Kenya - Demographic and Health Survey - 1999

Publication date: 1999

World Summit for Children Indicators: Kenya 1998 _________________________________________________________________________________________________ BASIC INDICATORS Value _________________________________________________________________________________________________ Childhood mortality Infant mortality rate (adjusted rate) 74 per 1,000 Under-five mortality rate 112 per 1,000 Maternal mortality Maternal mortality ratio 590 per 100,000 Childhood undernutrition Percent stunted 33 Percent wasted 6 Percent underweight 22 Clean water supply Percent of households within 15 minutes of a safe water supply1 42 Sanitary excreta disposal Percent of households with flush toilets or VIP latrine 19 Basic education Percent of women 15-49 with completed primary education 52 Percent of men 15-49 with completed primary education 65 Percent of girls 6-12 attending school 85 Percent of boys 6-12 attending school 85 Percent of women 15-49 who are literate 83 Children in especially Percent of children who are orphans (both parents dead) 0.9 difficult situations Percent of children who do not live with their natural mother 15 Percent of children who live in single adult households 15 _________________________________________________________________________________________________ SUPPORTING INDICATORS _________________________________________________________________________________________________ Women's Health Birth spacing Percent of births within 24 months of a previous birth2 23 Safe motherhood Percent of births with medical antenatal care 92 Percent of births with antenatal care in first trimester 14 Percent of births with medical assistance at delivery 44 Percent of births in a medical facility 42 Percent of births at high risk 56 Family planning Contraceptive prevalence rate (any method, currently married women) 39 Percent of currently married women with an unmet need for family planning 24 Percent of currently married women with an unmet need for family planning to avoid a high-risk birth 20 Nutrition Maternal nutrition Percent of mothers with low BMI 12 Low birth weight Percent of births at low birth weight (of those reporting numeric weight) 9 Breastfeeding Percent of children under 4 months who are exclusively breastfed 17 Child Health Vaccinations Percent of children whose mothers received tetanus toxoid vaccination during pregnancy 90 Percent of children 12-23 months with measles vaccination 79 Percent of children 12-23 months fully vaccinated 65 Diarrhoea control Percent of children with diarrhoea in preceding 2 weeks who received oral rehydration therapy (ORS or sugar-salt-water solution) 69 Acute respiratory infection Percent of children with acute respiratory infection in preceding 2 weeks who were taken to a health facility or provider 57 _________________________________________________________________________________________________ 1 Piped, well, and bottled water 2 First births are excluded Kenya Demographic and Health Survey 1998 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 April1999 The report summarises the findings of the 1998 Kenya Demographic and Health Survey (KDHS), which was conducted by the National Council for Population and Development and the Central Bureau of Statistics. Macro International Inc. provided technical assistance. Funding was provided by the U.S. Agency for International Development (USAID/Nairobi) and the Department for International Development (DFID/U.K.). 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 on the Kenya survey may be obtained from the National Council for Population and Development, the Chancery, 4th Floor, Valley Road, Nairobi, Kenya (telephone: 711-600/1; fax: 710-281). Additional information about the DHS program may be obtained by writing to DHS, Macro International Inc., 11785 Beltsville Drive, Suite 300, Calverton, MD 20705, USA (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). 1999. Kenya Demographic and Health Survey 1998. Calverton, Maryland: NDPD, CBS, and MI. iii Contents Page Tables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ix Figures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xiii Foreword . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xv Executive Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xvii Map of Kenya . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xxii CHAPTER 1 INTRODUCTION Peter Thumbi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 1.1 Geography, History and Economy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 1.2 Population . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 1.3 Population and Family Planning Policies and Programmes . . . . . . . . . . . . . . . . . . . . . . 3 1.4 Health Priorities and Programmes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 1.5 Objectives of the 1998 Kenya Demographic and Health Survey . . . . . . . . . . . . . . . . . . 5 1.6 Survey Organisation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 1.7 Sample Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 1.8 Questionnaire . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 1.9 Training and Fieldwork . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 CHAPTER 2 CHARACTERISTICS OF HOUSEHOLDS AND RESPONDENTS Vane Nyong’a and George Bicego . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 2.1 Household Population . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 2.1.1 Age-Sex Composition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 2.1.2 Household Composition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 2.1.3 Educational Level of Household Members . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 2.1.4 School Enrolment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 2.2 Housing Characteristics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 2.2.1 Household Durable Goods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17 2.3 Characteristics of Survey Respondents . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17 2.3.1 Background Characteristics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17 2.3.2 Educational level of survey respondents . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 2.3.3 Reasons for Leaving School . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20 2.3.4 Access to Mass Media . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21 2.3.5 Women’s Employment Status . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23 2.3.6 Employer and Form of Earnings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24 2.3.7 Occupation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25 iv Page 2.3.8 Decision on Use of Earnings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26 2.3.9 Child Care While Working . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27 CHAPTER 3 FERTILITY LEVELS AND DIFFERENTIALS John Kekevole . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29 3.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29 3.2 Current Fertility . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29 3.3 Fertility Trends . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31 3.4 Children Ever Born and Living . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33 3.5 Birth Intervals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34 3.6 Age at First Birth . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35 3.7 Adolescent Fertility . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36 CHAPTER 4 FERTILITY REGULATION Karugu Ngatia, Zipora Gatiti, and Samuel Ogola . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39 4.1 Knowledge of Contraceptive Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39 4.2 Ever Use of Contraception . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41 4.3 Current Use of Contraceptive Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41 4.4 Trends at the National Level . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43 4.5 Differentials in Current Use by Background Characteristics . . . . . . . . . . . . . . . . . . . . . 47 4.6 Trends in Use of Contraception in Selected Districts . . . . . . . . . . . . . . . . . . . . . . . . . . 48 4.7 Number of Children at First Use of Contraception . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48 4.8 Knowledge of the Fertile Period . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49 4.9 Knowledge of Contraceptive Effects of Breastfeeding . . . . . . . . . . . . . . . . . . . . . . . . . 49 4.10 Timing of Female Sterilisation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50 4.11 Source of Family Planning Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51 4.12 Willingness to Pay for Pills . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52 4.13 Rates of Discontinuation within 12 Months of Use . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53 4.14 Intention to Use Family Planning Among Nonusers . . . . . . . . . . . . . . . . . . . . . . . . . . . 54 4.15 Reasons for Nonuse of Contraception . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55 4.16 Preferred Method of Contraception for Future Use . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56 4.17 Exposure to Family Planning Messages in the Electronic Media . . . . . . . . . . . . . . . . . 56 4.18 Acceptability of Use of Electronic Media to Disseminate Family Planning Messages . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57 4.19 Exposure to Family Planning Messages from Other Types of Media . . . . . . . . . . . . . . 59 4.20 Discussion about Family Planning between Spouses . . . . . . . . . . . . . . . . . . . . . . . . . . 60 4.21 Attitudes of Male and Female Respondents Toward Family Planning . . . . . . . . . . . . . 60 4.22 Family Planning for Youth . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63 4.23 Contact of Nonusers of Family Planning with Family Planning Providers . . . . . . . . . . 64 v Page CHAPTER 5 OTHER PROXIMATE DETERMINANTS OF FERTILITY Michael Mbaya . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67 5.1 Marital Status . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67 5.2 Polygyny . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68 5.3 Age at First Marriage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 70 5.4 Age at First Sexual Intercourse . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72 5.5 Recent Sexual Activity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73 5.6 Postpartum Amenorrhoea, Abstinence and Insusceptibility . . . . . . . . . . . . . . . . . . . . . 76 5.7 Termination of Exposure to Pregnancy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78 CHAPTER 6 FERTILITY PREFERENCES Dr. L.I.A. Ettyang . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79 6.1 Desire for More Children . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79 6.2 Need for Family Planning Services . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83 6.3 Ideal Family Size . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85 6.4 Wanted and Unwanted Fertility . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87 CHAPTER 7 EARLY CHILDHOOD MORTALITY George Kichamu . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89 7.1 Background and Assessment of Data Quality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89 7.2 Levels and Trends in Early Childhood Mortality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 90 7.3 Socioeconomic Differentials in Early Childhood Mortality . . . . . . . . . . . . . . . . . . . . . 91 7.4 Biodemographic Differentials in Early Childhood Mortality . . . . . . . . . . . . . . . . . . . . 93 7.5 High-Risk Fertility Behaviour . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 94 CHAPTER 8 MATERNAL AND CHILD HEALTH Jennifer Liku . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 97 8.1 Antenatal Care . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 97 8.3 Caesarean Section and Small Size at Birth . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 103 8.4 Vaccinations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 104 8.5 Acute Respiratory Infection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 107 8.6 Fever . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 108 8.7 Diarrhoea . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 110 CHAPTER 9 MATERNAL AND CHILD NUTRITION Maria Mosomi and John Owuor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 115 9.1 Breastfeeding and Supplementation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 115 9.1.1 Initiation of Breastfeeding . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 115 vi Page 9.1.2 Age Pattern of Breastfeeding . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 116 9.1.3 Types of Weaning Foods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 119 9.2 Nutritional Status of Children under Age Five . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 120 9.2.1 Measures of Nutritional Status in Childhood . . . . . . . . . . . . . . . . . . . . . . . . . 120 9.2.2 Levels of Child Malnutrition in Kenya . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 121 9.3 Nutritional Status of Mothers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 124 CHAPTER 10 AIDS AND OTHER SEXUALLY TRANSMITTED DISEASES Michael Muindi and George Bicego . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 127 10.1 Number of Sexual Partners . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 127 10.2 Payment for Sexual Relations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 130 10.3 Awareness of Sexual Transmitted Diseases . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 131 10.4 Self-reporting of Recent Sexual Transmitted Diseases . . . . . . . . . . . . . . . . . . . . . . . . 134 10.5 AIDS Knowledge and Awareness . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 136 10.6 Reported Ways to Avoid AIDS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 139 10.7 Perception of Risk of getting AIDS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 145 10.8 Behaviour Change . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 148 10.9 Source of Condom Supply . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 150 10.10 Use of Condoms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 152 10.11 Recognition of Trust Condoms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 154 10.12 Willingness to Pay for Condoms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 155 10.13 Testing for the HIV/AIDS Virus . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 156 CHAPTER 11 ADULT AND MATERNAL MORTALITY George Bicego and George Kichamu . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 161 11.1 The Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 161 11.2 Direct Estimates of Adult Mortality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 162 11.3 Direct Estimates of Maternal Mortality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 165 CHAPTER 12 FEMALE CIRCUMCISION Vane Nyong’a . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 167 12.1 Prevalence . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 167 12.2 The Decision to Circumcise Daughters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 170 12.3 Circumstances of the Procedure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 171 12.4 Reasons for Continuation or Discontinuation of Female Circumcision . . . . . . . . . . . 173 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 175 vii Page APPENDIX A SAMPLE DESIGN . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 177 APPENDIX B ESTIMATES OF SAMPLING DESIGNS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 183 APPENDIX C DATA QUALITY TABLES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 199 APPENDIX D PERSONS INVOLVED IN THE 1998 KENYA DEMOGRAPHIC AND HEALTH SURVEY . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 207 APPENDIX E QUESTIONNAIRES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 211 ix Tables Page Table 1.1 Basic demographic indicators, Kenya 1969, 1979, and 1989 censuses . . . . . . . . . . . . 2 Table 1.2 Results of the household and individual interviews . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 Table 2.1 Household population by age, residence and sex . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 Table 2.2 Population by age from selected sources . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 Table 2.3 Household composition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 Table 2.4 Fosterhood and orphanhood . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 Table 2.5 Educational level of the female household population . . . . . . . . . . . . . . . . . . . . . . . . 13 Table 2.6 School enrolment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 Table 2.7 Housing characteristics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16 Table 2.8 Household durable goods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17 Table 2.9 Background characteristics of respondents . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18 Table 2.10 Level of education . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20 Table 2.11 Reasons for leaving school . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21 Table 2.12 Access to mass media . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22 Table 2.13 Employment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24 Table 2.14 Employer and form of earnings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25 Table 2.15 Occupation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26 Table 2.16 Decision on use of earnings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27 Table 2.17 Child care while working . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28 Table 3.1 Current fertility . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29 Table 3.2 Fertility by background characteristics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30 Table 3.3 Trends in fertility . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31 Table 3.4 Trends in fertility by province . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32 Table 3.5 Age-specific fertility rates . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32 Table 3.6 Fertility by marital duration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32 Table 3.7 Children ever born and living . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33 Table 3.8 Birth intervals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34 Table 3.9 Age at first birth . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35 Table 3.10 Median age at first birth by background characteristics . . . . . . . . . . . . . . . . . . . . . . . 36 Table 3.11 Adolescent pregnancy and motherhood . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37 Table 4.1 Knowledge of contraceptive methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39 Table 4.2 Couples’ knowledge of contraceptive methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40 Table 4.3 Ever use of contraception . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41 Table 4.4 Current use of contraception: women . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42 Table 4.5 Current use of contraception: men . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44 Table 4.6 Current use of contraception by background characteristics . . . . . . . . . . . . . . . . . . . . 46 Table 4.7 Trend in current use of contraception by district . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48 Table 4.8 Number of children at first use of contraception . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49 Table 4.9 Knowledge of the fertile period . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50 Table 4.10 Perceived contraceptive effect of breastfeeding . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51 Table 4.11 Timing of sterilisation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52 Table 4.12 Source of supply for modern contraceptive methods . . . . . . . . . . . . . . . . . . . . . . . . . 52 Table 4.13 Willingness to pay for pill supply . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52 Table 4.14 Contraceptive discontinuation rates . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53 Table 4.15 Reasons for discontinuation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54 Table 4.16 Future use of contraception . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55 x Page Table 4.17 Reasons for not intending to use contraception . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55 Table 4.18 Preferred method of contraception for future use . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56 Table 4.19 Heard about family planning on radio and television . . . . . . . . . . . . . . . . . . . . . . . . . 57 Table 4.20 Acceptability of media messages on family planning . . . . . . . . . . . . . . . . . . . . . . . . . 58 Table 4.21 Sources of family planning messages . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59 Table 4.22 Discussion of family planning with husband . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60 Table 4.23 Wives perceptions of couple's attitude toward family planning . . . . . . . . . . . . . . . . . 61 Table 4.24 Attitudes of couples toward family planning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62 Table 4.25 Family planning and adolescents . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63 Table 4.26 Contact of non-users with family planning providers disseminating family planning information . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64 Table 5.1 Current marital status . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67 Table 5.2 Polygyny . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68 Table 5.3 Age at first marriage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 70 Table 5.4 Median age at first marriage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71 Table 5.5 Age at first sexual intercourse . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72 Table 5.6 Median age at first intercourse . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73 Table 5.7 Recent sexual activity: women . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74 Table 5.8 Recent sexual activity: men . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75 Table 5.9 Postpartum amenorrhoea, abstinence and insusceptibility . . . . . . . . . . . . . . . . . . . . . 76 Table 5.10 Median duration of postpartum insusceptibility by background characteristics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77 Table 5.11 Menopause . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78 Table 6.1 Fertility preferences by number of living children . . . . . . . . . . . . . . . . . . . . . . . . . . . 80 Table 6.2 Fertility preferences by age . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81 Table 6.3 Desire for more children among monogamous couples . . . . . . . . . . . . . . . . . . . . . . . 82 Table 6.4 Desire to limit childbearing by background characteristics . . . . . . . . . . . . . . . . . . . . 82 Table 6.5 Need for family planning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84 Table 6.6 Ideal and actual number of children . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 86 Table 6.7 Mean ideal number of children by background characteristics . . . . . . . . . . . . . . . . . . 87 Table 6.8 Fertility planning status . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 88 Table 6.9 Wanted fertility rates . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 88 Table 7.1 Rates of early childhood mortality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 90 Table 7.2 Neonatal, postneonatal, infant child, and under-five mortality by socioeconomic characteristics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 92 Table 7.3 Neonatal, postneonatal, infant child, and under-five mortality by biodemographic characteristics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 94 Table 7.4 High-risk fertility behaviour . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 96 Table 8.1 Antenatal care . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 98 Table 8.2 Number of antenatal care visits and stage of pregnancy . . . . . . . . . . . . . . . . . . . . . . . 99 Table 8.3 Tetanus toxoid vaccinations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100 Table 8.4 Place of delivery . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 101 Table 8.5 Assistance during delivery . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 102 Table 8.6 Delivery characteristics: caesarean section, birth weight and size . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 103 Table 8.7 Vaccinations by source of information . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 104 Table 8.8 Vaccinations by background characteristics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 106 Table 8.9 Prevalence and treatment of acute respiratory infection . . . . . . . . . . . . . . . . . . . . . . 108 xi Page Table 8.10 Prevalence and treatment of fever . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 109 Table 8.11 Prevalence of diarrhoea . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 110 Table 8.12 Knowledge of diarrhoea care . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 111 Table 8.13 Treatment of diarrhoea . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 112 Table 8.14 Feeding practices during diarrhoea . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 113 Table 9.1 Initial breastfeeding . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 116 Table 9.2 Breastfeeding status . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 117 Table 9.3 Median duration and frequency of breastfeeding by background variables . . . . . . . 118 Table 9.4 Types of food received by children in preceding 24 hours . . . . . . . . . . . . . . . . . . . . 119 Table 9.5 Nutritional status of children by background characteristics . . . . . . . . . . . . . . . . . . 122 Table 9.6 Maternal nutritional status by background characteristics . . . . . . . . . . . . . . . . . . . . 125 Table 10.1.1 Number of sexual partners: women . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 128 Table 10.2.2 Number of sexual partners: men . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 129 Table 10.2 Payment for sexual relations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 131 Table 10.3.1 Knowledge of sexually transmitted diseases: women . . . . . . . . . . . . . . . . . . . . . . . 132 Table 10.3.2 Knowledge of sexually transmitted diseases: men . . . . . . . . . . . . . . . . . . . . . . . . . . 133 Table 10.4.1 Self-reporting of sexually transmitted diseases in the last year: women . . . . . . . . . 134 Table 10.4.2 Self-reporting of sexually transmitted diseases in the last year: men . . . . . . . . . . . . 135 Table 10.5 Action taken by respondents who reported a sexually transmitted disease in the last year . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 136 Table 10.6.1 Knowledge of AIDS and sources of AIDS information: women . . . . . . . . . . . . . . . 137 Table 10.6.2 Knowledge of AIDS and sources of AIDS information: men . . . . . . . . . . . . . . . . . 138 Table 10.7.1 Knowledge of ways to avoid AIDS: women . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 140 Table 10.7.2 Knowledge of ways to avoid AIDS: men . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 141 Table 10.8.1 AIDS-related knowledge: women . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 143 Table 10.8.2 AIDS-related knowledge: men . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 144 Table 10.9.1 Perception of the risk of getting AIDS: women . . . . . . . . . . . . . . . . . . . . . . . . . . . . 145 Table 10.9.2 Perception of the risk of getting AIDS: men . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 146 Table 10.10 Perception of the risk of getting AIDS among couples . . . . . . . . . . . . . . . . . . . . . . . 147 Table 10.11 Reasons for perception of small/no risk of getting AIDS . . . . . . . . . . . . . . . . . . . . . 147 Table 10.12 Reasons for perception of moderate/great risk of getting AIDS . . . . . . . . . . . . . . . . 148 Table 10.13.1 AIDS prevention behaviour: women . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 149 Table 10.13.2 AIDS prevention behaviour: men . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 150 Table 10.14.1 Knowledge of source for condoms: women . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 151 Table 10.14.2 Knowledge of source for condoms: men . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 152 Table 10.15 Use of condoms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 153 Table 10.16 Heard of Trust condoms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 154 Table 10.17.1 Willingness to pay for condoms: women . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 155 Table 10.17.2 Willingness to pay for condoms: men . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 156 Table 10.18 Testing for HIV/AIDS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 157 Table 10.19 Knowledge of sources for HIV/AIDS testing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 158 Table 10.20 Sources used for HIV/AIDS test . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 159 Table 11.1 Data on siblings: completeness of the reported data . . . . . . . . . . . . . . . . . . . . . . . . 162 Table 11.2 Adult female and male mortality rates by age . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 163 Table 11.3 Direct estimates of maternal mortality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 165 Table 12.1 Prevalence of female circumcision . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 168 Table 12.2 Decisionmakers regarding female circumcision . . . . . . . . . . . . . . . . . . . . . . . . . . . . 170 Table 12.3 Persons who perform female circumcision . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 171 xii Page Table 12.4 Place of circumcision and instrument used in circumcision . . . . . . . . . . . . . . . . . . . 172 Table 12.5 Attitudes toward continuation of female circumcision . . . . . . . . . . . . . . . . . . . . . . . 173 Table 12.6 Reasons for favouring continuation of female circumcision . . . . . . . . . . . . . . . . . . . 173 Table 12.7 Reasons for favouring discontinuation of female circumcision . . . . . . . . . . . . . . . . 174 Table A.1.1 Sample implementation: Women . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 181 Table A.1.2 Sample implementation: Men . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 182 Table B.1 List of selected variables for sampling errors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 188 Table B.2 Sampling errors - National . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 189 Table B.3 Sampling errors - Urban . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 190 Table B.4 Sampling errors - Rural . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 191 Table B.5 Sampling errors - Nairobi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 192 Table B.6 Sampling errors - Central . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 193 Table B.7 Sampling errors - Coast . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 194 Table B.8 Sampling errors - Eastern . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 195 Table B.9 Sampling errors - Nyanza . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 196 Table B.10 Sampling errors - Rift Valley . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 197 Table B.11 Sampling errors - Western . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 198 Table C.1 Household age distribution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 201 Table C.2 Age distribution of eligible and interviewed women . . . . . . . . . . . . . . . . . . . . . . . . 202 Table C.3 Completeness of reporting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 202 Table C.4 Births by calendar years . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 203 Table C.5 Reporting of age at death in days . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 204 Table C.6 Reporting of age at death in moths . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 205 . xiii FIGURES Page Figure 2.1 Single-year age distribution of the household population, by sex . . . . . . . . . . . . . . . . 8 Figure 2.2 Distribution of the household population by age and sex . . . . . . . . . . . . . . . . . . . . . . 9 Figure 2.3 Median years of schooling by sex and region . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 Figure 2.4 Housing conveniences by residence . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16 Figure 2.5 Distribution of respondents by religion and ethnicity . . . . . . . . . . . . . . . . . . . . . . . . . 20 Figure 3.1 Total fertility rates in selected countries in Southeast Asia . . . . . . . . . . . . . . . . . . . . . 32 Figure 3.2 Age-specific fertility rates by residence . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34 Figure 3.3 Total fertility rate among women age 15-49 by residence and education . . . . . . . . . . 34 Figure 3.4 Total fertility rate, Philippines 1970-1996 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36 Figure 3.5 Mean number of children ever born among women age 15-49 by age group . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39 Figure 3.6 Median number of months since previous birth by age of mother and birth order . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40 Figure 3.7 Percentage of women age 15-19 (teenagers) who have begun childbearing by residence and education . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46 Figure 3.8 Percentage of women age 15-19 (teenagers) who have begun childbearing by region . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46 Figure 4.1 Knowledge of contraception among currently married women age 15-49 . . . . . . . . . 49 Figure 4.2 Use of contraception among currently married women 15-19 . . . . . . . . . . . . . . . . . . 53 Figure 4.3 Trends in contraceptive use, Philippines 1968-1998 . . . . . . . . . . . . . . . . . . . . . . . . . . 56 Figure 4.4 Contraceptive discontinuation rates for first year of life . . . . . . . . . . . . . . . . . . . . . . . 66 Figure 5.1 Median age at first marriage by residence and education . . . . . . . . . . . . . . . . . . . . . . 78 Figure 5.2 median ge at first marriage by region . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78 Figure 5.3 Percentage of births for which mothers are postpartum amenorrheic, abstaining and insusceptible . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84 xiv Page Figure 6.1 Fertility preferences among currently married women age 15-49 . . . . . . . . . . . . . . . 91 Figure 6.2 Percentage of currently married women who want no more children by residence and region . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 92 Figure 6.3 Mean ideal number of children for all women by region . . . . . . . . . . . . . . . . . . . . . . 98 Figure 6.4 Currently married women by perceived consensus with husband regarding the number of children desired . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 102 Figure 6.5 Currently married women whose desired number of children is the same as that perceived as desired by their husband . . . . . . . . . . . . . . . . . . . . . . . . . 102 Figure 7.1 Deaths among children under two years for three 5-year periods preceding the survey . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 104 Figure 7.2 Trends in infant mortality in the Philippines, various sources, 1970-1995 . . . . . . . . 106 Figure 7.3 Infant mortality by background characteristics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 108 Figure 8.1 Number of prenatal care visits and stage of pregnancy at first visit . . . . . . . . . . . . . 115 Figure 8.2 Knowledge of dangerous signs and symptoms during pregnancy among women who received prenatal care . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 117 Figure 8.3 Percentage of live births with complications during pregnancy . . . . . . . . . . . . . . . . 123 Figure 8.4 Distribution of live births by source of postnatal care . . . . . . . . . . . . . . . . . . . . . . . 127 Figure 8.5 Vaccination coverage among children 12-23 months . . . . . . . . . . . . . . . . . . . . . . . . 130 Figure 8.6 Feeding practices among children under five with diarrhea . . . . . . . . . . . . . . . . . . . 138 Figure 9.1 Distribution of children by breastfeeding (BF) status according to age . . . . . . . . . . 144 Figure 10.1 Sources of Anti-TB medicines . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 153 Figure 10.2 Percentage of households that utilized health facilities in the 6 months preceding the survey . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 162 xv Foreword The 1998 Kenya Demographic and Health Survey (KDHS) is the third survey of its kind to be conducted in Kenya, following the 1989 KDHS and 1993 KDHS. Like earlier DHS surveys, the 1998 survey was designed to provide information on demographic trends and indicators of maternal and child health in Kenya. However, in line with the expansion of programmes in health and population, the 1998 survey instruments were more extensive and the treatment of certain topics more exhaustive than in the earlier surveys. This report is intended to provide policy makers and programme managers with a comprehensive look at levels and trends in key health and demographic parameters. Of particular note, the 1998 KDHS findings provide evidence of a significant decline in fertility rates and an increase in the use of family planning methods since the 1993 KDHS. The KDHS also provides evidence pointing to an increase in infant and under-five mortality during the 1990s, which may in part be associated with the HIV/AIDS epidemic. While comprehensive, the report cannot cover all aspects of concern to the health and population community. We expect that this report will raise important questions and establish the groundwork for further analysis of the KDHS data. NCPD stands firm with its partners in a commitment to make the KDHS data available and accessible to responsible investigators. The NCPD wishes to acknowledge the joint effort of a number of organization and individuals who contributed immensely towards the success of the survey. First we would like to acknowledge the financial assistance from the United States Agency for International Development (USAID) and the Department for International Development (DFID) (U.K.); Macro International/DHS for technical backstopping; staff of the Central Bureau of Statistics (CBS) and NCPD who worked tirelessly to ensure successful completion of field work; and the UNFPA, the Division of Primary Health Care (DPHC) and National AIDS Control Programme (NASCOP) for providing vehicles for fieldwork. Also, my sincere thanks go to all the professionals from the government, NGO, donor, and scientific communities who contributed to the design of the survey questionnaires. Finally, we gratefully acknowledge the cooperation of the thousands of survey respondents who gave generously of their time to provide the information that forms the basis of this report. Ambassador S. B. A. Bullut, DIRECTOR NATIONAL COUNCIL FOR POPULATION AND DEVELOPMENT xvii Executive Summary The 1998 Kenya Demographic and Health Survey (KDHS) is a nationally representative survey of 7,881 women age 15-49 and 3,407 men age 15-54. The KDHS was implemented by the National Council for Population and Development (NCPD) and the Central Bureau of Statistics (CBS), with significant technical and logistical support provided by the Ministry of Health and various other governmental and non- governmental organizations in Kenya. Macro International Inc. of Calverton, Maryland (U.S.A.) provided technical assistance throughout the course of the project in the context of the worldwide Demographic and Health Surveys (DHS) programme, while financial assistance was provided by the U.S. Agency for International Development (USAID/Nairobi) and the Department for International Development (DFID/U.K.). Data collection for the KDHS was conducted from February to July 1998. Like the previous KDHS surveys conducted in 1989 and 1993, the 1998 KDHS was designed to provide information on levels and trends in fertility, family planning knowledge and use, infant and child mortality, and other maternal and child health indicators. However, the 1998 KDHS went further to collect more in-depth data on knowledge and behaviours related to AIDS and other sexually transmitted diseases (STDs), detailed “calendar” data that allows estimation of contraceptive discontinuation rates, and information related to the practice of female circumcision. Further, unlike earlier surveys, the 1998 KDHS provides a national estimate of the level of maternal mortality (i.e. related to pregnancy and childbearing). The KDHS data are intended for use by programme managers and policymakers to evaluate and improve health and family planning programmes in Kenya. Fertility. The survey results demonstrate a continuation of the fertility transition in Kenya. At current fertility levels, a Kenyan women will bear 4.7 children in her life, down 30 percent from the 1989 KDHS when the total fertility rate (TFR) was 6.7 children, and 42 percent since the 1977/78 Kenya Fertility Survey (KFS) when the TFR was 8.1 children per woman. A rural woman can expect to have 5.2 children, around two children more than an urban women (3.1 children). Fertility differentials by women's education level are even more remarkable; women with no education will bear an average of 5.8 children, compared to 3.5 children for women with secondary school education. Marriage. The age at which women and men first marry has risen slowly over the past 20 years. Currently, women marry for the first time at an average age of 20 years, compared with 25 years for men. Women with a secondary education marry five years later (22) than women with no education (17). The KDHS data indicate that the practice of polygyny continues to decline in Kenya. Sixteen percent of currently married women are in a polygynous union (i.e., their husband has at least one other wife), compared with 19 percent of women in the 1993 KDHS, 23 percent in the 1989 KDHS, and 30 percent in the 1977/78 KFS. While men first marry an average of 5 years later than women, men become sexual active about one- half of a year earlier than women; in the youngest age cohort for which estimates are available (age 20-24), first sex occurs at age 16.8 for women and 16.2 for men. Fertility Preferences. Fifty-three percent of women and 46 percent of men in Kenya do not want to have any more children. Another 25 percent of women and 27 percent of men would like to delay their next child for two years or longer. Thus, about three-quarters of women and men either want to limit or to space their births. xviii The survey results show that, of all births in the last three years, 1 in 10 was unwanted and 1 in 3 was mistimed. If all unwanted births were avoided, the fertility rate in Kenya would fall from 4.7 to 3.5 children per woman. Family Planning. Knowledge and use of family planning in Kenya has continued to rise over the last several years. The 1998 KDHS shows that virtually all married women (98 percent) and men (99 percent) were able to cite at least one modern method of contraception. The pill, condoms, injectables, and female sterlisation are the most widely known methods. Overall, 39 percent of currently married women are using a method of contraception. Use of modern methods has increased from 27 in the 1993 KDHS to 32 percent in the 1998 KDHS. Currently, the most widely used methods are contraceptive injectables (12 percent of married women), the pill (9 percent), female sterilisation (6 percent), and periodic abstinence (6 percent). Three percent of married women are using the IUD, while over 1 percent report using the condom and 1 percent use of contraceptive implants (Norplant). The rapid increase in use of injectables (from 7 to 12 percent between 1993 and 1998) to become the predominant method, plus small rises in the use of implants, condoms and female sterilisation have more than offset small decreases in pill and IUD use. Thus, both new acceptance of contraception and method switching have characterised the 1993-1998 intersurvey period. Contraceptive use varies widely among geographic and socioeconomic subgroups. More than half of currently married women in Central Province (61 percent) and Nairobi Province (56 percent) are currently using a method, compared with 28 percent in Nyanza Province and 22 percent in Coast Province. Just 23 percent of women with no education use contraception versus 57 percent of women with at least some secondary education. Government facilities provide contraceptives to 58 percent of users, while 33 percent are supplied by private medical sources, 5 percent through other private sources, and 3 percent through community-based distribution (CBD) agents. This represents a significant shift in sourcing away from public outlets, a decline from 68 percent estimated in the 1993 KDHS. While the government continues to provide about two-thirds of IUD insertions and female sterilisations, the percentage of pills and injectables supplied out of government facilities has dropped from over 70 percent in 1993 to 53 percent for pills and 64 percent for injectables in 1998. Supply of condoms through public sector facilities has also declined: from 37 to 21 percent between 1993 and 1998. The survey results indicate that 24 percent of married women have an unmet need for family planning (either for spacing or limiting births). This group comprises married women who are not using a method of family planning but either want to wait two year or more for their next birth (14 percent) or do not want any more children (10 percent). While encouraging that unmet need at the national level has declined (from 34 to 24 percent) since 1993, there are parts of the country where the need for contraception remains high. For example, the level of unmet need is higher in Western Province (32 percent) and Coast Province (30 province) than elsewhere in Kenya. Early Childhood Mortality. One of the main objectives of the KDHS was to document current levels and trends in mortality among children under age 5. Results from the 1998 KDHS data make clear that childhood mortality conditions have worsened in the early-mid 1990s; this after a period of steadily improving child survival prospects through the mid-to-late 1980s. Under-five mortality, the probability of dying before the fifth birthday, stands at 112 deaths per 1000 live births which represents a 24 percent increase over the last decade. Survival chances during age 1-4 years suffered disproportionately: rising 38 percent over the same period. xix Survey results show that childhood mortality is especially high when associated with two factors: a short preceding birth interval and a low level of maternal education. The risk of dying in the first year of life is more than doubled when the child is born after an interval of less than 24 months. Children of women with no education experience an under-five mortality rate that is two times higher than children of women who attended secondary school or higher. Provincial differentials in childhood mortality are striking; under-five mortality ranges from a low of 34 deaths per 1000 live births in Central Province to a high of 199 per 1000 in Nyanza Province. Maternal Health. Utilisation of antenatal services is high in Kenya; in the three years before the survey, mothers received antenatal care for 92 percent of births (Note: These data do not speak to the quality of those antenatal services). The median number of antenatal visits per pregnancy was 3.7. Most antenatal care is provided by nurses and trained midwives (64 percent), but the percentage provided by doctors (28 percent) has risen in recent years. Still, over one-third of women who do receive care, start during the third trimester of pregnancy—too late to receive the optimum benefits of antenatal care. Mothers reported receiving at least one tetanus toxoid injection during pregnancy for 90 percent of births in the three years before the survey. Tetanus toxoid is a powerful weapon in the fight against neonatal tetanus, a deadly disease that attacks young infants. Forty-two percent of births take place in health facilities; however, this figure varies from around three-quarters of births in Nairobi to around one-quarter of births in Western Province. It is important for the health of both the mother and child that trained medical personnel are available in cases of prolonged labour or obstructed delivery, which are major causes of maternal morbidity and mortality. The 1998 KDHS collected information that allows estimation of mortality related to pregnancy and childbearing. For the 10-year period before the survey, the maternal mortality ratio was estimated to be 590 deaths per 100,000 live births. Bearing on average 4.7 children, a Kenyan woman has a 1 in 36 chance of dying from maternal causes during her lifetime. Childhood Immunisation. The KDHS found that 65 percent of children age 12-23 months are fully vaccinated: this includes BCG and measles vaccine, and at least 3 doses of both DPT and polio vaccines. This finding represents a significant decline in full vaccination coverage from the 79 percent estimated in the 1993 KDHS. More detailed analysis suggests that the worsening picture is due to: (a) a decline in measles vaccine coverage, and (b) an increase in the dropout rate between first and third doses of DPT and polio vaccines. Vaccination coverage fell in all areas of Kenya, but declined most in Nyanza Province, to less than 50 percent of children. Childhood Illnesses and Treatment. In the two weeks preceding the survey, 20 percent of children under three years of age were reported to have experienced symptoms of acute respiratory infection (ARI)—cough with short, rapid breathing. Children with ARI are more likely to be taken to a health facility or provider for treatment if they live in urban areas (74 percent) than rural areas (54 percent). Malaria poses an increasing threat to child health and survival in Kenya. As fever is the major manifestation of malaria, the KDHS included a series of questions on prevalence of fever and treatment of febrile children. In the two weeks before the survey, 42 percent of children under age three were reported to have had a fever; with highest prevalence rates in Nyanza and Western provinces (49 percent). Fifty-nine percent of febrile children were taken to a health facility or provider for treatment, and 40 percent were given an antimalarial drug in response to the fever. Coast, Western, and Nyanza provinces had the highest rates of antimalarial use (for treatment). xx Seventeen percent of children under age three were reported to have had diarrhoea in the two weeks preceding the survey. The period of peak susceptibility to diarrhoea occurs during age 6-23 months, which is when most children are weaned and increasingly exposed to disease-causing agents. Around 44 percent of children with diarrhoea are taken to a health facility or provider for treatment. Over two-thirds of sick children received oral rehydration therapy using either a solution prepared from ORS packets (i.e., Oralite) or a recommended home fluid. However, 1 in 10 children with diarrhoea received no treatment at all; and the mothers of 1 in 6 children reported that they decreased fluid intake in response to the diarrhoea. Dehydrating diarrhoeal disease remains a leading cause of under-five mortality in Kenya Infant Feeding. Almost all children (98 percent) are breastfed for some period of time; however, only 58 percent are breastfed within the first hour of life, and 86 percent within the first day after birth. The median duration of breastfeeding in Kenya is 21 months; but the introduction of supplementary liquids and foods occurs much earlier in life. Nearly three-quarters of children under 2 months of age are already given some form of supplementary feeding. Until age 4-6 months, exclusive breastfeeding (i.e., without any other foods or liquids) is recommended because it provides all the necessary nutrients and avoids exposure to disease agents. Yet, only 17 percent of children under 4 months are exclusively breastfed. Nutritional Status. In the KDHS children under five years of age and their mothers were weighed and measured to obtain data for estimating levels of malnutrition. The results indicate that one-third of children in Kenya are stunted (i.e., too short for their age), a condition reflecting chronic malnutrition; and 1 in 16 children are wasted (i.e., very thin), a problem indicating acute or short-term food deficit. Peak levels of wasting occur during ages 6-23 months. The probability of being nutritionally “at-risk” is especially high for children of women with low levels of education. Women whose body mass index (BMI)—weight (in kilograms) divided by the squared height (in metres)—falls below 18.5 are considered at nutritional risk. The data show that 1 in 8 mothers of young children have a BMI value below 18.5, indicating that they are very thin. The percentage of mothers with a low BMI varies from around 5 percent in Nairobi and Western provinces to around 15 percent in Rift Valley, Eastern, and Coast provinces. Teenage mothers (less than 20 years of age) are at especially high risk of having a low BMI. Knowledge, Attitudes and Behaviour regarding HIV/AIDS and Other Sexually Transmitted Infections. As a measure of the increasing toll taken by AIDS on Kenyan society, the percentage of respondents who reported “personally knowing someone who has AIDS or has died from AIDS” has risen from about 40 percent of men and women in the 1993 KDHS to nearly three-quarters of men and women in 1998. While nearly all survey respondents reported a general knowledge of AIDS, there remain significant numbers of women and men in Kenya who still lack an appreciation for key aspects of the epidemic. For example, about 1 in 10 men and women do not think that AIDS can be prevented. For those who did report that AIDS was preventable, less than one-half cited condom use as an effective means to prevent the spread of the virus. Male respondents tend to be slightly more knowledgeable than women about means of preventing HIV transmission. Men get their AIDS-related information predominantly from mass media sources. Women, on the other hand, rely more than men on community level sources such as friends, relatives, and health facility staff. Consistent condom use is a powerful weapon to combat HIV transmission. Almost all men and women reported that they know of condoms, but when asked whether they know where to get them, 39 percent of women and 24 percent of men where not able to cite a single source. In the most recent sexual encounter before the survey, just 21 percent of men and 6 percent of women reported having used a condom. xxi For both men and women, condom use is much more limited with spouses than with premarital and extramarital sexual partners. When KDHS respondents were asked about their experience with the test for HIV, the AIDS virus, 14 percent of women and 17 percent of men reported that they had already been tested. Of those not yet tested, over 60 percent of women and men reported a desire to be tested. However, over one-third of respondents desiring to be tested were not able to cite a source to obtain an AIDS test. Female Circumcision. The 1998 KDHS included a series of questions regarding the experience of women and their eldest daughters with the practice of female circumcision (FC). The results indicate that 38 percent of women age 15-49 in Kenya have been circumcised. The prevalence of FC has however declined significantly over the last 2 decades from about one-half of women in the oldest age cohorts to about one- quarter of women in the youngest cohorts (including daughters age 15+). There exists wide variation in the prevalence of FC across Kenya’s ethnic groups, from virtually no FC practice amongst the Luo and Luyha, to very widespread or universal practice amongst the Kisii and Masai. About one-half of circumcisions are performed by circumcision practitioners; about one-third by doctors, trained nurses, or midwives; and most of the remainder by traditional birth attendants. The instrument most commonly used to perform the circumcision was a razor blade. Three-quarters of respondents reported that they would like to see the practice of FC stopped. Adolescents. It is increasingly recognized that the concerns of Kenya’s youth need to be understood and addressed within the development process. It is thus useful to summarize, for males and females age 15- 19, some important KDHS findings in the following key areas: education, fertility, family planning, sex activity, and AIDS. Education remains the primary pathway towards economic and social advancement in Kenya. By age 15, most boys and girls should have completed their primary education. However, since the 1993 KDHS the percentage of young persons age 15-19 who have actually achieved this goal has declined sharply from 56 to 40 percent (females) and 52 to 38 percent (males). This pattern represents a disinvestment in Kenya’s future. Despite declines in fertility at all other age groups, teenage fertility remains constant at early-1990s levels. It is still true that one-half of Kenyan women will have started childbearing before the age of 20. Sex begins on average at age 16.2 for boys and 16.8 for girls; yet, contraceptive use is very low in the age group 15-19 and seldom involves effective family planning methods. This is not surprising, since youth are little exposed to family planning information and services. Among females age 15-19 who are not using a family planning method, very few were contacted by community-based distribution agents. Unlike older females, when attending health facilities, female adolescents are seldom given information about pregnancy prevention. This is puzzling since 79 percent of women (age 15-49) interviewed and 88 percent of men (age 15-54) reported that they felt family planning information should be made available to persons under age 18. In the same vein, the KDHS data also indicate that respondents under age 20 are more likely than older respondents to demonstrate a lack of understanding about key aspects of the AIDS epidemic. For example, adolescents were less likely to know about sexually-transmitted diseases (STDs), more likely to hold misconceptions about modes of HIV transmission, less likely to know of a place where condoms can be obtained, and less likely to report multiple sources for information about HIV/AIDS. 1 CHAPTER 1 INTRODUCTION Peter Thumbi 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 in 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 bisected by the equator. The country falls into two distinct regions: lowland and highland (upland). Altitude plays an important role in Kenya’s climatic patterns, patterns of human settlement, and agricultural activities. The country has an unusually diverse physical environment, including savanna grasslands and woodlands, tropical rain forest, and semi-desert environments. Approximately 80 percent of the land area of Kenya is arid or semi-arid and only 20 percent is arable. A large proportion of the arid and semi-arid land has 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 subdivided into districts. In all, there are 75 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 then taking place the world over, Parliament repealed the section of the constitution which made Kenya a one-party state. The country is multi-ethnic, with 43 ethno-linguistic groups. The major groups are Kikuyu, Luo, Luhya, Kamba Kalenjin, Mijikenda, Meru, Embu, and Kisii. Kikuyus live primarily in Central Province, Luos inhabit the Western part of Nyanza Province, Luhyas live in Western Province, Kambas in the southern part of Eastern Province, Kalenjins in Rift Valley Province, Mijikendas in Coast Province, Merus and Embus 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 26 percent of the gross domestic product (GDP) while manufacturing accounts for about 14 percent. Tea, tourism, coffee, and horticulture in that order are the main foreign-exchange earners. 2 Table 1.1 Basic demographic indicators, Kenya, 1969, 1979, and 1989 censuses __________________________________________________ Population census ________________________ Indicator 1969a 1979b 1989c __________________________________________________ Population (millions) 10.9 16.2 23.2d Density (pop./km2) 19.0 27.0 37.0 Percent urban 9.9 15.1 18.1 Crude birth rate 50.0 54.0 48.0 Crude death rate 17.0 14.0 11.0 Growth rate 3.3 3.8 3.4d Total fertility rate (children per woman) 7.6 7.8 6.7 Infant mortality rate (per 1,000 live births) 119 88 66 Life expectancy at birth (years) 50 54 60 __________________________________________________ a CBS, 1970b CBS 1981bc CBS, 1991a; CBS, 1994; CBS, 1996d Based on 1979-89 intercensal period Since independence in 1963, the economy of the country has had mixed performance. In the first 10 years of independence, the country enjoyed high GDP growth rates averaging 6.5 percent per annum, low inflation, high job creation, and a relatively stable balance-of-payments position. During the 1973-1980 period the country’s record growth was upset by three major shocks. The first was the sharp rise in oil prices in 1973, which created considerable internal and external economic imbalance. In 1977-78, the price of coffee and tea rose significantly, which immediately improved the balance-of- payments position but subsequently created internal economic imbalances. The third shock was experienced when oil prices rose again in 1979. Despite these setbacks, Kenya enjoyed an average growth in the 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 1980-1985 period was characterised by slow growth in the GDP (2.5 percent). This economic decline resulted from several confounding factors, including the high cost of oil, a global recession in 1980- 1982, as well as a drought in 1984. To accelerate economic growth, the government implemented adjustment programmes in the agricultural, trade, and financial sectors in 1986. The adjustment programmes accelerated the growth in the GDP to an average of 5.8 percent per annum. In 1990, growth in the GDP fell to 4.3 percent and in 1991 to 2.2 percent; by 1992, it was just 0.4 percent per annum. In 1993, the government introduced more and far-reaching structural reforms, including removal of price controls, removal of all import licencing, and removal of foreign exchange controls. These reforms bore fruit, with the GDP growing at 3.0 percent and 4.9 percent in 1994 and 1995, respectively. The growth slowed to 4.8 percent in 1996 and declined substantially to 1.2 percent in 1997. 1.2 Population Kenya’s population increased from 5.4 million in 1948 to 16.2 million in 1979 and to 23.2 million in 1989 (CBS, 1994) (see Table 1.1). Results of the 1989 census indicate that the inter- censal population growth rate for Kenya is 3.4 per- cent per annum, although the current growth rate is probably around 3.0 percent or slightly less. This represents a decline from the growth rate of 3.8 percent per annum estimated from the 1979 population census. Even with declining population growth (driven by declining fertility rates, see Chapter 3), and increases in mortality associated with the HIV/AIDS epidemic, the size of Kenya’s population is expected to exceed 30 million by the year 2000 (NCPD, 1997). The crude birth rate increased from 50 per 1,000 in 1969 to 54 per 1,000 in 1979 but declined to 48 per 1,000 in 1989, whereas the crude death rate decreased from 17 to 14 to 11 per 1,000 in the same period. The infant mortality rate decreased from 119 deaths per 1,000 live births in 1969 to 88 in 1979 and further to 66 deaths per 1,000 live births in 1989. As a result of high fertility and declining mortality in the past, Kenya is characterised by a young population. Almost 50 percent of Kenya’s population is less than 15 years of age. 3 Kenya’s population lives mainly in rural areas. According to the 1989 census, only 18 percent of Kenya’s population lives in urban areas (CBS, 1994). Most of the urban population (89 percent) is concentrated in towns with a population of 10,000 or more, of which there were 46 in 1989. Small towns, defined as those with a population of less than 10,000, have higher a growth rate than larger towns. Towns with a population of less than 5,000 had an intercensal growth rate of 9.1 percent while towns with a population of 5,000 to 10,000 and those with more than 10,000 had intercensal growth rates of 6.8 and 4.9 percent, respectively. The observed increase in the urban population is largely attributable to urban-rural migration. 1.3 Population and Family Planning Policies and Programmes The Government of Kenya adopted an explicit population policy in 1967 when the official national family planning programme was launched. Family planning was integrated into the maternal and child health division of the Ministry of Health. In 1984, a set of population policy guidelines were issued to guide population policy and programme implementation. The International Conference on Population and Development (ICPD), held in Cairo in 1994, agreed upon a Programme of Action on Population and Development which changed the scope of population policy and programme by placing more emphasis on the welfare of an individual rather than on the achievement of demographic targets. The Government updated the Sessional Paper No. 4 of 1984 on Population Policy Guidelines to address population and development issues which had emerged since that time and to have a population policy that was in line with ICPD Programme of Action. This culminated in the formulation of Sessional Paper No.1 of 1997 on National Population Policy for Sustainable Development, which substantially widened the scope of the population policy. The National Population Policy for Sustainable Development has a set of goals, objectives and targets to guide its implementation up to the year 2010. The targets are categorised into three broad areas: demographic, health and social service. Demographic targets include: C Reduction of the infant mortality rate (per 1,000 live births) from 67 in 1995 to 66 by the year 2000 to 63 by 2005 and to 59 by 2010; C Reduction of the maternal mortality ratio (per 100,000 births) from 365 in 1995 to 230 by 2005 and to 170 by 2010; C Reduction of the total fertility rate (average number of births per woman) from 5.0 in 1995 to 4.0 by the year 2000 to 3.5 by 2005 and to 2.5 by 2010; and C Increase in the contraceptive prevalence rate (all methods among all women) from 33 percent in 1993 to 43 percent by the year 2000 to 53 by 2005 and to 62 by 2010. Health service targets include: C Increase in full immunisation coverage from 80 percent in 1995 to 98 percent by the year 2010; and C Increase in professionally attended deliveries from 45 percent in 1995, to 90 percent by the year 2010. 4 1.4 Health Priorities and Programmes In 1994, the government of Kenya issued a health policy framework paper which presents a comprehensive vision of current Ministry of Health policies and provides guidelines to health policy makers for regularly reviewing and revising policies within a set framework. Kenya’s health policy framework has identified the critical problems for the Kenyan health sector as: finances, inadequate capacity of the public health-care system, inequitable distribution of key health personnel (with a noted concentration in urban areas and in in-patient services), and inadequate and unenforced laws governing the health sector. To improve the overall function of the health sector, the health policy framework has identified the major strategies to be employed. The paper which will operate with the strategic theme of “Investing in Health” has stipulated the following overall goal until the year 2010: C Ensure the equitable allocation of Government resources to reduce disparities in health status; C Increase the cost effectiveness and the cost efficiency of resource allocation and use; C Continue to manage population growth; C Enhance the role of Government in all aspects of health care provision; C Create an enabling environment for increased private sector and community involvement in health service provision and finance; and C Increase and diversify per capita financial flows to the health sector. To meet the goal of the health sector and to respond to the future health needs of the Kenyan people, the Government has proposed and committed to implementing reforms in the health sector. These reforms will include: C Adoption of an explicit strategy to reduce the burden of disease among the Kenyan population and definition of those cost-effective and essential curative and preventive services which will be provided for by the Ministry of Health; C Reinforcement of the provincial level to permit effective supervision of the districts and further decentralisation of planning, management and resource creation; C Strengthening of nongovernmental organisations (NGO), local authorities, and private- and mission-sector health service providers; C Generation of increased levels of financial resources for the provision of cost-effective services through widely accepted cost sharing and alternative health-financing initiatives; C Prevention and control of AIDS, HIV infection, and sexually transmitted diseases; C Increasing inter-sectoral collaboration with other ministries involved in the improvement of health status; and 5 C Encouraging nongovernmental 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 distribution (CBD) agents to provide services is being emphasised. It is estimated that, at present, CBD agents employed by government and nongovernmental agencies to provide nonclinical family planning methods have increased from slightly over 10,000 in 1992 to about 20,000 in 1998. 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 been a major hindrance to provision of health services in the country. 1.5 Objectives of the 1998 Kenya Demographic and Health Survey The principal aim of the 1998 KDHS project is to provide up-to-date information on fertility and childhood mortality levels, nuptiality, fertility preferences, awareness and use of family planning methods, use of maternal and child health services, and knowledge and behaviours related to HIV/AIDS and other sexually-transmitted diseases. It was designed as a follow-on to the 1989 KDHS and 1993 KDHS, national- level surveys of similar size and scope. Ultimately, the 1998 KDHS project seeks to: C Assess the overall demographic situation in Kenya; C Assist in the evaluation of the population and reproductive health programmes in Kenya; C Advance survey methodology; and C Assist the NCPD to strengthen its capacity to conduct demographic and health surveys. The 1998 KDHS was specifically designed to: C Provide data on the family planning and fertility behaviour of the Kenyan population, and to thereby enable the NCPD to evaluate and enhance the national family planning programme; C Measure changes in fertility and contraceptive prevalence and at the same time study the factors which affect these changes, such as marriage patterns, desire for children, availability of contraception, breastfeeding habits, and important social and economic factors; C Examine the basic indicators of maternal and child health in Kenya, including nutritional status, use of antenatal and maternity services, treatment of recent episodes of childhood illness, and use of immunisation services; C Describe levels and patterns of knowledge and behaviour related to the prevention of AIDS and other sexually transmitted infection; C Measure adult and maternal mortality at the national level; and C Ascertain the extent and pattern of female circumcision in the country. 6 1.6 Survey Organisation The 1998 KDHS was a national survey carried out by the National Council for Population and Development (NCPD) in collaboration with the Central Bureau of Statistics (CBS). Macro International Inc. (USA) provided technical and financial assistance through its contract with the U.S. Agency for International Development (USAID). Funding for the KDHS was provided by USAID and the British Department for International Development (DFID). The United Nations Population Fund (UNFPA), the Division of Primary Health Care (DPHC), and the National AIDS Control Programme (NASCOP) provided logistical assistance. 1.7 Sample Design The 1998 KDHS 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 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 selected sample units (clusters). Six of the 536 clusters (1 percent) were not surveyed due to inaccessibility. Details of the sample design and implementation are given in Appendix A. Despite the need for obtaining district-level data for planning purposes, reliable estimates could not be produced from the KDHS for all districts in the country—which have increased in number from 48 to 75 since 1993—without expanding the sample to an unmanageable size. It was felt, however, that reliable estimates for certain variables could be produced for the rural areas in 15 districts: Bungoma, Kakamega, Kericho, Kilifi, Kisii, Machakos, Meru, Murang’a, Nakuru, Nandi, Nyeri, Siaya, South Nyanza, Taita-Taveta, and Uasin Gishu. These areas plus Nairobi and Mombasa were targeted because: (1) before subdivision, they were generally the larger districts in their provinces, (2) most were districts in which the NCPD had posted District Population Officers, and (3) the districts were also targeted in the 1989 and 1993 KDHS projects. Although most of these districts were subdivided in the recent past, the previous boundaries have been used in order to maintain comparability with the two previous KDHS surveys. Due to this oversampling at the district level, the KDHS sample is not self-weighting at the national level. Sample weights were used to compensate for the unequal probability of selection between geographically defined strata, and weighted figures are used throughout the remainder of this report. During late 1997 to early 1998, field staff from the Central Bureau of Statistics conducted a household listing in each of the selected clusters. From these household lists, a systematic sample of households was drawn: 22 households per urban cluster and 17 households per rural cluster totaling 9,465 selected households. All women age 15-49 were to be interviewed (i.e., eligible) in these households. Every second household was included in the male sample and, in those households, all men age 15-54 were also eligible for interview. 1.8 Questionnaire Three types of questionnaires were used in the 1998 KDHS: the Household Questionnaire, the Women’s Questionnaire, and the Men’s Questionnaire. The Women’s and Men’s questionnaires were based on the DHS Model A Questionnaire, which is designed for use in countries with relatively high levels of contraceptive use. A series of meetings were held with policy experts, programme managers, and other professionals to review, adapt, and revise the questionnaires. This process culminated in a set of English- language questionnaires, which were translated into Kiswahili and nine of the most widely spoken local languages: Kalenjin, Kamba, Kikuyu, Kisii, Luhya, Luo, Masai, Meru, and Mijikenda. 7 The Household Questionnaire was used to list all of the usual members and visitors in the selected households. Basic information on each person listed was collected including age, sex, education, and relationship to the head of the household. The main purpose of the Household Questionnaire was to identify all of the women age 15-49 and men age 15-54 eligible for the individual interview. In addition, information was collected about characteristics of the household, such as the source of water, type of toilet facilities, materials used to construct the household’s dwelling, and ownership of various consumer goods. The Women’s Questionnaire was used to collect information from women age 15-49, and included questions on the following topics: • Background characteristics (age, education, religion, etc.), • Reproductive history (to arrive at fertility and childhood mortality rates), • Knowledge and use of family planning methods, • Antenatal and delivery care, • Infant feeding practices including patterns of breastfeeding, • Childhood vaccinations, • Recent episodes of childhood illness and responses to illness, • Marriage and sexual activity, • Fertility preferences, • Husband’s background and respondent’s work status, • Mortality of adults, including maternal mortality, • AIDS-related knowledge, attitudes, and behaviour, • Female circumcision, and • Nutritional status of children and mothers. The Men’s Questionnaire covered many of the same topics but excluded the detailed reproductive history and sections dealing with maternal and child health, maternal mortality, and female circumcision. The Men’s Questionnaire is consequently much shorter than the Women’s Questionnaire. The questionnaires were pretested by language-specific teams of one woman and one man who had been trained for two weeks at the Machakos Technical Training Institute. During the pretest fieldwork, supervised by NCPD staff, 200 Household, Women’s, and Men’s Questionnaires were completed in locations around Kenya where interviews could be carried out in the various local languages. Based on observations in the field and suggestions made by the pretest field teams and trainers, revisions were made in the wording and translation of the questionnaires. 1.9 Training and Fieldwork A total of 120 interviewers were recruited by NCPD from areas where they would eventually conduct the KDHS fieldwork. A three-week training course was organised for the recruits at the St. Mary’s Pastoral Training Centre in Nakuru. The first phase of the training course consisted of lectures on the underlying rationale of the questionnaires’ content and how to complete the questionnaire. Local language-specific groups were formed to review the translations, after which supervised mock interviews between participants were conducted to allow practice in proper interviewing techniques and the posing of questions. Several days were spent training participants in the methods for measuring height and weight of women and children. Towards the end of the training, the participants spent several days practicing interviews under close supervision in households near the training centre. Fieldwork commenced on 16 February 1998 and was completed on 29 July 1998. The interviewers were organised into 12 mobile teams. Each team consisted of 1 supervisor, 1 field editor, 4-5 female 8 Table 1.2 Results of the household and individual interviews Number of households, number of interviews and response rates, according to urban-rural residence, Kenya 1998 ____________________________________________________ Residence _______________ Result Urban Rural Total ____________________________________________________ Household interviews Households sampled Households occupied Households interviewed Household response rate Individual interviews: women Number of eligible women Number of eligible women interviewed Eligible woman response rate Individual interviews: men Number of eligible men Number of eligible men interviewed Eligible man response rate 2,002 7,463 9,465 1,777 6,884 8,661 1,647 6,733 8,380 92.7 97.8 96.8 1,576 6,657 8,233 1,466 6,415 7,881 93.0 96.4 95.7 855 2,990 3,845 656 2,751 3,407 76.7 92.0 88.6 interviewers, and 1 male interviewer, with the exception of the Masai team which had just 2 female interviewers and 1 male interviewer. Nine NCPD staff based in Nairobi coordinated the work, while 17 field coordinators were involved in the day-to-day supervision of the teams. Table 1.2 shows response rates for the survey. A total of 9,465 households were selected for inclusion in the 1998 KDHS, of which 8,661 were occupied and thus eligible for interview. Of the eligible households, 8,380 were successfully interviewed, giving a response rate of 97 percent. The main reason for eligible households not being interviewed was that a competent member of the household could not be found and interviewed during the course of work in the cluster. In interviewed households, 8,233 eligible women (age 15-49) were identified and 7,881 were successfully interviewed, yielding a response rate of 96 percent. Of the 4,747 households subsampled for inclusion in the KDHS male survey, 4,337 households were occupied and therefore eligible for interview. About 97 percent of these households were successfully interviewed. A total of 3,845 men (age 15-54) were identified in the surveyed households and 3,407 of these were interviewed, yielding a response rate of 89 percent. Response rates for male and female individual interviews were higher in rural areas than in urban areas. The main reason for nonresponse was failure to find the individuals despite repeated visits to the household and place of work. 1 A household refers to a person or group of related and unrelated persons who live together in the same dwelling unit(s), who acknowledge one adult male or female as head of household, who share the same housekeeping arrangements, and are considered as one unit. A member of the household is any person who usually lives in the household and a visitor is someone who is not a usual member of the household but had slept in the household the night before the interview date. The household population presented in this chapter includes, unless otherwise stated, all usual members of the household who slept in the household the night before the survey and visitors (de facto population). 9 CHAPTER 2 CHARACTERISTICS OF HOUSEHOLDS AND RESPONDENTS Vane Nyong’a and George Bicego This chapter presents information on social and economic characteristics of the household population and the individual survey respondents, such as: age, sex, education, patterns of employment, and place of residence. It also examines the environmental profile of households in the KDHS sample. Taken together, these descriptive data provide a context for the interpretation of demographic and health indices, and can furnish an approximate indication of the representativeness of the survey. The background characteristics of women age 15-49 and men age 15-54 are discussed in the last part of the chapter. This information is useful for understanding the factors which affect health-seeking behaviours and contraceptive use. 2.1 Household Population The KDHS household questionnaire was used to collect data on the demographic and social characteristics of all usual residents of the sampled household and visitors who had spent the previous night in the household.1 2.1.1 Age-Sex Composition The distribution of the KDHS household population is shown in Table 2.1, by five-year age groups, according to sex and urban-rural residence. The KDHS households constitute a population of 36,169 persons. Fifty-one percent of the population are females and 49 percent are males. There are more persons in the younger age groups than in the older age groups of each sex in both urban and rural areas. The age-sex structure of the population can be understood by use of a population pyramid (see Figure 2.1). The Kenya pyramid is wide-based, a pattern that is typical of high-fertility populations. The number of children under age five is less than the number age 5-9, which is slightly less than the number age 10-14, a finding that is consistent with recent fertility decline (see Chapter 3 for details). 10 Table 2.1 Household population by age, residence and sex Percent distribution of the de facto household population by five-year age group, according to urban-rural residence and sex, Kenya 1998 ____________________________________________________________________________________________________ Urban Rural Total _______________________ _______________________ _______________________ Age group Male Female Total Male Female Total Male Female Total ____________________________________________________________________________________________________ 0-4 5-9 10-14 15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59 60-64 65-69 70-74 75-79 80 + Missing/Don't know Total Number 13.4 13.1 13.2 15.6 14.1 14.8 15.2 13.9 14.5 12.1 11.4 11.7 17.1 15.2 16.1 16.1 14.5 15.3 9.1 11.9 10.4 17.6 16.6 17.1 15.9 15.8 15.8 9.1 12.5 10.8 11.1 9.9 10.5 10.7 10.4 10.5 10.2 14.1 12.1 6.7 7.5 7.1 7.4 8.6 8.0 12.6 12.1 12.4 5.1 6.8 6.0 6.6 7.7 7.2 9.5 7.4 8.5 4.8 4.9 4.9 5.7 5.4 5.5 7.9 6.6 7.2 4.3 5.4 4.9 5.0 5.6 5.3 5.3 3.1 4.2 3.5 3.8 3.6 3.8 3.7 3.7 3.8 2.8 3.3 3.1 2.7 2.9 3.3 2.7 3.0 3.1 2.4 2.8 2.3 3.6 3.0 2.4 3.4 2.9 1.7 1.2 1.4 2.4 2.9 2.7 2.3 2.6 2.4 1.1 0.5 0.8 2.2 2.2 2.2 1.9 1.9 1.9 0.5 0.4 0.4 1.5 1.9 1.7 1.3 1.7 1.5 0.5 0.4 0.4 1.3 1.1 1.2 1.2 1.0 1.1 0.3 0.1 0.2 0.6 0.6 0.6 0.6 0.5 0.5 0.0 0.2 0.1 0.7 0.6 0.7 0.5 0.6 0.6 0.1 0.2 0.1 0.1 0.1 0.1 0.1 0.1 0.1 .100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 .3,484 3,229 6,714 14,204 15,239 29,456 17,689 18,468 36,1691 _____________________________________________________________________________________________________ 1 Total includes 12 persons for whom sex is missing Figure 2.1 Population Pyramid of Kenya 80+ 75-79 70-74 65-69 60-64 55-59 50-54 45-49 40-44 35-39 30-34 25-29 20-24 15-19 10-14 5-9 0-4 0246810 0 2 4 6 8 10 Percent Male Female KDHS 1998 Age 2 The dependency ratio is defined as the sum of all persons age under 15 years or over 64 years divided by the number of persons age 15-64, multiplied by 100. 11 Table 2.2 Population by age from selected sources Percent distribution of the de facto household population by age group at different dates, Kenya 1989, 1993, 1998 ___________________________________________________ 1989 1993 1998 Age group KDHS KDHS KDHS ____________________________________________________ < 15 52.5 49.1 45.7 15-64 44.0 47.0 50.6 64+ 3.5 3.6 3.7 Missing/Don’t know 0.0 0.3 0.1 Median age NA 15.3 16.9 ____________________________________________________ NA = Not applicable Table 2.3 Household composition Percent distribution of households by sex of head of household, household size, and presence of foster children, according to urban-rural residence and province, Kenya 1998 ______________________________________________________________________________________________________ Province Residence _____________________________________________________ ______________ Rift Characteristic Urban Rural Nairobi Central Coast Eastern Nyanza Valley Western Total ______________________________________________________________________________________________________ Household headship Male Female Number of usual members 1 2 3 4 5 6 7 8 9+ Total Mean size Percent with foster children 1 76.8 65.6 80.4 63.6 68.3 64.9 65.5 72.4 64.6 68.3 23.2 34.4 19.6 36.4 31.7 35.1 34.5 27.6 35.4 31.7 26.3 12.5 26.9 20.9 19.0 11.7 11.8 14.7 11.8 15.8 17.6 11.2 20.4 15.5 14.2 10.6 11.9 10.2 10.6 12.7 14.1 13.3 13.6 15.7 13.1 13.0 13.4 11.7 14.9 13.5 14.3 14.9 14.5 17.3 12.1 14.5 13.4 15.3 15.0 14.7 11.7 14.1 12.2 11.4 10.6 14.1 16.2 13.4 14.1 13.5 7.0 12.2 6.7 9.2 9.2 12.0 12.7 11.8 12.1 11.0 3.5 9.1 2.4 5.1 7.2 9.3 9.1 9.3 8.9 7.8 2.5 5.7 1.6 3.0 5.5 5.9 6.7 5.1 5.3 4.9 2.9 7.0 1.4 1.5 9.0 9.0 4.7 8.6 6.9 6.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 3.3 4.6 3.1 3.5 4.4 4.8 4.5 4.6 4.5 4.3 8.1 17.6 5.7 9.5 15.2 13.4 19.0 16.8 24.9 15.3 ______________________________________________________________________________________________________ Note: Table is based on de jure members; i.e., usual residents.1 Foster children are children under age 15 living in households with neither their mother nor their father present. Table 2.2 shows the change in the age structure of Kenya’s population by comparing the proportion of persons in broad age groups from the 1989 KDHS, the 1993 KDHS, and the 1998 KDHS. The proportion of the population under 15 years of age has fallen from 53 percent in 1989 to 49 percent in 1993 to 46 percent in 1998. As a result of this shift, the dependency ratio2 in Kenya has dropped from 127 in 1989 to 112 in 1994 to 98 in 1998. This means that, currently, there is slightly less than one person under 15 years or over 64 years in Kenya for every person age 15- 64 years. 2.1.2 Household Composition Table 2.3 shows that about one in three Kenyan households is headed by a female. There is a larger proportion of female-headed households in rural areas (34 percent) than in urban areas (23 percent). There is not much variation in this indicator by province, although households in Nairobi and Rift Valley provinces are less likely than households in the other provinces to be headed by a woman. 12 Table 2.4 Fosterhood and orphanhood Percent distribution of de jure children under age 15 by survival of parents and child's living arrangements, according to child's age, sex, residence, and province, Kenya 1998 ______________________________________________________________________________________________________ Living Living with mother with father but not father but not mother Not living with either parent Missing Living ____________ _____________ __________________________ infor- with Father Mother mation Number Background both Father Father Mother Mother Both only only Both on father/ of characteristic parents alive dead alive dead alive alive alive dead mother Total children ______________________________________________________________________________________________________ Age <2 3-5 6-9 10-14 Sex Male Female Residence Urban Rural Province Nairobi Central Coast Eastern Nyanza Rift Valley Western Total 65.0 25.8 3.0 0.5 0.1 1.9 0.3 0.3 0.1 3.1 100.0 3,190 62.0 21.6 3.2 2.1 0.7 6.0 0.6 0.3 0.5 3.1 100.0 2,998 56.8 19.4 6.3 2.8 1.1 8.2 0.9 1.2 0.8 2.5 100.0 4,500 52.5 18.0 7.6 3.1 1.5 9.5 1.2 1.8 1.6 3.3 100.0 5,710 58.8 20.6 5.7 2.6 1.0 6.3 0.8 0.9 0.8 2.6 100.0 8,311 56.9 20.5 5.4 2.1 0.9 7.8 0.9 1.2 1.0 3.4 100.0 8,078 62.2 18.6 3.5 4.3 1.3 4.9 0.7 1.1 0.7 2.5 100.0 2,362 57.1 20.9 5.9 2.0 0.9 7.4 0.8 1.0 0.9 3.1 100.0 14,035 69.4 12.9 3.9 1.9 2.4 3.9 1.1 0.9 0.6 3.0 100.0 809 54.0 29.4 3.1 0.8 0.9 5.4 0.1 0.5 0.5 5.5 100.0 1,813 51.6 24.4 5.9 2.5 1.1 9.7 0.7 1.3 1.2 1.7 100.0 1,162 56.4 24.5 5.6 2.1 1.3 4.8 0.7 1.2 0.4 3.0 100.0 2,770 58.7 15.4 8.8 2.4 1.1 6.2 1.0 1.2 1.5 3.6 100.0 3,446 62.1 18.7 5.1 2.0 0.6 6.9 0.5 0.7 0.7 2.7 100.0 4,227 52.7 20.5 3.6 4.5 0.3 12.5 2.1 1.7 0.9 1.2 100.0 2,171 57.9 20.5 5.5 2.3 1.0 7.0 0.8 1.1 0.9 3.0 100.0 16,397 ______________________________________________________________________________________________________ Note: By convention, foster children are those who are not living with either biological parent. This includes orphans, i.e., children with both parents dead. The average size of a Kenyan household has decreased from 4.8 persons in the 1993 KDHS to 4.3 persons in the 1998 KDHS. Urban households are on average smaller (3.3 persons) than rural households (4.6 persons). There is considerable variation in household size across provinces, with the largest occurring in Eastern Province (4.8 persons) and the smallest in Nairobi (3.1 persons). Fifteen percent of households have foster children—8 percent of households in urban areas and 18 percent of households in rural areas. Foster children are those persons under 15 years of age who have neither natural parent in the household. Information regarding fosterhood and orphanhood of children under age 15 is provided in Table 2.4. About 58 percent of children under 15 years of age are living with both their parents, 26 percent are living with their mother (but not with their father), 3 percent with their father (but not their mother), and 10 percent are living with neither parent. Among children under age 15 years, 8 percent have lost their fathers, 3 percent have lost their mothers, and about 1 percent of children have lost both of their parents. 2.1.3 Educational Level of Household Members Table 2.5 shows the distribution of female and male household members (age 6 and above) by the highest level of education attended (even if they did not complete that level), and the median number of years of education completed, according to age and residence. Generally, educational attainment is higher for 13 Table 2.5 Educational level of the female and male household population Percent distribution of the de facto female and male household population age six and over by highest level of education attended, and median number of years of schooling, according to selected background characteristics, Kenya 1998 ___________________________________________________________________________________________________________ Level of education Number Median _________________________________________________ of number Background No Primary Primary Second- Don’t know/ women/ of years of characteristic education incomplete complete ary + missing Total men schooling ____________________________________________________________________________________________________________ FEMALE ___________________________________________________________________________________________________________ Age 6-9 10-14 15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59 60-64 65+ Residence Urban Rural Province Nairobi Central Coast Eastern Nyanza Rift Valley Western Total 16.2 82.8 0.0 0.1 0.9 100.0 2,171 0.0 5.0 91.4 2.4 1.0 0.1 100.0 2,916 3.4 3.4 56.7 17.9 18.8 0.0 100.0 1,912 6.4 5.3 32.4 25.8 36.5 0.0 100.0 1,594 7.5 7.2 36.9 20.3 35.3 0.3 100.0 1,425 7.3 8.6 25.9 29.7 35.5 0.3 100.0 990 6.6 19.2 29.0 24.2 27.6 0.1 100.0 1,031 6.1 31.1 27.6 20.1 20.2 1.0 100.0 676 4.2 40.4 30.8 15.7 12.6 0.5 100.0 507 2.6 57.3 20.4 11.9 8.7 1.7 100.0 633 0.0 66.1 24.2 5.2 3.0 1.5 100.0 477 0.0 73.0 20.8 1.9 1.8 2.4 100.0 345 0.0 83.7 10.5 1.5 0.8 3.6 100.0 696 0.0 9.4 37.6 16.4 36.2 0.4 100.0 2,726 6.9 21.5 54.1 12.2 11.6 0.7 100.0 12,667 3.5 4.5 33.7 18.8 42.6 0.3 100.0 1,076 7.4 17.1 48.4 17.7 16.4 0.3 100.0 1,919 4.7 36.0 38.6 11.8 12.5 1.1 100.0 1,120 1.7 20.9 51.1 14.4 13.3 0.4 100.0 2,716 3.7 17.5 59.3 9.1 13.3 0.7 100.0 3,284 3.7 20.9 53.3 11.9 13.0 0.9 100.0 3,430 3.8 18.3 53.4 11.7 16.2 0.5 100.0 1,847 3.7 19.3 51.2 12.9 15.9 0.6 100.0 15,3931 4.1 ____________________________________________________________________________________________________________ MALE ___________________________________________________________________________________________________________ Age 6-9 10-14 15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59 60-64 65+ Residence Urban Rural Province Nairobi Central Coast Eastern Nyanza Rift Valley Western Total 16.8 82.3 0.0 0.1 0.8 100.0 2,347 0.0 3.5 94.5 1.2 0.7 0.1 100.0 2,815 3.1 2.7 59.4 14.6 16.5 0.2 100.0 1,896 6.4 2.7 26.9 28.4 41.8 0.2 100.0 1,304 7.7 3.2 26.6 20.8 49.1 0.2 100.0 1,169 7.9 4.2 14.9 31.6 49.1 0.2 100.0 1,010 7.8 4.4 17.3 27.5 49.9 0.9 100.0 885 7.7 9.4 17.0 28.5 44.1 1.0 100.0 674 6.9 13.4 22.7 25.8 37.9 0.2 100.0 578 6.7 13.3 25.2 31.7 27.7 2.0 100.0 432 6.6 27.4 31.8 24.4 15.2 1.1 100.0 404 3.9 34.4 39.0 14.1 11.0 1.5 100.0 343 3.1 59.1 30.1 3.6 3.6 3.6 100.0 626 0.0 5.5 31.3 16.4 46.1 0.7 100.0 2,931 7.6 11.6 56.8 14.3 16.6 0.6 100.0 11,567 4.1 3.6 26.0 15.3 54.6 0.4 100.0 1,252 8.9 6.9 50.4 18.9 23.1 0.7 100.0 1,758 5.5 17.7 43.5 16.2 21.6 0.9 100.0 1,067 4.8 11.7 56.8 14.6 16.2 0.8 100.0 2,466 4.2 7.1 58.8 13.9 19.7 0.6 100.0 2,914 4.7 13.8 52.3 13.7 19.6 0.7 100.0 3,438 4.4 11.2 56.5 12.6 19.3 0.4 100.0 1,603 3.9 10.4 51.7 14.7 22.6 0.7 100.0 14,4991 5.0 ___________________________________________________________________________________________________ 1 Includes 20 women and 16 men for whom age is missing 14 Table 2.6 School enrolment Percentage of the de facto household population age 6-24 years enrolled in school, by age, sex, and residence, Kenya 1998 ____________________________________________________________________________________________________ Male Female Total _________________________ _________________________ _________________________ Age Urban Rural Total Urban Rural Total Urban Rural Total ____________________________________________________________________________________________________ 6-10 11-15 6-15 16-20 21-24 86.2 81.3 82.0 84.5 82.2 82.5 85.4 81.8 82.3 87.8 90.2 89.9 77.7 88.3 86.9 82.3 89.2 88.4 86.9 85.5 85.7 81.2 85.1 84.6 84.0 85.3 85.2 38.2 48.9 46.8 21.8 39.9 35.4 28.9 44.5 41.0 6.4 9.3 8.5 3.9 3.6 3.7 5.0 6.1 5.8 males than females, although this varies substantially by age. About 90 percent of males have attended school at some time versus 81 percent of females. The percentage of children in the youngest age group (6-9 years) who never attended school is difficult to interpret since some children not yet attending will eventually go to school (i.e., late beginners). Comparing children ages 10-14 and 15-19, the percentage who never attended school has increased, suggesting that education prospects for both boys and girls have not improved and perhaps have worsened over the last decade. While most Kenyans attend school, only a small proportion are able to continue to higher levels of education. The median number of years of schooling completed for females and males is 4 and 5 years, respectively. Sixteen percent of females and 23 percent of males have reached the secondary level of education. An encouraging long-term trend toward increasing educational attainment is observed by looking at differences among age groups in the median number of years completed. The median educational attainment peaks at over seven completed years for females (age 20-24) and about eight years for males (25-29). This trend, however, captures patterns occurring several years before the survey, and is not sensitive to recent changes. As expected, educational attainment is greater in urban than rural areas. The median number of completed years of education is highest in Nairobi and Central Provinces (both males and females), and lowest in the Coast Province (females) and Western Province (males). One way to assess more recent trends in educational attainment is to compare the 1993 and 1998 KDHS surveys with regard to the percentage of males and females age 15-19 who have completed primary school. Between 1993 and 1998, the percentage of females age 15-19 who have completed primary school has declined from 56 to 40 percent. For males age 15-19, the percentage has decreased from 52 to 38 percent. These results reflect a disinvestment in Kenya’s future. 2.1.4 School Enrolment In Table 2.6, school enrolment ratios by age group, sex, and residence for the population age 6 to 24 years are presented. A school enrolment ratio is the number of enrolled persons in a specific age group per hundred persons in that particular age group. Eighty-five percent of persons age 6-15 are in school; rural enrolment is about the same (85 percent) as urban enrolment (84 percent). There is a significantly higher enrolment ratio in rural areas (45 percent) than in urban areas (29 percent) for the age group 16-20 years. This is explained largely by the fact that individuals tend to enroll and advance to the next school level at older ages in rural areas. By age 21-24, urban and rural areas have comparable enrolment ratios at 5-6 percent. 3 Ventilated, improved pit toilet or latrine. 15 Figure 2.2 shows that the rate of school entrance is nearly the same for boys as for girls, but that girls tend to drop out earlier than boys. About 82 percent of both girls and boys are enrolled at age 6-10, and 87 to 90 percent at age 11-15, but by age 16-20 only 35 percent of Kenyan females are still in school versus 47 percent of males. By age 21-24, 4 percent of women and 9 percent of men are still in school. 2.2 Housing Characteristics Information on the characteristics of sampled households is shown in Table 2.7. The physical characteristics of the household have an important effect on environmental exposure to disease, as well as reflecting the household’s economic condition. Fifteen percent of the households in Kenya have electricity, up from 11 percent based on the 1993 KDHS. There is a significant difference in access to electricity between rural and urban areas. Forty-eight percent of urban households have electricity compared with just 4 percent of rural households. About 23 percent of households have water piped into the residence, yard, or plot: 58 percent of households in urban areas and 12 percent in rural areas. In rural areas, natural (but often contaminated) water sources (e.g., rivers, streams, lakes, ponds) are the main source of drinking water (55 percent), followed by public wells (15 percent). The median time to get to the source of drinking water is 15 minutes in rural areas and less than a minute in urban areas. About 85 percent of Kenyan households have access to some type of toilet facility. The most common type of toilet in rural areas is the traditional pit latrine (73 percent); in urban areas, 43 percent of households use a flush toilet, 42 percent use a traditional pit latrine, and 11 percent use a Blair toilet.3 Figure 2.2 Percentage of Males and Females Enrolled in School by Age 6-10 11-15 16-20 21-24 Age in Years 0 20 40 60 80 100 Percent Male Female KDHS 1998 16 Table 2.7 Housing characteristics Percent distribution of households by housing characteristics, according to urban-rural residence and province, Kenya 1998 ______________________________________________________________________________________________________ Province Residence _____________________________________________________ ______________ Rift Characteristic Urban Rural Nairobi Central Coast Eastern Nyanza Valley Western Total ______________________________________________________________________________________________________ Electricity No Yes Missing/Don't know Total Source of drinking water Piped into residence Public tap Well in residence Public well River, stream Pond, lake Rainwater Other Total Time to water source (in minutes) <15 minutes Median time to source Sanitation facility Own flush toilet Shared flush toilet Traditional pit toilet Vent. improved pit latrine No facility Other Missing/Don’t know Total Main floor material Mud, sand, dung Wood planks Polished wood/vinyl/tiles Cement Other Missing/Don’t know Total Persons per sleeping room 1-2 3-4 5-6 7+ Missing/Don’t know Total Mean Total 47.5 4.3 60.1 11.4 22.7 6.3 7.0 9.0 7.1 14.5 52.2 95.4 39.9 87.9 76.5 93.5 92.8 90.5 92.9 85.1 0.3 0.3 0.0 0.6 0.8 0.1 0.2 0.5 0.0 0.3 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 58.2 12.3 77.6 30.9 21.3 17.5 5.9 18.1 13.4 23.2 25.9 6.3 14.5 6.5 33.9 12.1 6.6 9.1 8.1 11.0 3.3 8.6 1.2 13.6 4.6 1.9 3.9 15.2 4.9 7.3 3.5 14.9 0.2 5.1 15.5 18.1 18.0 8.4 18.9 12.2 3.5 49.3 0.4 34.9 17.8 43.8 52.7 42.5 50.1 38.4 0.1 5.5 0.0 3.2 3.7 4.1 10.3 3.5 0.7 4.2 0.4 1.6 0.0 2.8 0.3 1.1 0.9 2.4 0.6 1.3 4.9 1.2 6.1 2.5 2.6 1.2 1.5 0.5 3.3 2.1 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 82.9 43.8 95.1 66.5 46.0 37.2 35.4 56.5 48.9 53.1 0.0 14.8 0.0 2.2 14.3 19.8 19.7 9.4 14.1 9.7 24.7 1.5 26.9 2.8 9.1 3.8 3.1 5.8 6.4 7.0 18.3 0.6 29.1 1.8 4.4 1.1 0.5 3.5 2.0 4.8 42.3 73.3 29.7 85.3 50.1 69.8 67.4 62.8 82.2 65.9 10.7 5.7 13.2 9.0 8.8 6.3 4.7 5.2 5.1 6.9 2.6 18.6 0.8 0.6 26.9 18.8 24.2 20.7 4.3 14.8 1.0 0.1 0.0 0.0 0.0 0.1 0.0 1.2 0.0 0.3 0.3 0.3 0.2 0.4 0.7 0.1 0.2 0.8 0.0 0.3 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 20.0 76.9 16.7 62.1 50.9 65.0 78.0 67.8 79.2 63.4 0.8 1.1 0.4 4.1 0.2 0.4 0.8 0.9 0.0 1.0 5.5 0.5 8.6 1.0 1.0 0.0 0.3 2.0 0.8 1.7 73.7 21.2 74.3 32.0 47.6 34.6 20.9 28.9 19.9 33.6 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.0 0.1 0.3 0.0 0.8 0.3 0.1 0.2 0.3 0.0 0.2 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 63.2 56.9 63.7 76.1 66.6 60.7 55.2 48.3 48.1 58.4 25.7 27.4 26.1 17.6 23.9 27.1 28.4 30.9 31.5 27.0 8.6 9.8 9.2 3.6 6.2 8.6 10.8 12.6 12.6 9.5 1.6 5.2 0.8 0.8 2.1 3.4 5.1 7.2 7.6 4.3 1.0 0.7 0.2 1.9 1.3 0.2 0.6 1.1 0.1 0.8 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 2.4 2.8 2.4 2.0 2.4 2.7 2.9 3.1 3.2 2.7 1,988 6,393 856 1,188 605 1,303 1,643 1,827 959 8,380 17 Table 2.8 Household durable goods Percentage of households possessing selected durable consumer goods, by urban-rural residence and province, Kenya 1998 ______________________________________________________________________________________________________ Province Residence _____________________________________________________ ______________ Rift Durable goods Urban Rural Nairobi Central Coast Eastern Nyanza Valley Western Total ______________________________________________________________________________________________________ Radio 78.2 58.4 79.2 68.9 56.9 59.9 54.5 61.9 67.0 63.1 Television 33.4 6.7 38.1 13.1 15.1 8.8 6.8 11.8 8.0 13.0 Telephone 9.1 0.7 11.2 1.8 3.5 0.9 1.2 1.9 2.5 2.7 Refrigerator 13.3 0.8 16.7 2.4 8.2 0.7 1.3 2.3 2.4 3.8 Bicycle 15.3 26.6 11.0 18.2 18.6 28.7 25.7 22.8 38.6 23.9 Motorcycle 1.8 0.6 2.2 0.9 1.1 0.7 0.3 1.1 0.4 0.9 Private car 12.2 2.5 15.3 4.0 3.3 2.4 2.8 5.5 2.8 4.8 None of the above 20.0 36.4 19.3 29.3 37.8 35.3 38.8 34.4 26.7 32.5 Number of households 1,988 6,392 856 1,188 604 1,303 1,643 1,827 959 8,380 The most commonly used flooring materials in Kenya are earth/sand/dung, followed by cement. Almost three-quarters of urban households have cement floors, while about the same proportion of rural households have floors made of packed earth, sand, or occasionally dung. A question on the number of rooms used for sleeping by households was included in the KDHS questionnaire. This information provides a rough measure of household crowding. The results indicate that, in the average household, 2.7 persons sleep together per sleeping room, with only a small urban-rural differential observed. Of the rural-based provinces, sleeping arrangements are most crowded in Western and Rift Valley provinces (more than 3 persons per room) and least crowded in Central Province (2 persons per room). 2.2.1 Household Durable Goods Table 2.8 shows the percentage of households owning certain durable goods by residence. The availability of durable consumer goods is a rough measure of household socioeconomic status. Among selected durable goods, a radio is available in 63 percent of the households and a bicycle in 24 percent of the households. The percentage of households that have a television has more than doubled from 6 percent in the 1993 KDHS to 13 percent in 1998. The proportion of households with durable goods varies by urban-rural residence. For example, 78 percent of households in urban areas have a radio compared with 58 percent of rural households, and 33 percent of urban households enjoy a television compared with just 7 percent of rural households. On the whole, 36 percent of rural households and 20 percent of urban households have none of the selected durable goods. 2.3 Characteristics of Survey Respondents 2.3.1 Background Characteristics Background characteristics of the 3,407 men and 7,881 women interviewed in the KDHS are presented in Table 2.9. The distribution of the respondents according to age shows a similar pattern for males and females. The proportion of the respondents in each age group declines with increasing age for 18 Table 2.9 Background characteristics of respondents Percent distribution of women and men by selected background characteristics, Kenya 1998 ______________________________________________________________________________________ Number of women Number of men __________________ __________________ Background Weighted Un- Weighted Un- characteristic percent Weighted weighted percent Weighted weighted ______________________________________________________________________________________ Age 15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 Residence Urban Rural Province Nairobi Central Coast Eastern Nyanza Rift Valley Western Marital status Never married Married Living together Widowed Divorced Not living together Education No education Primary incomplete Primary complete Secondary+ Secondary incomplete Secondary complete Higher Currently attending school Yes No Religion Catholic Protestant/other Christian Muslim No religion Other religion Missing Ethnic group Kalenjin Kamba Kikuyu Kisii Luhya Luo Masai Meru/Embu Mijikenda/Swahili Somali Taita/Taveta Other Missing Total 23.5 1,851 1,852 23.8 811 831 19.6 1,548 1,542 17.3 589 596 17.4 1,371 1,344 13.6 463 458 12.5 986 977 12.3 418 404 12.6 991 999 11.0 375 382 8.1 637 643 8.5 291 288 6.3 497 524 8.2 278 272 - - - 5.4 183 176 23.2 1,830 1,466 26.8 913 656 76.8 6,051 6,415 73.2 2,494 2,751 9.8 770 419 12.7 431 168 10.6 834 787 10.0 341 307 7.7 605 1,226 7.1 242 532 17.6 1,386 1,186 18.6 633 553 21.5 1,690 1,390 18.8 641 542 21.5 1,696 1,977 22.3 758 919 11.4 899 896 10.6 361 386 30.1 2,372 2,375 43.7 1,489 1,518 58.8 4,630 4,631 51.5 1,756 1,719 2.6 203 216 1.0 35 44 3.7 289 299 0.6 21 21 1.8 141 135 0.6 21 22 3.1 246 225 2.5 85 83 11.5 909 1,010 3.8 131 136 36.7 2,893 2,903 30.7 1,047 1,108 22.5 1,777 1,816 24.7 841 862 29.2 2,302 2,152 40.7 1,388 1,301 11.3 890 884 12.8 436 447 15.6 1,229 1,120 23.7 808 741 2.3 183 148 4.2 144 113 12.7 1,003 1,018 15.8 537 542 86.9 6,851 6,833 82.2 2,801 2,792 27.7 2,186 2,128 30.4 1,036 1,003 64.5 5,083 5,026 58.2 1,983 2,005 5.1 399 444 4.7 160 179 1.8 145 214 5.6 192 188 0.8 60 57 0.8 29 26 0.1 9 12 0.2 8 6 12.6 992 1,316 11.7 399 549 12.8 1,008 855 13.0 441 385 17.9 1,414 1,255 18.6 634 522 10.9 860 645 10.1 345 255 14.5 1,142 1,117 14.8 504 518 13.6 1,074 959 13.0 441 404 1.4 113 70 1.6 53 32 7.2 564 503 8.3 284 253 5.0 391 633 4.1 139 234 0.2 16 19 0.4 14 8 1.0 81 291 1.0 34 135 2.8 218 210 3.3 111 106 0.1 7 8 0.2 8 6 100.0 7,881 7,881 100.0 3,407 3,407 19 both sexes. About 43 percent of the women and 41 percent of the men are in the age range 15 to 24 years, 26 percent of females and 30 percent of males are in the 25 to 34 year age range, and the rest of the respondents are in the age groups 35 to 49 years (women) and 35-54 years (men). The proportion of males in urban areas (27 percent) is larger than that of females (23 percent). This is expected since men are more likely to migrate to cities and towns in search of work. For both sexes, the largest proportion of the population is in Rift Valley and Nyanza provinces, whilst the smallest proportion is in Coast Province. Fifty-nine percent of females compared with 52 percent of males are currently married. Male respondents were much more likely than female respondents to have never married. The proportion of women who have never been to school is three times greater than that for men (12 versus 4 percent). Male respondents were also much more likely to reach secondary school (41 percent) than their female counterparts (29 percent), and nearly twice as likely to continue school beyond the secondary level. Table 2.9 also shows that with respect to religion, the large majority of the both male and female respondents reported themselves as Christians (one-third of which were Roman Catholic). Five percent of respondents (males and females) reported their religion as Muslim. Men (6 percent) were more likely than women (2 percent) to report that they had no religion. The KDHS also collected information on ethnic affiliation of the respondent. The Kikuyu are the most numerous group in Kenya, followed closely by the other major ethnic groups: Luhya, Luo, Kamba, and Kalenjin. 2.3.2 Educational level of survey respondents Presented in Table 2.10 are the percent distributions of female and male respondents by highest level of education attended according to age, urban-rural residence, and province. Younger people have attended school to higher levels than older people. The majority of men (60 percent) and nearly one-half of women in urban areas have attended at least some secondary school, while the large majority of people in rural Kenya have not gone beyond the primary level of education. Among the rural-based provinces, Central Province has the largest proportion of men and women who have attended secondary school or above. As described above, the educational level of women in Coast Province is much lower than that of women in other provinces. 20 Table 2.10 Level of education Percent distribution of women and men by the highest level of education attended, according to selected background characteristics, Kenya 1998 ________________________________________________________________________________________________________________ Highest level of education: women Highest level of education: men ________________________________________ ________________________________________ Primary Primary Number Primary Primary Background No edu- incom- com- of No edu- incom- com- Number characteristic cation plete plete Secondary+ Total women cation plete plete Secondary+ Total of men _________________________________________________________________________________________________________________ Age 15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 Residence Urban Rural Province Nairobi Central Coast Eastern Nyanza Rift Valley Western Total 2.9 55.3 18.5 23.3 100.0 1,851 1.8 55.5 15.4 27.3 100.0 811 4.4 32.6 26.2 36.7 100.0 1,548 1.4 26.8 27.2 44.6 100.0 589 7.0 36.1 20.4 36.6 100.0 1,371 2.6 25.7 20.0 51.7 100.0 463 8.8 27.1 29.1 35.0 100.0 986 3.7 16.7 33.5 46.1 100.0 418 19.8 28.7 24.3 27.1 100.0 991 2.0 18.6 28.2 51.2 100.0 375 31.4 27.5 21.3 19.8 100.0 637 6.3 16.7 32.0 44.9 100.0 291 41.9 28.5 17.0 12.5 100.0 497 12.7 26.6 25.2 35.4 100.0 278 S - - - - - 10.6 31.6 29.8 28.1 100.0 183 5.5 22.5 22.7 49.4 100.0 1,830 2.3 15.0 23.1 59.6 100.0 913 13.4 41.0 22.5 23.1 100.0 6,051 4.4 36.5 25.3 33.9 100.0 2,494 1.2 21.0 23.4 54.4 100.0 770 1.8 13.7 19.0 65.5 100.0 431 4.7 29.1 32.0 34.2 100.0 834 1.5 22.1 34.6 41.8 100.0 341 30.6 26.5 21.8 21.1 100.0 605 7.5 26.7 27.6 38.1 100.0 242 10.0 39.3 25.7 25.1 100.0 1,386 2.8 41.0 26.4 29.8 100.0 633 10.7 47.2 16.6 25.4 100.0 1,690 2.2 37.2 21.0 39.6 100.0 641 14.5 39.2 21.7 24.6 100.0 1,696 6.6 29.9 26.0 37.4 100.0 758 12.2 35.7 21.6 30.5 100.0 899 4.9 34.2 20.6 40.4 100.0 361 11.5 36.7 22.5 29.2 100.0 7,881 3.8 30.7 24.7 40.7 100.0 3,407 2.3.3 Reasons for Leaving School Among women age 15-24 years who had ever attended school but were not currently attending, the KDHS asked why they had left school. One of most important determinants of a woman’s social and economic status is her educational level. Knowledge of the reasons why women leave school can provide guidance for policies designed to enhance women’s status. Table 2.11 shows the percent distribution of women age 15-24 years who were no longer attending school by their reported reason for leaving school, according to highest level of education attended. The most common reason for leaving school was the family could not pay the school fees (42 percent). This pattern is especially marked for those women who left after having completed primary school (i.e., have not advanced to secondary school). Once women start attending secondary school, school costs are still the primary problem for leaving, but other reasons become more important. For those women who finished their education while still in secondary school, a prominent reason for leaving is pregnancy or marriage. For those who left after having completed secondary school, the main reason cited is that she had “had enough” school. Women in rural areas are much more likely than their urban counterparts to have reported that they left school because of pregnancy or marriage (not shown). 21 Table 2.11 Reasons for leaving school Percent distribution of women age 15-24 who had ever attended school but were not currently attending by reason for leaving school, according to highest level of education attended, Kenya 1998 _________________________________________________________________________________ Highest level of education _____________________________________________ Reason stopped Primary Primary Secondary Secondary attending school incomplete complete incomplete complete Higher Total _________________________________________________________________________________ Got pregnant 11.3 8.7 30.8 1.1 (0.0) 9.9 Got married 11.4 6.4 8.4 3.8 (5.5) 8.1 Take care of children 1.1 0.3 0.0 0.0 (0.0) 0.5 Family needed help 1.0 0.1 0.3 0.2 (0.0) 0.5 Could not pay school fees 47.6 59.7 48.7 4.3 (0.0) 42.2 Need to earn money 1.0 0.4 0.3 2.2 (0.0) 1.0 Graduated, enough 2.4 8.5 1.8 84.4 (86.1) 21.4 Did not pass exams 1.4 4.1 0.0 1.7 (0.0) 2.1 Did not like school 13.5 8.1 4.4 0.3 (0.0) 8.4 School not accessible 0.5 0.0 0.0 0.0 (0.0) 0.2 Other 7.9 2.4 2.9 0.3 (0.0) 4.3 Don’t know/missing 0.9 1.3 2.3 1.7 (8.4) 1.4 Total 100.0 100.0 100.0 100.0 100.0 100.0 Number 938 677 184 450 27 2,276 ___________________________________________________________________________________ Note: Figures in parentheses are based on 25-49 cases. 2.3.4 Access to Mass Media Table 2.12 shows the percentage of male and female respondents exposed to different types of mass communication media by age, urban-rural residence, province, and educational level. It is important to know which types of persons are more or less likely to be reached by the media for purposes of planning programmes intended to spread information about health and family planning. About 37 percent of the women and 61 percent of men read newspapers or magazine weekly, 26 percent of women and 46 percent of men watch television at least once a week, and 58 percent of women and 81 percent of men listen to radio every day. Fifteen percent of women and one-third of men are exposed to all three of these media sources. Thirty percent of women and 10 percent of men have no access to mass media. The proportion of persons with no access to mass media is about three times higher in rural areas than in urban areas. The rural disadvantage is much less pronounced regarding radio listening than for TV viewing or newspaper reading (Figure 2.3). The less-educated men and women tended to have much less exposure to media outlets. Among rural-based provinces, women in Nyanza Province were the least likely to have access to the media. Since the 1993 KDHS, the percentage of women exposed regularly to television has gone up sharply (15 to 26 percent) while the percentage listening daily to the radio has declined (65 to 58 percent). 22 Table 2.12 Access to mass media Percentage of women and men who usually read a newspaper once a week, watch television once a week, or listen to radio weekly, by selected background characteristics, Kenya 1998 _________________________________________________________________________________ Mass media ____________________________________ No Read Watch Listen to All Number Background mass newspaper television radio three of characteristic media weekly weekly daily media women _________________________________________________________________________________ FEMALE _________________________________________________________________________________ Age 15-19 20-24 25-29 30-34 35-39 40-44 45-49 Residence Urban Rural Province Nairobi Central Coast Eastern Nyanza Rift Valley Western Education No education Primary incomplete Primary complete Secondary+ Total 30.6 41.6 27.1 51.2 14.2 1,851 24.8 44.6 28.1 62.4 17.7 1,548 25.8 40.7 27.3 63.8 16.7 1,371 30.7 37.0 27.0 60.8 18.1 986 34.8 27.5 24.4 57.7 12.0 991 36.8 23.8 18.0 56.7 9.9 637 39.7 20.7 18.4 53.4 8.5 497 12.2 61.6 57.3 71.6 37.4 1,830 35.7 29.5 16.1 54.1 8.0 6,051 10.7 61.8 67.3 70.9 42.0 770 25.5 36.8 22.0 66.8 12.7 834 31.0 36.7 34.5 57.1 19.2 605 32.4 38.0 18.6 54.9 11.1 1,386 43.5 30.1 12.2 43.4 6.8 1,690 28.1 38.5 29.4 60.8 16.6 1,696 26.6 24.1 16.9 67.9 8.4 899 55.1 1.3 10.2 41.6 0.5 909 40.0 24.1 16.2 48.4 6.2 2,893 25.6 39.0 24.1 61.8 12.8 1,777 11.7 65.6 45.0 74.2 32.9 2,302 30.2 36.9 25.7 58.2 14.8 7,881 __________________________________________________________________________________ MALE ___________________________________________________________________________________ Age 15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 Residence Urban Rural Province Nairobi Central Coast Eastern Nyanza Rift Valley Western Education No education Primary incomplete Primary complete Secondary+ Total 12.0 51.6 44.0 75.9 27.0 811 8.4 65.4 50.5 82.3 36.8 589 6.4 68.4 48.8 84.4 37.7 463 10.9 64.0 49.1 82.8 36.3 418 8.5 65.4 49.3 84.3 39.3 375 8.9 61.7 40.9 83.0 31.0 291 15.5 54.3 40.2 78.2 32.3 278 13.5 56.2 34.3 81.2 26.5 183 3.4 83.9 71.8 83.6 56.6 913 12.7 52.1 36.4 80.1 24.9 2,494 3.0 84.5 80.4 82.1 61.9 431 5.3 66.2 48.0 92.1 42.3 341 16.0 62.0 39.8 75.0 32.5 242 14.4 56.6 46.5 77.3 31.6 633 13.9 55.5 40.2 71.6 23.8 641 11.9 53.7 43.4 80.8 30.1 758 2.0 56.4 21.2 97.0 18.4 361 38.1 5.2 18.6 56.7 2.5 131 17.4 35.7 35.1 74.6 18.5 1,047 9.5 60.0 41.6 80.0 28.3 841 2.6 85.0 59.2 88.7 50.6 1,388 10.2 60.6 45.9 81.0 33.4 3,407 4 Employment is defined as receiving payment in cash or kind for work. 23 2.3.5 Women’s Employment Status The KDHS collected information from women regarding their current employment situation. Table 2.13 shows that 48 percent of women are not currently employed, 4 39 percent are employed all year, 10 percent are employed seasonally, and 3 percent are employed once in a while. Proportionally, there are more women who work seasonally in rural areas (11 percent) than in urban areas (6 percent); whereas, urban women are more likely to report regular full-time employment (42 percent) than rural women (32 percent). Seasonal work decreases with increasing level of education. Substantial regional variations exist in employment characteristics of women. Over one-half of women are currently employed in Nairobi, Nyanza, and Rift Valley provinces; whereas, less than 40 percent of women in Coast Province are currently employed. Eastern, Nyanza, and Rift Valley provinces have a relatively high percentage (13 percent or more) of their employed female work force engaged in seasonal or occasional jobs. Figure 2.3 Access to Media by Urban-rural Residence and Sex URBAN Reads newsapers Listens to radio Watches television All three media RURAL Reads newsapers Listens to radio Watches television All three media 0 20 40 60 80 100 Percent Male female KDHS 1998 24 Table 2.13 Employment Percent distribution of women by employment status and continuity of employment, according to selected background characteristics, Kenya 1998 ______________________________________________________________________________________________________ Not currently employed Currently employed _________________ ___________________________________________ Did not work Worked All year in last in ________________ Number Background 12 last 12 5+ days <5 days Season- Occasion- of characteristic months months per week per week ally ally Missing Total women ______________________________________________________________________________________________________ Age 15-19 20-24 25-29 30-34 35-39 40-44 45-49 Residence Urban Rural Province Nairobi Central Coast Eastern Nyanza Rift Valley Western Education No education Primary incomplete Primary complete Secondary+ Total 75.3 2.3 11.9 2.4 5.4 2.6 0.1 100.0 1,851 47.1 3.6 30.5 4.5 9.3 4.9 0.1 100.0 1,548 35.9 3.1 41.5 5.5 10.6 3.4 0.1 100.0 1,371 30.6 2.8 45.6 5.4 11.3 3.8 0.5 100.0 986 30.4 1.8 47.3 5.6 11.3 3.3 0.3 100.0 991 29.7 1.1 50.4 4.9 11.9 1.8 0.2 100.0 637 34.9 2.4 42.4 4.1 13.4 2.5 0.2 100.0 497 42.0 3.3 42.1 2.5 6.2 3.7 0.1 100.0 1,830 46.5 2.4 32.1 5.0 10.6 3.3 0.2 100.0 6,051 40.6 2.6 47.5 2.1 3.1 4.1 0.0 100.0 770 55.6 1.1 30.8 2.4 6.0 4.1 0.0 100.0 834 62.3 1.5 23.5 2.1 8.7 1.6 0.3 100.0 605 48.1 4.6 27.4 6.5 10.2 3.2 0.1 100.0 1,386 35.2 2.2 39.1 4.8 14.3 4.3 0.1 100.0 1,690 41.2 2.6 38.5 4.1 10.1 2.9 0.4 100.0 1,696 52.2 2.4 28.0 6.5 8.1 2.6 0.2 100.0 899 42.3 2.0 36.7 5.4 11.6 1.9 0.1 100.0 909 49.1 2.1 30.0 4.2 10.9 3.6 0.1 100.0 2,893 44.3 3.0 35.0 5.4 8.2 3.8 0.3 100.0 1,777 43.0 3.3 38.6 3.5 8.1 3.3 0.2 100.0 2,302 45.4 2.6 34.4 4.4 9.6 3.4 0.2 100.0 7,881 2.3.6 Employer and Form of Earnings Table 2.14 shows the percent distribution of the 4,086 employed women by type of employer and form of earnings, according to background characteristics. About 49 percent of the women are self-employed and earning cash, 14 percent are self-employed and not earning cash, 26 percent are employed by nonrelatives and earning cash, and only 1 percent are employed by nonrelatives and not earning cash. About 10 percent of employed women work for relatives; more than half of these earn cash for their work. Taken together, about 1 in 5 working women is not paid in cash for her work. Generally, rural-based employed women are more likely than their urban counterparts to be self- employed but are also more likely to not receive cash for their work. Urban women, especially those in Nairobi, tend to be employed by nonrelatives and receive cash for their work. Women in Nyanza are the most likely to be self-employed and also the most likely to receive no cash for their work. A relatively high percentage of women working in Rift Valley province are employed by relatives and most are paid in cash. The pattern of employer-type and form of earnings shows that women with more education are less likely to be self-employed and to work without cash compensation. 25 Table 2.14 Employer and form of earnings Percent distribution of currently employed women by employer and form of earnings, according to selected background characteristics, Kenya 1998 ______________________________________________________________________________________________________ Employed by Employed by Self-employed a nonrelative a relative _______________ ________________ _________________ Does Does Does Number Background Earns not earn Earns not earn Earns not earn of characteristic cash cash cash cash cash cash Missing Total women ______________________________________________________________________________________________________ Age 15-19 20-24 25-29 30-34 35-39 40-44 45-49 Residence Urban Rural Province Nairobi Central Coast Eastern Nyanza Rift Valley Western Education No education Primary incomplete Primary complete Secondary+ Total 28.2 7.0 35.5 2.2 6.9 20.2 0.1 100.0 413 44.6 12.8 28.9 0.7 6.5 6.0 0.6 100.0 763 50.8 13.5 26.5 0.8 5.3 3.1 0.0 100.0 836 50.7 15.8 27.4 0.8 3.7 1.1 0.5 100.0 653 55.4 15.7 20.2 0.4 6.4 1.6 0.3 100.0 670 55.7 17.3 21.0 0.6 4.6 0.8 0.0 100.0 440 50.2 21.2 24.3 0.1 3.0 1.2 0.0 100.0 311 42.4 3.8 47.9 1.8 2.9 1.3 0.0 100.0 999 50.6 17.9 19.2 0.5 6.2 5.4 0.3 100.0 3,087 39.5 4.6 50.8 2.1 2.9 0.0 0.0 100.0 438 53.2 4.0 32.5 0.0 7.7 2.7 0.0 100.0 361 49.2 7.2 33.0 0.7 4.7 5.1 0.1 100.0 218 58.4 8.3 27.3 0.1 3.8 2.0 0.0 100.0 654 43.7 31.2 13.8 0.7 2.3 8.3 0.0 100.0 1,058 47.7 12.2 23.7 1.1 10.7 3.9 0.7 100.0 949 52.6 9.7 26.9 0.6 4.2 5.1 0.9 100.0 408 51.9 23.5 16.7 0.6 4.7 2.6 0.0 100.0 506 49.5 18.8 18.0 0.8 6.8 5.7 0.3 100.0 1,412 56.6 11.1 19.9 1.0 6.6 4.5 0.4 100.0 935 40.0 8.2 44.2 0.7 3.0 3.6 0.2 100.0 1,232 48.6 14.4 26.2 0.8 5.4 4.4 0.3 100.0 4,086 2.3.7 Occupation Information on current occupation of employed women is shown in Table 2.15. Forty-eight percent of the women have agricultural occupations and 52 percent have nonagricultural occupations. The majority of women who have agricultural occupations work on their own land while the majority of women who do not work in agriculture have sales and services occupations. Eight percent of employed Kenyan women do domestic work, and 12 percent work in the professions or in technical, clerical, or managerial fields. As expected, employment in nonagricultural occupations is relatively more common among women who live in urban areas and those who have more formal education. The urban employment profile of women is concentrated into professional, technical, and sales and service work on one hand and domestic help on the other. 26 Table 2.15 Occupation Percent distribution of currently employed women by occupation and type of agricultural land worked or type of nonagricultural employment, according to selected background characteristics, Kenya 1998 ___________________________________________________________________________________________________________________ Agricultural Nonagricultural ____________________________ ______________________________________ Prof./ Household Number Background Own Family Rented Other's tech./ Sales/ Skilled Unskilled and of characteristic land land land land manag. services manual manual domestic Missing Total women __________________________________________________________________________________________________________________ Age 15-19 20-24 25-29 30-34 35-39 40-44 45-49 Residence Urban Rural Province Nairobi Central Coast Eastern Nyanza Rift Valley Western Education No education Primary incomplete Primary complete Secondary+ Total 9.7 27.9 0.9 3.5 0.6 17.8 4.8 2.6 32.1 0.1 100.0 413 21.2 15.1 1.7 6.5 12.2 25.2 5.0 1.5 11.5 0.2 100.0 763 26.3 10.0 2.7 6.0 15.1 26.2 5.4 2.6 5.7 0.2 100.0 836 27.5 6.8 2.3 7.4 15.7 27.9 5.3 3.4 3.4 0.3 100.0 653 32.8 9.5 2.9 5.4 12.1 26.4 4.5 1.4 4.7 0.3 100.0 670 39.4 8.4 3.2 8.2 12.3 23.9 1.7 1.2 1.6 0.1 100.0 440 41.9 9.8 1.2 5.8 10.1 21.0 2.8 2.1 5.3 0.0 100.0 311 2.6 1.7 0.4 2.8 25.3 37.3 4.3 3.4 22.0 0.2 100.0 999 35.6 15.3 2.8 7.3 7.7 20.8 4.5 1.7 4.1 0.2 100.0 3,087 0.8 0.4 0.0 2.5 26.5 33.6 4.2 2.5 29.0 0.4 100.0 438 25.3 7.4 1.4 8.3 13.8 23.1 9.1 6.2 5.4 0.0 100.0 361 10.4 4.3 0.1 4.9 14.3 40.6 9.2 4.6 11.4 0.2 100.0 218 34.1 10.4 3.8 7.2 9.4 20.5 4.3 3.2 7.0 0.0 100.0 654 39.2 12.4 1.6 6.1 6.8 25.6 4.0 0.6 3.7 0.0 100.0 1,058 28.6 19.9 3.6 6.9 11.1 20.2 3.0 1.3 5.2 0.3 100.0 949 23.8 15.9 2.6 5.8 13.5 24.0 3.2 0.9 9.7 0.6 100.0 408 43.0 13.1 2.6 10.0 0.7 20.6 1.4 2.6 6.0 0.0 100.0 506 33.0 16.6 2.6 8.3 0.9 24.0 2.0 2.2 10.2 0.0 100.0 1,412 27.1 12.4 2.3 5.0 4.2 29.5 7.4 2.1 9.5 0.4 100.0 935 15.2 6.0 1.7 3.0 35.3 23.8 6.4 1.9 6.6 0.2 100.0 1,232 27.5 12.0 2.2 6.2 12.0 24.8 4.5 2.1 8.4 0.2 100.0 4,086 ________________________________________________________________________________________________________________ Note: Professional/technical/managerial includes professional, technical, clerical and managerial occupations. 2.3.8 Decision on Use of Earnings Information on who decides how the cash earnings of employed women are used is a measure of women's status. Table 2.16 shows that 55 percent of the 3,278 women who receive cash earnings decide for themselves how to spend their money, 26 percent decide jointly with their husband/partner, and for 16 percent their husband/partner decides how their earnings are used. Younger, urban women with more education are less likely to report that their husband/partner decides how to spend their earnings, but this pattern is not a strong one. Sixty-three percent of employed women in urban areas make their own decision on how to use the money they earn, compared with 52 percent of employed women in rural areas. Among the provinces, women in Rift Valley are most likely to report that their husband/partner makes the spending decisions. 27 Table 2.16 Decision on use of earnings Percent distribution of women receiving cash earnings by person who decides on use of earnings, according to selected background characteristics, Kenya 1998 _____________________________________________________________________________________________________ Person who decides how earnings are used ___________________________________________ Jointly Jointly with with Number Background Self Husband/ husband/ Someone someone of characteristic only partner partner else else Missing Total women ______________________________________________________________________________________________________ Age 15-19 20-24 25-29 30-34 35-39 40-44 45-49 Residence Urban Rural Province Nairobi Central Coast Eastern Nyanza Rift Valley Western Education No education Primary incomplete Primary complete Secondary+ Marital status Currently married Not married Total 60.1 11.0 8.0 13.9 7.0 0.0 100.0 291 58.5 15.7 21.7 2.2 1.9 0.0 100.0 612 51.6 15.4 31.7 0.4 0.7 0.2 100.0 690 53.2 16.5 29.5 0.0 0.3 0.4 100.0 536 54.1 19.2 25.5 0.2 0.3 0.7 100.0 550 53.6 15.6 30.4 0.3 0.1 0.0 100.0 358 54.7 14.6 30.2 0.0 0.2 0.3 100.0 241 62.9 11.9 20.5 2.6 1.8 0.2 100.0 931 51.5 17.4 28.3 1.5 1.0 0.3 100.0 2,347 64.4 11.7 17.1 3.2 3.2 0.5 100.0 408 47.2 12.9 38.0 0.6 0.7 0.5 100.0 337 65.8 14.8 13.6 3.2 2.4 0.2 100.0 189 47.9 14.3 34.0 2.2 1.6 0.0 100.0 586 61.5 13.5 23.8 0.9 0.2 0.0 100.0 633 49.1 22.7 26.0 1.3 0.7 0.3 100.0 783 56.8 15.6 22.8 2.6 1.6 0.7 100.0 342 54.3 21.8 21.8 0.8 1.2 0.1 100.0 371 55.4 16.0 22.9 3.7 1.6 0.3 100.0 1,052 55.9 16.7 24.9 1.5 0.8 0.2 100.0 777 53.5 13.1 31.4 0.6 1.2 0.3 100.0 1,078 89.6 0.5 0.0 5.8 4.0 0.0 100.0 993 39.6 22.5 37.4 0.0 0.1 0.4 100.0 2,284 54.8 15.9 26.1 1.8 1.3 0.3 100.0 3,278 2.3.9 Child Care While Working Table 2.17 gives the percent distribution of employed women, by whether they have a child under six years of age, and if they do, who takes care of the child when they are working. Slightly over half (52 percent) of employed women have a child under age six. Of employed women who have a child under six, 42 percent look after their own child(ren) while at work, and 17 percent have relatives (other than husband) to look after their children. In 15 percent of cases, another child (largely female) minds the young child. In urban areas (especially Nairobi) and among women with more education, a woman’s young child is more likely to be taken care of by a hired worker and less likely by some other child (male or female). For example, use of other children to take care of a woman’s children under six during working hours increases from 7 percent for employed women with secondary education to 11 percent for women with completed primary education to 19 percent for women with incomplete primary education to 29 percent for women with no education. 28 Ta bl e 2. 17 C hi ld c ar e w hi le w or ki ng Pe rc en t d ist rib ut io n of cu rre nt ly em pl oy ed w om en b y w he th er th ey h av e a c hi ld u nd er si x ye ar s o f a ge at h om e, an d th e p er ce nt d ist rib ut io n of em pl oy ed m ot he rs w ho h av e a ch ild u nd er si x by p er so n w ho c ar es fo r c hi ld w hi le m ot he r is at w or k, a cc or di ng to se le ct ed b ac kg ro un d ch ar ac te ris tic s, K en ya 1 99 8 _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ O ne o r Ch ild 's ca re ta ke r w hi le m ot he r i s a t w or k N o ch ild m o re _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ N ot N u m be r u n de r ch ild re n R e- N ei gh - Ch ild O th er O th er w o rk ed o f B ac kg ro un d six u n de r s ix sp on d- H us ba nd / O th er bo r/ H ire d is in fe m al e m al e sin ce em pl oy ed ch ar ac te ris tic at h om e at h om e en t pa rtn er re la tiv e Fr ie nd he lp sc ho ol ch ild ch ild bi rth 1 O th er M iss in g To ta l w o m en _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ R es id en ce U rb an R ur al Pr ov in ce N ai ro bi Ce nt ra l Co as t Ea st er n N ya nz a R ift V al le y W es te rn Ed uc a tio n N o ed u ca tio n Pr im ar y in co m pl et e Pr im ar y co m pl et e Se co n da ry + W or k st at us Fo r f am ily m em be r Fo r s om eo ne e lse Se lf- em pl oy ed O cc u pa tio n A gr ic ul tu ra l N on ag ric ul tu ra l Em pl o ym en t s ta tu s A ll ye ar , f ul l w ee k A ll ye ar , p ar t w ee k Se as o n al O cc as io na l To ta l 63 .2 36 .8 33 .0 1. 1 11 .3 4. 7 28 .8 7. 9 5. 5 1. 0 1. 9 0. 4 4. 3 10 0. 0 99 9 42 .8 57 .2 44 .0 1 .7 18 .6 3 .8 5 .6 3 .6 12 .0 4 .3 2 .2 0 .9 3 .2 10 0. 0 3, 08 7 68 .5 31 .5 29 .3 1. 3 8. 0 6. 7 42 .7 2. 7 4. 0 1. 3 1. 3 0. 0 2. 7 10 0. 0 43 8 48 .7 51 .3 48 .6 1. 8 18 .5 0. 3 7. 4 6. 5 4. 7 0. 5 4. 3 1. 0 6. 4 10 0. 0 36 1 55 .9 44 .1 41 .5 3. 4 21 .1 3. 5 12 .2 4. 0 10 .1 2. 2 1. 6 0. 0 0. 5 10 0. 0 21 8 51 .0 49 .0 32 .4 2. 1 25 .4 1. 8 11 .0 5. 8 11 .3 3. 2 3. 1 0. 6 3. 3 10 0. 0 65 4 44 .7 55 .3 41 .2 2 .2 15 .7 6 .8 4 .6 3 .6 13 .0 6 .8 0 .8 1 .4 3 .8 10 0. 0 1, 05 8 38 .4 61 .6 51 .2 0. 9 13 .1 3. 2 6. 8 4. 9 12 .2 2. 3 1. 9 0. 7 2. 8 10 0. 0 94 9 45 .0 55 .0 37 .7 0. 8 24 .3 3. 3 8. 5 1. 8 11 .4 4. 8 3. 8 0. 3 3. 3 10 0. 0 40 8 57 .5 42 .5 50 .9 1. 9 9. 8 4. 3 1. 0 0. 1 19 .6 9. 3 0. 2 0. 3 2. 5 10 0. 0 50 6 43 .6 56 .4 47 .7 1 .7 18 .3 4 .4 1 .4 2 .3 13 .9 5 .4 1 .5 0 .6 2 .9 10 0. 0 1, 41 2 46 .1 53 .9 45 .6 2. 3 20 .5 3. 0 4. 2 4. 6 8. 7 2. 4 3. 0 1. 1 4. 5 10 0. 0 93 5 49 .7 50 .3 29 .2 0 .9 16 .2 4 .1 27 .5 8 .2 5 .9 0 .7 2 .9 0 .9 3 .5 10 0. 0 1, 23 2 48 .8 51 .2 57 .3 0. 0 16 .1 1. 9 2. 8 4. 3 12 .7 2. 6 0. 3 1. 2 0. 8 10 0. 0 39 9 60 .1 39 .9 13 .4 1 .6 23 .2 5 .7 28 .0 8 .7 11 .3 2 .4 2 .4 0 .3 3 .0 10 0. 0 1, 10 5 42 .3 57 .7 48 .7 1 .9 15 .8 3 .8 5 .1 3 .0 10 .5 4 .3 2 .3 0 .9 3 .8 10 0. 0 2, 57 4 40 .5 59 .5 53 .1 1 .3 15 .1 3 .4 2 .4 3 .5 12 .8 3 .9 1 .3 0 .9 2 .2 10 0. 0 1, 95 9 54 .5 45 .5 29 .0 2 .0 20 .1 4 .7 18 .4 5 .3 8 .7 3 .5 3 .2 0 .7 4 .6 10 0. 0 2, 12 0 49 .7 50 .3 42 .9 1 .8 14 .5 4 .0 12 .0 5 .2 9 .5 3 .7 2 .0 0 .8 3 .6 10 0. 0 2, 71 1 39 .9 60 .1 37 .3 0. 9 23 .7 4. 4 7. 2 2. 3 14 .6 4. 0 2. 4 0. 3 2. 8 10 0. 0 34 9 42 .5 57 .5 42 .8 1. 3 21 .8 3. 9 5. 1 3. 0 12 .6 3. 3 2. 4 0. 7 3. 1 10 0. 0 75 4 52 .5 47 .5 41 .0 2. 7 22 .4 3. 0 3. 2 2. 6 14 .3 4. 3 2. 0 2. 0 2. 5 10 0. 0 26 6 47 .8 52 .2 42 .1 1 .6 17 .3 4 .0 9 .6 4 .3 10 .9 3 .7 2 .1 0 .8 3 .4 10 0. 0 4, 08 6 _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ N ot e: T ot al in cl ud es tw o w om en fo r w ho m in fo rm at io n on e m pl oy m en t s ta tu s w as n ot a va ila bl e. 1 R es po nd en t i s c ur re nt ly e m pl oy ed b ut ha s n ot w or ke d sin ce la st bi rth . 1 Numerators for the age-specific fertility rates are calculated by summing the number of live births that occurred in the 1-36 months preceding the survey (determined by the date of interview and birth date of the child), and classifying them by age (in five-year groups) of the mother at the time of birth (determined by the mother’s birth date). The denominators of the rates are the number of woman-years lived in each of the specified five-year age groups during the 1-36 months preceding the survey. 29 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 1998 _______________________________________________________ Residence ______________ Age group Urban Rural Total _______________________________________________________ 15-19 20-24 25-29 30-34 35-39 40-44 45-49 TFR women 15-49 TFR women 15-44 General fertility rate Crude birth rate 90 119 111 190 271 248 165 237 218 115 208 188 48 122 109 6 59 51 10 17 16 3.12 5.16 4.70 3.07 5.08 4.62 125 179 166 33.6 34.7 34.6 _______________________________________________________ Note: Rates are for the period 1-36 months preceding the survey. Rates for age group 45-49 may be slightly biased due to truncation. Total fertility rate expressed per woman. General fertility rate (births divided by number of women 15-49), expressed per 1,000 women. Crude birth rate expressed per 1,000 population. CHAPTER 3 FERTILITY LEVELS AND DIFFERENTIALS John Kekevole 3.1 Introduction The assessment of Kenya’s fertility dynamics has been an important objective of the national demographic and health surveys since they were initiated in the late 1970s. The focus on fertility is due in part to its important role in determining Kenya’s population growth rate. This chapter presents the KDHS findings on fertility levels, trends and differentials, based on analysis of the complete birth histories of women age 15-49. This information was collected by first asking the women to indicate the number of their own children who were living with them, the number who were staying elsewhere, and the number who had died. As in previous Demographic and Health Surveys, the women were then asked to provide a detailed history of each live birth. The information collected on each live birth included name, sex, date of birth, survival status (whether alive or dead), current age if alive, and age at death if dead. 3.2 Current Fertility The most widely used measures of current fertility are the total fertility rate (TFR) and its component age-specific fertility rates (ASFR). The TFR is defined as the number of children a woman would have by the end of her childbearing years if she were to pass through those years bearing children at the currently observed age-specific rates.1 The results in Table 3.1 indicate that the total fertility rate for the three years preceding the survey (early 1995 to early 1998) is 4.7 children per woman. Peak childbearing occurs during ages 20-24 and 25-29, falling sharply after age 34. The total fertility rate is higher in rural areas (5.2 children per woman) than in urban areas (3.1 children per woman). This pattern of higher rural fertility is evident at every age. 30 Table 3.2 Fertility by background characteristics Total fertility rate for the three years preceding the survey, percentage currently pregnant and mean number of children ever born to women age 40-49, by selected background characteristics, Kenya 1998 ______________________________________________________ Mean number of children Total Percentage ever born Background fertility currently to women characteristic rate1 pregnant age 40-49 _______________________________________________________ Residence Urban Rural Province Nairobi Central Coast Eastern Nyanza Rift Valley Western Education No education Primary incomplete Primary complete Secondary+ Total 3.12 5.56 4.59 5.16 7.99 6.99 (2.61) 5.01 4.14 (3.67) 5.32 5.93 5.05 8.95 6.28 4.68 7.70 6.56 4.98 7.27 7.40 5.31 8.24 7.03 (5.63) 8.75 6.97 (5.80) 5.76 7.11 5.24 8.80 7.21 4.79 8.10 6.31 3.53 5.83 4.93 4.70 7.43 6.62 _______________________________________________________ Note: Figures in parentheses are based on 400-999 women.1 Women age 15-49 years Table 3.2 and Figure 3.1 show differ- entials in fertility by urban-rural residence, province, and level of education. Educational attainment of a woman is closely linked to fertility; the TFR for women with no formal education is 5.8 children per woman, versus 5.2 for women with primary incomplete education, 4.8 for women with a completed primary edu- cation only, and 3.5 for women with at least some secondary schooling. Fertility varies widely across provinces, ranging from a low of 2.6 children per woman in Nairobi to over 5 children per woman in Western, Rift Valley and Coast provinces. Table 3.2 also allows a crude assess- ment of differential trends in fertility over time among population subgroups. The mean num- ber of children ever born to women age 40-49 is a measure of past completed fertility. A com- parison of current fertility with past fertility (TFR) shows that there has been a substantial decline in urban and rural areas, in all prov- inces, and in the four education categories. Overall, comparison of past and present fertility indicators suggests a recent decline of about two children per woman, from 6.6 to 4.7 chil- dren per woman. Figure 3.1 Total Fertility Rate by Background Characteristics 4.7 3.1 5.2 2.6 3.7 4.7 5 5.1 5.3 5.6 5.8 5.2 4.8 3.5 KENYA RESIDENCE Urban Rural PROVINCE Nairobi Central Eastern Nyanza Coast Rift Valley Western EDUCATION No education Primary incomplete Primary complete Secondary + 0 1 2 3 4 5 6 7 Number of Children KDHS 1998 31 Table 3.3 Trends in fertility Age-specific fertility rates (per 1,000 women) and total fertility rates for selected surveys, 1997/78/KFS, 1989 KDHS, 1993 KDHS, and 1998 KDHS _____________________________________________________________ 1977/78 1989 1993 1998 KFS KDHS KDHS KDHS Age group 1975-78a 1984-89b 1990-93c 1995-98 _____________________________________________________________ 15-19 168 152 110 111 20-24 342 314 257 248 25-29 357 303 241 218 30-34 293 255 197 188 35-39 239 183 154 109 40-44 145 99 70 51 45-49 59 35 50 16 TFR women age 15-49 8.1 6.7 5.4 4.7 _____________________________________________________________ Note: Rates refer to the three-year period preceding the survey except for the 1989 KDHS (five-year period before survey).a CBS, 1980b NCPD, 1989c NCPD, 1994 At the time of the survey, 7 percent of interviewed women reported that they were pregnant. This is an underestimate of the true percentage pregnant because many women who are early in their pregnancy will not yet know that they are pregnant and some women may not want to declare that they are pregnant. Still, differentials in pregnancy status parallel differentials in current fertility. 3.3 Fertility Trends Trends in current fertility can be examined by observing a time series of estimates produced from demographic surveys fielded over the last two decades, beginning with the 1977/78 Kenya Fertility Survey (KFS). The estimates shown in Table 3.3 describe the ongoing Kenyan fertility transition. The TFR has de- clined dramatically from 8.1 children per woman in the mid-1970s to the current level of 4.7 children per wom- an; a decline of 42 percent over a 20- year period. Based on this cursory analysis, the steepest drop in the TFR occurred during the late 1980s and early 1990s, and has slowed somewhat during the mid-1990s. Figure 3.2 shows that fertility has fallen recently at every age except amongst the youngest women, age 15-19. Figure 3.2 Age-Specific Fertility Rates for Women Age 15-49 1989 KDHS, 1993 KDHS, and 1998 KDHS 15-19 20-24 25-29 30-34 35-39 40-44 45-49 Age in Years 0 50 100 150 200 250 300 350 Births per 1,000 Women 1989 KDHS 1993 KDHS 1998 KDHS 2 The rates for the older age groups (shown in brackets in Table 3.5) become progressively more truncated as one goes further back in time. For example, rates cannot be calculated for women age 45-49 years for the period 5-9 years before the survey, because these women would have been over age 50 years at the time of the survey and were not interviewed. 32 Table 3.4 Trends in fertility by province Total fertility rates by province, and percent decline, 1993 KDHS and 1998 KDHS ____________________________________________ 1993 1998 KDHS KDHS Percent Province (1990-93) (1995-98) decline ______________________________________________ Nairobi 3.4 2.6 24 Central 3.9 3.7 5 Coast 5.3 5.1 4 Eastern 5.9 4.7 20 Nyanza 5.8 5.0 14 Rift Valley 5.7 5.3 7 Western 6.4 5.6 13 Total 5.4 4.7 13 ______________________________________________ Note: Rates refer to the 3-year period prior to the survey. Table 3.5 Age-specific fertility rates Age-specific fertility rates for 5-year periods preceding the survey, Kenya 1998 _______________________________________________ Number of years preceding the survey Age _________________________________ group 0-4 5-9 10-14 15-19 _______________________________________________ 15-19 111 131 165 177 20-24 246 271 317 318 25-29 222 266 325 327 30-34 185 217 287 [263] 35-39 107 163 [206] - 40-44 54 [98] - - 45-49 [16] - - - _______________________________________________ Note: Age-specific fertility rates per 1,000 women. Esti- mates enclosed in brackets are truncated. Table 3.6 Fertility by marital duration Fertility rates for ever-married women by number of years since first marriage, for 5-year periods preceding the survey, Kenya 1998 _______________________________________________ Years Number of years preceding the survey since first _________________________________ marriage 0-4 5-9 10-14 15-19 _______________________________________________ 0-4 336 364 399 377 5-9 236 290 339 351 10-14 200 241 304 314 15-19 136 204 265 [229] 20-24 95 133 [255] [218] 25-29 34 [84] [150] - _______________________________________________ Note: Fertility rates per 1,000 women. Estimates enclosed in brackets are truncated. Table 3.4 gives an idea of trends in fertility occurring at the provincial level since the 1993 KDHS. Some provinces (Nairobi and Eastern) continue to experience substantial declines in fertility (20 percent or more), while others have experienced much more modest declines. Coast, Rift Valley, and Central provinces are examples where fertility has declined by no more than 7 percent since the 1993 KDHS. Coast Province, once characterised by relatively low fertility (probably due in large part to STD-related subfertility), now has one of the highest levels of fertility in the country. Tables 3.5 and 3.6 provide further evidence of a recent fertility decline in Kenya. Table 3.5 shows the age-specific fertility rates (ASFR) for five-year periods preceding the survey. Within each age group, substantial and sustained declines in ASFRs are observed from 10- 14 years before the survey (circa 1983-88) to 0-4 years before the survey (circa 1993-98).2 Fertility rates for ever-married women by duration since first marriage for five-year periods preceding the survey are shown in Table 3.6. This table is analogous to Table 3.5, but is confined to ever-married women and replaces age with duration since first marriage. The data confirm a sharp decline in fertility, and indicate that the drop has occurred within marriage and at all marital durations. 33 Table 3.7 Children ever born and living Percent distribution of all women and of currently married women by number of children ever born and mean number of children ever born (CEB) and mean number of living children, according to five-year age groups, Kenya 1998 ______________________________________________________________________________________________________ Mean Mean number Number of children ever born Number number of Age __________________________________________________________ of of living group 0 1 2 3 4 5 6 7 8 9 10+ Total women CEB children ______________________________________________________________________________________________________ ALL WOMEN ______________________________________________________________________________________________________ 15-19 82.7 14.1 3.0 0.2 0.1 0.0 0.0 0.0 0.0 0.0 0.0 100.0 1,851 0.21 0.18 20-24 30.8 31.7 22.4 11.0 2.7 1.3 0.2 0.0 0.0 0.0 0.0 100.0 1,548 1.28 1.15 25-29 7.4 16.9 26.2 19.8 15.2 9.1 3.5 1.6 0.2 0.1 0.0 100.0 1,371 2.70 2.43 30-34 2.7 6.6 15.9 17.8 17.2 15.1 12.8 7.4 3.0 1.1 0.4 100.0 986 4.03 3.59 35-39 2.4 2.9 7.0 10.1 17.3 12.9 16.3 12.2 9.1 6.0 3.8 100.0 991 5.32 4.83 40-44 1.7 2.1 3.5 8.9 10.8 9.5 13.8 14.8 11.2 11.0 12.7 100.0 637 6.37 5.59 45-49 2.6 2.2 4.1 4.7 7.1 8.6 13.3 10.4 14.3 12.5 20.1 100.0 497 6.94 5.81 Total 27.7 14.0 13.1 10.2 8.8 6.7 6.3 4.6 3.4 2.6 2.8 100.0 7,881 2.89 2.57 ______________________________________________________________________________________________________ CURRENTLY MARRIED WOMEN ______________________________________________________________________________________________________ 15-19 34.9 47.9 15.9 0.9 0.3 0.0 0.0 0.0 0.0 0.0 0.0 100.0 285 0.84 0.73 20-24 12.3 33.1 31.8 16.5 4.3 1.7 0.3 0.0 0.0 0.0 0.0 100.0 948 1.74 1.57 25-29 3.4 12.0 26.7 22.4 17.7 10.9 4.4 2.0 0.2 0.1 0.0 100.0 1,069 3.02 2.72 30-34 1.5 4.5 14.7 17.6 18.0 16.2 13.7 8.7 3.4 1.2 0.5 100.0 822 4.27 3.81 35-39 1.7 2.2 6.2 10.0 16.8 12.9 17.5 12.1 9.8 6.6 4.2 100.0 832 5.49 5.03 40-44 1.5 1.3 1.8 7.9 12.0 8.7 14.2 14.7 11.9 12.3 13.7 100.0 511 6.60 5.82 45-49 2.7 1.6 3.6 4.6 4.9 7.1 13.8 10.7 14.6 12.8 23.6 100.0 365 7.23 6.11 Total 6.1 13.4 17.1 14.1 12.4 9.2 8.9 6.4 4.7 3.6 4.0 100.0 4,834 3.97 3.54 3.4 Children Ever Born and Living The distribution of women by the number of children ever born is presented in Table 3.7 for all women and for currently married women. The table also shows the mean number of children ever born (CEB) to women in each five-year age group. On average, women in their late twenties have given birth to almost 3 children, women in their late thirties have had over 5 children, and women currently at the end of their childbearing years have had nearly 7 children. Of the 6.9 children ever born to women age 45-49, only 5.8 will have survived. The results for younger women who are currently married differ from those for the sample as a whole because of the large percentage of young unmarried women with minimal fertility. Differences at older ages generally reflect the impact of marital dissolution (either divorce or widowhood). Only 2-3 percent of married women age 45-49 have not had a child. Under the proposition that desire for at least one child is universal in Kenya, this 2-3 percent is a rough measure of primary infertility or the inability to bear children. 34 Table 3.8 Birth intervals Percent distribution of births in the five years preceding the survey by number of months since previous birth and median length of birth interval, according to selected demographic and socioeconomic characteristics, Kenya 1998 _____________________________________________________________________________________________________ Median number of months Number of months since previous birth Number since ____________________________________________ of previous Characteristic 7-17 18-23 24-35 36-47 48+ Total births birth ______________________________________________________________________________________________________ Age of mother 15-19 20-29 30-39 40 + Birth order 2-3 4-6 7 + Sex of prior birth Male Female Survival of prior birth Dead Living Residence Urban Rural Province Nairobi Central Coast Eastern Nyanza Rift Valley Western Education No education Primary incomplete Primary complete Secondary+ Total 25.7 26.3 28.8 15.7 3.6 100.0 61 23.9 10.0 17.6 36.7 18.4 17.3 100.0 2,098 30.6 7.1 11.3 33.6 17.4 30.5 100.0 1,666 35.2 4.6 7.4 26.3 22.3 39.4 100.0 336 39.8 8.6 16.7 32.8 17.7 24.2 100.0 1,880 32.5 9.2 12.6 36.2 18.1 24.0 100.0 1,499 33.1 7.7 12.2 35.7 19.9 24.5 100.0 782 33.3 8.1 14.5 34.9 18.2 24.3 100.0 2,116 32.9 9.2 14.3 34.2 18.3 24.1 100.0 2,045 32.9 26.8 19.6 25.0 12.8 15.7 100.0 455 25.0 6.4 13.7 35.7 18.9 25.2 100.0 3,706 33.7 11.2 13.2 28.4 15.5 31.7 100.0 639 34.8 8.2 14.6 35.7 18.8 22.8 100.0 3,522 32.7 10.6 15.9 23.9 15.0 34.5 100.0 208 35.9 6.4 12.0 24.1 20.8 36.8 100.0 338 38.8 8.7 15.1 26.9 19.8 29.5 100.0 317 35.8 6.7 12.0 36.4 19.4 25.6 100.0 674 34.2 9.1 13.6 37.7 18.0 21.6 100.0 936 32.0 9.4 15.2 35.4 17.5 22.5 100.0 1,128 31.7 9.5 17.3 40.0 17.7 15.5 100.0 559 30.4 8.7 12.7 34.0 18.4 26.2 100.0 574 34.2 8.8 15.0 37.3 19.3 19.5 100.0 1,656 32.0 7.3 14.7 32.7 18.7 26.7 100.0 997 34.0 9.8 13.9 31.8 15.9 28.6 100.0 933 33.5 8.7 14.4 34.5 18.3 24.2 100.0 4,161 32.9 ____________________________________________________________________________________________________ Note: First-order births are excluded. The interval for multiple births is the number of months since the end of the preceding pregnancy that ended in a live birth. 3.5 Birth Intervals Information on the length of birth intervals provides insight into birth spacing patterns. Research has shown that children born too soon after the birth of a previous birth are at increased risk of poor health, particularly when the interval is less than 24 months. Maternal health is also threatened by rapid childbearing. Table 3.8 shows the distribution of births in the five years before the survey by the number of months (interval) since the previous birth, according to various demographic and socioeconomic variables. 3 For the age group 20-24, less than 50 percent of women had had a birth by age 20 precluding a precise estimate of the median age at first birth. However, this does mean that the median age at first birth for women 20-24 is no less than 20.0 years. This additional piece of evidence supports the notion that age at first birth is rising. 35 Table 3.9 Age at first birth Percent distribution of women 15-49 by age at first birth, according to current age, Kenya 1998 ____________________________________________________________________________________________________ Women Median with Age at first birth Number age at no _____________________________________________ of first Current age births <15 15-17 18-19 20-21 22-24 25+ Total women birth ____________________________________________________________________________________________________ 15-19 82.7 1.4 10.1 5.8 NA NA NA 100.0 1,851 a 20-24 30.8 4.1 19.2 23.0 17.9 5.1 NA 100.0 1,548 a 25-29 7.4 7.4 24.5 21.7 18.0 15.4 5.6 100.0 1,371 19.6 30-34 2.7 7.0 25.5 24.0 16.4 16.7 7.7 100.0 986 19.5 35-39 2.4 7.6 26.5 24.0 18.8 12.9 7.8 100.0 991 19.3 40-44 1.7 13.1 25.4 24.9 14.8 13.0 7.2 100.0 637 18.9 45-49 2.6 10.2 22.5 18.2 19.7 17.2 9.5 100.0 497 19.9 ____________________________________________________________________________________________________ NA = Not applicablea The medians for cohorts 15-19 and 20-24 could not be determined because half of the women had not had a birth before reaching the lowest age of the age group. Nearly one in four children (23 percent) is born after a “too short” interval (less than 24 months). The median interval length is shorter among births to young women and especially when the previous child has died. The median birth interval length is 33 months for all births, but only 24 months if the mother is less than 20 years old, and 25 months if the previous child is dead. Birth intervals are longer in urban areas (35 months) than rural areas (33 months). This could be related to the higher rates of contraceptive use (for spacing) among urban women, especially those living in Nairobi. Birth interval length varies substantially amongst the provinces from 30 months in Western Province to 39 months in Central Province. 3.6 Age at First Birth One of the factors that typically drives transition from high to low fertility is a rising age at first birth. The KDHS data show that there has been a trend over the last two decades toward delaying the first birth (Table 3.9). In the youngest cohort for which a median age at first birth can be calculated (age 25-29), first birth occurs at a median age of 19.6 years.3 This is only very slightly higher than the median age at first birth for the same age cohort observed in the 1993 KDHS (19.3 years), suggesting a rather modest rise in age at first birth in the few years before the 1998 survey. However, a more significant longer-term trend is suggested by the fall in the percentage of first births occurring before age 18; from 39 percent in the cohort currently age 40-44 to 32 percent in the age group 25-29 to 23 percent among women currently age 20-24. This slow but steady decline indicates success in delaying childbearing and thereby allowing girls and women the chance to participate more fully in social and economic activities of the country. 36 Table 3.10 Median age at first birth by background characteristics Median age at first birth among women 25-49, by current age and selected background characteristics, Kenya 1998 __________________________________________________________________________________ Current age Women Background ____________________________________________ age characteristic 25-29 30-34 35-39 40-44 45-49 25-49 _________________________________________________________________________________ Residence Urban Rural Province Nairobi Central Coast Eastern Nyanza Rift Valley Western Education No education Primary incomplete Primary complete Secondary+ Total 21.1 21.2 19.9 20.1 20.7 20.7 19.2 19.1 19.3 18.7 19.6 19.1 22.3 22.0 20.0 20.5 22.0 21.9 20.4 20.1 20.1 19.0 20.9 20.1 20.2 20.0 19.4 18.3 20.3 19.9 20.0 19.4 19.4 19.3 20.0 19.6 18.3 17.9 18.6 18.0 18.3 18.2 18.7 19.4 19.3 18.9 21.1 19.2 20.1 20.2 20.0 18.9 19.3 19.8 17.1 17.8 18.4 18.3 18.7 18.2 17.9 18.0 18.2 18.2 19.5 18.1 19.8 19.3 19.4 18.7 20.7 19.5 22.0 21.5 20.9 21.7 22.4 21.6 19.6 19.5 19.3 18.9 19.9 19.4 _________________________________________________________________________________ Note: The medians for cohorts 15-19 and 20-24 could not be determined because half of the women had not had a birth before reaching the lowest age of the age group. Table 3.10 summarises the median age at first birth for different age cohorts across urban-rural and educational subgroups. For all age groups of women, the median age at first birth is higher for urban areas than for rural areas. Similarly, age at first birth increases markedly with increasing level of education; for example, within the cohort age 25-29, women without any education have their first birth around age 17, five years earlier than their counterparts with a secondary or higher education. Childbearing begins earliest in Nyanza Province (18 years) and latest in Nairobi Province (22 years). 3.7 Adolescent Fertility The issue of adolescent fertility is an important one on both health and social grounds. Children born to very young mothers are at increased risk of illness and death. Adolescent mothers are more likely to experience adverse pregnancy outcomes and are more constrained in their ability to pursue educational opportunities than their counterparts who delay childbearing. Adolescent mothers may also suffer irreparable damage to their self-esteem due to the inherent incompatibility between the roles they are expected to assume as mothers and their physical and emotional immaturity (McCauley and Salter, 1995; Zabin and Kiragu 1998). Table 3.11 shows the percentage of adolescent women (age 15-19) who were mothers or were pregnant with their first child at the time of the survey, according to selected background characteristics. The proportion of teenagers who are already mothers is 17 percent, and another 4 percent are currently pregnant. The proportion of adolescents already on the family formation pathway rises rapidly with age from 3 percent at age 15 years to 45 percent at age 19 years (Figure 3.3). As expected, rural adolescents and those with less education tend to start childbearing earlier. Adolescent childbearing is especially prevalent in the Coast and Rift Valley provinces, where 28 percent of women age 15-19 are either pregnant or already mothers. 37 Table 3.11 Adolescent pregnancy and motherhood Percentage of women 15-19 who are mothers or pregnant with their first child, by selected background characteristics, Kenya 1998 _______________________________________________________________ Percentage who are: Percentage _________________ who have Pregnant begun Number Background with first child- of characteristic Mothers child bearing women _______________________________________________________________ Age 15 16 17 18 19 Residence Urban Rural Province Nairobi Central Coast Eastern Nyanza Rift Valley Western Education No education Primary incomplete Primary complete Secondary+ Total 1.7 1.6 3.3 421 4.3 1.7 6.0 335 14.1 5.5 19.6 299 26.2 3.9 30.1 430 39.5 5.4 44.9 365 14.9 2.7 17.5 408 18.0 3.8 21.8 1,443 9.2 1.0 10.2 180 13.3 1.8 15.1 144 25.2 2.6 27.8 132 12.4 3.3 15.7 347 19.3 3.7 23.0 460 23.1 4.7 27.8 357 16.4 5.3 21.6 232 40.6 0.7 41.4 54 17.2 4.5 21.7 1,024 25.7 4.2 29.9 343 8.1 1.1 9.2 431 17.3 3.5 20.9 1,851 Figure 3.3 Percentage of Adolescent Women Who Are Mothers or Pregnant with Their First Child, by Age 3.3 6 19.6 30.1 44.9 15 16 17 18 19 Age in Years 0 10 20 30 40 50 Percent Mothers Pregnant (1st child) KDHS 1998 39 Table 4.1 Knowledge of contraceptive methods Percentage of all women and men, of currently married women and men, and of sexually active and inactive unmarried women and men who know specific contraceptive methods, Kenya 1998 _____________________________________________________________________________________________________ Women Men ___________________________________ ____________________________________ Sexually Sexually Currently active No Currently active No Contraceptive All married unmarried sexual All married unmarried sexual method women women women experience men men men experience ______________________________________________________________________________________________________ Any method Any modern method Pill IUD Injectables Diaphragm/Foam/Jelly Condom Female sterilisation Male sterilisation Implants Any traditional method Periodic abstinence Withdrawal Other Number of respondents Mean number of methods 96.8 98.3 99.3 88.7 98.0 99.2 99.6 88.8 96.3 97.7 99.1 88.3 97.7 98.6 99.6 88.8 92.6 96.5 95.1 75.8 89.9 95.6 91.1 65.0 72.0 79.9 77.2 37.8 65.4 76.3 60.6 29.8 89.7 95.1 93.4 66.2 84.4 92.2 83.1 54.7 33.6 36.9 40.0 19.2 36.3 38.2 41.0 14.3 91.5 93.4 97.9 81.0 96.9 97.6 99.3 87.6 81.8 88.4 81.7 58.0 79.5 88.1 76.6 50.7 47.7 53.0 51.0 27.8 60.3 68.9 55.7 27.6 48.7 56.1 57.2 18.9 27.0 33.7 25.3 6.0 72.6 78.1 78.2 49.5 85.1 91.5 85.8 55.9 68.8 73.7 76.1 47.0 82.0 88.3 83.7 51.5 36.9 40.9 43.4 18.3 60.5 67.8 61.1 26.1 8.1 9.9 6.5 3.0 6.3 9.1 4.4 0.6 7,881 4,834 434 1,242 3,407 1,791 537 436 6.7 7.2 7.2 4.5 6.9 7.6 6.8 4.1 CHAPTER 4 FERTILITY REGULATION Karugu Ngatia, Zipora Gatiti, and Samuel Ogola This chapter presents the 1998 KDHS results regarding various aspects of contraceptive knowledge, attitudes, and behaviour. While the focus is on women, some results from the male survey are also presented, since men play an important role in the realisation of reproductive goals. To get an indication of interspousal communication and (perceived) agreement in knowledge and attitudes of couples regarding family planning, the responses of men were, where possible, compared with responses of their spouses in the same household. 4.1 Knowledge of Contraceptive Methods An important objective of the 1998 KDHS was to develop a profile of Kenyan men and women regarding knowledge of family planning methods. Individuals who are adequately informed about their options regarding methods of contraception are better able to develop a rational approach to planning their families. Information on knowledge of contraception 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 the respondent recognised it. As married women have the greatest level of exposure to the risk of pregnancy, the following presentation places emphasis on this subgroup. Table 4.1 shows the percent distribution of all women and men, currently married women and men, and sexually active, unmarried women and men by knowledge of contraceptive methods. Knowledge of family planning methods is nearly universal, with 96 percent of all women age 15-49 and 98 percent of all men age 15-54 knowing at least one modern method of family planning. Amongst the married population, men’s knowledge of contraceptive methods is slightly more 40 Table 4.2 Couples’ knowledge of contraceptive methods Percent distribution of couples by knowledge of specific contraceptive methods, Kenya 1998 ________________________________________________________________________________ Wife Husband knows Both knows method, Number Background know method, not hus- Neither of characteristic method not wife band know Total couples ________________________________________________________________________________ Any method Any modern method Pill IUD Injectables Diaphragm/Foam/Jelly Condom Female sterilisation Male sterilisation Implants Any traditional method Periodic abstinence Withdrawal Other 97.3 1.9 0.8 0.1 100.0 1,335 96.3 2.1 0.7 1.0 100.0 1,335 92.8 2.5 2.6 2.0 100.0 1,335 64.8 11.2 13.7 10.2 100.0 1,335 87.7 3.9 6.1 2.3 100.0 1,335 17.4 21.8 18.3 42.5 100.0 1,335 92.3 4.8 1.4 1.4 100.0 1,335 78.1 9.5 9.3 3.1 100.0 1,335 40.3 28.3 13.0 18.4 100.0 1,335 23.3 10.2 32.8 33.7 100.0 1,335 72.1 19.6 6.4 2.0 100.0 1,335 66.6 22.5 7.7 3.3 100.0 1,335 30.2 39.0 10.2 20.6 100.0 1,335 1.2 7.7 9.1 82.1 100.0 1,335 extensive, on average, than women’s. But among the unmarried, both those sexually active and those sexually inexperienced, women tend to be more informed about family planning. For instance, married women and men know an average of 7.2 and 7.6 methods, respectively, compared with 7.2 and 6.8 methods for unmarried sexually active women and men. The gap in knowledge between married and unmarried men, while not large, is most apparent for long-term and permanent methods. That this gap does not exist for women suggests that, while men tend to wait until marriage to become familiar with some methods of family planning (except for condoms), women begin their knowledge-seeking earlier—often before marriage. If true, this indicates young men in particular could benefit from programmes to improve knowledge of contraceptive methods. Among both currently married men and women, the pill, injectables, and condoms are the best-known methods of family planning. Injectables and the IUD tend to be better known among female respondents; whereas, male respondents are more likely to know about male sterilisation, withdrawal, and periodic abstinence than female respondents. Due to the recent introduction of contraceptive implants to the family planning programme in Kenya, and thus their more limited availability, implants are not well known, and were cited by only 56 percent of currently married women and 34 percent of currently married men. In 1993, just 14 percent of currently married women knew of implants. The vaginal methods (diaphragms, foams, jellies) are not well known by either male and female respondents. Other traditional methods of family planning (e.g., herbs) were mentioned by 10 percent of married women and 9 percent of married men. Knowledge of modern methods of contraception has increased since the 1993 KDHS. Knowledge of the pill was already high in 1993 (92 percent among currently married women) but rose further to 97 percent. Among other modern methods, significant increases in knowledge occurred for injectables (88 to 95 percent), condoms (83 to 93 percent), male sterilisation (41 to 53 percent), IUD (73 to 80 percent), and female sterilisation (81 to 88 percent). Table 4.2 shows the distribution of couples in the KDHS sample of households by contraceptive knowledge. For most methods, both husband and wife tend to report knowledge of family planning. The exceptions occur for the least-known methods (i.e., vaginals, implants, periodic abstinence, and “other traditional methods”); in these cases, usually only the husband or only the wife knows of the method. When 41 Table 4.3 Ever use of contraception Percentage of all women and of currently married women who have ever used a contraceptive method, by method and age, Kenya 1998 _____________________________________________________________________________________________________________ Modern method Traditional method ___________________________________________________________ ___________________________ Any Female Other Any Periodic Number Any modern Inject- Con- sterili- Im- modern trad. absti- With- of Age method method Pill IUD ables dom sation plants methods method nence drawal Other women ___________________________________________________________________________________________________________________ ALL WOMEN ___________________________________________________________________________________________________________________ 15-19 15.8 9.9 4.3 0.1 1.7 5.9 0.0 0.0 0.0 8.7 8.1 1.1 0.3 1,851 20-24 52.1 38.7 23.7 2.0 15.0 12.4 0.0 1.0 0.0 23.7 22.3 4.5 1.1 1,548 25-29 67.3 57.3 38.2 5.5 26.7 13.4 1.2 1.4 0.7 23.8 21.6 4.2 2.1 1,371 30-34 70.2 60.5 40.6 8.8 30.5 11.9 5.2 1.2 0.9 23.8 21.4 4.7 2.1 986 35-39 68.6 61.8 35.6 13.2 32.2 6.8 11.7 1.5 1.3 16.9 14.3 2.9 2.5 991 40-44 61.1 53.1 27.0 14.8 23.8 7.0 15.2 0.4 1.6 17.0 13.0 2.5 3.8 637 45-49 52.7 42.7 26.3 13.4 17.0 5.1 10.9 0.4 1.5 17.8 14.2 2.7 3.5 497 Total 51.3 42.2 25.7 6.2 18.8 9.4 4.2 0.8 0.6 18.4 16.5 3.2 1.8 7,881 ____________________________________________________________________________________________________________________ CURRENTLY MARRIED WOMEN ____________________________________________________________________________________________________________________ 15-19 37.2 23.5 10.9 0.0 5.4 13.6 0.0 0.0 0.0 22.8 20.2 4.8 1.3 285 20-24 59.7 45.5 29.0 3.0 19.4 11.8 0.0 1.2 0.0 24.9 22.8 5.0 1.6 948 25-29 69.6 58.3 38.8 5.8 27.3 11.7 1.4 1.3 0.5 25.0 22.5 4.4 2.6 1,069 30-34 71.1 60.4 40.5 8.7 31.2 10.6 5.7 1.1 0.7 24.0 22.0 5.0 1.6 822 35-39 69.5 62.8 35.5 13.5 31.8 6.6 12.9 1.6 1.4 16.4 13.4 3.2 2.7 832 40-44 63.6 55.2 27.3 16.0 24.1 5.4 16.8 0.5 1.9 17.7 13.9 2.5 3.2 511 45-49 52.8 42.9 25.6 12.8 18.5 5.8 11.9 0.3 1.6 18.2 14.8 2.2 3.2 365 Total 64.1 53.4 32.7 8.3 24.9 9.7 6.2 1.1 0.8 21.9 19.3 4.1 2.3 4,834 only the husband or the wife knows the method, usually it is the husband who knows the method. The exception is implants, which are more likely to be known by women than men. 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 any method (with the intention of delaying or avoiding pregnancy). Table 4.3 shows the percentage of women who have ever used family planning, according to method and age. Sixty-four percent of currently married women reported having ever used a method of family planning; 53 percent used a modern method, and 22 percent used a traditional method. The modern methods most commonly used are the pill (33 percent), injectables (25 percent), and condoms (10 percent). Ever use of other modern methods does not exceed 8 percent. 4.3 Current Use of Contraceptive Methods The contraceptive prevalence rate (CPR) for Kenya—i.e., percentage of currently married women who are using any method of family planning—is 39 percent (Table 4.4). Most current users of contraception use a modern method; the CPR for modern methods is 32 percent, while 8 percent of currently married women use a traditional method (considered less effective for the prevention of unwanted pregnancy). Injectables and pills are the most commonly used contraceptive methods; they are currently used by 12 and 9 percent of married women, respectively. Six percent of married women have been sterilised, 3 percent are using the IUD, and 1 percent each are using condoms and implants. Use of male sterilisation and vaginal methods (diaphragm, foam, etc.) is rare. Current use of periodic abstinence as a contraceptive method (rhythm, calendar method, Billings, etc.) was reported by 6 percent, withdrawal by 1 percent, and other traditional methods by 1 percent of married women. 42 Table 4.4 Current use of contraception: women Percentage of all women, of currently married women, and of sexually active unmarried women who are currently using a contraceptive method, by method and age, Kenya 1998 _________________________________________________________________________________________________________________________ Modern method Traditional method _______________________________________________________ __________________________ Any Female Any Periodic Not Number Any modern Inject- Con- sterili- Im- Other trad. absti- With- currently of Age method method Pill IUD ables dom sation plants modern method nence drawal Other using Total women _________________________________________________________________________________________________________________________ ALL WOMEN _________________________________________________________________________________________________________________________ 15-19 7.6 4.2 1.7 0.0 1.0 1.6 0.0 0.0 0.0 3.3 3.0 0.1 0.2 92.4 100.0 1,851 20-24 27.0 19.9 7.9 0.8 8.9 1.6 0.0 0.7 0.0 7.1 6.4 0.3 0.4 73.0 100.0 1,548 25-29 38.7 31.1 10.3 2.1 14.6 1.6 1.2 1.4 0.0 7.6 6.5 0.5 0.6 61.3 100.0 1,371 30-34 43.8 34.9 11.4 2.6 12.9 1.8 5.2 1.0 0.0 8.8 7.3 0.9 0.6 56.2 100.0 986 35-39 44.0 37.7 5.7 2.7 15.1 1.3 11.7 1.2 0.0 6.3 4.9 0.5 0.9 56.0 100.0 991 40-44 40.8 33.3 5.2 5.8 5.7 0.6 15.2 0.4 0.3 7.5 5.6 0.5 1.5 59.2 100.0 637 45-49 28.0 23.6 2.6 3.1 5.3 1.7 10.9 0.0 0.0 4.4 3.0 0.1 1.3 72.0 100.0 497 Total 29.9 23.6 6.5 1.9 8.8 1.5 4.2 0.7 0.0 6.3 5.3 0.4 0.6 70.1 100.0 7,881 _________________________________________________________________________________________________________________________ CURRENTLY MARRIED WOMEN _________________________________________________________________________________________________________________________ 15-19 18.0 10.1 3.8 0.0 4.1 2.3 0.0 0.0 0.0 7.9 6.7 0.1 1.2 82.0 100.0 285 20-24 31.2 24.8 10.0 1.3 11.1 1.6 0.0 0.7 0.0 6.4 5.3 0.5 0.7 68.8 100.0 948 25-29 40.1 32.2 10.6 2.5 15.4 1.2 1.4 1.2 0.0 8.0 6.7 0.6 0.6 59.9 100.0 1,069 30-34 45.6 35.9 11.9 2.8 13.2 1.4 5.7 0.9 0.0 9.7 8.1 1.1 0.5 54.4 100.0 822 35-39 47.2 40.4 6.1 3.1 15.6 1.2 12.9 1.4 0.0 6.8 5.2 0.6 1.0 52.8 100.0 832 40-44 44.3 36.5 6.1 6.2 6.0 0.4 16.8 0.5 0.4 7.8 5.9 0.4 1.6 55.7 100.0 511 45-49 31.1 26.1 3.3 3.2 5.9 1.9 11.9 0.0 0.0 5.0 3.9 0.1 1.0 68.9 100.0 365 Total 39.0 31.5 8.5 2.7 11.8 1.3 6.2 0.8 0.0 7.5 6.1 0.6 0.8 61.0 100.0 4,834 _________________________________________________________________________________________________________________________ SEXUALLY ACTIVE, UNMARRIED WOMEN _________________________________________________________________________________________________________________________ 15-19 30.4 20.4 6.9 0.0 2.2 11.3 0.0 0.0 0.0 9.9 9.0 1.0 0.0 69.6 100.0 149 20-24 50.7 35.0 11.8 0.0 17.3 4.1 0.0 1.8 0.0 15.7 15.7 0.0 0.0 49.3 100.0 98 25+ 57.1 49.5 13.1 3.2 17.5 7.6 5.7 2.3 0.0 7.6 7.6 0.0 0.0 42.9 100.0 187 Total 46.5 36.2 10.7 1.4 12.2 8.1 2.5 1.4 0.0 10.2 9.9 0.3 0.0 53.5 100.0 434 1 It should be borne in mind that contraceptive use among males is likely to be higher than among females because men who are in a polygynous or multi-partner relationship will often report on use with any partner. 43 Use of modern methods rises with age from 10 percent among married women age 15-19 to a peak of 40 percent at age 35-39, after which it declines to 26 percent among women age 45-49. As expected, female sterilisation is used more commonly by older women, while pills and injectables are used by women in the peak childbearing years (age 20-39). Use of modern methods is slightly higher among sexually active unmarried women (36 percent) than among married women (32 percent). The difference is largely attributable to the greater use of condoms by unmarried women (8 percent) than currently married women (1 percent). Reported use of family planning by men (and their partners) is higher than use reported by women1 (Table 4.5). The CPR for married men age 15-54 is 62 percent; for modern methods, the CPR is 39 percent. Most of the male-female difference in use of modern methods is explained by higher reported use of the pill (12 percent) and condoms (8 percent) among men. Men also report much higher use of periodic abstinence (20 percent) than women, but this is probably the result of men adopting a broader (and incorrect) definition of this method to include all periods of abstinence (volitional or not). There is a sharp contrast between married men and sexually active unmarried men regarding injectables and pill use on one hand and condom use on the other. Nearly one-half of unmarried men (47 percent) report using condoms (vs. 8 percent of married men), but only 4 percent report using the pill or injectables (vs. 21 percent of married men). This may represent different reproductive and health (disease prevention) strategies related to marital status. That sexually active unmarried women are reporting greater pill or injectables use (23 percent) than their male counterparts (4 percent) may mean that these men are often not told by their partners of pill or injectables use. 4.4 Trends at the National Level Compared with other countries in East and southern Africa where DHS surveys have been recently conducted, Kenya’s level of contraceptive use is exceeded only by Zimbabwe and South Africa (Figure 4.1). Contraceptive use, especially use of modern methods, has risen sharply since the early 1980s and is probably the principal cause of the fertility decline shown in the previous section. The 1984 Contraceptive Prevalence Survey (CPS), 1989 KDHS, 1993 KDHS, and 1998 KDHS have documented the increase in modern method use from 10 to 18 to 27 to, now, 32 percent. The rate of increase in uptake of contraception has slowed, however. Between 1984 and 1993, nearly two percentage points were added to the contraceptive prevalence rate (modern methods) each year; this has slowed to less than one percentage point per year between the 1993 KDHS and 1998 KDHS. The current method mix indicates a shift in the contraceptive behaviour of Kenyan women (Figure 4.2). The rapid increase in use of injectables (from 7 percent in 1993 to 12 percent in 1998) to become the predominant method, plus small rises in the use of implants, condoms, and female sterilisation, have more than offset small drops in pill and IUD use. Thus, new acceptance of contraception and method switching have characterised the 1993-1998 intersurvey period. 44 Ta bl e 4. 5 C ur re nt u se o f c on tra ce pt io n: m en Pe rc en ta ge o f a ll m en , o f c ur re n tly m ar rie d m en , a nd o f s ex ua lly a ct iv e un m ar rie d m en w ho a re c ur re nt ly u sin g a co nt ra ce pt iv e m et ho d, by m et ho d an d ag e, K en ya 1 99 8 _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ M o de rn m et ho d Tr ad iti on al m et ho d _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ A ny Fe m al e A n y Pe rio di c N o t N um be r A ny m o de rn In jec t- Co n - st er ili - Im - O th er tr ad . ab sti - W ith - cu rr en tly o f A ge m et ho d m et ho d Pi ll IU D ab le s do m sa tio n pl an ts m o de rn m et ho d n en ce dr aw al O th er u sin g To ta l m en _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ A LL M EN _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 15 -1 9 24 .7 17 .5 0. 9 0. 0 0. 1 16 .6 0. 0 0. 0 0. 0 7. 1 7. 0 0. 1 0. 0 75 .3 10 0. 0 81 1 20 -2 4 54 .6 34 .8 2. 5 0. 0 0. 9 31 .0 0. 0 0. 0 0. 4 19 .8 18 .3 0. 8 0. 7 45 .4 10 0. 0 58 9 25 -2 9 60 .3 43 .3 10 .1 1. 1 5 .2 25 .0 0. 0 1. 5 0. 3 17 .0 16 .3 0. 4 0. 3 39 .7 10 0. 0 46 3 30 -3 4 62 .4 40 .0 15 .7 1. 0 11 .5 9. 2 1. 3 1. 2 0. 0 22 .5 19 .3 0. 6 2. 6 37 .6 10 0. 0 41 8 35 -3 9 64 .6 41 .1 13 .9 1. 3 13 .4 8. 2 2. 6 1. 4 0. 5 23 .5 21 .2 0. 5 1. 8 35 .4 10 0. 0 37 5 40 -4 4 59 .4 35 .7 11 .3 3. 4 6. 6 5. 1 8. 0 0. 6 0. 9 23 .7 20 .6 0. 7 2. 4 40 .6 10 0. 0 29 1 45 -4 9 64 .8 42 .5 6. 8 5. 3 5. 2 5. 7 17 .9 1. 6 0. 0 22 .3 18 .8 1. 4 2. 2 35 .2 10 0. 0 27 8 50 -5 4 56 .9 32 .1 6. 8 1. 8 2. 4 4. 6 16 .3 0. 0 0. 0 24 .8 17 .4 1. 4 6. 0 43 .1 10 0. 0 18 3 To ta l 51 .7 33 .7 7. 4 1. 2 4. 9 15 .9 3. 5 0. 7 0. 2 18 .0 16 .0 0. 6 1. 4 48 .3 10 0. 0 3, 40 7 _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ CU RR EN TL Y M A RR IE D M EN _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 15 -1 9 * * * * * * * * * * * * * * 10 0. 0 6 20 -2 4 44 .9 20 .7 3. 3 0. 0 5. 3 12 .1 0. 0 0. 0 0. 0 24 .2 18 .7 5. 2 0. 3 55 .1 10 0. 0 95 25 -2 9 57 .8 41 .6 15 .7 0. 9 7 .9 15 .5 0. 0 1. 0 0. 5 16 .2 15 .4 0. 7 0. 1 42 .2 10 0. 0 28 3 30 -3 4 64 .4 39 .6 17 .0 1. 2 12 .2 6. 3 1. 6 1. 3 0. 0 24 .8 21 .2 0. 7 3. 0 35 .6 10 0. 0 36 4 35 -3 9 67 .2 42 .0 15 .3 1. 4 13 .7 7. 1 2. 8 1. 5 0. 2 25 .2 22 .7 0. 5 2. 0 32 .8 10 0. 0 34 1 40 -4 4 63 .8 38 .9 12 .3 3. 7 7. 2 5. 3 8. 7 0. 6 1. 0 25 .0 21 .6 0. 8 2. 6 36 .2 10 0. 0 26 5 45 -4 9 66 .3 43 .3 6. 2 5. 6 5. 5 5. 4 19 .0 1. 7 0. 0 23 .0 19 .2 1. 5 2. 3 33 .7 10 0. 0 26 3 50 -5 4 58 .5 33 .1 7. 2 1. 9 2. 4 4. 6 17 .1 0. 0 0. 0 25 .4 17 .7 1. 5 6. 2 41 .5 10 0. 0 17 5 To ta l 62 .3 39 .1 12 .4 2. 2 8. 7 7. 8 6. 6 1. 1 0. 3 23 .3 19 .8 1. 1 2. 4 37 .7 10 0. 0 1, 79 1 _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ SE X U A LL Y A CT IV E, U N M A RR IE D M EN _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 15 -1 9 59 .3 44 .5 1. 9 0. 0 0. 0 42 .6 0. 0 0. 0 0. 0 14 .8 14 .5 0. 3 0. 0 40 .7 10 0. 0 19 3 20 -2 4 71 .0 52 .7 2. 0 0. 0 0. 0 50 .7 0. 0 0. 0 0. 0 18 .3 18 .3 0. 0 0. 0 29 .0 10 0. 0 21 0 25 + 73 .3 57 .2 4. 7 2. 0 3. 9 46 .0 0. 0 0. 7 0. 0 16 .1 16 .1 0. 0 0. 0 26 .7 10 0. 0 13 4 To ta l 67 .4 50 .9 2. 7 0. 5 1. 0 46 .6 0. 0 0. 2 0. 0 16 .5 16 .4 0. 1 0. 0 32 .6 10 0. 0 53 7 _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ N ot e: A n as te ris k in di ca te s t ha t t he fi gu re is b as ed o n fe w er th an 2 5 un w ei gh te d ca se s a nd h as b ee n su pp re ss ed . 45 Figure 4.1 Current Use of Family Planning among Currently Married Women Age 15-49, Selected Countries in East Africa and Southern Africa 56 48 39 26 18 13 6 South Africa 1998 Zimbabwe 1994 KENYA 1998 Zambia 1996 Tanzania 1996 Uganda 1995 Mozambique 1997 0 10 20 30 40 50 60 Percent Modern Methods Traditional Methods Figure 4.2 Percentage of Currently Married Women Currently Using Contraception by Method,1993 KDHS and 1998 KDHS Modern method Pill Injectables Female sterilisation IUD Condom Other modern Traditional method 0 5 10 15 20 25 30 Percent 1993 KDHS 1998 KDHS 46 Ta bl e 4 .6 C ur re nt u se o f c on tra ce pt io n by b ac kg ro un d ch ar ac te ris tic s Pe rc en t d ist rib ut io n of cu rre nt ly m ar rie d w om en b y co nt ra ce pt iv e m et ho d cu rre nt ly u se d, ac co rd in g to se le ct ed b ac kg ro un d ch ar ac te ris tic s, K en ya 1 99 8 _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

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