Pakistan - Demographic and Health Survey - 2019

Publication date: 2019

Pakistan Demographic and Health Survey 2017-18 P akistan 2017-18 D em ographic and H ealth S urvey PAKISTAN DEMOGRAPHIC AND HEALTH SURVEY 2017-18 National Institute of Population Studies Islamabad, Pakistan The DHS Program ICF Rockville, Maryland, USA January 2019 The 2017-18 Pakistan Demographic and Health Survey (2017-18 PDHS) was implemented by the National Institute of Population Studies (NIPS) under the aegis of the Ministry of National Health Services, Regulations and Coordination, Islamabad, Pakistan. ICF provided technical assistance through The DHS Program, a project funded by the United States Agency for International Development (USAID) that provides support and technical assistance in the implementation of population and health surveys in countries worldwide. Support for the survey was also provided by the Department for International Development (DFID) and the United Nations Population Fund (UNFPA). Additional information about the 2017-18 PDHS may be obtained from the National Institute of Population Studies, Ministry of National Health Services, Regulations and Coordination, National Institute of Health (NIH), Park Road, Chak Shahzad, Islamabad, Pakistan; telephone: +92-51-9255937; fax: +92-51-9255932; internet: www.nips.org.pk. 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 photo: “Blue Hour at Pakistan Monument” ©2016 by Muhammad Ashar [CC BY-SA 4.0], from Wikimedia Commons ISBN: 978-969-9732-04-1 Suggested citation: National Institute of Population Studies (NIPS) [Pakistan] and ICF. 2019. Pakistan Demographic and Health Survey 2017-18. Islamabad, Pakistan, and Rockville, Maryland, USA: NIPS and ICF. Contents • iii CONTENTS TABLES AND FIGURES . ix FOREWORD . xvii ACKNOWLEDGEMENTS . xix 2017-18 PAKISTAN DEMOGRAPHIC AND HEALTH SURVEY TECHNICAL ADVISORY COMMITTEE . xxi CONTRIBUTORS TO THE REPORT . xxiii ACRONYMS AND ABBREVIATIONS . xxv READING AND UNDERSTANDING TABLES FROM THE 2017-18 PAKISTAN DEMOGRAPHIC AND HEALTH SURVEY (PDHS) . xxix SUSTAINABLE DEVELOPMENT GOALS INDICATORS . xxxvii MAP OF PAKISTAN . xxxviii 1 INTRODUCTION AND SURVEY METHODOLOGY . 1 1.1 Survey Objectives . 1 1.2 Sample Design . 2 1.3 Questionnaires . 3 1.4 Anthropometry . 4 1.5 Pretest . 4 1.6 Training of Field Staff . 4 1.7 Fieldwork . 5 1.8 Data Processing . 6 1.9 Response Rates . 6 2 HOUSING CHARACTERISTICS AND HOUSEHOLD POPULATION . 9 2.1 Drinking Water Sources and Treatment . 9 2.2 Sanitation . 10 2.3 Exposure to Smoke inside the Home . 11 2.3.1 Other Housing Characteristics . 11 2.4 Household Wealth . 11 2.4.1 Household Durable Goods . 11 2.5 Hand washing . 12 2.6 Household Population and Composition . 12 2.7 Children’s Living Arrangements and Parental Survival . 13 2.8 Birth Registration . 14 2.8.1 Registration with NADRA . 15 2.9 Education . 15 2.9.1 Educational Attainment . 15 2.9.2 School Attendance . 16 3 CHARACTERISTICS OF RESPONDENTS . 33 3.1 Basic Characteristics of Survey Respondents . 33 3.2 Education and Literacy . 34 3.3 Mass Media Exposure . 35 3.4 Employment . 36 3.5 Occupation . 36 3.6 Health Insurance Coverage and Safety Net . 37 3.7 Tobacco Use . 38 3.8 Knowledge Concerning Tuberculosis . 38 3.9 Knowledge Concerning Hepatitis . 38 iv • Contents 4 MARRIAGE AND SEXUAL ACTIVITY . 67 4.1 Marital Status . 67 4.2 Polygyny . 68 4.3 Age at First Marriage . 69 4.4 Consanguinity . 69 4.5 Age at First Sexual Intercourse . 70 4.6 Recent Sexual Activity . 71 5 FERTILITY . 83 5.1 Current Fertility . 84 5.2 Children Ever Born and Living . 85 5.3 Birth Intervals . 86 5.4 Insusceptibility to Pregnancy . 86 5.5 Age at First Birth . 88 5.6 Teenage Childbearing . 88 6 FERTILITY PREFERENCES . 101 6.1 Desire for Another Child . 101 6.2 Ideal Family Size . 103 6.3 Fertility Planning Status . 104 6.4 Wanted Fertility Rates . 104 7 FAMILY PLANNING . 113 7.1 Contraceptive Knowledge and Use . 114 7.2 Source of Modern Contraceptive Methods . 116 7.3 Informed Choice . 117 7.4 Discontinuation of Contraceptives . 117 7.5 Demand for Family Planning . 118 7.5.1 Decision Making about Family Planning . 120 7.5.2 Future Use of Contraception . 120 7.5.3 Exposure to Family Planning Messages in the Media . 120 7.6 Contact of Nonusers with Family Planning Providers . 121 7.7 Postpartum Counselling on Family Planning . 122 7.8 Men’s Attitude towards Contraceptive Use . 122 8 INFANT AND CHILD MORTALITY . 145 8.1 Infant and Child Mortality . 146 8.2 Biodemographic and Sociodemographic Risk Factors . 146 8.3 Perinatal Mortality . 148 8.4 High-Risk Fertility Behaviour . 149 9 MATERNAL HEALTH CARE . 155 9.1 Antenatal Care Coverage and Content . 156 9.1.1 Skilled Providers . 156 9.1.2 Timing and Number of ANC Visits . 157 9.2 Components of ANC Visits . 157 9.3 Protection against Neonatal Tetanus . 158 9.4 Delivery Services . 158 9.4.1 Institutional Deliveries . 158 9.4.2 Skilled Assistance during Delivery . 160 9.4.3 Delivery by Caesarean Section . 161 9.5 Postnatal Care . 162 9.5.1 Postnatal Health Check for Mothers . 162 9.5.2 Postnatal Health Check for Newborns . 163 Contents • v 9.5.3 Newborn Care Practices . 163 9.5.4 Pregnancy Outcomes . 164 9.6 Problems in Accessing Health Care . 164 10 CHILD HEALTH . 183 10.1 Birth Weight . 184 10.2 Vaccination of Children . 184 10.3 Symptoms of Acute Respiratory Infection . 187 10.4 Fever . 188 10.5 Diarrhoeal Disease . 189 10.5.1 Prevalence of Diarrhoea and Treatment-seeking Behaviour . 189 10.5.2 Feeding Practices . 190 10.5.3 Treatment of Diarrhoea . 190 10.5.4 Knowledge of ORS Packets . 192 10.6 Treatment of Childhood Illness . 192 10.7 Disposal of Children’s Stools . 192 11 NUTRITION OF CHILDREN AND WOMEN . 209 11.1 Nutritional Status of Children . 209 11.1.1 Measurement of Nutritional Status among Young Children . 210 11.1.2 Data Collection . 211 11.1.3 Malnutrition Prevalence in Children . 211 11.2 Infant and Young Child Feeding Practices . 212 11.2.1 Initiation of Breastfeeding . 213 11.2.2 Exclusive Breastfeeding . 213 11.2.3 Reasons for Not Breastfeeding or Stopping Breastfeeding . 215 11.2.4 Median Duration of Breastfeeding . 215 11.2.5 Complementary Feeding . 215 11.2.6 Minimum Acceptable Diet . 216 11.3 Micronutrient Intake and Supplementation among Children . 217 11.4 Nutritional Status of Women . 218 11.5 Micronutrient Supplementation And Deworming During Pregnancy . 219 12 MALARIA . 233 12.1 Ownership of Insecticide-treated Nets . 234 12.2 Household Access to and Use of ITNs . 235 12.3 Use of ITNs by Children and Pregnant Women . 236 12.4 Use of Antimalarial Drugs . 236 13 HIV/AIDS-RELATED KNOWLEDGE, ATTITUDES, AND BEHAVIOUR . 245 13.1 HIV/AIDS Knowledge, Transmission, and Prevention Methods . 246 13.2 Knowledge about Mother-to-Child Transmission . 247 13.3 Discriminatory Attitudes towards People Living with HIV . 248 13.4 Coverage of HIV Testing Services . 248 13.4.1 Awareness of HIV Testing Services and Experience with HIV Testing . 249 13.5 Self-reporting of Sexually Transmitted Infections . 249 13.6 HIV/AIDS-related Knowledge and Behaviour among Young People . 249 13.6.1 Knowledge . 249 13.6.2 First Sex . 250 13.6.3 Coverage of HIV Testing Services . 250 13.7 Knowledge of Treatment of HIV . 250 vi • Contents 14 DISABILITY . 263 14.1 Disability by Domain and Age . 263 14.2 Disability among Adults by Other Background Characteristics . 264 15 WOMEN’S EMPOWERMENT . 269 15.1 Married Women’s and Men’s Employment . 270 15.2 Control over Women’s Earnings . 270 15.3 Control over Men’s Earnings . 271 15.4 Women’s Control over Their Own Earnings and Those of Their Husbands . 272 15.5 Women’s and Men’s Ownership of Assets . 272 15.6 Ownership of Title or Deed for House and Land . 273 15.7 Ownership and Use of Bank Accounts and Mobile Phones . 273 15.8 Women’s Participation in Decision Making . 274 15.9 Attitudes toward Wife Beating . 275 15.10 Attitude towards Negotiating Safer Sexual Relations with Husband . 276 15.11 Ability to Negotiate Sexual Relations with Husband . 277 15.12 Women’s Empowerment Indicators . 278 15.13 Current Use of Contraception by Women’s Empowerment . 278 15.14 Ideal Number of Children and Unmet Need for Family Planning by Women’s Empowerment . 278 15.15 Reproductive Health Care by Women’s Empowerment . 279 15.16 Early Childhood Mortality and Women’s Empowerment . 279 15 DOMESTIC VIOLENCE . 303 16.1 Measurement of Violence . 304 16.2 Women’s Experience of Physical Violence . 304 16.2.1 Perpetrators of Physical Violence . 305 16.3 Experience of Sexual Violence . 305 16.3.1 Prevalence of Sexual Violence . 306 16.3.2 Perpetrators of Sexual Violence . 306 16.4 Experience of Different Forms of Violence . 306 16.5 Marital Control by Husband . 306 16.6 Forms of Spousal Violence . 307 16.6.1 Prevalence of Spousal Violence . 307 16.6.2 Onset of Spousal Violence . 310 16.7 Injuries to Women due to Spousal Violence . 310 16.8 Response to Violence . 310 16.8.1 Help Seeking among Women Who Have Experienced Violence . 310 16.8.2 Sources for Help . 311 16.8.3 Reasons for Seeking Help . 311 16.8.4 Reasons for Not Seeking Help . 311 17 MIGRATION . 327 17.1 In-migration and Immigration . 328 17.1.1 Incidence of In-migration and Immigration . 328 17.1.2 Duration of Continuous Residence . 329 17.1.3 Most Recent Place of Residence Prior to Current Residence . 329 17.1.4 Direction of In-migration . 329 17.1.5 Reasons for In-migration . 331 17.2 Out-migration . 332 17.2.1 Out-migration within Pakistan . 332 17.2.2 Direction of Movement among Out-migrants . 333 17.2.3 Reasons for Out-migration within Pakistan . 334 Contents • vii 17.3 Emigration . 334 17.4 Remittances . 335 REFERENCES . 345 APPENDIX A SAMPLE DESIGN . 347 A.1 Introduction . 347 A.2 Sample Frame . 347 A.3 Sample Design and Implementation . 348 A.4 Sample Probabilities and Sampling Weights . 352 APPENDIX B ESTIMATES OF SAMPLING ERRORS . 355 APPENDIX C DATA QUALITY TABLES . 381 APPENDIX D ACCESS TO SERVICES IN RURAL COMMUNITIES . 397 APPENDIX E PERSONS INVOLVED IN THE 2017-18 PDHS . 401 APPENDIX F QUESTIONNAIRES . 405 Household . 407 Woman's . 429 Man's . 493 Biomarker . 515 Community . 521 Fieldworker . 531 Tables and Figures • ix TABLES AND FIGURES 1 INTRODUCTION AND SURVEY METHODOLOGY . 1 Table 1.1 Results of the household and individual interviews . 7 2 HOUSING CHARACTERISTICS AND HOUSEHOLD POPULATION . 9 Table 2.1 Household drinking water . 18 Table 2.2 Availability of water . 19 Table 2.3 Household sanitation facilities . 19 Table 2.4 Household characteristics . 20 Table 2.5 Household possessions . 21 Table 2.6 Wealth quintiles . 22 Table 2.7 Handwashing . 23 Table 2.8 Household population by age, sex, and residence . 24 Table 2.9 Household composition . 25 Table 2.10 Children’s living arrangements and orphanhood . 26 Table 2.11 Birth registration of children under age 5 . 27 Table 2.12 Registration with NADRA . 28 Table 2.13.1 Educational attainment of the female household population . 29 Table 2.13.2 Educational attainment of the male household population . 30 Table 2.14 School attendance ratios . 31 Table 2.15 Reasons for children dropping out of school . 32 Figure 2.1 Household drinking water by residence . 10 Figure 2.2 Household toilet facilities by residence . 10 Figure 2.3 Household wealth by residence . 12 Figure 2.4 Population pyramid . 13 Figure 2.5 Birth registration by household wealth . 14 Figure 2.6 Secondary school attendance by household wealth . 17 3 CHARACTERISTICS OF RESPONDENTS . 33 Table 3.1.1 Background characteristics of respondents . 40 Table 3.1.2 Background characteristics of respondents (Azad Jammu and Kashmir) . 41 Table 3.1.3 Background characteristics of respondents (Gilgit Baltistan) . 42 Table 3.2.1 Educational attainment: Women . 43 Table 3.2.2 Educational attainment: Men . 44 Table 3.3.1 Literacy: Women . 45 Table 3.3.2 Literacy: Men . 46 Table 3.4.1 Exposure to mass media: Women . 47 Table 3.4.2 Exposure to mass media: Men . 48 Table 3.5.1 Internet usage: Women . 49 Table 3.5.2 Internet usage: Men . 50 Table 3.6.1 Employment status: Women . 51 Table 3.6.2 Employment status: Men. 52 Table 3.7.1 Occupation: Women . 53 Table 3.7.2 Occupation: Men . 54 Table 3.8 Type of employment: Women . 55 Table 3.9.1 Health insurance coverage: Women . 56 Table 3.9.2 Health insurance coverage: Men . 57 Table 3.10 Benefit from Benazir Income Support Programme . 58 Table 3.11.1 Tobacco smoking: Women . 59 Table 3.11.2 Tobacco smoking: Men . 60 Table 3.12 Average number of cigarettes smoked daily by men . 61 Table 3.13 Smokeless tobacco use and any tobacco use . 62 x • Tables and Figures Table 3.14.1 Knowledge concerning tuberculosis: Women . 63 Table 3.14.2 Knowledge concerning tuberculosis: Men . 64 Table 3.15.1 Knowledge concerning hepatitis: Women . 65 Table 3.15.2 Knowledge concerning hepatitis: Men . 66 Figure 3.1 Education of survey respondents . 34 Figure 3.2 Secondary education by residence . 34 Figure 3.3 Exposure to mass media . 35 Figure 3.4 Employment status by wealth . 36 Figure 3.5 Occupation . 37 4 MARRIAGE AND SEXUAL ACTIVITY . 67 Table 4.1 Current marital status . 72 Table 4.2.1 Number of women’s co-wives . 73 Table 4.2.2 Number of men’s wives . 74 Table 4.3 Age at first marriage. 75 Table 4.4 Median age at first marriage by background characteristics . 76 Table 4.5 Marriage between relatives . 77 Table 4.6 Age at first sexual intercourse . 78 Table 4.7 Median age at first sexual intercourse according to background characteristics . 79 Table 4.8.1 Recent sexual activity: Women . 80 Table 4.8.2 Recent sexual activity: Men . 81 Figure 4.1 Marital status . 68 Figure 4.2 Women’s median age at marriage by education . 69 Figure 4.3 Median age at first sex and first marriage . 70 5 FERTILITY . 83 Table 5.1 Current fertility . 90 Table 5.2 Fertility by background characteristics . 91 Table 5.3.1 Trends in age-specific fertility rates . 92 Table 5.3.2 Trends in age-specific and total fertility rates . 92 Table 5.4 Children ever born and living . 93 Table 5.5 Birth intervals . 94 Table 5.6 Postpartum amenorrhoea, abstinence, and insusceptibility . 95 Table 5.7 Median duration of amenorrhoea, postpartum abstinence, and postpartum insusceptibility . 96 Table 5.8 Menopause . 97 Table 5.9 Age at first birth . 97 Table 5.10 Median age at first birth . 98 Table 5.11 Teenage pregnancy and motherhood. 99 Figure 5.1 Trends in fertility by residence . 84 Figure 5.2 Trends in age-specific fertility . 84 Figure 5.3 Fertility by education . 85 Figure 5.4 Fertility by region . 85 Figure 5.5 Birth intervals . 86 Figure 5.6 Median age at first birth by household wealth . 88 6 FERTILITY PREFERENCES . 101 Table 6.1 Fertility preferences by number of living children . 106 Table 6.2.1 Desire to limit childbearing: Women . 107 Table 6.2.2 Desire to limit childbearing: Men . 108 Table 6.3 Ideal number of children by number of living children . 109 Table 6.4 Mean ideal number of children according to background characteristics . 110 Table 6.5 Couple’s agreement on family size . 111 Tables and Figures • xi Table 6.6 Fertility planning status . 111 Table 6.7 Wanted fertility rates . 112 Figure 6.1 Desire to limit childbearing by number of living children . 102 Figure 6.2 Trends in desire to limit childbearing . 102 Figure 6.3 Ideal family size by number of living children . 103 Figure 6.4 Fertility planning status . 104 Figure 6.5 Trends in wanted and actual fertility . 105 7 FAMILY PLANNING . 113 Table 7.1 Knowledge of contraceptive methods . 123 Table 7.2 Knowledge of contraceptive methods according to background characteristics . 124 Table 7.3 Current use of contraception by age . 125 Table 7.4.1 Current use of contraception according to background characteristics . 126 Table 7.4.2 Trends in the current use of contraception . 128 Table 7.5 Knowledge of fertile period . 128 Table 7.6 Knowledge of fertile period by age . 128 Table 7.7 Timing of sterilisation . 129 Table 7.8 Source of modern contraception methods . 129 Table 7.9 Use of social marketing brand pills and condoms . 130 Table 7.10 Informed choice . 131 Table 7.11 Advise on method selection and use . 132 Table 7.12 Twelve-month contraceptive discontinuation rates . 132 Table 7.13 Reasons for discontinuation . 133 Table 7.14 Need and demand for family planning among currently married women . 134 Table 7.15 Decision making about family planning . 135 Table 7.16 Future use of contraception . 136 Table 7.17 Exposure to family planning messages . 136 Table 7.18.1 Exposure to specific family planning messages: Women . 137 Table 7.18.2 Exposure to specific family planning messages: Men . 139 Table 7.19 Contact of nonusers with family planning providers . 141 Table 7.20 Postpartum counselling on family planning . 142 Table 7.21 Men’s attitudes towards contraceptive use . 143 Figure 7.1 Contraceptive use . 114 Figure 7.2 Trends in contraceptive use . 115 Figure 7.3 Use of modern methods by household wealth. 115 Figure 7.4 Modern contraceptive use by region . 115 Figure 7.5 Source of modern contraceptive methods . 116 Figure 7.6 Demand for family planning . 118 Figure 7.7 Trends in demand for family planning . 119 Figure 7.8 Unmet need by wealth . 119 Figure 7.9 Unmet need by region . 119 8 INFANT AND CHILD MORTALITY . 145 Table 8.1 Early childhood mortality rates . 150 Table 8.2 Five-year early childhood mortality rates according to background characteristics . 150 Table 8.3 Ten-year early childhood mortality rates according to additional characteristics . 151 Table 8.4 Perinatal mortality . 152 Table 8.5 High-risk fertility behaviour . 153 Figure 8.1 Trends in early childhood mortality rates . 146 Figure 8.2 Childhood mortality by previous birth interval . 147 xii • Tables and Figures Figure 8.3 Under-5 mortality by mother’s education . 148 Figure 8.4 Under-5 mortality by region . 148 Figure 8.5 Perinatal mortality by mother’s age at birth . 149 9 MATERNAL HEALTH CARE . 155 Table 9.1 Antenatal care . 166 Table 9.2 Number of antenatal care visits and timing of first visit . 167 Table 9.3 Components of antenatal care . 168 Table 9.4 Counselling during antenatal care . 169 Table 9.5 Tetanus toxoid injections . 170 Table 9.6 Place of delivery . 171 Table 9.7 Assistance during delivery . 172 Table 9.8 Caesarean section . 173 Table 9.9 Duration of stay in health facility after birth . 174 Table 9.10 Timing of first postnatal check for the mother . 175 Table 9.11 Type of provider of first postnatal check for the mother. 176 Table 9.12 Timing of first postnatal check for the newborn . 177 Table 9.13 Type of provider of first postnatal check for the newborn . 178 Table 9.14 Content of postnatal care for the newborn . 179 Table 9.15 Newborn care practices . 180 Table 9.16 Pregnancy outcomes by background characteristics . 181 Table 9.17 Problems in accessing health care . 182 Figure 9.1 Trends in antenatal care coverage . 156 Figure 9.2 Components of antenatal care . 157 Figure 9.3 Trends in place of birth . 159 Figure 9.4 Health facility births by education . 159 Figure 9.5 Health facility births by region . 160 Figure 9.6 Assistance during delivery . 160 Figure 9.7 Skilled assistance at delivery by mother’s education . 161 Figure 9.8 Postnatal care by place of delivery . 162 10 CHILD HEALTH . 183 Table 10.1 Child’s size and weight at birth . 194 Table 10.2 Vaccinations by source of information . 195 Table 10.3 Vaccinations by background characteristics . 196 Table 10.4 Possession and observation of vaccination cards, according to background characteristics . 198 Table 10.5 Prevalence and treatment of symptoms of acute respiratory infection . 199 Table 10.6 Source of advice or treatment for children with symptoms of acute respiratory infection . 200 Table 10.7 Prevalence and treatment of fever . 201 Table 10.8 Prevalence and treatment of diarrhoea . 202 Table 10.9 Feeding practices during diarrhoea . 203 Table 10.10 Oral rehydration therapy, zinc, and other treatments for diarrhoea . 205 Table 10.11 Source of advice or treatment for children with diarrhoea . 207 Table 10.12 Disposal of children’s stools . 208 Figure 10.1 Childhood vaccinations . 185 Figure 10.2 Trends in childhood vaccinations . 186 Figure 10.3 Vaccination coverage by mother’s education . 186 Figure 10.4 Vaccination coverage by region . 187 Figure 10.5 Diarrhoea prevalence by age . 189 Figure 10.6 Feeding practices during diarrhoea . 190 Figure 10.7 Treatment of diarrhoea . 191 Figure 10.8 Prevalence and treatment of childhood illness . 192 Tables and Figures • xiii 11 NUTRITION OF CHILDREN AND WOMEN . 209 Table 11.1 Nutritional status of children . 221 Table 11.2 Initial breastfeeding . 223 Table 11.3 Breastfeeding status by age . 224 Table 11.4 Reasons for not breastfeeding or stopping breastfeeding . 224 Table 11.5 Median duration of breastfeeding . 225 Table 11.6 Foods and liquids consumed by children in the day or night preceding the interview . 226 Table 11.7 Minimum acceptable diet . 227 Table 11.8 Micronutrient intake among children . 229 Table 11.9 Nutritional status of women . 231 Table 11.10 Micronutrient intake among mothers . 232 Figure 11.1 Stunting in children by household wealth . 212 Figure 11.2 Stunting in children by region . 212 Figure 11.3 Breastfeeding practices by age . 214 Figure 11.4 IYCF Indicators on Breastfeeding Status . 214 Figure 11.5 IYCF indicators on Minimum Acceptable Diet (MAD) . 217 Figure 11.6 Nutrition status of women . 218 Figure 11.7 Trends in women’s nutritional status . 219 12 MALARIA . 233 Table 12.1 Household possession of mosquito nets . 237 Table 12.2 Source of mosquito nets . 238 Table 12.3 Access to an insecticide-treated net (ITN) . 239 Table 12.4 Access to an ITN by background characteristics . 239 Table 12.5 Use of mosquito nets by persons in the household . 240 Table 12.6 Use of existing ITNs . 241 Table 12.7 Use of mosquito nets by children . 242 Table 12.8 Use of mosquito nets by pregnant women . 243 Table 12.9 Source of advice or treatment for children with fever . 244 Table 12.10 Type of antimalarial drugs used . 244 Figure 12.1 ITN ownership by household wealth . 234 Figure 12.2 Source of ITNs . 235 13 HIV/AIDS-RELATED KNOWLEDGE, ATTITUDES, AND BEHAVIOUR . 245 Table 13.1 Knowledge of HIV or AIDS . 252 Table 13.2 Knowledge of HIV prevention methods . 253 Table 13.3 Comprehensive knowledge about HIV . 254 Table 13.4 Knowledge of prevention of mother-to-child transmission of HIV . 254 Table 13.5 Discriminatory attitudes towards people living with HIV . 255 Table 13.6.1 Coverage of prior HIV testing: Women . 256 Table 13.6.2 Coverage of prior HIV testing: Men . 257 Table 13.7 Self-reported prevalence of sexually transmitted infections (STIs) and STI symptoms . 258 Table 13.8 Women and men seeking treatment for STIs . 259 Table 13.9 Comprehensive knowledge about HIV among young people . 259 Table 13.10 Age at first sexual intercourse among young people . 260 Table 13.11 Recent HIV tests among young people . 260 Table 13.12 Knowledge regarding treatment of HIV . 261 Figure 13.1 Knowledge of HIV prevention methods by education . 246 Figure 13.2 Knowledge of mother-to-child transmission (MTCT) . 247 Figure 13.3 Discriminatory attitudes* towards people living with HIV by education . 248 xiv • Tables and Figures 14 DISABILITY . 263 Table 14.1 Disability by domain and age . 266 Table 14.2.1 Disability among adults according to background characteristics: Women . 267 Table 14.2.2 Disability among adults according to background characteristics: Men . 268 Figure 14.1 A lot of difficulty or no ability at all in at least one domain . 264 Figure 14.2 A lot of difficulty or no ability at all in at least one domain by education . 265 15 WOMEN’S EMPOWERMENT . 269 Table 15.1 Employment and cash earnings of currently married women and men . 280 Table 15.2.1 Control over women’s cash earnings and relative magnitude of women’s cash earnings . 281 Table 15.2.2 Control over men’s cash earnings . 282 Table 15.3 Women’s control over their own earnings and over those of their husbands . 283 Table 15.4 Inheriting of land or house . 284 Table 15.5.1 Ownership of assets: Women . 285 Table 15.5.2 Ownership of assets: Men . 286 Table 15.6.1 Ownership of title or deed for house: Women . 287 Table 15.6.2 Ownership of title or deed for house: Men . 288 Table 15.7.1 Ownership of title or deed for land: Women . 289 Table 15.7.2 Ownership of title or deed for land: Men . 290 Table 15.8.1 Ownership and use of bank accounts and mobile phones: Women . 291 Table 15.8.2 Ownership and use of bank accounts and mobile phones: Men . 292 Table 15.9 Participation in decision making . 293 Table 15.10.1 Women’s participation in decision making by background characteristics . 294 Table 15.10.2 Men’s participation in decision making by background characteristics . 295 Table 15.11.1 Attitude toward wife beating: Women . 296 Table 15.11.2 Attitude toward wife beating: Men . 297 Table 15.12 Attitudes toward negotiating safer sexual relations with husband . 298 Table 15.13 Ability to negotiate sexual relations with husband . 299 Table 15.14 Indicators of women’s empowerment . 300 Table 15.15 Current use of contraception by women’s empowerment . 300 Table 15.16 Ideal number of children and unmet need for family planning by women’s empowerment . 301 Table 15.17 Reproductive health care by women’s empowerment . 301 Table 15.18 Early childhood mortality rates by women’s empowerment . 302 Figure 15.1 Employment by age . 270 Figure 15.2 Control over women’s earnings . 271 Figure 15.3 Ownership of assets . 273 Figure 15.4 Women’s participation in decision making . 275 Figure 15.5 Attitudes towards wife beating . 276 16 DOMESTIC VIOLENCE . 303 Table 16.1 Experience of physical violence . 313 Table 16.2 Experience of violence during pregnancy . 314 Table 16.3 Persons committing physical violence . 315 Table 16.4 Experience of sexual violence . 316 Table 16.5 Age at first experience of sexual violence . 317 Table 16.6 Persons committing sexual violence . 317 Table 16.7 Experience of different forms of violence . 317 Table 16.8 Marital control exercised by husbands . 318 Table 16.9 Forms of spousal violence . 319 Table 16.10 Spousal violence by background characteristics . 320 Tables and Figures • xv Table 16.11 Spousal violence by husband’s characteristics and empowerment indicators . 321 Table 16.12 Violence by any husband in the last 12 months . 322 Table 16.13 Experience of spousal violence by duration of marriage . 323 Table 16.14 Injuries to women due to spousal violence . 323 Table 16.15 Consequences of violence . 323 Table 16.16 Help seeking to stop violence . 324 Table 16.17 Sources for help to stop the violence . 325 Table 16.18 Reasons that encouraged women to seek help . 325 Table 16.19 Consequences faced for seeking help . 326 Table 16.20 Reasons for not seeking help . 326 Figure 16.1 Women’s experience of violence by marital status . 305 Figure 16.2 Violence during pregnancy by number of living children. 305 Figure 16.3 Forms of spousal violence . 308 Figure 16.4 Spousal violence by region . 309 Figure 16.5 Spousal violence by husband’s alcohol consumption . 309 Figure 16.6 Help seeking by type of violence experienced . 311 17 MIGRATION . 327 Table 17.1 Status of in-migration/immigration in household . 336 Table 17.2 Inter- and intra-regional migration: Place of birth . 337 Table 17.3 Inter- and intra-regional migration: Place of current residence . 337 Table 17.4 Rural-urban in-migration . 337 Table 17.5 Age of in-migrants . 338 Table 17.6 Reasons for in-migrating . 338 Table 17.7 Reasons for in-migrating by sex . 338 Table 17.8 Reasons for in-migrating by age . 339 Table 17.9 Households reporting out-migrants . 339 Table 17.10 Inter- and intra-province out-migration . 340 Table 17.11 Rural-urban out-migration . 340 Table 17.12 Age of out-migrants . 340 Table 17.13 Reasons for out-migrating . 341 Table 17.14 Households reporting an emigrant . 341 Table 17.15 Destination of emigrants . 342 Table 17.16 Characteristics of emigrants . 342 Table 17.17 Reasons for emigrating . 343 Table 17.18 Remittances from out-migrants and emigrants . 343 Figure 17.1 Current residence of in-migrants . 330 Figure 17.2 Sex composition of in-migrants . 331 Figure 17.3 Place of destination of out-migrants by sex . 332 APPENDIX A SAMPLE DESIGN . 347 Table A.1 Number of enumeration blocks by region and by type of residence . 348 Table A.2 Sample allocation of enumeration blocks and households by province and by type of residence . 349 Table A.3 Sample allocation of expected women and men interviews by province and by type of residence . 349 Table A.4 Sample implementation: Women . 350 Table A.5 Sample implementation: Men . 351 APPENDIX B ESTIMATES OF SAMPLING ERRORS . 355 Table B.1 List of selected variables for sampling errors, Pakistan DHS 2017-18 . 358 Table B.2 Sampling errors: Total sample, Pakistan DHS 2017-18 . 359 Table B.3 Sampling errors: Urban sample, Pakistan DHS 2017-18 . 360 Table B.4 Sampling errors: Rural sample, Pakistan DHS 2017-18 . 361 Table B.5 Sampling errors: Punjab sample, Pakistan DHS 2017-18 . 362 xvi • Tables and Figures Table B.6 Sampling errors: Punjab Urban sample, Pakistan DHS 2017-18 . 363 Table B.7 Sampling errors: Punjab Rural sample, Pakistan DHS 2017-18 . 364 Table B.8 Sampling errors: Sindh sample, Pakistan DHS 2017-18 . 365 Table B.9 Sampling errors: Sindh Urban sample, Pakistan DHS 2017-18 . 366 Table B.10 Sampling errors: Sindh Rural sample, Pakistan DHS 2017-18 . 367 Table B.11 Sampling errors: Khyber Pakhtunkhwa sample, Pakistan DHS 2017-18 . 368 Table B.12 Sampling errors: Khyber Pakhtunkhwa Urban sample, Pakistan DHS 2017-18 . 369 Table B.13 Sampling errors: Khyber Pakhtunkhwa Rural sample, Pakistan DHS 2017-18 . 370 Table B.14 Sampling errors: Balochistan sample, Pakistan DHS 2017-18 . 371 Table B.15 Sampling errors: Balochistan Urban sample, Pakistan DHS 2017-18 . 372 Table B.16 Sampling errors: Balochistan Rural sample, Pakistan DHS 2017-18 . 373 Table B.17 Sampling errors: ICT Islamabad sample, Pakistan DHS 2017-18 . 374 Table B.18 Sampling errors: FATA sample, Pakistan DHS 2017-18 . 375 Table B.19 Sampling errors: Gilgit Baltistan sample, Pakistan DHS 2017-18. 376 Table B.20 Sampling errors: Azad Jammu and Kashmir sample, Pakistan DHS 2017-18 . 377 Table B.21 Sampling errors: Azad Jammu and Kashmir Urban sample, Pakistan DHS 2017-18 . 378 Table B.22 Sampling errors: Azad Jammu and Kashmir Rural sample, Pakistan DHS 2017-18 . 379 APPENDIX C DATA QUALITY TABLES . 381 Table C.1.1 Household age distribution . 381 Table C.1.2 Household age distribution – Azad Jammu and Kashmir . 382 Table C.1.3 Household age distribution – Gilgit Baltistan . 383 Table C.2.1.1 Age distribution of eligible and interviewed women . 383 Table C.2.1.2 Age distribution of eligible and interviewed women – Azad Jammu and Kashmir . 384 Table C.2.1.3 Age distribution of eligible and interviewed women – Gilgit Baltistan . 384 Table C.2.2.1 Age distribution of eligible and interviewed men . 385 Table C.2.2.2 Age distribution of eligible and interviewed men – Azad Jammu and Kashmir . 385 Table C.2.2.3 Age distribution of eligible and interviewed men – Gilgit Baltistan . 386 Table C.3.1 Completeness of reporting . 386 Table C.3.2 Completeness of reporting – Azad Jammu and Kashmir . 387 Table C.3.3 Completeness of reporting – Gilgit Baltistan . 387 Table C.4.1 Births by calendar years . 388 Table C.4.2 Births by calendar years – Azad Jammu and Kashmir . 388 Table C.4.3 Births by calendar years – Gilgit Baltistan . 389 Table C.5.1 Reporting of age at death in days . 389 Table C.5.2 Reporting of age at death in days – Azad Jammu and Kashmir . 390 Table C.5.3 Reporting of age at death in days – Gilgit Baltistan . 390 Table C.6.1 Reporting of age at death in months. 391 Table C.6.2 Reporting of age at death in months – Azad Jammu and Kashmir . 391 Table C.6.3 Reporting of age at death in months – Gilgit Baltistan . 392 Table C.7.1 Height and weight data completeness and quality for children . 393 Table C.7.2 Height and weight data completeness and quality for children – Azad Jammu and Kashmir . 394 Table C.7.3 Height and weight data completeness and quality for children – Gilgit Baltistan . 395 APPENDIX D ACCESS TO SERVICES IN RURAL COMMUNITIES . 397 Table D.1 Availability of services in rural areas . 397 Table D.2 Availability of services in rural areas of Azad Jammu and Kashmir . 398 Table D.3 Availability of services in rural areas of Gilgit Baltistan . 399 Foreword • xvii FOREWORD he 2017-18 Pakistan Demographic and Health Survey (PDHS) is the fourth survey conducted as part of the DHS international series. The National Institute of Population Studies (NIPS), a leading research organisation in the field of population and development, successfully completed the PDHS with technical support from ICF and the Pakistan Bureau of Statistics (PBS) and financial support from the United States Agency for International Development (USAID). The overall objective of the 2017-18 PDHS was to collect high-quality data on fertility levels and preferences, contraceptive use, maternal and child health, infant mortality levels, immunisation, nutritional status of mothers and children, disability, migration, women’s empowerment, domestic violence, awareness and behaviour regarding HIV/AIDS, and other health-related issues. The primary goal was to provide information needed by health and family planning programmes for evidence-based planning and to offer guidelines to programme managers and policymakers so that they can effectively plan and implement future interventions. The 2017-18 PDHS also provides updates on data already collected through censuses and other sources. The successful completion of the project demonstrates the spirit of teamwork. The professional contributions of and assistance by the Technical Advisory Committee (TAC) at different stages of the survey are greatly appreciated. Special appreciation and congratulations are extended to the PDHS core team for their untiring efforts, dedication, and determination, which led to the generation and compilation of accurate and reliable data. I appreciate how Dr. Mukhtar Ahmed and Mr. Pervaiz Ahmed Junejo, former executive directors of the Institute, initiated and conducted the project, and created an environment for team work at NIPS. They brought together health and population experts from all over the country and steered the implementation of the project as a consultative process. On behalf of NIPS and the Ministry of National Health Services, Regulations and Coordination (NHSRC), I thank the United States Agency for International Development for providing financial support through ICF, the Department for International Development (DFID), and the United Nations Population Fund (UNFPA). I would like to express gratitude to all governmental and nongovernmental organisations for extending the required support for the 2017-18 PDHS. Khizar Hayat Khan Executive Director National Institute of Population Studies, Ministry of National Health Services, Regulations and Coordination, Government of Pakistan Islamabad T Acknowledgements • xix ACKNOWLEDGEMENTS he 2017-18 Pakistan Demographic and Health Survey (PDHS) is the result of the ceaseless efforts of individuals and organisations. The survey was conducted under the aegis of the Ministry of National Health Services, Regulations and Coordination, and implemented by the National Institute of Population Studies (NIPS). The United States Agency for International Development provided financial support through ICF. The United Nations Population Fund (UNFPA) and Department for International Development (DFID) provided logistic support for monitoring the fieldwork of the survey. The Pakistan Bureau of Statistics (PBS) provided assistance in the selection of the sample and household listing for the sampled primary sampling units. Technical assistance for the survey was provided by ICF. NIPS is highly indebted to all of these agencies. The NIPS core team expresses our deep sense of appreciation to the technical experts in the fields of population and health for their valuable contributions during various phases of the survey, including the finalisation of questionnaires, reviewing the preliminary results, and providing valuable comments and finalising the report. The guidance provided by the Technical Advisory Committee is highly appreciated. The fieldwork of the survey spanned a 6-month period during which the entire staff of NIPS and the fieldwork force worked relentlessly with devotion and commitment. The efforts of the core team, including Ms. Azra Aziz, Director (Research and Survey); Mr. Ali Anwar Buriro and Ms. Rabia Zafar, Research Fellows; Dr. G. M. Arif, Principle Investigator; Mr. Zafar Zahir, Advisor of Operations; Mr. Moiz Agha, Office Coordinator; and Ms. Mehar Nisha, Research Associate, were instrumental in organizing a disciplined listing and training programme, dispatching questionnaires to the data collection teams, managing the completed questionnaires, and tracking their movement. I acknowledge the contribution of each one with appreciation. Monitoring the fieldwork of the survey was an arduous job also assigned to the core team members. Each one of them showed commitment and devotion, and I appreciate their contribution. The administrative and financial staff of NIPS made it possible to release funds on time and make logistic arrangements for the fieldwork. The support of Mr. Zafar Iqbal Niazi, Mr. Asif Amin Khan, and Mr. Hammad Ali Syed, and the financial management of Mr. Muhammad Arif, Accounts Officer, Mr. Shakeel Ahmad and Mr. Ali Asghar, Account Support, are appreciated. I am highly thankful to Ms. Anjushree Pradhan, Senior Technical Specialist at ICF, who was a source of inspiration and encouragement throughout the survey operation. I acknowledge, with deep gratitude and thanks, the relentless and committed efforts of Ms. Pradhan, who provided immense moral support and technical assistance at each stage of the project. I am thankful to Mr. Ruben Hume, Data Processing Consultant, Dr. Ruilin Ren, Senior Sampling Statistician, and the entire ICF team for their support. Special thanks go to Mr. Mohammad Ali Raza, Ms. Gulnaz Mushtaq, Mr. Qamar, Farman Ali, and the data entry operators for all work on data entry and processing. I appreciate and acknowledge the untiring efforts, interest, and dedication of Mr. Khizar Hayat (Executive Director) who encouraged and helped the core team put in their best effort and complete the survey on time. I express my gratitude for his sincere leadership and professional approach. Dr. Aysha Sheraz Senior Fellow Deputy Project Director, PDHS T 2017-18 Pakistan Demographic and Health Survey Technical Advisory Committee • xxi 2017-18 PAKISTAN DEMOGRAPHIC AND HEALTH SURVEY TECHNICAL ADVISORY COMMITTEE Mr. Khizar Hayat Khan, Executive Director, NIPS Chairperson Mr. Pervaiz Ahmed Junejo, Former Executive Director, NIPS Member Mr. Muhammad Ali Shahzada, Additional Secretary, MNHSRC Member Dr. Asad Hafeez, Director General, MNHSRC Member Dr. Huma Qureshi, Former Executive Director, PHRC Member Mr. Habib Ullah Khan, Member, Pakistan Bureau of Statistics Member Mr. Qamar Abbas, Chief, Population and Social Sector Planning Member Ms. Khawar Mumtaz, National Commission for Status of Women Member Dr. Ismat Tahira, Secretary, Population Welfare Department, Government of Punjab Member Mr. Laiq Ahmed, Secretary, Population Welfare Department, Government of Sindh Member Mr. Fazal Nabi Khan, Secretary, Population Welfare Department, Member Government of Khyber Pakhtunkhwa Mr. Ashrafullah Kakar, Secretary, Population Welfare Department, Member Government of Balochistan Mr. Saeedullah Khan Niazi, Secretary, Health and Population Welfare Department, Member Government of Gilgit Baltistan Mr. Zahid Khan Abbasi, Secretary, Population Welfare Department, Government of AJK Member Mr. Najam Ahmed Shah, Secretary, Specialized Healthcare & Medical Education Member Department, Government of the Punjab Dr. Fazalullah Peechuho, Secretary, Health Department, Government of Sindh Member Mr. Muhammad Abid Majeed, Secretary, Health Department, Member Government of Khyber Pakhtunkhwa Mr. Noor-ul-Haq Baloch, Secretary, Department of Health, Government of Balochistan Member Secretary, Health Department – Azad Jammu and Kashmir Member Dr. Zeba A Sathar, Country Director, The Population Council Member Dr. Tauseef Ahmad, Former Senior Technical Advisor, Member The Pathfinder International Pakistan Office Mr. Muzaffar Mahmood Qureshi, Resident Director, Green Star Social Marketing Member Dr. Durr-e-Nayab, Joint Director, PIDE, Quaid-e-Azam University Member Prof. Dr. Shahzad Ali Khan, Head, Department of Management Sciences, Member Health Services Academy, MNHSRC Dr. Nabeela Ali, Chief of Party, JSI Research & Training Institute, Inc. Member Syed Kamal Shah, Chief Executive Officer, FPAP Rahnuma Member Dr. Farid Midhet, Country Director, JHPIEGO Member Ms. Asma Balal, Country Director, Marie Stopes Society (INGO) Member xxii • 2017-18 Pakistan Demographic and Health Survey Technical Advisory Committee Dr. Yasmeen Sabeh Qazi, Senior Country Advisor, Population Program, Member The David and Lucile Packard Foundation Dr. Arshad Mahmood, Deputy Chief of Party, Health Systems Strengthening Member Component, USAID’s MCH Program Dr. Zareef Khan, Consultant, JSI Member Dr. Muhammad Isa, Senior Technical Advisor, Health Office USAID Member Dr. Hassan Mohtashami, Country Representative, UNFPA Member Mr. Andy Murray, DFID, British High Commission Member Ms. Melanie Galvin, Chief (Nutrition), Pakistan Country Officer, UNICEF Member Dr. Rubina Ali, Country Representative, Rutgers – Pakistan Member Country Representative, UNDP Member Country Representative, WHO Office Member Country Director, World Food Programme Member Country Representative, World Population Foundation Member Country Representative, Food & Agriculture Organization, (FAO-UN) Member Country Representative, UN-Women, Pakistan Member Country Representative, Global Funds for Women (INGO) Member Syed Mazhar H. Hashmi, Former DDG, Pakistan Bureau of Statistics Member Dr. Sadiqua N. Jafarey, President, National Committee on Maternal Health Member Dr. Rashida Pandezai, Chairperson, Mahec Helping Council for Community Member Development and Welfare Balochistan Dr. Adnan A. Khan, Chief Knowledge Officer, Research & Development Solutions Member Syed Mubashir Ali, Freelance Consultant Member Dr. G. M. Arif, Principal Investigator PDHS, NIPS Member Dr. Naushin Mahmood, Advisor, Pakistan Centre for Philanthropy Member Ms. Azra Aziz, Director, Research and Survey, NIPS Member Dr. Aysha Sheraz, Senior Fellow/Deputy Project Director, PDHS Secretariat Contributors to the Report • xxiii CONTRIBUTORS TO THE REPORT Mr. Pervaiz Ahmed Junejo, Executive Director, NIPS Ms. Azra Aziz, Director, Research and Survey, NIPS Dr. Aysha Sheraz, Senior Fellow/Deputy Project Director, PDHS/NIPS Mr. Ali Anwar Buriro, Fellow, NIPS Ms. Rabia Zafar, Fellow, NIPS Ms. Rizwana Timsal, Research Associate, NIPS Dr. Ghulam Muhammad Arif, Principle Investigator, PDHS/NIPS Mr. Zafar Zahir, Advisor of Operations, PDHS/NIPS Mr. Moiz Agha, Office Coordinator, PDHS/NIPS Ms. Gulnaz Mushtaq, DES/NA, PDHS/NIPS Ms. Mehar Nisha, Research Associate, PDHS/NIPS Ms. Samia Asif, OE, PDHS/NIPS Ms. Aysha Gull, OE, PDHS/NIPS Dr. Farid Midhet, Freelance Consultant Dr. Tauseef Ahmed, Freelance Consultant Dr. Naushin Mahmood, Freelance Consultant Dr. Mumtaz Esker, Freelance Consultant Dr. Zareef Uddin Khan, Consultant JSI, USAID MCH Programme Dr. Adnan Khan, Chief Knowledge Officer, RDS-NGO Dr. Najma, Javaid, Senior Medical Officer, PHRC Mr. Mubashir Ali, Principal Investigator, 2012-13 PDHS Mr. Zahir Hussain, Deputy Director, BISP Mr. Minhaj Ul Haq, Freelance Consultant Acronyms and Abbreviations • xxv ACRONYMS AND ABBREVIATIONS ACT artemisinin-based combination therapy AIDS acquired immunodeficiency syndrome AJK Azad Jammu and Kashmir AL artemether + lumefantrine ANC antenatal care ARI acute respiratory infection ART antiretroviral therapy AS+SP artesunate + sulfadoxine-pyrimethamine ASFR age-specific fertility rate BCG Bacille-Calmette-Guerin vaccine against tuberculosis BISP Benazir Income Support Programme BMI body mass index CAFE computer-assisted field editing CBR crude birth rate CEB children ever born CI confidence interval CNIC computerized national identity card CPR contraceptive prevalence rate CSO civil society organization CSPro Censuses and Surveys Processing DFID Department for International Development DHS Demographic and Health Survey DPT diphtheria, pertussis, and tetanus vaccine EB enumeration block EmONC emergency obstetric and newborn care EPI Expanded Programme on Immunisation FATA Federally Administered Tribal Areas FP family planning GAR gross attendance ratio GB Gilgit Baltistan GBV gender-based violence GFR general fertility rate GMAP global malaria plan of action GoP Government of Pakistan GPI gender parity index GTS global technical strategy HepB hepatitis B Hib Haemophilus influenzae type B HIV human immunodeficiency virus xxvi • Acronyms and Abbreviations ICT Islamabad Capital Territory IDP internally displaced population IFSS internet file streaming system ILO International Labour Organisation IMNCI integrated management of newborn and childhood illness IPV inactivated polio vaccine ITN insecticide-treated net IU international unit IUD intrauterine device IYCF infant and young child feeding LAM lactational amenorrhea method LHV lady health visitor LHW lady health worker LLIN long-lasting insecticide-treated net LPG liquid petroleum gas MAD minimum acceptable diet MCH maternal and child health MDG millennium development goals MNCH maternal, neonatal and child health MoNHSRC Ministry of National Health Services, Regulation and Coordination MTCT mother-to-child transmission NACP National AIDS Control Programme NADRA National Database and Registration Authority NAR net attendance ratio NGO nongovernmental organisation NIH National Institutes of Health NIPS National Institute of Population Studies NN neonatal mortality OPV oral polio vaccine ORS oral rehydration salts ORT oral rehydration therapy PBS Pakistan Bureau of Statistics PCV pneumococcal conjugate vaccine PDHS Pakistan Demographic and Health Survey PLHIV people living with HIV PNC postnatal care PNN postneonatal mortality PPS probability proportional to size PSU primary sampling unit RHF recommended homemade fluids SD standard deviation SDGs sustainable development goals SDM standard days method STI sexually transmitted infection Acronyms and Abbreviations • xxvii TB tuberculosis TFR total fertility rate UK United Kingdom UNAIDS Joint United Nations Programme on HIV/AIDS UNDP United National Development Programme UNFPA United Nations Population Fund UNICEF United Nations Children’s Fund USAID United States Agency for International Development VAD vitamin A deficiency VIP ventilated improved pit WG Washington Group WHO World Health Organization Reading and Understanding Tables from the 2017-18 PDHS • xxix READING AND UNDERSTANDING TABLES FROM THE 2017-18 PAKISTAN DEMOGRAPHIC AND HEALTH SURVEY (PDHS) he new format of the 2017-18 PDHS 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 regions in Pakistan. 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, PDHS data users should be comfortable reading and interpreting tables. The following pages provide an introduction to the organisation of PDHS 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 PDHS tables. T xxx • Reading and Understanding Tables from the 2017-18 PDHS 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 ever-married women age 15-49 who are exposed to specific media on a weekly basis, according to background characteristics, Pakistan DHS 2017-18 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 3.3 38.1 4.5 0.3 58.1 600 20-24 4.7 49.1 4.1 0.8 48.8 1,889 25-29 4.9 52.9 4.1 0.5 44.8 2,548 30-34 5.4 53.1 2.7 0.4 44.5 2,413 35-39 5.2 51.2 3.6 0.3 46.1 2,163 40-44 5.8 52.0 3.7 0.4 45.2 1,437 45-49 5.2 46.7 4.0 0.6 50.5 1,316 Residence Urban 8.7 70.7 3.2 0.6 27.2 4,550 Rural 3.0 38.9 4.0 0.4 58.4 7,814 Education No education 0.2 31.7 3.7 0.0 66.0 6,080 Primary 4.3 57.5 3.5 0.2 39.5 2,037 Middle 5.7 67.5 4.2 0.5 30.5 1,160 Secondary 9.2 74.4 3.8 1.2 22.8 1,463 Higher 20.0 78.9 3.3 1.7 18.2 1,624 Wealth quintile Lowest 0.5 14.2 3.4 0.0 83.4 2,258 Second 1.2 32.0 4.1 0.2 64.4 2,430 Middle 2.4 53.3 4.5 0.2 44.2 2,504 Fourth 7.0 69.6 3.1 0.7 28.6 2,594 Highest 13.5 78.2 3.4 1.2 19.5 2,579 Region Punjab 5.2 60.3 2.2 0.5 38.4 6,630 Urban 7.7 74.9 2.0 0.5 23.6 2,402 Rural 3.7 52.0 2.3 0.4 46.9 4,228 Sindh 6.6 51.6 3.9 0.6 46.7 2,850 Urban 10.7 71.5 3.7 0.8 26.7 1,527 Rural 1.8 28.5 4.0 0.4 69.8 1,323 Khyber Pakhtunkhwa 3.3 26.9 4.4 0.3 69.0 1,901 Urban 7.7 53.6 3.9 0.1 41.9 366 Rural 2.2 20.6 4.5 0.4 75.4 1,535 Balochistan 2.9 28.0 14.4 0.3 59.7 642 Urban 6.9 44.8 11.2 0.8 47.8 188 Rural 1.3 21.1 15.8 0.1 64.6 454 ICT Islamabad 16.1 77.5 6.1 2.4 20.0 107 FATA 0.7 5.6 8.6 0.0 86.8 234 Total1 5.1 50.6 3.7 0.5 46.9 12,364 Azad Jammu Kashmir 6.7 51.2 5.3 0.8 45.9 1,720 Urban 9.8 66.6 3.9 0.6 31.6 292 Rural 6.0 48.1 5.6 0.9 48.9 1,428 Gilgit Baltistan 3.9 43.5 2.5 0.1 55.5 984 1 Total excludes Azad Jammu and Kashmir and Gilgit Baltistan. 1 2 3 4 6 5 Reading and Understanding Tables from the 2017-18 PDHS • xxxi Step 1: Read the title and subtitle, highlighted in orange in the table above. They tell you the topic and the specific population group being described. In this case, the table is about ever-married women age 15-49 and their exposure to different types of media. All eligible ever-married 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 categorised. In this table, the first three columns of data show different types of media that ever-married women access at least once a week. The fourth column shows ever-married women who access all three types of media, while the fifth column shows ever-married women who do not access any of the three types of media on a weekly basis. The last column lists the number of ever-married 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 ever-married women’s exposure to media by age, urban-rural residence, level of education, wealth quintile, and region. Regions are further divided into urban-rural residence. Most of the tables in the PDHS report will be divided into these same categories. Step 4: Look at the row near the bottom of the table highlighted in pink. These percentages represent the totals (excluding Azad Jammu and Kashmir and Gilgit Baltistan) of all ever-married women age 15-49 and their weekly access to different types of media. In this case, 5.1%* of ever-married women age 15-49 read a newspaper at least once a week, 50.6% watch television at least weekly, and 3.7% listen to the radio on a weekly basis. Step 5: Scan the last four rows highlighted in grey in Example 1. While the 2017-18 PDHS collected data in Azad Jammu and Kashmir and Gilgit Baltistan, those data are not included in the national total or the background characteristics. The data for these regions are presented separately in the last four rows. For more information on sampling, see Example 3. Step 6: To find out what percentage of ever-married women with higher education watch television at least once a week, draw two imaginary lines, as shown on the table. This shows that 78.9% of ever-married women age 15-49 with higher education watch television on a weekly basis. By looking at patterns by background characteristics, we can see how exposure to mass media varies across Pakistan. Mass media are often used to communicate health messages. Knowing how mass media exposure varies among different groups can help programme planners and policy makers 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. xxxii • Reading and Understanding Tables from the 2017-18 PDHS Practice: Use the table in Example 1 to answer the following questions: a) What percentage of ever-married women in Pakistan do not access any of the three media at least once a week? b) Which age group of ever-married women are most likely to watch television at least once a week? c) Compare ever-married women in urban areas to rural areas – which group is more likely to read a newspaper weekly? d) What are the lowest and highest percentages (range) of ever-married women who do not access any of the three media at least once a week by region? e) Is there a clear relationship in exposure to newspapers on a weekly basis by education level? f) Is there a clear relationship in exposure to television on a weekly basis by wealth quintile? Answers: a) 46.9% b) Ever-married women age 30-34: 53.1% of ever-married women in this age group watch television on a weekly basis. c) Ever-married women in urban areas, 8.7% read a newspaper weekly, compared to 3.0% of ever-married women in rural areas. d) Ever-married women with no exposure to media ranges from a low of 20.0% in ICT Islamabad to a high of 86.8% in FATA. e) Exposure to newspapers on a weekly basis increases as a women’s level of education increases; 0.2% of ever-married women with no education read a newspaper on a weekly basis, compared to 20.0% of ever-married women with higher education. f) Exposure to television on a weekly basis increases as household wealth increases; 14.2% of ever-married women from the lowest wealth quintile watch television on a weekly basis, compared to 78.2% of ever-married women from the highest wealth quintile. Reading and Understanding Tables from the 2017-18 PDHS • xxxiii Example 2 – Prevalence and Treatment of Symptoms 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, Pakistan DHS 2017-18 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 Percentage who took antibiotic drugs Number of children Age in months <6 13.6 1,147 82.1 53.4 34.2 156 6-11 17.4 817 89.1 54.3 43.9 142 12-23 16.6 1,975 87.5 56.9 46.9 328 24-35 12.5 1,919 77.9 41.7 48.3 241 36-47 14.5 1,960 83.9 48.3 49.4 283 48-59 10.3 1,982 85.4 50.6 50.1 203 Sex Male 14.1 4,874 84.4 50.8 45.3 685 Female 13.6 4,926 84.1 50.7 47.4 668 Mother's smoking status Smokes cigarettes/tobacco 17.9 452 70.4 22.6 31.1 81 Does not smoke 13.6 9,345 85.1 52.6 47.3 1,272 Cooking fuel Electricity or gas 12.6 4,409 89.3 61.0 49.8 555 Coal/lignite * 11 * * * 0 Charcoal 8.1 196 * * * 16 Wood/straw3 15.3 4,777 79.8 44.2 44.1 731 Animal dung 12.1 404 (90.1) (34.6) (45.8) 49 No food cooked in household * 2 * * * 2 Residence Urban 12.8 3,173 87.4 57.4 46.1 407 Rural 14.3 6,627 82.8 47.9 46.5 946 Mother's education No education 14.1 4,750 80.7 42.7 45.1 672 Primary 16.7 1,614 85.2 55.7 41.0 269 Middle 14.6 930 86.9 54.5 40.2 136 Secondary 12.9 1,224 88.9 64.8 58.1 158 Higher 9.3 1,282 92.2 62.0 57.0 119 Wealth quintile Lowest 15.2 2,183 73.9 36.0 40.8 331 Second 16.7 1,933 83.8 45.6 41.9 323 Middle 13.8 2,043 88.3 56.6 52.4 283 Fourth 11.3 1,898 89.1 57.5 47.0 215 Highest 11.6 1,742 90.7 67.9 53.4 202 Region Punjab 13.0 5,104 86.1 60.9 46.4 662 Urban 12.3 1,657 89.0 65.0 44.1 204 Rural 13.3 3,447 84.8 59.1 47.4 458 Sindh 14.7 2,275 85.4 36.3 48.4 334 Urban 10.9 1,027 89.6 48.4 48.5 112 Rural 17.8 1,247 83.3 30.1 48.4 222 Khyber Pakhtunkhwa 16.3 1,592 84.3 54.2 49.5 260 Urban 20.9 283 86.4 58.0 53.9 59 Rural 15.3 1,310 83.7 53.0 48.1 201 (Continued…) 1 2 4 a b xxxiv • Reading and Understanding Tables from the 2017-18 PDHS Table 10.5—Continued 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 Percentage who took antibiotic drugs Number of children Balochistan 11.4 512 62.2 26.8 23.4 58 Urban 15.7 157 70.4 38.6 32.3 25 Rural 9.4 354 56.1 18.0 16.9 33 ICT Islamabad 9.4 74 83.6 40.2 48.7 7 FATA 13.2 243 70.6 11.1 40.4 32 Total4 13.8 9,800 84.2 50.8 46.4 1,353 Azad Jammu and Kashmir 17.0 1,314 80.8 49.1 48.9 224 Urban 14.9 194 88.7 52.9 55.3 29 Rural 17.4 1,119 79.7 48.5 48.0 195 Gilgit Baltistan 12.0 995 76.3 35.6 50.6 119 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 public sector (government hospital, rural health centre, maternal and child health centre, basic health unit, lady health worker), private medical sector (private hospital, clinic, chemist, medical store, private doctor, homeopath, dispenser, compounder, other private), shops and other. Excludes advice or treatment from a traditional practitioner. 3 Includes grass, shrubs, crop residues 4 Total excludes Azad Jammu and Kashmir and Gilgit Baltistan. Total includes 3 cases with missing information mother’s smoking status and 1 case with missing information on type of cooking fuel. Step 1: Read the title and subtitle. In this case, the table is about two separate groups of children: all children under five (a) and children under five with symptoms of ARI in the two weeks before the survey (b). Step 2: Identify the two panels. First, identify the columns that refer to all children under five (a), and then isolate the columns that refer only to children under five with symptoms of ARI in the two weeks before the survey (b). Step 3: Look at the first panel. What percentage of children under five had symptoms of ARI in the two weeks before the survey? It’s 13.8%. Now look at the second panel. How many children under five are there who had symptoms of ARI in the two weeks before the survey? It’s 1,353 children or 13.8% of the 9,800 children under five (with rounding). The second panel is a subset of the first panel. Step 4: Only 13.8% of children under five had symptoms of ARI in the two 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. • Among children whose households use animal dung for cooking fuel, what percentage of children under five who had recent symptoms of ARI had advice or treatment sought? It’s 90.1%. This percentage is in parentheses because there are between 25 and 49 unweighted cases 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.) • Among children whose households use charcoal for cooking fuel, what percentage of children under five who had recent symptoms of ARI had advice or treatment sought? There is no number in this cell—only an asterisk. This is because fewer than 25 children under five who had recent symptoms of ARI in households that use charcoal as a cooking fuel had advice or treatment sought. 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. a b 3 Reading and Understanding Tables from the 2017-18 PDHS • xxxv Example 3 – Understanding Sampling Weights in PDHS Tables A sample is a group of people who have been selected for a survey. In the PDHS, 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 2017-18 PDHS, the survey sample is representative at the national level; for urban and rural areas separately; for four provinces including Punjab, Sindh, Khyber Pakhtunkhwa, and Balochistan; for two regions including Azad Jammu and Kashmir (AJK) and Gilgit Baltistan (GB); ICT Islamabad; and FATA. In total, there are 13 second-level survey domains. To generate statistics that are representative of the Pakistan (excluding AJK and GB) and the 6 regions, the number of ever-married women surveyed in each region should contribute to the size of the total (excluding AJK and GB) sample in proportion to size of the region. However, if some regions have small populations, then a sample allocated in proportion to each region’s population may not include sufficient women from each region for analysis. To solve this problem, regions with small populations are oversampled. For example, let’s say that you have enough money to interview 12,364 ever-married women and want to produce results that are representative of Pakistan (excluding AJK and GB) and its regions (as in Table 3.1.1). However, the total population of Pakistan (excluding AJK and GB) is not evenly distributed among the regions: some regions, such as Punjab, are heavily populated while others, such as ICT Islamabad are not. Thus, ICT Islamabad must be oversampled. A sampling statistician determines how many ever-married women should be interviewed in each region in order to get reliable statistics. The blue column (1) in the table at the right shows the actual number of ever-married women interviewed in each region. Within the regions, the number of ever-married women interviewed ranges from 1,012 in FATA to 3,400 in Punjab. The number of interviews is sufficient to get reliable results in each region. With this distribution of interviews, some regions are overrepresented and some regions are underrepresented. For example, the population in Punjab is about 54% of the population in Pakistan (excluding AJK and GB), while ICT Islamabad’s population contributes only 1% of the population in Pakistan (excluding AJK and GB). But as the blue column shows, the number of ever-married women interviewed in Punjab accounts for only about 27% of the total sample of ever-married women interviewed (3,400 / 12,364) and the number of ever-married women interviewed in ICT Islamabad accounts for 9% of the total sample of ever-married women interviewed (1,111 / 12,364). This unweighted distribution of ever-married women does not accurately represent the population. In order to get statistics that are representative of Pakistan (excluding AJK and GB), the distribution of the ever-married women in the sample needs to be weighted (or mathematically adjusted) such that it resembles the true distribution in the Pakistan (excluding AJK and GB). Ever-married women from a small region, like ICT Islamabad, should only contribute a small amount to the national total. Ever-married women from a large region, like Punjab, should contribute much more. Therefore, DHS statisticians mathematically calculate a “weight” which is used to adjust the number of ever-married women from each region so that each region’s contribution to the total is proportional to the actual population of the region. 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 regional level. The total national sample size (excluding AJK and GB) of 12,364 ever-married women has not changed after weighting, but the distribution of the Table 3.1.1 Background characteristics of respondents Percent distribution of ever-married women age 15-49 by selected background characteristics, Pakistan DHS 2017-18 Women Background characteristic Weighted percent Weighted number Unweighted number Region Punjab 53.6 6,630 3,400 Sindh 23.1 2,850 2,739 Khyber Pakhtunkhwa 15.4 1,901 2,378 Balochistan 5.2 642 1,724 ICT Islamabad 0.9 107 1,111 FATA 1.9 234 1,012 Total1 100.0 12,364 12,364 1 Total excludes Azad Jammu and Kashmir and Gilgit Baltistan 1 2 3 xxxvi • Reading and Understanding Tables from the 2017-18 PDHS ever-married women in the regions has been changed to represent their contribution to the total population size (excluding AJK and GB). 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 Pakistan (excluding AJK and GB), you would see that ever-married women in each region are contributing to the total sample with the same weight that they contribute to the population of the Pakistan (excluding AJK and GB). The weighted number of ever-married women in the survey now accurately represents the proportion of ever-married women who live in Punjab and the proportion of ever-married women who live in ICT Islamabad. With sampling and weighting, it is possible to interview enough ever-married women to provide reliable statistics at national (excluding AJK and GB) and regional levels. In general, only the weighted numbers are shown in each of the PDHS tables, so don’t be surprised if these numbers seem low: they may actually represent a larger number of ever-married women interviewed. Sustainable Development Goals Indicators • xxxvii SUSTAINABLE DEVELOPMENT GOALS INDICATORS Sustainable Development Goals Indicators—Pakistan DHS 2017-18 Sex Total DHS table number Indicator Male Female 2. Zero hunger 2.2.1 Prevalence of stunting among children under 5 years of age 38.2 37.1 37.6 11.1 2.2.2 Prevalence of malnutrition among children under 5 years of age 9.9 9.2 9.5 na a) Prevalence of wasting among children under 5 years of age 7.6 6.6 7.1 11.1 b) Prevalence of overweight among children under 5 years of age 2.3 2.6 2.5 11.1 3. Good health and well-being 3.1.2 Proportion of births attended by skilled health personnel na na 69.3 9.7 3.2.1 Under-five mortality rate1 80 68 74 8.2 3.2.2 Neonatal mortality rate1 52 33 42 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 methods2 na 48.6 na 7.13.1 3.7.2 Adolescent birth rates per 1,000 women a) Girls aged 10-14 years3 na 0.0 na 5.1 b) Women aged 15-19 years4 na 46 na 5.1 3.a.1 Age-standardised prevalence of current tobacco use among persons aged 15 years and older5 22.6 4.7 13.7a 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 77.0 73.6 75.4 10.3 b) Coverage of measles containing vaccine (2nd dose)7 69.6 63.7 66.6 10.3 c) Coverage of pneumococcal conjugate vaccine (last dose in schedule)8 76.6 72.6 74.7 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 24.8 na 16.12 a) Physical violence na 13.6 na 16.12 b) Sexual violence na 3.6 na 16.12 c) Psychological violence na 20.6 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 3.6 na 4.3 b) before age 18 na 18.3 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 31.4 na 15.0 5.b.1 Proportion of individuals who own a mobile telephone12 92.7 39.2 66.0a 15.8.1, 15.8.2 Residence Total DHS table number Urban Rural 7. Affordable clean energy 7.1.1 Proportion of population with access to electricity 99.4 88.1 92.2 2.4 7.1.2 Proportion of population with primary reliance on clean fuels and technology13 87.8 25.5 48.2 2.4 Sex Total DHS table number Male Female 8. Decent work and economic growth 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 31.6 6.0 18.8a 15.8.1, 15.8.2 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 42.5 41.9 42.2 2.11 17. Partnerships for the goals 17.8.1 Proportion of individuals using the Internet15 28.4 12.0 20.2a 3.5.1, 3.5.2 Note: Table excludes Azad Jammu and Kashmir and Gilgit Baltistan na = Not applicable 1 Expressed in terms of deaths per 1,000 live births for the 5-year period preceding the survey 2 Data available for currently married women 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-standardised 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 a two doses of measles 8 The percentage of children age 12-23 months who received a 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 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 Pakistan Introduction and Survey Methodology • 1 INTRODUCTION AND SURVEY METHODOLOGY 1 he 2017-18 Pakistan Demographic and Health Survey (PDHS) was implemented by the National Institute of Population Studies (NIPS) under the aegis of the Ministry of National Health Services, Regulations and Coordination. This PDHS is the fourth to be conducted in Pakistan and follows surveys in 1990-91, 2006-07, and 2012-13. Data collection took place from 22 November 2017 to 30 April 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. Support for the survey was also provided by the Department for International Development (DFID) of the United Nations Population Fund (UNFPA). According to the Population Census of 2017, the total population of Pakistan is 207 million with a growth rate of 2.4% (Government of Pakistan 2017). The size of the population and the growth rate present serious challenges to governmental efforts to prevent food insecurity, water scarcity, rapid urbanisation, inadequate housing, and loss of economic opportunities. Such challenges necessitate regular assessment of their demographic impact through collection of reliable data in surveys such as the PDHS. 1.1 SURVEY OBJECTIVES The primary objective of the 2017-18 PDHS is to provide up-to-date estimates of basic demographic and health indicators. The PDHS provides a comprehensive overview of population, maternal, and child health issues in Pakistan. Specifically, the 2017-18 PDHS collected information on: ▪ Key demographic indicators, particularly fertility and under-5 mortality rates, at the national level, for urban and rural areas, and within the country’s eight regions ▪ Direct and indirect factors that determine levels and trends of fertility and child mortality ▪ Contraceptive knowledge and practice ▪ Maternal health and care including antenatal, perinatal, and postnatal care ▪ Child feeding practices, including breastfeeding, and anthropometric measures to assess the nutritional status of children under age 5 and women age 15-49 ▪ Key aspects of family health, including vaccination coverage and prevalence of diseases among infants and children under age 5 ▪ Knowledge and attitudes of women and men about sexually transmitted infections (STIs), including HIV/AIDS, and potential exposure to risk ▪ Women's empowerment and its relationship to reproductive health and family planning ▪ Disability level ▪ Extent of gender-based violence ▪ Migration patterns The information collected through the 2017-18 PDHS is intended to assist policymakers and program managers at the federal and provincial government levels, in the private sector, and at international organisations in evaluating and designing programs and strategies for improving the health of the country’s T 2 • Introduction and Survey Methodology population. The data also provides information on indicators relevant to the Sustainable Development Goals. 1.2 SAMPLE DESIGN The sampling frame used for the 2017-18 PDHS is a complete list of enumeration blocks (EBs) created for the Pakistan Population and Housing Census 2017, which was conducted from March to May 2017. The Pakistan Bureau of Statistics (PBS) supported the sample design of the survey and worked in close coordination with NIPS. The 2017-18 PDHS represents the population of Pakistan including Azad Jammu and Kashmir (AJK) and the former Federally Administrated Tribal Areas (FATA), which were not included in the 2012-13 PDHS1. The results of the 2017-18 PDHS are representative at the national level and for the urban and rural areas separately. The survey estimates are also representative for the four provinces of Punjab, Sindh, Khyber Pakhtunkhwa, and Balochistan; for two regions including AJK and Gilgit Baltistan (GB); for Islamabad Capital Territory (ICT); and for FATA. In total, there are 13 second- level survey domains. The 2017-18 PDHS followed a stratified two-stage sample design. The stratification was achieved by separating each of the eight regions into urban and rural areas. In total, 16 sampling strata were created. Samples were selected independently in every stratum through a two-stage selection process. Implicit stratification and proportional allocation were achieved at each of the lower administrative levels by sorting the sampling frame within each sampling stratum before sample selection, according to administrative units at different levels, and by using a probability-proportional-to-size selection at the first stage of sampling. The first stage involved selecting sample points (clusters) consisting of EBs. EBs were drawn with a probability proportional to their size, which is the number of households residing in the EB at the time of the census. A total of 580 clusters were selected. The second stage involved systematic sampling of households. A household listing operation was undertaken in all of the selected clusters, and a fixed number of 28 households per cluster was selected with an equal probability systematic selection process, for a total sample size of approximately 16,240 households. The household selection was carried out centrally at the NIPS data processing office. The survey teams only interviewed the pre-selected households. To prevent bias, no replacements and no changes to the pre-selected households were allowed at the implementing stages. Due to non-proportional sample allocation, the sample was not self-weighting. Weighting factors have been calculated, added to the data file, and applied so that results are representative at the national level for Pakistan (including FATA and ICT Islamabad) and separately for Azad Jammu and Kashmir and Gilgit Baltistan. The 2017-18 PDHS included all ever-married women age 15-49. 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 survey of men was conducted in one-third of the sample households, and all ever-married men age 15-49 in these households were included. In these households, one eligible woman in each household was randomly selected to be asked additional questions about domestic violence. Similarly, height and weight information was collected from eligible women age 15-49 and children age 0-59 months only in those households selected for the man’s survey. The survey was successfully carried out in 561 clusters, after dropping 19 clusters due to security concerns during the fieldwork. These clusters were in Balochistan (1), FATA (2), Gilgit Baltistan (6), Khyber 1 The 2017-18 PDHS presents national data totals for Pakistan that exclude Azad Jammu and Kashmir as well as Gilgit Baltistan. To compare the current data with older data from the 2012-13 PDHS (which already excluded Azad Jammu and Kashmir), the data was rerun to also exclude Gilgit Baltistan. Introduction and Survey Methodology • 3 Pakhtunkhwa (4), Azad Jammu and Kashmir (1), Punjab (2), Sindh (1) and ICT Islamabad (2 restricted areas). 1.3 QUESTIONNAIRES Six questionnaires were used in the 2017-18 PDHS: Household Questionnaire, Woman’s Questionnaire, Man’s Questionnaire, Biomarker Questionnaire, Fieldworker Questionnaire, and the Community Questionnaire. The first five 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 Pakistan. The Community Questionnaire was based on the instrument used in the previous rounds of the Pakistan DHS. Comments were solicited from various stakeholders representing government ministries and agencies, nongovernmental organisations, and international donors. The survey protocol was reviewed and approved by the National Bioethics Committee, Pakistan Health Research Council, and ICF Institutional Review Board. After the questionnaires were finalised in English, they were translated into Urdu and Sindhi. The 2017-18 PDHS used paper-based questionnaires for data collection, while computer- assisted field editing (CAFE) was used to edit the questionnaires in the field. 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 head of household. For children under age 18, survival status of parents was determined. The data on age, sex, and marital status of household members was used to identify women and men 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; ownership of mosquito nets; migration; and disability. The Woman’s Questionnaire was used to collect information from all eligible ever-married women age 15-49. These women were asked questions on the following topics: ▪ Background characteristics (including age, education, and media exposure) ▪ Pregnancy 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 ▪ Marriage and sexual activity ▪ Fertility preferences (including desire for more children, ideal number of children) ▪ Women’s work and husbands’ background characteristics ▪ Knowledge, awareness, and behaviour regarding HIV/AIDS and sexually transmitted infections ▪ (STIs) ▪ Knowledge, attitudes, and behaviour related to other health issues (e.g., smoking, tuberculosis, hepatitis) ▪ Domestic violence The Man’s Questionnaire was administered to all ever-married men age 15-49 in the subsample of households selected for the man’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 the anthropometry measurements of women and children. This questionnaire was administered only to a sub-sample selected for the men’s survey. All children 0-59 months and all ever-married women age 15-49 were eligible for height and weight measurement. 4 • Introduction and Survey Methodology The purpose of the Fieldworker Questionnaire was to collect basic background information on the people who collected data in the field (supervisor, editor, and interviewers).The questionnaire was used to record background information from the interviewers that will serve as a tool in conducting analyses of data quality. Each fieldworker completed a self-administered Fieldworker Questionnaire after the final selection of fieldworkers and before the fieldworkers entered the field. No personal identifiers are attached to each 2017-18 PDHS fieldworker’s data file. The Community Questionnaire was administered during the fieldwork to collect information about basic infrastructure in the clusters and access to health facilities and services. The Community Questionnaire was only implemented in rural clusters. Community representatives who provided information for the questionnaire included, among others, village leaders, counsellors, religious leaders, local teachers, lady health visitors, and lady health workers. 1.4 ANTHROPOMETRY In a subsample of the households selected for the man’s survey, the 2017-18 PDHS recorded height and weight measurements for children age 0-59 months and women age 15-49. Two enumerators in each field team were assigned to jointly take measurements. In contrast to the data collection procedure for the household and individual interviews, data related to anthropometry was initially recorded on the Biomarker Questionnaire and subsequently entered into interviewers' tablet computers. 1.5 PRETEST Thirty-one enumerators, eight members of the core team of the project, and two data processing personnel of NIPS participated in the training to pretest the PDHS survey protocol over a 3-week period in August 2017. Most participants had previous experience in carrying out the PDHS surveys and other household surveys. The data processing staff was included in the pretest to familiarise them with the survey instruments. ICF provided technical support for the training. In addition to discussion on the technical aspects of the survey, the pretest training was designed to train the trainers for the main training. The training focused on key components such as age probing, interviewing techniques, and procedures for completing the PDHS questionnaires by using (1) a contraceptive calendar, (2) completing the vaccination section, and (3) standardizing procedures for anthropometry. The hands-on training emphasised adult learning principles. The participants worked in groups using various training techniques, such as interactive question-and-answer sessions, case studies, and role plays. Along with the enumerators, the trainers administered the questionnaires in the field, provided feedback on the content and language of the questionnaires, and learned the various techniques of training. The fieldwork for the pretest was carried out in four locations focusing on the two language groups (Urdu and Sindhi). These locations were (1) Gujar Khan Tehsil in Rawalpindi, Punjab; (2) Haveli in Abbottabad, Khyber Pakhtunkhwa; (3) Panjaar in Kahuta Tehsil, Punjab; and (4) Sukkur in Sindh. Each team carried out the pretest in both an urban and a rural location. Following the fieldwork, a debriefing session was held with the pretest field staff. The questionnaires were modified based on lessons drawn from the exercise. 1.6 TRAINING OF FIELD STAFF The main training of the 2017-18 PDHS started on 23 October 2017 in Islamabad. The training included four weeks of orientation on data collection instruments followed by field practice. The 169 participants for the main training were selected through a strict vetting process. Applicants had to take written and computerised tests followed by a personal interview to qualify for the main training. Attendees came from different parts of Pakistan 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 PDHS. Introduction and Survey Methodology • 5 Six members of the core project staff and one data processor participated in the main training as facilitators. ICF staff provided technical support during the training sessions. The participants were divided into three classrooms of about 56 participants each. The training sessions included discussion of concepts, procedures, and methodology of conducting the DHS survey. Participants were guided through the questionnaires. In-class exercises were carried out, keeping in mind that involving participants in the training process gives them a better understanding of the training content. Various techniques were used to facilitate the training. These included role playing on filling a household schedule, age probing in pairs, consistency checking for age and date of birth, correcting errors in the pregnancy history table, filling up a contraceptive calendar with given cases, and transcribing vaccination cards. The field editors trained on using the CAFE system. The 2017-18 PDHS interviewers collected data on height and weight for eligible women and children. Two female members of each team were trained to take both measurements. The anthropometry training included lecture sessions, hands-on demonstrations, and practical exercises. Children were brought to the training venue for the participants to practice taking their measurements. After the training and practice sessions, a standardisation exercise was carried out for anthropometry, in which the designated 44 measurers weighed and measured the same group of children twice to assess the accuracy and precision of the measurements. The results of the standardisation exercise were presented. Inter-observer and intra- observer variations of the same measurements as well as the concept of accuracy and precision were explained to the participants. Those who were out of range three or more times were trained further. In addition, the supervisors and quality control staff were trained on anthropometry to equip them to monitor the fieldwork and provide appropriate feedback. Throughout the training, participants were evaluated through in-class exercises, quizzes, and observations made during field practice. At the end of the training, the 22 fieldwork teams were formed by selecting supervisors, enumerators, and field editors based on their performance. Ultimately, 22 supervisors, 88 participants, and 22 field editors were identified, while the rest of the participants were kept as reserves. The supervisors received additional training in performing supervisory activities, data quality control procedures, fieldwork coordination, and management. They learned to assign households and review the completed questionnaires. The field editors received the completed questionnaires and edited them with the CAFE system, identifying and dealing with error messages, providing feedback to the field teams, closing clusters, and transferring interviews to the central office via the secure internet file streaming system (IFSS) developed by The DHS Program. Four provincial coordinators and 13 quality controllers were trained along with the supervisors and also received additional training on supporting the teams and monitoring the fieldwork. 1.7 FIELDWORK The fieldwork of the 2017-18 PDHS was launched under close supervision from three focal points; namely, Islamabad on 22 November 2017 and Sindh and Balochistan on 23 November 2017. Fourteen teams were deployed in clusters around Islamabad, four teams in Sindh, and four teams in Balochistan. Each team consisted of one supervisor, one field editor, one male interviewer, and three female interviewers. The NIPS core team, provincial coordinators, quality controllers, and ICF staff closely monitored the teams. After fieldwork in the first clusters, teams were brought back to the central location for a review session where the teams had an opportunity to clarify any questions. The teams were then dispatched to their respective clusters. The fieldwork and data collection lasted until 30 April 2018. The fieldwork in some districts took longer than expected due to access and security challenges. As mentioned earlier, the fieldwork could not be carried out in 19 out of the 580 clusters. Fieldwork monitoring was an integral part of the 2017-18 PDHS, and several rounds were carried out by the PDHS core team, the provincial coordinators, the quality controllers, and ICF staff. The monitors were provided with guidelines for overseeing the fieldwork. The quality and progress of data collection was also 6 • Introduction and Survey Methodology monitored through weekly field check tables and dashboards generated from conducted interviews. These were sent to the central office and used to provide regular feedback to the teams. 1.8 DATA PROCESSING The processing of the 2017-18 PDHS data began simultaneously with the fieldwork. As soon as data collection was completed in each cluster, all electronic data files were transferred via IFSS to the NIPS central office in Islamabad. These data files were registered and checked for inconsistencies, incompleteness, and outliers. The field teams were alerted to any inconsistencies and errors. Secondary editing was carried out in the central office, which involved resolving inconsistencies and coding the open- ended questions. The NIPS data processing manager coordinated the exercise at the central office. The PDHS core team members assisted with the secondary editing. Data entry and editing were carried out using the CSPro software package. The concurrent processing of the data offered a distinct advantage as it maximised the likelihood of the data being error-free and accurate. The secondary editing of the data was completed in the first week of May 2018. The final cleaning of the data set was carried out by The DHS Program data processing specialist and completed on 25 May 2018. Throughout this report, numbers in the tables reflect weighted numbers. Percentages based on 25 to 49 unweighted cases are shown in parentheses. Percentages based on fewer than 25 unweighted cases are suppressed and replaced with an asterisk, thereby cautioning readers 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 2017-18 PDHS. A total of 15,671 households were selected for the survey, of which 15,051 were occupied. The response rates are presented separately for Pakistan, Azad Jammu and Kashmir, and Gilgit Baltistan. Of the 12,338 occupied households in Pakistan, 11,869 households were successfully interviewed, yielding a response rate of 96%. Similarly, the household response rates were 98% in Azad Jammu and Kashmir and 99% in Gilgit Baltistan. In the interviewed households, 94% of ever-married women age 15-49 in Pakistan, 97% in Azad Jammu and Kashmir, and 94% in Gilgit Baltistan were interviewed. In the subsample of households selected for the male survey, 87% of ever-married men age 15-49 in Pakistan, 94% in Azad Jammu and Kashmir, and 84% in Gilgit Baltistan were successfully interviewed. Overall, the response rates were lower in urban than in rural areas. The difference is slightly less pronounced for Azad Jammu and Kashmir and Gilgit Baltistan. The response rates for men are lower than those for women, as men are often away from their households for work. Introduction and Survey Methodology • 7 Table 1.1 Results of the household and individual interviews Number of households, number of interviews, and response rates, according to residence (unweighted), Pakistan DHS 2017-18 Pakistan Total Azad Jammu and Kashmir Gilgit Baltistan Result Urban Rural Urban Rural Total Urban Rural Total Household interviews Households selected 6,631 6,184 12,815 921 871 1,792 336 728 1,064 Households occupied 6,389 5,949 12,338 895 833 1,728 307 678 985 Households interviewed 6,091 5,778 11,869 877 820 1,697 304 670 974 Household response rate1 95.3 97.1 96.2 98.0 98.4 98.2 99.0 98.8 98.9 Interviews with ever-married women age 15-49 Number of eligible women 6,545 6,573 13,118 871 898 1,769 330 713 1,043 Number of eligible women interviewed 6,098 6,266 12,364 846 874 1,720 310 674 984 Eligible women response rate2 93.2 95.3 94.3 97.1 97.3 97.2 93.9 94.5 94.3 Household interviews in subsample Households selected 2,368 2,208 4,576 329 311 640 120 260 380 Households occupied 2,296 2,136 4,432 318 301 619 111 243 354 Households interviewed 2,187 2,076 4,263 313 298 611 108 242 350 Household response rate in subsample1 95.3 97.2 96.2 98.4 99.0 98.7 97.3 99.6 98.9 Interviews with ever-married men age 15-49 Number of eligible men 1,928 1,706 3,634 190 169 359 86 164 250 Number of eligible men interviewed 1,640 1,505 3,145 172 164 336 72 138 210 Eligible men response rate2 85.1 88.2 86.5 90.5 97.0 93.6 83.7 84.1 84.0 1 Households interviewed/households occupied 2 Respondents interviewed/eligible respondents Housing Characteristics and Household Population • 9 HOUSING CHARACTERISTICS AND HOUSEHOLD POPULATION 2 Key Findings ▪ Drinking water: 95% of all households have access to an improved drinking water source. Only 7% of the households use an appropriate water treatment method. ▪ Sanitation: 70% have an improved sanitation facility that is not shared with the other households; however, 25% have flush toilet linked to the septic tank. ▪ Electricity: 93% of the households have electricity. ▪ Indoor smoke: 49% of the households use solid fuel for cooking. ▪ Birth registration: 42% of children under age 5 are registered, and 36% have a birth certificate; 84% of adults age 18 and above have a National Identity Card. ▪ Education: 50% of women have no education compared with 34% of men. ▪ School attendance: Net attendance ratio (NAR) is 59% at the primary level and 38% at the middle/secondary level. nformation on the socioeconomic characteristics of the household population in the 2017-18 PDHS provides context to interpret demographic and health indicators and indicate the representativeness of the survey. In addition, this information sheds light on the living conditions of the population. This chapter presents information on household population composition, wealth, educational attainment, school attendance, birth registration, family living arrangements, and housing characteristics, including source of drinking water, sanitation, exposure to smoke inside the home, and hand washing. 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, and rainwater. Households that use bottled water for drinking are classified as using an improved source only if their water source for cooking and hand washing comes from an improved source. Sample: Households I 10 • Housing Characteristics and Household Population Improved sources of water protect against outside contamination so that water is more likely to be safe to drink. In Pakistan, almost all households (95%) have access to an improved source of drinking water (Table 2.1 and Figure 2.1). The most common source of drinking water in Pakistan is a tube well or borehole (55%), followed by piped water (24%). Tube wells or boreholes are the most common source in the both urban and rural areas (37% and 65%, respectively). Seventy-three percent of households have drinking water on their premises, and 10% of households spend more than 30 minutes to obtain water. Eighty-seven percent of households using piped water or water from a tube well or borehole reported that water was available without interruption in the past 2 weeks (Table 2.2). Availability of water without interruption was higher in rural (92%) than in urban (78%) areas. Only 7% of households follow appropriate water treatment practices prior to drinking. Appropriate treatment practices are followed more often in urban areas (15%) than in rural areas (2%) (Table 2.1). Trends: In 2017-18, 95% of households used an improved source of drinking water, as compared with 94% in 2012-13. There was also a slight decline (1%) in the use of appropriate water treatment practices, from 8% to 7%, in the same period. 2.2 SANITATION Improved toilet facilities Include any non-shared toilet of the following types: flush/pour flush toilets to piped sewer systems, septic tanks, and pit latrines; ventilated improved pit (VIP) latrines; pit latrines with slabs. Sample: Households Use of improved toilet facilities, which are non- shared facilities that prevent people from coming into contact with human waste, helps reduce the transmission of communicable diseases such as cholera and typhoid. Overall, 70% of households (58% in rural areas and 88% in urban areas) use improved toilet facilities (Figure 2.2). Thirteen percent of households have no toilet facility (20% in rural areas and under 1% in urban areas) (Table 2.3). Trends: There have been substantial improvements in the use of improved sanitation facilities in the past 5 years. Households using improved facilities increased from 59% in 2013 to 70% in 2018. Similarly, the percentage of households with no toilet facility decreased from 21% to 13%. Figure 2.1 Household drinking water by residence Figure 2.2 Household toilet facilities by residence 24 36 16 7 9 5 55 37 65 3 1 4 4 7 3 3 7 <15 3 7 Total Urban Rural Percent distribution of households by source of drinking water Unimproved source Bottled water, improved source for cooking/handwashing Filtration plant Protected well or spring Tube well or borehole Public tap/standpipe Piped water into dwelling/yard/plot/ neighbor’s yard Note: Excludes Azad Jammu and Kashmir and Gilgit Baltistan 70 88 58 11 8 13 7 4 9 13 1 20 Total Urban Rural Percent distribution of households by type of toilet facilities No facility/ bush/field Unimproved facility Shared facility Improved facility Note: Excludes Azad Jammu and Kashmir and Gilgit Baltistan Housing Characteristics and Household Population • 11 2.3 EXPOSURE TO SMOKE INSIDE THE HOME Exposure to smoke inside the home, from cooking with solid fuels or smoking tobacco, has potentially harmful health effects. Ninety-three percent of cooking takes place inside the home, while 6% of households have a separate building for cooking (Table 2.4). LPG, natural gas, and biogas are the most common type of solid fuel used for cooking (50%). Use of clean fuel (electricity and liquefied petroleum gas/natural gas/biogas) is more common in urban areas than in rural areas (88% and 27%, respectively). In Pakistan households, one in three persons are exposed to tobacco smoke daily. 2.3.1 Other Housing Characteristics The survey collected data on access to electricity, flooring materials, and the number of rooms used for sleeping. A vast majority (93%) of the households in Pakistan (99% in urban areas and 89% in rural areas) have access to electricity (Table 2.4). In Pakistani households, cement (35%) and earth and sand (34%) are the most commonly used materials for flooring. Earth and sand are the most commonly used in rural households (51%), and cement is most common in urban households (50%). 2.4 HOUSEHOLD WEALTH 2.4.1 Household Durable Goods The survey also collected information on household effects, means of transportation, and ownership of agricultural land and farm animals (Table 2.5). Mobile phones and televisions are the most common information and communication devices used in Pakistan, and almost all households (94%) have at least one mobile phone. In addition to mobile phones, 6% of households also have landline phones (11% in urban areas and 3% in rural areas). About two in three households (63%) in Pakistan own a television, although urban households are more likely than rural households to own a television (86% versus 48%). Five percent of urban and 7% of rural households own a radio. Rural households are more likely to own agricultural land than urban households (38% versus 11%). As expected, ownership of farm animals is much more common in rural households (62%) than in urban households (13%). 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 their score, and then dividing the distribution into five equal categories, each with 20% of the population. Sample: Households Table 2.6 presents data on wealth quintiles and the Gini coefficient according to residence, region, and province. The Gini coefficient indicates the level of concentration of wealth, with 0 representing an equal wealth distribution and 1 representing a totally unequal distribution. Pakistan’s Gini coefficient is 0.27, indicating a relatively uneven distribution of wealth in the population. 12 • Housing Characteristics and Household Population The wealthiest households are concentrated in urban areas (42%), whereas in rural areas over half of the population (57%) falls in the two lowest wealth quintiles. (Figure 2.3). A majority of the households in ICT are concentrated in the highest wealth quintile (57%). About 51% of FATA households are in the poorest wealth quintile (Table 2.6). 2.5 HAND WASHING Hand washing is one of the most effective ways to prevent germs from spreading. A place for hand washing was observed in 93% of the surveyed households in the 2017-18 PDHS (Table 2.7). Seventy-four percent of the households had a fixed place for hand washing, and 19% had a mobile hand- washing place. Sixty-nine percent of households used soap and water. One in 10 households did not have water, soap, or any other cleaning agents in place for hand washing. Patterns by background characteristics ▪ Eighty-nine percent of urban households had soap and water available for washing hands, as compared with 57% of rural households. ▪ Thirty-one percent of households in FATA, 29% of households in rural Sindh, and 28% of households in rural Balochistan had no water, soap, or any other cleansing agent, whereas only 3% of households in ICT Islamabad and Punjab did not have water, soap, or any other cleansing agents for hand washing. ▪ Thirty-one percent of households in the lowest wealth quintile did not have water or any cleansing agents for hand washing, as compared with 6% of households in the highest three wealth quintiles. 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 specified otherwise. Figure 2.3 Household wealth by residence 3 307 27 17 22 31 14 42 7 Urban Rural Percent distribution of de jure population by wealth quintiles Wealthiest Fourth Middle Second Poorest Note: Excludes Azad Jammu and Kashmir and Gilgit Baltistan Housing Characteristics and Household Population • 13 The de facto survey population (those who stayed overnight in the surveyed households) is 77,818; 49% of these individuals are male and 51% are female, yielding a sex ratio (number of males per 100 females) of 98. Thirty-eight percent of the population is under age 15. Children under age 5 and adolescents age 10-19 account for 13% and 23% of the population, respectively. About 4% of the population is age 65 and above, a group considered to be a dependent population (Table 2.8 and Figure 2.4). Trends: There has not been a substantial change in Pakistan’s household population distribution since 2012-13. The proportion of the population under age 15 has declined slightly, from 39% in 2012-13 to 38% in 2017-18. There has also been a decline in the share of children under age 5 (14% to 13%) in the past 5 years. However, their proportion in the rural population has increased. The proportion of the population age 0-17 is 47% in rural areas compared with 41% in urban areas. There is a slight differential between rural (41%) and urban (35%) proportions of the household population under age 14. The proportion of female-headed households has increased by two percentage points from 11% in 2012-13 to 13% in 2017-18 (Table 2.9). This seems to be at least partially the result of recent male outward migration from Pakistan. The average household size is 6.6 persons, which is slightly less than in 2012-13 (6.8). The average household size is slightly larger in rural (6.8) than urban (6.3) areas. Ten percent of households have foster and/or orphan children, with a slight difference between households in rural (11%) and urban (9%) areas (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 Eighty-one percent of de jure children under age 18 live with both of their parents; 2% are not living with their biological parents. Five percent of children under age 18 are orphans, with one or both parents dead (Table 2.10). Figure 2.4 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 Note: Excludes Azad Jammu and Kashmir and Gilgit Baltistan 14 • Housing Characteristics and Household Population Patterns by background characteristics ▪ Orphanhood increases with age. Two percent of children age 0-4 are orphans, as compared with 11% age 15-17 who are orphans. ▪ Children in the lowest wealth quintile are nearly twice as likely to be orphaned as children in the highest quintile (7% and 4%, respectively). ▪ Orphanhood ranges from 4% to 5% among regions with slight variations. 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 Birth certificates are made mandatory for services such as school enrolment, passports, voter registration, and marriage registration. Local governmental and nongovernmental organisations participate in birth registration for workplace populations. Table 2.11 presents the percentage of the de jure population under age 5 whose births are registered with the civil authorities, according to background characteristics. The results show that more than 4 in 10 children (42%) under age 5 have been registered, and 36% have a birth certificate. Although the government’s vital data registration system requires that a newborn be registered within the shortest possible time after birth, Table 2.11 indicates that children under age 2 are less likely to be registered (39%) than children age 2-4 (44%). The registration of older children is primarily driven by the practice of asking parents to produce a child’s birth certificate for school admission. Patterns by background characteristics ▪ Birth registration is considerably higher in urban (60%) than in rural (34%) areas. ▪ There is no difference in the extent of birth registration between male and female children. ▪ Only 2% of children in FATA and 19% of children in Khyber Pakhtunkhwa are registered as compared with 82% of children in ICT Islamabad. ▪ Children from the highest wealth quintile are more likely to have their births registered (76%) than children from the lowest wealth quintile (9%) (Figure 2.5). Trends: There has been improvement in formal registering of births in the past 5 years. The remarkable improvements in birth registration of children under age 5 have been observed in Balochistan (8% to 38%) followed by Khyber Pakhtunkhwa (10% to 19%), ICT (74% to 82%), and Sindh (25% to 28%) in the last 5 years. Figure 2.5 Birth registration by household wealth 9 27 44 63 76 Lowest Second Middle Fourth Highest Percentage of de jure children under age 5 whose births are registered with the civil authorities Poorest Wealthiest Note: Excludes Azad Jammu and Kashmir and Gilgit Baltistan Housing Characteristics and Household Population • 15 2.8.1 Registration with NADRA National Database and Registration Authority (NADRA) is a legal entity in Pakistan that oversees registration of the population. All children under age 18 are registered using the “Bay Form,” and adults age 18 and older are issued a computerised national identity card (CNIC). These documents are compulsory for procurement of any official document such as a passport or a driver’s license, for admission in schools, and for obtaining a government job. Table 2.12 presents information on the registration status of household members. Overall, 35% of the household population under age 18 has a Bay Form. More than four in five adults (age 18 and over) in all regions have a CNIC. People living in rural areas and in the lowest wealth quintile are less likely to register with NADRA than other subgroups. 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 Tables 2.13.1 and 2.13.2 present educational attainment of household population among women and men, respectively. Half of the women and 34% of men in Pakistan have no education. Only 9% of the women have secondary and 10% have a higher level of education. Fourteen percent of men have secondary and 13% have a higher level of education. The median number of years of schooling among men (4.0 years) is greater than among women (0.1 year) (Tables 2.13.1 and 2.13.2). Patterns by background characteristics ▪ Rural women (59%) and men (41%) are more likely than urban women (33%) and men (23%) to have no education. ▪ Younger women and men are much more likely to have completed more education than older women and men. For example, 53% of women and 62% of men age 10-14 have completed primary level schooling as compared to 14% of women and 15% of men age 40-49. ▪ Eighty-five percent of women in FATA have no education compared to 28% of women in ICT Islamabad. ▪ Among wealth quintiles, 0.2% of women and 2% of men have higher level of education from the lowest wealth quintile as compared with 31% of women and 35% of men from the highest wealth quintile (Tables 2.13.1 and 2.13.2). Trends: The percentages of the household population, especially of women who have a secondary or higher level of education, have increased in the past 5 years, whereas educational attainment among men has remained the same (Tables 2.13.1 and 2.13.2). 16 • Housing Characteristics and Household Population 2.9.2 School Attendance Net attendance ratios (NAR) Percentage of the school-age population that attends primary or secondary school. Sample: Children age 5-9 for primary school NAR and children age 10-14 for secondary school NAR Gross attendance ratios (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 5-9 for primary school GAR and children age 10-14 for secondary school GAR Table 2.14 shows that the net attendance ratio (NAR) for primary school children (age 5-9) is 59% whereas for secondary school children (age 10-14) it is 38%. The NAR for primary and secondary school is slightly higher among boys (61% and 40%, respectively) than among girls (55% and 36%, respectively). Gender Parity Indices (GPI) The ratio of female to male students attending primary school and the ratio of female to male students attending middle/secondary school. The index reflects the magnitude of the gender gap. Sample: Primary school students and middle/secondary school students Data on the gross attendance ratio (GAR) and the gender parity index (GPI) is presented in Table 2.14. The primary school GAR is 87%, and the secondary school GAR is 56%. A gender parity index (GPI) of 1 indicates parity or equality between 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 that level of schooling. A GPI higher than 1 indicates a gender disparity in favour of females. The GPI for NAR is 0.90 at the primary school, indicating that more boys are attending school than girls; however, the GPI for NAR is 0.89 at the middle/secondary school level, indicating that girls are dropping out. (Table 2.14). Patterns by background characteristics ▪ Both the primary and middle/secondary school NAR are lower in rural areas (54%) than in urban areas (67%). Fifty-four percent of rural children and 67% of urban children have attended primary school. Similarly, 32% of rural children and 49% of urban children have attended middle/secondary school. ▪ The primary school NAR is lowest in Balochistan (39%) and highest in ICT Islamabad (74%). ▪ The middle/secondary school NAR is lowest in FATA (18%) and highest in ICT Islamabad (59%). ▪ The pattern of GPI in middle/secondary school attendance is lower than primary in most regions. However, in FATA the middle/secondary (0.24) school attendance is lowest among all regions and lower than primary school attendance (0.48). Housing Characteristics and Household Population • 17 ▪ The children in the highest wealth quintile have the highest NAR compared with children in the lowest wealth quintile for primary, middle, and secondary level of education. (Figure 2.6). Reasons for school drop outs The 2017-18 PDHS asked the reason for dropping out of school for de facto households members age 5-24. The most common reasons cited for women are getting married and thinking further education was not necessary (18% each) followed by not being interested in education (17%), costing too much (13%), and school being too far (9%) (Table 2.15). LIST OF TABLES For more information on household population and housing characteristics, see the following tables: ▪ Table 2.1 Household drinking water ▪ Table 2.2 Availability of water ▪ Table 2.3 Household sanitation facilities ▪ 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 Registration with NADRA ▪ 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 ▪ Table 2.15 Reasons for children dropping out of school Figure 2.6 Secondary school attendance by household wealth 8 22 38 56 66 21 34 41 48 66 Lowest Second Middle Fourth Highest Net attendance ratio for middle and secondary school among children age 10-14 Girls Boys WealthiestPoorest Note: Excludes Azad Jammu and Kashmir and Gilgit Baltistan 18 • Housing Characteristics and Household Population Table 2.1 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 using various methods to treat drinking water, and percentage using an appropriate treatment method, according to residence, Pakistan DHS 2017-18 Households Population Characteristic Urban Rural Total Urban Rural Total Source of drinking water Improved source 96.7 93.4 94.6 96.6 92.7 94.1 Piped into dwelling/yard/plot 34.5 13.6 21.6 34.4 13.9 21.4 Piped to neighbour 1.0 2.5 1.9 1.0 2.2 1.8 Public tap/standpipe 9.4 4.7 6.5 9.0 4.9 6.4 Tube well or borehole 37.3 65.1 54.5 38.7 64.3 54.9 Protected dug well 0.8 2.7 2.0 0.8 2.9 2.1 Protected spring 0.3 1.7 1.2 0.3 1.7 1.2 Rain water 0.0 0.1 0.1 0.0 0.2 0.1 Bottled water, improved source for cooking/handwashing1 6.7 0.3 2.8 6.0 0.3 2.4 Filtration plant 6.8 2.7 4.3 6.5 2.3 3.8 Unimproved source 3.2 6.6 5.3 3.3 7.2 5.8 Unprotected dug well 0.1 1.6 1.0 0.1 1.8 1.2 Unprotected spring 0.2 1.9 1.2 0.1 2.0 1.3 Tanker truck/cart with small tank 2.2 0.4 1.1 2.5 0.5 1.2 Surface water 0.1 2.6 1.7 0.1 2.9 1.9 Bottled water, unimproved source for cooking/handwashing1 0.6 0.1 0.3 0.5 0.0 0.2 Other 0.1 0.1 0.1 0.1 0.1 0.1 Total 100.0 100.0 100.0 100.0 100.0 100.0 Time to obtain drinking water (round trip) Water on premises2 73.0 72.1 72.5 74.2 72.6 73.2 Less than 30 minutes 20.0 15.3 17.1 19.0 14.4 16.1 30 minutes or longer 5.9 12.0 9.6 5.7 12.4 9.9 Don’t know/missing 1.1 0.5 0.7 1.1 0.6 0.8 Total 100.0 100.0 100.0 100.0 100.0 100.0 Water treatment prior to drinking3 Boiled 12.8 1.6 5.9 12.9 1.5 5.6 Bleach/chlorine added 0.4 0.2 0.3 0.4 0.2 0.3 Strained through cloth 3.7 1.5 2.3 3.6 1.6 2.3 Ceramic, sand or other filter 1.8 0.5 1.0 2.2 0.5 1.1 Solar disinfection 0.0 0.0 0.0 0.0 0.0 0.0 Let it stand and settle 0.3 0.8 0.6 0.3 0.8 0.6 No treatment Percentage using an appropriate treatment method4 14.8 2.3 7.1 15.3 2.2 7.0 Number 4,540 7,329 11,869 28,578 49,763 78,341 Note: Table excludes Azad Jammu and Kashmir and Gilgit Baltistan. 1 Households using bottled water for drinking are classified as using an improved or unimproved source according to their water source for cooking and handwashing. 2 Includes water piped to a neighbour 3 Respondents may report multiple treatment methods, so the sum of treatment may exceed 100%. 4 Appropriate water treatment methods include boiling, bleaching, and filtering. Housing Characteristics and Household Population • 19 Table 2.2 Availability of water Among households and de jure population using piped water or water from a tube well or borehole, percentage with lack of availability of water in the last 2 weeks, according to residence, Pakistan DHS 2017-18 Households Population Availability of water in last 2 weeks Urban Rural Total Urban Rural Total Not available for at least one day 19.8 7.0 12.0 19.9 7.0 11.8 Available with no interruption of at least 1 day 78.4 92.2 86.8 78.3 92.2 87.0 Don’t know/missing 1.8 0.8 1.2 1.8 0.8 1.2 Total 100.0 100.0 100.0 100.0 100.0 100.0 Number using piped water or water from a tube well1 4,034 6,314 10,348 25,462 42,648 68,111 Note: Table excludes Azad Jammu and Kashmir and Gilgit Baltistan. 1 Includes households reporting piped water or water from a tube well or borehole as their main source of drinking water and households 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 Household sanitation facilities Percent distribution of households and de jure population by type of toilet/latrine facilities and percent distribution of households and de jure population with a toilet/latrine facility by location of the facility, according to residence, Pakistan DHS 2017-18 Households Population Type and location of toilet/latrine facility Urban Rural Total Urban Rural Total Improved sanitation 87.7 58.1 69.5 88.4 60.2 70.5 Flush/pour flush to piped sewer system 61.8 8.5 28.9 61.2 8.9 28.0 Flush/pour flush to septic tank 20.1 28.0 24.9 20.9 28.2 25.6 Flush/pour flush to pit latrine 5.4 18.7 13.6 5.7 19.7 14.6 Ventilated improved pit (VIP) latrine 0.1 0.5 0.4 0.1 0.5 0.4 Pit latrine with slab 0.4 2.4 1.6 0.5 2.8 1.9 Unimproved sanitation 12.2 41.9 30.5 11.6 39.8 29.5 Shared facility1 7.7 13.0 11.0 6.8 11.7 9.9 Flush/pour flush to piped sewer system 4.0 1.1 2.2 3.8 1.1 2.1 Flush/pour flush to septic tank 2.9 6.8 5.3 2.3 5.8 4.5 Flush/pour flush to pit latrine 0.8 4.4 3.0 0.7 4.0 2.8 Ventilated improved pit (VIP) latrine 0.0 0.1 0.1 0.0 0.1 0.1 Pit latrine with slab 0.1 0.6 0.4 0.1 0.6 0.4 Unimproved facility 3.9 9.0 7.1 4.0 9.5 7.5 Flush/pour flush not to sewer/septic tank/ pit latrine 3.3 4.4 4.0 3.4 4.5 4.1 Pit latrine without slab/open pit 0.4 3.3 2.2 0.5 3.6 2.4 Bucket 0.1 0.8 0.5 0.1 0.8 0.6 Hanging toilet/hanging latrine 0.0 0.3 0.2 0.0 0.3 0.2 Other 0.1 0.3 0.2 0.1 0.3 0.2 Open defecation (no facility/bush/field) 0.6 19.8 12.5 0.8 18.6 12.1 Total 100.0 100.0 100.0 100.0 100.0 100.0 Number of households/population 4,540 7,329 11,869 28,578 49,763 78,341 Location of toilet facility In own dwelling 98.7 95.1 96.7 98.8 95.3 96.8 In own yard/plot 0.8 3.6 2.4 0.8 3.5 2.4 Elsewhere 0.4 1.3 0.9 0.3 1.1 0.8 Total 100.0 100.0 100.0 100.0 100.0 100.0 Number of households/population with a toilet/latrine facility 4,511 5,880 10,391 28,363 40,504 68,867 Note: Table excludes Azad Jammu and Kashmir and Gilgit Baltistan. 1 Facilities that would be considered improved if they were not shared by two or more households 20 • 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, Pakistan DHS 2017-18 Households Population Housing characteristic Urban Rural Total Urban Rural Total Electricity Yes 99.4 88.5 92.7 99.4 88.1 92.2 No 0.5 11.5 7.3 0.6 11.9 7.8 Total 100.0 100.0 100.0 100.0 100.0 100.0 Flooring material Earth, sand 6.4 51.1 34.0 7.1 51.5 35.3 Dung 0.6 3.6 2.5 0.7 3.8 2.7 Ceramic tiles 3.3 1.0 1.9 3.2 1.1 1.9 Cement 49.6 25.9 35.0 48.8 25.0 33.7 Carpet 1.7 1.1 1.3 2.0 1.3 1.6 Chips/terrazzo 11.6 3.6 6.7 11.4 3.7 6.5 Bricks 6.7 7.7 7.3 6.9 7.6 7.3 Mats 0.8 1.7 1.3 0.9 1.9 1.5 Marble 19.0 3.9 9.7 18.6 3.7 9.1 Other 0.2 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 32.5 41.0 37.7 24.3 32.1 29.2 Two 39.9 36.5 37.8 38.1 36.0 36.8 Three or more 27.6 22.3 24.3 37.6 31.7 33.9 Total 100.0 100.0 100.0 100.0 100.0 100.0 Place for cooking In the house 94.7 91.6 92.8 95.1 91.9 93.1 In a separate building 4.2 7.7 6.4 4.5 7.7 6.5 Outdoors 0.1 0.4 0.3 0.1 0.3 0.2 No food cooked in household 0.9 0.3 0.5 0.3 0.1 0.2 Total 100.0 100.0 100.0 100.0 100.0 100.0 Cooking fuel Electricity 0.2 0.1 0.1 0.2 0.1 0.1 LPG/natural gas/biogas 88.2 26.7 50.2 87.6 25.5 48.1 Coal/lignite 0.1 0.2 0.1 0.1 0.2 0.2 Charcoal 0.8 2.8 2.0 0.9 2.9 2.2 Wood 8.3 61.1 40.9 9.1 62.1 42.8 Straw/shrubs/grass 0.1 1.9 1.2 0.1 2.0 1.3 Agricultural crop 0.1 2.0 1.3 0.0 2.2 1.4 Animal dung 1.4 4.9 3.5 1.6 4.9 3.7 No food cooked in household 0.9 0.3 0.5 0.3 0.1 0.2 Total 100.0 100.0 100.0 100.0 100.0 100.0 Percentage using solid fuel for cooking1 10.6 72.9 49.1 11.9 74.4 51.6 Percentage using clean fuel for cooking2 88.4 26.8 50.4 87.8 25.5 48.2 Frequency of smoking in the home Daily 25.5 37.9 33.1 28.1 39.8 35.6 Weekly 2.0 1.8 1.9 2.0 1.6 1.8 Monthly 0.1 0.2 0.2 0.2 0.2 0.2 Less than once a month 0.3 0.5 0.4 0.3 0.4 0.4 Never 71.9 59.6 64.3 69.4 57.9 62.1 Total 100.0 100.0 100.0 100.0 100.0 100.0 Number of households/ population 4,540 7,329 11,869 28,578 49,763 78,341 Note: Table excludes Azad Jammu and Kashmir and Gilgit Baltistan. LPG = Liquefied petroleum gas 1 Includes coal/lignite, charcoal, wood, straw/shrubs/grass, agricultural crops, and animal dung 2 Includes electricity and LPG/natural gas/biogas Housing Characteristics and Household Population • 21 Table 2.5 Household possessions Percentage of households possessing various household effects, means of transportation, agricultural land, and livestock/farm animals by residence, Pakistan DHS 2017-18 Residence Total Possession Urban Rural Household effects Radio 5.3 7.1 6.4 Television 86.4 48.1 62.8 Mobile phone 97.5 91.6 93.9 Non-mobile telephone 10.9 2.5 5.7 Refrigerator 77.1 41.9 55.4 Almirah/cabinet 77.5 44.8 57.3 Chair 67.1 47.4 54.9 Room cooler 25.1 11.2 16.5 Air conditioner 21.7 3.8 10.6 Washing machine 82.9 44.4 59.1 Water pump 68.3 46.8 55.0 Bed 80.9 59.6 67.7 Clock 84.8 54.0 65.8 Sofa 54.9 27.6 38.0 Camera 9.9 3.8 6.1 Sewing machine 71.4 51.5 59.1 Computer 26.4 8.1 15.1 Internet connection 22.9 4.9 11.8 Watch 61.5 48.3 53.3 Means of transport Bicycle 17.7 21.9 20.3 Animal drawn cart 2.1 12.5 8.5 Motorcycle/scooter 61.6 49.4 54.1 Car/truck 15.2 6.4 9.8 Tractor 0.9 5.0 3.5 Boat with a motor 0.1 0.1 0.1 Rickshaw/chingchi 3.3 2.5 2.8 Ownership of agricultural land 10.6 38.0 27.5 Average land ownership for household (acres)1 12.1 7.4 8.1 Ownership of farm animals2 13.4 61.7 43.2 Number 4,540 7,329 11,869 Note: Table excludes Azad Jammu and Kashmir and Gilgit Baltistan. 1 Average includes only households with valid information in agriculture land (don’t know and missing are not considered). 2 Cows, bulls, other cattle, horses, donkeys, mules, goats, sheep, camels, chickens, or other poultry 22 • 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 and region, Pakistan DHS 2017-18 Wealth quintile Total Number of persons Gini coefficient Residence/region Lowest Second Middle Fourth Highest Residence Urban 2.9 7.2 16.9 30.7 42.3 100.0 28,578 0.14 Rural 29.8 27.4 21.8 13.8 7.2 100.0 49,763 0.29 Region Punjab 11.4 18.8 22.1 23.2 24.5 100.0 40,684 0.24 Urban 0.7 4.9 15.6 29.0 49.8 100.0 14,914 0.10 Rural 17.7 26.8 25.9 19.8 9.8 100.0 25,770 0.26 Sindh 36.3 13.6 13.1 19.1 17.9 100.0 18,717 0.39 Urban 5.5 8.5 18.1 33.8 34.0 100.0 9,591 0.18 Rural 68.7 18.9 7.8 3.6 1.0 100.0 9,126 0.38 Khyber Pakhtunkhwa 16.9 28.8 24.9 15.5 13.8 100.0 11,895 0.24 Urban 2.3 7.7 17.3 32.6 40.1 100.0 2,297 0.10 Rural 20.4 33.9 26.7 11.5 7.5 100.0 9,599 0.23 Balochistan 28.8 30.7 21.4 12.6 6.5 100.0 4,694 0.26 Urban 10.8 21.1 21.3 27.7 19.1 100.0 1,331 0.24 Rural 35.9 34.6 21.4 6.7 1.5 100.0 3,363 0.22 ICT Islamabad 0.4 4.4 14.1 23.8 57.2 100.0 680 0.15 FATA 51.3 34.5 8.7 3.8 1.7 100.0 1,670 0.34 Total1 20.0 20.0 20.0 20.0 20.0 100.0 78,341 0.27 Azad Jammu and Kashmir 13.0 26.5 27.8 18.4 14.3 100.0 10,550 0.27 Urban 2.4 15.7 28.3 25.5 28.1 100.0 1,815 0.21 Rural 15.3 28.7 27.7 16.9 11.4 100.0 8,735 0.27 Gilgit Baltistan 40.2 37.2 14.1 5.1 3.3 100.0 7,521 0.36 1 Total excludes Azad Jammu and Kashmir and Gilgit Baltistan. Housing Characteristics and Household Population • 23 Table 2.7 Handwashing Percentage of households in which the place most often used for washing hands was observed and determined to be fixed or mobile, and percentage of households in which the place for handwashing was observed; and among households in which the place for handwashing was observed, percent distribution by availability of water, soap, and other cleansing agents available, according to background characteristics, Pakistan DHS 2017-18 Percentage of households in which place for washing hands was observed: Number of households Among households in which place for handwashing was observed, percentage with: Number of households in which a place for hand- washing was observed Background characteristic And place for hand- washing was a fixed place And place for hand- washing was mobile Total Soap and water1 Water and cleansing agent other than soap only2 Water only Soap but no water3 Cleansing agent other than soap only2 No water, no soap, no other cleansing agent Total Residence Urban 82.3 8.9 91.3 4,540 88.7 0.4 7.9 0.4 0.0 2.6 100.0 4,144 Rural 68.2 25.5 93.7 7,329 56.5 2.0 26.5 0.7 0.5 13.7 100.0 6,864 Wealth quintile Lowest 44.5 46.6 91.1 2,322 21.2 3.3 42.5 0.9 1.4 30.6 100.0 2,115 Second 68.0 26.1 94.1 2,449 53.3 2.4 30.8 1.0 0.3 12.1 100.0 2,304 Middle 78.7 15.1 93.8 2,318 77.7 1.1 16.7 0.6 0.0 3.9 100.0 2,176 Fourth 87.9 6.5 94.4 2,397 91.4 0.3 6.6 0.2 0.0 1.6 100.0 2,263 Highest 88.3 2.0 90.3 2,383 98.4 0.1 1.3 0.0 0.0 0.1 100.0 2,151 Region Punjab 83.3 12.1 95.5 6,596 79.6 1.3 15.6 0.2 0.1 3.3 100.0 6,299 Urban 89.1 6.4 95.5 2,466 93.4 0.2 5.0 0.3 0.0 1.1 100.0 2,355 Rural 79.9 15.6 95.5 4,130 71.3 1.9 21.9 0.1 0.1 4.6 100.0 3,944 Sindh 58.3 27.7 86.0 2,789 61.0 2.6 17.5 1.5 1.4 16.0 100.0 2,397 Urban 71.2 11.8 83.0 1,515 88.2 0.8 6.2 0.6 0.2 3.9 100.0 1,257 Rural 42.9 46.6 89.5 1,274 31.0 4.6 29.9 2.4 2.8 29.2 100.0 1,140 Khyber Pakhtunkhwa 67.0 27.1 94.1 1,595 47.7 0.6 32.8 0.4 0.0 18.5 100.0 1,501 Urban 87.4 10.7 98.1 328 67.5 0.1 28.8 0.3 0.0 3.2 100.0 321 Rural 61.8 31.3 93.1 1,268 42.3 0.8 33.9 0.4 0.0 22.7 100.0 1,180 Balochistan 60.3 31.3 91.6 565 40.2 0.4 35.0 1.3 0.0 23.1 100.0 517 Urban 76.7 17.1 93.9 157 63.3 0.5 23.1 1.2 0.0 11.9 100.0 147 Rural 54.0 36.7 90.7 408 31.1 0.4 39.7 1.3 0.0 27.5 100.0 370 ICT Islamabad 72.0 10.7 82.7 119 89.3 0.0 5.7 2.1 0.0 2.9 100.0 98 FATA 56.7 38.5 95.2 205 33.4 0.8 34.8 0.4 0.2 30.5 100.0 196 Total4 73.6 19.2 92.7 11,869 68.6 1.4 19.5 0.6 0.3 9.5 100.0 11,008 Azad Jammu and Kashmir 67.4 31.8 99.3 1,697 68.5 0.2 11.1 0.9 0.0 19.3 100.0 1,685 Urban 80.5 18.2 98.7 311 80.6 0.1 8.8 0.7 0.0 9.8 100.0 306 Rural 64.5 34.9 99.4 1,386 65.8 0.2 11.7 1.0 0.0 21.4 100.0 1,378 Gilgit Baltistan 77.4 19.2 96.6 974 54.9 0.7 14.8 1.5 0.1 27.9 100.0 941 1 Soap includes soap or detergent in bar, liquid, powder, or paste form. This column includes households with soap and water only as well as those that had soap and water and another cleansing agent. 2 Cleansing agents other than soap include locally available materials such as ash, mud, or sand 3 Includes households with soap only as well as those with soap and another cleansing agent 4 Total excludes Azad Jammu and Kashmir and Gilgit Baltistan. 24 • Housing Characteristics and Household Population Table 2.8 Household population by age, sex, and residence Percent distribution of the de facto household population by age groups, according to sex and residence, Pakistan DHS 2017-18 Urban Rural Male Female Total Age Male Female Total Male Female Total <5 11.8 11.5 11.7 14.1 13.9 14.0 13.3 13.0 13.1 5-9 12.3 11.8 12.0 14.7 13.9 14.3 13.8 13.1 13.5 10-14 10.6 11.2 10.9 12.4 12.1 12.3 11.8 11.8 11.8 15-19 10.8 10.6 10.7 11.0 11.1 11.0 10.9 10.9 10.9 20-24 9.9 10.7 10.3 8.3 9.2 8.8 8.9 9.8 9.4 25-29 8.3 8.9 8.6 7.5 8.5 8.0 7.8 8.7 8.2 30-34 7.1 7.2 7.1 5.7 6.3 6.0 6.2 6.6 6.4 35-39 6.5 6.6 6.6 5.3 5.6 5.4 5.7 6.0 5.9 40-44 4.6 4.5 4.6 3.8 3.6 3.7 4.1 3.9 4.0 45-49 4.7 3.6 4.2 3.6 3.3 3.4 4.0 3.4 3.7 50-54 3.6 4.0 3.8 2.9 3.4 3.2 3.2 3.6 3.4 55-59 3.0 3.2 3.1 2.8 3.3 3.1 2.9 3.3 3.1 60-64 2.7 2.4 2.5 2.5 2.1 2.3 2.6 2.2 2.4 65-69 1.7 1.6 1.6 2.0 1.4 1.7 1.8 1.5 1.7 70-74 1.4 1.0 1.2 1.9 1.1 1.5 1.7 1.1 1.4 75-79 0.5 0.5 0.5 0.7 0.5 0.6 0.6 0.5 0.6 80 + 0.7 0.6 0.7 0.9 0.7 0.8 0.8 0.7 0.7 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Dependency age groups 0-14 34.7 34.5 34.6 41.3 39.8 40.5 38.8 37.9 38.4 15-64 61.1 61.7 61.4 53.3 56.5 55.0 56.2 58.4 57.3 65+ 4.2 3.7 4.0 5.4 3.6 4.5 5.0 3.7 4.3 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 41.2 40.8 41.0 48.0 46.4 47.2 45.5 44.4 44.9 18+ 58.8 59.2 59.0 52.0 53.6 52.8 54.5 55.6 55.1 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Adolescents 10-19 21.3 21.8 21.6 23.5 23.1 23.3 22.7 22.7 22.7 Number of persons 14,278 14,110 28,388 24,179 25,251 49,430 38,457 39,361 77,818 Note: Table excludes Azad Jammu and Kashmir and Gilgit Baltistan. Housing Characteristics and Household Population • 25 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 age18, according to residence, Pakistan DHS 2017-18 Residence Total Characteristic Urban Rural Household headship Male 88.4 87.0 87.5 Female 11.6 13.0 12.5 Total 100.0 100.0 100.0 Number of usual members 1 1.9 1.2 1.5 2 4.9 4.4 4.6 3 8.9 7.3 7.9 4 13.1 12.0 12.4 5 17.4 13.8 15.2 6 15.3 14.8 15.0 7 12.4 12.9 12.7 8 7.7 9.8 9.0 9+ 18.4 23.8 21.7 Total 100.0 100.0 100.0 Mean size of households 6.3 6.8 6.6 Percentage of households with orphans and foster children under age 18 Double orphans 0.5 0.3 0.4 Single orphans1 5.4 7.1 6.5 Foster children2 4.2 5.3 4.9 Foster and/or orphan children 8.8 11.2 10.3 Number of households 4,540 7,329 11,869 Note: Table is based on de jure household members, that is, usual residents. It excludes Azad Jammu and Kashmir and Gilgit Baltistan. 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. 26 • Housing Characteristics and Household Population 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, Pakistan DHS 2017-18 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 biological 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 82.9 14.6 0.9 0.1 0.4 0.7 0.3 0.0 0.0 100.0 1.0 1.6 10,337 <2 83.0 15.5 0.5 0.1 0.2 0.4 0.2 0.0 0.0 100.0 0.7 0.9 4,061 2-4 82.8 14.1 1.1 0.2 0.6 0.9 0.3 0.0 0.0 100.0 1.2 2.0 6,276 5-9 81.7 13.3 2.1 0.5 1.1 1.0 0.3 0.1 0.0 100.0 1.3 3.5 10,500 10-14 81.1 9.9 4.7 0.6 1.6 1.3 0.2 0.2 0.3 100.0 2.1 7.1 9,172 15-17 75.7 7.9 7.1 0.9 2.8 4.1 0.4 0.5 0.5 100.0 5.5 11.3 5,120 Sex Male 81.3 11.8 3.4 0.5 1.3 1.2 0.1 0.1 0.2 100.0 1.6 5.1 17,584 Female 80.7 12.2 2.9 0.5 1.2 1.6 0.4 0.2 0.2 100.0 2.4 4.9 17,545 Residence Urban 84.5 8.8 3.0 0.6 0.9 1.5 0.3 0.1 0.2 100.0 2.1 4.5 11,685 Rural 79.3 13.6 3.2 0.4 1.5 1.4 0.3 0.2 0.2 100.0 2.0 5.3 23,445 Wealth quintile Lowest 82.2 9.0 4.0 0.4 2.6 1.4 0.1 0.1 0.2 100.0 1.8 7.0 8,195 Second 80.2 12.5 3.6 0.3 1.1 1.7 0.2 0.2 0.1 100.0 2.3 5.2 7,442 Middle 79.6 14.6 2.2 0.5 1.1 1.3 0.3 0.2 0.1 100.0 1.9 3.9 7,229 Fourth 79.7 13.3 3.3 0.8 0.7 1.5 0.3 0.1 0.3 100.0 2.2 4.7 6,442 Highest 83.7 11.0 2.3 0.4 0.5 1.3 0.4 0.1 0.2 100.0 2.0 3.6 5,821 Region Punjab 77.8 14.8 3.3 0.6 1.1 1.5 0.4 0.2 0.2 100.0 2.3 5.3 17,508 Urban 81.4 11.7 3.0 0.9 0.5 1.8 0.4 0.2 0.3 100.0 2.6 4.3 6,016 Rural 75.8 16.5 3.5 0.5 1.5 1.4 0.5 0.2 0.1 100.0 2.2 5.8 11,492 Sindh 87.6 5.4 3.2 0.3 1.6 1.4 0.0 0.2 0.2 100.0 1.8 5.2 8,299 Urban 88.0 5.3 3.2 0.4 1.5 1.3 0.0 0.1 0.1 100.0 1.6 4.9 3,808 Rural 87.3 5.5 3.2 0.3 1.7 1.4 0.0 0.3 0.3 100.0 2.0 5.4 4,491 Khyber Pakhtunkhwa 77.7 16.2 2.9 0.3 1.3 1.4 0.1 0.1 0.0 100.0 1.6 4.4 5,798 Urban 86.6 9.2 2.1 0.2 0.5 1.0 0.3 0.1 0.0 100.0 1.4 3.0 1,020 Rural 75.8 17.7 3.1 0.3 1.5 1.5 0.1 0.1 0.0 100.0 1.7 4.8 4,778 Balochistan 91.7 2.0 2.4 0.7 1.3 1.1 0.3 0.2 0.2 100.0 1.8 4.4 2,375 Urban 88.7 3.4 3.7 0.6 1.5 1.0 0.4 0.2 0.4 100.0 2.0 6.2 661 Rural 92.9 1.5 1.8 0.7 1.3 1.2 0.2 0.2 0.1 100.0 1.8 3.7 1,714 ICT Islamabad 86.4 7.1 2.2 0.4 1.4 2.2 0.0 0.1 0.3 100.0 2.6 4.0 254 FATA 75.0 20.1 3.0 0.1 0.4 1.1 0.1 0.1 0.1 100.0 1.4 3.7 896 Total <15 2 81.9 12.7 2.5 0.4 1.0 1.0 0.2 0.1 0.1 100.0 1.4 3.9 30,009 Total <18 2 81.0 12.0 3.1 0.5 1.3 1.4 0.3 0.1 0.2 100.0 2.0 5.0 35,130 Azad Jammu and Kashmir Total <15 64.7 30.5 1.6 0.2 1.0 1.3 0.6 0.1 0.1 100.0 2.1 3.3 3,955 Total <18 65.1 28.6 2.1 0.3 1.1 1.9 0.6 0.1 0.2 100.0 2.8 4.1 4,655 Gilgit Baltistan Total <15 79.4 15.9 1.4 0.4 1.4 1.3 0.1 0.1 0.0 100.0 1.5 3.0 3,345 Total <18 79.1 14.7 1.9 0.5 1.4 2.0 0.2 0.1 0.1 100.0 2.3 3.6 3,900 Housing Characteristics and Household Population • 27 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, Pakistan DHS 2017-18 Percentage of children whose births are registered and who: Total percentage of children whose births are registered Number of children Background characteristic Had a birth certificate Did not have birth certificate Age <2 33.9 5.0 38.9 4,061 2-4 37.5 6.8 44.3 6,276 Sex Male 36.3 6.2 42.5 5,128 Female 35.9 6.0 41.9 5,209 Residence Urban 53.5 6.7 60.3 3,333 Rural 27.8 5.8 33.6 7,004 Wealth quintile Lowest 6.3 3.0 9.3 2,369 Second 19.1 8.1 27.3 2,027 Middle 37.3 6.9 44.2 2,130 Fourth 55.3 8.2 63.4 1,981 Highest 71.4 4.6 76.0 1,830 Region Punjab 52.9 5.0 57.8 5,362 Urban 65.2 5.2 70.5 1,756 Rural 46.9 4.8 51.7 3,606 Sindh 24.0 3.6 27.6 2,409 Urban 48.4 5.4 53.8 1,062 Rural 4.8 2.1 6.9 1,347 Khyber Pakhtunkhwa 11.2 7.6 18.8 1,652 Urban 18.8 11.6 30.4 291 Rural 9.6 6.7 16.3 1,362 Balochistan 12.7 24.9 37.6 574 Urban 24.7 21.3 46.0 173 Rural 7.5 26.5 34.0 401 ICT Islamabad 71.3 11.1 82.4 78 FATA 1.9 0.2 2.2 262 Total1 36.1 6.1 42.2 10,337 Azad Jammu and Kashmir 21.6 7.4 29.0 1,364 Urban 32.9 3.9 36.8 207 Rural 19.6 8.0 27.6 1,158 Gilgit Baltistan 16.7 10.4 27.1 1,102 1 Total excludes Azad Jammu and Kashmir and Gilgit Baltistan. 28 • Housing Characteristics and Household Population Table 2.12 Registration with NADRA Percentage of de jure household population registered with NADRA, according to background characteristics, Pakistan DHS 2017-18 Among those under age 18 Among those age 18 or above Background characteristic Percentage with Bay Form Number Percentage with CNIC Number Sex Male 34.9 17,584 91.3 21,067 Female 34.0 17,545 76.2 22,140 Residence Urban 48.8 11,685 86.1 16,893 Rural 27.4 23,445 82.0 26,315 Wealth quintile Lowest 9.5 8,195 76.8 7,475 Second 24.3 7,442 80.1 8,218 Middle 36.6 7,229 82.2 8,442 Fourth 50.1 6,442 85.1 9,226 Highest 62.8 5,821 91.6 9,847 Region Punjab 44.1 17,508 84.5 23,174 Urban 54.0 6,016 87.3 8,898 Rural 38.8 11,492 82.8 14,276 Sindh 23.6 8,299 81.4 10,417 Urban 42.5 3,808 83.9 5,784 Rural 7.5 4,491 78.2 4,634 Khyber Pakhtunkhwa 21.8 5,798 84.3 6,097 Urban 39.1 1,020 86.7 1,276 Rural 18.2 4,778 83.7 4,821 Balochistan 39.7 2,375 82.0 2,319 Urban 48.4 661 86.8 671 Rural 36.3 1,714 80.0 1,649 ICT Islamabad 78.6 254 92.6 426 FATA 3.9 896 79.5 774 Total1 34.5 35,130 83.6 43,207 Azad Jammu and Kashmir 51.0 4,655 89.2 5,895 Urban 56.1 724 92.0 1,091 Rural 50.1 3,932 88.6 4,804 Gilgit Baltistan 36.8 3,900 86.3 3,621 Note: Excludes cases with age not known or missing. NADRA = National Database and Registration Authority CNIC = computerised national identity card 1 Total excludes Azad Jammu and Kashmir and Gilgit Baltistan. Housing Characteristics and Household Population • 29 Table 2.13.1 Educational attainment of the female household population Percent distribution of the de facto female household population age 5 and over by highest level of schooling attended or completed and median years completed, according to background characteristics, Pakistan DHS 2017-18 Background characteristic No education Primary1 Middle2 Secondary3 Higher4 Don’t know/ missing Total Number Median years completed Age 5-9 70.0 29.8 0.1 0.0 0.0 0.1 100.0 5,160 0.0 10-14 26.8 52.6 19.2 1.4 0.0 0.1 100.0 4,633 2.8 15-19 30.8 17.7 19.3 20.3 11.9 0.0 100.0 4,284 5.4 20-24 33.9 15.1 10.5 14.5 26.0 0.0 100.0 3,847 5.9 25-29 39.4 14.6 11.0 13.7 21.3 0.0 100.0 3,415 4.6 30-34 44.9 16.0 9.9 12.0 17.2 0.0 100.0 2,600 3.9 35-39 48.6 15.8 8.1 13.6 13.8 0.1 100.0 2,359 1.7 40-44 59.7 14.4 7.2 7.8 11.0 0.0 100.0 1,544 0.0 45-49 65.2 13.6 6.1 5.9 9.2 0.0 100.0 1,346 0.0 50-54 73.9 10.6 4.2 5.8 5.6 0.0 100.0 1,421 0.0 55-59 77.6 10.4 3.0 4.2 4.9 0.0 100.0 1,298 0.0 60-64 79.6 8.4 3.2 4.4 4.4 0.0 100.0 876 0.0 65+ 87.3 5.6 2.9 2.3 1.6 0.3 100.0 1,449 0.0 Residence Urban 32.5 21.7 12.8 14.5 18.5 0.0 100.0 12,483 4.5 Rural 59.3 21.7 7.9 5.5 5.5 0.1 100.0 21,748 0.0 Wealth quintile Lowest 84.2 12.8 1.9 0.8 0.2 0.1 100.0 6,557 0.0 Second 64.7 24.5 5.9 3.3 1.6 0.1 100.0 6,823 0.0 Middle 48.4 27.3 12.4 7.4 4.4 0.0 100.0 6,846 0.4 Fourth 32.6 25.3 14.7 14.1 13.2 0.0 100.0 6,919 4.3 Highest 20.5 18.5 12.9 17.5 30.7 0.0 100.0 7,086 7.8 Region Punjab 40.5 24.7 11.9 10.4 12.5 0.0 100.0 18,055 2.6 Urban 28.0 22.5 14.0 15.2 20.3 0.0 100.0 6,542 4.9 Rural 47.6 26.0 10.7 7.6 8.0 0.0 100.0 11,513 0.6 Sindh 54.4 19.0 7.7 9.0 10.0 0.0 100.0 7,951 0.0 Urban 33.5 21.4 12.1 15.3 17.6 0.0 100.0 4,177 4.4 Rural 77.4 16.3 2.8 2.0 1.5 0.1 100.0 3,774 0.0 Khyber Pakhtunkhwa 61.2 19.5 7.6 5.4 6.2 0.1 100.0 5,216 0.0 Urban 41.1 21.2 11.4 10.7 15.5 0.2 100.0 1,008 2.5 Rural 66.0 19.1 6.7 4.2 3.9 0.1 100.0 4,208 0.0 Balochistan 71.9 15.2 5.5 4.0 3.3 0.1 100.0 2,000 0.0 Urban 61.5 16.5 7.0 6.7 8.1 0.3 100.0 568 0.0 Rural 76.1 14.7 4.9 2.9 1.4 0.0 100.0 1,433 0.0 ICT Islamabad 28.2 21.9 10.5 13.3 25.9 0.3 100.0 291 5.0 FATA 85.2 10.9 1.9 1.1 0.7 0.1 100.0 718 0.0 Total5 49.5 21.7 9.7 8.8 10.3 0.1 100.0 34,231 0.1 Azad Jammu and Kashmir 36.9 23.3 13.8 12.4 13.5 0.0 100.0 5,013 3.7 Urban 25.2 21.3 13.8 16.1 23.5 0.0 100.0 859 6.2 Rural 39.4 23.8 13.8 11.7 11.4 0.0 100.0 4,155 3.0 Gilgit Baltistan 33.4 26.4 16.0 11.5 12.7 0.1 100.0 2,944 3.7 1 Primary refers to completing classes 1-5. 2 Middle refers to completing classes 6-8. 3 Secondary refers to completing classes 9-10. 4 Higher refers to completing class 11 and above. 5 Total excludes Azad Jammu and Kashmir and Gilgit Baltistan. Total includes 1 case with missing information on age. 30 • Housing Characteristics and Household Population Table 2.13.2 Educational attainment of the male household population Percent distribution of the de facto male household population age 5 and over by highest level of schooling attended or completed and median years completed, according to background characteristics, Pakistan DHS 2017-18 Background characteristic No education Primary1 Middle2 Secondary3 Higher4 Don’t know/ missing Total Number Median years completed Age 5-9 68.3 31.6 0.0 0.0 0.0 0.1 100.0 5,308 0.0 10-14 17.2 61.8 19.7 1.2 0.0 0.2 100.0 4,520 3.0 15-19 17.9 17.9 29.1 24.8 10.3 0.0 100.0 4,202 7.1 20-24 21.8 15.1 16.6 19.3 27.2 0.0 100.0 3,430 7.7 25-29 24.6 16.7 15.5 17.1 26.0 0.0 100.0 2,986 7.4 30-34 25.5 16.1 16.5 20.9 21.0 0.0 100.0 2,379 7.2 35-39 26.1 18.1 15.6 21.8 18.4 0.0 100.0 2,193 7.1 40-44 29.7 14.7 11.7 22.4 21.5 0.0 100.0 1,574 7.2 45-49 34.5 14.9 12.2 16.8 21.6 0.0 100.0 1,541 5.4 50-54 38.7 17.1 11.4 16.1 16.7 0.0 100.0 1,217 4.5 55-59 43.6 16.7 12.7 16.3 10.6 0.0 100.0 1,103 4.1 60-64 48.4 16.0 9.8 14.8 11.1 0.0 100.0 991 1.7 65+ 57.4 15.5 7.2 9.5 10.4 0.0 100.0 1,909 0.0 Residence Urban 22.7 22.9 15.8 17.5 21.1 0.1 100.0 12,595 6.4 Rural 40.9 26.2 13.4 11.4 8.2 0.0 100.0 20,760 2.1 Wealth quintile Lowest 62.6 24.9 7.0 3.8 1.7 0.0 100.0 6,549 0.0 Second 42.9 29.4 13.0 9.8 4.9 0.1 100.0 6,734 1.5 Middle 31.0 29.0 17.3 13.8 8.8 0.1 100.0 6,614 4.0 Fourth 21.7 24.1 19.9 19.4 14.9 0.0 100.0 6,721 6.1 Highest 12.6 17.3 14.2 21.3 34.5 0.1 100.0 6,737 9.1 Region Punjab 29.2 26.0 16.6 15.8 12.4 0.0 100.0 17,233 4.4 Urban 19.8 24.1 17.7 19.1 19.4 0.0 100.0 6,531 6.9 Rural 34.9 27.2 16.0 13.8 8.1 0.0 100.0 10,701 3.5 Sindh 38.4 23.6 10.8 11.4 15.6 0.1 100.0 8,168 3.3 Urban 24.2 22.0 13.6 16.2 23.8 0.2 100.0 4,300 6.3 Rural 54.3 25.5 7.7 6.0 6.5 0.0 100.0 3,868 0.0 Khyber Pakhtunkhwa 35.7 25.1 14.4 12.2 12.5 0.1 100.0 4,907 3.1 Urban 23.5 21.7 16.6 16.4 21.8 0.0 100.0 984 6.1 Rural 38.7 25.9 13.9 11.1 10.2 0.2 100.0 3,923 2.5 Balochistan 52.0 20.4 8.7 9.4 9.3 0.1 100.0 2,074 0.0 Urban 43.2 18.9 10.1 11.6 16.0 0.2 100.0 579 1.8 Rural 55.5 21.0 8.2 8.6 6.7 0.0 100.0 1,495 0.0 ICT Islamabad 16.4 21.1 14.3 18.4 29.6 0.2 100.0 302 7.8 FATA 42.8 27.8 12.9 9.0 7.4 0.0 100.0 671 1.3 Total5 34.0 24.9 14.3 13.7 13.0 0.1 100.0 33,355 4.0 Azad Jammu and Kashmir 22.9 23.2 19.8 20.5 13.5 0.1 100.0 4,161 5.8 Urban 15.7 21.5 18.8 22.2 21.8 0.0 100.0 744 7.5 Rural 24.5 23.6 20.1 20.1 11.7 0.1 100.0 3,418 5.4 Gilgit Baltistan 33.4 26.4 16.0 11.5 12.7 0.1 100.0 2,944 3.7 1 Primary refers to completing classes 1-5. 2 Middle refers to completing classes 6-8. 3 Secondary refers to completing classes 9-10. 4 Higher refers to completing class 11 and above. 5 Total excludes Azad Jammu and Kashmir and Gilgit Baltistan. Total includes three cases with missing information on age. Housing Characteristics and Household Population • 31 Table 2.14 School attendance ratios Net attendance ratios (NARs) and gross attendance ratios (GARs) for the de facto household population by sex and level of schooling; and the Gender Parity Index (GPI), according to background characteristics, Pakistan DHS 2017-18 Net attendance ratio1 Gross attendance ratio2 Background characteristic Male Female Total Gender Parity Index3 Male Female Total Gender Parity Index3 PRIMARY SCHOOL Residence Urban 68.4 66.4 67.4 0.97 98.8 95.4 97.1 0.97 Rural 58.0 50.3 54.2 0.87 90.3 73.6 82.0 0.81 Wealth quintile Lowest 42.3 30.2 36.3 0.71 70.4 44.8 57.7 0.64 Second 57.9 52.6 55.4 0.91 92.3 84.1 88.5 0.91 Middle 67.7 63.9 65.8 0.94 104.3 93.3 98.7 0.89 Fourth 74.9 69.6 72.3 0.93 106.8 98.1 102.6 0.92 Highest 74.7 72.6 73.6 0.97 101.3 96.8 99.0 0.96 Region Punjab 65.8 63.1 64.4 0.96 94.3 89.2 91.7 0.95 Urban 71.7 68.9 70.3 0.96 97.9 95.3 96.6 0.97 Rural 62.6 60.2 61.4 0.96 92.3 86.2 89.2 0.93 Sindh 57.4 53.3 55.4 0.93 90.6 79.2 85.1 0.87 Urban 67.4 69.2 68.3 1.03 102.9 104.0 103.4 1.01 Rural 49.1 40.5 44.9 0.82 80.5 59.2 70.1 0.74 Khyber Pakhtunkhwa 63.4 49.2 56.6 0.78 101.2 75.1 88.6 0.74 Urban 67.6 58.8 63.2 0.87 104.9 89.6 97.3 0.85 Rural 62.6 47.2 55.2 0.75 100.4 72.1 86.9 0.72 Balochistan 44.2 32.8 38.7 0.74 71.5 52.1 62.2 0.73 Urban 46.7 40.0 43.5 0.86 76.7 61.2 69.2 0.80 Rural 43.4 30.4 37.1 0.70 69.8 49.0 59.8 0.70 ICT Islamabad 73.3 75.0 74.1 1.02 103.3 96.3 99.8 0.93 FATA 54.1 25.9 40.1 0.48 105.9 40.0 73.3 0.38 Total4 61.4 55.4 58.5 0.90 93.1 80.6 86.9 0.87 Azad Jammu and Kashmir 70.0 71.4 70.7 1.02 99.0 105.7 102.3 1.07 Urban 73.9 75.6 74.7 1.02 97.0 110.2 102.9 1.14 Rural 69.2 70.6 69.9 1.02 99.4 104.9 102.2 1.06 Gilgit Baltistan 58.8 57.8 58.3 0.98 97.6 92.5 95.1 0.95 MIDDLE/SECONDARY SCHOOL Residence Urban 47.9 49.8 48.9 1.04 76.4 70.8 73.6 0.93 Rural 35.7 28.3 32.0 0.79 56.4 38.1 47.2 0.68 Wealth quintile Lowest 20.5 8.3 14.4 0.40 35.1 10.1 22.7 0.29 Second 33.5 22.0 27.7 0.66 55.3 29.6 42.3 0.54 Middle 40.6 38.3 39.5 0.94 63.0 53.8 58.5 0.85 Fourth 48.0 55.7 51.9 1.16 78.6 79.3 79.0 1.01 Highest 66.2 66.3 66.3 1.00 97.2 91.0 94.0 0.94 Region Punjab 43.5 46.7 45.1 1.07 66.2 62.8 64.5 0.95 Urban 52.1 57.7 54.9 1.11 82.8 80.5 81.7 0.97 Rural 38.8 41.0 40.0 1.06 57.3 53.7 55.5 0.94 Sindh 35.0 26.2 30.5 0.75 57.3 37.4 47.2 0.65 Urban 43.5 43.1 43.3 0.99 69.0 62.6 65.7 0.91 Rural 27.3 10.5 18.9 0.38 46.9 13.9 30.4 0.30 Khyber Pakhtunkhwa 43.0 26.2 34.9 0.61 68.6 37.1 53.5 0.54 Urban 52.4 45.6 49.1 0.87 78.8 64.0 71.7 0.81 Rural 40.8 21.8 31.7 0.53 66.3 31.1 49.3 0.47 Balochistan 27.4 20.7 23.9 0.75 49.2 33.0 40.8 0.67 Urban 30.2 28.6 29.5 0.95 58.6 45.3 52.1 0.77 Rural 26.2 17.8 21.7 0.68 45.2 28.5 36.3 0.63 ICT Islamabad 56.0 63.0 59.3 1.13 88.8 88.3 88.5 0.99 FATA 27.3 6.5 17.9 0.24 54.7 12.3 35.6 0.22 Total4 39.9 35.6 37.7 0.89 63.2 49.1 56.1 0.78 Azad Jammu and Kashmir 61.2 56.5 58.7 0.92 89.7 77.5 83.3 0.86 Urban 64.3 66.7 65.6 1.04 94.1 89.9 91.9 0.96 Rural 60.7 54.6 57.5 0.90 88.9 75.2 81.8 0.85 Gilgit Baltistan 54.9 43.4 49.1 0.79 91.0 72.1 81.4 0.79 1 The NAR for primary school is the percentage of the primary-school age (5-9 years) population that is attending primary school. The NAR for middle/secondary school is the percentage of the middle/secondary-school age (10-14 years) population that is attending secondary school. By definition the NAR cannot exceed 100.0. 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 middle/secondary school is the total number of middle/secondary school students, expressed as a percentage of the official middle/secondary-school-age population. If there are significant numbers of overage and underage students at a given level of schooling, the GAR can exceed 100.0 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 middle/secondary school is the ratio of the middle/secondary school NAR (GAR) for females to the NAR (GAR) for males. 4 Total excludes Azad Jammu and Kashmir and Gilgit Baltistan. 32 • Housing Characteristics and Household Population Table 2.15 Reasons for children dropping out of school Percent distribution of the de facto household members age 5-24 who dropped out of school by the main reason for not attending school, according to sex and residence, Pakistan DHS 2017-18 Urban Rural Total Main reason Male Female Male Female Male Female Reasons for not attending school School too far 0.2 2.1 2.7 13.5 1.8 9.1 Transport not available 0.0 0.2 0.6 1.2 0.4 0.8 Further education not necessary 8.9 20.7 6.6 16.6 7.5 18.2 Required for household/farm 2.5 4.3 8.7 9.2 6.3 7.3 Got married 0.7 22.3 1.3 15.9 1.0 18.4 Costs too much 11.9 15.9 10.1 11.6 10.8 13.2 Not interested in studies 28.7 16.2 33.8 17.1 31.9 16.8 Repeated failures 0.8 0.2 1.6 1.3 1.3 0.9 Did not get admission 0.4 0.5 0.6 0.7 0.5 0.6 Not safe 0.0 0.9 0.2 0.9 0.1 0.9 Need to earn 36.1 4.1 25.1 0.7 29.4 2.0 Other 8.3 11.1 7.4 10.0 7.8 10.5 Don’t know/missing 1.5 1.5 1.3 1.3 1.3 1.4 Total 100.0 100.0 100.0 100.0 100.0 100.0 Number 1,451 1,541 2,339 2,452 3,790 3,994 Note: Table excludes Azad Jammu and Kashmir and Gilgit Baltistan. Characteristics of Respondents • 33 CHARACTERISTICS OF RESPONDENTS 3 Key Findings ▪ Marital status: 96% of ever-married women and 98% of ever-married men are currently married, while 4% of women and 2% of men are divorced, separated, or widowed. ▪ Education: Ever-married men are more likely than ever-married women to have secondary or higher education (39% versus 25%). ▪ Exposure to media: Television is the most commonly accessed form of media among both women (51%) and men (55%). Men also are more likely than women to be exposed to the radio and newspapers. Among internet users, however, 60% of women and 53% of men reported daily use in the past 12 months. ▪ Employment: 17% of women and 96% of men are currently employed. ▪ Occupation: Women are more likely to be employed in agriculture than men (32% and 21%, respectively). About a quarter of women (24%) who are involved in agriculture do not receive any payment for their work. ▪ Health insurance: Women are less likely than men to have health insurance. Overall, 8% of women and 9% of men benefit from the Benazir Income Support Programme (BISP). ▪ Tobacco use: More men than women smoke and use other types of tobacco. While 23% of men use a form of tobacco; only 5% of women do. 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 2017-18 PDHS interviewed 12,364 ever-married women and 3,145 ever-married men age 15-49 in the country, 1,720 ever-married women and 336 ever-married men in Azad Jammu and Kashmir, and 984 ever-married women and 210 ever-married men in Gilgit Baltistan (Tables 3.1.1, 3.1.2, and 3.1.3). Table 3.1.1 indicates that the percentage of ever-married women rises with age until age group 25-29, after which it declines. Among ever-married men, the percentage peaks at age group 35-39. This reflects the occurrence of later marriages among men. Forty-one percent of ever-married women and 29% of ever- married men are under age 30. As expected, almost all ever-married women (96%) and ever-married men (98%) are currently married, while 4% of ever-married women and 2% of ever-married men are divorced, separated, or widowed. More than 6 in 10 ever-married women (63%) and men (60%) live in rural areas. Nearly half of the ever-married women (49%) and one-fourth (25%) of ever-married men are uneducated. T 34 • Characteristics of Respondents Table 3.1.2 shows that Azad Jammu and Kashmir is predominantly rural with 83% of ever-married women and 81% of ever-married men residing in the rural areas. Thirty-three percent of ever-married women have no education compared with only 10% of ever-married men. Gilgit Baltistan is also predominantly rural with 83% of ever-married women and 80% of ever-married men living in the rural areas (Table 3.1.3). More than half of the ever-married women have no education (54%) compared with only 23% of ever-married men having no education. 3.2 EDUCATION AND LITERACY Literacy Respondents who have attended higher than secondary school are assumed to be literate. All other respondents, shown a typed sentence to read aloud, are considered literate if they could read all or part of the sentence. Sample: Ever married women and men age 15-49 Men are more likely than women to have secondary or higher education (39% and 25%, respectively) (Figure 3.1, Tables 3.2.1 and 3.2.2). Half of women and one-fourth of men have no education. Seventy percent of men are literate, as compared with 50% of women (Tables 3.3.1 and 3.3.2) Trends: The median number of years of schooling among respondents age 15-49 has increased slightly since the 2012-13 PDHS, from zero to 1.0 among ever-married women and from 5.0 to 7.0 among ever-married men. The literacy rate among married women in 2017-18 is 6 percentage points higher than the rate reported in 2012-13 (44%). Patterns by background characteristics ▪ Urban women and men (43% and 52%, respectively) are more likely to have completed secondary or higher education than their rural counterparts (15% and 30%, respectively) (Figure 3.2, Tables 3.2.1 and 3.2.2). ▪ The proportions of women and men with secondary or higher education are highest among those in the highest wealth quintile (65% and 72% respectively) (Tables 3.2.1 and 3.2.2). ▪ By region, women in FATA are least likely to have completed secondary or higher education (3%) compared with women in ICT Islamabad (50%) (Table 3.2.1). ▪ Women from FATA are least likely to be literate (9%) followed by Balochistan (16%) (Table 3.3.1). Similarly, men in Balochistan (55%) are comparatively less literate than men in other regions (Table 3.3.2). Figure 3.1 Education of survey respondents Figure 3.2 Secondary education by residence 49 25 17 20 9 15 12 20 13 19 Women Men Percent distribution of women and men age 15-49 by highest level of schooling attended or completed Higher Secondary Middle Primary No education Note: Excludes Azad Jammu and Kashmir and Gilgit Baltistan 25 43 15 39 52 30 Total Urban Rural Percentage of women and men age 15-49 with secondary education complete or higher Women Men Note: Excludes Azad Jammu and Kashmir and Gilgit Baltistan Characteristics of Respondents • 35 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: Ever-married women and men age 15-49 Television is the most commonly accessed form of media among both women (51%) and men (55%). Men are more likely than women to be exposed to the other two forms of media: 27% of men and 5% of women read a newspaper, while 8% of men and 4% of women listen to the radio (Figure 3.3, Tables 3.4.1 and 3.4.2). Forty-seven percent of women and 36% of men have no access to any of the three media. Trends: Women have been getting more access to media in the last 5 years, so the proportion of ever- married women having no access to any of the three media declined from 51% in 2012-13 to 47% in 2017-18. Overall, 12% of women and 28% of men age 15-49 reported having used the internet in the past 12 months. Among those who had used the internet in the past 12 months, more than half of women and men tended to use it on a daily basis during the past month (60% and 53%, respectively) (Tables 3.5.1 and 3.5.2). Patterns by background characteristics ▪ Women and men residing in urban areas are more exposed to mass media, particularly television (71% and 68%, respectively). ▪ Rural women are more likely than their urban counterparts (58% and 27%, respectively) to have no access to the three media (newspaper, television, and radio). The pattern is similar among men (45% versus 24%) (Tables 3.4.1 and 3.4.2). ▪ Exposure to mass media increases with increasing educational attainment and wealth (Tables 3.4.1 and 3.4.2). ▪ Among regions, ever-married women from ICT Islamabad are more likely to watch television (78%) as compared with women in FATA (6%). A similar pattern is found among ever-married men. ▪ Internet use is least common among those living in rural areas, those who are not educated, and those in the lowest wealth quintile (Tables 3.5.1 and 3.5.2). ▪ Internet use in the past 12 months is relatively higher in urban areas (22% of women and 40% of men) than in rural areas (7% of women and 21% of men). Figure 3.3 Exposure to mass media 5 51 4 <1 47 27 55 8 3 36 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 Note: Excludes Azad Jammu and Kashmir and Gilgit Baltistan 36 • Characteristics of Respondents 3.4 EMPLOYMENT Currently employed Respondents who were employed in the 7 days before the survey Sample: Ever-married women and men age 15-49 More women than men were unemployed in the past 12 months (80% versus 2%). Seventeen percent of women and 96% of men reported current employment (Tables 3.6.1 and 3.6.2). Trends: Current employment among men has remained stagnant in the past 5 years (96%). Among women, current employment has declined from 27% in 2012-13 to 17% in 2017-18. Patterns by background characteristics ▪ Younger women and men (age 20-24) are less likely to be employed (12% and 95%, respectively) than older women and men (Tables 3.6.1 and 3.6.2). ▪ Eighteen percent of women and 93% of men who have higher education are currently employed, while 21% of women and 96% of men who have no education are employed. ▪ Among regions, FATA has <1% of ever-married women who are currently employed while Sindh has 21% and Punjab has 20% (Table 3.6.1). ▪ Women in the fourth and highest wealth quintile (12% each) are less likely to be employed than their counterparts in the lowest wealth quintile (27%) (Figure 3.4 and Table 3.6.1). 3.5 OCCUPATION Occupation Categorised as professional/technical/managerial, clerical, sales and services, skilled manual, unskilled manual, domestic service, agriculture, and other Sample: Ever-married women and men age 15-49 who were currently employed or had worked in the 12 months before the survey Figure 3.4 Employment status by wealth 27 21 16 12 12 98 95 96 97 95 Lowest Second Middle Fourth Highest Percentage of women and men age 15-49 who are currently employed Women Men WealthiestPoorest Note: Excludes Azad Jammu and Kashmir and Gilgit Baltistan Characteristics of Respondents • 37 Women are far more likely to be employed in agriculture than men (32% versus 21%) (Figure 3.5, Tables 3.7.1 and 3.7.2). Women are slightly less likely than men to be employed in professional/technical/ managerial occupations (12% versus 13%), as well as clerical services (less than 1% versus 3%), sales and services (14% versus 22%), and unskilled manual labour (7% versus 22%). Women are more likely to be involved in skilled manual labour than men (35% versus 20%). Twenty-four percent of women who were employed in agriculture in the past 12 months did not receive any payment for their work (Table 3.8). Trends: Involvement in agricultural work has decreased among women over the past 5 years, from 37% in 2012-13 to 32% in 2017-18. In contrast, involvement in professional/technical/managerial work has increased, from 8% to 12% among ever- married women and from 8% to 13% among ever- married men. Patterns by background characteristics ▪ Urban women are more likely to be involved in skilled manual work (43%) and in professional/technical/managerial occupations (25%), while rural women are more likely to be involved in agriculture (44%) (Tables 3.7.1 and 3.7.2). ▪ Among the employed, the percentage employed in agriculture falls with each increase in the wealth quintile, from 54% of women and 50% of men in the lowest wealth quintile to a low of 3% of women and 5% of men in the highest wealth quintile. 3.6 HEALTH INSURANCE COVERAGE AND SAFETY NET The overall objective of insurance coverage is to promote equitable access to sustainable quality health care, increase financial protection, and enhance social inclusion for the majority of people. Overall, Tables 3.9.1 and 3.9.2 show that women are less likely than men to have any type of health insurance in Pakistan (1% versus 4%, respectively). Women and men with higher education are more likely to have any type of health insurance as compared with the rest of the women and men (3% and 10%, respectively). Benazir Income Support Programme (BISP) is the largest social safety net programme in Pakistan. Currently 5.4 million women beneficiaries are covered by this programme through an unconditional cash grant (UCT) (Memon 2017). Overall, 8% of women and 9% men are receiving benefits from the BISP. The majority of the beneficiaries belong to the lowest and second wealth quintile (30% of women and 32% of men). Rural women and men (11% each) are more likely to have benefited from the programme than urban women and men (3% and 5%, respectively). Among the regions, the coverage is higher in Sindh (13% of women and 17% of men), Khyber Pakhtunkhwa (13% of women and 16% of men), FATA (13% of women and 11% of men), and Gilgit Baltistan (12% of women and 17% of men) (Table 3.10). Figure 3.5 Occupation 12 <1 14 35 7 32 13 3 22 20 22 21 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 Note: Excludes Azad Jammu and Kashmir and Gilgit Baltistan 38 • Characteristics of Respondents 3.7 TOBACCO USE Men are more likely than women to use tobacco. Twenty-three percent of men use any type of tobacco, as compared with 5% of women. Among those who smoke other tobacco products, cigarettes are most common (22% of men and 3% of women) (Tables 3.11.1 and 3.11.2). While almost 77% of men are non- smokers, 20% smoke on a daily basis and 3% smoke occasionally. Among those who smoke cigarettes daily, 48% of women (data not shown) and 17% of men smoke fewer than five cigarettes a day (Table 3.12). Trends: Use of cigarettes has decreased slightly during the past 5 years among ever-married men, from 28% to 22%. Among ever-married women it has increased from 1% in 2012-13 to 3% in 2017-18. Patterns by background characteristics ▪ Among men, the prevalence of cigarette smoking rises consistently with age, from 13% among those age 20-24 to 31% among those age 45-49 (Table 3.11.2). ▪ Cigarette smoking decreases with education attainment: 4% of women and 23% of men with no education smoke cigarettes, as compared with 3% of women and 16% of men with higher education (Tables 3.11.1 and 3.11.2). ▪ Sindh and Balochistan have more women who use cigarettes (6% each), while Balochistan has the highest proportion of women who use other types of tobacco too (13%). Among men, Azad Jammu and Kashmir have the highest proportion using cigarettes (31%). ▪ Use of any type of smokeless tobacco is much higher among men (15%) than among women (3%) (Table 3.13). 3.8 KNOWLEDGE CONCERNING TUBERCULOSIS Ninety-one percent of women and 96% of men age 15-49 have heard of tuberculosis (TB). Among those who report having heard of tuberculosis, 55% of women and 53% of men know that TB is spread through the air by coughing or sneezing. (Tables 3.14.1 and 3.14.2). Patterns by background characteristics ▪ Women in rural areas (49%) are less likely than women in urban areas (66%) to correctly report that TB is spread through the air by coughing or sneezing (Table 3.14.1). ▪ The percentage of women and men who correctly report that TB is spread through the air by coughing or sneezing increases remarkably with increasing wealth; 36% of women and 34% of men in the lowest wealth quintile have correct knowledge regarding the spread of TB, compared with 74% of women and 68% of men in the highest quintile. 3.9 KNOWLEDGE CONCERNING HEPATITIS Eighty-eight percent of women and 94% of men age 15-49 have heard of hepatitis B or C. Among those who reported having heard of hepatitis, 18% of women and 34% of men mentioned that avoiding contaminated food/water will prevent them from getting, hepatitis; 13% of women and 23% of men mentioned that using a disposable syringe will help prevent hepatitis (Tables 3.15.1 and 3.15.2). Characteristics of Respondents • 39 Patterns by background characteristics ▪ Women in rural areas (87%) are less likely than women in urban areas (91%) to have heard of hepatitis B or C (Tables 3.15.1 and 3.15.2). ▪ The percentage of women and men who have heard of hepatitis increases remarkably with increasing wealth; 81% of women and 89% of men in the lowest wealth quintile have heard of hepatitis B or C, compared with 95% of women and 97% of men in the highest quintile. LIST OF TABLES For more information on the characteristics of survey respondents, see the following tables: ▪ Table 3.1.1 Background characteristics of respondents ▪ Table 3.1.2 Background characteristics of respondents (Azad Jammu and Kashmir) ▪ Table 3.1.3 Background characteristics of respondents (Gilgit Baltistan) ▪ Table 3.2.1 Educational attainment: Women ▪ Table 3.2.2 Educational attainment: Men ▪ Table 3.3.1 Literacy: Women ▪ Table 3.3.2 Literacy: Men ▪ Table 3.4.1 Exposure to mass media: Women ▪ Table 3.4.2 Exposure to mass media: Men ▪ Table 3.5.1 Internet usage: Women ▪ Table 3.5.2 Internet usage: Men ▪ Table 3.6.1 Employment status: Women ▪ Table 3.6.2 Employment status: Men ▪ Table 3.7.1 Occupation: Women ▪ Table 3.7.2 Occupation: Men ▪ Table 3.8 Type of employment: Women ▪ Table 3.9.1 Health insurance coverage: Women ▪ Table 3.9.2 Health insurance coverage: Men ▪ Table 3.10 Benefit from Benazir Income Support Programme ▪ Table 3.11.1 Tobacco smoking: Women ▪ Table 3.11.2 Tobacco smoking: Men ▪ Table 3.12 Average number of cigarettes smoked daily by men ▪ Table 3.13 Smokeless tobacco use and any tobacco use ▪ Table 3.14.1 Knowledge concerning tuberculosis: Women ▪ Table 3.14.2 Knowledge concerning tuberculosis: Men ▪ Table 3.15.1 Knowledge concerning hepatitis: Women ▪ Table 3.15.2 Knowledge concerning hepatitis: Men 40 • Characteristics of Respondents Table 3.1.1 Background characteristics of respondents Percent distribution of ever-married women and men age 15-49 by selected background characteristics, Pakistan DHS 2017-18 Women Men Background characteristic Weighted percent Weighted number Unweighted number Weighted percent Weighted number Unweighted number Age 15-19 4.8 600 661 1.3 40 48 20-24 15.3 1,889 1,861 8.4 265 268 25-29 20.6 2,548 2,591 19.3 607 582 30-34 19.5 2,413 2,310 19.2 603 651 35-39 17.5 2,163 2,213 19.6 617 633 40-44 11.6 1,437 1,468 16.0 502 482 45-49 10.6 1,316 1,260 16.2 511 481 Marital status Married 95.7 11,831 11,902 98.1 3,084 3,091 Divorced/separated 1.6 203 157 1.4 43 34 Widowed 2.7 330 305 0.6 18 20 Residence Urban 36.8 4,550 6,098 40.2 1,264 1,640 Rural 63.2 7,814 6,266 59.8 1,881 1,505 Education No education 49.2 6,080 6,682 25.4 800 800 Primary1 16.5 2,037 1,693 20.3 640 545 Middle2 9.4 1,160 980 15.2 478 440 Secondary3 11.8 1,463 1,327 20.1 633 634 Higher4 13.1 1,624 1,682 18.9 594 726 Wealth quintile Lowest 18.3 2,258 2,406 17.6 554 579 Second 19.7 2,430 2,451 19.5 613 647 Middle 20.3 2,504 2,310 19.7 619 570 Fourth 21.0 2,594 2,441 21.6 680 656 Highest 20.9 2,579 2,756 21.6 680 693 Region Punjab 53.6 6,630 3,400 52.7 1,657 853 Sindh 23.1 2,850 2,739 24.9 784 778 Khyber Pakhtunkhwa 15.4 1,901 2,378 13.9 438 505 Balochistan 5.2 642 1,724 5.9 185 522 ICT Islamabad 0.9 107 1,111 1.0 32 265 FATA 1.9 234 1,012 1.5 49 222 Total 100.0 12,364 12,364 100.0 3,145 3,145 Note: Education categories refer to the highest level of education attended. Table excludes Azad Jammu and Kashmir and Gilgit Baltistan. 1 Primary refers to classes 1-5. 2 Middle refers to classes 6-8. 3 Secondary refers to classes 9-10. 4 Higher refers to class 11 and above. Characteristics of Respondents • 41 Table 3.1.2 Background characteristics of respondents (Azad Jammu and Kashmir) Percent distribution of ever-married women and men age 15-49 by selected background characteristics, Pakistan DHS 2017-18 Women Men Background characteristic Weighted percent Weighted number Unweighted number Weighted percent Weighted number Unweighted number Age 15-19 1.8 31 30 0.0 0 0 20-24 13.5 232 207 5.7 19 15 25-29 21.1 363 361 16.2 54 45 30-34 20.4 350 362 20.3 68 69 35-39 19.1 329 338 19.3 65 66 40-44 12.0 206 219 15.1 51 59 45-49 12.1 208 203 23.4 79 82 Marital status Married 95.8 1,648 1,643 97.7 328 327 Divorced/separated 2.1 36 38 1.7 6 6 Widowed 2.1 35 39 0.5 2 3 Residence Urban 17.0 292 846 19.3 65 172 Rural 83.0 1,428 874 80.7 271 164 Education No education 33.1 569 480 10.4 35 34 Primary1 18.0 310 302 13.7 46 46 Middle2 16.1 276 265 22.7 76 76 Secondary3 17.1 294 328 34.9 117 105 Higher4 15.7 270 345 18.3 61 75 Wealth quintile Lowest 12.2 209 173 10.4 35 30 Second 27.2 468 424 24.1 81 82 Middle 27.9 480 487 32.4 109 99 Fourth 18.8 324 354 13.9 47 55 Highest 13.9 239 282 19.1 64 70 Total 100.0 1,720 1,720 100.0 336 336 Note: Education categories refer to the highest level of education attended. 1 Primary refers to classes 1-5. 2 Middle refers to classes 6-8. 3 Secondary refers to classes 9-10. 4 Higher refers to class 11 and above. 42 • Characteristics of Respondents Table 3.1.3 Background characteristics of respondents (Gilgit Baltistan) Percent distribution of ever-married women and men age 15-49 by selected background characteristics, Pakistan DHS 2017-18 Women Men Background characteristic Weighted percent Weighted number Unweighted number Weighted percent Weighted number Unweighted number Age 15-19 3.7 37 37 0.5 1 1 20-24 13.7 135 152 4.5 9 10 25-29 21.7 214 194 20.5 43 45 30-34 19.8 195 181 23.9 50 45 35-39 18.7 184 187 18.9 40 37 40-44 12.3 121 134 16.6 35 39 45-49 9.9 97 99 15.1 32 33 Marital status Married 97.4 958 957 100.0 210 210 Divorced/separated 0.9 9 6 0.0 0 0 Widowed 1.8 17 21 0.0 0 0 Residence Urban 17.0 168 310 19.6 41 72 Rural 83.0 816 674 80.4 169 138 Education No education 53.9 530 465 22.8 48 35 Primary1 11.1 110 108 19.2 40 37 Middle2 8.0 78 81 10.9 23 25 Secondary3 13.2 129 151 17.3 36 43 Higher4 13.9 137 179 29.8 63 70 Wealth quintile Lowest 39.0 383 307 40.2 84 63 Second 38.7 380 365 34.6 73 72 Middle 12.9 127 169 14.9 31 39 Fourth 5.6 55 83 4.4 9 14 Highest 3.9 38 60 5.9 12 22 Total 100.0 984 984 100.0 210 210 Note: Education categories refer to the highest level of education attended. 1 Primary refers to classes 1-5. 2 Middle refers to classes 6-8. 3 Secondary refers to classes 9-10. 4 Higher refers to class 11 and above. Characteristics of Respondents • 43 Table 3.2.1 Educational attainment: Women Percent distribution of ever-married women age 15-49 by highest level of schooling attended or completed, and median years completed, according to background characteristics, Pakistan DHS 2017-18 Highest level of schooling Total Median years completed Number of women Background characteristic No education Primary1 Middle2 Secondary3 Higher4 Age 15-24 46.4 18.4 11.9 13.2 10.0 100.0 2.9 2,489 15-19 54.0 18.5 13.1 10.9 3.6 100.0 0.0 600 20-24 44.0 18.4 11.6 14.0 12.1 100.0 3.8 1,889 25-29 43.8 15.3 10.2 14.2 16.5 100.0 4.1 2,548 30-34 42.4 18.1 10.4 12.5 16.5 100.0 4.2 2,413 35-39 49.4 16.5 8.1 13.4 12.5 100.0 0.8 2,163 40-44 59.8 14.5 6.6 7.7 11.4 100.0 0.0 1,437 45-49 65.1 14.0 6.3 5.4 9.2 100.0 0.0 1,316 Residence Urban 27.8 16.6 12.7 19.1 23.9 100.0 7.2 4,550 Rural 61.6 16.4 7.5 7.6 6.9 100.0 0.0 7,814 Wealth quintile Lowest 90.0 7.6 1.2 0.9 0.3 100.0 0.0 2,258 Second 74.8 16.9 4.0 3.1 1.2 100.0 0.0 2,430 Middle 50.5 23.0 12.2 9.3 5.1 100.0 0.0 2,504 Fourth 27.0 22.2 15.2 19.8 15.8 100.0 5.3 2,594 Highest 10.3 11.7 13.1 24.1 40.8 100.0 9.6 2,579 Region Punjab 38.1 20.7 11.5 14.1 15.5 100.0 4.4 6,630 Urban 19.6 19.3 14.0 20.9 26.2 100.0 7.7 2,402 Rural 48.6 21.6 10.1 10.2 9.5 100.0 1.3 4,228 Sindh 54.7 13.1 7.8 11.1 13.3 100.0 0.0 2,850 Urban 31.4 14.4 12.2 18.8 23.2 100.0 6.8 1,527 Rural 81.5 11.6 2.7 2.4 1.8 100.0 0.0 1,323 Khyber Pakhtunkhwa 64.2 11.7 7.4 8.6 8.2 100.0 0.0 1,901 Urban 43.7 12.9 10.3 14.9 18.2 100.0 4.2 366 Rural 69.1 11.4 6.7 7.0 5.8 100.0 0.0 1,535 Balochistan 83.7 5.7 3.1 3.9 3.6 100.0 0.0 642 Urban 70.0 8.0 5.6 7.3 9.2 100.0 0.0 188 Rural 89.4 4.8 2.1 2.5 1.2 100.0 0.0 454 ICT Islamabad 25.0 16.7 8.4 18.1 31.6 100.0 8.0 107 FATA 90.4 5.0 1.5 1.4 1.7 100.0 0.0 234 Total5 49.2 16.5 9.4 11.8 13.1 100.0 1.3 12,364 Azad Jammu and Kashmir 33.1 18.0 16.1 17.1 15.7 100.0 4.9 1,720 Urban 15.6 17.5 15.2 23.7 28.0 100.0 8.3 292 Rural 36.7 18.2 16.2 15.7 13.2 100.0 4.6 1,428 Gilgit Baltistan 53.9 11.1 8.0 13.2 13.9 100.0 0.0 984 1 Primary refers to classes 1-5. 2 Middle refers to classes 6-8. 3 Secondary refers to classes 9-10. 4 Higher refers to class 11 and above. 5 Total excludes Azad Jammu and Kashmir and Gilgit Baltistan. 44 • Characteristics of Respondents Table 3.2.2 Educational attainment: Men Percent distribution of ever-married men age 15-49 by highest level of schooling attended or completed, and median years completed, according to background characteristics, Pakistan DHS 2017-18 Highest level of schooling Total Median years completed Number of men Background characteristic No education Primary1 Middle2 Secondary3 Higher4 Age 15-24 26.7 25.4 18.7 12.8 16.4 100.0 4.9 305 15-19 (25.8) (24.2) (16.6) (20.8) (12.6) 100.0 (5.0) 40 20-24 26.8 25.6 19.0 11.5 17.0 100.0 4.8 265 25-29 27.4 18.9 18.4 15.5 19.8 100.0 6.3 607 30-34 20.9 19.9 16.1 22.4 20.7 100.0 7.4 603 35-39 19.2 24.7 15.1 24.5 16.4 100.0 7.1 617 40-44 27.4 16.0 13.8 26.1 16.8 100.0 7.2 502 45-49 33.3 18.5 9.8 16.3 22.1 100.0 4.8 511 Residence Urban 13.7 18.4 15.7 25.3 27.0 100.0 8.4 1,264 Rural 33.3 21.7 14.9 16.7 13.4 100.0 4.6 1,881 Wealth quintile Lowest 59.3 22.6 8.0 7.1 3.0 100.0 0.0 554 Second 38.6 26.8 10.5 16.8 7.2 100.0 3.9 613 Middle 22.9 24.5 19.5 19.3 13.8 100.0 5.7 619 Fourth 9.7 20.4 21.3 26.4 22.2 100.0 7.9 680 Highest 4.0 8.8 15.3 28.3 43.6 100.0 9.7 680 Region Punjab 20.6 22.5 18.9 23.2 14.9 100.0 7.1 1,657 Urban 12.1 21.7 18.4 28.0 19.8 100.0 7.8 660 Rural 26.2 23.0 19.2 20.0 11.6 100.0 5.3 997 Sindh 28.2 19.5 9.2 16.1 27.0 100.0 6.4 784 Urban 13.8 15.5 11.9 22.0 36.8 100.0 9.4 441 Rural 46.7 24.7 5.7 8.4 14.4 100.0 1.9 342 Khyber Pakhtunkhwa 31.6 16.5 15.1 16.6 20.2 100.0 5.9 438 Urban 13.7 13.3 17.3 25.1 30.6 100.0 9.0 87 Rural 36.1 17.3 14.5 14.5 17.6 100.0 4.6 350 Balochistan 45.6 14.0 6.8 17.5 16.1 100.0 4.1 185 Urban 33.9 12.0 8.4 20.5 25.2 100.0 7.3 56 Rural 50.7 14.9 6.1 16.1 12.2 100.0 0.0 129 ICT Islamabad 6.8 14.8 19.8 24.8 33.9 100.0 9.1 32 FATA 25.9 23.5 17.3 20.9 12.5 100.0 5.2 49 Total5 25.4 20.3 15.2 20.1 18.9 100.0 6.7 3,145 Azad Jammu and Kashmir 10.4 13.7 22.7 34.9 18.3 100.0 8.3 336 Urban 9.3 12.8 21.5 27.3 29.1 100.0 8.8 65 Rural 10.7 14.0 23.0 36.7 15.7 100.0 8.2 271 Gilgit Baltistan 22.8 19.2 10.9 17.3 29.8 100.0 7.7 210 Note: Figures in parentheses are based on 25-49 unweighted cases. 1 Primary refers to classes 1-5. 2 Middle refers to classes 6-8. 3 Secondary refers to classes 9-10. 4 Higher refers to class 11 and above. 5 Total excludes Azad Jammu and Kashmir and Gilgit Baltistan. Characteristics of Respondents • 45 Table 3.3.1 Literacy: Women Percent distribution of ever-married women age 15-49 by level of schooling attended and level of literacy, and percentage literate, according to background characteristics, Pakistan DHS 2017-18 Class 10 or higher No schooling and classes 1-9 Total Percentage literate1 Number of women Background characteristic Can read a whole sentence Can read part of a sentence Cannot read at all No card with required language Blind/ visually impaired Age 15-24 21.2 25.1 6.1 47.6 0.0 0.0 100.0 52.4 2,489 15-19 12.6 24.1 7.5 55.8 0.0 0.0 100.0 44.2 600 20-24 23.9 25.5 5.6 45.0 0.0 0.0 100.0 55.0 1,889 25-29 29.1 21.7 4.7 44.3 0.1 0.0 100.0 55.5 2,548 30-34 27.5 22.6 6.6 43.2 0.0 0.0 100.0 56.8 2,413 35-39 24.5 19.9 4.9 50.7 0.0 0.0 100.0 49.2 2,163 40-44 18.0 18.5 5.3 58.0 0.0 0.2 100.0 41.8 1,437 45-49 13.7 18.3 4.1 64.0 0.0 0.0 100.0 36.0 1,316 Residence Urban 41.0 24.4 5.5 29.1 0.0 0.1 100.0 70.8 4,550 Rural 13.3 19.9 5.3 61.5 0.0 0.0 100.0 38.5 7,814 Wealth quintile Lowest 1.1 4.9 3.3 90.5 0.1 0.0 100.0 9.4 2,258 Second 3.8 15.5 5.6 75.1 0.0 0.0 100.0 24.9 2,430 Middle 12.9 30.2 6.5 50.4 0.0 0.0 100.0 49.6 2,504 Fourth 32.7 32.2 6.7 28.3 0.0 0.1 100.0 71.6 2,594 Highest 62.5 22.6 4.5 10.4 0.0 0.0 100.0 89.6 2,579 Region Punjab 27.5 29.5 5.1 37.7 0.0 0.0 100.0 62.2 6,630 Urban 44.8 30.2 4.0 21.0 0.0 0.0 100.0 79.0 2,402 Rural 17.8 29.2 5.8 47.3 0.1 0.0 100.0 52.7 4,228 Sindh 23.4 13.2 6.8 56.4 0.0 0.1 100.0 43.5 2,850 Urban 40.2 19.2 7.6 32.7 0.0 0.3 100.0 67.0 1,527 Rural 4.0 6.3 5.9 83.7 0.0 0.0 100.0 16.3 1,323 Khyber Pakhtunkhwa 16.0 14.1 4.7 65.2 0.0 0.0 100.0 34.8 1,901 Urban 31.8 18.4 5.6 44.1 0.0 0.0 100.0 55.8 366 Rural 12.3 13.0 4.5 70.2 0.0 0.0 100.0 29.8 1,535 Balochistan 7.2 4.4 4.2 84.1 0.0 0.0 100.0 15.9 642 Urban 16.2 6.7 6.2 70.9 0.0 0.0 100.0 29.1 188 Rural 3.5 3.5 3.4 89.6 0.0 0.0 100.0 10.4 454 ICT Islamabad 46.0 21.4 6.4 26.0 0.1 0.0 100.0 73.9 107 FATA 3.0 3.3 2.6 91.0 0.0 0.0 100.0 9.0 234 Total2 23.5 21.5 5.4 49.6 0.0 0.0 100.0 50.4 12,364 Azad Jammu and Kashmir 28.5 29.4 5.9 36.2 0.0 0.0 100.0 63.8 1,720 Urban 45.4 29.3 7.5 17.7 0.1 0.0 100.0 82.2 292 Rural 25.0 29.4 5.6 39.9 0.0 0.0 100.0 60.0 1,428 Gilgit Baltistan 25.9 9.3 8.6 56.2 0.0 0.0 100.0 43.8 984 1 Refers to women who attended class 10 or higher and women who can read a whole sentence or part of a sentence 2 Total excludes Azad Jammu and Kashmir and Gilgit Baltistan. 46 • Characteristics of Respondents Table 3.3.2 Literacy: Men Percent distribution of ever-married men age 15-49 by level of schooling attended and level of literacy, and percentage literate, according to background characteristics, Pakistan DHS 2017-18 Class 10 or higher No schooling and classes 1-9 Total Percentage literate1 Number of men Background characteristic Can read a whole sentence Can read part of a sentence Cannot read at all No card with required language Blind/ visually impaired Age 15-24 26.4 26.3 15.3 31.7 0.3 0.0 100.0 68.0 305 15-19 (24.1) (22.4) (15.1) (38.4) (0.0) (0.0) 100.0 (61.6) 40 20-24 26.8 26.9 15.3 30.7 0.3 0.0 100.0 69.0 265 25-29 31.6 25.6 11.2 31.6 0.0 0.0 100.0 68.4 607 30-34 37.7 25.1 10.9 26.4 0.0 0.0 100.0 73.6 603 35-39 35.3 28.1 12.1 24.5 0.0 0.0 100.0 75.5 617 40-44 38.5 21.7 8.8 31.0 0.0 0.0 100.0 69.0 502 45-49 36.0 16.9 10.3 36.5 0.0 0.3 100.0 63.2 511 Residence Urban 47.1 23.5 11.3 18.0 0.0 0.0 100.0 82.0 1,264 Rural 26.6 24.3 11.1 37.9 0.0 0.1 100.0 62.0 1,881 Wealth quintile Lowest 8.6 15.6 13.6 62.2 0.0 0.0 100.0 37.8 554 Second 20.1 20.7 13.4 45.6 0.0 0.2 100.0 54.1 613 Middle 28.8 30.2 13.0 28.0 0.0 0.0 100.0 72.0 619 Fourth 44.0 31.3 9.5 15.0 0.1 0.0 100.0 84.8 680 Highest 65.7 21.0 7.2 6.1 0.0 0.0 100.0 93.9 680 Region Punjab 32.0 32.5 10.5 24.9 0.0 0.1 100.0 75.0 1,657 Urban 39.7 32.0 11.0 17.2 0.0 0.0 100.0 82.8 660 Rural 26.9 32.7 10.2 30.0 0.0 0.1 100.0 69.9 997 Sindh 41.7 13.5 12.8 31.9 0.0 0.0 100.0 68.1 784 Urban 57.5 13.9 11.7 16.9 0.0 0.0 100.0 83.1 441 Rural 21.5 12.9 14.3 51.3 0.0 0.0 100.0 48.7 342 Khyber Pakhtunkhwa 33.0 17.6 9.6 39.7 0.0 0.0 100.0 60.2 438 Urban 49.7 17.8 13.6 18.7 0.2 0.0 100.0 81.1 87 Rural 28.9 17.5 8.6 45.0 0.0 0.0 100.0 55.0 350 Balochistan 33.1 9.6 12.0 44.9 0.5 0.0 100.0 54.6 185 Urban 45.2 8.0 10.2 36.7 0.0 0.0 100.0 63.3 56 Rural 27.8 10.3 12.7 48.5 0.7 0.0 100.0 50.8 129 ICT Islamabad 52.4 30.2 5.4 12.0 0.0 0.0 100.0 88.0 32 FATA 29.4 14.5 20.9 35.3 0.0 0.0 100.0 64.7 49 Total2 34.8 24.0 11.2 29.9 0.0 0.0 100.0 70.0 3,145 Azad Jammu and Kashmir 44.0 29.7 9.9 16.4 0.0 0.0 100.0 83.6 336 Urban 48.8 32.8 5.5 12.9 0.0 0.0 100.0 87.1 65 Rural 42.8 29.0 11.0 17.2 0.0 0.0 100.0 82.8 271 Gilgit Baltistan 45.8 13.7 10.1 30.5 0.0 0.0 100.0 69.5 210 Note: Figures in parentheses are based on 25-49 unweighted cases. 1 Refers to men who attended class 10 or higher and men who can read a whole sentence or part of a sentence 2 Total excludes Azad Jammu and Kashmir and Gilgit Baltistan. Characteristics of Respondents • 47 Table 3.4.1 Exposure to mass media: Women Percentage of ever-married women age 15-49 who are exposed to specific media on a weekly basis, according to background characteristics, Pakistan DHS 2017-18 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 3.3 38.1 4.5 0.3 58.1 600 20-24 4.7 49.1 4.1 0.8 48.8 1,889 25-29 4.9 52.9 4.1 0.5 44.8 2,548 30-34 5.4 53.1 2.7 0.4 44.5 2,413 35-39 5.2 51.2 3.6 0.3 46.1 2,163 40-44 5.8 52.0 3.7 0.4 45.2 1,437 45-49 5.2 46.7 4.0 0.6 50.5 1,316 Residence Urban 8.7 70.7 3.2 0.6 27.2 4,550 Rural 3.0 38.9 4.0 0.4 58.4 7,814 Education No education 0.2 31.7 3.7 0.0 66.0 6,080 Primary 4.3 57.5 3.5 0.2 39.5 2,037 Middle 5.7 67.5 4.2 0.5 30.5 1,160 Secondary 9.2 74.4 3.8 1.2 22.8 1,463 Higher 20.0 78.9 3.3 1.7 18.2 1,624 Wealth quintile Lowest 0.5 14.2 3.4 0.0 83.4 2,258 Second 1.2 32.0 4.1 0.2 64.4 2,430 Middle 2.4 53.3 4.5 0.2 44.2 2,504 Fourth 7.0 69.6 3.1 0.7 28.6 2,594 Highest 13.5 78.2 3.4 1.2 19.5 2,579 Region Punjab 5.2 60.3 2.2 0.5 38.4 6,630 Urban 7.7 74.9 2.0 0.5 23.6 2,402 Rural 3.7 52.0 2.3 0.4 46.9 4,228 Sindh 6.6 51.6 3.9 0.6 46.7 2,850 Urban 10.7 71.5 3.7 0.8 26.7 1,527 Rural 1.8 28.5 4.0 0.4 69.8 1,323 Khyber Pakhtunkhwa 3.3 26.9 4.4 0.3 69.0 1,901 Urban 7.7 53.6 3.9 0.1 41.9 366 Rural 2.2 20.6 4.5 0.4 75.4 1,535 Balochistan 2.9 28.0 14.4 0.3 59.7 642 Urban 6.9 44.8 11.2 0.8 47.8 188 Rural 1.3 21.1 15.8 0.1 64.6 454 ICT Islamabad 16.1 77.5 6.1 2.4 20.0 107 FATA 0.7 5.6 8.6 0.0 86.8 234 Total1 5.1 50.6 3.7 0.5 46.9 12,364 Azad Jammu and Kashmir 6.7 51.2 5.3 0.8 45.9 1,720 Urban 9.8 66.6 3.9 0.6 31.6 292 Rural 6.0 48.1 5.6 0.9 48.9 1,428 Gilgit Baltistan 3.9 43.5 2.5 0.1 55.5 984 1 Total excludes Azad Jammu and Kashmir and Gilgit Baltistan. 48 • Characteristics of Respondents Table 3.4.2 Exposure to mass media: Men Percentage of ever-married men age 15-49 who are exposed to specific media on a weekly basis, according to background characteristics, Pakistan DHS 2017-18 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 men Age 15-19 (17.6) (53.0) (14.1) (5.1) (32.8) 40 20-24 19.2 49.9 6.8 0.7 41.1 265 25-29 23.7 54.6 8.7 1.7 37.5 607 30-34 30.2 62.2 8.6 3.5 31.6 603 35-39 29.4 59.6 8.9 3.6 30.7 617 40-44 29.5 49.2 7.6 2.1 40.7 502 45-49 26.8 52.5 8.0 2.9 40.9 511 Residence Urban 32.5 68.3 7.8 2.9 24.2 1,264 Rural 23.4 46.8 8.7 2.4 44.5 1,881 Education No education 0.8 30.9 7.4 0.0 65.1 800 Primary 16.7 52.6 8.4 1.0 38.2 640 Middle 31.6 66.0 5.8 2.2 24.4 478 Secondary 42.8 63.3 10.3 5.3 24.6 633 Higher 53.3 74.5 9.5 5.4 17.8 594 Wealth quintile Lowest 10.2 18.2 9.2 1.4 71.8 554 Second 14.4 45.7 9.5 1.1 44.5 613 Middle 29.0 62.5 9.4 2.6 27.6 619 Fourth 34.1 68.1 6.2 2.7 26.0 680 Highest 43.4 75.3 7.8 5.0 18.3 680 Region Punjab 27.9 65.8 6.0 2.6 28.5 1,657 Urban 30.3 75.2 5.9 2.2 20.2 660 Rural 26.3 59.7 6.0 2.8 34.0 997 Sindh 27.2 49.3 11.4 3.3 39.5 784 Urban 33.6 59.6 10.1 3.8 29.2 441 Rural 19.0 36.0 13.0 2.7 52.7 342 Khyber Pakhtunkhwa 27.8 38.0 11.7 2.0 49.2 438 Urban 46.4 67.2 10.1 3.8 20.6 87 Rural 23.1 30.8 12.1 1.6 56.4 350 Balochistan 17.8 34.1 5.6 1.3 58.8 185 Urban 25.2 53.5 7.3 2.8 40.6 56 Rural 14.6 25.6 4.8 0.6 66.7 129 ICT Islamabad 42.8 81.8 16.1 7.9 12.7 32 FATA 14.0 18.8 13.9 0.5 66.0 49 Total1 27.1 55.4 8.3 2.6 36.3 3,145 Azad Jammu and Kashmir 27.8 62.3 9.0 0.7 29.1 336 Urban 44.8 70.1 5.6 0.9 21.7 65 Rural 23.8 60.4 9.8 0.7 30.9 271 Gilgit Baltistan 27.2 57.2 7.9 1.3 37.1 210 Note: Figures in parentheses are based on 25-49 unweighted cases. 1 Total excludes Azad Jammu and Kashmir and Gilgit Baltistan. Characteristics of Respondents • 49 Table 3.5.1 Internet usage: Women Percentage of ever-married women age 15-49 who have ever used the internet, and percentage who have used the internet in the past 12 months; and among women who have used the internet in the past 12 months, percent distribution by frequency of internet use in the past month, according to background characteristics, Pakistan DHS 2017-18 Ever used the internet Used the internet in the past 12 months Number Among respondents who have used the internet in the past 12 months, percentage who, in the past month, used internet: Background characteristic Almost every day At least once a week Less than once a week Not at all Missing Total Number Age 15-19 6.5 5.7 600 (34.4) (45.9) (19.7) (0.0) (0.0) 100.0 34 20-24 14.6 14.1 1,889 56.3 25.9 14.9 2.3 0.6 100.0 267 25-29 16.1 15.3 2,548 61.2 28.0 9.8 1.0 0.0 100.0 390 30-34 15.1 14.1 2,413 62.4 23.8 10.3 3.5 0.0 100.0 340 35-39 11.2 11.0 2,163 63.3 26.2 10.4 0.1 0.0 100.0 238 40-44 8.5 8.4 1,437 61.6 23.4 14.4 0.6 0.0 100.0 120 45-49 8.1 7.4 1,316 59.7 25.0 14.4 0.9 0.0 100.0 98 Residence Urban 22.4 21.5 4,550 62.8 26.1 9.2 1.7 0.2 100.0 980 Rural 6.9 6.5 7,814 55.3 26.4 16.9 1.3 0.0 100.0 507 Education No education 1.1 1.0 6,080 49.0 29.1 17.1 4.7 0.0 100.0 59 Primary 6.4 6.1 2,037 50.8 27.8 20.0 1.4 0.0 100.0 124 Middle 11.8 10.8 1,160 55.5 30.3 12.9 0.0 1.4 100.0 125 Secondary 22.4 21.4 1,463 55.6 25.7 17.6 1.1 0.0 100.0 313 Higher 55.3 53.3 1,624 64.8 25.4 8.0 1.8 0.0 100.0 865 Wealth quintile Lowest 0.2 0.2 2,258 * * * * * * 5 Second 1.6 1.5 2,430 (39.7) (33.2) (25.6) (1.6) (0.0) 100.0 37 Middle 4.3 3.8 2,504 44.9 25.3 26.4 3.5 0.0 100.0 94 Fourth 14.3 13.5 2,594 56.2 26.2 15.0 2.5 0.0 100.0 350 Highest 40.3 38.8 2,579 64.1 25.9 8.6 1.1 0.2 100.0 1,001 Region Punjab 15.7 15.2 6,630 58.1 27.4 12.6 1.9 0.0 100.0 1,009 Urban 25.9 25.3 2,402 59.1 29.2 9.5 2.2 0.0 100.0 608 Rural 9.9 9.5 4,228 56.4 24.7 17.4 1.5 0.0 100.0 401 Sindh 11.7 11.0 2,850 69.1 21.5 8.1 0.8 0.5 100.0 313 Urban 20.5 19.2 1,527 72.0 19.0 7.6 0.7 0.6 100.0 294 Rural 1.5 1.5 1,323 * * * * * * 19 Khyber Pakhtunkhwa 6.8 6.0 1,901 53.6 28.4 17.0 1.0 0.0 100.0 114 Urban 13.3 12.0 366 51.4 28.4 17.7 2.5 0.0 100.0 44 Rural 5.2 4.5 1,535 55.0 28.5 16.5 0.0 0.0 100.0 70 Balochistan 2.8 2.3 642 60.9 31.7 7.0 0.4 0.0 100.0 15 Urban 9.2 7.5 188 61.1 32.8 5.6 0.4 0.0 100.0 14 Rural 0.2 0.1 454 * * * * * * 0 ICT Islamabad 31.7 31.0 107 68.9 23.2 7.2 0.7 0.0 100.0 33 FATA 1.5 1.3 234 * * * * * * 3 Total1 12.6 12.0 12,364 60.3 26.2 11.8 1.6 0.1 100.0 1,487 Azad Jammu and Kashmir 13.4 12.6 1,720 65.3 24.8 8.0 1.8 0.0 100.0 217 Urban 23.1 22.8 292 71.5 20.2 4.9 3.5 0.0 100.0 67 Rural 11.4 10.6 1,428 62.6 26.9 9.4 1.1 0.0 100.0 151 Gilgit Baltistan 6.7 5.9 984 41.3 36.1 20.5 2.0 0.0 100.0 58 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 Total excludes Azad Jammu and Kashmir and Gilgit Baltistan. 50 • Characteristics of Respondents Table 3.5.2 Internet usage: Men Percentage of ever-married men age 15-49 who have ever used the internet ever, and percentage who have used the internet in the past 12 months; and among men who have used the internet in the past 12 months, percent distribution by frequency of internet use in the past month, according to background characteristics, Pakistan DHS 2017-18 Ever used the internet Used the internet in the past 12 months Number Among respondents who have used the internet in the past 12 months, percentage who, in the past month, used internet: Background characteristic Almost every day At least once a week Less than once a week Not at all Missing Total Number Age 15-19 (31.1) (26.2) 40 * * * * * * 10 20-24 31.2 30.6 265 58.0 33.2 8.0 0.9 0.0 100.0 81 25-29 31.5 31.0 607 54.4 34.5 11.1 0.0 0.0 100.0 188 30-34 36.8 33.9 603 58.0 27.5 14.2 0.1 0.3 100.0 205 35-39 31.8 30.0 617 47.3 42.0 10.7 0.0 0.0 100.0 185 40-44 24.0 22.2 502 55.1 30.1 14.8 0.0 0.0 100.0 112 45-49 22.4 21.7 511 48.1 31.6 20.3 0.0 0.0 100.0 111 Residence Urban 42.3 40.1 1,264 54.1 31.9 14.0 0.0 0.0 100.0 506 Rural 21.5 20.5 1,881 51.8 35.7 12.2 0.2 0.1 100.0 386 Education No education 4.8 3.7 800 (61.4) (32.6) (6.0) (0.0) (0.0) 100.0 30 Primary 11.8 10.9 640 26.6 45.4 28.0 0.0 0.0 100.0 70 Middle 31.4 30.2 478 32.3 48.3 18.9 0.5 0.0 100.0 144 Secondary 40.9 38.8 633 51.7 31.3 16.9 0.0 0.1 100.0 246 Higher 69.9 67.8 594 65.5 27.6 6.8 0.0 0.1 100.0 403 Wealth quintile Lowest 6.5 5.7 554 (48.2) (42.4) (7.2) (2.2) (0.0) 100.0 32 Second 11.8 11.2 613 40.8 46.7 12.4 0.1 0.0 100.0 69 Middle 22.1 21.4 619 46.3 45.3 8.5 0.0 0.0 100.0 132 Fourth 37.9 35.5 680 49.0 30.7 20.3 0.0 0.0 100.0 241 Highest 64.1 61.5 680 60.1 28.6 11.2 0.0 0.1 100.0 418 Region Punjab 31.3 30.4 1,657 49.4 34.7 15.9 0.0 0.0 100.0 504 Urban 43.4 42.3 660 50.6 31.8 17.6 0.0 0.0 100.0 279 Rural 23.2 22.5 997 47.9 38.4 13.8 0.0 0.0 100.0 225 Sindh 27.0 24.3 784 53.1 34.9 12.0 0.0 0.0 100.0 190 Urban 39.3 35.4 441 53.2 34.3 12.5 0.0 0.0 100.0 156 Rural 11.2 9.9 342 (52.6) (37.8) (9.6) (0.0) (0.0) 100.0 34 Khyber Pakhtunkhwa 30.2 29.5 438 67.0 24.9 7.6 0.5 0.0 100.0 129 Urban 47.1 45.7 87 72.9 25.6 1.5 0.0 0.0 100.0 40 Rural 26.0 25.5 350 64.3 24.6 10.3 0.8 0.0 100.0 89 Balochistan 26.5 23.0 185 55.8 39.3 4.4 0.0 0.5 100.0 43 Urban 41.2 37.4 56 60.9 34.2 3.8 0.0 1.1 100.0 21 Rural 20.1 16.8 129 (50.8) (44.2) (5.0) (0.0) (0.0) 100.0 22 ICT Islamabad 55.2 54.4 32 65.5 22.1 9.5 1.1 1.8 100.0 18 FATA 18.3 18.3 49 (28.9) (55.8) (15.3) (0.0) (0.0) 100.0 9 Total1 29.8 28.4 3,145 53.1 33.5 13.2 0.1 0.1 100.0 892 Azad Jammu and Kashmir 26.6 25.5 336 63.0 26.0 8.3 2.7 0.0 100.0 86 Urban 41.7 39.7 65 48.1 32.0 16.3 3.6 0.0 100.0 26 Rural 23.0 22.2 271 (69.3) (23.5) (4.9) (2.3) (0.0) 100.0 60 Gilgit Baltistan 34.1 33.3 210 57.6 32.9 8.0 0.0 1.5 100.0 70 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 Total excludes Azad Jammu and Kashmir and Gilgit Baltistan. Characteristics of Respondents • 51 Table 3.6.1 Employment status: Women Percent distribution of ever-married women age 15-49 by employment status, according to background characteristics, Pakistan DHS 2017-18 Employed in the 12 months preceding the survey Not employed in the 12 months preceding the survey Total Number of women Background characteristic Currently employed1 Not currently employed Age 15-19 8.7 3.9 87.4 100.0 600 20-24 11.9 3.3 84.8 100.0 1,889 25-29 13.5 2.5 84.0 100.0 2,548 30-34 17.8 2.8 79.4 100.0 2,413 35-39 22.6 2.3 75.1 100.0 2,163 40-44 21.6 2.8 75.6 100.0 1,437 45-49 21.8 2.2 75.9 100.0 1,316 Marital status Married 16.3 2.6 81.0 100.0 11,831 Divorced/separated/ widowed 38.9 3.8 57.3 100.0 533 Number of living children 0 13.5 3.5 83.0 100.0 1,760 1-2 14.7 2.2 83.0 100.0 3,834 3-4 19.1 2.2 78.6 100.0 3,837 5+ 20.5 3.4 76.1 100.0 2,933 Residence Urban 14.4 1.3 84.3 100.0 4,550 Rural 19.0 3.5 77.5 100.0 7,814 Education No education 21.0 3.5 75.4 100.0 6,080 Primary 15.5 2.9 81.5 100.0 2,037 Middle 8.4 1.8 89.7 100.0 1,160 Secondary 9.9 0.5 89.5 100.0 1,463 Higher 18.4 1.9 79.6 100.0 1,624 Wealth quintile Lowest 27.3 5.6 67.1 100.0 2,258 Second 21.3 4.2 74.4 100.0 2,430 Middle 16.2 2.4 81.4 100.0 2,504 Fourth 11.6 0.9 87.5 100.0 2,594 Highest 11.5 0.9 87.6 100.0 2,579 Region Punjab 19.7 3.9 76.4 100.0 6,630 Urban 15.3 1.5 83.1 100.0 2,402 Rural 22.1 5.2 72.6 100.0 4,228 Sindh 21.3 2.2 76.5 100.0 2,850 Urban 14.7 1.1 84.2 100.0 1,527 Rural 29.0 3.5 67.5 100.0 1,323 Khyber Pakhtunkhwa 7.4 0.4 92.2 100.0 1,901 Urban 9.2 0.7 90.1 100.0 366 Rural 7.0 0.4 92.7 100.0 1,535 Balochistan 10.1 0.8 89.1 100.0 642 Urban 8.7 1.4 90.0 100.0 188 Rural 10.6 0.6 88.8 100.0 454 ICT Islamabad 15.8 1.0 82.8 100.0 107 FATA 0.9 0.0 99.1 100.0 234 Total2 17.3 2.7 80.0 100.0 12,364 Azad Jammu and Kashmir 11.3 0.5 88.3 100.0 1,720 Urban 14.8 0.4 84.8 100.0 292 Rural 10.5 0.5 89.0 100.0 1,428 Gilgit Baltistan 7.5 0.9 91.7 100.0 984 1 “Currently employed” is defined as having done work in the past seven days. Includes persons who did not work in the past seven days but who are regularly employed and were absent from work for leave, illness, vacation, or any other such reason 2 Total excludes Azad Jammu and Kashmir and Gilgit Baltistan. 52 • Characteristics of Respondents Table 3.6.2 Employment status: Men Percent distribution of ever-married men age 15-49 by employment status, according to background characteristics, Pakistan DHS 2017-18 Employed in the 12 months preceding the survey Not employed in the 12 months preceding the survey Total Number of men Background characteristic Currently employed1 Not currently employed Age 15-19 (89.5) (0.7) (9.8) 100.0 40 20-24 95.3 1.6 3.0 100.0 265 25-29 96.1 0.8 3.1 100.0 607 30-34 97.2 1.1 1.6 100.0 603 35-39 97.2 2.0 0.8 100.0 617 40-44 96.3 1.9 1.9 100.0 502 45-49 94.5 2.2 3.4 100.0 511 Marital status Married 96.2 1.6 2.2 100.0 3,084 Divorced/separated/ widowed 94.3 0.0 5.7 100.0 61 Number of living children 0 94.4 1.3 4.4 100.0 467 1-2 96.8 1.6 1.5 100.0 1,067 3-4 96.0 1.2 2.8 100.0 962 5+ 96.5 2.2 1.3 100.0 650 Residence Urban 96.4 1.1 2.5 100.0 1,264 Rural 96.0 1.8 2.1 100.0 1,881 Education No education 96.3 1.7 2.0 100.0 800 Primary 98.9 0.7 0.4 100.0 640 Middle 95.2 2.8 2.0 100.0 478 Secondary 96.5 1.2 2.3 100.0 633 Higher 93.4 1.6 5.0 100.0 594 Wealth quintile Lowest 97.7 1.0 1.3 100.0 554 Second 95.4 1.7 2.9 100.0 613 Middle 96.0 2.3 1.6 100.0 619 Fourth 96.5 1.4 2.1 100.0 680 Highest 95.4 1.3 3.3 100.0 680 Region Punjab 96.9 1.2 1.9 100.0 1,657 Urban 96.4 1.1 2.5 100.0 660 Rural 97.2 1.3 1.5 100.0 997 Sindh 97.7 0.7 1.7 100.0 784 Urban 97.4 1.0 1.6 100.0 441 Rural 98.0 0.2 1.8 100.0 342 Khyber Pakhtunkhwa 91.5 4.7 3.8 100.0 438 Urban 92.5 2.0 5.5 100.0 87 Rural 91.3 5.3 3.4 100.0 350 Balochistan 94.8 1.5 3.5 100.0 185 Urban 93.0 1.5 5.4 100.0 56 Rural 95.6 1.5 2.7 100.0 129 ICT Islamabad 95.2 0.4 4.4 100.0 32 FATA 92.9 1.3 5.9 100.0 49 Total2 96.1 1.6 2.3 100.0 3,145 Azad Jammu and Kashmir 88.0 6.0 5.9 100.0 336 Urban 96.1 2.3 1.2 100.0 65 Rural 86.1 6.9 7.0 100.0 271 Gilgit Baltistan 87.8 10.3 2.0 100.0 210 Note: Figures in parentheses are based on 25-49 unweighted cases. 1 “Currently employed” is defined as having done work in the past seven days. Includes persons who did not work in the past seven days but who are regularly employed and were absent from work for leave, illness, vacation, or any other such reason 2 Total excludes Azad Jammu and Kashmir and Gilgit Baltistan. Characteristics of Respondents • 53 Table 3.7.1 Occupation: Women Percent distribution of ever-marri

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