishu; in addition, Nairobi and Mombasa were also targetted. These areas were targetted because they are generally the larger districts in their provinces, most were districts in which NCPD had posted District Population Officers, and most were also targetted in the 1989 KDHS. Although six of these districts were subdivided shortly before the sample design was finalised, the previous boundaries of these districts were used for the KDHS in order to maintain comparability with the 1989 survey. Due to this oversampling, the KDHS sample is not self-weighting at the national level. Sample weights were used to compensate for the unequal probability of selection between strata, and weighted figures are used throughout the remainder of this report. Questionnaires The survey utilised four types of questionnaires. A Household Schedule was used to list the names and certain characteristics of all usual members and visitors to a selected household. The Woman's Questionnaire was used to collect information from women age 15-49. In addition, interviewing teams measured the height and weight of mothers and of all her children under age five. Information from a subsample of men age 20-54 was collected using a Man 's Questionnaire. The Serviees Availability Questionnaire was used to collect information on the health and family planning services near the sample areas. One services availability questionnaire was to be completed in each sample point. The questionnaires were developed in English by task forces established in Kenya. All except the Services Availability Questionnaire were translated into and printed in Kiswahili and eight of the most widely spoken local languages in Kenya (for more information, see Appendix A). Fieldwork Fieldwork for the KDHS was carried out by 12 interviewing teams. In total, there were 12 supervisors, 11 field editors, 60 female interviewers, 12 male interviewers and 12 drivers. Each team was also coordinated by one NCPD officer. District Population Officers and some District Statistical Officers coordinated some teams and assisted in field logistics. Before launching the survey on 17th February 1993, interviewers, supervisors and field editors had previously been trained. Fieldwork was completed on 15th August 1993. The proportion of households interviewed by month was approximately: February (6 percent); March (17 percent); April (15 percent); May (18 percent); June (20 percent); July (21 percent); August (3 percent). Table 1.2 shows a summary of response rates from the household and individual interviews. A total of 8,805 households was selected for the survey, of which 7,950 were successfully interviewed. The shortfall is primarily due to dwellings being vacant or in which the inhabitants had left for an extended period at the time they were visited by the interviewing teams (for details, see Appendix Table A.1). Of the 8,185 households that were found, 97 percent were interviewed. Within these households, 7,952 women were identified as eligible for an individual interview and of these, 7,540, or 95 percent, were interviewed. In the one half of the households that were selected for inclusion in the male survey, 2,762 eligible men were identified, of which 2,336, or 85 percent, were interviewed. Response rates were higher in rural than in urban areas. 5 Table 1.2 Results of the household and individual interviews Number of households, number of interviews and response rates, Kenya 1993 Residence Result Urban Rural Total Household Interviews Households sampled 1654 7151 8805 Households found 1483 6702 8185 Households interviewed 1379 6571 7950 Household response rate 93.0 Individual Interviews Number of eligible women Number of eligible women interviewed Eligible woman response rate Number of eligible men Number of eligible men interviewed Eligible man response rate 98.0 97.1 1266 6686 7952 1161 6379 7540 91.7 95.4 94.8 616 2146 2762 480 1856 2336 77.9 86.5 84.6 6 CHAPTER 2 CHARACTERISTICS OF HOUSEHOLDS AND RESPONDENTS The purpose of this chapter is to provide a short descriptive summary of some socioeconomic characteristics of the household population and the individual survey respondents, such as: age, sex, residence and educational level. It also examines the environmental conditions such as household facilities and household characteristics. This information on the characteristics of the households and the individual women interviewed is essential for the interpretation of survey findings and can provide an approximate indication of the representativeness of the survey. 2.1 Characteristics of the Household Population In the KDHS, information was collected about all usual residents and visitors who had spent the previous night in the selected household. A household was defined as a person or group of people who live together and share food. Age and Sex The distribution of the household population in the KDHS is shown in Table 2.1 by five year age groups, according to sex and urban-rural residence. The age distribution is typical of high fertility regimes in which a larger proportion of the population is to be found in the younger age groups than in the older age groups (see Figure 2.1 ). However, it is encouraging that the number of children under five is slightly less than the number age 5-9, which is possible evidence of a recent decline in fertility. Table 2.1 Household population by ag% residence and sex Percent distribution of the de facto household population by residence and sex, Kenya 1993 five-year age groups, according to urban-rural Urban Rural Total Age group Male Female Total Male Female Total Male Female Total 0-4 13.6 13.5 13.6 17.2 15.4 16.3 16.7 15.2 15.9 5-9 10.8 14,0 12.4 18.3 17.9 18.1 17.2 17.4 17.3 10-14 9.6 l l . l 10.3 17,1 16.5 16.8 16.0 15.8 15,9 15-19 8.4 10.9 9.6 11.5 9.1 10.2 11.0 9.4 10.2 20-24 10.2 16.2 13.1 6.5 7.6 7.1 7.0 8.7 7.9 25-29 11.9 11.4 11.7 4.5 6.1 5.3 5.6 6.8 6.2 30-34 11.4 8.1 9.8 4.6 5.2 5.0 5.6 5.6 5.6 35-39 7.6 4.7 6.2 3.3 4.0 3.7 3.9 4.1 4.0 40-44 5.2 3.2 4.2 3.3 3.4 3.4 3,6 3.4 3.5 45-49 4,2 1.7 3,0 2.7 2.3 2.5 2.9 2,2 2.5 50-54 2.4 2.4 2.4 2.1 3.7 3.0 2.2 3.6 2.9 55-59 2.2 0.9 1,6 2.1 2.3 2.2 2.1 2.1 2.1 60-64 1.2 0.6 0.9 2,1 2.4 2.2 1.9 2.2 2.1 65-69 0.5 0,4 0.4 1.5 1.5 1.5 1.3 1.3 1.3 70-74 0.4 0.5 0.4 1.3 1.0 1.1 1.2 0.9 1.0 75-79 0.1 0.2 0.1 0.6 0.6 0.6 0.5 0.6 0.5 80 + 0.2 0.2 0.2 0.8 0.7 0.8 0.7 0.6 0.7 Missing/Don't know 0.3 0.0 0.2 0.4 0.2 0.3 0.4 0.2 0.3 Total I00.0 100.0 100.0 100,0 100.0 100.0 100.0 100.0 100.0 Number 2673 2529 5202 15616 17406 33022 18289 19935 38224 7 Age 80+ 75-79 70-74 Figure 2.1 Population Pyramid, Kenya 1993 55-5~ Male ~ Female 50-54 40-44 2s-~ 20-24 15-19 I 10-140-4 s-9 10 5 0 5 Percent 10 KDHS 1993 There seems to be an excess of females over males at ages 5-24, especially in urban areas and especially at ages 20-24. The irregular bulge of women at age 50-54 is indicative of women from ages 45-49 being pushed to 50-54 age group, perhaps to reduce the workload of the interviewer. This pattern has been observed in other DHS surveys (Rutstein and Bicego, 1990). This pattern is more pronounced among women in rural than in urban areas. However, the impact of these irregularities on the quality of the data is probably small. Figure 2.2 shows the distribution of the male and female household population by single year of age (see also Appendix Table C.1). The data show evidence of a preference to report ages that end in zeros and to a lesser extent, fives (age "heaping" or digit preference) that is commonly found in countries where ages are not known well. There is also a relative dearth of women age 15 and an excess of women age 13 and 14, relative to men. This pattem is almost certainly due to interviewers intentionally pushing women outside of the age range established for the individual interview, thus reducing their workloads. This same phenomenon probably caused the excess of women at ages 51-54 relative to men. It is difficult to know the reason for the somewhat odd excess of boys at ages 0-2 and age 4, or the excess of women at ages 20-28. Table 2.2 compares the broad age structure of the population from the 1977/78 Kenya Fertility Survey (KFS), the 1984 Kenya Contraceptive Prevalence Survey (KCPS), the 1989 KDHS, and the 1993 KDHS. It emerges that the proportion of the population less than 15 years had remained stable through the 1989 KDHS and has only recently declined from 53 percent in 1989 to 49 percent in 1993. Similarly, the proportion of population age 15-64 years has risen from 44 to 47 percent. The most likely explanation for this change is a recent decline in fertility. 8 Figure 2.2 Distribution of De Facto Household Population by Single Year of Age and Sex Percent [ I I I I I I I I I I I I 5 10 15 20 25 30 35 40 45 50 55 60 65 70+ Single Year of Age - 'Ma le - -Female / KDHS 1993 Table 2.2 Population by age from selected sources Percent distribution of the de facto population by age group, selected sources 1977/78 1984 1989 1993 Age group KFS KCPS KDHS KDHS Less than 15 52.5 52.0 52.5 49.1 15-64 43.9 44.9 44.0 47.0 65+ 3.5 2.8 3.5 3.6 Missing/don't know 0.0 0.0 0.0 0.3 Total 100.0 100.0 100.0 100.0 Median age NA NA NA 15.3 Note: Totals may not add due to rounding NA = Not available Sources: KFS--CBS. 1980, p. 45; KCPS--CBS. 1986, p. 22; 1989 KDHS-- NCPD. 1989, p. l l3. Household Composition Table 2.3 shows that a large majority of households in Kenya are headed by males (67 percent), with only one-third (33 percent) headed by women. Female-headed households are more common in rural than in urban areas (35 vs. 22 percent). Among the provinces, Nairobi has the lowest proportion of female-headed 9 Table 2.3 Household composition Percent distribution of households by sex of head of household, household size, kinship structure, and presence of foster childre~rt, according to urban-rural residence and region, Kenya 1993 Residence Province Rift Chenaeterislic Urban Rural Nairobi Centxal Coast Eastern Nyanza Valley Western Total Household headship Male 78.5 64.7 80.3 62.8 73.2 61.6 59.7 74.3 65.9 67.3 Female 21.5 35.3 19.7 37.2 26.8 38.4 40.3 25.7 34.1 32.7 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Number of usual membe~ 1 ~.1 11.1 33.0 19.7 21.0 9.0 11.2 12.7 7.0 14.6 2 18.0 9.8 ~.5 12.3 12.4 6.7 13.1 11.5 7.4 11.3 3 13.6 11.2 13.3 11.9 9.2 11.8 12.4 11.3 11.3 11.7 4 11.8 12.2 13.7 13.2 8.9 10.6 12.8 12.1 12.8 12.1 5 10.2 13.8 8.6 12.9 9.5 12.8 14.6 12.8 17.6 13.1 6 6.1 12.4 4.5 12.5 6.5 14.0 11.4 12.6 10.8 11.2 7 4.4 10.0 3.1 7.5 7.7 12.0 10.0 8.6 10.4 8.9 8 2.8 7.4 1.4 4.1 8.1 9.8 7.2 6.4 6.6 6.5 9+ 3.9 12.1 1.6 5.9 16.5 13.4 7.2 12.0 16.0 10.5 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 I00.0 Meana l~ 3.4 5.1 2.9 4.2 5.2 5.5 4.7 4.9 5.5 4.8 Relationship structure One adult 34.9 23.0 37.1 31.2 28.6 20.6 23.7 22.7 20.8 25.3 Two related adults: Of opposite sex 27.2 32.3 29.3 31.7 21,2 29.8 33.1 36.6 29.5 31.3 Of same sex 8.6 5.2 8.2 5.3 9,4 5.9 6.6 4.6 3.6 5.8 Three or more related adults 20.2 35.1 17.0 27.3 36,8 36.7 34.5 30.6 39.2 32.2 Other 9.0 4,3 8.2 4.5 4,0 6.8 2,1 5.2 6.9 5.2 Total 100.0 100.0 100.0 100.0 100,0 100.0 100.0 100.0 100.0 100.0 With foster children a 10.8 18.9 6.8 11.7 16,8 17.9 21.0 18.0 25.3 17.4 Note: Table is b~ed on de jure members; i.e. usual residents. aFoster children are those under age 15 living in households with neither their mother nor their father present. households (20 percent), followed by Rift Valley Province (26 percent). Nyanza Province has the highest proportion of female-headed households (40 pereen0. The average household size in Kenya is 4.8 people. Households in rural areas are substantially larger, on average, than those in urban areas (5.1 vs. 3.4 persons). Single-person households are more common in urban than in the rural areas. They are more common in Nairobi and in Coast and Central Provinces than in the other provinces. One quarter of Kenyan households consist of only one adult, either with or without children. Roughly one-third of households contain two related adults of opposite sexes (presumably most of which are married couples); another one-third consist of three or more related adults. Households of three or more related adults 10 are more common in Western Province (39 percent) and least common in Nairobi (17 percent) and Central Province (27 percent). The pattern of household structures has been influenced by the high rates of rural- urban migration. Children who live with neither their natural mother nor father have been shown to be socioeconomically disadvantaged. In Kenya, almost one in five households includes one or more of these foster children. Households with foster children are more common in rural (19 percent) than in urban areas (11 percent). Westem Province has the highest proportion of households with foster children (25 percent), while Nairobi (mainly urban) has the lowest (7 percent). Less than one percent of children under age 15 arc orphaned, that is, both their parents have died (data not shown); however, 2 percent have lost their mothers and 5 percent have lost their fathers. Education Kenya's formal education is based on a three-tier system, known as the 8-4-4 system. In this system primary education consists of 8 years and secondary education 4 years. Graduates of secondary school may then further their education by enrolling at any of the five national universities or in any of several private universities, or by joining colleges or technical institutes to acquire certain skills necessary for national development. The 8-4-4 system was adopted in 1985, replacing a four-tier system (7-4-2-3) consisting of seven years of primary school, four of secondary, two of higher secondary, and three of university. KDHS results show that there is still a strong differential in education between males and females in Kenya (Tables 2.4.1 and 2.4.2). The data indicate that 17 percent of men and 27 percent of women age six Table 2.4.1 Edueati~aal level of the male household population Percent disla'ibution of the de facto male household population age six and over by highest level of education attended, according to selected background characteristics, Kenya 1993 Background Primary Primary Second- characteristic None incomplete complete ary+ Missing Total Number Age 1 6-9 35.5 63.4 0.1 0.1 0.9 100.0 2590 10-14 5.0 89.4 4.6 0.6 0,5 100.0 2921 15-19 3.4 44.4 35.5 16.5 0.3 100.0 2016 20-24 4.3 18.3 35.1 41.7 0.6 100.0 1286 25-29 3.7 16,5 32.7 46.7 0.4 1O0.0 1028 30-34 5.5 19.1 30.0 44.7 0.8 100.0 1027 35-39 9.2 23.8 25.3 41.2 0.5 100.0 717 40-44 16.8 26.6 21.4 33.4 l.S 100.0 659 45-49 14.6 28.7 32.7 22.6 1.4 100.0 528 50-54 25.8 36.3 24.8 10.8 2.2 100.0 398 55-59 40.6 34.3 17.0 6.6 1.5 100.0 392 60-64 45.4 41.1 7.1 4.6 1.7 100.0 357 65+ 65. I 26.9 3.5 3.0 1.6 1GO.0 684 Residence Urban 7.0 27.8 19,9 43.9 1.3 100.0 2253 Rural 18.2 50,3 17.8 12.8 0.9 100.0 12420 Province Nairobi 6.3 23.4 21,3 47.6 1.4 100.0 880 Central 11.2 47,0 23.3 17,5 1.0 100.0 2118 Coast 21.3 40.6 19.4 16.7 2.1 100,0 1390 Eastern 17.7 52,4 17.1 12.4 0,4 100,0 2787 Nyanza 16,0 52.2 17.8 13,1 0.9 100.0 2137 Rift Valley 20.3 46.5 16.1 15.8 1.3 100.0 3325 Western 15.9 48.5 15.6 19.8 0.2 100.0 2036 Total 16.5 46.8 18.2 17.5 1.0 100,0 14672 1Excludes 69 men for whom an age was not reported. 11 Table 2,4.2 Educaticctal level of the female hotlsehold pOpulatice Percent distribution of the de facto female bouf, ehold population age six end over by highest level of educallo~ attended, according to selected background characteristics, Kenya 1993 Background Primary Primary Second- characteristic None incomplete complete ary+ Missing Total Number Age I 6-9 35.7 62.9 0.0 0.0 1.4 1(30.0 2865 10-14 5.0 86.8 7.1 0.6 0.5 100.0 3158 15-19 4.3 38.8 37.5 18.8 0.6 100.0 1867 20-24 6.2 25.5 36.4 31.6 0.3 100.0 1736 25-29 12.5 25.6 27.5 33.9 0.5 100.0 1346 30-34 21.4 32.0 18.5 27.6 0.5 100.0 1118 35-39 36.5 29.6 16.2 17.2 0.4 100.0 811 40-44 42.4 30,4 17,9 8.1 1.2 100.0 675 45-49 54.7 26.5 11.9 6.0 0.9 100.0 446 50-54 70.3 21.7 4.2 2.1 1.7 100.0 712 55-59 77.3 17.5 2.5 1.2 1.4 100.0 423 60-64 84.6 11.6 1.2 0.1 2.5 100.0 430 65+ 87.5 8.6 0.6 0.6 2.8 100.0 687 Residence Urban 13.5 31.8 21.1 32.8 0.7 1OO.0 2108 Rural 29.1 46.8 14.4 8.7 1.0 100.0 14207 province Nairobi 12,7 22.1 24.1 40.6 0.6 100.0 707 Central 21.0 45.1 19.7 13.8 0.5 100.0 2409 Coast 41.0 34.1 13.6 8.9 2.4 100.0 1525 Eastern 27.2 47.0 15.3 9,8 0.8 100.0 3200 Nyanza 28.5 49.2 13.0 8.4 0.9 100.0 2583 Rift Valley 28.4 47.0 13.3 9.9 1.4 1(30.0 3552 Western 24.8 47.7 14.5 12.5 0.4 100.0 2339 Total 27.1 44.9 15.3 11.8 1.0 100.0 16315 tExcludes 40 women for whom an age was not reported. and above have not received any formal education. At almost every age group there are smaller proportions of men than women with no education and more men than women with secondary education (Figure 2.3). However, the sex differential is narrowing over time; differences in educational attainment between school- age boys and girls are insignificant. The proportion of both men and women with no education is higher in rural than in urban areas. Rural residents are more than twice as likely to have never attended school compared to urban dwel lers~l 8 vs. 7 percent for males and 29 vs. 14 percent for females. Residents of Nairobi and Central Province are more educated than residents of other provinces. Table 2.5 presents enrolment rates by age, sex and residence of children age 6-24 years. Almost nine in ten children (86 percent) age 6-15 years are enrolled in school. Enrolment drops substantially after age 15; only 44 percent of the older teenagers are still in school and only 9 percent of those in their early twenties are still in school. It is somewhat surprising that at all age groups, enrolment is higher in rural areas than in urban areas. At ages 6-15 boys are slightly more likely to be enrolled than girls (87 percent of boys compared to 85 percent of girls). By ages 16-20, men are much more likely to be enrolled than women (52 percent compared to 36 percent), presumably because of early marriage and childbearing which cause young women to drop out of school. 12 Table 2.5 School enrolment Percentage of the de facto household population age 6-24 years enrolled in school, by age group, sex, and urban- rural residence, Kenya 1993 Male Female Total Age group Urban Rural Total Urb~m Rural Total Urban Rural Total 6-I0 84.6 85.3 85.3 81.9 82.9 82.8 83.2 84.1 84.0 11-15 83,7 89.9 89.4 74.0 88.8 87.4 78.4 89.4 88,4 6-15 84.2 87.4 87.1 78.3 85.5 84.8 81,0 86.4 85.9 16-20 42.6 53.6 52.2 22.7 38.2 35.6 31.0 45.8 43.6 21-24 I0.3 13.1 12.4 6.4 5.7 5.9 8.1 8.9 8.7 100 8O 4O 2O Figure 2.3 Percentage of Males and Females Who Have Completed Primary Education by Age Group Percent 0 [ ] I I I I I " r .,. -,, 15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59 60-64 65+ Age Group KDHS 1993 13 2.2 Hous ing Character i s t i cs Soc ioeconomic cond i t ions were assessed by ask ing respondents quest ions about the i r househo ld env i ronment . Th is in fo rmat ion is summar ised in Tab le 2.6. Table 2.6 Housing characteristics Percent distribution of households by housing characteristics, according to urban-rural residence and region, Kenya 1993 Residence Province Rift Characteristic Urban Rural Nalrobi Central Coast Eastern Nyanza Valley Western Total Electricity Yes 42.5 3.4 50.8 9.8 16.9 4.1 3.4 7.1 7.6 10.9 No 57,0 96.2 48.8 89,6 82.7 95.7 95.8 92.5 92.1 88.7 Missing 0.5 0.4 0.4 0.6 0.4 0.2 0,8 0,4 0.3 0.4 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Source of dr inking water Piped into residence 55.8 10.7 65.0 27.4 15.8 14.8 3.5 15.9 14.4 19.4 Public tap 31.4 8.9 27.3 10.7 37.4 11.6 8.4 9.8 5.3 13.2 Well with hand pump 0.9 10.8 0.0 5.5 13.6 3,3 8.2 5.0 31.2 8.9 Well without hand pump 2.1 14.6 0.2 13,6 5.4 13.5 7.3 15.2 21.7 12.2 Lake/pond 0.1 8.7 0.0 1.9 9.4 7.1 21.8 4.6 2.5 7.1 River/stream 1.6 41.2 0.0 33.2 12.1 45.8 43.7 44.0 23.2 33.6 Rainwater 0.6 2.6 0.0 5.2 0.5 2.5 1.3 2.8 1.1 2.2 Other 6.6 1,9 6.8 1.5 5.4 1.3 5.0 2.1 0.7 2.8 Missing/Don't know 0.8 0.5 0.8 1.0 0.4 0.2 0.9 0.8 0.0 0.6 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Sanitation facility Own flush toilet 23.5 1.1 19.3 2.0 5.9 2.1 1.5 6.9 7.2 5.4 Shared flush toilet 21.4 0.5 34,0 1,2 3,8 1.0 1.6 3.5 0.7 4.5 Trad. pit toilet 42.3 71.4 36.5 83.3 58.1 73.4 61.7 55.6 80.2 65.8 Vent. imp. pit latrine 6.9 5.9 3.3 10.3 7.9 5.4 4.3 6.2 4.1 6,1 No facility/bush 2.1 20.3 3.1 0.8 23.7 17.8 29.9 26.0 7.6 16.8 Other 3.0 0.3 3.1 1.2 0.1 0.0 0.2 1.5 0.0 0.8 Missing/Don't know 0.9 0.5 0.8 1.3 0.5 0.4 0.8 0.3 0,3 0.6 Total 100.0 I00.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100,0 Flooring Earth/dung floor 20.6 79.9 24.4 63.4 58.7 72.8 82.8 70.8 82.4 68.5 Wood planks (rudim.) 0.3 0.2 0.4 0.4 0.1 0.0 0.0 0,6 0.0 0.2 Parquet/polished wood 0.7 0.1 1.2 0.1 0.0 0.0 0.4 0.0 0.1 0.2 Vinyl/linoleum/asphalt 0.3 0.0 0.4 0.0 0.0 0.0 0.0 0.1 0.0 0.1 Ceramic files 3,0 0.3 4.9 0.3 0.7 0.3 1.0 0.2 0.1 0.8 Cement 74.0 19.2 67.4 35.1 39.9 26.6 14.9 28.0 17.3 29.7 Other 0.2 0.0 0.4 0.0 0.1 0.0 0.0 0.0 0.0 0.0 Missing/Don't know 0.9 0.3 0.8 0.7 0.5 0.3 0.8 0.2 0.0 0.4 Total 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 65.1 54.9 66.6 74.2 67.2 55.2 50.2 48.0 47.4 56.9 34 23.5 29.0 21.9 18.8 23.5 28.8 31.8 32.5 32.5 27.9 5-6 7.9 10.2 7.8 5.5 5.4 9.4 10.9 12.3 14.3 9.8 7 + 2.4 4.9 2.9 0.7 3.0 5.7 5.8 5.8 5.4 4.5 Missing/Don't know 1.1 0.9 0.8 0.7 0.8 0.8 1.3 1.4 0.4 1.0 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Mean persons per room 2.4 2,9 2.3 2.i 2.4 2.9 3.0 3.1 3.2 2.8 Number of households 1527 6423 645 1282 678 1348 1245 1745 1007 7950 14 The table shows that electricity is available to only 11 percent of households in Kenya. Electricity is more available in urban households (43 percent) than rural households (3 percent). Electricity is much more common in Nairobi (51 percent of households) and Coast Province (17 percent). Nyanza Province has the lowest proportion of households with electricity (3 percent). Sources of drinking water differ widely by area of residence. In the urban areas, piped water is the major source; 56 percent of households have water piped into the residence and another 31 percent obtain water from a public tap. In rural areas, only 11 percent of households have water piped into the residence. The major sources of water in the rural areas are rivers and streams (41 percent) and wells (25 percent). Water sources differ widely by province of residence. Sixty-five percent of households in Nairobi have water piped into the residence, compared to 27 percent of households in Central Province, about 15 percent of households in Rift Valley, Coast, Eastern, and Western Provinces, and only 4 percent of households in Nyanza Province. Households in Coast Province rely more heavily on public taps as a source of drinking water (37 percent) than households in other provinces, while households in Western Province use wells more frequently as a source of drinking water (53 percent). A majority of households in Kenya (66 percen0 have traditional pit toilets. Seventeen percent have no facility at all, while only 5 percent have their own flush toilets. Households in both urban and rural areas commonly use traditional pit latrines (42 percent and 71 percent, respectively). In urban areas, 24 percent of households have their own flush toilets and 21 percent have shared flush toilets. There are large differences among provinces in types of sanitary facilities; the traditional pit latrine is most common in Central Province (83 percent of households) and least common in Rift Valley Province (56 percent) and Nairobi (37 percent). Thirty percent of households in Nyanza Province have no toilet facilities, compared to less than one percent of households in Central Province. Almost all Kenyan households live in residences with floors made out of either earth (69 percent) or cement (30 percent). Cement flooring is most common in urban areas (74 percent), while earthen floors are most common in rural areas (80 percent). Cement flooring is most common for households in Nairobi (67 percent). Earthen floors are the most common in all the other provinces. As a way of estimating the extent of crowding, information was gathered on the number of rooms households use for sleeping. The majority of households (57 percent) have one or two persons per sleeping room, while about one quarter (28 percent) have three or four persons per sleeping room. The mean is 2.8 persons per sleeping room. There is only a small difference in the number of persons per sleeping room between households in urban and rural areas. Among the provinces, crowding seems to be less common in households in Central Province than in the other provinces. Household Durable Goods Respondents were asked about ownership of particular household goods such as radios and televisions (to assess access to media), refrigerators (to assess access to food storage), bicycles (to assess modes of transportation), and cattle, goats, sheep and cash crops (to assess levels of wealth). The results presented in Table 2.7 indicate that 52 percent of Kenyan households own a radio (68 percent of urban households and 48 percent of rural households) and 6 percent own a television (22 percent in urban areas and 2 percent in rural areas). Only 3 percent of Kenyan households own refrigerators. The relative lack of televisions and refrigerators in rural areas is presumably because of lack of electricity and greater financial constraints. Overall, one in five households (22 percent) owns a bicycle. A large majority own land (80 percent) or cattle, goats and sheep (63 percent). One-third of the households have cash crops. The proportion of households owning a television ranges from 24 percent in Nairobi to 2 percent in Eastern 15 Table 2.7 Household durable goods Percentage of households possessing various durable consumer goods, by urban-rural residence and region, Kenya 1993 Residence Province Rift Charac~ristie Urban Rural Nairobi Central Coast Eastern Nyanza Valley Western Total Radio 67.7 48.1 68.9 55.3 46.4 51.6 42.3 49.3 56.8 51.9 Television 22.0 2.4 24.0 6.0 6.7 2.1 2.0 6.8 4.0 6.1 Refrigerator 12.0 0.6 13.5 2.0 4.5 0.6 1.1 2.8 0.9 2.8 Bicycle 16.9 23.3 13.9 16.1 21.4 25.4 22.9 18.8 35.5 22.1 Land 43.0 88.8 49.6 75.5 59.4 90.9 88.5 81.5 91.4 80.0 Cattle/goats/sheep 29.6 70.7 36.7 63.5 36.3 74.4 65.7 70.1 64.8 62.8 Cash crops 16.4 38.3 23.4 44.0 26.1 41.5 35.8 24.0 39.5 34.1 Number of households 1527 6423 645 1282 678 1348 1245 1745 1007 7950 and Nyanza Provinces, while the proportion with bicycles ranges from 36 percent in Western Province to 14 percent in Nairobi. 2.3 Background Characteristics of Women Respondents General Characteristics Women were asked two questions in the individual interview to assess their age: "In what month and year were you bom?" and "How old were you at your last birthday?" Interviewers were trained to probe situations in which respondents did not know their age or date of birth, and they were instructed as a last resort to record their best estimate of the respondent's age. Table 2.8 shows the distribution of female respondents in five-year age groups. Table 2.8 indicates that 61 percent of female respondents are currently married or living with a man, ~ while about 30 percent have never been married (single). Three percent each are widowed, divorced, or separated. In the 1989 KDHS, 67 percent of women of childbearing age were married, 26 percent had never married, while 7 percent were either widowed, divorced, or separated. A large majority of the respondents have had some education; only 18 percent of women 15-49 have no formal education at all. Fifty-three percent have completed primary school (including those with secondary school), while 25 percent have gone to some secondary school. This shows considerable improvement since the 1989 KDHS. In 1989, 25 percent of women had never bcen to school, 47 percent had completed primary school and only 20 percent had continued to secondary school (NCPD, 1989, p.6). Kenya still remains predominantly rural, with less than one out of five women (18 percent) living in urban areas. The distribution of women by province is similar to that from other surveys and censuses. About one in five women are from each of Rift Valley and Eastern Provinces, approximately 15 percent are from each of Nyanza, Western and Central Provinces, while 10 percent are from Coast Province and 7 percent from Nairobi. ~Throughout this report, the term "married" includes both those in formal and informal marriages (living together). 16 Table 2.8 Background characteristics of respondents Percent distribution of women by selected background characteristics, Kenya 1993 Number of women Background Weighted Un- characteristic percent Weighted weighted Age 15-19 23.3 1754 1788 20-24 21.7 1638 1605 25-29 16.2 1221 1199 30-34 14.4 1088 1112 35-39 10.2 768 743 40-44 8.5 638 653 45-49 5.8 434 440 Marital status Never married 30.2 2280 2320 Married 58.3 4394 4329 Living together 3.1 235 254 Widowed 3.1 231 234 Divorced 2.7 202 198 Separated 2.6 198 205 Education No education 17.9 1352 1297 Primary incomplete 28.9 2179 2226 Primary complete 28.7 2166 2223 Secondary+ 24.5 1844 1794 Residence Urban 17.8 1339 1161 Rural 82.2 6201 6379 Province Nairobi 6.7 507 367 Central 14.5 1094 1075 Coast 9.5 717 1091 Eastern 18.6 1406 1044 Nyanza 15.4 1158 1264 Rift Valley 20.7 1562 1754 Western 14.5 1096 945 Religion Catholic 31.4 2368 2336 Protestant/other Christian 59.8 4509 4556 Muslim 4.9 370 366 No religion 2.7 204 201 Other 1.0 73 66 District t Mombasa 2.4 178 372 Murang'a 3.5 265 361 Nyeri 2.3 175 367 Kilifi 3.8 289 337 Taita Taveta 0.8 62 281 Machakos/Makueni 7.6 571 438 Meru/Tharaka-Nithi 5.2 388 364 Kisii/Nyamira 6.1 461 488 Siaya 2.6 196 408 South Nyanza 4.1 306 257 Kericho/Bomet 3.5 266 322 Nakuru 2.4 182 252 Nandi 2.2 164 403 Uasin Gishu 1.5 113 315 Bungoma 3.7 280 396 Kakamega/Vihiga 6.8 514 381 Total 100.0 7540 7540 IMombasa refers to the city; district refers only to rural areas of the district; the sum for districts does not add to I00.0. 17 Almost all the women interviewed report themselves as Christians (91 percent), either Protestant (60 percent) or Catholic (31 percent). Those who believe in Islam account for 5 percent, with about 3 percent reporting having no religion. Table 2.8 also presents the percentage of women who live in the rural areas of each of the 15 specially targetted districts and Mombasa. These figures provide a frame of reference for later statistics. Differentials in Educat ion Table 2.9 presents the distribution of female respondents by education according to selected characteristics. Results indicate that education is inversely related to age, that is, older women are less educated than younger women. For instance, only 4 percent of women age 15-19 have had no education, compared to 57 percent of women age 45-49. Rural women are more disadvantaged in education than urban women. Twenty percent of rural women have had no education at all, compared to 9 percent of urban women. Almost half (46 percent) of women in urban areas have attended secondary school, compared to 20 percent in the rural areas. There are also wide differentials in education attainment between regions. While less than 10 percent of the women in Nairobi and Central Province have no education, 37 percent of those in Coast Province are reported as having no education at all. Table 2.9 Level of education Percent distribution of women by the highest level of education attended, according to selected background characteristics, Kenya 1993 Highest level of education Number Background Primary Primary Second- of characteristic None incomplete complete ary+ Total women Age 15-19 4.2 33.5 41.0 21.4 100.0 1754 20-24 5.8 24.0 37.8 32.3 100.0 1638 25-29 12.7 25.4 26.0 35.9 100.0 1221 30-34 20.4 31.3 21.0 27.3 100.0 1088 35-39 36.9 30.6 15.7 16.8 100.0 768 40-44 43.2 30.8 17.6 8.4 100.0 638 45-49 57.0 26.6 11.3 5.1 100.0 434 Residence Urban 8.7 16.8 28.8 45.8 100.0 1339 Rural 19.9 31.5 28.7 19.9 100.0 6201 Province Nairobi 7.6 12.8 31.6 48.0 100.0 507 Central 9.5 22.5 36.6 31.3 100.0 1094 Coast 36.7 22.2 23.6 17.5 100.0 717 Eastern 16.6 32.2 29.9 21.3 100.0 1406 Nyanza 18.2 38.0 25.6 18.2 100.0 1158 Rift Valley 22.5 28.8 27.1 21.7 100.0 1562 Western 13.8 33.4 27.1 25.8 100.0 1096 Total 17.9 28.9 28.7 24.5 100.0 7540 18 Access to Media Women were asked if they usually read a newspaper, listen to the radio or watch television at least once a week. This information is crucial for planning the dissemination of family planning messages. Table 2.10 shows that two-thirds of women listen to the radio, one-third read a newspaper and 15 percent watch television at least once a week. Younger women have greater access to the media than older women. The higher the level of education the more access there is to the media; while only 2 percent of women with no education read a newspaper once a week, 61 percent of women with secondary education and above do so. Women in rural areas are more disadvantaged in access to media. While 80 percent of women in urban areas listen to the radio weekly, only 61 percent of rural women do so. Similarly, 56 percent of women in urban areas read a newspaper once a week, compared to only 26 percent of women in rural areas. Understandably, urban Nairobi enjoys more access to media than the other provinces. Fifty-nine percent of the women in Nairobi read a newspaper once a week, compared to only 23 percent of women in Westem Province. Women in Eastern and Nyanza Provinces are less likely to watch television than women in other provinces. Table 2.10 Access to mass media Percentage of women who usually read a newspaper once a week, watch television once a week, or listen to radio once a week, by selected background characteristics, Kenya 1993 Read Watch Listen to Number Background newspaper television radio of characteristic weekly weekly weekly women Age 15-19 38.1 18.6 67.7 1754 20-24 38.9 17.4 67.2 1638 25-29 33.3 14.5 68.7 1221 30-34 28.8 14.5 65.5 1088 35-39 22.7 10,5 56.5 768 40-44 17.3 9.5 55.0 638 45-49 13.7 8.2 59.2 434 Education No education 1.7 3.8 41.5 1352 Primary incomplete 18.7 8.4 56.6 2179 Primary complete 37.5 14.1 71.6 2166 Secondary+ 61.0 31.8 83.2 1844 Residence Urban 55.8 45.5 79.9 1339 Rural 26.2 8,3 61,4 6201 Province Nairobi 58.9 48.5 81.7 507 Central 29.7 17.0 69.0 1094 Coast 29.2 17.6 55.3 717 Eastern 26.8 6.2 64.4 1406 Nyanza 36.1 6.1 58.7 1158 Rift Valley 31.2 17.3 64.8 1562 Western 23.3 12.7 65.5 1096 Total 31.4 14.9 64.7 7540 19 CHAPTER 3 FERTILITY 3.1 Introduction The measurement of fertility levels, differentials and determinants has remained a major objective in all the demographic, contraceptive and health surveys that have been carried out in Kenya since 1977. The 1993 Kenya Demographic and Health Survey (KDHS) was no exception to this rule. The level of fertility has been a major factor underlying Kenya's high population growth rate. The understanding of fertility dynamics is therefore of paramount importance. The fertility indicators presented in this chapter are based on reports provided by women age 15-49 years regarding their reproductive histories. As in the 1989 KDHS, each woman was asked to provide information on the total number of sons and daughters to whom she bad given birth who were living with her, the number living elsewhere, and the number who had died. The women were also asked for a history of all live births, including such information as: name, month and year of birth, sex and survival status. For children who had died, information on age at death was solicited. The above information is analysed in the following sections to provide fertility levels and trends; fertility differentials by age, birth order, sex, residence, province and education; and limited measures of determinants. 3.2 Fertility Levels Table 3.1 gives the reported age-specific fertility rates for the three-year period preceding the survey per 1000 women. 1 The sum of the age-specific fertility rates (known as the total fertility rate) is a useful means of summarising the level of fertility. It can be interpreted as the number of children a woman would have by the end of her childbearing years if she were to pass through those years beating children at the currently observed rates. The general fertility rate represents the annual number of births in a population per 1,000 women age 15-44. The crude birth rate is the annual number of births in a population per 1,000 people. Both these measures are calculated using the birth history data for the three-year period before the survey and the age and sex distribution of the household population. The total fertility rate for the three years before the survey (representing early 1990 to early 1993) is 5.4 children per woman. The age pattem of fertility indicates that women in Kenya have children early in the childbearing period; by age 30, a Kenyan woman will have given birth to almost 60 percent of the children she will ever have. Table 3.1 and Figure 3.1 present fertility rates by urban-rural residence. These rates are higher in rural areas than in urban areas, a pattern that has persisted in various censuses and demographic surveys that have been carried out in the country. The total fertility rate is estimated at 5.8 in rural areas, about 70 percent ~Numerators of the age-specific fertility rates are calculated by summing the number of live births that occurred in the period 1-36 months preceding the survey (determined by the date of interview and the date of birth of the child), and classifying them by the age (in five-year groups) of the mother at the time of birth (determined by the mother's date of birth). The denominators of the rates are the number of woman-years lived in each of the specified five-year age gmups during the 1-36 months preceding the survey. 21 Table 3.1 Current fertility Age-specific and cumulative fertility rates and the crude birth rate for the three years preceding the survey, by urban-rural residence, Kenya 1993 Residence Age group Urban Rural Total 15-19 74 119 110 20-24 176 281 257 25-29 178 258 241 30-34 133 209 197 35-39 74 166 154 40-44 (34) 74 70 45-49 (21) 53 50 TFR 15-49 3.44 5.80 5.40 TFR 15-44 3.34 5.54 5.15 GFR 129 194 182 CBR 35.1 35.9 35.8 Note: Rates axe for the period 1-36 months preceding the survey. Rates for age group 45-49 may be slightly biased due to truncation. Rates in parentheses are based on fewer than 250 woman-yeaxs of exposure, TFR: Total fertility rate expressed per woman GFR: General fertility rate (births divided by number of women 15-44), expressed per 1,000 women CBR: Crude birth rate, expressed per 1,000 population Figure 3.1 Age-Specific Fertility Rates By Urban-Rural Residence Births per 1,000 Women 30o 2OO I I I I I 15-19 20-24 25-29 30-34 35-39 40-44 Age Group 45-49 KDHS 1993 22 higher than that in the urban areas (3.4). The difference in urban and rural fertility rates is particularly pronounced among women at older ages, when urban fertility rates are half those of rural women. 3.3 Fertility Differentials Table 3.2 and Figure 3.2 provide differentials in fertility by province and education. Western, Rift Valley, Nyanza and Eastern Provinces retain fertility rates that are above the national level. Nairobi and Central Province depict the lowest fertility levels. The total fertility rate in Westem Province (6.4) is almost twice the rate in Nairobi (3.4). Table 3.2 Fertility by background characteristics Total fertility rate for the three years preceding the survey and mean number of children ever born to women age 40-49, by selected background characteristics, Kenya 1993 Mean number of children Total ever born Background fertility to women characteristic rate 1 age 40-49 Residence Urban (3.44) 4.67 Rural 5.80 7.62 Province Nairobi (3.40) (4.26) Central (3.93) 6.89 Coast (5.25) 6.44 Eastern (5.89) 7.44 Nyanza (5.80) 7.69 Rift Valley (5.70) 7.91 Western (6.35) 7.86 Education No education (6.03) 7.58 Primary incomplete (6.18) 7.71 Primary complete (5.02) 6.83 Secondary+ (4.03) 4.99 Total 5.40 7.32 Note: Rates shown in parentheses indicate that one or more of the component age-specific rates is based on fewer than 250 woman-years of exposure. IRate for women age 15-49 years Female education apparently has a strong effect on fertility. Women with no education or only some primary school give birth to more than six children on average in their lifetime, compared to five children for women who completed primary school and four children for women with some secondary school. 23 Figure 3.2 Total Fertility Rate by Selected Background Characteristics RESIDENCE Urban Rural PROVINCE Nairobi Central Coast Eastern Nyanza R. Valley Western EDUCATION No Education Prim. Incomp. Prim. Comp. Secondary + 0 3.4 3.9 5.3 1 2 3 4 5 Total Fertility Rate 6,4 6 KDHS 1993 One way of examining trends in fertility over time is to compare the total fertility rates for the three years preceding the survey with the average number of children ever bom to women by the end of their childbearing period, age 40-49. The former is a measure of current fertility, while the latter is a measure of past or completed fertility. The data in Table 3.2 imply that there has been a decline of about two children over the past 10-20 years in Kenya. The decline has occurred across all the provinces and all education levels. 3.4 Fertility Trends Table 3.3 examines the trend in fertility in Kenya by comparing the results of the 1989 KDHS with those of earlier surveys. Fertility has declined from 8.1 births per woman in the mid-70s to 5.4 births for the period 1990-92. The decline has accelerated recently, with fertility dropping by 20 percent between 1984-88 and 1990-92. This is the most dramatic drop in fertility ever recorded in Kenya and one of the most dramatic recorded anywhere. As shown in Figure 3.3, the fertility decline has been experienced by women of all reproductive ages. Table 3.4 shows that, although all provinces in Kenya experienced a recent decline in fertility, some changed much more than others. The major declines--above 20 percent--in total fertility rates have been recorded in Central and Westem Provinces and in Nairobi. Central Province shows the largest decline in fertility, from a total fertility rate of 6.0 to 3.9 or a 35 percent decline. Meanwhile, fertility in Coast Province--traditionally an area of lower fertility--has hardly declined at all. 24 Table 3.3 Trends in current fertility rates Age-specific fertility rates and total fertility rates as reported in various surveys 1977/78 1984 1989 1993 KFS KCPS KDHS KDHS Agehime period 1975-77 1983 1984-88 1990-92 15-19 168 143 152 110 20-24 342 358 314 257 25-29 357 338 303 241 30-34 293 291 255 197 35-39 239 233 183 154 40-44 145 109 99 70 45-49 59 66 35 50 Total fertility rate 8.1 7.7 6.7 5.4 Note: The rates refer to the following periods prior to the survey: for 1977/78, a 3-ye~ period; for 1984, a 1-year period; for 1989, a 5-year period, and for 1993, a 3-year period. Sources: KFS--CBS. 1980, p. 87; KCPS--CBS. 1984, p. 50; 1989 KDHS--NCPD. 1989, p.18. Table 3.4 Trends in fertility by province Total fertility rates by province and percent change 1984-88 and 1990-92 1989 1993 KDHS KDHS Province/ Percent period 1984-88 1990-92 change Nairobi 4.6 3.4 -.26 Central 6.0 3.9 -.35 Coast 5.5 5.3 -.04 Eastern 7.0 5.9 -.16 Nyanza 7.1 5.8 -.18 Rift Valley 7.0 5.7 -.19 Western 8.1 6.4 -.21 Total 6.7 5.4 -.19 Note: Rates for the 1989 KDHS refer to the 5-year period prior to the survey, while those for the 1993 KDHS refer to the 3-year period prior to the survey. Source: NCPD. 1989, p. 22. Figure 3.3 Age-Specific Fertility Rates 1977/78 KFS, 1989 KDHS and 1993 KDHS Births per 1,000 Women 400 30o 2oo 100 ~ 0 I I I I I 15-19 20-24 25-29 30-34 35-39 40-44 Age Group 45-49 25 Table 3.5 shows trends in the percentage of women who reported that they were pregnant at the time of the interview, according to age group. The proportions show a steady decline, from 13 percent in 1977/78, to 11 percent in 1984, 9 percent in 1989, and 8 percent in 1993. The decline appears to have slowed somewhat between 1989 and 1993. Table 3.5 Percent pregnant Percentage of all women who are pregnant at the time of interview by age group as reported in various surveys 1977/78 1984 1989 1993 Age KFS KCPS KDHS KDHS 15-19 8 8 6.8 5.3 20-24 17 16 13.6 12.6 25-29 19 17 10.5 10.9 30-34 16 13 10.9 9.2 35-39 12 10 8.4 7.3 40-44 9 6 3.6 3.3 45-49 3 2 2.2 1.1 Total 13 11 8.9 8.2 Sources: KFS--CBS. 1980, p. 88; KCPS--CBS. 1984, p. 53; 1989 KDHS--NCPD. 1989, p. 21. Table 3.6 provides further insights into the apparent fertility decline documented above. The table gives the age-specific fertility rates for four-year periods preceding the survey, using data from respondents' birth histories. Figures in brackets represent partial fertility rates due to truncation; women 50 years of age and older were not included in the survey and the further back into time rates are calculated, the more severe is the truncation. For example, rates cannot be calculated for women age 45-49 for the period 8-11 years before the survey, because those women would have been over age 50 at the time of the survey and were not interviewed. It should also be noted that misreporting of the date of birth of children can result in the appearance of false trends in fertility. The data show declining fertility experienced by women in all age groups during the last two decades. Table 3.6 Age-specific fertility rates Age-specific fertility rates for four-year periods preceding the survey, by mother's age at the time of birth, Kenya 1993 Number of years preceding the survey Mother's age 0-3 4-7 8-11 12-15 16-19 15-19 118 143 166 184 187 20-24 266 312 333 353 334 25-29 256 304 333 342 [3441 30-34 204 268 281 325 [330] 35-39 152 195 [242] [303] 40-44 73 [141] [(245)] 45-49 [501 Note: Age-specific fertility rates are per 1,000 women. Estimates enclosed in brackets are truncated. Parentheses indicate that the figure is based on fewer than 250 woman-years of exposure. 26 Table 3.7 presents fertility rates for ever-married women by duration since first marriage for four-year periods preceding the survey. It is analogous to Table 3.6, but is confined to ever-married women and replaces age with duration since first marriage. The data confirm that the decline in fertility is apparent for all marriage durations. Table 3.7 Fertility by marital duration Fertility rates for ever-married women by duration since Ftrst marriage in years, for four-year periods preceding the survey, Kenya 1993 Marriage duration at birth Number of years preceding the survey 0-3 4-7 8-11 12-15 16-19 0-4 354 390 390 406 386 5-9 273 337 360 374 367 10-14 239 288 315 347 324 15-19 179 241 283 284 I302] 20-24 115 163 I189] [335] 25-29 63 [931 Note: Duration-specific fertility rates are per t,000 women. Estimates enclosed in brackets are truncated. 3.5 Children Ever Born The distribution of all women and currently married women by age and number of children ever bom is presented in Table 3.8. The table also shows the mean number of children ever born to women in each five-year age group, an indicator of the momentum of childbearing. The table shows that 17 percent of women age 15-19 years have given birth to a child. This represents a decline from the level of 21 percent reported in the 1989 KDHS and probably reflects a gradual increase in age at marriage which has been reinforced by rising school enrolment at these ages. However, high fertility is apparent for women age 25 years and over. Women in their early thirties have given birth to an average of 4.5 children and those age 45- 49 report an average of 7.9 children. This same pattem is reflected by currently married women with the exception that the percentage of currently married women age 15-19 who have had children is of course high (59 percent) compared to all women age 15-19. The percentage of women aged 45-49 who have never had children provides an indicator of the level of primary infertility---the proportion of women who are unable to bear children at all. Voluntary childlessness is rare in Kenya, and married women with no births are most likely unable to bear children. The KDHS results suggest that primary infertility islow, about 1 percent. This is slightly lower than that recorded in the 1989 KDHS (about 2 percent). It should be noted that this estimate of primary infertility does not include women who may have had one or more births but who are unable to have more (secondary infertility). 27 Table 3.8 Chi ldren ever born and living Percent distribution of all women and of currently married women by number of chi ldren ever born (CEB) and mean number ever born and living, according to five-year age groups, Kenya 1993 Number of children ever born (CEIt) Number Mean no. Mean no. Age of of of living group 0 1 2 3 4 5 6 7 8 9 10+ Total women CEB children ALL WOMEN 15-19 83.2 13.6 2.8 0.5 0.0 0.0 0.0 0.0 0.0 0.0 0.0 100.0 1754 0.20 0.18 20-24 29.5 29.2 24.1 11.9 4.1 1.2 0.0 0.1 0.0 0.0 0,0 100.0 1638 1.36 1.25 25-29 5.8 10.3 21.0 21.6 21.0 13.I 4.8 2.0 0.4 0.1 0.0 100.0 1221 3.13 2.85 30-34 4.5 5.2 8.5 14.1 15.3 18.9 15.4 10.0 4.3 2.5 1.2 100.0 1088 4.53 4.06 35-39 2.5 1.5 3.4 5.8 11.1 14.8 17.1 13.0 13.8 9.0 8.0 100.0 768 6.13 5.45 40-44 2.7 3.1 3.6 4.5 7.8 8.5 9.7 13.0 13.7 14.1 19.2 100.0 638 6.95 6.11 45-49 1.1 2.6 4.1 2.4 5.1 6.6 9.1 11.2 14.3 12.8 30.8 100.0 434 7.87 6.72 Total 27.9 12.5 11.4 9.3 8.6 7.7 6.1 4.9 4.1 3.2 4.4 100.0 7540 3.17 2.82 CURRENTLY MARRIED WOMEN 15-19 41.0 42.9 14.3 1.9 0.0 0.0 0.0 0.0 0.0 0.0 0.0 100.0 261 0.77 0.65 20-24 11.0 30.7 31.8 17.8 6.6 2.0 0.0 0.1 0.0 0.0 0.0 100.0 937 1.85 1.71 25-29 2.5 7.7 19.6 23.5 22.9 15.2 5.7 2.3 0.4 0.1 0.0 100.0 1003 3.40 3.10 30-34 2.5 3.7 7.0 13.9 16.3 20.3 16.4 10.9 4.9 2.6 1.5 100.0 918 4.79 4.30 35-39 1.5 1.3 3.1 5.4 10.2 15.3 16.2 13.8 14.7 9.7 8.9 100.0 644 6.32 5.67 40-44 2.2 2.3 2.8 4.7 6.2 8.4 8.8 13.3 13.9 15.0 22.3 100.0 519 7.28 6.45 45-49 1.2 1.4 4.3 2.5 3.5 6.6 8.9 11.2 14.2 14.9 31.4 100.0 348 8.04 6.94 Total 6.1 11.6 13.9 13.0 11.9 11.3 8.4 6.9 5.7 4.7 6.4 100.0 4629 4.40 3.94 A comparison of the mean number of children ever born reported in the 1993 KDHS and various other surveys is presented in Table 3.9. Except for the data from the 1984 KCPS, which are uniformly higher than the other sources, 2 the figures show a steady decline in completed fertility over time. The one exception is the apparent rise in mean children ever born to women age 45-49 between the 1989 and 1993 KDHSs. It is unlikely that this is actually true; a more likely explanation is that for some reason the figure was either underreported in the 1989 survey, overreported in the 1993 survey or both. 3.6 Birth Intervals Table 3.9 Trends in chi ldren ever born Mean number of clfildren ever born by age group as retmrted in various surveys 1977/78 1984 1989 1993 Age KFS KCPS KDHS KDHS 15-19 0.4 0.4 0.3 0.2 20-24 1.8 2.0 1.6 1.4 25-29 3.8 4.0 3.5 3.1 30-34 5.6 5.7 5.0 4.5 35-39 6.8 7.0 6.5 6.1 40-44 7.6 7.8 7.4 7.0 45-49 7.9 8.2 7.6 7.9 Sources: KFS- CI~S. 1980, p. 84; KCPS--CBS. 1984, p. 45; 1989 KDHS- -NCPD. 1989, p. 24. Information on birth intervals provides insight into birthspacing patterns which have far-reaching impact on both fertility and child mortality levels. Research has shown that children born too close to a previous birth are at increased risk of dying at an early age. ~l'he KCPS is the only one of these surveys in which a complete birth history was not asked for each respondent; instead, the survey relied on summary data on the number of children ever born. Studies have shown that summary data produce higher estimates of cumulative fertility than birth histories (Central Bureau of Statistics, 1975 and 1977). 28 As shown in Table 3.10, one in four births occurs after an interval of less than 24 months, about 40 percent take place 24-35 months (two years) after the previous birth and one-third occur three years or more after the previous birth. A shorter median interval prevails for children whose preceding sibling has died, compared to those whose prior sibling is alive. This pattern presumably reflects early resumption of sexual intercourse, shortened breastfeeding period, and minimal use of contraceptives. Birth intervals have lengthened slightly over time; the median birth interval was 29 months for births occuring in the five years prior to the 1989 KDHS, compared to 30 months for the 1993 KDHS (data not shown). Table 3.10 Birth intervals Percent distribution of births in the five years preceding the survey by number of months since previous birth, according to demographic and socioeconomic characteristics, Kenya 1993 Number of months since previous birth Characteris6c 7-17 18-23 24-35 36-47 48+ Median number of Number months since of Total previous birth births Age of mother 15-19 11.1 36.7 35.2 9.6 7.3 100.0 24.3 64 20-29 10.7 18.3 43.5 17.2 10.3 100.0 28.6 2385 30-39 8.1 12.8 40.9 18.7 19.6 100.0 31.8 1923 40 + 7.5 13.2 31.7 23.7 23.9 100.0 34.7 505 Birth order 2-3 10.3 17.2 40.8 16.7 14.9 I00.0 29.4 1892 4-6 7.9 15.0 42.0 19.3 15.8 100.0 30.7 1823 7 + 9.8 15.0 40.4 19.5 15.3 100.0 30.5 1162 Sex of prior birth Male 9.3 16.2 41.2 17.9 15.4 100.0 30.3 2362 Female 9.3 15.5 41.1 18.8 15.3 100.0 30.0 2515 Survival of prior birth Living 7.2 15.8 42.1 19.1 15.7 100.0 30.6 4405 Dead 29.1 16.2 32.0 11.1 11.6 100.0 24.8 472 Residence Urban 12.4 17,1 30.3 18.4 21.9 100.0 30.8 522 Rural 8.9 15.7 42.5 18.4 14.5 100.0 30.1 4356 Province Nalrobi 14.5 17.7 27.4 17.7 22.6 100.0 32.0 171 Central 7.2 18.3 40.8 16.9 16.8 100.0 30.0 541 Coast 7.7 13.0 40.1 20.7 18.6 100.0 33.1 443 Eastern 6.1 15.2 44.0 18.6 16.1 100.0 30.6 988 Nyanza 13.7 15.2 39.8 17.8 13.6 100.0 29.4 832 Rift Valley 7.9 17.2 40.8 18.5 15.6 100.0 30.2 1074 Western 11.8 15.2 43.2 18.2 11.6 100.0 28.7 827 Education No education 9.8 13.3 34.8 23.3 18.9 100.0 32.8 1112 Primary incomplete 8.4 14.3 48.7 16.3 12.2 100.0 29.7 1644 Primary complete 9.6 19.1 40.4 17.6 13.3 100.0 28.8 1190 Secondary+ 10.0 17.5 36.5 17.0 19.0 100.0 30.9 931 Total 9.3 15.9 41.2 18.4 15.3 100.0 30.1 4877 Not~: Firs~order births are excluded. The interval for multiple births is the number of months since the preceding pregnancy that ended in a live birth. 29 3.7 Age at First Birth The age at first birth is a crucial demographic indicator that usually reflects age at first marriage, level of contraceptive use and pre-marital sexual exposure. Early initiation into childbearing is generally a major determinant of large family size and rapid population growth, particularly in countries where family planning is not widely practised. Moreover, bearing children at a young age involves substantial risks to the health of both the mother and child. Early childbearing also tends to restrict educational and economic opportunities for women. Table 3.11 presents the percent distribution of women by age at first birth according to current age. Childbearing begins early in Kenya, with the majority of women becoming mothers before they reach the age of 20. The median age at first birth is 19. Moreover, the data show that median age at first birth has remained around 19 years for all women, irrespective of their current age, with the possible exception of women age 20-24, for whom the median age is 19.8. The median age at first birth does not appear to have changed significantly since the 1989 KDHS (with medians mostly around 19). Table 3.11 Age at first birth Percent distribution of women 1549 by age at first birth, according to current age, Kenya 1993 Curtentage Women Median with Age at first birth Number age at no of first births <15 15-17 18-19 20-21 22-24 25+ Total women birth 15-19 83.2 1.4 10.6 4.8 NA NA NA 100.0 1754 a 20-24 29.5 4.4 23.5 24.3 14.0 4.4 NA 100.0 1638 19.8 25-29 5.8 5.3 28.4 24.9 18.3 12.7 4.6 100.0 1221 19.3 30-34 4.5 6.2 30.0 25.4 16.5 11.4 6.0 100.0 1088 19.0 35-39 2.5 9.6 29.5 23.4 17.6 11.2 6.3 100.0 768 19.0 40-44 2.7 10.4 27.2 21.1 17.9 12.9 7.7 100.0 638 19.0 45-49 1.1 8.4 26.1 24.0 15.1 11.6 13.8 100.0 434 19.3 NA = Not applicable aLess than 50 percent of the women in the age group x to x+4 have had a birth by age x Differentials in median age at first birth are shown in Table 3.12. The most notable differentials are that urban women start childbearing later than rural women; educated women--particularly those with secondary education--start childbearing later than those with no education; and women in Nyanza Province have the lowest median age at first birth (18.2). 30 Table 3.12 Median age at first birth Median age at first birth among women age 20-49 years, by current age and selected background characteristics, Kenya 1993 Current age Background Ages Ages characteristic 20-24 25-29 30-34 35-39 40-44 45-49 20-49 25-49 Residence Urban a 20.7 20.0 19.7 21.0 (21.0) a 20.5 Rural 19.5 19.0 18.8 18.8 18.8 19.2 19.1 18.9 Province Nairobi a 20.4 (22.2) (18.5) (21.0) * a 20.6 Central a 19.7 19.5 19.9 18.9 19.5 19.7 19.6 Coast a 19.2 19.0 18.6 19.2 21.3 19.4 19.1 Eastern 19.8 19.6 19.1 19.1 18.9 18.9 19.3 19.2 Nyanza 18.6 18.0 18.2 18.4 18.3 19.1 18.3 18.2 Rift Valley 19.7 19.4 18.6 18.7 19.1 20.0 19.3 19.0 Western 19.6 19.2 19.2 18.6 19.2 17.9 19.2 18.9 Education No education 18.2 17.2 18.0 18.0 18.3 19.1 18.2 18.2 Primary incomplete 18.4 18.1 18.3 18.9 18.6 18.8 18.4 18.4 Primary complete 19.6 19.2 19.2 18.8 20.4 19.7 19.4 19.3 Secondary+ a 20.9 20.7 21.5 22.4 * a 21.1 Total 19.8 19.3 19.0 19.0 19.0 19.3 19.3 19.1 Note: The medians for cohort 15-19 could not be determined because half the women have not yet had a birth. aMedians were not calculated for these cohorts because less than 50 percent of women in the age group x to x+4 have had a birth by age x. Numbers in parentheses are based on 25-49 women; an asterisk indicates that the figure is based on fewer than 25 women and has been suppressed. 3.8 Teenage Fertility Early childbearing, particularly among teenagers (those under 20 years of age) has diverse negative demographic, socioeconomic and sociocultural consequences. Teenage mothers suffer most from severe complications during delivery, their socioeconomic advancement, such as educational attainment and accessibility to better job opportunities, is curtailed, and socially---especially if they are not married---~ey arc more likely to become outcasts and be relegated to ineffective roles in society. Table 3.13 shows the percentage of teenagers age 15-19 who arc mothers or pregnant with their first child, according to various background characteristics. Seventeen percent of teenage women arc mothers and another 4 percent arc pregnant with their first child. This represents a decline in teen childbearing--the 1989 KDHS showed that 21 percent of women 15-19 were already mothers. 31 Table 3.13 Teenage pregnancy and motherhood Percentage of teenagers 15-19 who are mothers or pregnant with their first child, by selected background characteristics, Kenya 1993 Percentage who are: Percentage who have Pregnant begun Number Background with first child- of characteristic Mothers child bearing teenagers Age 15 3.4 1.8 5.2 302 16 3.1 2.5 5.6 373 17 10.5 3.5 14.1 370 18 27.7 5.9 33.6 391 I9 39.5 4,4 43.9 318 Residence Urban 14.0 3.3 17.3 275 Rural 17.3 3.8 21.1 1479 Province Nairobi 15.5 3.4 19.0 80 Central 13.6 2.0 15.6 242 Coast 13,2 3.8 17.0 173 Eastern 18.0 1.8 19.8 296 Nyanza 21.6 6.4 28.0 299 Rift Valley 15.6 3.9 19.5 367 Western 17.4 4.1 21.5 297 Education No education 22.1 7.8 29.9 73 Primary incomplete 17.3 3.0 20.3 587 Primary complete 19.5 4.6 24.2 719 Secondary+ 9.8 2.4 12.1 375 Total 16.8 3.7 20.5 1754 As expected, the proportion of women who have begun childbearing rises rapidly with age, from 5 percent of those age 15 to 44 percent of those age 19. Those residing in rural areas, those with less than secondary education and those residing in Nyanza and Western Provinces are also more likely than others to have begun childbearing. These differentials parallel the differentials documented earlier about patterns in current and cumulative fertility. 32 Whereas most teenage women who have begun childbearing have given birth only once, a small proportion have had two births. As shown in Table 3.14, only 3 percent of women age 15-19 have had two or more births. The proportion rises to 11 percent among women age 19. Table 3.14 Children born to teenagers Percent distribution of teenagers 15-19 by number of children ever born (CEB), Kenya 1993 Age 0 1 2+ Number of Mean children ever born number Number of of Total CEB teenagers 15 96.6 3.1 0.3 100.0 0.04 302 16 96.9 3.0 0.1 100.0 0.03 373 17 89.5 10.0 0.5 100.0 0.11 370 18 72.3 22.7 5.0 100.0 0.33 391 19 60.5 28.8 10.7 100.0 0.52 318 Total 83.2 13.6 3.2 100.0 0.20 1754 33 CHAPTER 4 FERTILITY REGULATION 4.1 Knowledge of Contraception Determining the level of knowledge of contraceptive methods and accessibility of services was a major objective of the KDHS, since knowledge of specific methods and of the places where they can be obtained is a precondition for their use. Information about knowledge of contraceptive methods was collected by asking the respondent to name ways or methods by which a couple could delay or avoid pregnancy. If the respondent failed to mention a particular method spontaneously, the interviewer described the method and asked if she recognised it. Eight modem methods---the pill, IUD, injection, vaginal methods (diaphragm, foam tablets, jelly), condom, female sterilisation, male sterilisation (vasectomy), and Norplant--were described, as well as three traditional methods--the calendar rhythm method, natural family planning (temperature or mucus method), and withdrawal. Other methods mentioned by the respondent, such as herbs or breastfeeding, were also recorded. For each method recognised, the respondent was asked if she knew of a source or a person from whom she could obtain the method. If she reported knowing about calendar rhythm or natural family planning, she was also asked if she knew a place or a person where advice could be obtained on how to use the method. The KDHS results indicate that almost all (96 percent) Kenyan women know at least one method of family planning (Table 4.1). Knowledge of methods is slightly higher among married women than among all women. This chapter will focus primarily on married women since they are at greatest risk of pregnancy. A high proportion of married women (97 percent) report knowing a modem method and 76 percent of them have some knowledge about a traditional method. The methods most widely known by married women are the pill (95 percent), injection (93 percent), and female sterilisation (87 percent), followed by the condom (85 percent) and IUD (80 percent). Male sterilis0tion and vaginal methods are known by just over 40 percent of women. Due to its availability only recently and on a limited basis, Norplant is the least widely known method (14 percent). Considering the traditional methods included in the questionnaire, calendar rhythm (67 percent) is more widely known than withdrawal (34 percent), natural family plarming (31 percent), or any other traditional method (11 percent); the latter consist mostly of herbs, abstinence and breastfeeding. It should be noted that for all methods, knowledge is higher among currently married women than among all women. Knowledge of sources for obtaining family planning methods is widespread in Kenya. Ninety-four percent of currently married women know a source for a contraceptive method and 56 percent know a place to get information about bow to use the rhythm or natural family planning methods. Most married women (90 percent) know of a source where they can obtain the pill, 88 percent know where to obtain injectables, 81 percent know a source for female sterilisation and 76 percent know a source for the IUD. More than three quarters know where to obtain condoms. It is encouraging to note that 41 percent of currently married women know a source for male sterilisation, while 40 percent know where to obtain vaginal methods. In summary, for modem methods, over 90 percent of the women who have heard of a method also know where to obtain it. 35 Table 4.1 Knowledge of contraceptive methods and source for methods Percentage of all women and currently married women who know specific contraceptive methods and who know a source (for information or services), by specific methods, Kenya 1993 Know method Know a source 1 Currently Currently Con/xaceptive All married All married method women women women women Any method 95.6 97.2 88.2 93.5 Any modern method 95.2 96.9 87.6 93.1 Pill 91.9 95.1 82.7 89.7 IUD 73,3 80.4 67.4 76.0 Injection 87.6 93.1 80.1 87.9 Diaphragm/foam/jelly 38.3 42.3 35.2 39.8 Condom 83.4 85.1 73.3 78.3 Female sterilisation 81.1 87.4 72.7 80.9 Male sterilisation 41.3 45.4 36.9 41.4 Norplant 12.5 13.8 10.9 12.2 Any traditional method 71.9 75.9 51.8 55.6 Rhythrrffcounting days 64.2 66.7 48.6 52.0 Natural family planning 28.8 30.8 21.8 23.9 Withdrawal 29.5 33.6 NA NA Other traditional methods 9.3 11.2 NA NA Number of women 7540 4629 7540 4629 NA = Not applicable IFor modem methods, source refers to a place to obtain the method or procedure. For rhythm and natural family planning, refers to a place or person to obtain advice on practicing these methods. Trends in Knowledge of Methods and Sources Knowledge of family planning methods has increased considerably since the late 1970s. Table 4.2 shows comparable data for all women from the 1977/78 KFS, the 1984 KCPS and the 1989 and 1993 KDHSs. t While the level of knowledge of any method has increased only slightly (from 88 percent in 1977/78 to 96 percent in 1993), knowledge of many specific methods has increased more dramatically. For example, the proportion of women who have heard of contraceptive injections increased from 55 to 88 percent since 1977/78 and the proportion who have heard of condoms doubled from 40 to 83 percent. While some of the increase in knowledge of family planning methods occurred during the 1980s, there has been a large gain between 1989 and 1993, most notably in knowledge of condoms and male sterilisation. Knowledge of traditional methods has also become more widespread. ~AII four surveys used much the same techniques for probing knowledge of methods, however they included some different methods and used somewhat different terminology; for example, the 1977/78 KFS and the 1984 KCPS included douche, abortion, and abstinence, while the 1993 KDHS omitted these methods but included Norplant and natural family planning. 36 Table 4.2 Trends in knowledge of family planning methods and sources Percentage of women who know specific family planning methods and who know a source (for family planning information or services), Kenya, 1977/78, 1984, 1989, and 1993 Know method Know source 1977/78 1984 1989 1993 1989 1993 Method KFS l KCPS KDHS KDHS KDHS KDHS Any method 88.0 81.0 90.0 95.6 88.1 88.2 Any modern method 84.0 79.7 88.4 95.2 86.5 87.6 Pill 74.0 72.7 84.4 91.9 81.6 82.7 IUD 49.0 55.2 62.0 73.3 60.0 67.4 Injection 55.0 58.9 76.3 87.6 74.2 80.1 Diaphragm/foam/jelly 20,0 26.3 24.4 38.3 23.2 35.2 Condom 40.0 41.5 53.4 83.4 49.2 73.3 Female sterilisation 54.0 55.0 68.2 81.1 65.9 72.7 Male sterilisation 14.0 18.1 19.8 41.3 19.0 36.9 Any traditional method U 62.0 54.8 71.9 44.6 51.8 Rhythm 51.0 46.1 50.7 64.22 44.6 48.62 Withdrawal 24.0 24.6 16.8 29.5 NA NA Other U U 5. l 9.3 NA NA Number of women 8100 658l 7150 7540 7150 7540 NA = Not applicable U = No information 1Published data are presented in whole numbers; decimal was added to balance this table. 2Refers to calendar rhythm only, not to natural family planning Sources: KFS--CBS. 1980, p. 130, 132; KCPS--CBS. 1984, p.69; NCPD. 1989, p.29 Differentials in Knowledge of Methods and Sources KDHS data indicate that, in general, differences in knowledge of family planning methods by socioeconomic status or residence are minimal (see Table 4.3). Knowledge of any method is slightly lower among older women than younger women and the mean number of methods recognised is also lower (3.9 vs. 4.8). Urban women know slightly more methods on average than rural women. Provincial variations in contraceptive knowledge are rather small. The level of knowledge of family planning methods and places where they can be obtained increases with level of education; virtually all of the married women with secondary education know of a contraceptive method and can identify a source. Moreover, better educated women say they have heard of about 5 methods on average, compared to only about 4 methods for uneducated women. 37 Table 4.3 Knowledge of modern contraceptive methods and source for methods Percentage of currenfly married women who know at least one modem contraceptive method and who know a source (for information or services), by selected background characteristics. Kenya 1993 Mean Mean Know a Know no. of Know no. of source for Number Background any methods a modem modem modem of characteristic method known method 1 methods method women Age 15-19 98.1 4.8 97,0 3.7 89.6 261 20-24 97.8 4.7 97,5 3.5 94.1 937 25-29 98.1 4.7 98,1 3.5 95.6 1003 30-34 98.3 4.5 97,7 3.3 95.1 918 35-39 96.9 4.3 96.9 3.3 93.3 644 40-44 95.6 4.2 95,1 3.2 89.8 519 45-49 92.4 3.9 91,8 3.1 84.6 348 Residence Urban 98.5 4.8 98,3 3.5 95.7 697 Rural 97.0 4.4 96,6 3.4 92.6 3932 Province Nairobi 96.9 4.7 96,4 3.4 95.4 271 Central 99.8 4.7 99,8 3.4 97.1 610 Coast 94.6 4.3 933 3.2 85.7 445 Eastern 99.0 4.7 99,0 3.5 95.8 864 Nyanza 99.1 4.7 99,1 3.4 95,9 737 Rift Valley 92.9 4.1 92,1 3.1 87.4 992 Western 98.6 4.5 98,2 3.6 95.0 710 Education No education 91.5 3.8 90,3 3.0 81.9 1062 Primary incomplete 98,0 4.5 97,8 3.4 94.0 1411 Primary complete 99.2 4.8 99,2 3.6 96.8 1177 Secondary+ 99.8 4.9 99,8 3.5 99.4 980 Total 97.2 4.5 96,9 3.4 93.1 4629 llncludes pill. IUD, injection, vaginal methods (foaming tablets/diaphragm/foam/jelly), condom, female sterillsation, and male sterilisation. 4.2 Ever Use of Contraception All women interviewed in the KDHS who said that they had heard of a method of family planning were asked if they had ever used it. Forty-six percent of Kenyan women of repmducfive age have used a method of family planning at some time and over one third have used a modem method (Table 4.4). The corresponding proportions among currently married women are 55 and 43 percent, respectively. Ever use is lowest among the youngest age group (15-19 years), rising to a peak among those age 25-34, and then dropping among older women. Twice as many married women have used modem methods as traditional methods (43 vs. 22 percent). The most widely ever-used methods are the pill (28 percent), rhythm (19 percent), injection (14 percent) and the IUD (10 percent). Only seven percent of married women have used the condom (for family planning 38 Table 4.4 Ever use o f contraception Among all women and currently married women, the percentage who have ever used a contraceptive method, by specific method, according to age, Kenya 1993 Modern method Traditional method Any Dia- Female Male Natural modem phragm/ steri- steri- Any Rhythm/ fatal- With- Number Background Any meth- lnjec- foam/ Con- lisa- lisa- No¢- trad. counting ly draw- of characteristic method od Pill IUD tion jelly dora tioga tion plant method days planning al Other women ALL WOMEN 15-19 15.2 6.9 3.4 0.5 0.7 0.2 3.2 0.1 0.0 0.2 10,4 9.5 0.3 1.0 0.5 1754 20-24 47.3 31.5 20.7 2.8 6,6 0.9 9.1 0.2 0.2 0.2 25.9 24.3 1.3 2.8 0.9 1638 25-29 63.0 50.0 37.0 9.1 14.9 2.0 9.9 1.8 0.1 0.1 23.7 20.1 1,8 4.0 1.8 1221 30-34 61.7 50.2 32.9 12.3 21.3 4.8 7.8 5.2 0.1 0.2 23.5 19.2 2.6 4.7 2.4 10~8 35-39 57.5 45.3 28.1 14.7 17.1 3.7 6.4 10.3 0.3 0.3 20.9 16.0 1.0 3,1 3.9 768 40-44 51.5 42.3 21.8 12.1 14.7 2.4 5.3 12.3 0.0 0.4 16.4 13.7 1.3 1.8 2.2 638 45-49 43.9 35.4 21.0 11.3 12.2 3.5 4.7 11.5 0.2 0.3 16.6 12.6 0.7 2.3 4.6 434 Total 45.6 34.0 21.9 7.2 10.8 2.1 6.8 3.9 0.1 0.2 19.8 17.0 1.3 2.8 1.8 7540 CURRENTLY MARRIED WOMEN 15-19 31.0 14.1 9.5 0.5 2.0 0.5 4.9 0.0 0.0 0.3 21.9 20.3 1.0 2.5 0.6 261 20-24 49.4 34.8 24.2 4.1 8.3 0.7 7.5 0,1 0.1 0.0 24.7 229 1.5 3.1 0.9 937 25-29 62.9 50.0 36.7 9.8 14.4 2.0 9.9 1.9 0.2 0.1 23.4 19.9 1.9 4.1 2.0 10~3 30-34 62.6 50.3 32.0 11.6 21.4 4.5 7.5 6.0 0.2 0.3 23.8 19,2 3.0 4.8 2.7 918 35-39 57.6 45,3 27.1 14.5 15.8 3.8 6.4 11.1 0.3 0.3 21.4 15.8 0.8 3.2 4.3 644 40-44 53.6 43.5 21.9 13.0 15.6 2.3 5,3 13.0 0.0 0.3 17.4 14.2 1.0 1.8 2.2 519 45-49 45.8 37.2 22.2 13.4 13.4 3.7 5.5 12.3 0.2 0.4 18.1 14.3 0.9 2.5 4.6 348 Total 55.2 42.6 27.6 9,8 14.1 2.6 7.3 5.5 0.l 0.2 22.3 18.8 1.7 3.4 2.4 4629 purposes), while 6 percent have used female sterilisation and 3 percent have used withdrawal and vaginal methods. Ever use of family planning methods has increased greatly over the last 15 years, as evidenced by the data in Table 4.5. In 1977/78, less than one third of all women age 15-49 reported having ever used a method of family planning, compared to 46 percent in 1993. Ever use of modem methods has tripled over the same time period, with greater use of the pill and injection accounting for the bulk of the increase, especially in the four years between 1989 and 1993. 4.3 Current Use of Contracept ion Results from the 1993 KDHS indicate that 33 percent of m arried women in Kenya are currently using family planning (see Table 4.6). More women are using modem methods (27 percent) than traditional methods (6 percent). Thus, modem methods account for 83 percent of overall contraceptive use. The most widely used contraceptive method is the pill (10 percent), followed by injection (7 percent), female sterilisation (6 percent), IUD (4 percent) and rhythm (4 percent). Less than one percent of married women use other methods such as condom, vaginal methods, Norplant, natural family planning and withdrawal. Other traditional methods---mostly abstinence, herbs and breastfeeding--are used by less than one percent of married women. 39 Table 4.5 Trends in ever use of family planning methods Percentage of women who have ever used specific family planning methods, Kenya, 1977/78, 1984, 1989, and 1993 Contraceptive 1977/78 1984 1989 1993 method KFS 1 KCPS 1 KDHS KDHS Any method 29.0 28.5 39.1 45.6 Any modern method 11.0 14.1 24.1 34.0 Pill 7.0 9.0 15.1 21.9 IUD 2.0 4.0 6.8 7.2 Injection 2.0 2.0 5.5 10.8 Diaphragm/foam/jelly 1.0 1.0 1.8 2.1 Condom 3.0 2.0 3.6 6.8 Female sterilisation 1.0 2.0 3.8 3.9 Male sterilisation 0.0 0.0 0.2 0.1 Any tradit ional method U U 21.9 19.8 Rhytlun/counting days 13.0 13,0 19.4 17,02 Withdrawal 4.0 4.0 2.4 2.8 Other traditional methods U U 2.7 1.8 Number of women 8100 6581 7150 7540 U = No information tpublished data are presented in whole numbers; decimal was added to balance this table. ;~Refcrs to calendar rhythm only, not to natural family planning Sources: KFS--CBS. 1980, p. 130, 132; KCPS CBS. 1984, p. 78, 83; 1989 KDHS--NCPI). 1989, p.33. Table 4.6 Current use of contraception Percent distribution of all women and of currently married women by contraceptive method currently used, according to age, Kenya 1993 Modern method Traditional method Natural Any Dia- Female Rhythm fatal- Not modem phragm/ steri- Any count- ly With cur- Number Background Any meth- Injec- foam/ Con- lisa- Nor- trad. ing plan- draw- rently of ch~racteris6c method od Pill IUD tinn jelly dora tkm plant method days ning al Other using Total women ALL WOMEN 15-19 5.7 2.4 1.4 0.1 03 0.0 0.4 0.1 0.0 3.3 3.0 0.0 0.2 0.0 94.3 100.O 1754 20-24 23.0 16.2 9.7 1.3 3.6 0.0 1.4 0.2 0.0 6.7 63 0.2 0.1 0.1 77.0 100.0 1638 25-29 37.5 31.5 16.5 3.6 8.3 0.0 1.2 1.8 0.0 6.0 4.9 0.2 0.3 0.5 62.5 100.0 1221 30-34 38.3 32.2 8.9 5.2 11.5 0.1 l.I 5.2 0.0 6.2 4.9 0.4 0.3 0.6 61.7 100.0 1088 35-39 34.6 30.4 5.5 6.0 7.6 0.3 0.7 10.3 0.0 4.2 2.7 0.2 0.4 1.0 65.4 1130.0 768 40-44 34.2 29.4 4.8 4.5 7.0 0.1 0.8 12.3 0.0 4.9 3.4 0.3 0.6 0.6 65.8 100.0 638 45-49 26.7 22.3 1.8 3.2 5.2 0.0 0.5 I 1.5 0.0 4.4 3.1 0.0 0.0 1.3 73.3 leO.0 434 Total 25.9 20.7 7.5 2.8 5.5 0.1 0.9 3.9 0.0 5.2 4.3 0.2 0.3 0.4 74.1 leO.0 7540 CURRENTIN MARRIED WOMEN 15-19 10.3 6.1 4.6 0.0 0.8 0.0 0.4 0.0 0.3 4.1 3.0 0.0 1.1 0.0 89.7 1{30.0 261 20-24 23.6 18.3 11.5 1.8 4.0 0.0 08 0.1 0.0 5.3 4.9 0.2 0.2 0.0 76.4 lO0.O 937 25-29 37.2 31.5 17.0 3.9 7.6 0.0 11 1.9 0.0 5.7 4.5 0.3 03 0.5 62.8 100.0 1003 30-34 39.7 33.2 8.8 5.6 [1.9 0.0 0.9 6.0 0.1 6.5 5.0 0.4 0.3 0.7 60.3 100.0 918 35-39 35.9 31.6 5.2 7.0 7.3 0.3 0.7 11.1 0.0 4.3 2.5 0.2 0.4 1.2 64.1 I00.0 644 40-44 37.3 31.9 5.0 5.1 7.7 0.l 03 13.0 0.0 5.5 3.8 03 0.7 0.7 62.7 1130.0 519 45-49 30.4 24.9 2.2 4.0 5.7 0.0 0.7 12.3 0.0 5.5 3.8 0.0 0.0 1.7 69.6 1(20.0 348 Total 32.7 27.3 9.5 4.2 7.2 0.1 0.8 5.5 0.0 5.5 4.2 0.2 0.4 0.6 67.3 100.0 4629 40 The use of contraception increases steadily up through age group 30-34 and declines thereafter. The pill and calendar rhythm are the most commonly used methods among women age 15-24. There is a gradual shift to longer-term methods among older women, so that by age 25-29, injection has replaced rhythm as the second most popular method; by age 30-34, it is the most popular method. Above age 35, female sterilisation is the most widely used method, with the injection in second place. One in eight (12-13 percent) married women in their forties has been sterilised. Trends in Current Use of Family Planning Current use of family planning has shown a steady increase over the past nine years, from 17 percent of married women in 1984 to 33 percent in 1993 (see Table 4.7 and Figure 4.1). 2 Moreover, there has been a radical shift to greater use of modem methods. In 1984, 10 percent of married women were using modem methods, compared to 27 percent in 1993. Use of contraceptive injections has experienced a particularly steep increase, from less than one percent of married women in 1984 to 7 percent in 1993. Use of the pill has tripled and female sterilisation has doubled over the past 9 years, while IUD use showed more modest increases. Table 4.7 Trends in current use of family planning methods Percentage of currently married women age 15-49 who are currently using specific family planning methods, Kenya, 1984, 1989, and 1993 Contraceptive 1984 1989 1993 method KCPS KDHS KDHS Any method 17.0 26.9 32.7 Modern method 9.7 17.9 27.3 Pill 3.1 5.2 9.5 IUD 3.0 3.7 4.2 Injection 0.5 3.3 7.2 Diaphragm/foam/jelly 0.1 0.4 0.1 Condom 0.3 0.5 0.8 Female stefilisation 2.6 4.7 5.5 Male sterilisation 0.0 0.0 0.0 Any traditional method 7.3 9.0 5.5 Rhythm/counting days 3.8 7.5 4.41 Withdrawal 0.6 0.2 0.4 Other traditional methods 2.9 1.3 0.6 Number of women 4627 4765 4629 llncludes calendar rhythm and natural family planning Sources: KCPS--CBS. 1984, p. 85, 86; 1989 KDHS--NCPD. 1989, p. 35. 2In 1977/78, 7 percent of married women were using family planning (CBS. 1980, p. 133); data from the KFS regarding use of specific methods are not tabulated in a form that is readily comparable with data from the other surveys and thus are not shown in Table 4.7. 41 Figure 4.1 Trends in Contraceptive Use Currently Married Women 15-49 KDHS 1989 and KDHS 1993 Any Method Any Modern Method Any Traditional Method Pill IUD Injection Condom Female Sterilisation Periodic Abstinence 2~ F 8 10 20 30 Percent Using Method 40 Use of traditional methods declined sharply between 1989 and 1993. This was almost entirely due to a decrease in use of the rhythm method. There is reason to believe that some of the apparent decline is due to questionnaire design. In the 1989 KDHS, the term periodic abstinence was used to describe any method in which sexual intercourse was intentionally avoided on the days of the woman's menstrual cycle on which she thought she was most likely to be fertile. A sizeable proportion of women who reported that they were using periodic abstinence were actually either not sexually active in the month before the survey, abstaining after a birth, or amenorrhoeic. This implies that there was some confusion betweenperiodic abstinence and long-term or postpartum abstinence. In an attempt to avoid this problem, the 1993 KDHS questionnaire used the term rhythm~counting days to describe the calendar rhythm method. (The survey also introduced a separate category, "natural family planning" to describe the temperature and vaginal mucus methods of determining the fertile time.) To the extent that this modification reduced confusion of periodic with longer- term abstinence, it may account for some or all of the apparent decline in use of this method. Differentials in Current Use of Family Planning Table 4.8 and Figure 4.2 show the level of contraceptive use among currently married women by selected background characteristics. The table indicates that some women are much more likely to be using contraceptives than others. The level of contraceptive use is much higher in urban areas (43 percent) than rural areas (31 percent). The most popular methods among urban women are the pill, the IUD, and injection, while the most popular methods among rural women are the pill, injection and female sterilisation. 42 Table 4.8 Current use of family planning by method Percent distribution of currently married women by contraceptive method currently used, according to selected background characteristics, Kenya 1993 Any modem Background Any mcth- characterls6c method od Modern method Traditional method Natural Dia- Female Any farni- Not phragm/ steri- trad. Rhythm/ ly With- cut- Number Injec- foam/ Con- lisa- meth-countingplan- draw- rently of Pill IUD tinn jelly dora tinct od days ning al Other using Total women Residence Urban 43.4 37.9 15.7 9.5 6.2 0.0 1.3 5.2 5.5 4.6 0.7 0.2 0.0 56.6 100.0 697 Rural 30.9 25.4 8.4 3.2 7.4 0.1 0.8 5.6 5.4 4.1 0.2 0.4 0.7 69.1 100.0 3932 Province Nairobi 45,4 37,8 20A 9.7 4.6 0.0 1.0 2.0 7.7 6.6 0.5 0.5 0.0 54.6 100.0 271 Central 56.0 49,7 20.9 10.0 8.7 0.3 1.4 8.4 6.3 5.6 0.6 0.0 0.1 44.0 100.0 610 Coast 20,2 16.6 6.3 2.4 3.6 0.0 0.8 3,4 3,6 2.7 0.1 0.7 0.0 79.8 1(30.0 445 East~n 38.4 30.5 12.8 5.7 6.0 0.0 0.9 5.1 7.9 7.3 0.0 0.4 0.2 61.6 100.0 864 Nya~a 23.8 21.5 4.2 1.3 8.2 0.1 0.6 7.1 2.3 1.6 0.2 0.3 0.2 76.2 100.0 737 Rift Valley 27,8 21.0 4.3 2.0 7.9 0.0 0.7 5,9 6,9 4,7 0,3 0,7 1.3 72.2 100.0 992 Western 25.1 21.7 6.1 2.2 8.5 0.0 0.7 4,2 3,4 1,3 0,2 0,1 1.8 74.9 100.0 710 Education No education 19.5 15.3 2.9 1.1 5.4 0.0 0.3 5.7 4.2 2.6 0.0 0.4 1.2 80.5 100.0 IC62 Prima~y incomplete 27.9 22.7 6.8 2.5 7.3 0.0 0.5 5,4 5.2 3,8 0.1 0,5 0.8 72.1 100.0 1411 l~im sty complete 34.9 29,1 11.6 4.1 6.9 0.0 0.9 5.6 5.8 4.6 0.3 0.5 0.4 65.1 It0.0 1177 Secotadaty+ 51.6 44.9 17.9 10.0 9.4 0.2 1.9 5.5 6.7 6.0 0.6 0.1 0.1 48.4 1~.0 980 Number of living children 0 5.5 1.6 0.8 0.1 0,0 0.0 0.6 0.0 3.9 3.6 0.0 0.3 0.0 94.5 100.0 328 1 25.9 19.5 12.2 2.9 2.0 0.0 1.7 0.5 6.4 5.4 0,3 0.7 0.0 74.1 100.0 589 2 30.6 26.1 16.2 4.0 4.7 0.0 0.7 0.6 4.5 4.3 0.1 0.0 0.1 69.4 100.0 690 3 37.1 29.8 12.6 5.4 8.5 0,0 1.3 1.9 7.3 5.8 1.0 0.5 0.0 62.9 1430.0 668 4+ 37.7 32.5 7.1 4.7 9.8 0.1 0.6 tO.l 5.2 3.5 0.I 0.4 1.2 62.3 ICO.O 2353 Total 32.7 27.3 9.5 4.2 7,2 0.1 0.8 5.5 5.5 4.2 0.2 0.4 0.6 67.3 1~.0 4629 Note: Excludes Norplant There are large differences in levels of contraceptive use by province. Central Province has the highest level of current use (56 percent), followed by Nairobi (45 percent), and Eastern Province (38 percent). The contraceptive prevalence rate for the other provinces is below the national average. The pill is the most commonly used method in Nairobi and Central, Coast, and Eastern Provinces, while injection is the major method in the three western provinces--Rift Valley, Western and Nyanza. In all provinces, modem method use accounts for over 75 percent of all use. The largest differentials in current use of contraception are found for educational groups. Contraceptive use increases steadily with increasing level of education, from 20 percent of married women with no education to 52 percent of those with secondary education. The proportion of users who are using modem methods also increases with increasing level of education. Among women with no education, modem methods account for 78 percent of all use, compared to 87 percent for women with secondary education. Female sterilisation and injection are the favourite methods among women with no education, while injection and the pill are the favourite methods among women with some primary and completed 43 By Figure 4.2 Current Use of Contraception Selected Background Characteristics RESIDENCE Urban Rural PROVINCE / Na i rob i~ Central L. Coasl Eastern L - Nyanza R. Valley Western EDUCATION No Education Prim. Incomp. Prim, Comp. Secondary+ ~J~J J~ J~J~ 'T J~ J J~ J J~ J~43 ~ 45 ,~ 56 - -20 38 24 28 25 120 I 28 135 ] 52 10 20 30 40 50 60 Percent Using Any Method KDHS 1993 primary education. The pill, IUD and injection are favoured by those with secondary or higher education. Current contraceptive use increases with the number of children that a woman has, ranging from 6 percent among women with no children to 38 percent among those with four or more children. Table 4.9 shows data on contraceptive prevalence for the rural areas of 15 selected districts as well as for Mombasa. As mentioned above, these districts were selected because they are large in population size, most have been assigned a District Population Officer, and most were also targetted in the 1989 KDHS. The data should be viewed with caution, since the number of married women interviewed in many of the districts is small and the resulting figures are subject to higher sampling errors. It should also be noted that for the districts that were recently subdivided (i.e., Kakamega, Kericho, Kisii, Machakos, Meru, and South Nyanza), the former boundaries were used for the KDHS sample. Finally, except for Mombasa, the data for the individually targetted districts refer to rural women only. Of the districts studied, contraceptive prevalence is highest in Nyeri District; two thirds of the rural, married women in Nyeri District are using a family planning method (64 percent). This level is comparable to levels found in the most economically advanced developing countries and some developed countries. At the other end of the spectrum are rural South Nyanza (13 percent), Kilifi 04 percent) and Siaya (15 percent) Districts. Figure 4.3 shows trends in contraceptive prevalence rates for modem methods over the last four years for the rural areas of the districts that were targetted in both the 1989 and 1993 KDHSs. Extra caution is necessary in interpreting data on changes over time. Not only were the numbers of women interviewed in both surveys small, but they were also selected from independent samples and thus sampling errors are also independent. For this reason, for most districts, the contraceptive use rates in 1993 may not be significantly 44 Table 4.9 Current use of contraception by district Percent distribution of currently married women by contraceptive method currently used, according to selected districts. Kenya 1993 Any tandem Town/ Any meth- District method od Pill Modern method Traditional method Natural Diw Female Any fatal- Not ph'ngm/ steri- uad. Rhythm/ ly With- cur- Number Injec- foam/ Con- lisa- meth-countingplan- draw- rently of IUD tiota jelly d~n tion nd days ning al Other using Total women Mombasa 3 37.6 32.0 11.2 6.1 4.6 0.0 3.0 6.6 5.6 5.1 0.5 0.0 0.0 62.4 I00.0 94 Murang*a I 47.1 40.2 10.8 9.8 9.3 0.0 3.9 6.4 6.9 6.9 0.0 0.0 0.0 52.9 100.0 150 Nyeri I 64~2 60.3 18.1 12.3 15.2 0.0 2.9 11.8 3.9 2.9 0.5 0.0 0.5 35.8 100.0 97 Kilili ~ 13,8 10.3 3.0 0.9 3,0 0.0 0.0 3.4 3.4 3,0 0.0 0.4 0.0 86.2 100.0 199 Ta im Tavern I 33.7 28.7 11.9 3.1 10.6 0.0 2.5 0.6 5.0 3.7 0.0 1.2 0.0 66.2 I00.0 35 Maehakos 12 38.2 27.2 9.2 3.3 4.8 0.0 I.I 8.8 II.0 10.7 0.0 0.4 0.0 61.8 I00.0 355 Meru I 2 41.2 40.3 17.3 7.4 II.I 0.0 0.8 3.7 0.8 0.8 0.0 0.0 0.0 58.8 I00.0 259 Kisii I 2 40.3 37.9 5,5 1.7 16.2 0.0 1.7 12.8 2,4 1.7 0.0 0.3 0.3 59.7 100.0 274 Siaya ~ 15.2 10.9 2.3 0.4 4.7 0.4 0.0 3.1 4.3 3.5 0.4 0.0 0.4 84.8 100.0 124 South Nyanza I 2 12.8 11.3 3.6 0.5 3.6 0.0 0.0 3.6 1.5 0.5 0.5 0.5 0.0 87.2 100.0 232 Kericbo/23 26.4 23.6 2.4 0.0 13.9 0.0 0.0 6.7 2.9 1.9 0.5 0.5 0.0 73.6 100.0 172 Nakuru t 28.8 23.1 3.8 3.1 8.1 0.0 1.9 6,3 5.6 5.6 0.0 0.0 0.0 71.3 IC~.0 116 Nandi I 23.9 22.2 3.3 1.2 12.3 0.0 1.2 4.1 1.6 0.8 0.0 0.0 0.8 76.1 I00.0 99 Uasin Gishu 1 25.9 21.1 3.0 1.2 7.8 0.0 0.0 9,0 4.8 4.8 0.0 0.0 0.0 74.1 ICX).0 60 Bungoma I 20.8 16.9 3.9 0.8 8.2 0.0 0,4 3.5 3.9 1.2 0.0 0.4 2.4 79.2 100.0 180 Kakamega I 2 28.2 25.8 8.5 2.4 9.3 0.0 1.2 4.4 2.4 1.2 0,4 0.0 0.8 71.8 i00.0 334 ]Rural areas only 2Basnd on the fo~ner (undivided) boundaries of the district (see Chapter 1 for fuller explanation). ~Exclndes a tiny fraction of Norplant users Figure 4.3 Current Use of Modern Contraceptive Methods By District, KDHS 1989 and KDHS 1993 Murang 'a~ Nyer i~ Ma%; L~ Kisii ~ ' Siaya South Nyanza ~ Kericho Uasin Gishu Bungoma ~ Kakamega ~. , I M - - 0 10 20 30 40 50 Percent Using Modern Method 60 70 45 different (at a 95 percent level of confidence) from those in 1989, i.e., they may in fact be due to sampling errors. For example, in Meru District, 36 percent of rural married women interviewed in 1989 said that they were currently using family planning. The 95 percent confidence interval (within which the true prevalence rate could be said with 95 percent confidence to lie) for this figure ranged from 28 to 45 percent. In 1993, 41 percent of rural women in Meru District were using contraception; the 95 percent confidence intervals for this figure range from 34 to 49 (see Appendix Table B.14). Thus, since the intervals overlap, the apparent change from 36 percent in 1989 to 41 percent in 1993 cannot be said to be significant. Despite these cautionary notes, a number of points can be made. Prevalence of use of any method reportedly increased in the rural areas of every district studied except Machakos. The largest absolute increase was in Nyeri District, where the prevalence rate increased from 41 to 64 percent of married women. Even in districts in which the increase in overall prevalence was not large, the increase in use of modem methods was substantial (e.g., Machakos and Kisii Districts) (Figure 4.3). Finally, in terms of overall use, the districts are in roughly the same rank order in both surveys. 4.4 Number of Children at First Use Table 4.10 shows the number of living children at the time of first use of contraception among ever- married women. For the older cohorts (35-49 years), women generally started using contraception at higher parities than the younger women. For example, 21 percent of women aged 20-24 started using contraception after their first child, compared to only 5 percent of women 45-49. This probably reflects the fact that young women are more likely to use contraception to space births, while older women use it to limit births. Table 4.10 Number of children at first use of contraception Percent distribution of ever-married women by number of living children at the time of first use of contraception, according to current age, Kenya 1993 Number of living children at time Never of first use of contraception Number used of Current age contraception 0 1 2 3 4+ Missing Total women 15-19 68.4 20.1 9.9 1.0 0.0 0.0 0.6 100.0 284 20-24 48.3 14.9 20.9 10.5 3.2 1.4 0.8 100.0 1057 25-29 36.7 8.7 20.8 15.9 9.6 7.9 0.4 I00.0 1093 30-34 38.2 5.7 13.9 11.9 7.9 22.3 0.2 100.0 1030 35-39 43.0 2.7 8.6 5.9 7.6 31.6 0.6 100.0 748 40-44 48,5 2.4 5.9 4.0 5.4 32.7 1.1 100.0 627 45-49 56.1 1.9 4.9 4.6 4.6 27,7 0,2 100.0 422 Total 44.9 7.8 14.1 9.5 6.3 16.9 0.5 100.0 5260 4.5 Knowledge of Fertile Period A basic knowledge of reproductive physiology provides a useful background for successful practice of coital-related methods such as withdrawal, condom or barrier methods, but even more so for the calendar rhythm and natural family planning methods. The successful practice of these methods depends on an understanding of when, during the ovulatory cycle, a woman is most likely to conceive. Table 4.11 presents the percent distribution of all respondents and those who have ever used either the rhythm method or natural family planning by reported knowledge of the fertile period in the ovulatory cycle. 46 Table 4.11 Knowledge of fertile period Percent distribution of all women and of women who have ever used periodic abstinence by knowledge of the fertile period during the ovulatory cycle, Kenya 1993 Ever users Perceived All of periodic fertile period women abstinence t During menstrual period 2.3 3.3 Right after period has ended 32.6 34.8 In the middle of the cycle 20.0 29.0 Just before period begins 10.2 14.2 Other 1.4 1.7 Don't know 33.1 16.6 Missing 0.5 0.4 Total 100.0 100.0 Number 7540 1316 llncludes users of either calendar rhythm or natural family planning. One third of the women interviewed said a woman is most likely to conceive just after her period has ended, while the same proportion (33 percent) said they did not know when a woman is likely to conceive and 10peroentidentifiedthe fertile time tobejustbeforethe periodbcgins. Only2Opercentgavethecorrect response: that a woman is most likely to conceive in the middle of her ovulatory cycle. Women who have ever used either the calendar rhythm method or natural family planning are more knowledgable about the ovulatory cycle than women in general. Twenty-nine percent identified the fertile period as occurring in the middle of the cycle, and only 17 percent said they did not know when the fertile period occurred. It should be noted that the precoded response categories for this question are only one way of dividing the cycle into distinct periods. Women may actually have a more accurate understanding of their fertility cycles than is reflected by these categories, especially those who answered "right after her period has ended" (which could be interpreted as a correct response). However, it appears that over one third of all women and one fifth of those who have used periodic abstinence clearly do not understand the ovulatory process, since they either said they did not know when the fertile period is or they thought it occurred "during her period." 4.6 Timing of Sterillsation As mentioned above, more than I in 20 married women of reproductive age in Kenya has undergone a sterilisation procedure. This makes female sterilisation the third most popular contraceptive method after the pill and injection. Table 4.12 shows the distribution of sterilised women by the age at which they had the procedure, according to the number of years prior to the survey the procedure was done. The data show that the largest proportion--over one third---of sterilised women have the operation when they are in their early 30s, while almost the same proportion have the operation in their late 30s. The median age at sterilisation is 33. There does not seem to be any significant change in the recent past in the median age at which women have the operation. 47 Table 4,12 Timing of sterilisation Percent distribution of sterilised women by age at the time of sterilisation, according to the number of years since the operation, Kenya 1993 Age at time of sterillsation Number Years since of Median operation <25 25-29 30-34 35-39 40-44 45-49 Total women age I <2 6.6 19.6 35.9 20.0 9.7 8.2 100.0 86 32.5 2-3 4.9 11.6 32.6 37.6 13.3 0.0 100.0 61 34.3 4-5 1.8 25.4 32.7 28.5 11.7 0.0 100.0 54 32.2 6-7 (6.1) (25.8) (27.9) (32.3) (7.9) (0.0) 100.0 37 (32.7) 8-9 (0.0) (5.8) (48.6) (43.6) (2.0) (0.0) 100.0 25 (34.0) 10+ (5.3) (34.9) (42.9) (16.8) (0.0) (0.0) 100.0 29 Total 4.6 20.2 35.4 28.5 9.0 2.4 100.0 292 33.0 Note: Parentheses indicate that the figure is based on 25-49 women. IMedian age was calculated only for women less than 40 years of age to avoid problems of censoring. 4.7 Source of Supply In the KDHS, all current users of modem methods of family planning were asked to report the source from which they most recently obtained their methods. Since women often do not know exactly into which category the source they use falls (e.g. government hospital, mission health centre, etc.), interviewers were instructed to write the name of the source. Supervisors and field editors were instructed to verify that the name and the type of sources were consistent, asking cluster informants for the names of local family planning sources, if necessary. This practice was designed to improve the reporting of data on sources of family planning, although its actual effect is difficult to determine. The information in Table 4.13 and Figure 4.4 indicates that two thirds of women who use modem methods (68 percent) obtain their methods from public (government) sources, while 25 percent rely on private medical sources and 2 percent use other sources, such as shops or friends. Govemment hospitals are the single most frequently cited source, serving 30 percent of users, followed by government health centres (25 percent) and government dispensaries (14 percent). Private hospitals and clinics and facilities run by missions and churches each serve 8 percent of users. The source a woman uses to obtain contraceptive methods depends on many things, one of which is the type of method she may have chosen. Almost three quarters of pill users obtain their methods from public sources, mostly government health centres and hospitals; six percent obtain supplies from community-based distributors. Injections are also supplied mainly through government sources, with about one quarter supplied through the private sector. About two thirds of female sterilisations and IUD insertions are performed in govemment facilities, with one third occurring in private medical facilities. While condom users also rely heavily on government sources, many obtain supplies from pharmacies, shops and friends or relatives. The importance of various sources of contraceptives has not changed much since the 1989 KDHS, although modifications in the wording of the questionnaire hamper the comparison to some extent. 48 Table 4.13 Source of supply for modern contraceptive methods Percent distribution of current users of modem contraceptive methods by most recent source of supply, according to specific methods, Kenya 1993 Female All In jet- Con- sterili- modern Source of supply Pill 1UD tion dora sation methods Public 72.5 68.9 70.5 36.6 63.9 68.2 Government hospital 24.2 29.6 18.2 13.2 60.6 29.6 Government health centre 29.1 27.5 34.2 12.8 2.9 24.6 Government dispensary 19.1 11.8 18.2 10.6 0.4 13.9 Medical private 16.2 31.1 26.5 25.6 33.2 24.7 Mission/church hospital 4.5 5.6 8.8 2.4 15.1 7.7 FPAK clinic I 3.3 7.3 5.1 3.3 5.1 4.8 Other nongovernment service 0.4 0.6 1.6 0.0 0.9 0.8 Private hospital/clinic 4.5 11.6 8.8 3.3 11.2 7.8 Pharmacy 0.9 0.0 0.0 14.6 0.0 1.0 Privat~ doctor 2.6 6.0 2.2 2.0 0.9 2.6 Other private 2.5 0.0 0.0 21.9 0.0 1.9 Shop 0.0 0.0 0.0 9.2 0.0 0.4 Friends/relatives 2.5 0.0 0.0 12.7 0.0 1.5 Mobile clinic 1.0 0.0 1,8 1.9 0.4 1.0 Community distribution/ health worker 6.3 0.0 0.4 3.2 0.0 2.5 Other 0.6 0.0 0.3 0.0 0.0 0.3 Don't know 0.2 0.0 0.0 10.1 0.3 0.6 Missing 0.6 0.0 0.5 0.7 2.2 0.8 Total 100.0 100.0 100.0 100.0 100.0 100.0 Number 562 213 418 70 292 1560 Note: Total includes 4 users of foam tablets/jelly/diaphragm and 1 Norplant user. IFPAK = Family Planning Association of Kenya Figure 4.4 Percent Distribution of Current Users of Modern Methods by Most Recent Source of Supply Private Medical 25% CBD Workers 3% Other 5% uovernment Facilities 68% KDHS 1993 49 Women interviewed in the KDHS who were currently using a modem contraceptive method were asked how long it takes to travel from their home to the place where they obtain their method. Nonusers were asked if they knew a place where they could obtain a modem method and, if so, how long it would take to travel there. The results are presented in Table 4.14. Table 4.14 Time to source of supply for modem contraceptive methods Percent distribution of women who are currently using a modem contraceptive method, of women who are not using a modern method, and of women who know a method, by time to reach a source for family planning, according to urban-rural residence, Kenya 1993 Women who are currently Women who are not using Women who know a using a modem method a modem method contraceptive method Minutes to source Urban Rural Total Urban Rural Total Urban Rural Total Not applicable I 4.6 2.7 3.2 5.1 2.5 2.9 5.1 2.6 3.1 0-14 27.3 8.0 12.6 21.2 4.6 7.3 23.6 5.5 8.7 15-29 24.3 8.6 12.4 21.7 6.5 9.0 22.8 7.2 10.0 30-59 27.3 21.6 23.0 25.0 17.2 18.5 26.4 18.7 20.1 60 or more 14.2 57.8 47.3 9.4 50.3 43.8 10.9 53.9 46.1 Does not know time 1.1 1.0 1.0 1.8 0.9 1.0 1.7 0.9 1.1 Does not know source 0.0 0.0 0.0 15.1 17.6 17.2 8.7 10.7 10.4 Not stated 1.3 0.3 0.5 0.6 0.4 0.4 0.8 0.4 0.5 Total 100.0 100.0 100.0 100.0 I00.0 100.0 100.0 100.0 100.0 Median time to source 20.7 60.5 45.9 20.6 60.6 60.3 20.7 60.6 60.2 Number of women 376 t 184 1560 963 5017 5980 1301 5907 7208 IResponse was either "friends/relatives," "other," or "don't know." Among the women currently using a modem method, 25 percent are within 30 minutes (one-way travel time) of the place to which they go to get their method, while 23 percent are 30 minutes to one hour from their source. Almost half of users of modem methods are one hour or more from their source of supply. The median travel time for current users to reach their source is 46 minutes. As expected, urban users are generally closer than rural users to their supply sources; half of urban users are within 30 minutes of their supply sources, compared to one sixth of the rural users. Almost three fifths of the latter have to travel for one hour or more to get their supplies. Differences between the travel times reported by users and those reported by nonusers are not significant. This suggests that travel time to services is not a major barrier to use among Kenyan women. 4.8 Future Use To obtain information about potential demand for family planning services, all women who were not using contraception at the time of the survey were asked if they intended to use a method any time in the future. Table 4.15 shows the distribution of currently married women who were not using any contraceptive method at the time of the survey by their intention to use in the future, according to the number of living children. 50 Table 4.15 Future use of contraception Percent distribution of currently married women who are not using a contraceptive method by past experience with contraception and intention to use in the future, according to number of living children, Kenya 1993 Past experience with contraception and future intentions Number of living children I 0 1 2 3 4+ Total Never used contraception Intends to use in next 12 months 11.3 28.1 24.2 26.0 27.1 25.4 Intends to use later 16.9 11.3 8.4 7.7 3.8 7.0 Unsure as to timing 6,0 2.0 2.6 2.1 1.6 2.2 Unsure as to intention 12.3 7.5 7.0 6.1 5.2 6.4 Does not intend to use 31.6 24.8 22.9 21.7 26.4 25.4 Missing 0.4 0.0 0.2 0.0 0.1 0.1 Previously used contraception Intends to use in next 12 months 6.6 12.3 21.7 21.2 20.7 18.8 Intends to use later 5.1 6.3 4.5 4.0 3.0 3.9 Unsure as to timing 0.0 2.0 1.1 0.5 0.5 0.7 Unsure as to intention 0.2 0.9 0.8 1.9 1.6 1.3 Does not intend to use 9.8 4.9 6.3 8.7 9.6 8.3 Missing 0.0 0.0 0.4 0.3 0.4 0.3 Total 100.0 100.0 100.0 100.0 100.0 100.0 All currently married nonusers Intends to use in next 12 months 17.9 40.4 45.9 47.1 47.7 44.2 Intends to use later 22.0 17.6 12.9 11.7 6.8 11.0 Unsure as to timing 6.0 4.0 3.7 2.6 2.1 3,0 Unsure as to intention 12.5 8.3 7.8 8,0 6.8 7.8 Does not intend to use 41.3 29.6 29.2 30.3 36.1 33.7 Missing 0.4 0.0 0.5 0.3 0.5 0.4 Total 100.0 100.0 100.0 100.0 100.0 100.0 Number of women 226 406 512 423 1546 3113 llncludes current pregnancy. Almost three of five (58 percent) married nonusers say they intend to use family planning in the future, 44 percent within the next 12 months. One third of the women said they do not intend to use, while 8 percent are unsure. The proportion intending to use, and especially the timing of intended use, varies with the number of children. For example, the proportion who intend to use within the next 12 months is considerably lower among childless nonusers than among those with children, and the proportion who intend to use later is lower among women with four or more children. Looking at the relationship between previous use of family planning and intention to use in the future, those who intend to use in the future are more likely to have never used than to have used in the past. 51 4.9 Nonuse of Family Planning Reasons for Nonuse Table 4.16 presents the main reasons for not using family planning given by married nonusers who do not intend to use a contraceptive method in the future. One third of these women say they do not intend to use because of infecundity (either "difficult to get pregnant" or "menopausal"), while 22 percent cite the desire to have children as the reason. Other reasons given are side effects and other health concems (16 percent), opposition to family planning, either by the respondent, her husband, or someone else (8 percent), religion (7 percent), and lack of knowledge (5 percent). The younger cohort (under age 30) are more likely to say they do not to intend to use contraception in the future because they want more children, while those age 30 and over are more likely to cite reasons such as being menopausal or infecund. Table 4.16 Reasons for not using contraception Percent distribution of married women who are not using a contraceptive method and who do not intend to use in the future by main reason for not using, according to age, Kenya 1993 Age Reason for not using contraception 15-29 30-49 Total Wants children 38.8 15.1 22.1 Lack of knowledge 8,0 4.1 5.3 Partner opposed 6,2 3.0 3,9 Side effects 12.0 9.2 10.0 Fears sterility 2.3 1.1 1.5 Other health concern 4.2 4.1 4.2 Hard to get methods 0,4 0.1 0.2 Religion 5.3 7,1 6.6 Opposed to family planning 5.5 3.2 3.9 Fatalistic 1.5 1.0 1.2 Other people opposed 0.0 0.3 0.2 Infrequent sex 1.5 1.5 1.5 Difficult to get pregnant 7,0 28.3 22.0 Menopausal/had hysterectomy 0.6 16.8 12.0 Inconvenient 1.5 1,9 1.8 Other 2.5 2,1 2.2 Don't know 2.9 0,7 1.3 Missing 0.0 0,2 0.2 Total 100.0 100,0 100.0 Number 311 738 1049 Preferred Method Nonusers who said that they did intend to use family planning in the future were asked which method they preferred to use. Table 4.17 presents information on method preferences for currently married nonusers who say they intend to use in the future. The most popular method is injection (41 percent), followed by the pill (21 percent), and female sterilisation (13 percent). There is little difference in method preference according to timing of intended use, except that women who intend to use after 12 months and those who are unsure as to when they will use are more likely to be unsure of the method they will use. The method 52 Table 4.17 Preferred method of contraception for future use Percent distribution of currently married women who are not using a contraceptive method but who intend to use in the future by preferred method, according to whether they intend to use in the next 12 months or later, Kenya 1993 Intend to use In next After Unsure Preferred method 12 12 as to of contraception months months timing Total Pill 21.3 21.8 19.7 21.3 IUD 3.5 2.6 2.4 3.3 Injection 41.8 34.0 46.4 40.6 Diaphragm/foam/jelly 0.3 0.1 0.0 0.2 Condom 1.3 1.5 1.7 1.4 Female sterilisation 12.3 13.8 10.2 12.5 Norplant 1.7 2.0 0.0 1.6 Rhythm/counting days 3.2 2.0 2.4 2.9 Natural family planning 0.4 1.2 0.0 0.5 Withdrawal 0.3 0.0 0.0 0.2 Other 2.2 2.0 1.7 2.1 Unsure 11.7 19.0 15.5 13.3 Missing 0.1 0.0 0.0 0.2 Total 100.0 100.0 100.0 100.0 Number 1377 341 92 1812 preference has not changed since 1989, when nonusers who intended to use in the future indicated injection, pill and female sterilisation as their most preferred methods of contraception. 4.10 Exposure to Media Programmes on Family Planning Table 4.18 shows responses to a question on whether women have heard a family planning programme on the radio in the six months prior to the survey and if so, which one. Forty six percent of women have heard such a programme. Half of these women could not remember the name of the program they had heard. Of those who could remember the name, Panga Uzazi was by far the most widely heard programme. Differences by background characteristics are not large, except by education. More educated women are more likely to have heard a programme about family planning than less educated women. 53 Table 4.18 Heard family planning on radio Percentage of all women who have heard specific radio programs about family planning in the six months prior to interview, according to selected background characteristics, Kenya 1993 Name of program Maisha Kuclewa Ya Jifunze Ni Number Background Any Mwmda Panga Jamii Na Maisha Afya Daklari Kuzun- Do#t of charaeteristlc program Pole Uzazi Yako Ucndelea Bora Yako Akushauri gumza Other know women Age 15-19 42.5 1.3 I6.2 2.0 0.7 3.0 1.0 0.8 2.8 2.0 19.9 1754 20-24 50.3 3.0 18.8 2.8 0.9 3.4 1.7 1.1 5.2 1.4 22.9 1638 25-29 52.4 3.2 20.8 2.1 0.3 4.9 1.2 1.5 6.0 1.5 24.3 1221 30-34 48.9 2.0 18.5 2.2 0.8 3.5 1.9 3.0 4.5 1.2 22.7 1088 35-39 39.3 2.1 11.6 2.2 0.8 3.1 1.0 1.0 3.2 1.1 21.3 768 40-44 36.3 0.8 13.1 0.9 0.l 2.5 0.7 0.3 1.4 0.3 20.2 638 45-49 38.8 1.0 13.2 0.9 0.4 2.4 1.1 0.7 1.0 0.5 22.7 434 Res/dence Urban 49.9 2.4 16.9 3.6 0.9 2.9 1.1 2.4 8.3 1.2 22.8 1339 Rural 44.7 2.1 17.0 1.7 0.6 3.5 1.3 1.0 3.0 1.4 21.8 620l Provino~ Nairobi 45.5 1.9 12.5 4.1 0.5 2.7 1.9 2.7 7.1 0.8 21.5 507 Central 51.9 1.7 15.1 1.1 0.4 4.3 1.5 1.1 6.5 1.3 28.0 1094 Coast 32.8 1.7 12.5 1.7 0.9 2.9 0.9 1.1 4.2 0.8 12.9 717 Eastern 50.3 1.6 16.8 0.9 0.3 2.8 0.7 0.9 1.3 2.0 27.6 1406 Nyanza 44.2 3.4 24.7 3.2 1.4 5.3 2.5 1.9 4.3 1.6 14.0 1158 Rift Valley 40.7 2.5 15.8 2.1 0,6 3.1 0.6 1.0 2.4 1.6 19.7 1562 Western 50.6 1.7 17.3 2.7 0.3 2.2 1.6 1.1 4.7 0.6 26.7 1096 Education No education 24.7 0.3 8.3 0,9 0.2 1.4 0.4 0.2 0.8 0.6 14.2 1352 Primary incomplete 37.6 1.4 13.1 1.3 0.5 2.3 0.8 0.7 1.6 0.9 20.8 2179 Primary complete 50.8 2.3 19.6 2,1 0.7 3.6 1.6 1.1 3.7 1.4 24.5 2166 Secondary + 64.5 4.2 24.8 3,9 1.1 5.9 2.2 2.8 9.2 2.3 26.0 1844 Total 45.7 2.1 17.0 2,1 0.6 3.4 1.3 1.3 3.9 1.3 22.0 7540 4.11 Attitudes towards Family Planning Attitudes towards Family Planning for Youth In the KDHS, all women were asked if they thought that information about family planning or family planning services should be available for young people. Table 4.19 presents the percent distribution of women by their responses to these questions, according to background characteristics. Three quarters of women believe that family planning information should be available to young people, however, only half think that youth should be provided family planning services. Differentials by age and urban-rural residence are not large. It appears that women in Coast Province are more conservative than their counterparts in other provinces about making family planning information and services available to young people. Similarly, women with no formal education are least likely to approve of family planning information or supplies being available for Kenyan youth. 54 Table 4.19 Attitudes about family planning for youth Percent distribution of all women by whether they believe that family planning information and services should be available for young people by selected background characteristics, Kenya 1993 Believe information should be available Believe services should be available Number Background Don't Other/ Don't Other/ of characteristic Yes No know missing Total Yes No know missing Total women Age 15-19 71.0 21.4 7.2 0.4 100.0 47.8 42.6 9.1 0.5 100.0 1754 20-24 75.6 21.0 2.9 0.5 100.0 59.0 36.5 4.3 0.2 100.0 1638 25-29 76.3 19.8 3.3 0.6 100.0 56.2 38.5 4.4 0.9 100.0 1221 30-34 72.1 23.6 4.0 0.3 100.0 50.5 43.1 5.4 1.0 100.0 1088 35-39 70.7 23.7 5.3 0.3 100.0 47.5 45.5 6.7 0.3 100.0 768 40-44 72.5 21.3 5.5 0.8 100.0 51.5 41.5 6.1 0.9 100.0 638 45-49 66.8 26.0 7.0 0.2 100.0 43.7 44.7 10.9 0.6 100.0 434 Residence Urban 75.1 20.0 4.4 0.6 100.0 55.3 38.1 5.7 0.9 100.0 1339 Rural 72.4 22.3 4.9 0.4 100.0 51.3 41.7 6.5 0.5 100.0 6201 Province Nairobi 78.7 14.7 6.3 0.3 100.0 61.3 28.9 9.3 0.5 100.0 507 Central 81.4 15.3 2.6 0.8 100.0 59.3 36.4 3.8 0.5 100.0 1094 Coast 58.1 32.5 8.7 0.6 100.0 38.3 52.2 8.8 0.7 100.0 717 Eastern 78.6 17.3 3.9 0.2 100.0 62.9 32.8 4.4 0.0 100.0 1406 Nyanza 68.5 26.3 4.8 0.4 100.0 53.9 40.0 5.3 0.g 100.0 1158 Rift Valley 69.6 26.0 3.9 0.5 100.0 45.3 47.3 7.0 0.4 100.0 1562 Western 73.2 19.9 6.3 0.5 100.0 43.2 46.5 8.7 1.5 100.0 1096 Education No education 62.5 27.1 10.1 0.4 100.0 45.1 42.2 12.2 0.6 100.0 1352 Primary incomplete 70.0 23.9 5.7 0.4 100.0 50.8 41.4 7.3 0.5 100.0 2179 Primary complete 74.9 20.8 3.6 0.6 100.0 55.8 38.3 5.4 0.6 100.0 2166 Secondary + 81.5 16.8 1.4 0.3 100.0 54.2 42.9 2.2 0.8 100.0 1844 Total 72.9 21.9 4,8 0.5 100.0 52.0 41.0 6.4 0.6 100.0 7540 Approval of Family Planning An indication of the acceptability of family planning is the extent to which couples discuss the topic with each other. Table 4.20 indicates that, of married women who know a contraceptive method, roughly one third had never discussed family planning with their husbands in the year prior to the survey, one third bad discussed the topic only once or twice with their husbands, and one third had discussed family planning more often than once or twice. The tendency to discuss family planning with their husbands is greater among women in their 20s and 30s than among older or younger women. In order to obtain more direct information about the acceptability of family planning, respondents were asked if they approved or disapproved of couples using a method to avoid pregnancy. Although all women were asked this question, the data presented in Table 4.21 are confined to currently married women and exclude those women who had never heard of a contraceptive method. Currently married women were also asked if they thought that their husbands approved of the use of family planning. It should be noted that wives' opinions of their husbands' attitudes may be incorrect, either because they have misconstrued their husbands' true attitudes, or because of a tendency to report their husbands' attitudes as similar to their own. 55 Table 4,20 Discussion of family planning by couples Percent distribution of currently married women who know a contraceptive method by the number of times family planning was disctmsed with husband in the year preceding the survey, according to current age, Kenya 1993 Number of times family planning discussed Number Once or More of Age Never twice often Missing Total women 15-19 53.2 26,3 20.1 0.4 100.0 256 20-24 29.2 34.5 36.0 0,3 100.0 916 25 -29 25.1 31.6 43.1 0.1 100.0 984 30-34 30.4 29.8 39.6 0.0 100.0 903 35-39 35.1 29.0 35.5 0.0 100.0 624 40-44 41.2 32.0 26.4 0.0 100.0 496 45-49 55.1 16.4 28.1 0.1 I00.0 322 Total 33.9 30.1 35.7 0.1 100.0 4500 Table 4.21 Attitudes of couples toward famil~ planning Percent distribution of currently married women who know a contraceptive method by approval of family planning and by their perceplion of their husband's approval, according to selected background characteristics, Kenya 1993 Respondent Respondent approves disapproves Husband's Husband's Background Both Husband attitude is Husband attitude Both characteristic approve disapproves unknown approves unknown disapprove Missing Total Number Age 15-19 48.2 12.8 25.5 1.0 5.0 5.3 2,2 100.0 256 20-24 63.9 12.6 14.1 0.5 2,0 4,4 2.5 100.0 916 25-29 68.6 13.6 9.8 1.0 1.4 3.5 1,9 100.0 984 30-34 65.2 13.9 10.7 1.2 3.1 4.7 1.2 100.0 903 35-39 62.2 12.8 14.6 2.1 3.3 3.3 1.7 100.0 624 40-44 59.7 12.4 14,5 1,5 5.2 4.5 2.1 100.0 496 45-49 54.1 i2.0 15.7 1.0 5.6 9.9 1.7 100.0 322 Province Urban 74.0 8.1 9.7 0.9 2.1 3.1 2.1 100.0 686 Rural 60.9 14.0 14.0 1.2 3.2 4.8 1.8 100.0 3814 Region Nairobi 73.7 8.9 11.6 0.5 1,6 3.7 0.0 100,0 262 Central 72.9 10.2 6,5 1.6 2.2 3.7 2.9 100.0 609 Coast 48.8 11.1 18.7 1.3 7,7 10.8 1.7 100.0 421 Eastern 71.2 10.6 8.4 0.9 2.3 4.3 2.4 100.0 855 Nyanza 53.1 15.8 19.7 1.7 4.6 3.5 1.6 100.0 731 Rift Valley 62.5 12,9 13.0 1.5 2.3 5.1 2.7 100.0 922 Western 59.4 18.8 16.7 0.2 1.8 2.6 0.4 100.0 700 Education No education 44.1 16.6 20.6 1.6 6.0 9.0 2.2 100.0 971 Primary incomplete 57.9 14.3 16.9 1.4 3.4 4.4 1.8 100.0 1383 Primary complete 69.8 12,3 10.3 0.8 1.7 3.5 1.6 100,0 1168 Secondary+ 80.4 8.7 4.9 0,8 1.3 1.7 2.1 100.0 978 Total 62.9 13.1 13.4 1.2 3.1 4.6 1.9 100.0 4500 56 Overall, 89 percent ofm arried women who know a contraceptive method approve of family planning. Almost two thirds of the women say that their husbands also approve of family planning; 13 percent of women say that they approve of family planning and their husbands do not. Approval of family planning by married women does not vary much by age of the women except that women age 45-49 are less likely to approve than the younger cohorts. Married women who live in Coast Province and those who have no formal education are less likely than other women to approve of the use of family planning. They are also more likely than other married women not to know their husbands' attitudes towards family planning--another indication of the extent to which family planning is discussed among these couples. The proportion of wives who say they do not know their husbands' attitude towards family planning use is also high among women age 15-19. 4.12 Source of Family Planning Information In order to better assess where women learn about family planning, all women were asked how they first heard about family planning and from which place or person they leamed the most about family planning. Tables 4.22 and 4.23 show the percent distributions of women by these two sources, according to urban-rural residence and province. Friends and relatives are the most commonly reported first source of family planning information (31 percent), followed by health workers and clinics (29 percent). The radio was cited as a first source by one fifth of the women. Although friends and relatives are the most important first source of contraceptive information, more women said they got the most information from health workers and clinics (43 percent). Radio was cited as conveying the most information by 13 percent of women. These three sources were mentioned most often by women, regardless of their place of residence. Table 4.22 First source of family planning information Percent distribution of all women by source from which they first heard about family planning, according to urban-rural residence and province, Kenya 1993 Residence Province Rift Characteristic Urban Rural Nalrobi Central Coast Eastern Nyanza Valley Western Total Radio 26.3 19.0 29,4 12.4 18.3 10.2 26.0 24.7 25.8 20.3 Television 1.0 0.2 0.8 0,1 0.9 0.2 0.2 0.3 0.4 0.3 Newspapers 1.2 0,6 1.1 1.3 0.9 0.3 0.6 0.7 0.2 0.7 Posters 0.3 0.4 0.3 0.5 0.6 0.7 0.3 0.4 0.1 0.4 Husband 0.7 0.4 0.0 0.2 0.2 0.5 0.4 1.1 0.2 0.5 Friends/relatives 28,7 31.8 24.8 35.3 36,0 32.2 31.3 29.5 28,3 31.3 Health worker/clinic 23.3 29.8 23.2 33.3 25.6 34.9 26.6 23,7 29.9 28.7 Conununity distribution/ worker 2.2 3,2 2.7 1.5 4.3 3.1 2.9 4.0 2.4 3.0 Other 1.6 2.0 1.1 1.1 3.2 3,1 1.9 1.4 1.6 1.9 School/teacher 10.7 7.7 10.9 11.2 5.3 9.6 5.2 7,6 8.5 8.3 Church 0,2 0.4 0.3 0.4 0.1 0.7 0.6 0.1 0,1 0.3 Can't remember/ Don't know 3.5 4,4 5.2 2.8 4.2 4.4 3.8 6.5 2,5 4.3 Missing 0.3 0,0 0.3 0,0 0.4 0.0 0.0 0.2 0.0 0.I Total 100.0 100.0 I00.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Number 1339 6201 507 1094 717 1406 1158 1562 1096 7540 57 Table 4.23 Main source of family planning information Percent distribution of all women by source from which they got the most information about family planning, according to urban-rurnl residence and province. Kenya 1993 Residence Province Rift Chm'acleristic Urban Rural Nalxobi Central Coast Eastern Nyanza Valley Western Total Radio 16.2 12.7 14.7 8.2 13.7 5.9 16.7 19.7 14.8 13.4 Television 1.2 0.1 1.1 0.0 0.5 0.2 0.2 0.1 0.5 0.3 Newspapers 1.2 0.5 1.9 0.9 1.2 0.6 0.2 0.4 0.4 0.6 Posters 0.8 0.4 0.5 0.2 0.8 0.7 0,4 0.5 0.I 0.4 Husband 0.4 0.5 0,5 0.l 0.6 0.5 0,4 0.6 0.3 0.5 Friendsktelativas 21.0 24.2 21.5 19.0 27.6 24.8 25,5 22.8 24.3 23.6 Health worker/clinic 41.9 43.3 41.1 55.4 36.0 47.2 40,2 36.2 43.3 43.0 Community distribution/ worker 3.4 4.0 2.5 1.9 5.5 3.6 3,6 5.0 4.5 3.9 Other 1.8 2.4 2.2 2.5 3.4 3.5 1,7 1.7 1.6 2.3 School/teacher 8.3 6.7 9.0 8.0 5.9 7.8 5,8 6.4 6.7 7.0 Church 0.3 0.4 0.3 0.6 0.0 0.6 0,7 0.3 0.1 0.4 Can't remember/ Don't know 3.1 4.9 4.4 3.2 4.3 4.8 4,6 6.2 3.5 4.6 Missing 0.3 0.1 0.3 0.0 0.4 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 Number 1339 6201 507 1094 717 1406 1158 1562 1096 7540 4.13 Community-Based Distribution As mentioned in Chapter 1, the Kenyan family planning programme has put special emphasis on establishing a network of community-based distributors (CBDs) as one arm of the supply system. CBD workers have several functions. They provide family planning information, motivation and, in most cases, supplies to the women and men living in their catchment area. CBDs operate under the auspices of a number of organisations, both govemment and nongovemmental. They are usually provided with training, supplies and, in some cases, a small stipend. It is estimated that there are over 10,000 CBD workers in 37 of the (then) 41 districts (Lewis et al., 1992). With the aim of evaluating the coverage of the CBD programme, the KDHS interviewers briefly described to respondents what a CBD worker does and then asked if there were such a person in the respondent's area. If the answer was affirmative, the interviewer asked how often the CBD worker visited the respondent's home in the six months prior to the interview. The data are presented in Table 4.24. Only one fifth of women said that there was a CBD worker in their area and only I in 10 said she had been visited by a CBD worker in the past six months. There are several possible explanations for these low figures. Women may know CBD workers but be unaware of their role in the community for some reason. Presumably, CBD workers target women who are at higher risk of a dangerous or unwanted pregnancy and they may avoid talking to women who are not married, menopausal, sterilised, using another method, or openly opposed to family planning. Older women and those living in rural areas are more likely than other women to know of a CBD worker in their area and to have been visited in the six months before the survey. CBD workers are either more prevalent and/or better known to women in Western, Coast and Nyanza Provinces and are relatively unknown to women in Nairobi. 58 Table 4.24 CommunitT-based distribution Percent distribution of all women by presence of community-based family planning worker (CBD) in their area and if so, number of visits in the past six months according to selected background characteristics, Kenya 1993 Presence of CBD Percent visited in past 6 months Number Not Twice Background Don't of at or characteristic Yes No know Missing Total women all Once more Missing Total Age 15-19 13,5 71.9 14.4 0.1 100,0 1754 6.2 3.1 3.8 0.5 13.5 20-24 18.3 74.8 6.8 0.1 100,0 1638 8.3 4.3 5.7 0.1 18.3 25-29 22.1 75.1 2.8 0.0 100.0 1221 11.2 3.4 7.1 0,3 22.1 30-34 26.3 70.8 2.8 0.0 |00.0 1088 12.5 5.9 7.6 0.4 26.3 35-39 25.9 71,0 3.1 0.0 100.0 768 11,8 6.9 7.1 0.1 25.9 40-44 27.1 69.8 3,1 0.0 I00.0 638 12.9 4.1 9.3 0.8 27.1 45-49 22.1 74.1 3.8 0.0 100.0 434 12.1 2.6 6.9 0,5 22.1 Residence Urban 14.9 77.0 8.0 0.2 100.0 1339 6.3 2.9 5.1 0.6 14.9 Rural 22.0 71.8 6.2 0.0 100.0 6201 10.6 4.5 6.5 0.3 22,0 Province Nairobi 9.5 83.1 7.4 0.0 100.0 507 1.4 2.7 4.9 0,5 9.5 Central 20.6 71.6 7.8 0.0 100.0 1094 14.1 2.4 3.4 0.7 20.6 Coast 29.3 62.8 7.6 0.3 100.0 717 12.8 4.9 11.0 0.5 29.3 • Eastern 13.3 81.8 4.9 0.0 100,0 1406 4.8 3.7 4.5 0.3 13.3 Nyanza 24.0 71.1 4.9 0.0 1{30.0 1158 9.0 5.0 9.8 0.1 24.0 Rift Valley 15.8 79.9 4.1 0.1 100,0 1562 7.2 3.8 4.4 0.4 15.8 Western 33.3 55.6 11.1 0.0 100.0 1096 18.6 6.9 7.8 0.1 33.3 Education No education 18.1 77.1 4.7 0.0 100.0 1352 8.5 3.7 5.7 0.3 18.1 Primary incomplete 21.7 71.5 6.8 0.1 100.0 2179 10.5 4.9 5.9 0.3 21.7 Primary complete 21.7 70.8 7.4 0.1 100.0 2166 9.5 4.4 7.4 0.5 21,7 Secondary + 20.3 73.4 6.3 0.0 100.0 1844 10.5 3.7 5,8 0.3 20.3 Total 20.7 72.8 6.5 0.1 100.0 7540 9.8 4.2 6.3 0.4 20.7 59 CHAPTER 5 OTHER PROXIMATE DETERMINANTS OF FERTILITY 5.1 Introduction Addressed in this chapter are the principal factors, other than contraception, that affect a woman's risk of becoming pregnant: nuptiality and sexual intercourse, postpartum amenorrhoea and abstinence from sexual relations, and termination of exposure to pregnancy. While it is not by any means exact, marriage is an indicator of exposure of women to the risk of pregnancy, and is therefore important for the understanding of fertility. Populations in which age at marriage is low also tend to experience early childbearing and high fertility; hence, the motivation to examine trends in age at marriage. This chapter also includes more direct measures of the beginning of exposure to pregnancy and the level of exposure: age at first sexual intercourse and the frequency of intercourse. Measures of other proximate determinants of fertility are the durations of postpartum amenorrhoea and postpartum abstinence. 5.2 Marital Status Data on the marital status of respondents at the time of the survey are shown in Table 5.1. As in other reports on demographic surveys and censuses in Kenya, this report defines marriage to include informal unions. Although shown separately in Table 5.1, the categories of "married" and "living together" are combined in subsequent tables and are referred to as "currently married." Respondents who are currently married, widowed, divorced or no longer living together (separated) are referred to as "ever married." Table 5.1 shows that 30 percent of women of childbearing age in Kenya have never married, 61 percent are currently married, and 8 percent are either widowed, divorced or no longer living with a partner. The proportion who have never married falls sharply from 84 percent of women age 15-19 to 3 percent in the age group 45-49. The universality of marriage is evident from the fact that, among women age 35 and over, 97 percent are, or have been, married. Table 5.1 Current marital status Percent distribution of women by current marital status, according to age, Kenya 1993 Marital status Number Never Living Not living of Age married Married together Widowed Divorced together Total women 15-19 83.8 13.6 1.2 0.2 0.4 0.7 100.0 1754 20-24 35.5 54.1 3.1 0.7 2.2 4.4 100.0 1638 25-29 10.4 78.7 3.5 1.3 3.5 2.6 100.0 1221 30-34 5.4 79.5 4.8 2.8 3.9 3.6 100.0 1088 35-39 2.6 81.0 2.8 6.6 3.8 3.1 100.0 768 40-44 1.7 76.5 4.7 10.1 4.9 2.1 100.0 638 45-49 2.8 76.8 3.5 12.3 3.0 1.7 100.0 434 Total 30.2 58.3 3.1 3.1 2.7 2.6 100.0 7540 61 While the proportions widowed, divorced and separated are almost identical at 3 percent each, they show different patterns by age group. As expected, the proportion widowed increases with age of women; however, the proportions divorced and separated are more even across age groups. Table 5.2 shows the trend in the proportion of women reported as never married by age group from past censuses and surveys in Kenya. It is evident that the proportion of women under 30 years of age who have never married has been increasing. The 1993 KDHS data show an increase for the youngest age groups 15-19 and 20-24 since the 1989 KDHS. In the age group 15-19, the proportion of women who have never married rose from 80 percent in 1989 to 84 percent in 1993, while the proportion in the age group 20-24 rose from 32 percent in 1989 to 36 percent in 1993. Above age 25, there are no substantial changes in the proportions never married. Increased involvement of women in higher education may explain the increasing proportions of single women age 15-24. Table 5.2 Trends in proportion never married Percentage of women who have never married at the tinae of various surveys and censuses by age group, Kenya 1969 1977/78 1979 1984 1989 1993 Age census KFS cereus KCPS KDHS KDHS 15-19 64 72 71 74 80 84 20-24 18 21 25 24 32 36 25-29 6 4 9 6 t 1 10 30-34 4 1 5 4 5 5 35 -39 3 1 3 2 3 3 40-44 3 l 3 1 2 2 45 -49 3 0 2 1 2 3 Sources: 1969--CBS, 1970, p. 79; KFS--CBS, 1980, p. 71; 1979--CBS, 1981b, p. 24B; 1984--CBS, 1984, p. 40; 1989--NCPD, 1989, p. 9. 5.3 Po lygyny In the 1993 KDHS, the extent of polygyny in Kenya was measured by asking married women whether their husbands had other wives and, if so, how many. Table 5.3 shows the proportion of currently married women who are in polygynous unions according to age group and selected background characteristics. Overall, 20 percent of currently married women in Kenya are in polygynous unions. The practice is more common among older than younger women, with almost one-third of women in their 40s reporting that their husbands have other wives. The survey found that polygyny is more prevalent in the rural than urban areas. Overall, Coast Province has the highest proportion of polygnous unions (29 percent), followed by Western and Nyanza Provinces (26 percent each). Central Province has by far the lowest proportion of such unions (8 percent). The differences become even more pronounced by age group, although the number of cases is small and so the data should be viewed with caution. There is an inverse relationship between education and polygyny. The proportion of married women in polygynous unions decreases from 33 percent for women with no education to 11 percent for women with at least some secondary education. 62 Table 5.3 Polygyny Percentage of currently married women in a polygynous union, by age and selected background characteristics, Kenya 1993 Background Age of woman All characteristic 15-19 20-24 25-29 30-34 35-39 40-44 45-49 ages Residence Urban (11.0) I1.8 14.9 12.7 9.4 (28.0) (14.9) 13.7 Rural 18.1 12.7 15.3 20.6 25.6 29.9 30.8 20.5 Province Nairobi * 8.2 7.7 (10.3) * * * 11.2 Central * 4.2 3.7 9.3 0.8 13.8 18.0 7.5 Coast 22.4 12.4 25.0 32.0 47.9 (45.6) (34.6) 29.0 Eastern * 5.2 12.5 14.3 15.3 25.9 23.3 14.5 Nyanza 29.6 19.6 22.4 28.2 27.3 38.3 24.4 26.1 Rift Valley 10.0 14.1 16.0 16.3 26.6 27.8 32.6 19.3 Western (17.9) 19,6 18.3 25.0 30.8 38.5 (46.5) 26.4 Education No education * 23.7 31.1 33.2 39.4 33.3 33.5 33.3 Primary incomplete 20.9 12.3 18.2 20.4 21.2 29.7 29.8 20.2 Primary complete 15.4 11.1 8.6 15.6 11.7 23.8 (16.1) 13.0 Secondary+ (12.3) 11.3 11.5 10.0 8.0 (25.0) * 11.4 Total 17.2 12.5 15.2 19.4 23.7 29.7 29.4 19.5 Note: Rates shown in parentheses are based on 25-49 women, whereas an asterisk means the rate is based on fewer than 25 women and has been suppressed. Comparison of the 1993 KDHS data w

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