Nigeria - Demographic and Health Survey - 2019

Publication date: 2019

Nigeria Demographic and Health Survey 2018 N igeria 2018 D em ographic and H ealth S urvey The Federal Republic of Nigeria Nigeria Demographic and Health Survey 2018 National Population Commission Abuja, Nigeria The DHS Program ICF Rockville, Maryland, USA October 2019 The 2018 Nigeria Demographic and Health Survey (2018 NDHS) was implemented by the National Population Commission (NPC) in collaboration with the National Malaria Elimination Programme (NMEP) of the Federal Ministry of Health, Nigeria. The funding for the 2018 NDHS was provided by the United States Agency for International Development (USAID), Global Fund, Bill and Melinda Gates Foundation (BMGF), the United Nations Population Fund (UNFPA), and World Health Organisation (WHO). ICF provided technical assistance through The DHS Program, a USAID-funded project providing support and technical assistance in the implementation of population and health surveys in countries worldwide. Additional information about the 2018 NDHS may be obtained from the headquarters of the National Population Commission (NPC), Plot 2031, Olusegun Obasanjo Way, Zone 7, Wuse, PMB 0281, Abuja, Nigeria; telephone: 234-09-523-9173; fax: 234-09-523-1024; email: info@populationgov.ng; internet: www.population.gov.ng. Information about The DHS Program may be obtained from ICF, 530 Gaither Road, Suite 500, Rockville, MD 20850, USA; telephone: +1-301-407-6500; fax: +1-301-407-6501; email: info@DHSprogram.com; internet: www.DHSprogram.com. Cover photograph: © 2019 Media Unit of the National Theatre, Iganmu Lagos. Recommended citation: National Population Commission (NPC) [Nigeria] and ICF. 2019. Nigeria Demographic and Health Survey 2018. Abuja, Nigeria, and Rockville, Maryland, USA: NPC and ICF. Contents • iii CONTENTS TABLES AND FIGURES . ix FOREWORD . xix 2018 NIGERIA DEMOGRAPHIC AND HEALTH SURVEY STEERING COMMITTEE . xxi CONTRIBUTORS TO THE REPORT . xxiii READING AND UNDERSTANDING TABLES FROM THE 2018 NIGERIA DHS . xxv ACRONYMS AND ABBREVIATIONS . xxxiii SUSTAINABLE DEVELOPMENT GOAL INDICATORS . xxxvii MAP OF NIGERIA . xxxviii 1 INTRODUCTION AND SURVEY METHODOLOGY . 1 1.1 Survey Objectives . 1 1.2 Sample Design . 1 1.3 Questionnaires . 3 1.4 Anthropometry, Anaemia Testing, Malaria Testing, and Sickle Cell Anaemia Testing . 4 1.5 Pretest . 6 1.6 Training of Field Staff . 6 1.7 Fieldwork . 7 1.8 Data Processing . 8 1.9 Response Rates . 8 2 HOUSING CHARACTERISTICS AND HOUSEHOLD POPULATION . 11 2.1 Drinking Water Sources and Treatment . 11 2.2 Sanitation . 13 2.3 Exposure to Smoke inside the Home . 15 2.4 Household Wealth . 15 2.5 Handwashing . 16 2.6 Household Population and Composition . 16 2.7 Children’s Living Arrangements and Parental Survival . 17 2.8 Birth Registration . 17 2.9 Education . 18 2.9.1 Educational Attainment . 18 2.9.2 School Attendance . 19 3 CHARACTERISTICS OF RESPONDENTS . 43 3.1 Basic Characteristics of Survey Respondents . 43 3.2 Education and Literacy . 44 3.3 Mass Media Exposure . 45 3.4 Internet Usage . 46 3.5 Employment . 46 3.6 Occupation . 47 3.7 Health Insurance Coverage . 48 3.8 Tobacco Use . 49 4 MARRIAGE AND SEXUAL ACTIVITY . 79 4.1 Marital Status . 79 4.2 Polygyny . 80 4.3 Age at First Marriage . 81 iv • Contents 4.4 Age at First Sexual Intercourse . 81 4.5 Recent Sexual Activity . 82 5 FERTILITY . 97 5.1 Current Fertility . 97 5.2 Children Ever Born and Living . 99 5.3 Birth Intervals . 99 5.4 Insusceptibility to Pregnancy . 100 5.5 Age at First Birth . 101 5.6 Teenage Childbearing . 102 6 FERTILITY PREFERENCES . 117 6.1 Desire for Another Child . 117 6.2 Ideal Family Size . 118 6.3 Fertility Planning Status . 119 6.4 Wanted Fertility Rates . 120 7 FAMILY PLANNING . 129 7.1 Contraceptive Knowledge and Use . 130 7.2 Source of Modern Contraceptive Methods . 132 7.3 Informed Choice . 132 7.4 Discontinuation of Contraceptives . 133 7.5 Demand for Family Planning . 133 7.6 Contact of Nonusers with Family Planning Providers . 136 8 INFANT AND CHILD MORTALITY . 163 8.1 Infant and Child Mortality . 164 8.2 Biodemographic Risk Factors . 165 8.3 Perinatal Mortality . 166 8.4 High-risk Fertility Behaviour . 167 9 MATERNAL HEALTH CARE . 173 9.1 Antenatal Care Coverage and Content . 174 9.1.1 Skilled Providers . 174 9.1.2 Timing and Number of ANC Visits . 174 9.2 Components of ANC Visits . 175 9.3 Protection against Neonatal Tetanus . 175 9.4 Delivery Services . 176 9.4.1 Institutional Deliveries . 176 9.4.2 Skilled Assistance during Delivery . 177 9.4.3 Delivery by Caesarean . 178 9.4.4 Referral to Place of Delivery . 179 9.4.5 Reasons for Referral and Time Taken . 180 9.4.6 Means of Transportation to Health Facility . 180 9.4.7 Thermal Care for Newborns . 180 9.4.8 Cord Care . 180 9.5 Postnatal Care . 181 9.5.1 Postnatal Health Check for Mothers . 181 9.5.2 Postnatal Health Check for Newborns . 182 9.6 Problems in Accessing Health Care . 182 9.7 Fistula . 183 Contents • v 10 CHILD HEALTH . 223 10.1 Birth Weight . 223 10.2 Vaccination of Children. 224 10.3 Symptoms of Acute Respiratory Infection . 227 10.4 Fever . 228 10.5 Diarrhoeal Disease . 228 10.5.1 Prevalence of Diarrhoea and Treatment-seeking Behaviour . 228 10.5.2 Feeding Practices . 229 10.5.3 Oral Rehydration Therapy and Other Treatments . 229 10.5.4 Knowledge of ORS Packets . 230 10.6 Treatment of Childhood Illness . 231 10.7 Disposal of Children’s Stools . 231 11 NUTRITION OF CHILDREN AND WOMEN . 255 11.1 Nutritional Status of Children . 255 11.1.1 Anthropometry Training and Data Collection . 257 11.1.2 Levels of Child Malnutrition . 257 11.2 Infant and Young Child Feeding Practices . 259 11.2.1 Early Initiation of Breastfeeding . 259 11.2.2 Exclusive Breastfeeding and Continued Breastfeeding . 260 11.2.3 Median Duration of Breastfeeding . 260 11.2.4 Bottle Feeding . 261 11.2.5 Introduction of Complementary Foods . 261 11.2.6 Minimum Dietary Diversity, Minimum Meal Frequency, and Minimum Acceptable Diet . 262 11.3 Anaemia Prevalence in Children . 263 11.4 Prevalence of Sickle Cell Trait and Disease in Children . 265 11.5 Presence of Iodised Salt in Households . 265 11.6 Micronutrient Intake and Supplementation among Children. 266 11.7 Women’s Nutritional Status . 266 11.8 Anaemia Prevalence in Women . 268 11.9 Micronutrient Supplementation and Deworming during Pregnancy . 268 11.10 Minimum Dietary Diversity for Women . 269 12 MALARIA . 297 12.1 Ownership of Insecticide-treated Nets . 298 12.2 Household Access to and Use of ITNs . 300 12.3 Use of ITNs by Children and Pregnant Women . 301 12.4 Reasons for Not Using the Net the Night Preceding the Interview . 302 12.5 Malaria in Pregnancy . 302 12.6 Case Management of Malaria in Children . 303 12.7 Prevalence of Low Haemoglobin in Children . 304 12.8 Prevalence of Malaria in Children . 305 12.9 Beliefs about the Effectiveness of Malaria Behaviours and Products and about Malaria Consequences . 307 13 HIV/AIDS-RELATED KNOWLEDGE, ATTITUDES, AND BEHAVIOUR . 343 13.1 HIV/AIDS Knowledge, Transmission, and Prevention Methods . 344 13.2 Knowledge about Mother-to-Child Transmission . 346 13.3 Discriminatory Attitudes towards People Living with HIV . 347 13.4 Multiple Sexual Partners . 347 13.5 Paid Sex . 348 13.6 Male Circumcision . 348 vi • Contents 13.7 Self-reporting of Sexually Transmitted Infections . 349 13.8 HIV/AIDS-related Knowledge and Behaviour among Young People . 349 13.8.1 Comprehensive Knowledge . 349 13.8.2 First Sex . 350 13.8.3 Premarital Sex . 350 13.8.4 Multiple Sexual Partners . 350 14 ADULT AND MATERNAL MORTALITY . 371 14.1 Data . 371 14.2 Direct Estimates of Adult Mortality . 372 14.3 Trends in Adult Mortality . 373 14.4 Direct Estimates of Maternal Mortality . 373 14.5 Trends in Pregnancy-Related Mortality . 374 15 WOMEN’S EMPOWERMENT . 379 15.1 Married Women’s and Men’s Employment . 380 15.2 Control over Women’s Earnings . 381 15.3 Control over Men’s Earnings . 381 15.4 Women’s Control over Their Own Earnings and over Those of Their Husbands . 382 15.5 Women’s and Men’s Ownership of Assets . 382 15.6 Possession of Title or Deed for a House or Land . 383 15.7 Ownership and Use of Bank Accounts and Mobile Phones . 383 15.8 Women’s Participation in Decision Making . 383 15.9 Attitudes toward Wife Beating . 385 15.10 Negotiating Sexual Relations . 386 15.11 Women’s Empowerment and Demographic and Health Outcomes . 386 16 DOMESTIC VIOLENCE . 427 16.1 Measurement of Violence . 428 16.2 Women’s Experience of Physical Violence. 429 16.2.1 Perpetrators of Physical Violence . 430 16.3 Experience of Sexual Violence . 430 16.3.1 Prevalence of Sexual Violence . 430 16.3.2 Perpetrators of Sexual Violence . 430 16.4 Experience of Different Forms of Violence . 430 16.5 Marital Control by Husband . 431 16.6 Forms of Spousal Violence . 431 16.6.1 Prevalence of Spousal Violence . 431 16.6.2 Onset of Spousal Violence . 434 16.7 Injuries to Women due to Spousal Violence . 434 16.8 Violence Initiated by Women against Husbands . 435 16.9 Help Seeking among Women Who Have Experienced Violence . 435 17 DISABILITY . 457 17.1 Disability by Domain and Age . 457 17.2 Disability among Adults by Other Background Characteristics . 458 18 FEMALE GENITAL MUTILATION . 465 18.1 Respondents’ Knowledge of Female Genital Mutilation. 465 18.2 Prevalence of Female Genital Mutilation . 466 18.2.1 Prevalence and Type of Circumcision . 466 18.2.2 Unclassified Types of Female Circumcision . 467 18.2.3 Age at Circumcision . 468 Contents • vii 18.3 Circumcision of Daughters . 468 18.4 Person Who Performed the Circumcision . 469 18.5 Attitudes towards Female Circumcision . 469 REFERENCES. 485 APPENDIX A SAMPLE DESIGN . 489 A.1 Introduction . 489 A.2 Sample Frame . 489 A.3 Sample Design and Implementation . 491 A.4 Sample Probabilities and Sampling Weights . 496 APPENDIX B ESTIMATES OF SAMPLING ERRORS . 497 APPENDIX C DATA QUALITY TABLES . 547 APPENDIX D PERSONS INVOLVED IN THE 2018 NIGERIA DEMOGRAPHIC AND HEALTH SURVEY . 557 APPENDIX E QUESTIONNAIRES . 563 Household Questionnaire . 565 Woman’s Questionnaire . 583 Man’s Questionnaire . 663 Biomarker Questionnaire . 689 Fieldworker Questionnaire . 705 Tables and Figures • ix TABLES AND FIGURES 1 INTRODUCTION AND SURVEY METHODOLOGY . 1 Table 1.1 Results of the household and individual interviews . 9 Figure 1.1 2018 Nigeria DHS sample design . 2 2 HOUSING CHARACTERISTICS AND HOUSEHOLD POPULATION . 11 Table 2.1.1 Household drinking water . 21 Table 2.1.2 Drinking water according to zone, state, and wealth . 22 Table 2.1.3 Treatment of household drinking water . 23 Table 2.2 Availability of water . 24 Table 2.3.1 Household sanitation facilities . 24 Table 2.3.2 Sanitation facility type according to zone, state, and wealth . 25 Table 2.4 Household characteristics . 26 Table 2.5 Household possessions . 27 Table 2.6 Wealth quintiles . 28 Table 2.7 Handwashing . 29 Table 2.8 Household population by age, sex, and residence . 31 Table 2.9 Household composition . 32 Table 2.10 Children’s living arrangements and orphanhood . 33 Table 2.11 Birth registration of children under age 5 . 35 Table 2.12 Birth registration of children under age 5 by authority . 36 Table 2.13.1 Educational attainment of the female household population . 37 Table 2.13.2 Educational attainment of the male household population . 39 Table 2.14 School attendance ratios . 41 Figure 2.1 Household drinking water by residence . 12 Figure 2.2 Improved water source by state . 12 Figure 2.3 Household toilet facilities by residence . 14 Figure 2.4 Household wealth by residence . 16 Figure 2.5 Population pyramid . 17 Figure 2.6 Birth registration by household wealth . 18 Figure 2.7 Secondary school attendance by household wealth . 19 3 CHARACTERISTICS OF RESPONDENTS . 43 Table 3.1 Background characteristics of respondents . 51 Table 3.2.1 Educational attainment: Women . 53 Table 3.2.2 Educational attainment: Men . 54 Table 3.3.1 Literacy: Women . 55 Table 3.3.2 Literacy: Men . 56 Table 3.4.1 Exposure to mass media: Women . 58 Table 3.4.2 Exposure to mass media: Men . 60 Table 3.5.1 Internet usage: Women . 62 Table 3.5.2 Internet usage: Men . 64 Table 3.6.1 Employment status: Women . 66 Table 3.6.2 Employment status: Men. 68 Table 3.7.1 Occupation: Women . 70 Table 3.7.2 Occupation: Men . 72 Table 3.8 Type of employment: Women . 74 Table 3.9.1 Health insurance coverage: Women . 74 Table 3.9.2 Health insurance coverage: Men . 75 Table 3.10.1 Tobacco smoking: Women . 76 Table 3.10.2 Tobacco smoking: Men . 77 x • Tables and Figures Table 3.11 Average number of cigarettes smoked daily: Men . 78 Table 3.12 Smokeless tobacco use and any tobacco use . 78 Figure 3.1 Education of survey respondents . 44 Figure 3.2 Secondary education by household wealth . 44 Figure 3.3 Secondary education by state . 45 Figure 3.4 Exposure to mass media . 46 Figure 3.5 Employment status by education . 47 Figure 3.6 Occupation . 48 4 MARRIAGE AND SEXUAL ACTIVITY . 79 Table 4.1 Current marital status . 84 Table 4.2.1 Number of women’s co-wives . 85 Table 4.2.2 Number of men’s wives . 87 Table 4.3 Age at first marriage. 89 Table 4.4 Median age at first marriage by background characteristics . 90 Table 4.5 Age at first sexual intercourse . 91 Table 4.6 Median age at first sexual intercourse according to background characteristics . 92 Table 4.7.1 Recent sexual activity: Women . 93 Table 4.7.2 Recent sexual activity: Men . 95 Figure 4.1 Marital status . 79 Figure 4.2 Trends in polygyny . 80 Figure 4.3 Polygyny by state . 80 Figure 4.4 Women’s median age at marriage by wealth . 81 Figure 4.5 Median age at first sex and first marriage . 82 Figure 4.6 Trends in early sexual intercourse . 82 5 FERTILITY . 97 Table 5.1 Current fertility . 104 Table 5.2 Fertility by background characteristics . 105 Table 5.3.1 Trends in age-specific fertility rates . 106 Table 5.3.2 Trends in age-specific and total fertility rates . 106 Table 5.4 Children ever born and living . 106 Table 5.5 Birth intervals . 107 Table 5.6 Postpartum amenorrhoea, abstinence, and insusceptibility . 109 Table 5.7 Median duration of amenorrhoea, postpartum abstinence, and postpartum insusceptibility . 110 Table 5.8 Menopause . 111 Table 5.9 Age at first birth . 111 Table 5.10 Median age at first birth . 112 Table 5.11 Teenage pregnancy and motherhood. 113 Table 5.12 Sexual and reproductive health behaviours before age 15 . 115 Figure 5.1 Trends in fertility by residence . 98 Figure 5.2 Trends in age-specific fertility . 98 Figure 5.3 Fertility by state . 98 Figure 5.4 Fertility by mother’s education . 99 Figure 5.5 Birth intervals . 99 Figure 5.6 Teenage pregnancy and motherhood by state . 102 6 FERTILITY PREFERENCES . 117 Table 6.1 Fertility preferences by number of living children . 122 Table 6.2.1 Desire to limit childbearing: Women . 122 Table 6.2.2 Desire to limit childbearing: Men . 123 Table 6.3 Ideal number of children by number of living children . 124 Tables and Figures • xi Table 6.4 Mean ideal number of children . 125 Table 6.5 Fertility planning status . 127 Table 6.6 Wanted fertility rates . 128 Figure 6.1 Trends in desire to limit childbearing by number of living children . 118 Figure 6.2 Desire to limit childbearing by number of living children . 118 Figure 6.3 Ideal family size . 119 Figure 6.4 Ideal family size by number of living children . 119 Figure 6.5 Fertility planning status . 120 Figure 6.6 Trends in wanted and actual fertility . 121 7 FAMILY PLANNING . 129 Table 7.1 Knowledge of contraceptive methods . 138 Table 7.2 Current use of contraception by age . 139 Table 7.3 Trends in current use of contraception . 140 Table 7.4 Current use of contraception according to background characteristics . 141 Table 7.5 Knowledge of fertile period . 143 Table 7.6 Knowledge of fertile period by age . 143 Table 7.7 Source of modern contraception methods . 144 Table 7.8 Use of social marketing brand pills and condoms . 145 Table 7.9 Informed choice . 146 Table 7.10 Twelve-month contraceptive discontinuation rates . 146 Table 7.11 Reasons for discontinuation . 147 Table 7.12.1 Need and demand for family planning among currently married women . 148 Table 7.12.2 Need and demand for family planning for all women and for sexually active unmarried women . 150 Table 7.13 Decision making about family planning . 152 Table 7.14 Future use of contraception . 154 Table 7.15.1 Exposure to family planning messages: Women . 155 Table 7.15.2 Exposure to family planning messages: Men . 157 Table 7.16 Exposure to specific family planning messages . 159 Table 7.17 Contact of nonusers with family planning providers . 161 Figure 7.1 Contraceptive use . 130 Figure 7.2 Trends in contraceptive use . 130 Figure 7.3 Modern contraceptive use by state . 131 Figure 7.4 Use of modern methods by education . 131 Figure 7.5 Source of modern contraceptive methods . 132 Figure 7.6 Contraceptive discontinuation rates . 133 Figure 7.7 Demand for family planning . 134 Figure 7.8 Trends in demand for family planning . 134 Figure 7.9 Unmet need by state . 135 8 INFANT AND CHILD MORTALITY . 163 Table 8.1 Early childhood mortality rates . 168 Table 8.2 Five-year early childhood mortality rates according to background characteristics . 168 Table 8.3 Ten-year early childhood mortality rates according to additional characteristics . 169 Table 8.4 Perinatal mortality . 171 Table 8.5 High-risk fertility behaviour . 172 Figure 8.1 Trends in early childhood mortality rates . 164 Figure 8.2 Under-5 mortality by state . 165 Figure 8.3 Under-5 mortality by mother’s education . 165 xii • Tables and Figures Figure 8.4 Childhood mortality by previous birth interval . 166 Figure 8.5 Perinatal mortality by mother’s education . 167 9 MATERNAL HEALTH CARE . 173 Table 9.1 Antenatal care . 185 Table 9.2 Number of antenatal care visits and timing of first visit . 187 Table 9.3 Components of antenatal care . 188 Table 9.4 Tetanus toxoid injections . 190 Table 9.5 Place of delivery . 192 Table 9.6 Assistance during delivery . 194 Table 9.7 Caesarean section . 196 Table 9.8 Reasons for opting for caesarean section . 198 Table 9.9 Duration of stay in health facility after birth . 198 Table 9.10 Referral to place of delivery . 199 Table 9.11 Reasons for referral and time taken . 201 Table 9.12 Means of transportation to health facility . 202 Table 9.13 Thermal care for newborns . 204 Table 9.14 Cord care . 206 Table 9.15 Use of chlorhexidine . 208 Table 9.16 Timing of first postnatal check for the mother . 210 Table 9.17 Type of provider of first postnatal check for the mother. 212 Table 9.18 Timing of first postnatal check for the newborn . 214 Table 9.19 Type of provider of first postnatal check for the newborn . 216 Table 9.20 Content of postnatal care for newborns . 218 Table 9.21 Problems in accessing health care . 220 Figure 9.1 Trends in antenatal care coverage . 174 Figure 9.2 Components of antenatal care . 175 Figure 9.3 Trends in place of birth . 176 Figure 9.4 Health facility births by mother’s education . 177 Figure 9.5 Health facility births by state . 177 Figure 9.6 Assistance during delivery . 178 Figure 9.7 Skilled assistance at delivery by household wealth . 178 Figure 9.8 Postnatal care by place of delivery . 181 10 CHILD HEALTH . 223 Table 10.1 Child’s size and weight at birth . 233 Table 10.2 Vaccinations by source of information . 235 Table 10.3 Vaccinations by background characteristics . 236 Table 10.4 Possession and observation of vaccination cards, according to background characteristics . 239 Table 10.5 Prevalence and treatment of symptoms of ARI. 241 Table 10.6 Source of advice or treatment for children with symptoms of ARI . 242 Table 10.7 Prevalence and treatment of fever . 243 Table 10.8 Prevalence and treatment of diarrhoea . 245 Table 10.9 Feeding practices during diarrhoea . 247 Table 10.10 Oral rehydration therapy, zinc, and other treatments for diarrhoea . 248 Table 10.11 Source of advice or treatment for children with diarrhoea . 249 Table 10.12 Knowledge of ORS packets . 250 Table 10.13 Disposal of children’s stools . 252 Figure 10.1 Childhood vaccinations . 225 Figure 10.2 Trends in childhood vaccinations . 225 Figure 10.3 Vaccination coverage by mother’s education . 226 Figure 10.4 Vaccination coverage by state . 226 Figure 10.5 Feeding practices during diarrhoea . 229 Tables and Figures • xiii Figure 10.6 Treatment of diarrhoea . 230 Figure 10.7 Prevalence and treatment of childhood illness . 231 11 NUTRITION OF CHILDREN AND WOMEN . 255 Table 11.1 Nutritional status of children . 271 Table 11.2 Initial breastfeeding . 274 Table 11.3 Breastfeeding status by age . 276 Table 11.4 Infant and young child feeding (IYCF) indicators on breastfeeding status . 276 Table 11.5 Median duration of breastfeeding . 277 Table 11.6 Foods and liquids consumed by children in the day or night preceding the interview . 278 Table 11.7 Minimum acceptable diet . 279 Table 11.8 Prevalence of anaemia in children . 282 Table 11.9 Prevalence of sickle cell anaemia in children . 284 Table 11.10 Presence of iodised salt in household . 286 Table 11.11 Micronutrient intake among children . 287 Table 11.12 Nutritional status of women . 289 Table 11.13 Prevalence of anaemia in women . 291 Table 11.14 Micronutrient intake among mothers . 293 Table 11.15 Foods and liquids consumed by women in the day or night preceding the interview . 295 Figure 11.1 Stunting in children by state . 258 Figure 11.2 Stunting in children by mother’s education . 259 Figure 11.3 Breastfeeding practices by age . 260 Figure 11.4 IYCF indicators on minimum acceptable diet . 263 Figure 11.5 Childhood anaemia by residence. 264 Figure 11.6 Anaemia in children by state . 264 12 MALARIA . 297 Table 12.1 Household possession of mosquito nets . 309 Table 12.2 Source of mosquito nets . 310 Table 12.3 Access to an insecticide-treated net (ITN) . 311 Table 12.4 Access to an ITN by background characteristics . 312 Table 12.5 Use of mosquito nets by persons in the household . 313 Table 12.6 Use of existing ITNs . 315 Table 12.7 Use of mosquito nets by children . 316 Table 12.8 Use of mosquito nets by pregnant women . 318 Table 12.9 Reasons for not using the specific net the night preceding the interview . 319 Table 12.10 Use of intermittent preventive treatment (IPTp) by women during pregnancy . 321 Table 12.11 Prevalence, diagnosis, and prompt treatment of children with fever . 322 Table 12.12 Source of advice or treatment for children with fever . 324 Table 12.13 Type of antimalarial drugs used . 325 Table 12.14 Coverage of testing for anaemia and malaria in children . 326 Table 12.15 Haemoglobin <8.0 g/dl in children . 328 Table 12.16 Prevalence of malaria in children . 330 Table 12.17 Malaria prevalence among children with a fever in the last 2 weeks . 332 Table 12.18.1 Beliefs about the effectiveness of the recommended malaria behaviours and products: Women . 334 Table 12.18.2 Beliefs about the effectiveness of the recommended malaria behaviours and products: Men . 336 Table 12.19.1 Beliefs about the consequences of malaria: Women . 338 Table 12.19.2 Beliefs about the consequences of malaria: Men . 340 xiv • Tables and Figures Figure 12.1 Household ownership of ITNs . 298 Figure 12.2 Trends in household ownership of ITNs . 298 Figure 12.3 ITN ownership by household wealth . 299 Figure 12.4 ITN ownership by state . 299 Figure 12.5 Source of ITNs . 300 Figure 12.6 Access to and use of ITNs by residence . 300 Figure 12.7 Trends in use of ITNs by pregnant women and children . 301 Figure 12.8 Trends in IPTp use by pregnant women . 303 Figure 12.9 Trends in malaria prevalence among children . 306 Figure 12.10 Prevalence of malaria in children by age . 306 Figure 12.11 Prevalence of malaria in children by state . 306 13 HIV/AIDS-RELATED KNOWLEDGE, ATTITUDES, AND BEHAVIOUR . 343 Table 13.1 Knowledge of HIV prevention methods . 352 Table 13.2 Comprehensive knowledge about HIV . 354 Table 13.3 Knowledge of prevention of mother-to-child transmission of HIV . 355 Table 13.4 Discriminatory attitudes towards people living with HIV . 356 Table 13.5.1 Multiple sexual partners and higher-risk sexual intercourse in the past 12 months: Women . 358 Table 13.5.2 Multiple sexual partners and higher-risk sexual intercourse in the past 12 months: Men . 360 Table 13.6 Payment for sexual intercourse and condom use at last paid sexual intercourse . 362 Table 13.7 Male circumcision . 363 Table 13.8 Self-reported prevalence of sexually transmitted infections (STIs) and STI symptoms . 365 Table 13.9 Women and men seeking treatment for STIs . 367 Table 13.10 Comprehensive knowledge about HIV among young people . 367 Table 13.11 Age at first sexual intercourse among young people . 368 Table 13.12 Premarital sexual intercourse among young people . 368 Table 13.13.1 Multiple sexual partners and higher-risk sexual intercourse in the past 12 months among young people: Women . 369 Table 13.13.2 Multiple sexual partners and higher-risk sexual intercourse in the past 12 months among young people: Men . 370 Figure 13.1 Knowledge of HIV prevention among women by state . 345 Figure 13.2 Knowledge of mother-to-child transmission (MTCT) of HIV . 346 Figure 13.3 Trends in knowledge of mother-to-child transmission (MTCT) of HIV . 346 Figure 13.4 Discriminatory attitudes towards people living with HIV by education . 347 Figure 13.5 Trends in comprehensive HIV knowledge among youth . 349 14 ADULT AND MATERNAL MORTALITY . 371 Table 14.1 Completeness of information on siblings . 376 Table 14.2 Adult mortality rates . 376 Table 14.3 Adult mortality probabilities . 376 Table 14.4 Maternal mortality . 377 Figure 14.1 Adult mortality rates by age . 372 Figure 14.2 Trends in the pregnancy-related mortality ratio (PRMR) with confidence intervals . 375 15 WOMEN’S EMPOWERMENT . 379 Table 15.1 Employment and cash earnings of currently married women and men . 388 Table 15.2.1 Control over women’s cash earnings and relative magnitude of women’s cash earnings . 389 Table 15.2.2 Control over men’s cash earnings . 391 Tables and Figures • xv Table 15.3 Women’s control over their own earnings and over those of their husbands . 393 Table 15.4.1 Ownership of assets: Women . 394 Table 15.4.2 Ownership of assets: Men . 396 Table 15.5.1 Ownership of title or deed for house: Women . 398 Table 15.5.2 Ownership of title or deed for house: Men . 400 Table 15.6.1 Ownership of title or deed for land: Women . 402 Table 15.6.2 Ownership of title or deed for land: Men . 404 Table 15.7.1 Ownership and use of bank accounts and mobile phones: Women . 406 Table 15.7.2 Ownership and use of bank accounts and mobile phones: Men . 408 Table 15.8 Participation in decision making . 410 Table 15.9.1 Women’s participation in decision making by background characteristics . 411 Table 15.9.2 Men’s participation in decision making by background characteristics . 413 Table 15.10.1 Attitude toward wife beating: Women . 415 Table 15.10.2 Attitude toward wife beating: Men . 417 Table 15.11 Attitudes toward negotiating safer sexual relations with husband . 419 Table 15.12 Ability to negotiate sexual relations with husband . 421 Table 15.13 Indicators of women’s empowerment . 423 Table 15.14 Current use of contraception by women’s empowerment . 423 Table 15.15 Ideal number of children and unmet need for family planning by women’s empowerment . 424 Table 15.16 Reproductive health care by women’s empowerment . 424 Table 15.17 Early childhood mortality rates by women’s status . 425 Figure 15.1 Employment by age . 380 Figure 15.2 Control over women’s earnings . 381 Figure 15.3 Ownership of assets . 382 Figure 15.4 Women’s participation in decision making . 384 Figure 15.5 Attitudes towards wife beating . 385 16 DOMESTIC VIOLENCE . 427 Table 16.1 Experience of physical violence . 437 Table 16.2 Experience of violence during pregnancy . 439 Table 16.3 Persons committing physical violence . 440 Table 16.4 Experience of sexual violence . 441 Table 16.5 Persons committing sexual violence . 442 Table 16.6 Age at first experience of sexual violence . 443 Table 16.7 Experience of different forms of violence . 443 Table 16.8 Marital control exercised by husbands . 444 Table 16.9 Forms of spousal violence . 446 Table 16.10 Spousal violence by background characteristics . 447 Table 16.11 Spousal violence by husband’s characteristics and empowerment indicators . 449 Table 16.12 Violence by any husband/partner in the last 12 months . 450 Table 16.13 Experience of spousal violence by duration of marriage . 451 Table 16.14 Injuries to women due to spousal violence . 451 Table 16.15 Violence by women against their husband by women’s background characteristics . 452 Table 16.16 Violence by women against their husband by husband’s characteristics and empowerment indicators . 454 Table 16.17 Help seeking to stop violence . 455 Table 16.18 Sources for help to stop the violence . 456 Figure 16.1 Women’s experience of violence by marital status . 429 Figure 16.2 Forms of spousal violence . 432 Figure 16.3 Trends in women’s experience of spousal violence . 432 xvi • Tables and Figures Figure 16.4 Spousal violence by state . 433 Figure 16.5 Spousal violence by husband’s alcohol consumption . 434 Figure 16.6 Help seeking by type of violence experienced . 436 17 DISABILITY . 457 Table 17.1 Disability by domain and age . 460 Table 17.2.1 Disability among adults according to background characteristics: Women . 461 Table 17.2.2 Disability among adults according to background characteristics: Men . 463 Figure 17.1 Degree of difficulty . 458 Figure 17.2 Level of difficulty in at least one domain . 458 18 FEMALE GENITAL MUTILATION . 465 Table 18.1 Knowledge of female circumcision. 471 Table 18.2 Prevalence of female circumcision . 473 Table 18.3 Unclassified types of female circumcision . 475 Table 18.4 Age at circumcision . 476 Table 18.5 Prevalence of circumcision and age at circumcision: Girls age 0-14 . 476 Table 18.6 Circumcision of girls age 0-14 by mother’s background characteristics . 477 Table 18.7 Infibulation among circumcised girls age 0-14 . 479 Table 18.8 Aspects of circumcision among circumcised girls age 0-14 and women age 15-49 . 480 Table 18.9 Opinions of women about whether circumcision is required by religion . 481 Table 18.10 Opinions of women about whether the practice of circumcision should continue . 483 Figure 18.1 Types of FGM . 466 Figure 18.2 Trends in FGM by residence . 466 Figure 18.3 FGM by age . 467 Figure 18.4 FGM by state . 467 Figure 18.5 Age at FGM . 468 Figure 18.6 Attitudes about FGM by circumcision status . 469 APPENDIX A SAMPLE DESIGN . 489 Table A.1 Population distribution . 490 Table A.2 Enumeration areas . 491 Table A.3 Sample allocation of clusters and households by state . 492 Table A.4 Sample allocation of expected completed interviews with women and men . 493 Table A.5 Sample implementation: Women . 494 Table A.6 Sample implementation: Men . 495 APPENDIX B ESTIMATES OF SAMPLING ERRORS . 497 Table B.1 List of selected variables for sampling errors, Nigeria DHS 2018 . 499 Table B.2 Sampling errors: National sample, Nigeria DHS 2018 . 500 Table B.3 Sampling errors: Urban sample, Nigeria DHS 2018 . 501 Table B.4 Sampling errors: Rural sample, Nigeria DHS 2018 . 502 Table B.5 Sampling errors: North Central sample, Nigeria DHS 2018 . 503 Table B.6 Sampling errors: North East sample, Nigeria DHS 2018 . 504 Table B.7 Sampling errors: North West sample, Nigeria DHS 2018 . 505 Table B.8 Sampling errors: South East sample, Nigeria DHS 2018 . 506 Table B.9 Sampling errors: South South sample, Nigeria DHS 2018 . 507 Table B.10 Sampling errors: South West sample, Nigeria DHS 2018 . 508 Table B.11 Sampling errors: FCT-Abuja sample, Nigeria DHS 2018 . 509 Table B.12 Sampling errors: Benue sample, Nigeria DHS 2018 . 510 Table B.13 Sampling errors: Kogi sample, Nigeria DHS 2018 . 511 Tables and Figures • xvii Table B.14 Sampling errors: Kwara sample, Nigeria DHS 2018 . 512 Table B.15 Sampling errors: Nasarawa sample, Nigeria DHS 2018 . 513 Table B.16 Sampling errors: Niger sample, Nigeria DHS 2018 . 514 Table B.17 Sampling errors: Plateau sample, Nigeria DHS 2018 . 515 Table B.18 Sampling errors: Adamawa sample, Nigeria DHS 2018 . 516 Table B.19 Sampling errors: Bauchi sample, Nigeria DHS 2018 . 517 Table B.20 Sampling errors: Borno sample, Nigeria DHS 2018 . 518 Table B.21 Sampling errors: Gombe sample, Nigeria DHS 2018 . 519 Table B.22 Sampling errors: Taraba sample, Nigeria DHS 2018 . 520 Table B.23 Sampling errors: Yobe sample, Nigeria DHS 2018 . 521 Table B.24 Sampling errors: Jigawa sample, Nigeria DHS 2018 . 522 Table B.25 Sampling errors: Kaduna sample, Nigeria DHS 2018 . 523 Table B.26 Sampling errors: Kano sample, Nigeria DHS 2018 . 524 Table B.27 Sampling errors: Katsina sample, Nigeria DHS 2018 . 525 Table B.28 Sampling errors: Kebbi sample, Nigeria DHS 2018 . 526 Table B.29 Sampling errors: Sokoto sample, Nigeria DHS 2018 . 527 Table B.30 Sampling errors: Zamfara sample, Nigeria DHS 2018 . 528 Table B.31 Sampling errors: Abia sample, Nigeria DHS 2018 . 529 Table B.32 Sampling errors: Anambra sample, Nigeria DHS 2018 . 530 Table B.33 Sampling errors: Ebonyi sample, Nigeria DHS 2018 . 531 Table B.34 Sampling errors: Enugu sample, Nigeria DHS 2018 . 532 Table B.35 Sampling errors: Imo sample, Nigeria DHS 2018 . 533 Table B.36 Sampling errors: Akwa Ibom sample, Nigeria DHS 2018 . 534 Table B.37 Sampling errors: Bayelsa sample, Nigeria DHS 2018 . 535 Table B.38 Sampling errors: Cross River sample, Nigeria DHS 2018 . 536 Table B.39 Sampling errors: Delta sample, Nigeria DHS 2018 . 537 Table B.40 Sampling errors: Edo sample, Nigeria DHS 2018 . 538 Table B.41 Sampling errors: Rivers sample, Nigeria DHS 2018 . 539 Table B.42 Sampling errors: Ekiti sample, Nigeria DHS 2018 . 540 Table B.43 Sampling errors: Lagos sample, Nigeria DHS 2018 . 541 Table B.44 Sampling errors: Ogun sample, Nigeria DHS 2018 . 542 Table B.45 Sampling errors: Ondo sample, Nigeria DHS 2018 . 543 Table B.46 Sampling errors: Osun sample, Nigeria DHS 2018 . 544 Table B.47 Sampling errors: Oyo sample, Nigeria DHS 2018 . 545 Table B.48 Sampling errors for adult and maternal mortality rates, Nigeria DHS 2018 . 546 APPENDIX C DATA QUALITY TABLES . 547 Table C.1 Household age distribution . 547 Table C.2.1 Age distribution of eligible and interviewed women . 547 Table C.2.2 Age distribution of eligible and interviewed men . 548 Table C.3 Completeness of reporting . 548 Table C.4 Births by calendar years . 549 Table C.5 Reporting of age at death in days . 549 Table C.6 Reporting of age at death in months. 550 Table C.7 Standardisation exercise results from anthropometry training . 550 Table C.8 Height and weight data completeness and quality for children . 551 Table C.9 Height measurements from random subsample of measured children . 553 Table C.10 Sibship size and sex ratio of siblings . 553 Table C.11 Pregnancy-related mortality trends . 554 Table C.12 Data collection period . 555 Table C.13 Malaria prevalence according to rapid diagnostic test (RDT). 556 Foreword • xix FOREWORD he conducting of Demographic and Health Surveys is in line with one of the constitutional responsibilities of the National Population Commission (NPC), namely to collect, collate, analyse, and disseminate population census and survey data at all levels that contribute to policy formulation and coordination of population activities in the country.The 2018 Nigeria Demographic and Health Survey (2018 NDHS) is the sixth survey of its kind to be implemented by the National Population Commission. The 2018 NDHS is a national sample survey that provides up-to-date information on demographic and health indicators. The sample was selected using a stratified, two-stage cluster design, with enumeration areas (EAs) as the sampling units for the first stage. The second stage was a complete listing of households carried out in each of the 1,400 selected EAs. The target groups were women age 15-49 and men age 15-59 in randomly selected households across Nigeria. A representative sample of approximately 42,000 households was selected for the survey. One-third of the households (14,000) were selected for malaria, anaemia, and genotype testing of children age 6-59 months. Also, in the subsample of households selected for the men’s survey, one eligible woman in each household was randomly selected for additional questions regarding domestic violence. Specifically, information was collected on fertility levels, marriage, fertility preferences, awareness and use of family planning methods, child feeding practices, nutritional status of women and children, adult and childhood mortality, awareness and attitudes regarding HIV/AIDS, and female genital mutilation. The survey also assessed the nutritional status (according to weight and height measurements) of women and children in these households. In addition to presenting national estimates, the report provides estimates of key indicators for both rural and urban areas, the country’s six geopolitical zones and 36 states, and the Federal Capital Territory (FCT). The 2018 NDHS is unique in a number of ways. For the first time in a Nigeria DHS, the 2018 survey was implemented using computer-assisted personal interviewing (CAPI), allowing more rapid provision of data than in previous surveys. Also, the survey was adapted to assess the prevalence of malaria, to conduct genotype testing for sickle cell disease and sickle cell trait among children age 6-59 months, and to measure haemoglobin levels (anaemia) among women and children in the subsample of households selected for the male survey. Malaria slides were assessed through rapid diagnostic tests at the household level and microscopy on thick blood smears in the laboratory for children age 6-59 months. As sickle cell anaemia has become a national health burden in Nigeria, sickle cell disease testing was included, thus serving as a basis for testing this deadly disease in subsequent DHS surveys globally. In addition, the sample size was larger than that in the five previous NDHS surveys, covering a total of 1,400 clusters across the country. Data on social and behaviour change communication (SBCC) on malaria, minimum dietary diversity among women, female genital mutilation, fistula, and disability were included as requested by various stakeholders. I offer my candid appreciation to the Honourable Minister of Health Dr. Osagie Ehanire and the former Honourable Minister of Health Professor Isaac F. Adewole, PAS, FSPSP DSc (Hons), for leadership and commitment to the success of the survey as chairmen of the Survey Steering Committee. The effort of the National Malaria Elimination Programme (NMEP) in providing support for the malaria component of the survey is recognized. I also thank members of the Survey Steering Committee for their commitment and dedication to the survey’s successful implementation. On behalf of the Commission, I wish to express appreciation to the 2018 NDHS technical team; the project directors, Ms. Nwamaka Ezenwa and Osifo Tellson Ojogun; and the project coordinator, Inuwa Bakari Jalingo, for management of the technical, administrative, and logistical phases of the survey. My appreciation also goes to the state coordinators, biomarker monitors, quality control officers, supervisors, T xx • Foreword data collectors, listers and mappers, and drivers for their commitment and hard work during the survey. In addition, I would like to offer my sincere appreciation to the field staff, data processing team, and, in particular, survey respondents. Similarly, I wish to express appreciation to ICF for its technical assistance in all stages of the survey. I greatly appreciate Ms. Anjushree Pradhan (ICF DHS Country Manager), Ms. Deborah Collison (Survey Manager), and other ICF staff who provided technical assistance for the commitment and great expertise with which they managed all of the components of this survey. My special thanks go to the United States Agency for International Development (USAID/Nigeria), the Global Fund, the Bill and Melinda Gates Foundation (BMGF), the World Health Organization (WHO), and the United Nations Population Fund (UNFPA). In addition, I thank all of the laboratories that provided support during the survey, particularly the African Network for Drugs and Diagnostics Initiative (ANDI); the Department of Medical Microbiology and Pathology, College of Medicine, University of Lagos; the Institute of Tropical Disease Research and Prevention, University of Calabar, Cross River; and the International Foundation Against Infectious Diseases in Nigeria (IFAIN). Also acknowledged is the tireless effort of Deloitte and Touche (DT) in providing accounting and disbursement services that allowed for the timely and efficient transfer of project funds throughout all of the survey components. I would like to thank the former Chairman, Eze Duruiheoma, SAN; the former Ag. Chairmen, Alh. Hassan Bashir, CAN (Tafidan Bauchi), and Alhaji Mohammed Yusuff Anka (Ciroman Anka); and the Honourable Federal Commissioners for their support during the implementation period and for providing excellent leadership and advocacy support. Likewise, the unflinching support and technical assistance provided by Dr. Ghaji Ismaila Bello (Director-General), Mrs. Adenike O. Ogunlewe (Director, Planning and Research), and all other directors are hereby acknowledged. Finally, our deep appreciation goes to the survey respondents, state governments, local government authorities, and traditional authorities for their contributions and support during the implementation of the survey. __________________________________ Abimbola Salu-Hundeyin (LL.B) Ag. Chairman National Population Commission 2018 Nigeria Demographic and Health Survey Steering Committee • xxi 2018 NIGERIA DEMOGRAPHIC AND HEALTH SURVEY STEERING COMMITTEE Honourable Minister of Health (FMOH) Chair Chairman, National Population Commission (NPC) Co-chair National Malaria Elimination Programme (NMEP) Member Ministry of Budget & National Planning (MBNP) Member Federal Ministry of Women Affairs and Social Development (FMWASD) Member National Bureau of Statistics (NBS) Member Sustainable Development Goals (SDGs) Office Member United States Agency for International Development (USAID) Member Department for International Development (DFID) Member Canadian International Development Agency (CIDA) Member United Nations Population Fund (UNFPA) Member United Nations Children’s Fund (UNICEF) Member World Health Organization (WHO) Member World Bank (WB) Member Bill and Melinda Gates Foundation (BMGF) Member National Primary Health Care Development Agency (NPHCDA) Member ICF, Maryland, USA - Survey Manager Member Society for Family Health (SHF) Member Catholic Relief Services (CRS) Member News Agency of Nigeria (NAN) Member National Population Commission - Director Health Planning, Research and Statistics Member National Population Commission - 2018 NDHS Project Director Secretary Contributors to the Report • xxiii CONTRIBUTORS TO THE REPORT Ms. Ezenwa Nwamaka L., Project Director, NDHS (April 2017–June 2019), National Population Commission Mr. Osifo Tellson Ojogun, Project Director, NDHS, National Population Commission Mr. Inuwa B. Jalingo, Project Coordinator, NDHS, National Population Commission Ms. Yemisi Ogunmola, National Population Commission Mr. Narudeen L. Rasheed, National Primary Health Care Development Agency, FMOH Mr. Okoh Festus O., National Malaria Elimination Programme, FMOH Mr. Moronu Chike, National Population Commission Mr. Fasiku Adekunle David, National Population Commission Mr. Datsu Kalep Harris, National Population Commission Mr. Balogun Adeleke M., Department of Health Planning, FMOH Mr. Martin Makinwa, National Population Commission Ms. Margaret Akpan, National Population Commission Mr. Elue Dominic Chukwuma, Nutrition, Department of Family Health, FMOH Ms. Tinuola Taylor, Child Survival, Department of Family Health, FMOH Mr. Nasiru Baba-Saleh, Federal Ministry of Women Affairs and Social Development Ms. Bintu Ibrahim Abba, National Population Commission Mr. Mansur Bashir Darma, Malaria Consortium Mr. Bolaji Akinsulie, National Population Commission Mr. Audu Alayande, United Nations Population Fund (UNFPA) Dr. Sada Damusa, MidSpace Concept (M. SPACE) Ms. Bahijjatu Bello Garko, United Nations Population Fund (UNFPA) Ms. Ukor Nkiruka C., World Health Organization (WHO) Ms. Temitope A. Bombata, Federal Ministry of Health Dr. Oyeniyi Samuel O., Reproductive Health Division, Department of Family Health, FMOH Dr. Alayo Sopekan, Non-Communicable Diseases Control Programme, Department of Public Health, FMOH Dr. Ibrahim Maikore, National Malaria Elimination Programme, FMOH Dr. Samuel I. Kalu, Michael Okpara University of Agriculture, Umudike Prof. Tukur Dahiru, Ahmadu Bello University, Zaria Reading and Understanding Tables from the 2018 NDHS • xxv READING AND UNDERSTANDING TABLES FROM THE 2018 NIGERIA DHS The new format of the 2018 NDHS final report is based on approximately 200 tables of data. For quick reference, they are located at the end of each chapter and can be accessed through links in the pertinent text (electronic version). Additionally, this more reader-friendly version features about 90 figures that clearly highlight trends, subnational patterns, and background characteristics. Large, colourful maps display breakdowns for states in Nigeria. The text has been simplified to highlight key points in bullets and to clearly identify indicator definitions in boxes. While the text and figures featured in each chapter highlight some of the most important findings from the tables, not every finding can be discussed or displayed graphically. For this reason, NDHS data users should be comfortable reading and interpreting tables. The following pages provide an introduction to the organisation of NDHS tables, the presentation of background characteristics, and a brief summary of sampling and understanding denominators. In addition, this section provides some exercises for users as they practice their new skills in interpreting NDHS tables. xxvi • Reading and Understanding Tables from the 2018 NDHS Example 1: Exposure to Mass Media: Women A Question Asked of All Survey Respondents Table 3.4.1 Exposure to mass media: Women Percentage of women age 15-49 who are exposed to specific media on a weekly basis, according to background characteristics, Nigeria DHS 2018 Background characteristic Reads a newspaper at least once a week Watches television at least once a week Listens to the radio at least once a week Accesses all three media at least once a week Accesses none of the three media at least once a week Number of women Age 15-19 3.7 32.5 23.0 2.1 58.5 8,448 20-24 5.4 31.9 28.2 3.6 56.8 6,835 25-29 4.5 34.0 30.6 3.5 54.7 7,255 30-34 5.3 35.6 31.9 3.9 53.5 6,178 35-39 4.8 34.8 34.5 3.7 52.0 5,463 40-44 5.1 31.0 33.3 3.9 54.9 3,940 45-49 3.7 27.7 31.9 2.8 57.4 3,701 Residence Urban 6.9 51.2 38.9 5.0 38.2 19,163 Rural 2.7 17.3 22.0 1.8 70.2 22,658 Zone North Central 3.8 30.3 20.9 2.7 63.6 5,891 North East 2.4 15.4 18.0 1.2 73.1 6,636 North West 1.8 15.6 25.1 0.9 68.8 12,225 South East 10.9 38.1 43.9 8.4 45.0 4,963 South South 9.1 53.3 31.2 6.9 40.4 4,840 South West 4.7 62.7 44.8 3.7 28.0 7,266 State North Central FCT-Abuja 2.9 42.4 17.6 1.4 53.7 319 Benue 6.0 39.3 31.6 4.9 52.4 1,354 Kogi 2.9 30.9 12.7 1.9 65.3 654 Kwara 1.7 28.5 21.2 1.1 66.5 684 Nasarawa 10.2 34.6 35.7 7.8 54.5 648 Niger 1.6 27.6 15.5 1.1 68.6 1,357 Plateau 1.8 13.7 9.1 0.4 80.0 875 North East Adamawa 0.9 18.6 14.2 0.7 75.0 903 Bauchi 2.2 10.4 28.1 1.1 67.8 1,343 Borno 2.2 18.4 13.3 1.4 76.8 1,469 Gombe 4.0 14.5 29.7 3.5 67.4 717 Taraba 1.0 18.2 5.2 0.3 78.8 877 Yobe 4.0 13.7 17.6 1.0 72.2 1,327 North West Jigawa 1.3 10.2 32.0 0.7 64.7 1,382 Kaduna 1.8 28.5 32.5 0.9 54.9 2,493 Kano 3.5 23.2 35.9 2.0 57.1 2,692 Katsina 1.3 10.3 14.6 0.7 80.5 2,283 Kebbi 0.8 3.5 6.7 0.2 90.6 1,136 Sokoto 0.5 9.0 23.3 0.4 74.8 910 Zamfara 1.6 6.0 17.2 0.4 79.7 1,328 South East Abia 21.3 57.9 47.4 17.4 33.7 630 Anambra 15.7 51.9 49.7 13.3 37.3 1,477 Ebonyi 2.7 16.7 41.6 2.0 54.6 1,027 Enugu 4.4 26.6 36.4 3.8 59.5 880 Imo 11.5 37.5 41.9 5.9 40.7 948 South South Akwa Ibom 14.7 53.5 45.1 11.5 36.3 948 Bayelsa 20.4 64.8 57.2 19.3 27.9 298 Cross River 13.3 52.9 38.5 9.1 35.9 574 Delta 5.9 59.4 17.6 4.0 37.7 931 Edo 4.9 68.9 34.3 2.5 25.0 555 Rivers 5.3 41.7 22.1 4.2 54.3 1,534 South West Ekiti 5.9 34.8 47.5 3.9 42.4 475 Lagos 4.2 82.4 34.2 3.4 16.2 2,891 Ogun 3.2 21.1 18.1 1.7 70.4 927 Ondo 4.0 44.1 39.3 3.4 42.4 683 Osun 7.3 81.0 76.5 6.1 10.6 938 Oyo 5.1 55.6 65.8 4.0 24.1 1,352 Education No education 0.1 7.2 17.1 0.0 79.7 14,603 Primary 0.9 24.6 28.3 0.5 61.1 6,039 Secondary 5.5 48.0 36.2 3.6 41.6 16,583 More than secondary 20.7 70.5 48.5 16.1 22.1 4,596 Continued. 1 2 3 5 Reading and Understanding Tables from the 2018 NDHS • xxvii Table 3.4.1—Continued Background characteristic Reads a newspaper at least once a week Watches television at least once a week Listens to the radio at least once a week Accesses all three media at least once a week Accesses none of the three media at least once a week Number of women Wealth quintile Lowest 0.2 2.5 15.1 0.0 83.9 7,222 Second 0.9 7.8 18.1 0.3 78.5 8,045 Middle 2.7 24.6 28.7 1.5 59.6 8,207 Fourth 5.9 49.0 39.1 3.9 39.7 8,990 Highest 11.8 69.5 43.1 9.3 25.6 9,357 Total 4.6 32.9 29.8 3.3 55.6 41,821 Step 1: Read the title and subtitle, highlighted in orange in the table above. They tell you the topic and specific population group being described. The table is about women age 15-49 and their exposure to different types of media. All eligible female respondents age 15-49 were asked these questions. Step 2: Scan the column headings—highlighted in green in Example 1. They describe how the information is categorized. In this table, the first three columns of data show different types of media that women access at least once a week. The fourth column shows women who access all three types of media, while the fifth column shows women who do not access any of the three types of media on a weekly basis. The last column lists the number of women age 15-49 interviewed in the survey. Step 3: Scan the row headings—the first vertical column highlighted in blue in Example 1. These show the different ways the data are divided into categories based on population characteristics. In this case, the table presents women’s exposure to media by age, urban-rural residence, zone, state, level of education, and wealth quintile. Most of the tables in the NDHS report will be divided into these same categories. Step 4: Look at the row at the bottom of the table highlighted in red. These percentages represent the totals of all women age 15-49 and their weekly access to different types of media. In this case, 4.6%* of women age 15-49 read a newspaper, 32.9% watch television, and 29.8% listen to the radio at least once a week. Step 5: To find out what percentage of women with more than a secondary education access all three media at least once a week, draw two imaginary lines, as shown on the table. This shows that 16.1% of women age 15-49 with more than a secondary education access all three types of media at least once a week. By looking at patterns by background characteristics, we can see how exposure to mass media varies across Nigeria. Mass media are often used to communicate health messages. Knowing how mass media exposure varies among different groups can help programme planners and policymakers determine how to most effectively reach their target populations. *For the purpose of this document data are presented exactly as they appear in the table, including decimal places. However, the text in the remainder of this report rounds data to the nearest whole percentage point. Practice: Use the table in Example 1 to answer the following questions: a) What percentage of women in Nigeria do not access any of the three media at least once a week? b) Which age group of women are most likely to listen to the radio at least once a week? c) Compare women in urban areas to women in rural areas – which group is more likely to watch television on a weekly basis? d) What are the lowest and the highest percentages (range) of women who do not access any media at least once a week by state? e) Is there a clear pattern in exposure to radio at least once a week by wealth quintile? 4 xxviii • Reading and Understanding Tables from the 2018 NDHS Example 2: Prevalence and Treatment of ARI A Question Asked of a Subgroup of Survey Respondents Table 10.5 Prevalence and treatment of symptoms of ARI Among children under age 5, percentage who had symptoms of acute respiratory infection (ARI) in the 2 weeks preceding the survey; and among children with symptoms of ARI in the 2 weeks preceding the survey, percentage for whom advice or treatment was sought, according to background characteristics, Nigeria DHS 2018 Among children under age 5: Among children under age 5 with symptoms of ARI: Background characteristic Percentage with symptoms of ARI1 Number of children Percentage for whom advice or treatment was sought2 Percentage for whom treatment was sought same or next day Number of children Age in months <6 2.7 3,270 73.3 31.6 87 6-11 3.7 3,153 82.3 39.9 116 12-23 3.4 6,143 75.7 28.1 210 24-35 2.4 5,835 79.4 24.4 141 36-47 2.0 6,186 67.8 20.1 122 48-59 2.2 6,294 76.0 31.8 139 Sex Male 2.7 15,674 76.2 29.6 417 Female 2.6 15,208 75.6 28.2 397 Mother's smoking status Smokes cigarettes/tobacco 0.0 69 * * 0 Does not smoke 2.6 30,813 75.9 29.0 814 Cooking fuel Electricity or gas 1.3 2,997 (91.3) (66.2) 38 Kerosene 1.2 2,954 (96.0) (46.3) 35 Coal/lignite 0.0 194 * * 0 Charcoal 2.7 1,914 (90.8) (52.6) 51 Wood/straw3 3.0 22,813 72.9 24.3 690 Animal dung * 1 * * 0 No food cooked in household * 8 * * 0 Residence Urban 2.0 12,215 82.4 42.1 239 Rural 3.1 18,666 73.2 23.5 575 Zone North Central 1.3 4,255 60.0 32.1 55 North East 8.2 5,598 74.6 27.5 461 North West 1.3 10,883 86.9 27.8 146 South East 1.6 3,205 57.0 27.6 52 South South 2.4 2,787 90.6 34.7 66 South West 0.8 4,153 (72.4) (39.8) 34 Mother's education No education 3.1 13,867 73.6 21.0 436 Primary 3.3 4,618 71.3 26.2 152 Secondary 2.0 9,733 82.1 42.4 199 More than secondary 1.0 2,664 (93.6) (73.3) 27 Wealth quintile Lowest 4.2 6,625 74.2 19.5 277 Second 3.0 6,816 70.5 24.8 208 Middle 2.3 6,364 74.9 33.2 145 Fourth 1.9 5,816 79.9 35.9 112 Highest 1.4 5,260 93.8 57.9 72 Total 2.6 30,881 75.9 29.0 814 Note: Figures in parentheses are based on 25-49 unweighted cases. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 1 Symptoms of ARI include short, rapid breathing which was chest-related and/or difficult breathing which was chest- related. 2 Includes advice or treatment from the following sources: public sector, private medical sector, shop, market, itinerant drug seller, community-oriented resource person. Excludes advice or treatment from a traditional practitioner 3 Includes grass, shrubs, crop residues Answers: a) 55.6% b) Women age 35-39: 34.5% of women in this age group listen to the radio weekly. c) Women in urban areas: 51.2% of women in urban areas watch television on a weekly basis, compared to 17.3% of rural women. d) Women with no exposure to media at least once a week ranges from a low of 10.6% in Osun to a high of 90.6% in Kebbi. e) Yes. Exposure to radio increases as household wealth increases; 15.1% of women from the lowest wealth quintile listen to the radio at least once a week, compared to 43.1% of women from the highest wealth quintile. 1 2 3 a b 4 Reading and Understanding Tables from the 2018 NDHS • xxix Step 1: Read the title and subtitle. In this case, the table is about two separate groups of children: all children under age 5 (a) and children under age 5 with symptoms of acute respiratory infection (ARI) in the 2 weeks before the survey (b). Step 2: Identify the two panels. First, identify the columns that refer to children under age 5 (a), and then isolate the columns that refer only to children under age 5 with symptoms of ARI in the 2 weeks before the survey (b). Step 3: Look at the first panel. What percentage of children under age 5 had symptoms of ARI in the 2 weeks before the survey? It’s 2.6%. Now look at the second panel. How many children under age 5 are there who had symptoms of ARI in the 2 weeks before the survey? It’s 814 children, or 2.6% of the 30,881 children under age 5 (with rounding). The second panel is a subset of the first panel. Step 4: Only 2.6% of children under age 5 had symptoms of ARI in the 2 weeks before the survey. Once these children are further divided into the background characteristic categories, there may be too few cases for the percentages to be reliable. • What percentage of children under age 5 with symptoms of ARI in the 2 weeks before the survey whose mothers have more than a secondary education had advice or treatment sought? It’s 93.6%. This percentage is in parentheses because there are between 25 and 49 children (unweighted) in this category. Readers should use this number with caution—it may not be reliable. (For more information on weighted and unweighted numbers, see Example 3.) • What percentage of children under age 5 with symptoms of ARI in the 2 weeks before the survey whose households use coal/lignite had advice or treatment sought? There is no number in this cell—only an asterisk. This is because there are fewer than 25 unweighted cases. Results for this group are not reported. The subgroup is too small, and therefore the data are not reliable Note: When parentheses or asterisks are used in a table, the explanation will be noted under the table. If there are no parentheses or asterisks in a table, you can proceed with confidence that enough cases were included in all categories that the data are reliable. xxx • Reading and Understanding Tables from the 2018 NDHS Example 3: Understanding Sampling Weights in NDHS Tables A sample is a group of people who have been selected for a survey. In the NDHS, the sample is designed to represent the national population age 15-49. In addition to national data, most countries want to collect and report data on smaller geographical or administrative areas. However, doing so requires a large enough sample size in each area. For the 2018 NDHS, the survey sample is representative at the national and state levels and for urban and rural areas. To generate statistics that are representative of the country as a whole and the 37 states, the number of women surveyed in each state should contribute to the size of the total (national) sample in proportion to size of the state. However, if some states have small populations, then a sample allocated in proportion to each state’s population may not include sufficient women from each state for analysis. To solve this problem, states with small populations are oversampled. For example, let’s say that you have enough money to interview 41,821 women and want to produce results that are representative of Nigeria as a whole and its states (as in modified Table 3.1). However, the total population of Nigeria is not evenly distributed among the states: some states, such as Lagos, are heavily populated while others, such as FCT-Abuja, are not. Thus, FCT-Abuja must be oversampled. A sampling statistician determines how many women should be interviewed in each state in order to get reliable statistics. The blue column (1) in the table at right shows the actual number of women interviewed in each state. Within the states, the number of women interviewed ranges from 658 in Edo to 1,983 in Kano. The number of interviews is sufficient to get reliable results in each state. With this distribution of interviews, some states are overrepresented and some states are underrepresented. For example, the population in Lagos is about 7% of the population in Nigeria, while FCT-Abuja’s population contributes only 1% of the population in Nigeria. But as the blue column shows, the number of women interviewed in Lagos accounts for only about 3% of the total sample of women interviewed (1,445/41,821) and the number of women interviewed in FCT-Abuja accounts for 3% of women interviewed (1,186/41,821). This unweighted distribution of women does not accurately represent the population. In order to get statistics that are representative of Nigeria, the distribution of the women in the sample needs to be weighted (or mathematically adjusted) such that it resembles the true distribution in the country. Women from a small state, like FCT-Abuja, should contribute only a small amount to the national total. Women from a large state, like Lagos, should contribute much more. Therefore, DHS statisticians mathematically calculate a “weight” that is used to adjust the number of women from each state so that Table 3.1 Background characteristics of respondents Percent distribution of women and men age 15-49 by selected background characteristics, Nigeria DHS 2018 Women Background characteristic Weighted percent Weighted number Unweighted number State North Central FCT-Abuja 0.8 319 1,186 Benue 3.2 1,354 1,278 Kogi 1.6 654 907 Kwara 1.6 684 906 Nasarawa 1.5 648 1,121 Niger 3.2 1,357 1,292 Plateau 2.1 875 1,082 North East Adamawa 2.2 903 1,083 Bauchi 3.2 1,343 1,329 Borno 3.5 1,469 1,269 Gombe 1.7 717 1,356 Taraba 2.1 877 1,284 Yobe 3.2 1,327 1,318 North West Jigawa 3.3 1,382 1,405 Kaduna 6.0 2,493 1,610 Kano 6.4 2,692 1,983 Katsina 5.5 2,283 1,494 Kebbi 2.7 1,136 1,335 Sokoto 2.2 910 1,065 Zamfara 3.2 1,328 1,237 South East Abia 1.5 630 982 Anambra 3.5 1,477 1,244 Ebonyi 2.5 1,027 1,310 Enugu 2.1 880 1,038 Imo 2.3 948 997 South South Akwa Ibom 2.3 948 958 Bayelsa 0.7 298 771 Cross River 1.4 574 748 Delta 2.2 931 815 Edo 1.3 555 658 Rivers 3.7 1,534 1,130 South West Ekiti 1.1 475 774 Lagos 6.9 2,891 1,445 Ogun 2.2 927 798 Ondo 1.6 683 863 Osun 2.2 938 832 Oyo 3.2 1,352 918 Total 15-49 100.0 41,821 41,821 1 2 3 Reading and Understanding Tables from the 2018 NDHS • xxxi each state’s contribution to the total is proportional to the actual population of the state. The numbers in the purple column (2) represent the “weighted” values. The weighted values can be smaller or larger than the unweighted values at the state level. The total national sample size of 41,821 women has not changed after weighting, but the distribution of the women in the states has been changed to represent their contribution to the total population size. How do statisticians weight each category? They take into account the probability that a woman was selected in the sample. If you were to compare the green column (3) to the actual population distribution of Nigeria, you would see that women in each state are contributing to the total sample with the same weight that they contribute to the population of the country. The weighted number of women in the survey now accurately represents the proportion of women who live in FCT-Abuja and the proportion of women who live in Lagos. With sampling and weighting, it is possible to interview enough women to provide reliable statistics at national and state levels. In general, only the weighted numbers are shown in each of the NDHS tables, so don’t be surprised if these numbers seem low: they may actually represent a larger number of women interviewed. Acronyms and Abbreviations • xxxiii ACRONYMS AND ABBREVIATIONS ACT artemisinin-based combination therapy AIDS acquired immunodeficiency syndrome ANC antenatal care ANDI African Network for Drugs and Diagnostic Initiative ARI acute respiratory infection ART antiretroviral therapy ASFR age-specific fertility rate BCG bacille Calmette-Guerin vaccine against tuberculosis BMGF Bill and Melinda Gates Foundation BMI body mass index CAPI computer-assisted personal interviewing CBR crude birth rate CEB children ever born CEDAW Convention on the Elimination of All Forms of Discrimination against Women CEmOC Comprehensive Emergency Obstetrics Care CHW community health worker CI confidence interval CMAM community-based management of acute malnutrition CPR contraceptive prevalence rate CSPro Census and Survey Processing System cVDPV circulating vaccine-derived polio virus DHS Demographic and Health Survey DMPA-SC depot-medroxyprogesterone acetate - Subcutaneous DPT diphtheria, pertussis, and tetanus vaccine EA enumeration area EPI Expanded Programme on Immunisation ERGP Economic Recovery and Growth Plan FCT Federal Capital Territory FGM female genital mutilation FMOH Federal Ministry of Health GAR gross attendance ratio GDP gross domestic product GFR general fertility rate GPI gender parity index HepB hepatitis B HERA Health Research for Action Hib Haemophilus influenzae type B HIV human immunodeficiency virus HPLC high-performance liquid chromatography HRP histidine-rich protein HTP harmful traditional practices xxxiv • Acronyms and Abbreviations ICCMCI Integrated Community Case Management of Childhood Illness ICRH International Centre for Reproductive Health IFAIN International Foundation Against Infectious Disease in Nigeria IFSS internet file streaming system IMCI Integrated Management of Childhood Illness IPTp intermittent preventive treatment during pregnancy IPV inactivated polio vaccine ITN insecticide-treated net IU international unit IUD intrauterine device IYCF infant and young child feeding LAM lactational amenorrhea method LGA local government area LLIN long-lasting insecticide-treated net LPG liquid petroleum gas LUTH Lagos University Teaching Hospital MAD minimum acceptable diet MNTE maternal and neonatal tetanus elimination MTCT mother-to-child transmission NAR net attendance ratio NCD non-communicable disease NDHS Nigeria Demographic and Health Survey NGO nongovernmental organisation NHREC National Health Research Ethics Committee of Nigeria NMEP National Malaria Elimination Programme NMIS Nigeria Malaria Indicator Survey NN neonatal mortality NPC National Population Commission NPHC Nigeria Population and Housing Census OPV oral polio vaccine ORS oral rehydration salts ORT oral rehydration therapy PCV pneumococcal conjugate vaccine Pf Plasmodium falciparum PMS patent medicine store PMTCT prevention of mother-to-child transmission PNC postnatal care PNN postneonatal mortality PPS probability proportional to size PRMR pregnancy-related mortality ratio PSU primary sampling unit RDT rapid diagnostic test RHF recommended homemade fluids RUFT ready-to-use therapeutic food SBCC social and behavioural change SCD sickle cell disease SCT sickle cell trait Acronyms and Abbreviations • xxxv SD standard deviation SDGs sustainable development goals SDM standard days method SOP standard of practice SP sulfadoxine-pyrimethamine STI sexually transmitted infection TFR total fertility rate UNAIDS Joint United Nations Programme on HIV/AIDS UNFPA United Nations Population Fund UNICEF United Nations Children’s Fund UNSCR UN Security Council Resolution USAID United States Agency for International Development VAPP Violence Against Persons Prohibition Act VAD vitamin A deficiency VIP ventilated improved pit WG Washington Group WHO World Health Organization WPV wild polio virus Sustainable Development Goals Indicators • xxxvii SUSTAINABLE DEVELOPMENT GOAL INDICATORS Sustainable Development Goal Indicators—Nigeria DHS 2018 Sex Total DHS table number Indicator Male Female 2. Zero hunger 2.2.1 Prevalence of stunting among children under 5 years of age 39.4 34.2 36.8 11.1 2.2.2 Prevalence of malnutrition among children under 5 years of age 10.3 7.4 8.9 na a) Prevalence of wasting among children under 5 years of age 8.0 5.6 6.8 11.1 b) Prevalence of overweight among children under 5 years of age 2.3 1.8 2.1 11.1 3. Good health and well-being 3.1.1 Maternal mortality ratio1 na na 512 14.4 3.1.2 Proportion of births attended by skilled health personnel na na 43.3 9.6 3.2.1 Under-five mortality rate2 137 127 132 8.2 3.2.2 Neonatal mortality rate2 42 37 39 8.2 3.7.1 Proportion of women of reproductive age (aged 15-49 years) who have their need for family planning satisfied with modern methods na 35.7 na 7.12.2 3.7.2 Adolescent birth rates per 1,000 women a) Girls aged 10-14 years3 na 2 na 5.1 b) Women aged 15-19 years4 na 106 na 5.1 3.a.1 Age-standardized prevalence of current tobacco use among persons aged 15 years and older5 5.6 0.3 3.0a 3.10.1, 3.10.2 3.b.1 Proportion of the target population covered by all vaccines included in their national programme a) Coverage of DPT containing vaccine (3rd dose)6 50.0 50.2 50.1 10.3 b) Coverage of measles containing vaccine (2nd dose)7 16.0 15.1 15.6 10.3 c) Coverage of pneumococcal conjugate vaccine (last dose in schedule)8 47.2 47.5 47.3 10.3 5. Gender equality 5.2.1 Proportion of ever-partnered women and girls aged 15 years and older subjected to physical, sexual or psychological violence by a current or former intimate partner in the previous 12 months9,10 na 29.5 Na 16.12 a) Physical violence na 11.8 Na 16.12 b) Sexual violence na 4.7 Na 16.12 c) Psychological violence na 26.7 Na 16.12 5.3.1 Proportion of women aged 20-24 years who were married or in a union before age 15 and before age 18 a) Before age 15 na 15.7 Na 4.3 b) Before age 18 na 43.4 Na 4.3 5.6.1 Proportion of women aged 15-49 years who make their own informed decisions regarding sexual relations, contraceptive use and reproductive health care11 na 28.6 Na na 5.b.1 Proportion of individuals who own a mobile telephone12 80.6 55.3 68.0a 15.7.1, 15.7.2 Residence Total DHS table number 7. Affordable clean energy Urban Rural 7.1.1 Proportion of population with access to electricity 81.7 37.1 56.5 2.4 7.1.2 Proportion of population with primary reliance on clean fuels and technology13 22.5 2.7 11.3 2.4 Sex Total DHS table number 8. Decent work and economic growth Male Female 8.10.2 Proportion of adults (15 years and older) with an account at a bank or other financial institution or with a mobile-money-service provider14 38.5 22.1 30.3a 15.7.1, 15.7.2 16. Peace, justice, and strong institutions 16.9.1 Proportion of children under 5 years of age whose births have been registered with a civil authority 43.4 41.7 42.6a 2.11 17. Partnerships for the goals 17.8.1 Proportion of individuals using the Internet15 35.2 15.7 25.4a 3.5.1, 3.5.2 na = Not applicable 1 Expressed in terms of maternal deaths per 100,000 live births in the 7-year period preceding the survey 2 Expressed in terms of deaths per 1,000 live births for the 5-year period preceding the survey 3 Equivalent to the age-specific fertility rate for girls age 10-14 for the 3-year period preceding the survey, expressed in terms of births per 1,000 girls age 10-14 4 Equivalent to the age-specific fertility rate for women age 15-19 for the 3-year period preceding the survey, expressed in terms of births per 1,000 women age 15- 19 5 Data are not age-standardized and are available for women and men age 15-49 only. 6 The percentage of children age 12-23 months who received three doses of pentavalent (DPT-HepB-Hib) 7 The percentage of children age 24-35 months who received two doses of measles 8 The percentage of children age 12-23 months who received three doses of pneumococcal conjugate vaccine 9 Data are available for women age 15-49 who have ever been in union only. 10 In the DHS, psychological violence is termed emotional violence. 11 Data are available for currently married women who are not pregnant only. 12 Data are available for women and men age 15-49 only. 13 Measured as the percentage of the population using clean fuel for cooking 14 Data are available for women and men age 15-49 who have and use an account at a bank or other financial institution; information on use of a mobile-money- service provider is not available. 15 Data are available for women and men age 15-49 who have used the internet in the past 12 months. a The total is calculated as the simple arithmetic mean of the percentages in the columns for males and females. xxxviii • Map of Nigeria Introduction and Survey Methodology • 1 INTRODUCTION AND SURVEY METHODOLOGY 1 he 2018 Nigeria Demographic and Health Survey (2018 NDHS) was implemented by the National Population Commission (NPC). Data collection took place from 14 August to 29 December 2018. ICF provided technical assistance through The DHS Program, which is funded by the United States Agency for International Development (USAID) and offers financial support and technical assistance for population and health surveys in countries worldwide. Other agencies and organisations that facilitated the successful implementation of the survey through technical or financial support were the Global Fund, the Bill and Melinda Gates Foundation (BMGF), the United Nations Population Fund (UNFPA), and the World Health Organization (WHO). 1.1 SURVEY OBJECTIVES The primary objective of the 2018 NDHS is to provide up-to-date estimates of basic demographic and health indicators. Specifically, the NDHS collected information on fertility, awareness and use of family planning methods, breastfeeding practices, nutritional status of women and children, maternal and child health, adult and childhood mortality, women’s empowerment, domestic violence, female genital cutting, prevalence of malaria, awareness and behaviour regarding HIV/AIDS and other sexually transmitted infections (STIs), disability, and other health-related issues such as smoking. The information collected through the 2018 NDHS is intended to assist policymakers and programme managers in evaluating and designing programmes and strategies for improving the health of the country’s population. The 2018 NDHS also provides indicators relevant to the Sustainable Development Goals (SDGs) for Nigeria. 1.2 SAMPLE DESIGN The sampling frame used for the 2018 NDHS is the Population and Housing Census of the Federal Republic of Nigeria (NPHC), which was conducted in 2006 by the National Population Commission. Administratively, Nigeria is divided into states. Each state is subdivided into local government areas (LGAs), and each LGA is divided into wards. In addition to these administrative units, during the 2006 NPHC each locality was subdivided into convenient areas called census enumeration areas (EAs). The primary sampling unit (PSU), referred to as a cluster for the 2018 NDHS, is defined on the basis of EAs from the 2006 EA census frame. Although the 2006 NPHC did not provide the number of households and population for each EA, population estimates were published for 774 LGAs. A combination of information from cartographic material demarcating each EA and the LGA population estimates from the census was used to identify the list of EAs, estimate the number of households, and distinguish EAs as urban or rural for the survey sample frame. Before sample selection, all localities were classified separately into urban and rural areas based on predetermined minimum sizes of urban areas (cut-off points); consistent with the official definition in 2017, any locality with more than a minimum population size of 20,000 was classified as urban. The sample for the 2018 NDHS was a stratified sample selected in two stages. Stratification was achieved by separating each of the 36 states and the Federal Capital Territory into urban and rural areas. In total, 74 sampling strata were identified. Samples were selected independently in every stratum via a two-stage selection. Implicit stratifications were achieved at each of the lower administrative levels by sorting the sampling frame before sample selection according to administrative order and by using a probability proportional to size selection during the first sampling stage. T 2 • Introduction and Survey Methodology In the first stage, 1,400 EAs were selected with probability proportional to EA size. EA size was the number of households in the EA. A household listing operation was carried out in all selected EAs, and the resulting lists of households served as a sampling frame for the selection of households in the second stage. In the second stage’s selection, a fixed number of 30 households was selected in every cluster through equal probability systematic sampling, resulting in a total sample size of approximately 42,000 households. The household listing was carried out using tablets, and random selection of households was carried out through computer programming. The interviewers conducted interviews only in the pre-selected households. To prevent bias, no replacements and no changes of the pre-selected households were allowed in the implementing stages. Due to the non-proportional allocation of the sample to the different states and the possible differences in response rates, sampling weights were calculated, added to the data file, and applied so that the results would be representative at the national level as well as the domain level. Because the 2018 NDHS sample was a two-stage stratified cluster sample selected from the sampling frame, sampling weights were calculated based on sampling probabilities separately for each sampling stage and for each cluster. Figure 1.1 2018 Nigeria DHS sample design The 2018 NDHS included all women age 15-49 in the sample households. Those who were either permanent residents of the selected households or visitors who stayed in the households the night before the survey were eligible to be interviewed. The men’s survey was conducted in one-third of the sample households, and all men age 15-59 in these households were included (Figure 1.1). In this subsample, one eligible woman in each household was randomly selected to be asked additional questions about domestic violence. Similarly, biomarker information was collected only in those households selected for the men’s survey. The biomarkers included in this survey were height and weight for women age 15-49 and children age 0-59 months, haemoglobin testing for women age 15-49 and children age 6-59 months, and testing for Figure 1.1 2018 Nigeria DHS sample design 1,400 CLUSTERS 100% Households 1- Characteristics of household members 2- Birth registration 3- Housing characteristics 4- Household's possessions 5- Possession and use of mosquito nets 6- Salt testing 1- Background characteristics 1- Background characteristics 2- Reproduction (and child mortality) 2- Family planning 3- Family planning 3- Marriage and sexual activity 4- Pregnancy, prenatal and postnatal care 4- Fertility preferences 5- Child immunization 5- Employment and gender roles 6- Child health and nutrition 6- HIV/AIDS knowledge and attitudes 7- Marriage and sexual activity 7- Other health problems (including smoking) 8- Fertility preferences 9- Husband's characteristics, employment and gender roles 10- HIV/AIDS knowledge and attitudes 11- Other health problems (including smoking) 12- Maternal mortality 13- Domestic violence BIOMARKERS Height/weight (women 15-49, children <5) Anaemia (women 15-49, children 6-59 months) Genotype test for sickle cell disease (children 6-59 months) Microscopy malaria thick smear (children 6-59 months) Malaria RDT (children 6-59 months) Genotype test for sickle cell disease (children 6-59 months) Malaria RDT (children 6-59 months) BIOMARKERS Height/weight (women 15-49, children <5) Anaemia (women 15-49, children 6-59 months) 1- Background characteristics 2- Reproduction (and child mortality) 3- Family planning 4- Pregnancy, prenatal and postnatal care 5- Child immunization 6- Child health and nutrition 7- Marriage and sexual activity 8- Fertility preferences 9- Husband's characteristics, employment and gender roles 10- HIV/AIDS knowledge and attitudes 11- Other health problems (including smoking) 12- Maternal mortality 13- Female genital mutilation 14. Fistula 1/3 of households: 14,000 Exclude disability module 2/3 of households: 28,000 Include disability module HOUSEHOLDS 42,000 MEN (15-59) Confirmatory test for SickleSCAN (children 6-59 months) 1/3 of households: 3,500 2/3 of households: 10,500 WOMEN (15-49) WOMEN (15-49) Introduction and Survey Methodology • 3 malaria and sickle cell disease among children age 6-59 months. The disability module, female genital cutting module, and fistula module were implemented in the two-thirds of the households that were not selected for the men’s survey. The survey was successfully carried out in 1,389 clusters after 11 clusters with deteriorating law-and-order situations during fieldwork were dropped. These areas were in Zamfara (4 clusters), Lagos (1 cluster), Katsina (2 clusters), Sokoto (3 clusters), and Borno (1 cluster). In the case of Borno, 11 of the 27 LGAs were dropped due to high insecurity, and therefore the results might not represent the entire state. Please refer to Appendix A for details. 1.3 QUESTIONNAIRES Four questionnaires were used for the 2018 NDHS: the Household Questionnaire, the Woman’s Questionnaire, the Man’s Questionnaire, and the Biomarker Questionnaire. The questionnaires, based on The DHS Program’s standard Demographic and Health Survey (DHS-7) questionnaires, were adapted to reflect the population and health issues relevant to Nigeria. Comments were solicited from various stakeholders representing government ministries and agencies, nongovernmental organisations, and international donors. In addition, information about the fieldworkers for the survey was collected through a self-administered Fieldworker Questionnaire. The survey protocol was reviewed and approved by the National Health Research Ethics Committee of Nigeria (NHREC) and the ICF Institutional Review Board. After all questionnaires were finalised in English, they were translated into Hausa, Yoruba, and Igbo. The 2018 NDHS used computer-assisted personal interviewing (CAPI) for data collection. The Household Questionnaire listed all members of and visitors to selected households. Basic demographic information was collected on each person listed, including age, sex, marital status, education, and relationship to the head of the household. For children under age 18, survival status of parents was determined. Data on age, sex, and marital status of household members were used to identify women and men who were eligible for individual interviews. The Household Questionnaire also collected information on characteristics of the household’s dwelling unit, such as source of drinking water; type of toilet facilities; materials used for flooring, external walls, and roofing; ownership of various durable goods; and ownership of mosquito nets. In addition, data were gathered on salt testing and disability. The Woman’s Questionnaire was used to collect information from all eligible women age 15-49. These women were asked questions on the following topics: ▪ Background characteristics (including age, education, and media exposure) ▪ Birth history and child mortality ▪ Knowledge, use, and source of family planning methods ▪ Antenatal, delivery, and postnatal care ▪ Vaccinations and childhood illnesses ▪ Breastfeeding and infant feeding practices ▪ Women’s minimum dietary diversity ▪ Marriage and sexual activity ▪ Fertility preferences (including desire for more children and ideal number of children) ▪ Women’s work and husbands’ background characteristics ▪ Knowledge, awareness, and behaviour regarding HIV/AIDS and other sexually transmitted infections (STIs) ▪ Knowledge, attitudes, and behaviour related to other health issues (e.g., smoking) ▪ Female genital cutting ▪ Fistula ▪ Adult and maternal mortality ▪ Domestic violence 4 • Introduction and Survey Methodology The Man’s Questionnaire was administered to all men age 15-59 in the subsample of households selected for the men’s survey. The Man’s Questionnaire collected much of the same information as the Woman’s Questionnaire but was shorter because it did not contain a detailed reproductive history or questions on maternal and child health. The Biomarker Questionnaire was used to record the results of anthropometry measurements and other biomarkers for women and children. This questionnaire was administered only to the subsample selected for the men’s survey. All children age 0-59 months and all women age 15-49 were eligible for height and weight measurements. Women age 15-49 were also eligible for haemoglobin testing. Children age 6-59 months were also eligible for haemoglobin testing, malaria testing, and genotype testing for sickle cell disease. The purpose of the Fieldworker Questionnaire was to collect basic background information on the people who were collecting data in the field, including the team supervisor, field editor, interviewers, and the biomarker team (laboratory scientist and nurse). Each interviewer completed the self-administered Fieldworker Questionnaire after the final selection of interviewers and before the fieldworkers entered the field. No personal identifiers were attached to the 2018 NDHS fieldworkers’ data file. 1.4 ANTHROPOMETRY, ANAEMIA TESTING, MALARIA TESTING, AND SICKLE CELL ANAEMIA TESTING The 2018 NDHS incorporated four biomarkers: anthropometry, anaemia testing, malaria testing, and genotype testing for sickle cell anaemia. Biomarkers were collected in the one-third of households selected for the male survey. Blood specimens for the tests were collected from eligible women who voluntarily consented to be tested and from all children age 6-59 months for whom consent was obtained from their parents or the adult responsible for them. In contrast with the data collection procedure for the household and individual interviews, data related to biomarkers were initially recorded on a paper Biomarker Questionnaire and subsequently entered into interviewers’ tablet computers. As part of quality assurance, a Biomarker Checklist was used to verify that proper procedures were followed during collection of biomarker data and to enhance supportive supervision. Anthropometry: Height and weight measurements were recorded for children age 0-59 months and women age 15-49. The 2018 NDHS included quality assurance procedures to improve anthropometry data quality. These procedures, undertaken in real time during data collection, included re-measurement of all children with data outside of pre-specified flagged values on a subsequent day and re-measurement of the height and weight of 10% of a random sample of children on a subsequent day. Anaemia testing: Blood samples for anaemia testing were obtained from a drop of blood taken from a finger prick (or a heel prick for children age 6-11 months). A drop of blood from the prick site was drawn into a microcuvette, and a haemoglobin analysis was carried out on-site with a battery-operated portable HemoCue analyser. Results were provided verbally and in writing. Parents of children with a haemoglobin level below 8 g/dl were instructed to take the child to a health facility for follow-up care. Likewise, nonpregnant women and pregnant women were referred for follow-up care if their haemoglobin levels were below 8 g/dl and 7 g/dl, respectively. All households in which anaemia testing was conducted were given a brochure that explained the causes and prevention of anaemia. Malaria testing: Malaria testing was carried out among children age 6-59 months. With the same finger (or heel) prick used for anaemia testing, a drop of blood was tested immediately using the SD Bioline Ag P.f. (HRP-II)TM rapid diagnostic test (RDT), which is a qualitative test for the detection of histidine-rich protein II (HRP-II) antigen of Plasmodium falciparum (Pf) in human whole blood. Plasmodium falciparum is the predominant Plasmodium species found in Nigeria. A tiny volume of blood is captured with a disposable sample applicator and placed in the well of the testing device. All health technicians were trained to perform RDTs in the field according to the manufacturers’ instructions. Technicians read, Introduction and Survey Methodology • 5 interpreted, and recorded the RDT results after 15 minutes following the instructions in the kit insert. The RDT results were recorded as Pf positive or negative, with faint test lines being considered positive. As with anaemia testing, malaria RDT results were provided to the child’s parent or guardian in oral and written form and were recorded on the Biomarker Questionnaire. Children who tested positive for malaria by RDT were offered a full course of treatment according to the standard procedures for treating malaria in Nigeria if they did not have a severe case of malaria (diagnosed by symptoms or the presence of severe anaemia), were not currently on treatment, and had not completed a full course of artemisinin-based combination therapy (ACT) during the preceding 2 weeks. Nurses on each field team were instructed to ask about signs of severe malaria and about any medications the child might be taking. The nurses then provided the age-appropriate dose of ACT and instructions for administering the medicine to the child.1,2 The anaemia brochure also contained information on malaria and was given to all households in which malaria testing was conducted. Microscopy on thick blood smears: In addition to the SD Bioline Ag P.f. rapid test, a thick smear was prepared on a slide for 75% of the households where malaria RDTs were performed. These blood smears were dried and packed carefully in the field, assigned barcode labels corresponding to the Biomarker Questionnaire, and then transported to the state-level laboratory, where they were stained. There were 18 designated staining sites in the states, one site for each two states. The stained slides were then transferred to the Primary Testing Laboratory (ANDI Centre of Excellence for Malaria Diagnosis, Lagos University Teaching Hospital). Microscopy to determine malaria infection was carried out in this laboratory. External quality control was conducted on a selected proportion of the slides in the Secondary Testing Laboratory at the University of Calabar Teaching Hospital. Genotype testing for sickle cell disease: Sickle cell disease (SCD) is a common and life-threatening haematological disorder. Given that sickle cell anaemia is a public health concern in Nigeria, it was thought vital to include this disease in the survey as there is no reliable information at the national level. Blood collection for genotype testing was carried out among children age 6-59 months. With the same finger (or heel) prick used for anaemia and malaria testing, a drop of blood was tested immediately using the SickleSCAN® rapid diagnostic test kit. A tiny portion of blood was captured on the capillary sampler, dispensed into the PreTreatment Module, and mixed to allow complete treatment of the specimen with buffer. The specimen was then dispensed into the SickleSCAN cartridge. Results were available in 5 minutes. The results were provided to the respondent or the child’s parent/guardian through the pamphlet and also recorded on the Biomarker Questionnaire. Parents or guardians whose children have sickle cell disease were urged to take the child to a health facility for follow-up care. In 25% of the households where genotype testing was done, a confirmatory test for the SickleSCAN RDT was conducted. Using the same finger (or heel) prick used for the above tests, a drop of blood was collected on the filter paper card to form a dry blood spot to which a barcode label unique to the child was affixed. A duplicate label was attached to the Biomarker Data Collection Form. A third copy of the same barcode was affixed to the Dried Blood Spot Transmittal Sheet to track the blood samples from the field to the laboratory. The samples were then transported to the standard laboratory for high-performance liquid chromatography (HPLC) confirmatory testing at the International Foundation Against Infectious Disease in Nigeria (IFAIN) in Abuja. Upon arrival at the laboratory, each blood sample was logged into the CSPro Genotype Test Tracking System database, given a laboratory number, and stored at -20C or lower until 1 Dosage of ACT was based on the age of the recipient. The proper dosage for a child age 6 months to 3 years is one tablet of artemether-lumefantrine (co-formulated tablets containing 20 mg artemether and 120 mg lumefantrine) to be taken twice daily for 3 days, while the dosage for a child age 4-8 is two tablets of artemether-lumefantrine to be taken twice daily for 3 days. 2 Children who exhibited signs of severe malaria (based on symptoms or laboratory confirmation of severe anaemia) were referred to the nearest facility for treatment. 6 • Introduction and Survey Methodology tested. Test results for the 2018 NDHS were entered into a spreadsheet with a barcode as the unique identifier for each result. 1.5 PRETEST The pretest training was designed to prepare the trainers for the main training as well as to ensure that they were well versed with the NDHS questionnaires and procedures and able to test the questionnaires in the different languages. The training involved sessions of administering the NDHS questionnaires and a separate session for biomarker data collection. Forty-five participants, comprising 5 zonal and 20 state NPC coordinators, 5 National Malaria Elimination Programme (NMEP) coordinators, 2 senior lab scientists from the Lagos University Teaching Hospital (LUTH), 4 lab scientists, 4 nurses, 2 enumerators, and 3 data processing staff members, took part in the pretest training and fieldwork. The pretest took place over a 3-week period from 30 April to 20 May 2018. Most of the participants had previous experience carrying out NDHS surveys or the Nigeria Malaria Indicator Survey (NMIS). The idea behind having the data processing staff participate in the pretest was to familiarise them with the CAPI system. The training was conducted by ICF staff who focused on the technical components of the survey, biomarkers, and the CAPI data collection system. The training focused on key components of the survey, interview techniques and procedures for completing the NDHS questionnaires, and administration of interviews using the CAPI system. The biomarker training included orientation on collecting height and weight data, testing for anaemia and malaria and genotype testing for sickle cell disease, and standardisation procedures for anthropometry. The participants worked in groups using various training techniques, including interactive question-and-answer sessions, case studies, and role-plays. Before starting the fieldwork, the participants were given ample opportunities to practice on how to administer the questionnaires and to practice collection of biomarkers among women and children. The participants administered the questionnaires in the field, provided feedback on the content and language of the questionnaires, tested the CAPI software programme, commented on the biomarker procedure, and learned various training techniques. The fieldwork for the pretest was carried out in communities that spoke English, Hausa, Yoruba, and Igbo. Each team carried out the pretest in an urban and a rural location, completing eight clusters in total. Following the fieldwork, a debriefing session was held with the pretest field staff, and modifications to the questionnaires were made based on lessons learned from the exercise. 1.6 TRAINING OF FIELD STAFF Prior to the main training, biomarker training was held for the laboratory scientists and nurses from 25 June to 6 July 2018. The training was facilitated by the ICF team and supported by the trainers who were trained during the pretest. A total of 37 nurses and 37 laboratory scientists were trained on biomarker data collection and recording. This included training on anthropometry; using rapid test kits to test for anaemia, malaria, and sickle cell disease; preparing slides for malaria parasitaemia; and preparing dried blood spots for confirmatory testing of sickle cell diagnostics. The training utilised a variety of different learning tools. Plenary lectures were held on the technical aspects of biomarker collection, and other tools included video and hands-on demonstrations on the process of biomarker collection, instructions on how to fill out the questionnaire and transmittal sheets, and instructions on data quality procedures. In addition, break-out sessions were held daily at which trainees had the opportunity for hands-on practice with both adults and children. A total of four anthropometry standardisation exercises with 40 children and two re-standardisation exercises were undertaken. Following the standardisation exercise, the results of the exercise were presented. General observations on accuracy (difference between the reference value and the participant’s value) and precision (difference between the first and second readings) were discussed. Introduction and Survey Methodology • 7 The field coordinators were trained on the use of the Biomarker Checklist. Also implemented were random re-measurements for quality assurance and re-visitation of households for re-measurements for flagged cases involving children whose z-score values were less than -3 or greater than 3. A 2-day field practice was conducted. The nurses and laboratory scientists later joined the main team for refresher training before moving on to data collection. The main training for the 2018 NDHS started on 16 July 2018 and lasted until 13 August 2018. The training included 4 weeks of orientation on data collection instruments and procedures followed by field practice. The 358 participants for the main training were selected through a strict vetting process at the state level. Applicants took a written test and a computerised test and also completed a personal interview to qualify for participation in the main training. Attendees came from different parts of Nigeria and represented major language groups within the country. Most of the candidates had previous fieldwork experience, and some had experience gained through previous rounds of the Nigeria DHS and Malaria Indicator Survey. Twenty-eight state coordinators from the NPC and five national coordinators from the NMEP who had participated in the pretest training and training of trainers facilitated the training. ICF staff provided technical support during the training sessions. The participants were divided into six classrooms of about 45 participants with at least three facilitators in each room. The training sessions included discussion of concepts, procedures, and methodologies for conducting the DHS survey. Participants were guided through the questionnaires using various training techniques such as role-plays, age probing in pairs, group discussion, in-class exercises, case studies, and presentations. The training also included discussions of the CAPI system, demonstrations of the CAPI DHS menus, and conducting of interviews through the CAPI system. Participants were evaluated through in-class exercises, quizzes, and observations made during field practice. Ultimately, 37 supervisors and 37 field editors were identified based on their performance. Similarly, 74 male interviewers and 111 female interviewers were selected to serve as enumerators, while the rest were kept as reserves. Thirty-seven laboratory scientists and 37 nurses were also selected to participate in the survey. The team supervisors received additional training on providing logistical support, managing the field teams, observing interviews, keeping an inventory of supplies, and collecting biomarker data. They were also trained on implementing the Biomarker Checklist to carry out data quality assurance. The field editors received additional training in performing supervisory activities with the CAPI system, data quality control procedures, fieldwork coordination, and management. The field editors were trained on assigning households and receiving completed interviews from the interviewers, recognising and dealing with error messages, receiving system updates and distributing updates to interviewers, entering biomarker questionnaires, implementing the re-measurement and re-visit questionnaires and the Biomarker Checklist, resolving duplicated cases, and closing clusters. They were also trained on transferring interviews to the central office via the secure internet file streaming system (IFSS) developed by The DHS Program. Six quality controllers for biomarker data collection were identified from among the trainees who underwent training during biomarker training, pretest training, and the main training, and they received additional training on supporting the teams and monitoring fieldwork through the Biomarker Checklist. 1.7 FIELDWORK The fieldwork for the 2018 NDHS was launched under close supervision on 14 August 2018 in the clusters in the six zonal take-off centres. Thirty-seven teams, each consisting of one supervisor, one field editor, two male interviewers, three female interviewers, one lab scientist, and one nurse, were assigned across the different clusters in the zones. The teams were closely monitored by the state coordinators and the quality 8 • Introduction and Survey Methodology controllers. After completion of the fieldwork in the zonal take-off centres in the first week, all of the teams were brought back to the zonal office for a review session where they had an opportunity to clarify any questions they had. The teams were then dispatched to their respective states. Data collection lasted until 29 December 2018. The fieldwork in some states took longer than expected due to the security situation. Fieldwork monitoring was an integral part of the 2018 NDHS, and several rounds of monitoring were carried out by the NDHS core team, the state coordinators from the NPC and NMEP, and ICF staff. The monitors were provided with guidelines for overseeing the fieldwork. Weekly field check tables were generated from the completed interviews sent to the central office to monitor fieldwork progress, and regular feedback was sent out to the teams. 1.8 DATA PROCESSING The processing of the 2018 NDHS data began almost immediately after the fieldwork started. As data collection was completed in each cluster, all electronic data files were transferred via the IFSS to the NPC central office in Abuja. These data files were registered and checked for inconsistencies, incompleteness, and outliers. The field teams were alerted to any inconsistencies and errors. Secondary editing, carried out in the central office, involved resolving inconsistencies and coding the open-ended questions. The NPC data processor coordinated the exercise at the central office. The biomarker paper questionnaires were compared with electronic data files to check for any inconsistencies in data entry. Data entry and editing were carried out using the CSPro software package. The concurrent processing of the data offered a distinct advantage because it maximised the likelihood of the data being error-free and accurate. Timely generation of field check tables allowed for effective monitoring. The secondary editing of the data was completed in the second week of April 2019. Throughout this report, figures in the tables reflect weighted numbers. Percentages based on 25 to 49 unweighted cases are shown in parentheses, and percentages based on fewer than 25 unweighted cases are suppressed and replaced with an asterisk. This is to caution readers when interpreting data that a percentage based on fewer than 50 cases may not be statistically reliable. 1.9 RESPONSE RATES Table 1.1 shows response rates for the 2018 NDHS. A total of 41,668 households were selected for the sample, of which 40,666 were occupied. Of the occupied households, 40,427 were successfully interviewed, yielding a response rate of 99%. In the households interviewed, 42,121 women age 15-49 were identified for individual interviews; interviews were completed with 41,821 women, yielding a response rate of 99%. In the subsample of households selected for the male survey, 13,422 men age 15-59 were identified and 13,311 were successfully interviewed, yielding a response rate of 99%. Introduction and Survey Methodology • 9 Table 1.1 Results of the household and individual interviews Number of households, number of interviews, and response rates, according to residence (unweighted), Nigeria DHS 2018 Residence Total Result Urban Rural Household interviews Households selected 17,282 24,386 41,668 Households occupied 16,906 23,760 40,666 Households interviewed 16,780 23,647 40,427 Household response rate1 99.3 99.5 99.4 Interviews with women age 15-49 Number of eligible women 17,127 24,994 42,121 Number of eligible women interviewed 16,984 24,837 41,821 Eligible women response rate2 99.2 99.4 99.3 Household interviews in subsample Households selected 5,762 8,131 13,893 Households occupied 5,657 7,946 13,603 Households interviewed 5,614 7,900 13,514 Household response rate in subsample1 99.2 99.4 99.3 Interviews with men age 15-59 Number of eligible men 5,547 7,875 13,422 Number of eligible men interviewed 5,506 7,805 13,311 Eligible men response rate2 99.3 99.1 99.2 1 Households interviewed/households occupied 2 Respondents interviewed/eligible respondents Housing Characteristics and Household Population • 11 HOUSING CHARACTERISTICS AND HOUSEHOLD POPULATION 2 Key Findings ▪ Drinking water: Overall, 66% of households have access to an improved source of drinking water (74% in urban areas and 58% in rural areas). ▪ Availability of water: 71% of households using piped water or water from a tube well or borehole reported having water available to them without an interruption of at least 1 day. ▪ Sanitation: 56% of Nigerian households use an improved sanitation facility. ▪ Electricity: 59% of households have electricity (83% of urban households and 39% of rural households). ▪ Orphans: 6% of Nigerian children under age 18 are orphans (i.e., one or both parents are dead). Eight percent of children do not live with a biological parent. ▪ Birth registration: 43% of children under age 5 have their births registered with the civil authorities; among these 62% are registered with NPC. ▪ Education: Overall, 36% of females and 27% of males in Nigeria have no education. ▪ School attendance: The net attendance ratio (NAR) is 61% at the primary level and 49% at the secondary level. nowledge regarding the socioeconomic characteristics of the household population in the 2018 NDHS provides a context to interpret demographic and health indicators and can furnish an approximate indication of the accurateness of the survey. In addition, this information sheds light on the living conditions of the population. This chapter presents information on sources of drinking water, sanitation, exposure to smoke inside the home, wealth, handwashing, household population and composition, educational attainment, school attendance, birth registration, and family living arrangements. 2.1 DRINKING WATER SOURCES AND TREATMENT Improved sources of drinking water Include piped water, public taps, standpipes, tube wells, boreholes, protected dug wells and springs, rainwater, water delivered via a tanker truck or a cart with a small tank, and bottled water. Sample: Households In Nigeria, 66% of households have access to an improved source of drinking water, 74% in urban areas and 58% in rural areas (Table 2.1.1). Urban and rural households rely on similar sources of drinking water. The three most common improved sources of drinking water in urban and rural households are tube wells K 12 • Housing Characteristics and Household Population or boreholes (41% in urban and 34% in rural households), protected dug wells or springs (13% in urban and 12% in rural households), and public taps/standpipes (7% in urban and 8% in rural households) (Figure 2.1). Twenty-six percent of urban households and 42% of rural households still depend on unimproved sources for their drinking water. Among urban households, sachet water (18%) is the most common unimproved source of drinking water, while unprotected dug wells (22%) and surface water (15%) are the most common unimproved sources in rural households. Figure 2.2 Improved water source by state Percentage of households with improved source of drinking water The percentage of households with improved sources of drinking water is highest in the South East (81%) and lowest in the North East (60%). Across the states, access to an improved source of drinking water is lowest in Sokoto (34%) and highest in Imo (90%) (Figure 2.2). Access to an improved source of drinking Figure 2.1 Household drinking water by residence 4 6 2 8 7 8 37 41 34 12 13 12 5 8 3 34 26 42 Total Urban Rural Percent distribution of households by source of drinking water Unimproved source Other improved (rainwater/ tanker/cart/bottle) Protected well or spring Tube well or borehole Public tap/standpipe Piped water into dwelling/yard/plot/ neighbour’s yard Housing Characteristics and Household Population • 13 water is most common among residents in the fourth wealth quintile and least common among those in the lowest quintile (84% and 41%, respectively). Basic drinking water service Drinking water from an improved source, provided either water is on the premises or round-trip collection time is 30 minutes or less. Sample: De jure population Clean water is a basic need for human life; 62% of Nigeria’s population has basic drinking water service (72% of the urban population and 54% of the rural population) (Table 2.1.1). Only 38% of households in the lowest wealth quintile have basic drinking water service (Table 2.1.2). Limited drinking water service Drinking water from an improved source, and round-trip collection time is more than 30 minutes. Sample: De jure population Fetching drinking water is an additional chore that could be of great cost to household members, depending on the time spent to obtain it. Six percent of urban households and 8% of rural households report having to travel more than 30 minutes to access an improved source of drinking water (Table 2.1.1). Overall, 3% of households in Nigeria have limited drinking water service (4% in urban areas and 3% in rural areas). Most households in Nigeria (92%) report that they do not treat their water prior to drinking. Five percent of households use an appropriate treatment method, 7% in urban areas and 3% in rural areas. Appropriate treatment methods include boiling, adding bleach or chlorine, filtering through ceramic, sand, or other filters, and solar disinfecting (Table 2.1.3). Table 2.2 presents information on the percentage of households using piped water or water from a tube well or borehole that reported availability of water in the last 2 weeks. Seventy-one percent of households in Nigeria reported having water with no interruption of at least 1 day in the 2 weeks before the survey. Seventy-three percent of rural households had availability with no interruption of at least 1 day, as compared with 69% of urban households. Urban households were more likely than rural households to report not having water available for at least 1 day (31% and 27%, respectively). 2.2 SANITATION Improved toilet facilities Include flush/pour flush toilets that flush water and waste to a piped sewer system, septic tank, pit latrine, or an unknown destination; ventilated improved pit (VIP) latrines; pit latrines with slabs; or composting toilets. Sample: Households 14 • Housing Characteristics and Household Population Table 2.3.1 provides an overview of the types of sanitation facilities available in the surveyed households at the time of data collection. Overall, 56% of Nigerian households use improved toilet facilities, 74% in urban areas and 39% in rural areas (Figure 2.3). A pit latrine with a slab is the most common type of improved sanitation facility in Nigeria, used by 23% of households (24% in urban areas and 23% in rural areas). This is followed by flush/pour flush toilets that flush to a septic tank (16%); 27% of households in urban areas use this type of facility, as compared with only 6% of households in rural areas. Among rural households, 28% use unimproved toilet facilities, most commonly pit latrines without slabs (27%). Open defecation is still widespread in Nigeria, with 25% of households (33% of rural households and 15% of urban households) engaging in this practice. Trends: The proportion of households with no toilet facility has decreased over the last 5 years, from 29% of households in 2013 to 25% of households in 2018. Basic sanitation service Use of improved facilities that are not shared with other households. Sample: De jure population With respect to location of toilet facility, 37% of households in Nigeria have their toilet facility in their own dwelling (46% of urban households and 28% of rural households). Forty-three percent of households have basic sanitation service (48% of urban households and 37% of rural households) (Table 2.3.1). Limited sanitation service Use of improved facilities shared by two or more households. Sample: De jure population In Nigeria, 31% of households have limited sanitation service. Forty percent of urban households use improved toilet facilities that are shared with other households, as compared with only 21% of rural households. Overall, 53% of the Nigerian population has access to an improved sanitation facility, while 24% has access to an unimproved facility. Twenty-three percent of the population engages in open defecation. Patterns by background characteristics ▪ Open defecation is most common in the North Central zone (51%) and least common in the North West (9%) (Table 2.3.2). ▪ The percentage of households with access to an improved sanitation facility is highest in the South West zone (71%) and lowest in the North Central and North West zones (43% each). ▪ At the state level, Abia has the highest percentage of households with an improved sanitation facility (93%), while Ebonyi has the lowest (17%). ▪ Only 9% of households in Kebbi and 10% in Ebonyi have basic sanitation service, the lowest percentages among the states. Figure 2.3 Household toilet facilities by residence 56 74 39 20 11 28 25 15 33 Total Urban Rural Percent distribution of households by type of toilet facilities No facility/ bush/field Unimproved facility Improved facility Housing Characteristics and Household Population • 15 ▪ As expected, access to an improved sanitation facility is most common among households in the highest wealth quintile (94%) and least common among households in the lowest quintile (12%). 2.3 EXPOSURE TO SMOKE INSIDE THE HOME Exposure to smoke inside the home, from either cooking with solid fuels or smoking tobacco, has potentially harmful health effects. In Nigeria, 69% of households use some type of solid fuel for cooking, with 61% using wood (Table 2.4). Exposure to cooking smoke is greater when cooking takes place inside the house rather than in a separate building or outdoors. In 40% of households, cooking is done in the house (48% in urban areas and 34% in rural areas). In 7% of households, someone smokes inside the house on a daily basis. Overall, only 15% of households in Nigeria use clean fuel for cooking, 27% in urban areas and 4% in rural areas. Other Housing Characteristics The 2018 NDHS also collected data on access to electricity, flooring materials, and the number of rooms used for sleeping. Fifty-nine percent of households in Nigeria have access to electricity (83% in urban areas and 39% in rural areas) (Table 2.4). A majority of both urban (68%) and rural (54%) households use cement flooring in their dwellings. 2.4 HOUSEHOLD WEALTH Household Durable Goods The survey also collected information on household effects, means of transportation, and ownership of agricultural land and farm animals. In general, urban households are more likely than rural households to possess household effects. The most commonly found item in all households is a bed (94%). This is followed by a mobile phone (88%); 95% of urban and 82% of rural households own a mobile phone. As expected, rural households are more likely than urban households to own agricultural land and farm animals. Thirty-two percent of urban households own agricultural land, as compared with 76% of rural households (Table 2.5). Wealth Index Wealth index Households are given scores based on the number and kinds of consumer goods they own, ranging from a television to a bicycle or car, and housing characteristics such as source of drinking water, toilet facilities, and flooring materials. These scores are derived using principal component analysis. National wealth quintiles are compiled by assigning the household score to each usual (de jure) household member, ranking each person in the household population by her or his score, and then dividing the distribution into five equal categories, each comprising 20% of the population. Sample: Households 16 • Housing Characteristics and Household Population Table 2.6 shows that the wealthiest households are concentrated in urban areas (38%); only 6% of the wealthiest households are in rural areas (Figure 2.4). The South West zone has a much higher percentage of households in the highest wealth quintile (48%) than the North East and North West zones (5% and 9%, respectively). Among the states, Lagos has the highest percentage of households in the highest wealth quintile (75%), while Kebbi, Yobe, and Sokoto have the lowest (2% each). 2.5 HANDWASHING To obtain handwashing information, interviewers asked to see the place where members of the household most often wash their hands. Interviewers were able to observe a place for handwashing in 81% of households (84% in urban areas and 79% in rural areas) (Table 2.7). Thirty-eight percent of households had soap and 63% had water available. Cleansing agents other than soap were available in 1% of households. The availability of soap and water varies across zones, from a low of 12% and 44%, respectively, in the North East to a high of 61% and 85%, respectively, in the South West. Availability of soap and water increases with increasing wealth; 68% and 87% of households in the highest wealth quintile had soap and water available, as compared with 13% and 41% of households in the lowest quintile. 2.6 HOUSEHOLD POPULATION AND COMPOSITION Household A person or group of related or unrelated persons who live together in the same dwelling unit(s), who acknowledge one adult male or female as the head of the household, who share the same housekeeping arrangements, and who are considered a single unit. De facto population All persons who stayed in the selected households the night before the interview (whether usual residents or visitors). De jure population All persons who are usual residents of the selected households, whether or not they stayed in the household the night before the interview. How data are calculated All tables are based on the de facto population unless otherwise specified. Household composition and population data provide information on the socioeconomic characteristics of the households and respondents surveyed in terms of age, sex, and place of residence. A total of 187,974 individuals stayed overnight in the 40,427 interviewed households; 49% of these individuals were male and 51% were female, yielding a sex ratio (number of males per 100 females) of 97. Figure 2.4 Household wealth by residence 4 328 29 19 21 31 12 38 6 Urban Rural Percent distribution of de jure population by wealth quintiles Wealthiest Fourth Middle Second Poorest Housing Characteristics and Household Population • 17 Forty-six percent of individuals are in the 0-14 dependency age group, while 4% are in the 65 and above dependency age group (Table 2.8). Fifty percent of the population is in the 15-64 age group. Children age 0-17 form the bulk of the population (52%). The broad base of the population pyramid shows that Nigeria’s population is typical of countries with a low life expectancy and high fertility rates (Figure 2.5). The average household size in Nigeria is 4.7 persons. Urban households are slightly smaller than rural households (4.3 persons versus 5.0 persons). A majority of the households in Nigeria are headed by men (82%) (Table 2.9). 2.7 CHILDREN’S LIVING ARRANGEMENTS AND PARENTAL SURVIVAL Orphan A child with one or both parents who are dead. Sample: Children under age 18 Table 2.10 presents the percentage distribution of children under age 18 by living arrangements and survival status of parents. Eight percent of children under age 18 do not live with a biological parent, while 6% are orphans (i.e., one or both parents are dead). Among children less than age 2, 2% were not leaving with their parents at the time of the interview, and 1% had lost one or both parents. The percentage of children who are orphans rises rapidly with age, from 3% among those under age 2-4 to 14% among those age 15-17. The South East has the highest percentage of children who are orphans (9%), while the North West and South West have the lowest percentages (5% each). Trends: The percentage of children under age 18 living with both parents has increased over time, from 71% in 2008 to 74% in 2013 and 75% in 2018. 2.8 BIRTH REGISTRATION Registered birth Child has a birth certificate or child does not have a birth certificate, but his/her birth is registered with the civil authorities. Sample: De jure children under age 5 Table 2.11 presents information on birth registration of children under age 5. Birth registration is the documentation of the facts of each birth into an official log book kept at the registrar’s office. According to the Births and Deaths (Compulsory Registration) Act Number 69 of 1992, registration of births and deaths is compulsory in all cases in Nigeria. The National Population Commission is responsible for registering Figure 2.5 Population pyramid 10 6 2 2 6 10 <5 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+ Age Percent distribution of the household population Male Female 2610 18 • Housing Characteristics and Household Population these important events nationwide (NPC 1992). Information was collected in the household interview whereby respondents were asked if children under age 5 residing in the household have been registered. At the time of the survey, 43% of children under age 5 were registered with the civil authorities (39% of children under age 2 and 45% of children between age 2 and 4). One in five of these children had birth certificates. Children in urban areas are much more likely than rural children to have their births registered (60% versus 32%). Birth registration increases with increasing household wealth (Figure 2.6). Children in the highest wealth quintile are much more likely to have their birth registered (75%) than children in the lowest wealth quintile (16%). Table 2.12 presents the percent distribution of children under age 5 whose births are registered with the civil authorities by type of authority. The results show that 62% of births in the 5 years preceding the survey were registered with the National Population Commission. Ten percent of children were registered under a local government administration, 26% with a private clinic/hospital, and the remaining 3% with other agencies. The percentage of children registered with the National Population Commission is higher in urban areas (64%) than in rural areas (60%). Across the states, registration of births under the commission is highest in Delta (99%) and lowest in Adamawa (20%); Adamawa has the highest percentage of births registered with a private clinic/hospital (65%). Trends: The proportion of de jure children whose births were registered has increased since 2013, from 30% to 43%. Birth registration under the National Population Commission has also increased, from 57% to 62%. 2.9 EDUCATION 2.9.1 Educational Attainment Median educational attainment Half of the population has completed less than the median number of years of schooling, and half of the population has completed more than the median number of years of schooling. Sample: De facto household population age 6 and older Education is one of the most important aspects of social and economic development. Education improves capabilities and is strongly associated with various socioeconomic variables such as lifestyle, income, and fertility for both individuals and societies. Overall, 36% of females and 27% of males in Nigeria have no education (Table 2.13.1 and Table 2.13.2). Eighteen percent of females and 19% of males age 6 or older have attended some primary school; however, only 11% of both sexes have completed a primary education. The median number of years of schooling is 3.6 for women and 5.4 for men. Patterns by background characteristics ▪ Urban residents are much more likely than rural residents to be educated. Twenty percent of females age 6 and older in urban areas have no education, as compared with 49% of females in rural areas. The proportions among males are 13% and 37%, respectively. Figure 2.6 Birth registration by household wealth 16 28 43 61 75 Lowest Second Middle Fourth Highest Percentage of de jure children under age 5 whose births are registered with the civil authorities Poorest Wealthiest Housing Characteristics and Household Population • 19 ▪ At the zonal level, the North West and North East have the highest percentages of both females (55% and 57%, respectively) and males (40% and 47%, respectively) with no education. ▪ Twenty-four percent of women in the highest wealth quintile have more than a secondary education, while only 7% have no education. On the contrary, 75% of women in the lowest quintile have no education and less than 1% have more than a secondary education. Trends: The percentage of females age 6 and over with no education has decreased slightly since 2013, from 40% to 36%. A similar pattern is observed among males, with a reduction from 30% to 27%. Secondary school or higher level attainment among women has increased slightly, from 16% to 23%, while among men it has increased from 24% to 30%. The median number of years of schooling has increased from 1.7 to 3.6 among women and from 4.7 to 5.4 among men. 2.9.2 School Attendance Net attendance ratio (NAR) Percentage of the school-age population that attends primary or secondary school. Sample: Children age 6-12 for primary school NAR and children age 13-18 for secondary school NAR The primary school net attendance ratio (NAR) for children age 6-12 is 61% (59% for girls and 62% for boys). The secondary NAR drops drastically to 47% among girls and 52% among boys (Table 2.14). Patterns by background characteristics ▪ There is a substantial difference in the primary school NAR between urban and rural areas (72% and 53%, respectively). The difference increases at the secondary school level (65% in urban areas and 37% in rural areas). ▪ Among the zones, the primary and secondary NARs are highest in the South East (82% and 75%, respectively) and lowest in the North East (46% and 31%, respectively). ▪ The NAR increases with increasing household wealth, especially at the secondary school level. The overall secondary NAR rises from 15% in the lowest wealth quintile to 70% in the fourth and highest quintiles. Among girls, the secondary NAR increases from 12% in the lowest quintile to 68% in the fourth and highest quintiles (Figure 2.7). Other Measures of School Attendance Gross attendance ratio (GAR) The total number of children attending primary school divided by the official primary school-age population and the total number of children attending secondary school divided by the official secondary school-age population. Sample: Children age 6-12 for primary school GAR and children age 13-18 for secondary school GAR Figure 2.7 Secondary school attendance by household wealth 12 31 51 68 68 17 43 61 73 71 Lowest Second Middle Fourth Highest Net attendance ratio for secondary school among children age 13-18 Girls Boys WealthiestPoorest 20 • Housing Characteristics and Household Population Gender parity index (GPI) The ratio of female to male students attending primary school and the ratio of female to male students attending secondary school. The index reflects the magnitude of the gender gap. Sample: Primary school students and secondary school students The gross attendance ratio (GAR) and gender parity index (GPI) are also presented in Table 2.14. A primary school GAR value of more than 100% means that a significant number of primary school students are not of the official primary school age. In Nigeria, the GAR is 86% at the primary level (83% for females and 88% for males) and 71% at the secondary level (67% for females and 74% for males). A GPI of 1 indicates parity or equality between male and female school participation ratios. A GPI lower than 1 indicates a gender disparity in favour of males, with a higher proportion of males than females attending the specified level of schooling. A GPI higher than 1 indicates a gender disparity in favour of females. In Nigeria, the GPI is 0.95 at the primary school level and 0.91 at the secondary school level, indicating that more boys than girls attend primary and secondary school. LIST OF TABLES For more information on household population and housing characteristics, see the following tables: ▪ Table 2.1.1 Household drinking water ▪ Table 2.1.2 Drinking water according to zone, state, and wealth ▪ Table 2.1.3 Treatment of household drinking water ▪ Table 2.2 Availability of water ▪ Table 2.3.1 Household sanitation facilities ▪ Table 2.3.2 Sanitation facility type according to zone, state, and wealth ▪ Table 2.4 Household characteristics ▪ Table 2.5 Household possessions ▪ Table 2.6 Wealth quintiles ▪ Table 2.7 Handwashing ▪ Table 2.8 Household population by age, sex, and residence ▪ Table 2.9 Household composition ▪ Table 2.10 Children’s living arrangements and orphanhood ▪ Table 2.11 Birth registration of children under age 5 ▪ Table 2.12 Birth registration of children under age 5 by authority ▪ Table 2.13.1 Educational attainment of the female household population ▪ Table 2.13.2 Educational attainment of the male household population ▪ Table 2.14 School attendance ratios Housing Characteristics and Household Population • 21 Table 2.1.1 Household drinking water Percent distribution of households and de jure population by source of drinking water and by time to obtain drinking water, percentage of households and de jure population with basic drinking water service, and percentage with limited drinking water service, according to residence, Nigeria DHS 2018 Households Population Characteristic Urban Rural Total Urban Rural Total Source of drinking water Improved source 73.9 58.4 65.7 76.1 57.0 65.3 Piped into dwelling/yard/plot 4.8 1.5 3.0 5.7 1.8 3.5 Piped to neighbour 0.9 0.4 0.7 1.1 0.4 0.7 Public tap/standpipe 7.3 7.6 7.5 7.4 7.5 7.5 Tube well or borehole 40.8 34.0 37.2 41.1 33.1 36.6 Protected dug well 11.9 11.0 11.4 11.5 10.8 11.1 Protected spring 0.6 0.5 0.5 0.6 0.4 0.4 Rainwater 2.2 1.8 2.0 2.2 1.4 1.7 Tanker truck/cart with small tank 4.1 1.3 2.6 5.5 1.7 3.3 Bottled water 1.3 0.1 0.7 0.9 0.1 0.5 Unimproved source 25.9 41.6 34.2 23.7 42.9 34.6 Unprotected dug well 3.3 22.4 13.5 4.4 25.9 16.6 Unprotected spring 0.9 2.2 1.6 0.9 2.2 1.6 Surface water 3.6 14.5 9.4 3.6 13.3 9.1 Sachet water 18.1 2.4 9.8 14.8 1.4 7.2 Other 0.2 0.0 0.1 0.2 0.1 0.1 Total 100.0 100.0 100.0 100.0 100.0 100.0 Time to obtain drinking water (round trip) Water on premises1 41.7 26.3 33.5 41.6 26.8 33.2 30 minutes or less 52.2 65.8 59.5 52.2 65.5 59.7 More than 30 minutes 5.9 7.8 6.9 6.1 7.7 7.0 Total 100.0 100.0 100.0 100.0 100.0 100.0 Percentage with basic drinking water service2 70.2 55.5 62.4 72.1 54.1 61.9 Percentage with limited drinking water service3 3.6 2.8 3.2 4.0 2.8 3.3 Number of households/population 18,940 21,487 40,427 81,770 106,586 188,355 1 Includes water piped to a neighbour and those reporting a round-trip collection time of zero minutes 2 Defined as drinking water from an improved source, provided either water is on the premises or round-trip collection time is 30 minutes or less. Includes safely managed drinking water, which is not shown separately. 3 Drinking water from an improved source, and round-trip collection time is more than 30 minutes 22 • Housing Characteristics and Household Population Table 2.1.2 Drinking water according to zone, state, and wealth Percent distribution of de jure population by drinking water source, percentage of de jure population with basic drinking water service, and percentage with limited drinking water service, according to zone, state, and wealth quintile, Nigeria DHS 2018 Background characteristic Improved source of drinking water1 Unimproved source of drinking water2 Total Percentage with basic drinking water service3 Percentage with limited drinking water service4 Number of persons Zone North Central 63.8 36.2 100.0 62.2 1.6 25,640 North East 60.1 39.9 100.0 56.3 3.5 32,602 North West 60.7 39.3 100.0 57.7 2.9 58,840 South East 80.8 19.2 100.0 73.8 7.0 20,227 South South 71.9 28.1 100.0 69.7 2.1 20,552 South West 66.5 33.5 100.0 62.7 3.7 30,495 State North Central FCT-Abuja 68.4 31.6 100.0 65.6 2.7 1,292 Benue 73.1 26.9 100.0 72.0 1.1 5,267 Kogi 65.3 34.7 100.0 62.2 3.2 2,580 Kwara 63.4 36.6 100.0 61.7 1.7 3,265 Nasarawa 74.8 25.2 100.0 74.3 0.5 2,891 Niger 61.0 39.0 100.0 60.7 0.3 6,409 Plateau 45.4 54.6 100.0 41.7 3.6 3,936 North East Adamawa 51.6 48.4 100.0 51.5 0.0 4,118 Bauchi 62.5 37.5 100.0 62.3 0.2 7,245 Borno 71.5 28.5 100.0 64.8 5.3 6,790 Gombe 43.0 57.0 100.0 36.9 6.1 3,593 Taraba 44.6 55.4 100.0 41.4 3.2 3,905 Yobe 69.0 31.0 100.0 63.0 6.0 6,952 North West Jigawa 83.2 16.8 100.0 83.1 0.0 6,938 Kaduna 66.1 33.9 100.0 62.8 3.3 10,691 Kano 58.6 41.4 100.0 52.4 6.2 13,340 Katsina 63.6 36.4 100.0 59.3 4.3 11,449 Kebbi 48.7 51.3 100.0 47.5 0.6 5,267 Sokoto 34.4 65.6 100.0 34.0 0.4 4,755 Zamfara 56.2 43.8 100.0 56.2 0.1 6,400 South East Abia 89.5 10.5 100.0 84.6 4.9 2,607 Anambra 78.5 21.5 100.0 78.1 0.5 5,728 Ebonyi 76.7 23.3 100.0 60.8 15.8 4,248 Enugu 72.5 27.5 100.0 62.7 9.7 3,453 Imo 89.6 10.4 100.0 83.3 6.3 4,191 South South Akwa Ibom 77.3 22.7 100.0 73.7 3.6 3,867 Bayelsa 52.8 47.2 100.0 52.8 0.0 1,484 Cross River 53.6 46.4 100.0 49.5 4.1 2,360 Delta 75.4 24.6 100.0 75.1 0.2 4,286 Edo 73.8 26.2 100.0 68.9 4.9 2,712 Rivers 77.0 23.0 100.0 76.0 0.9 5,842 South West Ekiti 80.2 19.8 100.0 74.6 5.6 2,108 Lagos 50.3 49.7 100.0 44.1 6.2 11,272 Ogun 74.0 26.0 100.0 73.5 0.5 3,935 Ondo 65.6 34.4 100.0 61.7 3.8 2,968 Osun 81.1 18.9 100.0 77.8 3.3 4,038 Oyo 77.3 22.7 100.0 76.3 0.9 6,174 Wealth quintile Lowest 41.0 59.0 100.0 37.6 3.2 37,685 Second 56.1 43.9 100.0 53.1 2.9 37,674 Middle 73.5 26.5 100.0 69.4 4.1 37,656 Fourth 84.4 15.6 100.0 80.4 3.9 37,671 Highest 71.6 28.4 100.0 69.0 2.5 37,669 Total 65.3 34.7 100.0 61.9 3.3 188,355 1 See Table 2.1.1 for definition of an improved source. 2 See Table 2.1.1 for definition of an unimproved source. 3 Defined as drinking water from an improved source, provided either water is on the premises or round-trip collection time is 30 minutes or less. Includes safely managed drinking water, which is not shown separately. 4 Drinking water from an improved source, and round-trip collection time is more than 30 minutes. Housing Characteristics and Household Population • 23 Table 2.1.3 Treatment of household drinking water Percentage of households and de jure population using various methods to treat drinking water, and percentage using an appropriate treatment method, according to residence, Nigeria DHS 2018 Households Population Water treatment method Urban Rural Total Urban Rural Total Boil 3.7 1.4 2.5 3.6 1.2 2.2 Bleach/chlorine added 2.3 0.5 1.3 2.2 0.4 1.2 Strain through cloth 1.2 2.3 1.8 1.4 2.5 2.0 Ceramic, sand, or other filter 1.0 0.7 0.8 1.0 0.7 0.9 Solar disinfection 0.1 0.0 0.1 0.1 0.0 0.1 Let stand and settle 0.5 0.7 0.6 0.5 0.6 0.6 Alum 1.5 1.6 1.6 1.4 1.4 1.4 Other 0.2 0.1 0.1 0.2 0.0 0.1 No treatment 90.0 93.5 91.9 90.1 93.7 92.1 Percentage using an appropriate treatment method1 7.0 2.5 4.6 6.9 2.3 4.3 Number of households/population 18,940 21,487 40,427 81,770 106,586 188,355 Note: Respondents may report multiple treatment methods, so the sum of treatment may exceed 100%. 1 Appropriate water treatment methods include boiling, bleaching, filtering, and solar disinfecting. 24 • Housing Characteristics and Household Population Table 2.2 Availability of water Percent distribution of households and de jure population using piped water or water from a tube well or borehole, by availability of water in the last 2 weeks, according to residence, Nigeria DHS 2018 Households Population Availability of water in last 2 weeks Urban Rural Total Urban Rural Total Not available for at least 1 day 31.2 26.6 29.2 31.4 26.5 29.2 Available with no interruption of at least 1 day 68.7 73.2 70.7 68.5 73.4 70.7 Total 100.0 100.0 100.0 100.0 100.0 100.0 Number of households/population using piped water or water from a tube well1 12,948 9,616 22,564 54,940 46,116 101,057 1 Includes households/population reporting piped water or water from a tube well or borehole as their main source of drinking water and households/ population reporting bottled water as their main source of drinking water if their main source of water for cooking and handwashing is piped water or water from a tube well or borehole Table 2.3.1 Household sanitation facilities Percent distribution of households and de jure population by type of toilet/latrine facilities, percent distribution of households and de jure population with a toilet/latrine facility by location of the facility, percentage of households and de jure population with basic sanitation services, and percentage with limited sanitation services, according to residence, Nigeria DHS 2018 Households Population Type and location of toilet/latrine facility Urban Rural Total Urban Rural Total Improved sanitation facility 74.1 39.1 55.5 73.7 37.9 53.4 Flush/pour flush to piped sewer system 6.6 1.6 3.9 6.1 1.4 3.4 Flush/pour flush to septic tank 26.6 6.2 15.8 24.1 4.9 13.2 Flush/pour flush to pit latrine 13.8 5.2 9.2 12.8 4.3 7.9 Flush/pour flush, don’t know where 0.0 0.0 0.0 0.0 0.1 0.0 Ventilated improved pit (VIP) latrine 3.5 3.5 3.5 3.5 3.7 3.6 Pit latrine with slab 23.5 22.5 23.0 27.2 23.5 25.1 Composting toilet 0.1 0.2 0.1 0.1 0.1 0.1 Unimproved facility Unimproved sanitation facility 10.5 28.4 20.0 12.6 32.2 23.7 Flush/pour flush not to sewer/septic tank/pit latrine 1.3 0.5 0.9 1.6 0.5 1.0 Pit latrine without slab/open pit 7.4 27.2 17.9 9.4 31.2 21.7 Bucket 0.2 0.2 0.2 0.2 0.1 0.1 Hanging toilet/hanging latrine 1.4 0.5 1.0 1.4 0.4 0.8 Other 0.1 0.0 0.0 0.1 0.0 0.0 Open defecation (no facility/bush/field) 15.4 32.5 24.5 13.7 29.9 22.9 Total 100.0 100.0 100.0 100.0 100.0 100.0 Number of households/population 18,940 21,487 40,427 81,770 106,586 188,355 Location of toilet facility In own dwelling 45.5 27.5 36.9 44.8 27.7 36.0 In own yard/plot 49.3 66.4 57.4 50.3 67.3 59.0 Elsewhere 5.2 6.1 5.7 4.9 5.1 5.0 Total 100.0 100.0 100.0 100.0 100.0 100.0 Number of households/population with a toilet/ latrine facility 16,014 14,500 30,515 70,587 74,670 145,257 Percentage with basic sanitation service1 47.8 37.4 42.9 51.1 38.1 44.4 Percentage with limited sanitation service2 39.6 20.5 30.5 34.1 15.9 24.8 Number of households/population 18,940 21,487 40,427 81,770 106,586 188,355 1 Defined as use of improved facilities that are not shared with other households. Includes safely managed sanitation service, which is not shown separately. 2 Defined as use of improved facilities shared by 2 or more households Housing Characteristics and Household Population • 25 Table 2.3.2 Sanitation facility type according to zone, state, and wealth Percent distribution of de jure population by type of sanitation, percentage of de jure population with basic sanitation service, and percentage with limited sanitation service, according to zone, state, and wealth quintile, Nigeria DHS 2018 Type of sanitation Total Percentage with basic sanitation service3 Percentage with limited sanitation service4 Number of persons Background characteristic Improved sanitation facility1 Unimproved sanitation facility2 Open defecation Zone North Central 42.9 5.9 51.1 100.0 24.0 18.9 25,640 North East 51.2 26.4 22.5 100.0 41.8 9.3 32,602 North West 42.5 48.2 9.3 100.0 30.9 11.6 58,840 South East 64.0 10.1 25.8 100.0 48.1 15.9 20,227 South South 64.5 13.5 22.1 100.0 37.0 27.5 20,552 South West 71.4 4.3 24.3 100.0 30.4 40.6 30,495 State North Central FCT-Abuja 68.8 1.4 29.8 100.0 41.0 27.8 1,292 Benue 43.8 14.3 41.9 100.0 33.3 10.5 5,267 Kogi 26.7 2.9 70.4 100.0 14.3 12.4 2,580 Kwara 41.6 1.9 56.5 100.0 15.3 26.3 3,265 Nasarawa 65.7 12.3 22.0 100.0 28.9 36.8 2,891 Niger 38.5 3.8 57.7 100.0 20.0 18.4 6,409 Plateau 35.6 0.4 64.0 100.0 22.3 13.2 3,936 North East Adamawa 76.5 0.8 22.8 100.0 56.0 20.4 4,118 Bauchi 30.9 59.8 9.3 100.0 26.8 4.1 7,245 Borno 66.1 24.6 9.3 100.0 49.3 16.8 6,790 Gombe 73.5 13.6 12.9 100.0 67.8 5.7 3,593 Taraba 51.7 26.2 22.1 100.0 42.3 9.4 3,905 Yobe 30.8 15.2 54.0 100.0 28.0 2.8 6,952 North West Jigawa 17.9 66.1 16.0 100.0 17.3 0.6 6,938 Kaduna 65.8 30.2 4.0 100.0 27.1 38.7 10,691 Kano 54.0 42.1 3.9 100.0 45.1 8.8 13,340 Katsina 39.3 59.0 1.7 100.0 35.1 4.3 11,449 Kebbi 22.7 46.8 30.6 100.0 9.2 13.4 5,267 Sokoto 43.5 31.0 25.5 100.0 39.1 4.4 4,755 Zamfara 27.6 66.0 6.4 100.0 26.1 1.5 6,400 South East Abia 93.1 4.9 2.0 100.0 59.6 33.5 2,607 Anambra 82.5 0.0 17.5 100.0 63.3 19.2 5,728 Ebonyi 17.2 30.2 52.6 100.0 9.9 7.3 4,248 Enugu 39.2 17.9 42.9 100.0 25.1 14.2 3,453 Imo 88.6 0.4 11.0 100.0 78.1 10.5 4,191 South South Akwa Ibom 88.3 6.9 4.8 100.0 49.2 39.1 3,867 Bayelsa 31.5 7.0 61.5 100.0 20.1 11.4 1,484 Cross River 46.5 42.1 11.4 100.0 22.8 23.7 2,360 Delta 65.6 2.4 32.0 100.0 42.3 23.3 4,286 Edo 69.8 3.5 26.7 100.0 38.6 31.3 2,712 Rivers 61.0 20.7 18.3 100.0 34.3 26.7 5,842 South West Ekiti 49.7 0.1 50.1 100.0 23.9 25.9 2,108 Lagos 87.2 6.4 6.4 100.0 41.4 44.8 11,272 Ogun 77.1 5.5 17.5 100.0 24.4 52.7 3,935 Ondo 49.6 3.4 47.1 100.0 18.0 30.7 2,968 Osun 62.4 4.3 33.3 100.0 24.9 37.4 4,038 Oyo 62.7 1.5 35.8 100.0 25.8 36.9 6,174 Wealth quintile Lowest 12.0 46.7 41.4 100.0 10.2 1.8 37,685 Second 33.2 36.7 30.1 100.0 23.6 9.7 37,674 Middle 52.5 19.9 27.6 100.0 32.6 19.9 37,656 Fourth 75.5 10.8 13.7 100.0 41.6 33.8 37,671 Highest 94.1 4.4 1.5 100.0 63.4 30.5 37,669 Total 53.4 23.7 22.9 100.0 34.3 19.1 188,355 1 See Table 2.3.1 for definition of an improved facility. 2 See Table 2.3.1 for definition of an unimproved facility. 3 Defined as use of improved facilities that are not shared with other households. Includes safely managed sanitation service, which is not shown separately. 4 Defined as use of improved facilities shared by 2 or more households 26 • Housing Characteristics and Household Population Table 2.4 Household characteristics Percent distribution of households and de jure population by housing characteristics, percentage using solid fuel for cooking, percentage using clean fuel for cooking, and percent distribution by frequency of smoking in the home, according to residence, Nigeria DHS 2018 Households Population Housing characteristic Urban Rural Total Urban Rural Total Electricity Yes 82.7 38.9 59.4 81.7 37.1 56.5 No 17.3 61.1 40.6 18.3 62.9 43.5 Total 100.0 100.0 100.0 100.0 100.0 100.0 Flooring material Earth, sand 11.5 38.3 25.8 14.0 41.8 29.7 Dung 0.2 0.5 0.4 0.2 0.4 0.3 Wood/planks 0.1 0.3 0.2 0.0 0.2 0.1 Ceramic tiles 13.1 3.9 8.2 13.1 3.6 7.7 Cement 67.7 53.6 60.2 66.2 51.5 57.9 Carpet 7.0 3.1 5.0 6.2 2.2 3.9 Other1 0.3 0.3 0.3 0.3 0.3 0.3 Total 100.0 100.0 100.0 100.0 100.0 100.0 Rooms used for sleeping One 41.4 32.3 36.6 28.5 18.8 23.0 Two 31.4 34.9 33.3 32.3 33.4 32.9 Three or more 27.2 32.8 30.2 39.1 47.8 44.0 Total 100.0 100.0 100.0 100.0 100.0 100.0 Place for cooking In the house 47.6 34.2 40.4 47.6 38.1 42.2 In a separate building 23.0 31.1 27.3 24.6 30.3 27.8 Outdoors 28.2 32.7 30.6 27.4 31.0 29.4 No food cooked in household 1.3 2.1 1.7 0.4 0.5 0.5 Other 0.0 0.0 0.0 0.0 0.0 0.0 Total 100.0 100.0 100.0 100.0 100.0 100.0 Cooking fuel Electricity 1.1 0.3 0.7 1.0 0.2 0.6 LPG/natural gas/biogas 25.7 3.7 14.0 21.6 2.4 10.8 Kerosene 24.3 6.8 15.0 19.8 4.0 10.9 Coal/lignite 1.3 0.3 0.7 1.4 0.2 0.7 Charcoal 9.3 2.6 5.8 10.5 2.2 5.8 Wood 36.8 82.6 61.1 45.0 88.5 69.6 Agricultural crop/straw/shrubs/grass 0.3 1.6 1.0 0.4 1.9 1.2 Animal dung 0.0 0.0 0.0 0.0 0.0 0.0 Other 0.0 0.0 0.0 0.0 0.0 0.0 No food cooked in household 1.3 2.1 1.7 0.4 0.5 0.5 Total 100.0 100.0 100.0 100.0 100.0 100.0 Percentage using solid fuel for cooking2 47.7 87.0 68.6 57.3 92.8 77.4 Percentage using clean fuel for cooking3 26.7 4.0 14.7 22.5 2.7 11.3 Frequency of smoking in the home Daily 6.3 7.9 7.2 6.2 7.4 6.9 Weekly 1.6 1.7 1.7 1.5 1.5 1.5 Monthly 0.1 0.1 0.1 0.1 0.1 0.1 Less than once a month 0.3 0.2 0.3 0.2 0.2 0.2 Never 91.6 90.1 90.8 91.9 90.9 91.3 Total 100.0 100.0 100.0 100.0 100.0 100.0 Number of households/population 18,940 21,487 40,427 81,770 106,586 188,355 LPG = Liquefied petroleum gas 1 Includes palm/bamboo, parquet or polished wood, and vinyl or asphalt strips 2 Includes coal/lignite, charcoal, wood, straw/shrubs/grass, agricultural crops, and animal dung 3 Includes electricity and LPG/natural gas/biogas Housing Characteristics and Household Population • 27 Table 2.5 Household possessions Percentage of households possessing various household effects, means of transportation, agricultural land, and livestock/farm animals, by residence, Nigeria DHS 2018 Residence Total Possession Urban Rural Household effects Radio 70.9 51.6 60.6 Television 70.7 30.0 49.1 Mobile telephone 94.5 82.1 87.9 Non-mobile telephone 1.0 0.4 0.7 Computer 10.8 2.5 6.4 Refrigerator 35.3 10.3 22.0 Table 75.5 50.6 62.3 Chair 88.1 74.7 81.0 Bed 95.0 93.4 94.1 Sofa 38.6 35.0 36.7 Cupboard 51.1 39.4 44.9 Air conditioner 5.7 0.9 3.1 Electric iron 51.6 16.6 33.0 Generator 39.9 18.5 28.5 Fan 75.0 30.5 51.3 Means of transport Bicycle 9.4 15.2 12.5 Animal-drawn cart 0.7 5.2 3.1 Motorcycle/scooter 21.3 32.9 27.5 Car/truck 13.9 5.2 9.3 Boat with a motor 0.5 0.7 0.6 Canoe 1.1 2.7 1.9 Keke Napep 1.2 0.6 0.9 Ownership of agricultural land 31.6 75.5 54.9 Ownership of farm animals1 26.1 56.2 42.1 Number of households 18,940 21,487 40,427 1 Cows, bulls, other cattle, horses, donkeys, goats, sheep, pigs, camel, chickens or other poultry 28 • Housing Characteristics and Household Population Table 2.6 Wealth quintiles Percent distribution of the de jure population by wealth quintiles, and the Gini coefficient, according to residence, zone, and state, Nigeria DHS 2018 Wealth quintile Total Number of persons Gini coefficient Residence/region Lowest Second Middle Fourth Highest Residence Urban 4.2 8.0 18.9 30.6 38.4 100.0 81,770 0.15 Rural 32.2 29.2 20.8 11.9 5.9 100.0 106,586 0.32 Zone North Central 15.3 24.0 25.2 21.5 14.0 100.0 25,640 0.27 North East 38.1 25.3 19.0 12.1 5.4 100.0 32,602 0.33 North West 31.9 28.9 18.5 12.1 8.5 100.0 58,840 0.33 South East 4.9 10.2 24.2 32.1 28.6 100.0 20,227 0.17 South South 2.8 10.1 23.8 30.4 32.9 100.0 20,552 0.16 South West 3.4 6.9 14.1 27.3 48.3 100.0 30,495 0.13 State North Central FCT-Abuja 5.5 13.1 17.1 22.6 41.7 100.0 1,292 0.23 Benue 17.5 27.9 28.4 15.7 10.5 100.0 5,267 0.25 Kogi 2.8 20.1 34.7 31.2 11.2 100.0 2,580 0.12 Kwara 20.2 11.2 23.1 27.0 18.5 100.0 3,265 0.23 Nasarawa 3.9 17.2 27.2 33.6 18.2 100.0 2,891 0.17 Niger 17.4 30.4 23.7 16.1 12.4 100.0 6,409 0.26 Plateau 24.5 30.1 20.3 17.6 7.5 100.0 3,936 0.31 North East Adamawa 19.4 34.7 26.3 14.3 5.3 100.0 4,118 0.21 Bauchi 45.2 26.6 17.1 8.3 2.8 100.0 7,245 0.29 Borno 19.3 18.9 26.5 21.6 13.7 100.0 6,790 0.20 Gombe 40.8 28.2 14.8 11.2 4.9 100.0 3,593 0.26 Taraba 30.3 36.1 20.9 10.2 2.6 100.0 3,905 0.25 Yobe 63.2 17.0 10.5 7.1 2.2 100.0 6,952 0.32 North West Jigawa 55.3 24.8 11.5 4.3 4.0 100.0 6,938 0.24 Kaduna 6.2 30.3 29.7 17.1 16.6 100.0 10,691 0.25 Kano 29.4 24.2 17.3 14.6 14.5 100.0 13,340 0.26 Katsina 21.6 39.5 21.7 13.3 4.0 100.0 11,449 0.21 Kebbi 36.2 36.9 17.2 8.1 1.5 100.0 5,267 0.25 Sokoto 52.0 26.4 10.9 8.2 2.4 100.0 4,755 0.28 Zamfara 54.4 17.3 11.0 11.3 6.0 100.0 6,400 0.30 South East Abia 0.0 1.5 12.8 37.5 48.2 100.0 2,607 0.01 Anambra 0.2 6.1 19.7 35.6 38.4 100.0 5,728 0.07 Ebonyi 20.1 26.5 29.8 19.5 4.2 100.0 4,248 0.19 Enugu 3.2 14.1 35.3 25.0 22.5 100.0 3,453 0.13 Imo 0.3 1.6 22.7 42.7 32.7 100.0 4,191 0.09 South South Akwa Ibom 3.8 14.9 29.7 27.1 24.4 100.0 3,867 0.17 Bayelsa 1.7 12.1 31.8 30.3 24.2 100.0 1,484 0.13 Cross River 6.8 21.6 25.7 26.2 19.8 100.0 2,360 0.16 Delta 0.8 4.2 23.3 36.9 34.8 100.0 4,286 0.09 Edo 4.2 9.9 31.4 27.4 27.1 100.0 2,712 0.16 Rivers 1.8 6.4 13.8 30.9 47.2 100.0 5,842 0.11 South West Ekiti 12.0 13.0 24.4 29.7 20.9 100.0 2,108 0.21 Lagos 0.0 0.7 2.6 21.7 75.0 100.0 11,272 0.02 Ogun 1.0 7.0 16.0 26.7 49.4 100.0 3,935 0.14 Ondo 5.1 16.1 27.8 27.5 23.5 100.0 2,968 0.17 Osun 7.9 13.3 24.7 33.9 20.2 100.0 4,038 0.12 Oyo 4.3 7.5 17.0 32.7 38.5 100.0 6,174 0.13 Total 20.0 20.0 20.0 20.0 20.0 100.0 188,355 0.25 Housing Characteristics and Household Population • 29 Table 2.7 Handwashing Percentage of the de jure population for whom the place most often used for washing hands was observed, by whether the location was fixed or mobile; total percentage of the de jure population for whom the place for handwashing was observed; among the de jure population for whom the place for handwashing was observed, percentage with water available, percentage with soap available, and percentage with a cleansing agent other than soap available; percentage of the de jure population with a basic handwashing facility; and percentage with a limited handwashing facility, according to background characteristics, Nigeria DHS 2018 Percentage of de jure population for whom place for washing hands was observed: Number of persons Place for handwashing observed and: Number of persons for whom place for hand- washing was observed Percentage of de jure population with a basic hand- washing facility3 Percentage of de jure population with a limited hand- washing facility4 Number of persons for whom a place for hand- washing was observed or with no place for hand- washing in the dwelling, yard, or plot Background characteristic Place for hand- washing was a fixed place Place for hand- washing was mobile Total Water available Soap available1 Cleansing agent other than soap available2 Residence Urban 28.3 55.7 83.9 81,770 72.4 49.9 1.6 68,644 42.7 44.4 76,326 Rural 25.4 53.4 78.8 106,586 56.0 27.4 1.0 84,034 22.5 62.7 96,294 Zone North Central 9.3 75.4 84.7 25,640 47.8 17.8 0.9 21,719 14.4 70.4 25,105 North East 37.5 35.6 73.1 32,602 44.0 12.1 1.3 23,818 8.1 71.9 28,842 North West 32.1 49.9 82.0 58,840 58.7 31.2 1.4 48,237 28.0 64.7 50,481 South East 16.3 73.0 89.3 20,227 78.8 58.6 0.1 18,060 52.8 37.5 19,911 South South 19.0 45.2 64.2 20,552 74.6 60.9 0.1 13,197 41.4 28.7 17,992 South West 31.3 59.3 90.7 30,495 84.9 61.0 2.6 27,648 53.4 34.9 30,290 State North Central FCT-Abuja 17.8 65.6 83.3 1,292 72.7 44.6 0.0 1,077 36.0 46.3 1,288 Benue 1.1 98.8 100.0 5,267 1.9 1.4 0.0 5,266 1.2 98.6 5,267 Kogi 4.6 65.4 70.0 2,580 82.1 61.7 0.6 1,806 44.1 32.5 2,096 Kwara 2.9 90.9 93.8 3,265 48.1 4.7 0.7 3,062 4.3 88.8 3,265 Nasarawa 46.1 53.8 99.9 2,891 48.9 23.5 0.8 2,888 23.1 75.7 2,889 Niger 0.9 56.6 57.5 6,409 86.4 11.0 0.9 3,686 6.2 51.0 6,366 Plateau 12.4 87.5 99.9 3,936 49.6 24.5 2.8 3,933 24.2 72.8 3,933 North East Adamawa 52.9 34.7 87.6 4,118 39.4 3.3 1.6 3,609 2.9 84.4 4,061 Bauchi 59.6 36.7 96.4 7,245 11.8 5.5 0.2 6,982 3.9 93.4 7,066 Borno 22.6 29.1 51.7 6,790 54.7 11.0 3.2 3,511 5.6 45.2 6,734 Gombe 0.9 53.2 54.1 3,593 90.7 47.3 2.9 1,945 45.0 52.1 1,950 Taraba 1.6 30.2 31.8 3,905 96.6 9.9 4.8 1,241 5.2 50.7 2,115 Yobe 58.9 35.1 93.9 6,952 51.3 14.5 0.3 6,529 8.2 80.5 6,916 North West Jigawa 43.1 56.8 99.9 6,938 43.9 5.0 0.0 6,928 4.1 94.9 6,938 Kaduna 17.5 82.4 99.9 10,691 53.9 5.4 1.3 10,679 5.1 93.5 10,691 Kano 21.5 45.7 67.2 13,340 49.2 33.5 1.9 8,969 23.9 54.5 10,728 Katsina 86.5 11.7 98.2 11,449 96.8 92.9 2.2 11,245 90.2 5.1 11,434 Kebbi 1.8 52.7 54.5 5,267 70.4 2.1 2.0 2,870 2.0 94.2 2,925 Sokoto 2.7 22.6 25.2 4,755 93.4 4.5 0.9 1,201 3.9 83.8 1,368 Zamfara 15.8 83.4 99.1 6,400 17.1 9.1 1.1 6,345 4.8 89.6 6,398 South East Abia 53.6 46.3 99.9 2,607 97.6 77.0 0.1 2,604 75.7 22.9 2,607 Anambra 11.4 88.6 100.0 5,728 99.8 96.7 0.0 5,728 96.7 3.3 5,728 Ebonyi 4.3 55.5 59.8 4,248 15.1 10.9 0.6 2,539 5.9 53.7 4,203 Enugu 10.0 88.9 98.9 3,453 55.4 25.7 0.0 3,416 25.3 73.5 3,453 Imo 17.2 72.8 90.0 4,191 98.1 49.9 0.1 3,774 47.9 48.1 3,921 South South Akwa Ibom 9.3 24.4 33.7 3,867 36.1 32.2 0.5 1,304 10.4 23.7 3,730 Bayelsa 4.5 94.7 99.2 1,484 89.5 14.6 0.0 1,472 14.1 84.8 1,483 Cross River 63.6 35.4 99.0 2,360 89.3 66.5 0.0 2,337 62.6 33.3 2,355 Delta 12.5 38.9 51.4 4,286 77.0 71.4 0.3 2,204 60.4 28.1 2,242 Edo 10.6 66.6 77.3 2,712 45.4 40.9 0.0 2,095 31.4 50.7 2,444 Rivers 19.8 45.0 64.8 5,842 87.7 90.2 0.0 3,786 56.6 6.5 5,739 South West Ekiti 18.3 41.4 59.7 2,108 50.5 31.6 50.0 1,259 16.5 31.6 2,104 Lagos 35.9 61.2 97.1 11,272 94.9 63.2 0.7 10,945 61.4 35.9 11,192 Ogun 12.9 86.3 99.2 3,935 97.9 34.5 0.0 3,902 34.3 65.3 3,913 Ondo 2.9 48.2 51.1 2,968 6.1 6.2 0.2 1,517 2.9 48.5 2,942 Osun 47.6 50.9 98.5 4,038 98.6 94.4 0.0 3,977 93.6 5.5 4,013 Oyo 42.2 55.8 98.0 6,174 76.2 71.9 0.0 6,048 61.7 27.7 6,125 Continued. 30 • Housing Characteristics and Household Population Table 2.7—Continued Percentage of de jure population for whom place for washing hands was observed: Number of persons Place for handwashing observed and: Number of persons for whom place for hand- washing was observed Percentage of de jure population with a basic hand- washing facility3 Percentage of de jure population with a limited hand- washing facility4 Number of persons for whom a place for hand- washing was observed or with no place for hand- washing in the dwelling, yard, or plot Background characteristic Place for hand- washing was a fixed place Place for hand- washing was mobile Total Water available Soap available1 Cleansing agent other than soap available2 Wealth quintile Lowest 24.9 52.6 77.5 37,685 40.5 12.6 1.6 29,199 9.9 75.9 33,184 Second 24.6 53.3 77.9 37,674 55.2 25.5 1.7 29,361 20.5 63.9 33,771 Middle 21.6 57.2 78.8 37,656 59.2 31.2 1.5 29,678 24.6 58.1 34,775 Fourth 21.5 61.0 82.5 37,671 71.1 45.3 1.2 31,064 37.8 47.8 35,093 Highest 40.7 47.9 88.6 37,669 86.9 68.3 0.5 33,377 61.9 29.3 35,797 Total 26.7 54.4 81.1 188,355 63.4 37.5 1.3 152,679 31.4 54.6 172,620 1 Soap includes soap or detergent in bar, liquid, powder, or paste form. 2 Cleansing agents other than soap include locally available materials such as ash, mud, or sand. 3 The availability of a handwashing facility on premises with soap and water 4 The availability of a handwashing facility on premises without soap and/or water Housing Characteristics and Household Population • 31 Table 2.8 Household population by age, sex, and residence Percent distribution of the de facto household population by various age groups and percentage of the de facto household population age 10-19, according to sex and residence, Nigeria DHS 2018 Urban Rural Male Female Total Age Male Female Total Male Female Total <5 16.1 14.7 15.4 18.7 17.7 18.2 17.6 16.4 17.0 5-9 15.7 14.8 15.2 18.3 17.2 17.8 17.2 16.2 16.7 10-14 12.3 11.9 12.1 12.8 12.1 12.5 12.6 12.0 12.3 15-19 8.9 9.4 9.1 8.8 8.9 8.9 8.8 9.1 9.0 20-24 5.8 7.2 6.5 5.5 7.7 6.6 5.7 7.5 6.6 25-29 5.8 8.4 7.1 5.8 8.0 6.9 5.8 8.2 7.0 30-34 6.5 7.5 7.0 5.4 6.1 5.8 5.9 6.7 6.3 35-39 6.6 6.6 6.6 5.2 5.3 5.3 5.8 5.9 5.8 40-44 5.3 4.3 4.8 4.2 3.9 4.1 4.7 4.1 4.4 45-49 4.2 3.8 4.0 3.4 3.2 3.3 3.8 3.5 3.6 50-54 3.1 3.3 3.2 2.8 3.2 3.0 2.9 3.2 3.1 55-59 2.6 2.4 2.5 2.0 2.1 2.1 2.3 2.2 2.2 60-64 2.4 1.9 2.1 2.3 1.5 1.9 2.4 1.6 2.0 65-69 1.6 1.4 1.5 1.7 1.1 1.4 1.6 1.2 1.4 70-74 1.5 1.0 1.2 1.2 0.8 1.0 1.4 0.9 1.1 75-79 0.7 0.5 0.6 0.7 0.5 0.6 0.7 0.5 0.6 80+ 0.8 0.8 0.8 0.9 0.6 0.7 0.8 0.7 0.8 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Dependency age groups 0-14 44.1 41.4 42.7 49.8 47.1 48.5 47.4 44.6 46.0 15-64 51.2 54.8 53.0 45.6 50.0 47.8 48.0 52.1 50.1 65+ 4.6 3.7 4.2 4.5 2.9 3.7 4.6 3.3 3.9 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Child and adult populations 0-17 49.6 47.1 48.4 55.7 52.6 54.1 53.1 50.2 51.6 18+ 50.3 52.8 51.6 44.3 47.4 45.9 46.9 49.8 48.4 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Adolescents 10-19 21.2 21.3 21.2 21.6 21.1 21.3 21.4 21.2 21.3 Number of persons 40,176 41,511 81,686 52,495 53,793 106,288 92,670 95,304 187,974 32 • Housing Characteristics and Household Population Table 2.9 Household composition Percent distribution of households by sex of head of household and by household size, mean size of household, and percentage of households with orphans and foster children under age 18, according to residence, Nigeria DHS 2018 Residence Total Characteristic Urban Rural Household headship Male 78.2 85.3 82.0 Female 21.8 14.7 18.0 Total 100.0 100.0 100.0 Number of usual members 0 0.0 0.1 0.1 1 16.4 13.3 14.7 2 12.2 11.3 11.7 3 15.0 13.3 14.1 4 16.1 13.5 14.7 5 13.7 12.2 12.9 6 9.6 10.5 10.1 7 6.3 7.4 6.9 8 3.7 5.6 4.7 9+ 7.0 12.7 10.0 Total 100.0 100.0 100.0 Mean size of households 4.3 5.0 4.7 Percentage of households with orphans and foster children under age 18 Double orphans 0.7 0.8 0.7 Single orphans1 7.2 7.4 7.3 Foster children2 12.9 13.6 13.2 Foster and/or orphan children 17.2 17.9 17.6 Number of households 18,940 21,487 40,427 Note: Table is based on de jure household members, i.e., usual residents. 1 Includes children with one dead parent and an unknown survival status of the other parent 2 Foster children are those under age 18 living in households with neither their mother nor their father present, and the mother and/or the father are alive. Housing Characteristics and Household Population • 33 Table 2.10 Children’s living arrangements and orphanhood Percent distribution of de jure children under age 18 by living arrangements and survival status of parents, percentage of children not living with a biological parent, and percentage of children with one or both parents dead, according to background characteristics, Nigeria DHS 2018 Living with both parents Living with mother but not with father Living with father but not with mother Not living with either parent Total Percent- age not living with a biolo- gical parent Percent- age with one or both parents dead1 Number of children Background characteristic Father alive Father dead Mother alive Mother dead Both alive Only father alive Only mother alive Both dead Age 0-4 83.0 9.2 1.3 2.3 0.4 3.2 0.3 0.2 0.1 100.0 3.8 2.3 31,785 <2 85.6 10.7 0.8 1.1 0.3 1.2 0.2 0.1 0.0 100.0 1.5 1.4 11,733 2-4 81.5 8.4 1.6 3.0 0.4 4.3 0.3 0.2 0.2 100.0 5.1 2.8 20,053 5-9 76.6 7.4 2.7 4.9 1.0 5.9 0.5 0.8 0.3 100.0 7.4 5.2 31,311 10-14 70.6 7.0 4.9 5.7 1.6 7.5 0.6 1.4 0.5 100.0 10.1 9.1 23,129 15-17 59.2 6.1 6.7 5.5 2.3 15.3 1.1 2.4 1.4 100.0 20.2 13.9 10,622 Sex Male 76.5 7.6 3.2 4.7 1.1 5.2 0.4 0.9 0.3 100.0 6.8 6.0 49,137 Female 74.2 8.0 3.2 3.9 1.0 7.7 0.6 0.9 0.5 100.0 9.7 6.3 47,710 Residence Urban 71.7 10.1 3.9 4.1 1.0 7.1 0.6 1.0 0.4 100.0 9.1 7.0 39,399 Rural 77.9 6.2 2.7 4.4 1.1 5.9 0.5 0.9 0.4 100.0 7.7 5.6 57,448 Zone North Central 72.7 8.7 3.6 4.5 0.7 7.8 0.5 1.2 0.4 100.0 9.9 6.4 12,828 North East 78.9 3.4 3.3 4.1 1.6 6.3 0.7 1.0 0.6 100.0 8.6 7.2 18,315 North West 83.7 3.8 2.0 4.2 1.3 3.7 0.4 0.6 0.2 100.0 4.9 4.6 33,822 South East 65.6 13.3 6.4 2.6 0.6 9.2 0.5 1.2 0.5 100.0 11.5 9.2 9,499 South South 61.2 16.1 4.4 6.0 0.6 8.4 0.9 1.5 0.9 100.0 11.7 8.3 9,218 South West 68.4 13.3 2.5 4.7 0.8 8.8 0.5 0.6 0.3 100.0 10.2 4.7 13,166 State North Central FCT-Abuja 75.2 7.2 3.1 5.9 0.7 6.0 0.8 1.0 0.1 100.0 8.0 5.7 639 Benue 62.3 12.6 7.1 4.3 0.4 10.1 0.5 1.6 1.1 100.0 13.3 10.7 2,512 Kogi 53.3 20.0 4.0 5.6 0.8 11.9 0.9 2.7 0.8 100.0 16.2 9.2 1,206 Kwara 65.9 12.9 2.7 3.1 0.2 13.1 0.7 1.3 0.0 100.0 15.2 4.9 1,672 Nasarawa 79.0 4.6 3.1 4.9 1.3 4.6 0.4 1.5 0.5 100.0 7.0 6.9 1,426 Niger 90.0 1.5 1.2 3.4 0.7 2.5 0.2 0.3 0.1 100.0 3.2 2.5 3,431 Plateau 67.9 9.1 4.4 6.2 0.7 9.9 0.4 1.3 0.2 100.0 11.7 6.9 1,943 North East Adamawa 78.2 6.6 2.5 4.2 1.3 5.5 0.2 0.3 1.3 100.0 7.3 5.6 2,116 Bauchi 83.2 2.0 1.6 4.9 2.1 4.1 0.4 1.1 0.4 100.0 6.0 5.7 4,270 Borno 80.1 3.0 5.3 3.1 1.6 4.2 0.9 1.2 0.6 100.0 6.9 9.6 3,730 Gombe 80.0 3.1 2.3 4.7 2.6 5.4 0.5 1.0 0.3 100.0 7.2 6.8 2,034 Taraba 69.3 7.8 3.2 5.3 1.8 9.5 1.1 1.6 0.4 100.0 12.6 8.0 2,120 Yobe 78.3 1.4 4.4 3.3 0.7 9.7 0.8 0.9 0.6 100.0 11.9 7.3 4,044 North West Jigawa 84.0 1.8 1.6 5.5 1.5 4.1 0.6 0.6 0.3 100.0 5.7 4.6 4,047 Kaduna 86.2 2.4 1.7 4.0 2.0 3.1 0.1 0.4 0.2 100.0 3.9 4.4 5,923 Kano 76.6 9.6 1.9 5.5 1.3 3.9 0.4 0.7 0.2 100.0 5.1 4.4 7,713 Katsina 84.8 2.2 2.8 3.7 0.7 4.1 0.6 0.9 0.2 100.0 5.8 5.3 6,743 Kebbi 82.6 4.5 2.5 4.0 2.0 3.3 0.4 0.6 0.1 100.0 4.4 5.5 3,040 Sokoto 89.3 0.8 2.4 2.6 1.2 3.1 0.1 0.3 0.2 100.0 3.6 4.1 2,703 Zamfara 89.4 1.1 1.1 2.5 0.9 3.7 0.6 0.5 0.2 100.0 5.0 3.3 3,653 South East Abia 70.7 9.1 4.8 2.7 0.7 9.1 0.6 1.7 0.6 100.0 12.1 8.4 1,114 Anambra 75.0 11.3 4.5 0.9 0.3 6.6 0.3 0.8 0.2 100.0 8.0 6.2 2,672 Ebonyi 65.0 12.1 8.0 2.4 0.5 10.6 0.3 0.8 0.3 100.0 12.0 9.9 2,360 Enugu 59.0 16.1 7.9 3.0 0.3 11.1 0.5 1.6 0.2 100.0 13.4 10.6 1,504 Imo 55.3 17.7 6.7 4.9 1.2 9.8 1.0 1.8 1.3 100.0 14.0 12.1 1,849 South South Akwa Ibom 57.7 14.1 8.4 4.1 0.8 10.9 0.9 1.7 1.4 100.0 14.9 13.2 1,661 Bayelsa 54.4 21.1 2.4 8.8 0.7 10.4 0.5 1.4 0.2 100.0 12.5 5.2 706 Cross River 57.5 21.8 3.8 6.0 0.2 7.9 0.4 2.0 0.4 100.0 10.7 6.8 1,020 Delta 66.0 12.4 3.0 9.2 0.7 6.5 0.3 1.1 0.8 100.0 8.7 5.9 1,907 Edo 60.4 16.4 4.7 6.4 1.1 7.9 1.3 0.9 1.0 100.0 11.0 9.0 1,309 Rivers 63.4 16.3 3.6 3.9 0.4 8.3 1.3 1.9 0.8 100.0 12.3 8.0 2,614 South West Ekiti 60.2 20.2 2.2 4.6 0.7 11.2 0.2 0.7 0.0 100.0 12.1 3.8 906 Lagos 72.4 9.8 3.0 5.0 1.3 6.8 0.7 0.6 0.4 100.0 8.4 6.0 4,768 Ogun 72.4 11.0 3.5 4.5 0.6 6.1 0.3 0.9 0.8 100.0 8.1 6.0 1,745 Ondo 62.1 17.1 3.5 4.1 1.0 9.5 1.0 1.3 0.3 100.0 12.2 7.2 1,294 Osun 67.2 12.9 2.0 3.5 0.3 13.2 0.3 0.5 0.1 100.0 14.1 3.2 1,702 Oyo 65.7 17.0 0.9 5.4 0.4 10.1 0.3 0.2 0.0 100.0 10.6 1.8 2,751 Continued. 34 • Housing Characteristics and Household Population Table 2.10—Continued Living with both parents Living with mother but not with father Living with father but not with mother Not living with either parent Total Percent- age not living with a biolo- gical parent Percent- age with one or both parents dead1 Number of children Background characteristic Father alive Father dead Mother alive Mother dead Both alive Only father alive Only mother alive Both dead Wealth quintile Lowest 81.1 4.5 2.3 4.0 1.2 5.5 0.4 0.6 0.3 100.0 6.8 4.9 21,443 Second 77.2 6.1 3.6 4.1 1.3 5.9 0.4 0.8 0.5 100.0 7.6 6.6 20,698 Middle 72.4 9.0 4.2 4.6 0.9 6.7 0.6 1.2 0.5 100.0 9.0 7.3 19,593 Fourth 71.9 10.3 3.4 4.5 1.2 6.9 0.5 0.9 0.4 100.0 8.6 6.4 18,310 Highest 73.0 9.8 2.5 4.3 0.8 7.3 0.8 1.2 0.4 100.0 9.7 5.6 16,802 Total <15 77.4 8.0 2.8 4.1 0.9 5.3 0.5 0.7 0.3 100.0 6.8 5.2 86,225 Total <18 75.4 7.8 3.2 4.3 1.1 6.4 0.5 0.9 0.4 100.0 8.3 6.1 96,847 Note: Table is based on de jure members, i.e., usual residents. 1 Includes children with father dead, mother dead, both dead, and one parent dead but missing information on survival status of the other parent Housing Characteristics and Household Population • 35 Table 2.11 Birth registration of children under age 5 Percentage of de jure children under age 5 whose births are registered with the civil authorities, according to background characteristics, Nigeria DHS 2018 Percentage of children whose births are registered and who: Number of children Background characteristic Had a birth certificate Did not have a birth certificate Total percentage of children whose births are registered Age <2 20.5 18.3 38.8 11,733 2-4 22.7 22.0 44.8 20,053 Sex Male 22.5 20.9 43.4 16,233 Female 21.3 20.4 41.7 15,552 Residence Urban 30.6 29.0 59.6 12,482 Rural 16.3 15.2 31.5 19,304 Zone North Central 18.3 15.2 33.5 4,336 North East 16.9 18.9 35.9 5,837 North West 20.6 14.5 35.1 11,230 South East 23.1 35.9 59.0 3,278 South South 23.6 26.4 50.0 2,882 South West 33.9 29.2 63.1 4,222 State North Central FCT-Abuja 35.4 32.2 67.5 214 Benue 16.9 22.2 39.1 918 Kogi 21.0 21.4 42.4 376 Kwara 17.5 24.2 41.7 515 Nasarawa 38.1 19.8 57.9 486 Niger 11.5 5.6 17.1 1,226 Plateau 11.1 2.7 13.9 601 North East Adamawa 33.6 29.5 63.1 755 Bauchi 14.3 26.6 40.8 1,379 Borno 16.9 9.0 25.9 1,141 Gombe 14.1 18.7 32.8 636 Taraba 13.2 16.1 29.3 722 Yobe 13.3 14.7 28.0 1,202 North West Jigawa 17.6 8.7 26.3 1,318 Kaduna 30.3 14.3 44.6 2,085 Kano 9.5 27.1 36.7 2,467 Katsina 48.2 10.5 58.6 2,203 Kebbi 10.3 17.8 28.1 1,032 Sokoto 0.8 6.1 6.9 916 Zamfara 3.2 6.5 9.7 1,209 South East Abia 9.5 65.4 74.9 398 Anambra 41.9 16.1 58.0 983 Ebonyi 18.1 10.5 28.5 808 Enugu 7.8 61.4 69.2 462 Imo 20.2 62.3 82.5 626 South South Akwa Ibom 18.8 27.9 46.7 510 Bayelsa 11.4 20.3 31.7 218 Cross River 16.9 39.3 56.2 302 Delta 22.5 31.9 54.4 582 Edo 35.0 24.5 59.5 395 Rivers 27.4 19.7 47.1 875 South West Ekiti 42.1 27.5 69.6 297 Lagos 19.1 50.5 69.7 1,458 Ogun 32.8 13.4 46.2 580 Ondo 35.5 18.3 53.8 389 Osun 18.0 33.9 51.9 557 Oyo 63.6 8.1 71.7 941 Wealth quintile Lowest 7.5 8.3 15.9 6,952 Second 14.1 13.9 28.0 7,050 Middle 23.1 20.3 43.4 6,521 Fourth 31.8 29.4 61.2 5,865 Highest 38.5 36.3 74.8 5,398 Total 21.9 20.7 42.6 31,785 36 • Housing Characteristics and Household Population Table 2.12 Birth registration of children under age 5 by authority Among de jure children under age 5 whose births are registered with the civil authorities, percent distribution of children by authority with which the birth is registered, according to background characteristics, Nigeria DHS 2018 Authority with which birth is registered Total Number of children Background characteristic National Population Commission Local government administration Private clinic/hospital Other Age <2 61.3 8.2 27.9 2.6 100.0 4,554 2-4 62.8 10.2 24.5 2.5 100.0 8,975 Sex Male 62.0 9.9 25.4 2.7 100.0 7,039 Female 62.6 9.1 25.9 2.4 100.0 6,490 Residence Urban 64.1 8.2 25.3 2.3 100.0 7,445 Rural 60.0 11.1 26.0 2.8 100.0 6,084 Zone North Central 52.9 10.9 31.0 5.2 100.0 1,453 North East 58.5 5.2 32.4 3.9 100.0 2,092 North West 55.8 16.6 26.9 0.7 100.0 3,943 South East 64.7 1.7 31.0 2.6 100.0 1,935 South South 75.7 3.8 17.7 2.9 100.0 1,441 South West 71.0 10.4 15.9 2.7 100.0 2,664 State North Central FCT-Abuja 94.5 5.2 0.2 0.1 100.0 145 Benue 21.7 7.2 63.4 7.6 100.0 359 Kogi 69.3 11.5 15.8 3.5 100.0 159 Kwara 72.0 17.0 1.4 9.5 100.0 215 Nasarawa 52.9 1.1 39.1 7.0 100.0 282 Niger 33.0 26.9 40.1 0.0 100.0 210 Plateau 84.0 12.4 0.6 3.0 100.0 84 North East Adamawa 19.9 2.9 65.3 11.8 100.0 477 Bauchi 77.4 9.1 12.8 0.6 100.0 563 Borno 92.6 6.6 0.0 0.8 100.0 296 Gombe 65.7 3.5 29.5 1.3 100.0 209 Taraba 43.6 5.6 43.2 7.6 100.0 212 Yobe 56.6 1.5 41.8 0.0 100.0 337 North West Jigawa 37.0 47.9 15.1 0.0 100.0 347 Kaduna 36.4 17.5 46.0 0.1 100.0 930 Kano 41.7 11.1 46.4 0.8 100.0 905 Katsina 79.8 13.9 6.3 0.0 100.0 1,292 Kebbi 91.4 7.2 1.4 0.0 100.0 289 Sokoto 31.9 25.4 42.8 0.0 100.0 63 Zamfara 34.4 8.2 42.2 15.2 100.0 118 South East Abia 80.1 5.5 13.8 0.7 100.0 298 Anambra 85.9 0.7 13.4 0.0 100.0 570 Ebonyi 85.8 0.8 9.8 3.6 100.0 231 Enugu 58.3 3.3 30.6 7.9 100.0 320 Imo 27.1 0.1 70.1 2.7 100.0 517 South South Akwa Ibom 55.2 4.7 36.8 3.3 100.0 238 Bayelsa 63.5 10.9 3.5 22.1 100.0 69 Cross River 63.4 2.2 33.8 0.6 100.0 170 Delta 98.6 1.1 0.3 0.0 100.0 317 Edo 71.3 2.3 25.0 1.4 100.0 235 Rivers 79.4 5.6 11.6 3.4 100.0 412 South West Ekiti 91.3 0.7 6.5 1.6 100.0 207 Lagos 69.9 19.0 9.4 1.6 100.0 1,016 Ogun 92.8 1.2 3.1 2.9 100.0 268 Ondo 72.8 10.4 3.9 13.0 100.0 209 Osun 45.7 13.6 39.1 1.6 100.0 289 Oyo 68.1 2.8 27.3 1.8 100.0 675 Wealth quintile Lowest 47.9 20.2 26.9 4.9 100.0 1,102 Second 58.0 11.9 27.6 2.5 100.0 1,973 Middle 59.6 9.8 27.9 2.7 100.0 2,829 Fourth 63.3 7.4 27.3 2.0 100.0 3,589 Highest 69.3 7.1 21.2 2.4 100.0 4,035 Total 62.3 9.5 25.6 2.6 100.0 13,529 Housing Characteristics and Household Population • 37 Table 2.13.1 Educational attainment of the female household population Percent distribution of the de facto female household population age 6 and over by highest level of schooling attended or completed and median years completed, according to background characteristics, Nigeria DHS 2018 Background characteristic No education Some primary Completed primary1 Some secondary Completed secondary2 More than secondary Total Number Median years completed Age 6-9 39.6 59.0 0.9 0.5 0.0 0.0 100.0 12,057 0.3 10-14 24.3 37.6 12.0 25.7 0.4 0.0 100.0 11,468 3.8 15-19 24.1 4.1 8.2 40.5 20.6 2.5 100.0 8,719 8.3 20-24 30.8 2.6 9.3 11.3 34.2 12.0 100.0 7,139 9.4 25-29 32.5 2.3 11.8 8.3 31.0 14.0 100.0 7,798 8.4 30-34 33.8 2.4 13.7 7.5 26.2 16.4 100.0 6,403 6.2 35-39 35.2 3.1 16.4 7.2 24.3 13.7 100.0 5,584 5.7 40-44 39.6 3.5 19.4 7.0 18.8 11.6 100.0 3,918 5.4 45-49 37.4 5.6 22.2 6.5 17.7 10.5 100.0 3,290 5.3 50-54 54.0 4.2 16.2 3.4 13.7 8.4 100.0 3,096 0.0 55-59 54.5 4.9 19.0 2.8 9.9 8.9 100.0 2,132 0.0 60-64 65.9 5.7 17.4 1.3 4.4 5.2 100.0 1,570 0.0 65+ 73.3 6.3 12.5 1.2 4.1 2.7 100.0 3,123 0.0 Residence Urban 20.0 17.8 11.8 15.5 22.7 12.1 100.0 34,071 6.0 Rural 48.9 17.2 10.9 10.2 9.8 3.0 100.0 42,236 0.1 Zone North Central 35.7 18.4 11.5 14.4 13.1 7.0 100.0 10,297 3.6 North East 57.2 16.3 7.4 8.1 7.3 3.7 100.0 12,726 0.0 North West 54.7 17.8 8.9 8.5 7.3 2.7 100.0 22,912 0.0 South East 14.2 19.9 15.5 17.2 23.6 9.5 100.0 8,958 6.1 South South 11.2 17.1 14.8 19.2 27.3 10.5 100.0 8,625 8.0 South West 13.5 15.8 14.3 15.0 27.1 14.3 100.0 12,789 8.2 North Central FCT-Abuja 24.0 13.3 15.8 13.0 20.4 13.6 100.0 512 5.8 Benue 24.0 24.7 10.7 20.6 12.7 7.2 100.0 2,150 5.1 Kogi 24.6 17.3 16.5 14.0 20.9 6.7 100.0 1,142 5.5 Kwara 38.2 16.5 13.2 11.0 12.4 8.8 100.0 1,348 3.1 Nasarawa 30.0 18.5 10.8 18.5 14.2 8.0 100.0 1,110 5.1 Niger 63.5 11.8 4.9 7.3 8.4 4.1 100.0 2,386 0.0 Plateau 23.7 23.6 16.1 17.3 12.5 6.9 100.0 1,650 5.2 North East Adamawa 51.2 14.5 7.5 8.6 14.1 4.1 100.0 1,612 0.0 Bauchi 57.1 18.8 10.2 8.0 4.3 1.6 100.0 2,747 0.0 Borno 52.9 15.8 6.5 9.1 8.6 7.1 100.0 2,791 0.0 Gombe 61.6 14.5 6.9 7.1 7.1 2.7 100.0 1,348 0.0 Taraba 40.2 23.6 10.0 12.2 8.9 5.0 100.0 1,589 1.5 Yobe 73.7 11.7 3.8 4.7 4.2 1.8 100.0 2,640 0.0 North West Jigawa 56.9 19.9 10.1 7.5 4.8 0.8 100.0 2,729 0.0 Kaduna 41.2 18.9 9.5 12.4 12.5 5.5 100.0 4,141 1.7 Kano 45.5 22.3 8.9 10.5 8.0 4.7 100.0 5,271 0.2 Katsina 45.7 22.4 13.5 9.6 7.7 1.1 100.0 4,476 0.6 Kebbi 78.9 7.0 6.8 3.0 4.0 0.4 100.0 2,014 0.0 Sokoto 81.6 9.4 4.0 2.5 1.7 0.9 100.0 1,789 0.0 Zamfara 71.8 10.6 3.3 5.9 6.3 2.1 100.0 2,492 0.0 South East Abia 8.9 18.4 15.5 16.5 29.1 11.4 100.0 1,130 8.4 Anambra 10.2 19.9 16.3 18.0 26.5 9.1 100.0 2,562 7.3 Ebonyi 23.4 24.1 19.5 16.9 13.1 3.0 100.0 1,875 5.1 Enugu 17.2 19.4 13.8 16.8 22.0 10.8 100.0 1,599 6.0 Imo 11.1 17.1 11.5 17.1 28.6 14.6 100.0 1,793 9.6 South South Akwa Ibom 13.5 16.8 13.7 19.8 23.6 12.5 100.0 1,705 7.6 Bayelsa 10.2 21.2 16.7 20.5 24.9 6.4 100.0 595 6.5 Cross River 14.2 16.3 14.3 25.2 19.2 10.8 100.0 996 7.2 Delta 9.7 17.3 18.0 17.1 27.4 10.6 100.0 1,762 7.7 Edo 15.6 21.0 16.5 20.1 18.3 8.3 100.0 1,141 5.8 Rivers 7.5 14.6 12.1 17.0 37.9 10.8 100.0 2,426 10.7 South West Ekiti 12.3 17.9 13.7 19.0 23.5 13.5 100.0 890 7.9 Lagos 7.1 14.8 12.7 14.2 32.7 18.5 100.0 4,723 11.0 Ogun 16.6 16.9 17.6 13.4 22.4 13.2 100.0 1,659 5.9 Ondo 13.8 19.9 14.5 20.8 21.8 9.2 100.0 1,266 6.3 Osun 17.4 13.9 15.7 15.3 27.5 10.3 100.0 1,729 7.3 Oyo 21.2 15.2 14.2 13.2 23.1 12.9 100.0 2,521 6.0 Continued. 38 • Housing Characteristics and Household Population Table 2.13.1—Continued Background characteristic No education Some primary Completed primary1 Some secondary Completed secondary2 More than secondary Total Number Median years completed Wealth quintile Lowest 75.4 12.4 6.5 3.7 1.9 0.2 100.0 14,635 0.0 Second 52.1 19.3 12.0 9.9 5.9 0.7 100.0 15,002 0.0 Middle 31.8 21.0 14.7 15.5 14.4 2.6 100.0 15,409 4.1 Fourth 16.7 19.1 14.3 17.9 25.1 6.9 100.0 15,601 6.0 Highest 7.1 15.2 8.8 15.2 29.3 24.3 100.0 15,660 11.1 Total 36.0 17.5 11.3 12.6 15.6 7.1 100.0 76,307 3.6 Note: Total includes 12 cases with missing information on age. 1 Completed grade 6 at the primary level 2 Completed grade 6 at the secondary level Housing Characteristics and Household Population • 39 Table 2.13.2 Educational attainment of the male household population Percent distribution of the de facto male household population age 6 and over by highest level of schooling attended or completed and median years completed, according to background characteristics, Nigeria DHS 2018 Background characteristic No education Some primary Completed primary1 Some secondary Completed secondary2 More than secondary Total Number Median years completed Age 6-9 39.0 59.4 1.0 0.5 0.1 0.0 100.0 12,529 0.3 10-14 20.4 41.8 11.7 25.6 0.4 0.0 100.0 11,661 3.9 15-19 19.4 5.0 6.6 47.6 18.7 2.8 100.0 8,188 8.4 20-24 17.6 2.0 6.6 13.5 41.5 18.8 100.0 5,240 11.2 25-29 20.3 2.0 8.2 8.2 37.6 23.7 100.0 5,400 11.3 30-34 19.9 2.0 10.7 6.3 36.0 24.9 100.0 5,460 11.3 35-39 20.9 2.3 12.8 6.3 34.5 23.1 100.0 5,384 11.2 40-44 23.5 2.8 18.2 5.1 30.0 20.4 100.0 4,350 11.0 45-49 21.6 3.2 20.5 6.3 30.5 17.7 100.0 3,498 9.5 50-54 27.1 2.8 20.4 4.8 26.7 18.2 100.0 2,714 6.0 55-59 31.0 3.3 22.1 3.6 20.8 19.1 100.0 2,091 5.7 60-64 40.7 4.3 22.5 2.9 14.4 15.1 100.0 2,191 5.2 65+ 54.3 5.9 19.8 2.0 9.0 8.9 100.0 4,241 0.0 Residence Urban 13.1 18.9 10.9 15.0 24.6 17.4 100.0 32,319 8.2 Rural 37.4 19.2 10.9 11.6 14.5 6.3 100.0 40,641 2.8 Zone North Central 24.6 18.6 9.9 15.0 18.8 13.1 100.0 10,097 5.7 North East 47.4 17.4 6.4 9.7 11.0 8.2 100.0 12,597 0.4 North West 39.5 21.2 9.3 10.9 10.9 8.1 100.0 21,952 1.8 South East 8.7 22.4 19.8 16.6 23.2 9.2 100.0 7,401 5.9 South South 6.4 18.2 13.0 17.9 30.6 13.6 100.0 8,479 9.4 South West 9.1 15.9 12.3 13.7 31.0 17.9 100.0 12,434 10.6 State North Central FCT-Abuja 17.2 14.9 13.6 11.4 22.1 20.9 100.0 521 8.0 Benue 12.3 21.2 9.0 22.6 19.9 15.0 100.0 1,997 7.8 Kogi 13.0 20.9 10.7 15.1 26.6 13.7 100.0 976 8.0 Kwara 30.0 19.0 11.8 12.6 14.9 11.7 100.0 1,295 5.1 Nasarawa 16.7 21.1 12.4 15.5 19.2 15.1 100.0 1,175 6.0 Niger 46.9 12.8 4.6 10.2 14.2 11.2 100.0 2,591 1.1 Plateau 14.4 22.5 14.5 15.9 21.9 10.7 100.0 1,542 5.9 North East Adamawa 40.9 13.8 5.7 11.2 19.4 9.0 100.0 1,600 2.8 Bauchi 47.2 19.9 7.9 9.8 8.2 6.9 100.0 2,787 0.2 Borno 42.9 17.7 5.6 8.9 12.2 12.6 100.0 2,603 1.7 Gombe 52.3 16.5 7.2 8.4 10.6 5.0 100.0 1,463 0.0 Taraba 24.1 26.5 10.2 14.6 14.9 9.8 100.0 1,429 4.7 Yobe 65.2 12.2 3.5 7.5 5.9 5.7 100.0 2,715 0.0 North West Jigawa 42.2 23.0 10.4 10.2 7.2 7.0 100.0 2,431 1.2 Kaduna 26.1 24.6 9.8 12.8 16.8 9.9 100.0 4,001 4.7 Kano 30.1 25.1 8.8 13.7 10.6 11.7 100.0 5,066 3.1 Katsina 31.8 23.7 13.0 12.3 12.5 6.6 100.0 4,319 3.5 Kebbi 62.3 10.8 10.0 6.3 6.9 3.6 100.0 1,958 0.0 Sokoto 66.1 14.3 5.9 5.2 5.4 3.0 100.0 1,705 0.0 Zamfara 55.1 14.7 3.7 7.8 10.1 8.6 100.0 2,472 0.0 South East Abia 5.3 20.3 17.8 17.6 27.4 11.6 100.0 1,033 8.2 Anambra 6.7 21.3 23.7 17.8 23.6 7.0 100.0 2,054 5.9 Ebonyi 14.0 30.1 20.9 15.3 14.8 5.0 100.0 1,396 5.3 Enugu 10.6 23.6 20.1 15.1 20.4 10.1 100.0 1,285 5.8 Imo 7.4 17.8 14.9 17.0 29.4 13.3 100.0 1,633 8.8 South South Akwa Ibom 8.1 18.5 14.1 19.7 27.0 12.7 100.0 1,573 8.5 Bayelsa 5.2 19.5 11.1 16.9 33.3 13.9 100.0 639 10.2 Cross River 10.0 15.6 15.1 20.2 25.3 13.9 100.0 968 8.5 Delta 4.1 18.1 12.5 15.5 35.3 14.4 100.0 1,835 10.9 Edo 8.6 21.3 14.9 19.6 24.1 10.3 100.0 1,073 7.1 Rivers 4.9 17.5 11.7 17.0 33.9 15.0 100.0 2,391 10.7 South West Ekiti 8.1 18.4 13.5 16.7 25.0 18.2 100.0 860 8.9 Lagos 3.9 14.1 10.6 14.0 35.0 22.3 100.0 4,647 11.2 Ogun 11.7 16.9 14.9 11.6 28.9 15.9 100.0 1,586 8.3 Ondo 10.5 19.7 13.0 18.4 26.5 11.8 100.0 1,237 8.1 Osun 11.6 15.7 12.3 13.3 33.8 13.3 100.0 1,606 9.8 Oyo 14.9 15.9 13.1 11.4 27.5 17.0 100.0 2,497 8.5 Continued… 40 • Housing Characteristics and Household Population Table 2.13.2—Continued Background characteristic No education Some primary Completed primary1 Some secondary Completed secondary2 More than secondary Total Number Median years completed Wealth quintile Lowest 65.1 14.8 8.1 6.2 4.8 0.9 100.0 14,347 0.0 Second 36.9 22.4 12.6 12.5 12.1 3.4 100.0 14,043 2.5 Middle 19.5 23.4 13.7 15.7 20.4 7.2 100.0 14,278 5.5 Fourth 9.5 19.7 12.3 16.5 28.5 13.3 100.0 14,889 8.4 Highest 4.7 15.2 7.9 14.5 27.8 29.9 100.0 15,402 11.3 Total 26.6 19.1 10.9 13.1 19.0 11.2 100.0 72,959 5.4 Note: Total includes 11 cases with missing information on age. 1 Completed grade 6 at the primary level 2 Completed grade 6 at the secondary level Housing Characteristics and Household Population • 41 Table 2.14 School attendance ratios Net attendance ratios (NAR) and gross attendance ratios (GAR) for the de facto household population by sex and level of schooling, and the gender parity index (GPI), according to background characteristics, Nigeria DHS 2018 Net attendance ratio1 Gross attendance ratio2 Background characteristic Male Female Total Gender parity index3 Male Female Total Gender parity index3 PRIMARY SCHOOL Residence Urban 72.8 70.2 71.5 0.96 99.6 97.1 98.4 0.98 Rural 55.0 51.0 53.1 0.93 79.8 73.9 76.9 0.93 Zone North Central 62.1 62.1 62.1 1.00 87.6 91.3 89.4 1.04 North East 46.4 44.5 45.5 0.96 66.7 64.2 65.5 0.96 North West 57.9 51.8 54.9 0.90 83.4 74.3 78.9 0.89 South East 83.7 81.2 82.4 0.97 115.4 109.4 112.4 0.95 South South 72.8 68.0 70.5 0.93 97.2 92.4 94.9 0.95 South West 73.6 71.9 72.7 0.98 103.9 101.4 102.7 0.98 State North Central FCT-Abuja 75.0 74.5 74.8 0.99 104.9 103.8 104.4 0.99 Benue 75.2 74.7 74.9 0.99 108.8 117.5 113.2 1.08 Kogi 71.7 68.0 69.9 0.95 103.7 108.3 105.9 1.04 Kwara 59.2 62.2 60.6 1.05 80.1 87.2 83.5 1.09 Nasarawa 72.7 67.2 70.2 0.92 102.2 92.5 97.9 0.90 Niger 41.5 37.6 39.7 0.91 55.8 55.9 55.8 1.00 Plateau 70.0 75.1 72.6 1.07 102.9 105.4 104.2 1.02 North East Adamawa 44.2 46.5 45.3 1.05 62.9 65.2 64.1 1.04 Bauchi 48.1 45.8 46.9 0.95 69.7 68.4 69.1 0.98 Borno 53.3 48.8 50.9 0.92 72.2 65.3 68.6 0.90 Gombe 40.9 40.0 40.5 0.98 60.6 57.4 59.1 0.95 Taraba 65.3 59.3 62.3 0.91 98.3 90.6 94.5 0.92 Yobe 32.4 32.5 32.5 1.00 46.7 48.5 47.6 1.04 North West Jigawa 57.3 55.6 56.4 0.97 92.7 83.7 88.0 0.90 Kaduna 70.3 60.1 65.5 0.86 102.4 90.8 96.9 0.89 Kano 65.0 61.8 63.4 0.95 94.2 86.9 90.6 0.92 Katsina 70.9 65.7 68.3 0.93 96.8 91.2 94.0 0.94 Kebbi 30.6 22.0 26.4 0.72 44.0 31.8 38.1 0.72 Sokoto 31.8 25.9 28.9 0.81 48.2 37.3 42.8 0.77 Zamfara 43.9 32.3 38.2 0.73 57.7 43.1 50.5 0.75 South East Abia 82.5 80.0 81.2 0.97 115.6 102.4 108.9 0.89 Anambra 85.7 84.6 85.1 0.99 113.2 107.6 110.2 0.95 Ebonyi 84.1 77.4 80.7 0.92 115.6 111.2 113.4 0.96 Enugu 80.0 84.2 82.0 1.05 114.9 116.6 115.7 1.01 Imo 84.7 79.2 82.0 0.93 118.8 108.2 113.6 0.91 South South Akwa Ibom 69.5 64.2 66.8 0.92 95.7 85.1 90.3 0.89 Bayelsa 75.7 77.9 76.7 1.03 97.8 106.7 102.0 1.09 Cross River 63.2 60.9 62.0 0.96 90.7 85.1 87.7 0.94 Delta 80.7 70.6 75.8 0.88 107.7 94.9 101.5 0.88 Edo 74.3 74.2 74.2 1.00 96.2 98.6 97.4 1.02 Rivers 70.8 64.9 68.1 0.92 93.0 90.8 92.0 0.98 South West Ekiti 67.4 75.2 71.1 1.11 111.8 109.5 110.7 0.98 Lagos 75.5 72.7 74.0 0.96 104.1 106.1 105.2 1.02 Ogun 76.5 68.6 72.4 0.90 107.2 87.6 96.9 0.82 Ondo 79.4 78.4 78.9 0.99 104.1 108.0 106.0 1.04 Osun 75.0 71.5 73.2 0.95 101.9 103.1 102.5 1.01 Oyo 67.2 68.8 68.0 1.02 100.2 96.4 98.3 0.96 Wealth quintile Lowest 33.9 30.6 32.3 0.90 52.1 45.7 48.9 0.88 Second 60.6 55.6 58.1 0.92 87.5 81.4 84.5 0.93 Middle 73.1 69.4 71.3 0.95 103.1 98.4 100.8 0.95 Fourth 77.2 76.1 76.6 0.99 105.0 102.9 104.0 0.98 Highest 73.2 69.2 71.2 0.95 99.4 96.8 98.1 0.97 Total 62.2 58.8 60.5 0.95 87.8 83.3 85.6 0.95 Continued. 42 • Housing Characteristics and Household Population Table 2.14—Continued Net attendance ratio1 Gross attendance ratio2 Background characteristic Male Female Total Gender parity index3 Male Female Total Gender parity index3 SECONDARY SCHOOL Residence Urban 66.4 63.0 64.7 0.95 93.9 91.0 92.5 0.97 Rural 41.2 33.6 37.4 0.82 59.3 48.6 54.0 0.82 Zone North Central 54.4 49.0 51.7 0.90 81.4 72.5 77.0 0.89 North East 33.8 27.1 30.5 0.80 48.0 36.7 42.4 0.76 North West 41.8 32.0 36.8 0.77 58.3 43.9 51.0 0.75 South East 75.2 73.9 74.5 0.98 99.5 101.2 100.4 1.02 South South 72.7 69.0 70.9 0.95 104.5 108.5 106.4 1.04 South West 67.8 69.2 68.5 1.02 100.6 104.8 102.7 1.04 State North Central FCT-Abuja 61.1 60.1 60.6 0.98 97.2 87.8 92.4 0.90 Benue 60.1 46.9 53.2 0.78 88.3 69.4 78.4 0.79 Kogi 62.5 63.4 63.0 1.01 105.5 91.8 98.2 0.87 Kwara 56.4 53.6 55.0 0.95 81.9 83.5 82.7 1.02 Nasarawa 64.0 60.9 62.4 0.95 98.4 92.2 95.2 0.94 Niger 44.0 26.9 36.4 0.61 59.0 38.3 49.8 0.65 Plateau 49.3 54.3 51.8 1.10 78.0 79.3 78.7 1.02 North East Adamawa 50.0 28.1 38.2 0.56 63.0 35.8 48.3 0.57 Bauchi 29.2 27.2 28.2 0.93 45.5 39.7 42.7 0.87 Borno 42.4 34.0 38.0 0.80 57.0 44.1 50.3 0.77 Gombe 25.6 25.6 25.6 1.00 39.4 33.6 36.9 0.85 Taraba 50.9 32.3 40.6 0.63 78.2 50.4 62.8 0.64 Yobe 22.0 17.1 19.7 0.78 29.5 20.4 25.3 0.69 North West Jigawa 34.7 29.7 32.1 0.86 50.6 39.6 44.7 0.78 Kaduna 53.0 44.6 48.6 0.84 74.2 63.8 68.7 0.86 Kano 47.1 38.7 43.0 0.82 66.5 54.1 60.4 0.81 Katsina 49.6 32.5 40.9 0.65 66.7 44.8 55.5 0.67 Kebbi 23.1 13.7 18.4 0.59 33.2 16.1 24.8 0.49 Sokoto 18.3 10.5 14.4 0.57 25.8 13.6 19.7 0.53 Zamfara 36.6 28.0 32.3 0.76 51.0 35.6 43.2 0.70 South East Abia 75.5 74.1 74.8 0.98 105.4 103.5 104.4 0.98 Anambra 80.5 79.8 80.1 0.99 105.5 111.5 108.7 1.06 Ebonyi 66.5 62.2 64.1 0.94 82.7 82.6 82.6 1.00 Enugu 74.8 80.7 77.8 1.08 105.6 105.5 105.6 1.00 Imo 78.3 75.1 76.7 0.96 101.8 106.4 104.1 1.05 South South Akwa Ibom 72.9 63.2 68.1 0.87 101.0 100.9 100.9 1.00 Bayelsa 71.1 71.7 71.4 1.01 107.2 106.8 107.0 1.00 Cross River 75.5 81.7 78.3 1.08 114.8 150.3 130.7 1.31 Delta 70.6 71.3 70.9 1.01 97.5 108.6 102.7 1.11 Edo 72.4 71.2 71.8 0.98 105.0 108.6 106.8 1.03 Rivers 73.7 65.3 69.6 0.89 107.2 100.0 103.7 0.93 South West Ekiti 76.0 78.4 77.1 1.03 122.3 117.3 119.9 0.96 Lagos 70.5 69.0 69.7 0.98 99.5 103.1 101.4 1.04 Ogun 60.4 64.8 62.6 1.07 95.2 112.2 103.6 1.18 Ondo 68.9 69.8 69.3 1.01 94.2 93.2 93.7 0.99 Osun 68.8 66.2 67.4 0.96 97.8 94.5 96.0 0.97 Oyo 62.8 71.2 66.6 1.13 103.6 116.6 109.5 1.12 Wealth quintile Lowest 17.0 12.0 14.7 0.71 24.8 16.9 21.1 0.68 Second 43.3 31.2 37.1 0.72 61.8 42.9 52.1 0.69 Middle 60.5 51.1 55.7 0.84 85.1 73.2 79.1 0.86 Fourth 73.4 67.6 70.4 0.92 102.3 95.1 98.6 0.93 Highest 71.1 68.2 69.7 0.96 104.4 104.7 104.5 1.00 Total 52.1 46.6 49.4 0.89 74.3 67.4 70.8 0.91 1 The NAR for primary school is the percentage of the primary school-age (7-12 years) population that is attending primary school. The NAR for secondary school is the percentage of the secondary school-age (13-18 years) population that is attending secondary school. By definition, the NAR cannot exceed 100%. 2 The GAR for primary school is the total number of primary school students, expressed as a percentage of the official primary school-age population. The GAR for secondary school is the total number of secondary school students, expressed as a percentage of the official secondary school-age population. If there are significant numbers of overage and underage students at a given level of schooling, the GAR can exceed 100%. 3 The gender parity index for primary school is the ratio of the primary school NAR (GAR) for females to the NAR (GAR) for males. The gender parity index for secondary school is the ratio of the secondary school NAR (GAR) for females to the NAR (GAR) for males. Characteristics of Respondents • 43 CHARACTERISTICS OF RESPONDENTS 3 Key Findings ▪ Education: The percentage of women age 15-49 with no education has decreased since 2003, from 42% to 35%. The median number of years of schooling completed has increased from 5.0 to 6.5 years during the same period. ▪ Exposure to mass media: The level of exposure to mass media is generally low in Nigeria. More than half of the respondents age 15-49 have no access to any of the three media sources (newspaper, television, and radio) at least once a week (56% of female and 51% male). ▪ Internet usage: Urban women and men (31% and 55%, respectively) are more likely than rural women and men (6% and 25%, respectively) to have used the internet. ▪ Employment: 65% women and 86% of men age 15-49 are currently employed. his chapter presents information on the demographic and socioeconomic characteristics of the survey respondents such as age, education, place of residence, marital status, employment, and wealth status. This information is useful for understanding the factors that affect use of reproductive health services, contraceptive use, and other health behaviours. 3.1 BASIC CHARACTERISTICS OF SURVEY RESPONDENTS The 2018 NDHS interviewed 41,821 women age 15-49 and 13,311 men age 15-59. Table 3.1 shows the percent distribution of women and men age 15-49 by background characteristics. The majority of women and men are under age 30 (54% of women and 46% of men). Forty-six percent of men and women are Christian, while 54% are Islam and less than 1% are traditionalists. The main ethnic groups in Nigeria are Hausa (30% of women and 31% of men), Igbo (15% of both women and men), and Yoruba (15% of women and 16% of men). Women are more likely than men to be currently married or living together with a partner (70% and 57%, respectively). Women are less likely than men to have never been married (25% and 42%, respectively). Place of residence typically determines access to services and information about health and other aspects of life. Slightly more than half of women and men live in rural areas (54% each), while slightly less than half live in urban areas (46% each). T 44 • Characteristics of Respondents 3.2 EDUCATION AND LITERACY Literacy Respondents who had attended higher than secondary school were assumed to be literate. All other respondents, shown a typed sentence to read aloud, were considered literate if they could read all or part of the sentence. Sample: Women and men age 15-49 Education is an important factor influencing a person’s behaviour and opportunities. Tables 3.2.1 and 3.2.2 as well as Figure 3.1 show that men are better educated than women. Thirty-five percent of women and 22% of men age 15-49 have no formal education, while 11% of women and 17% of men have more than a secondary education. Trends: The percentage of women with no education has decreased since 2003, from 42% to 35%. The median number of years of schooling completed has increased from 5.0 to 6.5 years during the same period. Among men age 15-59, the median number of years of schooling has increased from 6.6 to 10.5 years. Patterns by background characteristics ▪ Table 3.2.1 shows that urban women are better educated than rural women; only 16% of urban women have no education, as opposed to 51% of rural women. ▪ Educational attainment among women increases with increasing household wealth (Figure 3.2). For example, only 3% of women in the lowest wealth quantile have a secondary education or higher, as compared with 75% of those in the highest quantile. A similar pattern is observed among men. ▪ There are wide variations by place of residence in median number of years of education completed. Urban women have completed a median of 11 years of education, while the median among rural women is zero. The corresponding figures among men are 11 and 7 years. Figure 3.1 Education of survey respondents Figure 3.2 Secondary education by household wealth 35 22 4 3 10 11 16 16 23 32 11 17 Women Men Percent distribution of women and men age 15-49 by highest level of schooling attended or completed More than secondary Completed secondary Some secondary Completed primary Some primary No education 3 10 26 47 75 10 28 48 64 81 Lowest Second Middle Fourth Highest Percentage of women and men age 15-49 with a secondary education or higher Women Men WealthiestPoorest Characteristics of Respondents • 45 Figure 3.3 Secondary education by state Percentage of women age 15-49 with a secondary education or higher ▪ The percentage of women who have a secondary education or more is highest in Lagos (68%) and lowest in Sokoto (5%) (Figure 3.3). ▪ Women and men in the lowest wealth quintile (11% and 29%, respectively) are less likely than other women and men to be literate (Table 3.3.1 and Table 3.3.2). 3.3 MASS MEDIA EXPOSURE Exposure to mass media Respondents were asked how often they read a newspaper, listened to the radio, or watched television. Those who responded at least once a week are considered regularly exposed to that form of media. Sample: Women and men age 15-49 Exposure to different mass media is key to information dissemination and expansion of knowledge. Tables 3.4.1 and 3.4.2 show the percentages of women and men who are exposed to different types of media, by background characteristics. The level of exposure to mass media is generally low in Nigeria. Among both women and men, radio and television are the most frequently accessed forms of media. Women are slightly more likely to watch television than to listen to the radio (33% versus 30%), while men are slightly more likely to listen to the radio (39% versus 34%). 46 • Characteristics of Respondents Figure 3.4 shows that more than half of respondents have no access to any of the three media sources at least once a week (56% of female respondents and 51% of male respondents). Trends: Since 2013, women’s and men’s exposure to mass media has shown a gradual decline. For example, the proportion of women who listen to the radio at least once a week has decreased from 39% to 30%. Among men, the proportion has declined from 55% to 39%. The proportion of respondents having no access to any of the three sources (newspaper, television, and radio) has increased from 50% to 56% among women and from 38% to 51% among men. Patterns by background characteristics ▪ The percentage of women who read a newspaper at least once a week is very low. However, urban women are over two times more likely to read a newspaper than rural women (7% and 3%, respectively). The urban-rural gap is more evident in television viewing, with 51% of urban women and only 17% of rural women watching television at least once a week. ▪ The percentages of women and men with no access to any of the three media source are highest in the North East (73% and 68%, respectively) and lowest in the South West (28% and 15%, respectively). 3.4 INTERNET USAGE The internet has gradually become an important means of transacting business and sharing information through social media. Other forms of media organisations have also adopted the internet as a means of reaching people. There are currently online shopping platforms through which business is transacted on a daily basis in Nigeria. Also, some e-health platforms have started operating in the country. The internet has become a very important tool through which information is accessed. Overall, 30% of women and 31% of men age 15-49 use the internet at least once a week (Tables 3.5.1 and 3.5.2). Patterns by background characteristics ▪ Urban women and men (31% and 55%, respectively) are more likely than rural women and men (6% and 25%, respectively) to have ever used the internet. ▪ The percentages of women and men who have ever used the internet are highest in the South West (39% and 57%, respectively). ▪ Among the states, Lagos has the highest proportion of women (60%) and men (74%) using the internet. Women and men in Kebbi (1% and 11%, respectively) and Sokoto (1% and 14%, respectively) are also least likely to have ever used the internet. 3.5 EMPLOYMENT Currently employed Respondents who were employed in the 7 days before the survey. Sample: Women and men age 15-49 Figure 3.4 Exposure to mass media 5 33 30 3 56 15 34 39 11 51 Reads news- paper Watches television Listens to radio All three media None of these media Percentage of women and men age 15-49 who are exposed to media on a weekly basis Women Men Characteristics of Respondents • 47 In the 2018 NDHS, respondents were asked whether they were employed at the time of the survey and, if not, whether they had worked at any time during the 12 months preceding the survey. Tables 3.6.1 and 3.6.2 show that 65% of women and 86% of men are currently employed. Furthermore, 3% of women and 2% of men reported that they had worked in the past 12 months but were not currently employed. Trends: Current employment among women age 15-49 has increased over the last decade, from 59% in 2008 to 65% in 2018. Similarly, the percentage of men who are currently employed has increased from 80% to 86%. Patterns by background characteristics ▪ Table 3.6.1 shows that divorced, separated, or widowed women (81%) are more likely to be employed than women who are currently married (71%) and those who have never been married (47%). Among men, those who are currently married or living together with a partner (99%) and those who are divorced, separated, or widowed (93%) are more likely to be employed than those who have never been married (69%) (Table 3.6.2). ▪ There are notable variations in the proportion of currently employed women and men by place of residence. Urban women are more likely than rural women to be employed (67% and 63%, respectively). Conversely, urban men are less likely to be employed than rural men (84% and 88%, respectively). ▪ The percentage of women who are currently employed generally increases with increasing education, from 59% among those with no education to 77% among those with primary education. Though it drops to 64% among those with secondary education, it rises to 72% among those with more than a secondary education. However, among men, there is a general decrease in current employment with increasing education, from 93% among those with no education to 87% among those with more than a secondary education (Figure 3.5). ▪ The percentage of women who are employed increases with increasing household wealth, from 58% among those in the lowest wealth quantile to 68% among those in highest quantile. Among men, the percentage who are employed decreases with increasing wealth, from 92% among those in the lowest quantile to 83% among those in the highest quantile. 3.6 OCCUPATION Occupation Categorised as professional/technical/managerial, clerical, sales and services, skilled manual, unskilled manual, agriculture, and other. Sample: Women and men age 15-49 who were currently employed or had worked in the 12 months before the survey Figure 3.5 Employment status by education 59 77 64 72 93 92 81 87 No education Primary Secondary More than secondary Percentage of women and men age 15-49 who are currently employed Women Men 48 • Characteristics of Respondents Tables 3.7.1 and 3.7.2 show that more men than women were employed in professional/technical/ managerial occupations in the 12 months before the survey (13% and 9%, respectively). Women dominate employment in sales and services (62% versus 26% among men), while a higher percentage of men than women are engaged in agricultural work (41% and 22%, respectively) (Figure 3.6). Eighteen percent of employed women in Nigeria are not paid for their work. Women engaged in agricultural work are much more likely (47%) than those working in nonagricultural occupations (10%) to not be paid for their work. Seventy percent of women who worked in the past year are self- employed (Table 3.8). Trends: There has been a rise since 2013 in the proportion of women working in agricultural occupations, from 16% to 22%. Among men, the proportion has increased from 34% to 41%. The proportion of women and men who are employed in sales and services has remained constant at 62% (versus 61% in 2013) and 26% (versus 25% in 2013), respectively. Patterns by background characteristics ▪ Tables 3.7.1 and 3.7.2 show that women and men living in rural areas are more likely to be engaged in agriculture (32% and 60%, respectively) than those living in urban areas (10% and 17%, respectively). ▪ Women and men with more than a secondary education are more likely than those at other educational levels to be engaged in professional/technical/managerial work (40% and 39%, respectively). Women with no education are mostly engaged in sales and services (67%), while men with no education are primarily engaged in agricultural work (72%). ▪ The percentages of men and women employed in professional/technical/managerial and clerical occupations generally increase with increasing wealth. 3.7 HEALTH INSURANCE COVERAGE Health insurance improves access to health care, thus promoting good health. Reasonable access to health care encourages individuals to seek health maintenance services more regularly than they otherwise would, thereby preventing potentially serious illnesses. Additionally, health insurance protects individuals from financial hardships that may result from large or unexpected medical bills. In Nigeria, health insurance can be obtained from private organisations or from government agencies. The act of parliament that came into force in October 2014 envisages a health care system that will cover all strata of society in all urban and rural communities (Federal Republic of Nigeria 2014). However, coverage is limited to public and large private organisations. The 2018 NDHS collected information about specific types of insurance coverage and the percentages of women and men with any health insurance according to background characteristics. Only 3% of women and men age 15-49 have health insurance (Table 3.9.1 and Table 3.9.2). Figure 3.6 Occupation 9 2 62 5 0 22 13 2 26 12 7 41 Professional/ technical/ managerial Clerical Sales and services Skilled manual Unskilled manual Agriculture Percentage of women and men age 15-49 employed in the 12 months before the survey by occupation Women Men Characteristics of Respondents • 49 Trends: The percentage of women who do not have any form of health insurance has decreased slightly since 2013, from 98% to 97%. There has been no change in the percentage among men (97% in both 2013 and 2018). The percentage of women with more than a secondary education who have employer-based insurance increased from 0% in 2008 to 11% in 2018. Among men with more than a secondary education, the percentage increased from less than 1% to 12%. Patterns by background characteristics ▪ Urban women and men (4% each) are more likely than rural women and men (1% each) to have employer-based insurance coverage. ▪ Eleven percent of women and 12% of men with more than a secondary education have employer- based insurance. Women (7%) and men (8%) in the highest wealth quantile are most likely to have employer-based insurance. 3.8 TOBACCO USE Table 3.10.1 shows that cigarette smoking and use of any type of tobacco are rare among women (less than 1%). Six percent of men smoke any type of tobacco, while 94% are non-smokers (Table 3.10.2). Among men who smoke cigarettes daily, more than one-third (38%) smoke less than 5 cigarettes each day, while one-third (33%) smoke 5-9 cigarettes; 8% of daily cigarette smokers smoke between 15 and 24 cigarettes each day (Table 3.11). One percent of men use smokeless tobacco (Table 3.12). Trends: The practice of smoking among women is uncom

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