Pakistan Demographic and Health Survey 2012p-13

Publication date: 2013

Pakistan Demographic and Health Survey 2012-13 Pakistan 2012-13 D em ographic and H ealth Survey PAKISTAN DEMOGRAPHIC AND HEALTH SURVEY 2012-13 National Institute of Population Studies Islamabad, Pakistan MEASURE DHS ICF International Calverton, Maryland, USA December 2013 This report summarizes the findings of the 2012-13 Pakistan Demographic and Health Survey (PDHS), conducted under the aegis of the Ministry of National Health Services, Regulations and Coordination and implemented by the National Institute of Population Studies (NIPS). ICF International provided financial and technical assistance for the survey through USAID/Pakistan. The PDHS is part of the worldwide Demographic and Health Survey program, which is designed to collect data on fertility, family planning, and maternal and child health. The opinions expressed in this report are those of the authors and do not necessarily reflect the views of USAID and the government of Pakistan. Additional information about the 2012-13 PDHS may be obtained from the National Institute of Population Studies (NIPS), Block 12-A, Capital Centre, G-8 Markaz, P.O. Box 2197, Islamabad, Pakistan (telephone: 92- 51-926-2790 or 926-2756; fax: 92-51-926-2754; Internet: http://www.nips.org.pk). Additional information about the MEASURE DHS project may be obtained from ICF International, 11785 Beltsville Drive, Suite 300, Calverton, MD 20705, USA (telephone: 301-572-0200; fax: 301-572-0999; e-mail: reports@macrointernational.com; Internet: http://www.measuredhs.com). Suggested citation: National Institute of Population Studies (NIPS) [Pakistan] and ICF International. 2013. Pakistan Demographic and Health Survey 2012-13. Islamabad, Pakistan, and Calverton, Maryland, USA: NIPS and ICF International. Contents • iii CONTENTS TABLES AND FIGURES . vii FOREWORD . xiii ACKNOWLEDGMENTS . xv TECHNICAL ADVISORY COMMITTEE . xvii CONTRIBUTORS TO THE REPORT . xix ABBREVIATIONS . xxi MILLENNIUM DEVELOPMENT GOAL INDICATORS . xxiii MAP OF PAKISTAN . xxiv 1 INTRODUCTION . 1 1.1 History and Physical Features of Pakistan . 1 1.2 Population . 2 1.3 Objectives of the Survey . 3 1.4 Organization of the Survey . 3 1.5 Survey Implementation . 4 1.5.1 Sample Design . 4 1.5.2 Questionnaires . 4 1.5.3 Training . 5 1.5.4 Fieldwork . 6 1.5.5 Field Supervision and Monitoring . 6 1.5.6 Field Problems and Challenges . 7 1.5.7 Data Processing . 7 1.6 Response Rates . 8 2 HOUSING CHARACTERISTICS AND HOUSEHOLD POPULATION . 9 2.1 Household Characteristics . 9 2.1.1 Water and Sanitation . 10 2.1.2 Housing Characteristics . 12 2.1.3 Household Possessions . 13 2.2 Socioeconomic Status Index . 14 2.3 Hand Washing . 15 2.4 Household Population by Age and Sex . 16 2.5 Household Composition . 19 2.6 Birth Registration of Children Under Age 5 . 20 2.7 Registration with NADRA . 21 2.8 Children’s Living Arrangements and Orphanhood . 22 2.9 Educational Attainment and School Attendance . 23 2.9.1 Educational Attainment of the Household Population . 24 2.9.2 School Attendance Ratios . 26 2.10 Migration Status . 29 2.11 Household Possession of Mosquito Nets . 32 2.12 Indoor Residual Spraying Against Mosquitoes . 33 2.13 Anti-Mosquito Actions . 34 3 CHARACTERISTICS OF RESPONDENTS . 37 3.1 Characteristics of Survey Respondents . 37 3.2 Educational Attainment . 38 3.3 Literacy . 40 3.4 Access to Mass Media . 43 3.5 Employment . 45 iv • Contents 3.6 Occupation . 48 3.7 Type of Employment . 51 3.8 Use of Tobacco . 52 3.9 Knowledge Concerning Tuberculosis . 54 3.10 Knowledge Concerning Hepatitis . 57 4 MARRIAGE . 61 4.1 Current Marital Status . 61 4.2 Polygyny . 62 4.3 Age at First Marriage . 64 4.4 Differentials in Age at First Marriage . 65 4.5 Consanguinity . 65 4.6 Recent Sexual Activity . 67 5 FERTILITY . 69 5.1 Current Fertility . 70 5.2 Fertility Trends . 71 5.3 Children Ever Born and Children Surviving . 73 5.4 Birth Intervals . 74 5.5 Postpartum Amenorrhea, Abstinence, and Insusceptibility . 75 5.6 Age at First Birth . 77 5.7 Teenage Fertility . 78 6 FERTILITY PREFERENCES . 81 6.1 Desire for More Children . 81 6.2 Desire to Limit Childbearing by Background Characteristics. 83 6.3 Ideal Family Size . 85 6.4 Fertility Planning . 88 6.5 Wanted Fertility Rates . 89 7 FAMILY PLANNING . 91 7.1 Knowledge of Contraceptive Methods . 92 7.2 Ever Use of Family Planning Methods . 93 7.3 Current Use of Contraceptive Methods . 94 7.4 Differentials in Contraceptive Use by Background Characteristics . 95 7.5 Trends in Current Use of Family Planning . 96 7.6 Timing of Sterilization . 97 7.7 Source of Contraception . 97 7.8 Use of Social Marketing Contraceptive Brands . 99 7.9 Informed Choice . 99 7.10 Side Effects of Family Planning Methods . 100 7.11 Treatment for Side Effects . 101 7.12 Contraceptive Discontinuation Rates . 103 7.13 Reasons for Discontinuation of Contraceptive Use . 103 7.14 Knowledge of Fertile Period . 104 7.15 Need and Demand for Family Planning Services . 105 7.16 Future Use of Contraception . 108 7.17 Exposure to Family Planning Messages . 108 7.18 Contact of Nonusers with Family Planning Providers . 111 7.19 Lady Health Worker Services . 112 7.20 Satisfaction with Family Planning Service Outlets . 113 7.21 Reasons for Not Visiting Family Planning Service Outlets . 114 Contents • v 8 INFANT AND CHILD MORTALITY . 117 8.1 Assessment of Data Quality . 118 8.2 Levels and Trends in Infant and Child Mortality . 119 8.3 Socioeconomic Differentials in Childhood Mortality . 121 8.4 Demographic Differentials in Mortality . 123 8.5 Perinatal Mortality . 124 8.6 High-Risk Fertility Behavior. 126 9 REPRODUCTIVE HEALTH . 129 9.1 Antenatal Care . 130 9.1.1 Number and Timing of Antenatal Visits . 132 9.2 Components of Antenatal Care . 133 9.3 Tetanus Toxoid Vaccinations . 135 9.4 Place of Delivery . 136 9.5 Assistance during Delivery . 138 9.6 Postnatal Care . 140 9.6.1 Timing of First Postnatal Checkup for Mother . 140 9.6.2 Provider of First Postnatal Checkup for Mother . 141 9.7 Newborn Care . 142 9.7.1 Provider of First Postnatal Checkup for Newborn . 144 9.8 Problems in Accessing Health Care . 145 10 CHILD HEALTH . 147 10.1 Child’s Weight and Size at Birth . 148 10.2 Vaccination Coverage . 149 10.3 Vaccination by Background Characteristics . 150 10.4 Trends in Immunization Coverage . 152 10.5 Prevalence and Treatment of Symptoms of ARI . 153 10.6 Prevalence and Treatment of Fever . 155 10.7 Prevalence of Diarrhea . 157 10.8 Diarrhea Treatment . 158 10.9 Feeding Practices during Diarrhea . 160 11 NUTRITION OF CHILDREN AND WOMEN . 163 11.1 Nutritional Status of Children . 163 11.1.1 Measurement of Nutritional Status among Young Children . 164 11.1.2 Data Collection . 165 11.1.3 Measures of Child Nutritional Status . 165 11.2 Breastfeeding and Complementary Feeding . 168 11.2.1 Initiation of Breastfeeding . 168 11.3 Breastfeeding Status by Age . 170 11.4 Duration of Breastfeeding . 172 11.5 Types of Complementary Foods . 173 11.6 Infant and Young Child Feeding (IYCF) Practices . 174 11.7 Micronutrient Intake among Children . 177 11.8 Nutritional Status of Women . 180 11.9 Micronutrient Intake among Mothers . 181 12 HIV/AIDS-RELATED KNOWLEDGE, ATTITUDES, AND BEHAVIOR . 185 12.1 Knowledge of AIDS . 186 12.2 Knowledge of HIV Prevention Methods . 186 12.3 Comprehensive Knowledge about AIDS . 188 12.4 Knowledge of Mother-to-Child Transmission of HIV . 191 12.5 Accepting Attitudes toward Those Living with HIV and AIDS . 192 12.6 Knowledge about Testing for HIV . 194 12.7 Self-Reporting of Sexually Transmitted Infections (STIs) . 195 12.8 Prevalence of Medical Injections . 197 vi • Contents 13 WOMEN’S EMPOWERMENT AND DEMOGRAPHIC AND HEALTH OUTCOMES . 199 13.1 Employment and Form of Earnings . 200 13.2 Women’s Control over Their Own Earnings and Relative Magnitude of Women’s Earnings . 201 13.3 Control over Husbands’ Earnings . 202 13.4 Women’s and Men’s Ownership of Selected Assets . 204 13.5 Women’s Participation in Decisionmaking . 206 13.6 Attitudes toward Wife Beating . 210 13.7 Women’s Empowerment Indicators . 213 13.8 Current Use of Contraception by Women’s Empowerment . 213 13.9 Ideal Family Size and Unmet Need by Women’s Empowerment . 214 13.10 Reproductive Health Care by Women’s Empowerment . 215 13.11 Infant and Child Mortality and Women’s Empowerment . 216 14 DOMESTIC VIOLENCE . 219 14.1 Valid Measures of Domestic Violence . 219 14.1.1 Use of Valid Measures of Violence . 219 14.1.2 Ethical Considerations in the 2012-13 PDHS . 220 14.1.3 Subsample for the Violence Module . 221 14.2 Experience of Physical Violence . 221 14.3 Perpetrators of Physical Violence . 223 14.4 Violence during Pregnancy . 223 14.5 Marital Control by Husband. 224 14.6 Forms of Spousal Violence . 226 14.7 Spousal Violence by Background Characteristics . 227 14.8 Violence by Spousal Characteristics and Women’s Empowerment Indicators . 229 14.9 Recent Spousal Violence . 231 14.10 Onset of Spousal Violence . 231 14.11 Physical Consequences of Spousal Violence . 232 14.12 Help-Seeking Behavior by Women Who Experience Violence . 232 REFERENCES . 235 APPENDIX A ADDITIONAL TABLES . 241 APPENDIX B SAMPLE DESIGN AND IMPLEMENTATION . 245 B.1 Introduction . 245 B.2 Sample Frame . 245 B.3 Sample Design and Implementation . 246 B.4 Selection Probabilities and Sample Weights . 248 APPENDIX C ESTIMATES OF SAMPLING ERRORS . 251 APPENDIX D DATA QUALITY TABLES . 263 APPENDIX E PERSONS INVOLVED IN THE SURVEY . 269 APPENDIX F QUESTIONNAIRES . 273 Tables and Figures • vii TABLES AND FIGURES 1 INTRODUCTION . 1 Table 1.1 Basic demographic indicators . 3 Table 1.2 Results of the household and individual interviews . 8 2 HOUSING CHARACTERISTICS AND HOUSEHOLD POPULATION . 9 Table 2.1 Household drinking water . 10 Table 2.2 Household sanitation facilities . 11 Table 2.3 Household characteristics . 12 Table 2.4 Household possessions . 14 Table 2.5 Wealth quintiles . 15 Table 2.6 Hand washing . 16 Table 2.7 Household population by age, sex, and residence. 17 Table 2.8 Trends in age distribution of household population . 19 Table 2.9 Household composition . 20 Table 2.10 Birth registration of children under age 5 . 21 Table 2.11 Registration with NADRA . 22 Table 2.12 Children’s living arrangements and orphanhood . 23 Table 2.13 School attendance by survivorship of parents . 23 Table 2.14.1 Educational attainment of the female household population . 24 Table 2.14.2 Educational attainment of the male household population . 25 Table 2.15 School attendance ratios . 27 Table 2.16 Reasons for children dropping out of school . 28 Table 2.17 Status of in-migration in households . 30 Table 2.18 Households with out-migration. 30 Table 2.19 Status of out-migration . 31 Table 2.20 Reasons for migration . 32 Table 2.21 Household possession of mosquito nets . 33 Table 2.22 Indoor residual spraying against mosquitoes . 34 Table 2.23 Other anti-mosquito actions . 35 Figure 2.1 Population pyramid . 18 Figure 2.2 Age-specific attendance rates . 28 3 CHARACTERISTICS OF RESPONDENTS . 37 Table 3.1 Background characteristics of respondents . 38 Table 3.2.1 Educational attainment: Women . 39 Table 3.2.2 Educational attainment: Men . 40 Table 3.3.1 Literacy: Women . 41 Table 3.3.2 Literacy: Men . 42 Table 3.4.1 Exposure to mass media: Women . 44 Table 3.4.2 Exposure to mass media: Men . 45 Table 3.5.1 Employment status: Women . 46 Table 3.5.2 Employment status: Men . 48 Table 3.6.1 Occupation: Women . 49 Table 3.6.2 Occupation: Men . 50 Table 3.7.1 Type of employment: Women . 51 Table 3.7.2 Type of employment: Men . 52 Table 3.8.1 Use of tobacco: Women . 53 Table 3.8.2 Use of tobacco: Men . 54 viii • Tables and Figures Table 3.9.1 Knowledge concerning tuberculosis: Women . 55 Table 3.9.2 Knowledge concerning tuberculosis: Men . 56 Table 3.10.1 Knowledge concerning hepatitis: Women . 58 Table 3.10.2 Knowledge concerning hepatitis: Men . 59 Figure 3.1 Literacy status of ever-married women and men, by region . 43 Figure 3.2 Women’s employment status in the past 12 months . 47 Figure 3.3 Women’s earnings by type of employment . 52 4 MARRIAGE . 61 Table 4.1 Current marital status . 62 Table 4.2.1 Number of women’s co-wives . 63 Table 4.2.2 Number of men’s wives . 63 Table 4.3 Age at first marriage . 64 Table 4.4 Median age at first marriage by background characteristics . 65 Table 4.5 Marriage between relatives . 66 Table 4.6 Recent sexual activity: Women . 67 5 FERTILITY . 69 Table 5.1 Current fertility . 70 Table 5.2 Fertility by background characteristics . 71 Table 5.3 Trends in age-specific fertility rates . 71 Table 5.4 Trends in fertility by background characteristics . 72 Table 5.5 Trends in age-specific and total fertility rates . 72 Table 5.6 Children ever born and living . 73 Table 5.7 Trends in children ever born . 74 Table 5.8 Birth intervals . 75 Table 5.9 Postpartum amenorrhea, abstinence, and insusceptibility . 76 Table 5.10 Median duration of amenorrhea, postpartum abstinence, and postpartum insusceptibility . 77 Table 5.11 Menopause . 77 Table 5.12 Age at first birth . 78 Table 5.13 Median age at first birth . 78 Table 5.14 Teenage pregnancy and motherhood . 79 Table 5.15 Pregnancy outcomes by background characteristics . 80 Figure 5.1 Trends in age-specific fertility rates . 73 6 FERTILITY PREFERENCES . 81 Table 6.1 Fertility preferences by number of living children . 82 Table 6.2.1 Desire to limit childbearing: Women . 84 Table 6.2.2 Desire to limit childbearing: Men . 84 Table 6.3 Desire to limit childbearing by sex of living children . 85 Table 6.4 Ideal number of children by number of living children . 86 Table 6.5 Mean ideal number of children . 87 Table 6.7 Fertility planning status . 88 Table 6.8 Wanted fertility rates . 89 7 FAMILY PLANNING . 91 Table 7.1 Knowledge of contraceptive methods . 93 Table 7.2 Ever use of contraception by age . 94 Table 7.3 Current use of contraception by age . 94 Table 7.4 Current use of contraception by background characteristics . 96 Table 7.5 Trends in the current use of contraception . 96 Table 7.6 Timing of sterilization . 97 Table 7.7 Source of modern contraception methods . 98 Tables and Figures • ix Table 7.9 Informed choice . 100 Table 7.10 Side effects from use of family planning methods. 101 Table 7.11 Treatment for side effects . 102 Table 7.12 Twelve-month contraceptive discontinuation rates . 103 Table 7.13 Reasons for discontinuation . 104 Table 7.14 Knowledge of fertile period . 104 Table 7.15 Need and demand for family planning among currently married women . 106 Table 7.16 Future use of contraception . 108 Table 7.17 Exposure to family planning messages . 109 Table 7.18.1 Exposure to specific family planning messages: Women . 110 Table 7.18.2 Exposure to specific family planning messages: Men . 111 Table 7.19 Contact of nonusers with family planning providers . 112 Table 7.20 Service from lady health worker (LHWs) . 113 Table 7.21 Satisfaction with family planning service outlets . 114 Table 7.22 Reasons for not visiting family planning service outlets . 115 Figure 7.1 Trends in contraceptive use among currently married women . 97 Figure 7.2 Source of treatment for side effects from use of family planning methods . 102 Figure 7.3 Trends in unmet need for family planning among currently married women age 15-49, 2006-07 and 2012-13 PDHS . 107 8 INFANT AND CHILD MORTALITY . 117 Table 8.1 Early childhood mortality rates . 119 Table 8.2 Trends in early childhood mortality rates . 121 Table 8.3 Early childhood mortality rates by socioeconomic characteristics . 122 Table 8.4 Early childhood mortality rates by demographic characteristics . 123 Table 8.5 Perinatal mortality . 125 Table 8.6 High-risk fertility behavior . 127 Figure 8.1 Trends in childhood mortality, 1986-2012 . 120 9 REPRODUCTIVE HEALTH . 129 Table 9.1 Antenatal care . 131 Table 9.2 Number of antenatal care visits and timing of first visit . 133 Table 9.3 Components of antenatal care . 134 Table 9.4 Tetanus toxoid injections . 135 Table 9.5 Place of delivery . 137 Table 9.6 Assistance during delivery . 139 Table 9.7 Timing of first postnatal checkup for the mother . 141 Table 9.8 Type of provider of first postnatal checkup for the mother . 142 Table 9.9 Timing of first postnatal checkup for the newborn . 143 Table 9.10 Type of provider of first postnatal checkup for the newborn . 144 Table 9.11 Problems in accessing health care . 146 Figure 9.1 Source of antenatal care . 132 Figure 9.2 Trends in place of delivery . 138 Figure 9.3 Mother’s duration of stay in the health facility after giving birth . 140 10 CHILD HEALTH . 147 Table 10.1 Child’s size and weight at birth . 149 Table 10.2 Vaccinations by source of information . 150 Table 10.3 Vaccinations by background characteristics . 151 Table 10.4 Trends in vaccination coverage . 152 Table 10.5 Prevalence and treatment of symptoms of ARI . 154 Table 10.6 Prevalence and treatment of fever . 156 x • Tables and Figures Table 10.7 Prevalence of diarrhea . 157 Table 10.8 Diarrhea treatment . 159 Table 10.9 Feeding practices during diarrhea . 161 Figure 10.1 Trends in vaccination coverage among children age 12-23 months . 152 11 NUTRITION OF CHILDREN AND WOMEN . 163 Table 11.1 Nutritional status of children . 166 Table 11.2 Initial breastfeeding . 169 Table 11.3 Breastfeeding status by age . 171 Table 11.4 Median duration of breastfeeding . 173 Table 11.5 Foods and liquids consumed by children in the day or night preceding the interview . 174 Table 11.6 Infant and young child feeding (IYCF) practices . 176 Table 11.7 Micronutrient intake among children . 178 Table 11.8 Nutritional status of women . 180 Table 11.9 Micronutrient intake among mothers . 182 Figure 11.1 Nutritional status of children by age . 168 Figure 11.2 Infant feeding practices by age . 171 Figure 11.3 IYCF indicators on breastfeeding status . 172 Figure 11.4 IYCF indicators on minimum acceptable diet . 177 12 HIV/AIDS-RELATED KNOWLEDGE, ATTITUDES, AND BEHAVIOR . 185 Table 12.1 Knowledge of AIDS . 186 Table 12.2 Knowledge of HIV prevention methods . 187 Table 12.3.1 Comprehensive knowledge about AIDS: Women . 189 Table 12.3.2 Comprehensive knowledge about AIDS: Men . 190 Table 12.4 Knowledge of prevention of mother-to-child transmission of HIV . 192 Table 12.5.1 Accepting attitudes toward those living with HIV/AIDS: Women . 193 Table 12.5.2 Accepting attitudes toward those living with HIV/AIDS: Men . 194 Table 12.6 Knowledge on where to get HIV testing . 195 Table 12.7 Self-reported prevalence of sexually transmitted infections (STIs) and STI symptoms . 196 Table 12.8 Prevalence of medical injections . 198 Figure 12.1 Comprehensive knowledge about AIDS among ever-married women and men age 15-49. 191 Figure 12.2 Women seeking treatment for STIs . 197 13 WOMEN’S EMPOWERMENT AND DEMOGRAPHIC AND HEALTH OUTCOMES . 199 Table 13.1 Employment and cash earnings of currently married women and men . 200 Table 13.2.1 Control over women’s cash earnings and relative magnitude of women’s cash earnings . 201 Table 13.2.2 Control over men’s cash earnings . 203 Table 13.3 Women’s control over their own earnings and over those of their husbands . 204 Table 13.4.1 Ownership of assets: Women . 205 Table 13.4.2 Ownership of assets: Men . 205 Table 13.5 Participation in decisionmaking . 206 Table 13.6.1 Women’s participation in decisionmaking by background characteristics . 208 Table 13.6.2 Men’s participation in decisionmaking by background characteristics . 209 Table 13.7.1 Attitude toward wife beating: Women . 211 Table 13.7.2 Attitude toward wife beating: Men . 212 Table 13.8 Indicators of women’s empowerment . 213 Table 13.9 Current use of contraception by women’s empowerment . 214 Tables and Figures • xi Table 13.10 Ideal number of children and unmet need for family planning by women’s empowerment . 215 Table 13.11 Reproductive health care by women’s empowerment . 216 Table 13.12 Early childhood mortality rates by women’s status . 217 Figure 13.1 Number of decisions in which currently married women participate . 207 14 DOMESTIC VIOLENCE . 219 Table 14.1 Experience of physical violence . 222 Table 14.2 Persons committing physical violence . 223 Table 14.3 Experience of violence during pregnancy . 224 Table 14.4 Marital control exercised by husbands . 225 Table 14.5 Forms of spousal violence . 226 Table 14.6 Spousal violence by background characteristics . 228 Table 14.7 Spousal violence by husband’s characteristics and empowerment indicators . 230 Table 14.8 Physical violence in the past 12 months by any husband . 231 Table 14.9 Experience of spousal violence by duration of marriage . 232 Table 14.10 Injuries to women due to spousal violence . 232 Table 14.11 Help seeking to stop violence . 233 Table 14.12 Sources for help to stop violence . 234 Figure 14.1 Forms of spousal violence . 227 APPENDIX A ADDITIONAL TABLES . 241 Table A2.1 Household drinking water . 241 Table A2.2 Household sanitation facilities . 242 Table A2.3 Household population by age, sex, and region . 243 Table A5.1 Current fertility . 244 Table A9.1 Number of antenatal care visits and timing of first visit . 244 APPENDIX B SAMPLE DESIGN AND IMPLEMENTATION . 245 Table B.1 Enumeration areas . 246 Table B.2 Sample allocation of clusters and households . 246 Table B.3 Sample implementation: Women . 247 Table B.4 Sample implementation: Men . 248 APPENDIX C ESTIMATES OF SAMPLING ERRORS . 251 Table C.1 List of selected variables for sampling errors, Pakistan 2012-13 . 253 Table C.2 Sampling errors for national sample, Pakistan 2012-13 . 254 Table C.3 Sampling errors for urban areas, Pakistan 2012-13 . 255 Table C.4 Sampling errors for rural areas, Pakistan 2012-13 . 256 Table C.5 Sampling errors for Punjab, Pakistan 2012-13 . 257 Table C.6 Sampling errors for Sindh, Pakistan 2012-13 . 258 Table C.7 Sampling errors for Khyber Pakhtunkhwa, Pakistan 2012-13 . 259 Table C.8 Sampling errors for Balochistan, Pakistan 2012-13 . 260 Table C.9 Sampling errors for ICT Islamabad, Pakistan 2012-13 . 261 Table C.10 Sampling errors for Gilgit Baltistan, Pakistan 2012-13 . 262 APPENDIX D DATA QUALITY TABLES . 263 Table D.1 Household age distribution . 263 Table D.2.1 Age distribution of eligible and interviewed women . 264 Table D.2.2 Age distribution of eligible and interviewed men . 264 Table D.3 Completeness of reporting . 265 Table D.4 Births by calendar years . 265 Table D.5 Reporting of age at death in days . 266 Table D.6 Reporting of age at death in months . 267 Foreword • xiii FOREWORD The 2012-13 Pakistan Demographic and Health Survey (PDHS) is the third survey conducted as part of the MEASURE DHS international series. The National Institute of Population Studies (NIPS), a leading research organization in the field of population and development, successfully completed the PDHS with technical support from ICF International and the Pakistan Bureau of Statistics (PBS) and financial support from the United States Agency for International Development (USAID). The overall objective of the 2012-13 PDHS was to collect high-quality data on fertility levels and preferences, contraceptive use, maternal and child health, infant mortality levels, immunization, nutritional status of mothers and children, and awareness regarding HIV/AIDS, tuberculosis, and other diseases and to investigate factors that have an impact on maternal and neonatal morbidity and mortality. The primary goal was to provide information needed by health and family planning programs for evidence-based planning and to offer guidelines to program managers and policymakers so that they can effectively plan and implement future interventions. The 2012-13 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. On behalf of NIPS and the Ministry of National Health Services, Regulations and Coordination (NHSRC), we thank USAID for its continuous trust, support, and financial assistance and the Pakistan Bureau of Statistics (PBS) and ICF International for their technical assistance and support. We would like to conclude by expressing gratitude to the Ministry of Planning and Development for extending the required support as executing agency for the 2012-13 PDHS. Imtiaz Inayat Elahi Abdul Basit Khan Secretary Executive Director Ministry of National Health Services, Regulations National Institute of Population Studies and Coordination Government of Pakistan Government of Pakistan Islamabad Acknowledgments • xv ACKNOWLEDGMENTS The 2012-13 Pakistan Demographic and Health Survey (PDHS), from its inception to its completion, has been a collaborative and consultative effort involving many stakeholders. The Ministry of Planning and Development was the executing agency. The National Institute of Population Studies (NIPS) implemented the PDHS project. The funding for the survey was provided by the United States Agency for International Development (USAID) through ICF International. The Pakistan Bureau of Statistics (PBS) provided assistance in the selection of sampling points and household listings. ICF International provided technical assistance and support for the project. The PDHS report was completed under surveillance of the Ministry of National Health Services, Regulations and Coordination (NHSRC). The role of all of these institutions is greatly acknowledged. The planning and implementation of the 2012-13 PDHS involved more than 30 national experts from the fields of population, development, and health, including the Technical Advisory Committee (TAC) members. Their professional input and valuable critique are gratefully acknowledged. The tough fieldwork, especially in the nonconducive environment resulting from the country’s law and order situation, would not have been completed without teamwork, spirit, quick decisionmaking, and vigilant monitoring on the part of the survey core team. We sincerely appreciate the great devotion and contributions of Mrs. Aysha Sheraz, Deputy Project Director; Mr. Zafar Zahir, Research Coordinator (Khyber Pakhtunkhwa and Gilgit Baltistan); Mr. Ali Anwar Buriro, Research Coordinator (Sindh and Balochistan); and Mrs. Rabia Zafar, Research Coordinator (Punjab). It is extremely gratifying that despite all of the challenges and ordeals, the NIPS monitoring teams traveled undauntedly even to the most remote areas of the country and did not compromise with respect to the quality of the data. We also acknowledge and thank the survey team members for collecting data under all circumstances and the quality control interviewers for efficient monitoring of the overall field activities. We commend the untiring efforts and dedication of Mr. Faateh ud din Ahmad, Deputy Principal Investigator for this project, who also supervised all of the data processing activities. Mr. Ahmad’s contributions were imperative at every stage of the project. We also express appreciation to his data processing team, including Mr. Shakeel Ahmad, Mr. Qamar Rasool, Mr. Farman Ali, and Mr. Takasar Amin. The contribution of the PDHS Office Coordinators, Mr. Sohail Rizwan and Mr. Hamid Ali, is duly acknowledged. The selfless and sincere support of Mr. Muhammad Arif and Mr. Muhammad Imran is much appreciated. We also thank the administrative staff of NIPS for their logistics support. We gratefully acknowledge and thank Mr. Muhammad Asad Khan Mengal, Secretary, Population Welfare Department, Balochistan, along with his field officers Mr. Tariq Masood, Mr. Khan Muhammad, Mr. Sartaj Aziz, and Mr. Sattar Shahwani, for their active support during the arduous and challenging field operations in Balochistan. We sincerely acknowledge the contributions of Syed Mazhar Hussain Hashmi, PDHS Advisor and Consultant for ICF International, in the form of technical assistance and guidance throughout the project period. We are indebted to Ms. Anjushree Pradhan, ICF International country manager for the PDHS, for providing immense technical support at all stages of the project. We extend our thanks to Dr. Ruilin Ren, sampling statistician, for his valuable input on sample design; Mr. Guillermo Rojas, data processing specialist, for his input on data processing and tabulation; and all of the technical experts of ICF International, who provided input on the finalization of this report. The support and cooperation extended by Ms. Kate Crawford, former Health Director, USAID/Pakistan; Mr. Jonathan Ross, Director, Health Office, USAID/Pakistan; and Mr. Khalid Mahmood, AID Project Management Assistant, USAID/Pakistan, are sincerely acknowledged. xvi • Acknowledgments We thank with gratitude Syed Khalid Ikhlaq Gilani, former Executive Director, NIPS, for providing sincere leadership, encouragement, and academic freedom for this project. We also acknowledge the efforts of Mr. Amanullah Bhatti, former Project Director, 2012-13 PDHS, for initiating and implementing activities at the early stage of the project. Special thanks go to Mr. Shahzad Ahmed Malik, Chief (PSP), Ministry of Planning and Development, for extending professional support at the take-off stage of the project. We extend our profound thanks to Mr. Abdul Basit Khan, Executive Director, NIPS, for his extensive support and guidance during the final stages of the project. Syed Mubashir Ali Tanvir Kiyani Principal Investigator Director, Research and Survey PDHS Project Director (PDHS) Technical Advisory Committee • xvii TECHNICAL ADVISORY COMMITTEE Mr. Abdul Basit Khan, Executive Director, National Institute of Population Studies Chairman Mr. Shahzad Ahmad Malik, Chief of Population, Planning, and Development Division Member Dr. Zeba A. Sathar, Country Director, Population Council Member Dr. Mohammad Nizamuddin, Vice Chancellor, University of Gujarat, Hafiz Hayat Campus Member Mr. Muzaffar Mahmood Qureshi, Resident Director, Green Star Social Marketing Member Dr. Mehtab S. Karim, Senior Advisor, South Asia and Affiliated Professor, School of Public Policy Member Dr. Muhammad Arshad Mehmood, Director, Monitoring and Evaluation, Population Council Member Dr. Tauseef Ahmad, Project Director, Path Finder Pakistan Member Dr. Naushin Mahmood, Freelance Consultant Member Dr. Abdul Razzaque Rukanuddin, Freelance Consultant Member Mr. Mehboob Sultan, Freelance Consultant Member Syed Mubashir Ali, Principal Investigator PDHS/Consultant ICF International Member Dr. Huma Qureshi, Director General, Health Services Academy Member Dr. Nabeela Ali, Chief of Party, Technical Assistance Unit (Health), USAID Member Dr. Sabiha H. Syed, Director, Migration Research Centre Member Syed Mazhar Hussain Hashmi, Survey Advisor PDHS/Consultant ICF International Member Dr. Durr-e-Nayab, Chief of Research, PIDE, Quaid-e-Azam University Campus, Islamabad Member Dr. Sajid Ahmad, CCM Coordinator, Global Fund Member Mr. Ayazuddin, Deputy Director General, Pakistan Bureau of Statistics Member Mr. Shaukat Zaman, Director, Pakistan Bureau of Statistics Member Prof. Dr. Ghazala Mahmood, Head of the Department of Gynecology, MCH Centre, PIMS Member Dr. Shafqat Javed Shaikh, Director General, Population Program Wing, Islamabad Member Dr. Ghulam Shabir, Technical Advisor, Maternal Newborn Child Health, (MNCH), UNFPA Member Ms. Kate Crawford, Representative, USAID Member Ms. Karen Allen, Deputy Representative, UNICEF Member Mr. Rabbi Royan, Country Representative, UNFPA Member Mr. Toshihiro Tanaka, Country Director, UNDP Member Dr. Guido Sabatinelli, Representative, WHO Member Dr. Saeed Shafqat, Professor and Founding Director, Centre for Public Policy and Governance, F. C. University, Lahore Member Ms. Anjushree Pradhan, ICF International Member Ms. Tanvir Kiyani, Director, Research and Survey/Project Director PDHS/NIPS Member/Secretary Contributors to the Report • xix CONTRIBUTORS TO THE REPORT Mr. Faateh ud din Ahmed, Data Processing Manager/Deputy Principal Investigator, PDHS/NIPS Syed Mubashir Ali, Principal Investigator, PDHS Ms. Azra Aziz, Senior Fellow, NIPS Mr. Rizwan Bashir, Chief Statistical Officer, PBS Mr. Ali Anwar Buriro, Associate Fellow/Research Coordinator PDHS/NIPS Dr. Mumtaz Eskar, Former Director General, Ministry of Population Welfare Syed Mazhar Hussain Hashmi, Survey Advisor, PDHS Dr. Zareef Uddin Khan, National Coordinator, WHO, MNCH Project Ms. Tanvir Kiyani, Director, Research and Survey/Project Director, PDHS/NIPS Dr. Arshad Mahmood, Director, Monitoring and Evaluations, JSI Research and Training Institute Dr. Nosheen Mehmood, Freelance Consultant Dr. Farid Midhet, Freelance Consultant Dr. Mohsin Saeed Khan, Freelance International Consultant Ms. Aysha Sheraz, Senior Fellow, Deputy Project Director, PDHS/NIPS Mr. Qamar-ul-Islam Siddiqui, Freelance Consultant/Ex-in-Charge, National AIDS Control Program Mr. Mahboob Sultan, Freelance Consultant Syeda Rabia Zafar, Associate Fellow/Research Coordinator, PDHS/NIPS Mr. Zafar Zahir, Associate Fellow/Research Coordinator, PDHS/NIPS Ms. Anjushree Pradhan, ICF International Abbreviations • xxi ABBREVIATIONS AIDS Acquired immune deficiency syndrome ANC Antenatal care ARI Acute respiratory infection ASFR Age-specific fertility rate BCG Bacille-Calmette-Guerin vaccine against tuberculosis BMI Body mass index CAFE Computer-assisted field editing CDC Centers for Disease Control and Prevention CNIC Computerized national identity card CPR Contraceptive prevalence rate DHS Demographic and Health Survey DPT Diphtheria, pertussis, and tetanus vaccine EB Enumeration block EPI Expanded Program on Immunization FALAH Family Advancement for Life and Health FATA Federally Administered Tribal Areas FPAP Family Planning Association of Pakistan GAR Gross attendance ratio GDP Gross domestic product GFR General fertility rate GPI Gender parity index HIV Human immunodeficiency virus HRCP Human Rights Commission of Pakistan ICPD International Conference on Population and Development ICT Islamabad capital territory IMCI Integrated management of childhood illness IMNCI Integrated management of newborn and childhood illness IRS Indoor residual spraying ITN Insecticide-treated net 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 bed net LPG Liquid petroleum gas xxii • Abbreviations MDGs Millennium Development Goals MMR Maternal mortality ratio MNCH Maternal, Newborn, and Child Health Program MOPW Ministry of Population Welfare MTCT Mother-to-child transmission NACP National AIDS Control Program NADRA National Database and Registration Authority NAR Net attendance ratio NCHS National Center for Health Statistics NGO Nongovernmental organization NHSRC Ministry of National Health Services, Regulations and Coordination NIPS National Institute of Population Studies NN Neonatal mortality OPV Oral polio vaccine ORS Oral rehydration salts ORT Oral rehydration therapy PAHO Pan American Health Organization PAIMAN Pakistan Initiative for Mothers and Newborns PBS Pakistan Bureau of Statistics PDHS Pakistan Demographic and Health Survey PFFPS Pakistan Fertility and Family Planning Survey PNN Postneonatal mortality PRHFPS Pakistan Reproductive Health and Family Planning Survey PSU Primary sampling unit RHSC Reproductive health service center SDM Standard days method SHS Secondhand smoke STI Sexually transmitted infection SWRHFPS Status of Women, Reproductive Health, and Family Planning Survey TAC Technical Advisory Committee TB Tuberculosis TFR Total fertility rate TWFR Total wanted fertility rate UN United Nations UNAIDS Joint United Nations Programme on HIV/AIDS UNDP United Nations Development Program UNICEF United Nations Children’s Fund USAID United States Agency for International Development VAD Vitamin A deficiency VIP Ventilated improved pit WHO World Health Organization Millennium Development Goal Indicators • xxiii MILLENNIUM DEVELOPMENT GOAL INDICATORS Millennium Development Goal Indicators Pakistan 2012-13 Indicator Sex Total Male Female 1. Eradicate extreme poverty and hunger 1.8 Prevalence of underweight children under 5 years of age 32.8 27.1 30.0 2. Achieve universal primary education 2.1 Net attendance ratio in primary education1 62.9 56.5 59.9 2.3 Literacy rate of 15- to 24-year-olds2 66.6a 49.4 58.0b 3. Promote gender equality and empower women 3.1 Ratio of girls to boys in primary, secondary, and tertiary education 3.1a Ratio of girls to boys in primary education3 na na 0.9 3.1b Ratio of girls to boys in secondary education3 na na 0.9 3.1c Ratio of girls to boys in tertiary education3 na na 0.8 4. Reduce child mortality 4.1 Under-five mortality rate4 98 96 89 4.2 Infant mortality rate4 82 79 74 4.3 Percentage of 1-year-old children immunized against measles 63.0 59.7 61.4 5. Improve maternal health 5.2 Percentage of births attended by skilled health personnel5 na na 52.1 5.3 Contraceptive prevalence rate6 na 35.4 na 5.4 Adolescent birth rate7 na 44 na 5.5 Antenatal care coverage 5.5a At least one visit8 na 73.1 na 5.5b Four or more visits9 na 36.6 na 5.6 Unmet need for family planning na 20.1 na 6. Combat HIV/AIDS, malaria, and other diseases 6.3 Percentage of the population age 15-24 years with comprehensive correct knowledge of HIV/AIDS10 5.2a 4.2 4.7b 6.8 Percentage of children under 5 with fever who are treated with appropriate antimalarial drugs11 3.0 3.8 3.4 Urban Rural Total 7. Ensure environmental sustainability 7.8 Percentage of population using an improved water source12 96.8 91.2 93.0 7.9 Percentage of population using an improved sanitation facility13 86.8 46.2 59.5 na = Not applicable 1 The ratio is based on reported attendance, not enrollment, in primary education among primary school age children (5- to 9-year-olds). The rate also includes children of primary school age enrolled in secondary education. This is a proxy for MDG indicator 2.1, net enrollment ratio. 2 Refers to respondents who attended secondary school or higher or who could read a whole sentence or part of a sentence 3 Based on reported net attendance, not gross enrollment, among 5- to 9-year-olds for primary, 10- to 14-year-olds for secondary, and 15- to 19-year-olds for tertiary education 4 Expressed in terms of deaths per 1,000 live births. Mortality by sex refers to a 10-year reference period preceding the survey. Mortality rates for males and females combined refer to the 5-year period preceding the survey. 5 Among births in the 5 years preceding the survey 6 Percentage of currently married women age 15-49 using any method of contraception 7 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 8 With a skilled provider 9 With any health care provider 10 Based on ever-married women and men age 15-24 for the 2012-13 PDHS. Comprehensive knowledge means knowing that consistent use of a condom during sexual intercourse and having just one uninfected faithful partner can reduce the chance of getting the AIDS virus, knowing that a healthy-looking person can have the AIDS virus, and rejecting the two most common local misconceptions about transmission or prevention of the AIDS virus. 11 Measured as the percentage of children age 0-59 months who were ill with a fever in the 2 weeks preceding the interview and received any antimalarial drug 12 Percentage of de jure population whose main source of drinking water is a household connection (piped), public tap or standpipe, tubewell or borehole, protected dug well, protected spring, rainwater collection, bottled water, or filtration plant 13 Percentage of de jure population whose household has a flush toilet, ventilated improved pit latrine, pit latrine with a slab, or composting toilet and does not share this facility with other households a Restricted to men in the subsample of households selected for the male interview b The total is calculated as the simple arithmetic mean of the percentages in the columns for males and females. xxiv • Map of Pakistan Introduction • 1 INTRODUCTION 1 he 2012-13 Pakistan Demographic and Health Survey (PDHS) is the third survey conducted so far in Pakistan under the umbrella of the global Demographic and Health Survey (DHS) program. The earlier two surveys were conducted in 1990-91 and 2006-07. The DHS surveys are designed to collect data about demographic and maternal and child health indicators with the purpose of providing reliable and updated information for policymakers and program managers. The 2012-13 PDHS specifically collected information about knowledge and practice of family planning, fertility levels, marriage, fertility preferences, child feeding practices, nutritional status of children and women, childhood mortality, maternal and child health, awareness and attitudes regarding HIV/AIDS, knowledge about other illnesses (e.g., tuberculosis, hepatitis B and C), and domestic violence. Information on the above-mentioned topics was mainly collected from ever-married women; however, some of the information was also collected from ever-married men. The collected information will provide a database for evaluation of relevant ongoing projects and can assist policymakers in developing appropriate strategies and plans for future projects. This chapter presents a brief description of Pakistan’s history, geography, economy, population growth (and its vital components), population density, urbanization status, and population welfare programs. In addition to these areas, it includes a detailed description of the organization and implementation of the 2012-13 PDHS. This discussion is deemed necessary to familiarize readers with the sociocultural, economic, and demographic features of the country. The chapter also highlights the methodology and important strategies utilized to ensure the reliability and quality of the data. It is important to note that the findings presented in this report are representative at the provincial/regional and subprovincial/subregional levels. Since the passage of the 18th Amendment to the Constitution of Pakistan, the official duties and responsibilities of the ministries related to sociodemographic programs have been devolved to provincial/regional administrative entities. Hence, the findings of the survey at the regional and subregional levels will provide a baseline status of various programs being run under the administrative set-up of the regional/provincial governments. 1.1 HISTORY AND PHYSICAL FEATURES OF PAKISTAN Pakistan gained its independence on 14 August 1947, after the subdivision of the Indian subcontinent then ruled by the British Empire. The foundation for its existence was laid much earlier, when the Muslims of India, as a minority on the Indian subcontinent, realized the need to form a political party that could represent and safeguard the interests of the Muslim population. The All-India Muslim League was formed in 1906 and, on 23 March 1940, it passed a resolution to establish a country named Pakistan for the Muslims of India. The area constituting Pakistan has at least a 4,000-year history dating from brick cities such as Mohen-jo-Daro and Harappa to the Hindu civilization and the Buddhists ruins contemporary to the birth of Christianity. Muslim leaders from central Asian countries and Afghanistan ruled the area from the 12th century to the 17th century, and their monuments, including mosques, gardens, forts, and tombs, are a common sight throughout Pakistan (National Institute of Population Studies [NIPS] and Macro International Inc., 2008). Pakistan is situated in the northwestern part of the south Asian subcontinent. Comprising a total land area of 796,096 square kilometers, it features a diversified terrain and topography. The Indus River flows through the country for about 2,500 kilometers starting from the Himalayas and the Karakoram mountain range in the north to the Arabian Sea in the south. The Hindu Kush is another majestic mountain range in the north. The three mountain ranges meet at a point, a unique geographical feature found only in T 2 • Introduction Pakistan. The country’s northern areas include five of the world’s 14 highest mountain peaks, each over 8,000 meters. Mount Godwin Austen (8,611 meters) and Nanga Parbat (8,126 meters) are the most famous of these peaks. Pakistan also has extensive glaciers, including the Siachen Glacier (more than 5,753 meters at its peak). Pakistan is located between 24° and 37° north latitude and between 61° and 75° east longitude. On its east and southeast lies India, to the north and northwest is Afghanistan, to the west is Iran, and to the south is the Arabian Sea. It has a common frontier with China on the border of its Gilgit region in the north. The old “silk route” connecting China to the Arabian Sea in south Pakistan is now a motorable asphalt road. The 4,733-meter Khunjerab Pass is the highest asphalt border crossing in the world. The road is open throughout the year despite its high altitude. Tajikistan, formerly a part of the USSR, is separated from Pakistan by a narrow strip of Afghan territory called the Wakhan. Administratively, Pakistan is composed of four provinces along with the Federally Administrative Tribal Areas (FATA) and the Gilgit Baltistan region. The sparsely populated province of Balochistan (with about 5 percent of the total population), in the southwestern part of the country, comprises 43 percent of the land area of Pakistan. Punjab is the largest province in terms of population, with about 56 percent of the country’s residents living there. The province of Sindh is the second largest, with about 23 percent of the population, and Khyber Pakhtunkhwa is the third largest, with about 17 percent. FATA accounts for just 0.5 percent of the population. Gilgit Baltistan (formerly known as the Northern Areas) comprises a total land area of 72,520 square kilometers, with a population of 883,799 (National Institute of Population Studies, 2009). In the northeast is Azad Kashmir, formerly part of Jammu and Kashmir and now physically under the control of Pakistan, with a land area of 11,639 square kilometers. Pakistan is an agricultural country, and about 64 percent of its population lives in rural areas. Agriculture is central to the country’s economic growth and development. As the dominant sector, it represents 21 percent of Pakistan’s gross domestic product (GDP) (Government of Pakistan, 2013). Although the economy of Pakistan has had many ups and downs, it has fared well overall and grown at an average rate of close to 6 percent per year till 2007-08. Recently, however, almost all sectors of the economy have performed below their capacity, mainly because of the energy crises and the worsening security and law and order situation in the country. Other factors that have affected the country’s growth during the last five years are devastating floods and rains. 1.2 POPULATION The population of Pakistan was 32.5 million in 1951, at which time it was the 14th most populous country in the world. Its population has since increased approximately 5.5-fold, reaching 184.5 million in 2012-13. Pakistan is now the sixth most populous country in the world (Government of Pakistan, 2013). The current population growth rate is 2 percent. According to estimates, Pakistan will become the fifth most populous country in 2050 at its current rate of population growth (Government of Pakistan, 2013). This scenario presents a picture that could be devastating for the country’s already-scarce national resources. At present, the population density in Pakistan is 231 persons per square kilometer (Table 1.1). Although birth and death rates have fallen in Pakistan over the past several decades, the decrease in the death rate is much more rapid than the decrease in the birth rate. Subsequently, life expectancy at birth has increased: from 63.4 years in 1981 to 66.5 years in 2013 for females and from 62.4 years in 1981 to 64.6 years in 2013, for males (Government of Pakistan, 2013). Introduction • 3 Efforts to reduce the population growth rate in Pakistan date as far back as 1953, when the Family Planning Association of Pakistan (FPAP), a nongovernmental organization, began providing family planning services to women. Realizing the need to stabilize population growth, the government of Pakistan joined forces with FPAP and offered assistance of Rs 0.5 million to the organization as part of the country’s first five-year plan (1955-1960). Realizing the effects of population growth on socioeconomic development, the government made the population control program an integral part of the second five-year plan (1960-1965). The population control program has remained an important policy issue since 1960. Nevertheless, because of changes in the government’s population policies every five to 10 years, the desired results have not been achieved. Another major shift in population planning was made in 2010 by devolving the population program to the provinces. 1.3 OBJECTIVES OF THE SURVEY The 2012-13 Pakistan Demographic and Health Survey was undertaken to provide current and reliable data on fertility and family planning, childhood mortality, maternal and child health, women’s and children’s nutritional status, women’s empowerment, domestic violence, and knowledge of HIV/AIDS. The survey was designed with the broad objective of providing policymakers with information to monitor and evaluate programmatic interventions based on empirical evidence. The specific objectives of the survey are to: • collect high-quality data on topics such as fertility levels and preferences, contraceptive use, maternal and child health, infant (and especially neonatal) mortality levels, awareness regarding HIV/AIDS, and other indicators related to the Millennium Development Goals and the country’s Poverty Reduction Strategy Paper • investigate factors that affect maternal and neonatal morbidity and mortality (i.e., antenatal, delivery, and postnatal care) • provide information to address the evaluation needs of health and family planning programs for evidence-based planning • provide guidelines to program managers and policymakers that will allow them to effectively plan and implement future interventions 1.4 ORGANIZATION OF THE SURVEY The National Institute of Population Studies undertook the responsibility of implementing the 2012-13 PDHS project, and the project was executed by the Pakistan Planning and Development Division (Islamabad). The Technical Advisory Committee, consisting of 30 national experts, professionals, researchers, and representatives from the provinces, provided input in the different stages of the project. NIPS was responsible for planning, organizing, and overseeing the survey operations, including hosting technical meetings; recruiting, training, and supervising fieldworkers and data processing staff; and writing this report. The Pakistan Bureau of Statistics (PBS) provided the sample design and household listings for the sampled areas across the country. The funding for the survey was provided by the United States Table 1.1 Basic demographic indicators Demographic indicators from selected sources for Pakistan, 1981- 2013 Indicators Census 1981 Census 1998 PES 2012-13 Population (millions) 84.2 132.3 184.5 Intercensal growth rate (percentage) 3.10 2.69 2.00 Density (population/km2) 106 166 231 Percentage urban 28.3 32.5 37.9 Life expectancy (years) Male 62.4 62.5 64.6 Female 63.4 63.0 66.5 Source: Population Census Organization, Islamabad, Government of Pakistan; The Pakistan Development Review 37.4/II (winter 1998), pp 37:4,481-493; National Institute of Population Studies NIPS, Planning and Development Division, Government of Pakistan (2013) 4 • Introduction Agency for International Development (USAID), while technical and logistical support was provided by ICF International through its MEASURE DHS project. 1.5 SURVEY IMPLEMENTATION 1.5.1 Sample Design The primary objective of the 2012-13 PDHS is to provide reliable estimates of key fertility, family planning, maternal, and child health indicators at the national, provincial, and urban and rural levels. NIPS coordinated the design and selection of the sample with the Pakistan Bureau of Statistics. The sample for the 2012-13 PDHS represents the population of Pakistan excluding Azad Jammu and Kashmir, FATA, and restricted military and protected areas. The universe consists of all urban and rural areas of the four provinces of Pakistan and Gilgit Baltistan, defined as such in the 1998 Population Census. PBS developed the urban area frame. All urban cities and towns are divided into mutually exclusive, small areas, known as enumeration blocks, that were identifiable with maps. Each enumeration block consists of about 200 to 250 households on average, and blocks are further grouped into low-, middle-, and high-income categories. The urban area sampling frame consists of 26,543 enumeration blocks, updated through the economic census conducted in 2003. In rural areas, lists of villages/mouzas/dehs developed through the 1998 population census were used as the sample frame. In this frame, each village/mouza/deh is identifiable by its name. In Balochistan, Islamabad, and Gilgit Baltistan, urban areas were oversampled and proportions were adjusted by applying sampling weights during the analysis. A sample size of 14,000 households was estimated to provide reasonable precision for the survey indicators. NIPS trained 43 PBS staff members to obtain fresh listings from 248 urban and 252 rural survey sample areas across the country. The household listing was carried out from August to December 2012. The second stage of sampling involved selecting households. At each sampling point, 28 households were selected by applying a systematic sampling technique with a random start. This resulted in 14,000 households being selected (6,944 in urban areas and 7,056 in rural areas). The survey was carried out in a total of 498 areas. Two areas of Balochistan province (Punjgur and Dera Bugti) were dropped because of their deteriorating law and order situations. Overall, 24 areas (mostly in Balochistan) were replaced, mainly because of their adverse law and order situation (for further details on sample size and design, see Appendix B). 1.5.2 Questionnaires The 2012-13 PDHS used four types of questionnaires: Household Questionnaire, Woman’s Questionnaire, Man’s Questionnaire, and Community Questionnaire. The contents of the Household, Woman’s, and Man’s Questionnaires were based on model questionnaires developed by the MEASURE DHS program. However, the questionnaires were modified, in consultation with a broad spectrum of research institutions, government departments, and local and international organizations, to reflect issues relevant to the Pakistani population, including migration status, family planning, domestic violence, HIV/AIDS, and maternal and child health. A series of questionnaire design meetings were organized by NIPS, and discussions from these meetings were used to finalize the survey questionnaires. The questionnaires were then translated into Urdu and Sindhi and pretested, after which they were further refined. The questionnaires were presented to the Technical Advisory Committee for final approval. The Household Questionnaire was used to list the usual members and visitors in the selected households. Basic information was collected on the characteristics of each person listed, including age, sex, marital status, education, and relationship to the head of the household. Data on current school attendance, migration status, and survivorship of parents among those under age 18 were also collected. The questionnaire also provided the opportunity to identify ever-married women and men age 15-49 who were eligible for individual interviews and children age 0-5 eligible for anthropometry measurements. The Introduction • 5 Household Questionnaire collected information on characteristics of the dwelling unit as well, such as the source of drinking water; type of toilet facilities; type of cooking fuel; materials used for the floor, roof, and walls of the house; and ownership of durable goods, agricultural land, livestock/farm animals/poultry, and mosquito nets. The Woman’s Questionnaire was used to collect information from ever-married women age 15-49 on the following topics: • Background characteristics (education, literacy, native tongue, marital status, etc.) • Reproductive history • Knowledge and use of family planning methods • Fertility preferences • Antenatal, delivery, and postnatal care • Breastfeeding and infant feeding practices • Vaccinations and childhood illnesses • Woman’s work and husband’s background characteristics • Infant and childhood mortality • Women’s decision making • Awareness about AIDS and other sexually transmitted infections • Other health issues (e.g., knowledge of tuberculosis and hepatitis, injection safety) • Domestic violence Similarly, the Man’s Questionnaire, used to collect information from ever-married men age 15-49, covered the following topics: • Background characteristics • Knowledge and use of family planning methods • Fertility preferences • Employment and gender roles • Awareness about AIDS and other sexually transmitted infections • Other health issues The Community Questionnaire, a brief form completed for each rural sample point, included questions about the availability of various types of health facilities and other services, particularly transportation, education, and communication facilities. All elements of the PDHS data collection activities were pretested in June 2012. Three teams were formed for the pretest, each consisting of a supervisor, a male interviewer, and three female interviewers. One team worked in the Sukkur and Khairpur districts in the province of Sindh, another in the Peshawar and Charsadda districts in Khyber Pakhtunkhwa, and the third in the district of Rawalpindi in Punjab. Each team covered one rural and one urban non-sample area. Data collection started on 20 June 2012 and required approximately one week to complete. A three-day debriefing session was held at NIPS. Lessons learned from the pretest were used to finalize the survey instruments. 1.5.3 Training NIPS staff responsible for the survey made considerable efforts to recruit people with the requisite skills to work as field staff. Advertisements were placed in national and local newspapers across the country, and, after screening the applicants, NIPS staff visited various provincial headquarters and large cities to administer tests and interviews before selecting the final candidates. Almost all of those recruited were university graduates; three-quarters had a master’s degree. A few had been involved in work for the 2006-07 PDHS. They came from 57 districts of Pakistan, including Gilgit Baltistan. NIPS organized a 6 • Introduction three weeks long training course (during September and October 2012) in Islamabad for the 144 participants. The training was conducted following the standard DHS procedures, which included class presentations, daily reviews, mock interviews, class exercises, and a written test at the end of the training. A few individuals who were unable to pass the test were excluded. The trainers consisted mainly of ICF International and NIPS staff. For the first time, the PDHS used the computer-assisted field editing (CAFE) system in the survey; specialized training was carried out for the participants selected to be field editors. Toward the end of the training, three days were set aside for field practice in Islamabad and Rawalpindi. Each day after the field practice, the completed questionnaires were reviewed by senior staff, and the problems identified were discussed in the morning plenary sessions. These questionnaires were also entered in the CAFE system to allow practice among the field editors. 1.5.4 Fieldwork A total of 20 teams were organized to collect data; each consisted of a supervisor, a field editor, one male interviewer, and three female interviewers. The teams were initially deployed around Islamabad and Rawalpindi to enable intense supervision and technical backstopping at an early stage. All of the teams completed one field cluster and electronically transferred the data to the central office. Each day, a review session was organized to share the experiences of the teams. The trainers provided necessary feedback on all aspects of the fieldwork, including field management and rapport building with respondents. The fieldwork was carried out from October 2012 to March 2013, with the exception of one team in Balochistan that completed its fieldwork in the third week of April. 1.5.5 Field Supervision and Monitoring Data quality was ensured through the inclusion of different levels of supervisory staff who monitored the fieldwork. In addition to the team supervisors, four quality control teams (each comprising one male member and two female members) were deployed to monitor fieldwork. Each quality control team visited field teams for two to three days and was responsible for observing interviews, reviewing the completed questionnaires to ensure that information was recorded correctly, verifying information by revisiting and reinterviewing respondents, observing height and weight measurements, and completing assignment sheets. The quality control teams were in the field from the beginning of the fieldwork to the end of the survey. Each team was provided with a separate vehicle to allow quick mobility. After each visit, the reports submitted by quality control teams to NIPS were examined, and feedback to the field teams was conveyed when necessary. NIPS also designated three professionals from its research staff to act as field coordinators. They visited the teams assigned to them frequently to check on household selection procedures, the interviewer assignment process, questionnaire editing, team coordination, and time management. These field coordinators, usually accompanied by the quality control interviewers, observed interviews, conducted reinterviews, edited completed questionnaires, reviewed any errors with team members, and provided on- the-job training to weaker field staff. In addition, monitoring was undertaken by NIPS senior staff, the survey advisor, and the principal investigator to check the quality of the data and other field procedures. Any deviations from set procedures by any member of the field team were pointed out and immediately rectified. Independent monitoring was also undertaken by the staff of USAID and ICF International. In view of the adverse law and order situation, particularly in Balochistan, help in field monitoring was also sought from community-based organizations and provincial population welfare departments. Data quality was monitored as well through the field check tables generated concurrently with data processing activities. Immediate feedback (by phone and through visiting and sharing with interviewers) was given. The interviewers were also cautioned not to repeat mistakes. Introduction • 7 1.5.6 Field Problems and Challenges A number of challenges were faced by the field teams, especially in Balochistan, Khyber Pakhtunkhwa, Gilgit Baltistan, and Karachi (Sindh). For example, team members received text messages on their cell phones of dire consequences and death threats if they continued collecting data. This scenario was especially true in Balochistan because of the prevailing law and order situation and security problems. Consultative meetings with security and civil agencies, the Population Welfare Department, and the Balochistan government were arranged, and on-the-spot strategies were adopted. Moreover, the survey teams were reshuffled, and one team was eliminated and replaced by a team with new members. These new team members were trained afresh in Islamabad. Although the field problems and challenges encountered resulted in delays in data collection, the quality of the data was not compromised. In parts of Khyber Pakhtunkhwa and Gilgit Baltistan, the teams faced mobility problems due to heavy snow and tough terrain. Consequently, the fieldwork in these areas was prolonged, but the data collection was completed. In Karachi, the teams faced resistance from the local community, which hampered field activities and thus affected the data collection schedule. In view of the adverse security situation in some parts of the provinces, different field strategies were adopted so that the teams were not as easily noticed when they were in the field. For example, instead of working consecutively for three days in a cluster, the teams were advised to start data collection in three clusters simultaneously in such a way that they worked on rotation. In some areas, instead of a 12-seater van, small taxis were used so that the presence of the team did not become obvious. Data collection was not possible in Punjgur district and Dera Bugti in Balochistan because of the serious law and order situation. In two of the four partially completed clusters (one in the Tank district of Khyber Pakhtunkhwa and the other in the Mastung district of Balochistan), the teams faced threats of dire consequences and had to stop their fieldwork. Other factors such as seasonal migration and closure of access roads due to heavy snowfall also hampered work in some areas. 1.5.7 Data Processing The processing of the 2012-13 PDHS data began simultaneously with the fieldwork. Completed questionnaires were edited and data entry was carried out immediately in the field by the field editors. The data were uploaded on the same day to enable retrieval in the central office at NIPS in Islamabad, and the Internet File Streaming System was used to transfer data from the field to the central office. The completed questionnaires were then returned periodically from the field to the NIPS office in Islamabad through a courier service, where the data were again edited and entered by data processing personnel specially trained for this task. Thus, all data were entered twice for 100 percent verification. Data were entered using the CSPro computer package. The concurrent processing of the data offered a distinct advantage because of the assurance that the data were error-free and authentic. Moreover, the double entry of data enabled easy identification of errors and inconsistencies, which were resolved via comparisons with the paper questionnaire entries. The secondary editing of the data was completed in the first week of May 2013. As noted, the PDHS used the CAFE system in the field for the first time. This application was developed and fully tested before teams were deployed in the field. Field editors were selected after careful screening from among the participants who attended the main training exercise. Seven-day training was arranged for field editors so that each editor could enter a sample cluster’s data under the supervision of NIPS senior staff, which enabled a better understanding of the CAFE system. The system was deemed efficient in capturing data immediately in the field and providing immediate feedback to the field teams. Early transfer of data back to the central office enabled the generation of field check tables on a regular basis, an efficient tool for monitoring the fieldwork. 8 • Introduction 1.6 RESPONSE RATES Table 1.2 shows the response rates for the 2012-13 PDHS. A total of 13,944 households were selected for the sample, of which 13,464 were found to be occupied at the time of the fieldwork. The shortfall is largely due to household members being absent. Of the occupied households, 12,943 were successfully interviewed, yielding a household response rate of 96 percent. In view of the adverse law and order situation in the country, this response rate is highly encouraging and appears to be the result of a well-coordinated team effort. Table 1.2 Results of the household and individual interviews Number of households, number of interviews, and response rates, according to residence (unweighted), Pakistan 2012-13 Result Residence Total Urban Rural Household interviews Households selected 6,944 7,000 13,944 Households occupied 6,685 6,779 13,464 Households interviewed 6,335 6,608 12,943 Household response rate1 94.8 97.5 96.1 Interviews with ever-married women age 15-49 Number of eligible women 6,964 7,605 14,569 Number of eligible women interviewed 6,351 7,207 13,558 Eligible women response rate2 91.2 94.8 93.1 Interviews with ever-married men age 15-49 Number of eligible men 2,007 1,984 3,991 Number of eligible men interviewed 1,521 1,613 3,134 Eligible men response rate2 75.8 81.3 78.5 1 Households interviewed/households occupied 2 Respondents interviewed/eligible respondents A total of 14,569 ever-married women age 15-49 were identified in the 12,943 households interviewed (an average of 1.13 women per household). Of the eligible women, 13,558 were successfully interviewed, yielding a response rate of 93 percent. The principal reason for non-response among eligible women was the failure to find individuals at home despite repeated visits to the household. Response rates were lower in urban areas than in rural areas. A sample of 3,991 men was identified as eligible to be interviewed. Of these men, 3,134 were successfully interviewed, yielding a response rate of 79 percent. As expected, the response rate for men was lower in urban areas than in rural areas, mainly because men in urban areas are often away from their households for work. In many instances, the interviewers could not contact them even after several visits in the late evenings and, in some cases, efforts to interview them at their place of work. Housing Characteristics and Household Population • 9 HOUSING CHARACTERISTICS AND HOUSEHOLD POPULATION 2 his chapter provides an overview of the socioeconomic characteristics of the household population, including household conditions, sources of drinking water, sanitation facilities, hand washing, availability of electricity, housing facilities, possession of durable goods, and means of transport. Information on household assets is used to create a wealth index as an indicator of household economic status. This chapter also describes the demographic characteristics of the household population, including population composition, age, sex, educational attainment, school dropout (and reasons for dropout), rates of school attendance, birth registration of children under age 5, and migration status. A household was defined as a person or group of related and unrelated persons who usually live together in the same dwelling unit(s), who have common cooking and eating arrangements, and who acknowledge one adult member as the head of the household. A member of the household is any person who usually lives in the household. Information is collected from all usual residents of a selected household (de jure population) as well as persons who stayed in the selected household the night before the interview (de facto population). The difference between these two populations is very small, and all tables in this report refer to the de facto population, unless otherwise specified, to maintain comparability with other PDHS reports. The information in this chapter is intended to facilitate interpretation of the key demographic, socioeconomic, and health indices presented later in the report. It is also intended to assist in the assessment of the representativeness of the survey sample. 2.1 HOUSEHOLD CHARACTERISTICS Household characteristics include access to basic utilities and sources of drinking water, time needed to obtain drinking water, and water treatment practices as well as type of and access to sanitation facilities and housing structure. The crowding of dwelling spaces and type of fuel used for cooking are physical characteristics of a household used to assess the general well-being and socioeconomic status of T Key Findings • Access to an improved source of drinking water is 93 percent in Pakistan, but only 8 percent of households use an appropriate water treatment method. • Fifty-nine percent of households have an improved toilet facility not shared with other households. • Ninety-four percent of households have electricity. • Sixty-two percent of households use solid fuel for cooking, and 39 percent are exposed daily to secondhand smoke. • Overall, 87 percent of households possess mobile phones (95 percent of households in urban areas and 83 percent in rural areas). • Thirty-four percent of children under age 5 are registered, and 32 percent have a birth certificate; 83 percent of adults age 18 and over are registered with a national identity card number. • Fifty-three percent of women have no education, as compared with 34 percent of men. • Net attendance ratios are 60 percent at the primary level and 37 percent at the secondary level. 10 • Housing Characteristics and Household Population its members. This section provides information from the 2012-13 PDHS on drinking water, sanitation facilities, housing characteristics, and possession of basic amenities. 2.1.1 Water and Sanitation Access to safe water and sanitation are basic determinants of better health. Lack of access to safe drinking water and sanitation facilities and poor hygiene are associated with skin diseases, acute respiratory infections (ARIs), and diarrheal diseases. ARIs and diarrheal diseases remain the leading causes of childhood deaths in Pakistan that are preventable with primary health care measures (NIPS and Macro International, 2008). Table 2.1 presents the percent distribution of households and the de jure population by area of residence and source of drinking water, time needed to obtain drinking water, and whether drinking water was treated. In this survey, sources that are likely to provide water suitable for drinking are identified as improved sources. These include a piped source within the dwelling, yard, or plot; a public tap/standpipe; borehole; a protected well; spring water; and rainwater (WHO and UNICEF Joint Monitoring Program for Water Supply and Sanitation, 2010). Access to an improved source of drinking water is nearly universal in Pakistan (93 percent). The most common source of drinking water in urban areas is water piped into a dwelling, yard, or plot (50 percent), followed by a tube well or borehole/hand pump (23 percent), a public tap or standpipe (9 percent), a filtration plant (8 percent), and bottled water (6 percent). In contrast, a tube well or borehole is the main source of drinking water in rural areas (62 percent), followed by water piped into a dwelling or yard (20 percent), a public tap or standpipe (5 percent), and a protected well (3 percent). For 77 percent of households, the source of drinking water is on the premises. Fifteen percent of households spend less than 30 minutes round trip to obtain water. As expected, it takes longer to obtain drinking water in rural areas than in urban areas. Table 2.1 Household drinking water Percent distribution of households and de jure population by source of drinking water, time to obtain drinking water, and treatment of drinking water, according to residence, Pakistan 2012-13 Characteristic Households Population Urban Rural Total Urban Rural Total Source of drinking water Improved source 97.1 91.5 93.4 96.8 91.2 93.0 Piped into dwelling/yard/plot 50.4 19.5 30.0 49.6 18.6 28.8 Public tap/standpipe 9.2 5.3 6.6 9.4 5.3 6.7 Tube well or borehole/hand pump 23.0 61.5 48.5 23.7 61.7 49.3 Protected well 0.8 2.6 2.0 0.9 2.7 2.1 Protected spring/rain water 0.1 1.3 0.9 0.1 1.4 1.0 Bottled water 5.5 0.2 2.0 5.1 0.3 1.8 Filtration plant 8.1 1.1 3.5 7.9 1.2 3.4 Non-improved source 2.4 7.7 5.9 2.8 8.2 6.4 Unprotected well 0.3 2.0 1.4 0.3 1.9 1.4 Unprotected spring 0.0 2.8 1.8 0.0 3.1 2.1 Tanker truck/cart with drum 1.6 1.5 1.6 1.9 1.7 1.7 Surface water 0.4 1.4 1.1 0.5 1.6 1.2 Other source 0.4 0.8 0.6 0.3 0.6 0.5 Total 100.0 100.0 100.0 100.0 100.0 100.0 Time to obtain drinking water (round trip) Water on premises 77.6 75.9 76.5 78.0 75.7 76.5 Less than 30 minutes 16.7 13.6 14.6 16.2 13.4 14.3 30 minutes or longer 5.2 10.1 8.4 5.2 10.5 8.8 Don’t know/missing 0.6 0.4 0.4 0.5 0.4 0.4 Total 100.0 100.0 100.0 100.0 100.0 100.0 Water treatment prior to drinking1 Boiled 18.5 1.2 7.1 17.0 1.2 6.4 Bleach/chlorine added 0.5 0.1 0.3 0.5 0.1 0.2 Strained through cloth 4.5 1.4 2.5 4.6 1.5 2.5 Ceramic, sand, or other filter 2.0 0.1 0.7 2.0 0.1 0.7 Solar disinfection 0.0 0.1 0.1 0.0 0.1 0.1 Other 0.2 0.5 0.4 0.2 0.6 0.5 No treatment 76.9 96.6 89.9 78.4 96.6 90.6 Percentage using an appropriate treatment method2 20.6 1.5 8.0 19.2 1.3 7.2 Number 4,383 8,560 12,943 28,773 58,944 87,717 1 Respondents may report multiple treatment methods so the sum of treatment may exceed 100 percent. 2 Appropriate water treatment methods include boiling, bleaching, filtering, and solar disinfecting. Housing Characteristics and Household Population • 11 The majority of households (90 percent) do not treat their drinking water, and only 8 percent of households use an appropriate water treatment method. Rural households are much less likely than urban households to treat their water appropriately (2 percent and 21 percent, respectively). Overall, boiling water prior to drinking is the most common treatment method (7 percent). One percent of rural households boil water, while almost 19 percent of urban households do so. Households’ sanitation facilities are important in preventing risks of diseases such as diarrhea, dysentery, and typhoid. At the household level, adequate sanitation facilities include an improved toilet and disposal that separates waste from human contact. A household is classified as having an improved toilet if it is used only by household members (is not shared with another household) and if it separates waste from human contact (WHO and UNICEF, 2010). Table 2.2 shows the percent distribution of households by type of toilet/latrine facilities and area of residence. A total of 59 percent of households have an improved, not shared toilet facility, and 11 percent use a shared facility. Urban households are more likely than rural households to use a toilet facility that is not shared (86 percent and 45 percent, respectively). About 30 percent of households use a non-improved toilet facility. Of these households, 6 percent use a flush toilet that is not drained to a sewer or septic tank/pit latrine, and 2 percent use pit latrines without slabs or have open pits. Twenty-one percent of households have no toilet facility, an improvement from 2006-07, when 30 percent of households reported having no toilet facility (NIPS and Macro International, 2008). Rural households are more likely than urban households to have no toilet facility (32 percent and less than 1 percent, respectively). Table 2.2 Household sanitation facilities Percent distribution of households and de jure population by type of toilet/latrine facilities, according to residence, Pakistan 2012-13 Type of toilet/latrine facility Households Population Urban Rural Total Urban Rural Total Improved, not shared facility 86.1 44.6 58.7 86.8 46.2 59.5 Flush/pour flush to piped sewer system 64.4 7.1 26.5 63.9 7.3 25.8 Flush/pour flush to septic tank 13.6 18.1 16.6 13.7 17.8 16.4 Flush/pour flush to pit latrine 6.7 16.2 13.0 7.4 17.4 14.1 Ventilated improved pit (VIP) latrine 0.4 0.7 0.6 0.6 0.9 0.8 Pit latrine with slab 1.0 2.5 2.0 1.1 2.9 2.3 Shared facility1 8.4 12.2 10.9 7.6 10.5 9.6 Flush/pour flush to piped sewer system 5.2 2.0 3.1 4.8 1.8 2.8 Flush/pour flush to septic tank 1.9 5.1 4.0 1.6 4.2 3.4 Flush/pour flush to pit latrine 1.1 4.2 3.2 1.0 3.8 2.9 Ventilated improved pit (VIP) latrine 0.1 0.3 0.2 0.1 0.3 0.2 Pit latrine with slab 0.1 0.5 0.4 0.1 0.4 0.3 Non-improved facility 5.5 43.2 30.4 5.6 43.3 30.9 Flush/pour flush not to sewer/septic tank/pit latrine 4.0 6.9 5.9 4.0 6.7 5.8 Pit latrine without slab/open pit 0.6 3.2 2.3 0.8 3.7 2.7 Bucket 0.0 0.6 0.4 0.0 0.7 0.5 Hanging toilet/hanging latrine 0.0 0.3 0.2 0.0 0.3 0.2 No facility/bush/field 0.6 31.7 21.2 0.6 31.5 21.4 Other 0.0 0.3 0.2 0.0 0.2 0.2 Missing 0.2 0.2 0.2 0.2 0.2 0.2 Total 100.0 100.0 100.0 100.0 100.0 100.0 Number 4,383 8,560 12,943 28,773 58,944 87,717 1 Facilities that would be considered improved if they were not shared by two or more households Data on provincial differentials in household drinking water and household sanitation facilities are shown in Appendix Tables A2.1 and A2.2. 12 • Housing Characteristics and Household Population 2.1.2 Housing Characteristics Housing characteristics and assets can be used as a measure of the socioeconomic status of household members. Also, cooking practices and cooking fuels affect the health of family members and the quality of their environment. For example, use of biomass fuels exposes household members to indoor pollution, which has a direct bearing on their health and surroundings. Table 2.3 provides information on house- hold characteristics such as availability of electric- ity, type of flooring material, number of rooms used for sleeping, place for cooking, type of fuel used for cooking, and frequency of smoking in the house. Overall, 94 percent of households in Pakistan have access to electricity, compared with 89 percent in the 2006-07 PDHS. Mud and sand are the most common flooring materials used in Pakistan (42 percent), followed by cement (34 percent), bricks (9 percent), and chips or terrazzo (7 percent). Mud and sand materials are predominantly used in rural areas (59 percent), while in urban areas the most common flooring material is cement (52 percent). The number of rooms used for sleeping in- dicates the extent of crowding in households. Overcrowding increases the risk of contracting infectious diseases, which particularly affect children and older household members. Thirty-nine percent of households have either one or two rooms for sleeping, while 21 percent have three or more rooms. There is substantial variation in the number of households with one room used for sleeping by urban and rural residence (33 percent and 42 percent, respectively). Forty-one percent of households in urban areas and 38 percent in rural areas use two rooms for sleeping. Indoor air pollution has important implica- tions for the health of household members. The type of fuel used for cooking, the place where cooking is done, and the type of stove used are all related to indoor air quality and the degree to which house- hold members are exposed to the risk of respiratory infections and other diseases. In Pakistan, the risk of indoor air pollution from cooking fuel is large given that 94 percent of households cook in the house, whereas only 6 percent cook in a separate building. Urban households are more likely than rural households to cook in the house (95 percent and 93 percent, respectively). Table 2.3 Household characteristics Percent distribution of households by housing characteristics, percentage using solid fuel for cooking, and percent distribution by frequency of smoking in the home, according to residence, Pakistan 2012-13 Housing characteristic Residence Total Urban Rural Electricity Yes 99.8 90.5 93.6 No 0.2 9.5 6.4 Total 100.0 100.0 100.0 Flooring material Mud, sand 7.0 59.3 41.6 Dung 0.2 2.6 1.8 Ceramic tiles 2.6 0.4 1.1 Cement 51.5 24.3 33.5 Carpet 2.9 0.3 1.2 Chips/terrazzo 14.8 2.2 6.5 Bricks 8.8 8.9 8.9 Marble 11.1 1.5 4.7 Other 1.1 0.4 0.6 Total 100.0 100.0 100.0 Rooms used for sleeping One 33.1 42.4 39.3 Two 41.0 37.9 38.9 Three or more 25.2 19.3 21.3 Missing 0.7 0.4 0.5 Total 100.0 100.0 100.0 Place for cooking In the house 95.4 92.8 93.7 In a separate building 4.1 6.4 5.6 Outdoors 0.2 0.4 0.3 No food cooked in household 0.3 0.3 0.3 Total 100.0 100.0 100.0 Cooking fuel LPG/natural gas/biogas 86.3 12.7 37.6 Coal/lignite 0.0 0.1 0.0 Charcoal 0.7 2.9 2.1 Wood 11.1 66.0 47.4 Straw/shrubs/grass 0.4 6.5 4.5 Animal dung 1.2 11.5 8.0 Other 0.1 0.0 0.1 No food cooked in household 0.3 0.3 0.3 Total 100.0 100.0 100.0 Percentage using solid fuel for cooking1 13.4 87.0 62.1 Frequency of smoking in the home Daily 31.9 42.9 39.1 Weekly 1.8 1.5 1.6 Monthly 0.4 0.2 0.3 Less than monthly 0.9 0.6 0.7 Never 65.1 54.8 58.3 Total 100.0 100.0 100.0 Number 4,383 8,560 12,943 LPG = Liquid petroleum gas 1 Includes coal/lignite, charcoal, wood/straw/shrubs/grass, and animal dung Housing Characteristics and Household Population • 13 Overall, more than half of households (62 percent) use solid fuel for cooking. There are substantial urban-rural differences in the use of solid fuel, however. In urban areas, only 13 percent of households use solid fuel for cooking, while the majority of rural households (87 percent) use solid fuel, including coal or lignite, charcoal, wood, straw, shrubs, grass, and animal dung that generate smoke that is unhealthy to breathe. The percentages of urban and rural households relying on wood for fuel decreased from 19 percent and 68 percent, respectively, in 2006-07 to 11 percent and 66 percent in 2012-13. As expected, use of liquid petroleum gas (LPG), natural gas, and biogas is limited to urban areas (86 percent). Reducing the proportion of the population that relies on solid fuels is one of the Millennium Development Goals (MDGs). The 2012-13 PDHS shows that Pakistan is slowly making progress toward this goal, with the proportion of the population using solid fuels decreasing from 67 percent in 2006-07 to 62 percent in 2012-13. Information on smoking was collected in the 2012-13 PDHS to assess the percentage of household members who are exposed to second-hand smoke (SHS), which is a risk factor for those who do not smoke. Pregnant women who are exposed to SHS have a higher risk of delivering a low birth weight baby (Windham et al., 1999). Also, children who are exposed to SHS are at a higher risk of respiratory and ear infections and poor lung development (U.S. Department of Health and Human Services, 2006). Table 2.3 provides information on the frequency of smoking in the home, which is used as a proxy for level of SHS exposure. Overall, 39 percent of households are exposed daily to SHS; rural households are more likely than urban households to be exposed daily to SHS (43 percent and 32 percent, respectively). 2.1.3 Household Possessions Possession of durable consumer goods is another useful indicator of household socioeconomic status. The possession and use of household durable goods have multiple effects and implications. For instance, access to a radio or television exposes household members to updated daily events, information, and educational materials. Similarly, a refrigerator prolongs food storage and keeps food fresh and hygienic. Ownership of transportation allows greater access to services away from the local area and enhances social and economic activities. Table 2.4 presents the percentages of urban and rural households that possess various durable commodities, means of transportation, and agricultural land and farm animals. The table shows that televisions and mobile telephones are common devices possessed by most households for information and communication. Possession of mobile and non-mobile phones increased from 46 percent in 2006-07 to 96 percent in 2012-13. Approximately 95 percent of households in urban areas and 83 percent of households in rural areas possess mobile phones. Six of 10 households have a television. Urban households are more likely to have a television (87 percent) than rural households (47 percent). Possession of a radio decreased from 32 percent in 2006-07 to 11 percent in 2012-13, while ownership of a television increased from 56 percent to 60 percent. Another indicator of household socioeconomic status is ownership of a computer and availability of an Internet connection. Thirteen percent of households in Pakistan own a computer, and 7 percent have access to an Internet connection. There are notable urban- rural variations in the proportions of households owning computers and having access to an Internet connection. For example, 29 percent of urban households and 5 percent of rural households own a computer. Similarly, 17 percent of urban households have access to an Internet connection, as compared with only 1 percent of rural households. 14 • Housing Characteristics and Household Population A refrigerator is available in 44 percent of households (70 percent of urban households and 30 percent of rural households). About one in two households possess an almirah/cabinet and a chair. About 11 percent of households possess a room cooler, with a higher percentage in urban areas than rural areas (19 percent and 7 percent, respectively). Seven percent of households own an air conditioner and 48 percent have a washing machine and water pump, with higher percentages in urban than rural households. Motorcycles/scooters and bicycles are the most common means of transportation in Pakistan; 35 percent of households own a motor- cycle, and 28 percent own a bicycle. Motorcycle ownership is more common in urban (47 percent) than rural (28 percent) areas, whereas bicycle ownership is common in both urban and rural areas (27 percent and 28 percent, respectively). Only 9 percent of households own an animal- drawn cart; percentages are higher in rural (12 percent) than urban (3 percent) households. Ownership of a car, truck, or bus is higher in urban areas (12 percent) than in rural areas (4 percent). Thirty-one percent of households own agricultural land. Ownership of a homestead or other land is less common in urban areas (11 percent) than in rural areas (41 percent). Ownership of land other than a homestead has declined slightly since 2006-07 (from 37 percent to 31 percent), especially in rural areas (50 percent to 41 percent). Forty-six percent of households own farm animals (cattle, cows, bulls, buffalo, horses, donkeys, camels, goats, sheep, chickens), the most commonly owned type of livestock. As expected, rural households are more likely than urban households to own livestock (64 percent and 12 percent, respectively). The proportion of households owning livestock has dropped (by 7 percentage points in rural areas and 5 percentage points in urban areas) since 2006-07. 2.2 Socioeconomic Status Index The wealth index used in this survey has been used in many DHS and other country-level surveys to measure inequalities in household characteristics, in the use of health and other services, and in health outcomes (Rutstein et al., 2000). It serves as an indicator of household-level wealth that is consistent with expenditure and income measures (Rutstein, 1999). The index is constructed using data on household ownership of assets based on principal components analysis. In its current form, which takes better account of urban-rural differences in indicators of wealth, the index is created in three steps. In the first step, a subset of indicators common to urban and rural areas is used to create wealth scores for households in both areas. Categorical variables are transformed into separate dichotomous (0-1) indicators. These indicators and those that are continuous are then examined using a principal components analysis to produce a common factor score for each household. In the second Table 2.4 Household possessions Percentage of households possessing various household effects, means of transportation, agricultural land, and livestock/farm animals by residence, Pakistan 2012-13 Possession Residence Total Urban Rural Household effects Radio 10.7 11.0 10.9 Television 86.5 46.7 60.2 Mobile telephone 94.7 83.0 87.0 Non-mobile telephone 19.5 3.6 9.0 Refrigerator 70.4 30.2 43.8 Almirah/cabinet 73.5 34.3 47.6 Chair 71.1 45.9 54.4 Room cooler 19.2 6.8 11.0 Air conditioner 17.9 1.7 7.2 Washing machine 79.3 32.7 48.4 Water pump 65.2 39.1 47.9 Bed 90.6 88.1 89.0 Clock 89.3 55.9 67.2 Sofa 56.3 18.7 31.5 Camera 19.1 4.2 9.3 Sewing machine 75.2 46.6 56.3 Computer 29.1 5.2 13.3 Internet connection 17.4 1.3 6.8 Watch 56.8 40.8 46.2 Means of transport Bicycle 26.9 28.2 27.8 Animal-drawn cart 3.1 12.0 9.0 Motorcycle/scooter 46.5 28.3 34.5 Car/truck/bus 11.5 3.5 6.2 Tractor 0.9 4.2 3.1 Boat with a motor 0.1 0.0 0.1 Boat without a motor 0.1 0.1 0.1 Ownership of agricultural land 11.3 40.8 30.8 Ownership of farm animals1 11.6 63.8 46.1 Number 4,383 8,560 12,943 1 Cattle, cows, bulls, buffalo, horses, donkeys, camels, goats, sheep, or chickens Housing Characteristics and Household Population • 15 step, separate factor scores are produced for households in urban and rural areas using area-specific indicators. The third step combines the separate area-specific factor scores to produce a nationally applicable combined wealth index by adjusting area-specific scores through a regression on the common factor scores. This three-step procedure permits greater adaptability of the wealth index in both urban and rural areas. The resulting combined wealth index has a mean of zero and a standard deviation of one. Once the index is computed, national-level wealth quintiles (from lowest to highest) are obtained by assigning household scores to each de jure household member, ranking each person in the population by his or her score, and then dividing the ranking into five equal categories, each comprising 20 percent of the population. Table 2.5 presents wealth quintiles by residence and region. Fifty percent of urban residents are in the highest wealth quintile, as compared with only 5 percent of rural residents. Residents of ICT Islamabad are more likely to fall in the highest wealth quintile (69 percent) than people living in other regions. In contrast, Gilgit Baltistan, Balochistan, and Sindh have the highest proportions of residents in the lowest wealth quintile (50 percent, 44 percent, and 32 percent, respectively). Table 2.5 Wealth quintiles Percent distribution of the de jure population by wealth quintiles, and the Gini coefficient, according to residence and region, Pakistan 2012-13 Residence/region Wealth quintile Total Number of persons Gini coefficient Lowest Second Middle Fourth Highest Residence Urban 1.5 4.5 14.0 30.1 50.0 100.0 28,773 0.15 Rural 29.1 27.6 22.9 15.1 5.3 100.0 58,944 0.31 Region Punjab 13.1 19.2 23.5 23.7 20.5 100.0 48,879 0.30 Urban 1.0 2.7 15.7 31.1 49.6 100.0 15,367 0.20 Rural 18.6 26.8 27.1 20.4 7.2 100.0 33,511 0.30 Sindh 32.0 14.4 10.0 16.3 27.2 100.0 20,990 0.38 Urban 1.3 5.3 9.0 29.1 55.3 100.0 10,058 0.20 Rural 60.2 22.8 11.0 4.6 1.4 100.0 10,932 0.40 Khyber Pakhtunkhwa 18.1 32.0 24.9 15.4 9.6 100.0 12,606 0.31 Urban 1.4 8.2 19.2 32.1 39.1 100.0 2,121 0.20 Rural 21.5 36.8 26.0 12.0 3.7 100.0 10,485 0.30 Balochistan 43.8 21.1 16.8 11.5 6.7 100.0 4,112 0.27 Urban 10.5 15.0 29.8 27.0 17.7 100.0 845 0.20 Rural 52.5 22.7 13.5 7.5 3.9 100.0 3,268 0.30 ICT Islamabad 1.6 2.2 8.7 18.2 69.4 100.0 428 0.16 Gilgit Baltistan 49.7 33.2 12.2 3.9 0.9 100.0 702 0.31 Total 20.0 20.0 20.0 20.0 20.0 100.0 87,717 0.28 Table 2.5 also includes information on the Gini coefficient, which indicates the distribution of wealth. This ratio is expressed as a proportion between 0 (equal distribution) and 1 (totally unequal distribution). Overall, Pakistan has a Gini coefficient of 0.28. Wealth inequality is much higher in rural than in urban areas (0.31 and 0.15, respectively), corresponding well with the wealth quintile results discussed above. Inequality in wealth is highest in Sindh and lowest in ICT Islamabad (0.38 and 0.16, respectively). 2.3 Hand Washing Observance and promotion of basic hygiene are fundamental for good public health. Hand washing with a detergent ensures that transmission of germs is restricted, especially among children who are prone to diarrhea and other childhood illnesses. Hand washing, which protects against communicable diseases, is promoted by the government of Pakistan through public awareness programs and development partners. Table 2.6 provides information, according to residence (urban or rural), region, and wealth quintile, on designated places for hand washing in households and on the use of water and cleansing agents for washing hands. 16 • Housing Characteristics and Household Population Table 2.6 Hand washing Percentage of households in which the place most often used for washing hands was observed, and among households in which the place for hand washing was observed, the percent distribution by availability of water, soap, and other cleansing agents, Pakistan 2012-13 Percentage of households where place for washing hands was observed Number of households Among households where place for hand washing was observed, percentage with: Number of households with place for hand washing observed Background characteristic Soap and water1 Water and cleansing agent2 other than soap only Water only Soap but no water3 Cleansing agent other than soap only2 No water, soap, or other cleansing agent Missing Total Residence Urban 83.8 4,383 88.0 0.3 9.6 0.5 0.2 1.3 0.1 100.0 3,672 Rural 85.0 8,560 51.6 2.5 33.8 0.4 0.2 11.4 0.1 100.0 7,279 Region Punjab 87.4 7,614 71.9 1.4 23.1 0.3 0.2 3.1 0.0 100.0 6,651 Sindh 87.1 3,004 52.4 2.7 31.3 0.3 0.1 13.2 0.0 100.0 2,616 Khyber Pakhtunkhwa 66.5 1,711 55.4 1.3 27.3 0.9 0.3 14.6 0.2 100.0 1,139 Balochistan 89.5 450 33.4 3.5 27.4 1.7 0.2 33.5 0.2 100.0 403 ICT Islamabad 84.9 72 92.1 0.1 4.0 1.6 0.0 2.2 0.0 100.0 61 Gilgit Baltistan 88.2 91 22.2 0.4 46.7 1.0 0.0 29.7 0.0 100.0 81 Wealth quintile Lowest 81.6 2,558 15.9 5.0 51.7 0.3 0.3 26.7 0.0 100.0 2,087 Second 84.4 2,601 45.0 2.5 40.5 0.6 0.3 11.1 0.0 100.0 2,196 Middle 85.9 2,609 69.8 1.3 25.5 0.2 0.3 2.7 0.1 100.0 2,240 Fourth 87.7 2,557 88.1 0.2 10.6 0.3 0.0 0.7 0.0 100.0 2,243 Highest 83.5 2,618 97.6 0.0 1.7 0.5 0.0 0.1 0.2 100.0 2,185 Total 84.6 12,943 63.8 1.8 25.7 0.4 0.2 8.0 0.1 100.0 10,951 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 In the 2012-13 PDHS, interviewers were instructed to observe the place where household members usually wash their hands. They looked for regularity of water supply and observed whether the household had cleansing agents near the place of hand washing. Overall, the interviewers observed designated places for hand washing in 85 percent of households, with little variation in urban and rural households (84 percent and 85 percent, respectively). Places for hand washing were observed in more than 85 percent of the households in all regions other than Khyber Pakhtunkhwa (67 percent). In addition, such facilities were observed in 82 percent or more of households in all wealth quintiles. Among households where the place of hand washing was observed, 64 percent had soap and water, 2 percent had water and other cleansing agents (ash, mud, sand, etc.), and 26 percent had water only. Overall, 8 percent of households do not have water, soap, or any cleansing agent in places of hand washing. Rural households (11 percent) are more likely than urban households (1 percent) not to have water, soap, or any cleansing agent. Eighty-eight percent of urban households have soap and water, as compared with 52 percent of rural households. Availability of hand washing facilities (soap and water) varies across regions, ranging from 22 percent of households in Gilgit Baltistan to 92 percent in ICT Islamabad. The use of soap and water for hand washing increases with increasing household wealth, from 16 percent of households in the lowest wealth quintile to 98 percent of households in the highest quintile. 2.4 HOUSEHOLD POPULATION BY AGE AND SEX Table 2.7 shows the distribution of the de facto household population by five-year age groups, according to urban-rural residence and sex. The total population counted in the 2012-13 PDHS was 87,784 (44,227 males and 43,557 females). Age and sex are important demographic variables and are the primary basis of demographic classifications in vital statistics, censuses, and surveys. They are also very important variables in the study of mortality, fertility, nuptiality, and migration. In general, a cross-classification by sex and age is useful for the effective analysis of all forms of data obtained in surveys. Housing Characteristics and Household Population • 17 Table 2.7 Household population by age, sex, and residence Percent distribution of the de facto household population by five-year age groups, according to sex and residence, Pakistan 2012-13 Age Urban Rural Male Female Total Sex ratioMale Female Total Sex ratio Male Female Total Sex ratio <5 12.2 12.1 12.2 101.9 14.2 14.0 14.1 101.9 13.6 13.4 13.5 101.5 5-9 11.4 11.3 11.3 100.7 15.3 13.5 14.4 113.7 14.0 12.8 13.4 109.7 10-14 12.0 11.3 11.7 106.0 13.3 11.5 12.4 116.1 12.9 11.4 12.2 112.8 15-19 11.5 11.7 11.6 97.9 11.1 11.1 11.1 99.6 11.2 11.3 11.3 99.0 20-24 10.3 11.1 10.7 92.8 8.4 10.1 9.2 82.5 9.0 10.4 9.7 86.2 25-29 8.8 8.9 8.9 99.3 6.9 8.2 7.5 84.2 7.5 8.4 8.0 89.6 30-34 6.7 7.1 6.9 94.9 5.5 6.1 5.8 89.8 5.9 6.4 6.2 91.7 35-39 5.7 6.1 5.9 93.3 4.7 5.6 5.2 84.3 5.0 5.8 5.4 87.5 40-44 5.0 4.9 5.0 101.6 4.2 4.1 4.1 103.3 4.5 4.4 4.4 102.8 45-49 4.5 4.4 4.5 102.7 3.9 3.6 3.8 106.2 4.1 3.9 4.0 105.0 50-54 2.9 2.7 2.8 107.1 2.3 2.9 2.6 78.5 2.5 2.8 2.7 87.6 55-59 2.4 2.9 2.7 84.9 2.5 3.1 2.8 80.5 2.5 3.0 2.7 81.8 60-64 2.4 1.8 2.1 130.0 2.6 2.4 2.5 107.8 2.5 2.2 2.4 113.7 65-69 1.6 1.5 1.6 107.6 1.9 1.4 1.7 131.6 1.8 1.5 1.6 123.4 70-74 1.3 0.8 1.1 155.9 1.5 1.2 1.4 128.1 1.5 1.1 1.3 134.9 75-79 0.5 0.5 0.5 94.7 0.6 0.5 0.5 134.2 0.6 0.5 0.5 120.0 80+ 0.6 0.7 0.6 95.1 1.1 0.7 0.9 151.6 0.9 0.7 0.8 133.8 Total 100.0 100.0 100.0 na 100.0 100.0 100.0 na 100.0 100.0 100.0 na Number 14,690 14,145 28,835 103.9 29,537 29,412 58,949 100.4 44,227 43,557 87,784 101.5 na = Not applicable The age structure of the household population in Pakistan is typical of a society with a youthful population. The sex and age distribution of the population is shown in the population pyramid in Figure 2.1. Pakistan has a pyramidal age structure due to the large number of children below age 15. It is evident that the pyramid is broad-based but slightly narrower at the lowest base (0-4 age group), a pattern that typically depicts a high fertility rate but with a recent declining trend. In Pakistan, children under age 15 account for 39 percent of the population, while 57 percent of the country’s residents are in the 15-64 age group and 4 percent are over 65. Although the proportion of the Pakistani population under age 15 remains large (39 percent) (Figure 2.1), this proportion has dropped since 2006-07 (41 percent). Fourteen percent of the population is under age 5. As noted, persons age 65 and over account for about 4 percent of the total population, the same proportion as in 2006-07 (NIPS and Macro International, 2008). The proportion of the population 65 and older is somewhat lower in urban areas (4 percent) than in rural areas (5 percent), as is the proportion under age 15, a pattern consistent with higher fertility in rural than urban areas (see Chapter 5). 18 • Housing Characteristics and Household Population Figure 2.1 Population pyramid The fact that there is a smaller proportion of children under age 5 in urban than rural areas suggests that recent declines in fertility are more evident in urban areas than in rural areas and that the transition to lower fertility has begun in the urban population. The age-sex structure shown in Figure 2.1 is typical of a historically high fertility level that has recently started to decline. The overall sex ratio is 102 males per 100 females (Table 2.8), a decline from the ratio of 108 males per 100 females shown in the 1990-91 PDHS. The marked difference in the sex ratio between the two surveys could be the changing survival rates of females. The sex composition of the population does not vary markedly by urban-rural residence. The sex ratio is lowest in the 20-24 and 55-59 age groups (86 and 82, respectively), indicating a low proportion of males in these groups. Table 2.8 also shows that about half of the total female population falls into the reproductive age groups of 15-49 years. The fact that this segment has been increasing over the last two decades is noteworthy, because they are in their childbearing years and hence contributing to overall population growth. A comparison of the 2012-13 PDHS age-sex distribution with distributions from previous surveys and the census shows that the sex ratio declined from 108 males per 100 females in 1990-91 (PDHS) and 1998 (census) to the current ratio of 102 males per 100 females. The lower male-female ratio in the 2012- 13 PDHS could be attributed to better enumeration of household members, especially females, thus leading to a more plausible sex ratio. Household population data by age, sex, and region, along with sex ratios, are presented in Appendix Table A2.3. Housing Characteristics and Household Population • 19 Table 2.8 Trends in age distribution of household population Percent distribution of household population by five-year age groups, overall sex ratio, and percentage of women age 15-49, Pakistan 1990-2013 Age group PDHS 1990-91 PFFPS 1996-97 Census 1998 PRHFPS 2000-01 SWRHFPS 2003 PDHS 2006-07 PDHS 2012-13 0-4 13.4 14.4 14.8 13.8 13.1 13.4 13.5 5-9 17.4 15.4 15.7 14.3 14.2 14.3 13.4 10-14 13.7 13.3 13.0 13.2 13.5 12.9 12.2 15-19 10.2 11.4 10.4 11.9 11.5 11.9 11.3 20-24 8.1 8.6 9.0 9.3 9.3 9.5 9.7 25-29 7.1 7.4 7.4 7.4 7.2 7.6 8.0 30-34 5.4 5.6 6.2 5.8 5.6 5.7 6.2 35-39 4.6 4.7 4.8 4.9 5.4 5.3 5.4 40-44 4.0 3.6 4.4 3.9 4.1 4.3 4.4 45-49 3.0 2.9 3.5 2.8 3.5 3.8 4.0 50-54 3.2 3.2 3.2 3.6 3.6 2.9 2.7 55-59 2.4 2.7 2.2 2.4 2.4 2.2 2.7 60-64 2.7 2.6 2.0 2.5 2.5 2.1 2.4 65 and over 5.0 4.3 3.5 4.2 4.3 4.1 4.2 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Sex ratio 108 107 108 103 106 102 102 Percentage of females (15-49) 42.6 44.0 46.2 46.4 47.4 49.7 49.6 PFFPS = Pakistan Fertility and Family Planning Survey PRHFPS = Pakistan Reproductive Health and Family Planning Survey SWRHFPS = Status of Women, Reproductive Health, and Family Planning Survey Sources: PDHS 1990-91: NIPS and Macro, 1992; PFFPS 1996-97: Hakim et al., 1998; Census 1998: Government of Pakistan, 1998; PRHFPS 2000-01: NIPS, 2001; SWRHFPS 2003: NIPS, 2007a; PDHS 2006-07: NIPS and Macro International, 2008; PDHS 2012-13: NIPS and ICF Macro Inc., 2013 Table 2.8 also shows changes in the age structure of the population since the 1990-91 PDHS. The proportion of the population under age 15 decreased from 45 percent in 1990-91 to 39 percent in 2012-13, indicating fertility declines over this period. Consequently, the proportion of residents of working age (15- 59 years) has increased, while the proportion of the elderly (age 60 and above) has not changed substantially. The proportion of the female population increased from 43 percent to 50 percent between 1990-91 and 2012-13, indicating a greater likelihood of increases in reproduction if fertility regulation measures are not adopted, especially among younger women. 2.5 HOUSEHOLD COMPOSITION Information on household composition is critical for understanding family size, household headship, and orphanhood and for implementing meaningful population-based policies and programs. Household composition is also a determinant of better health status and well-being. In the 2012-13 PDHS, a household was defined as a person or group of related and unrelated persons who live together in the same dwelling unit(s) or in connected premises, who acknowledge one adult member as head of the household, and who have common arrangements for cooking and eating. The household is considered to be the basic social and economic unit of society, and changes in household composition have repercussions for the family and the economy. Such changes also have an impact on the distribution of goods and services and on the planning and requirements of community institutions, schools, housing, and health infrastructure (Ekouevi et al., 1991). Table 2.9 shows the distribution of households by sex of the head of the household and by the number of household members in urban and rural areas. Households in Pakistan are predominantly male- headed, with 89 percent of households being headed by a male and only 11 percent being headed by a female (an increase from 9 percent in 2006-07). The proportion of female-headed households is higher in rural (12 percent) than urban (10 percent) areas. This could be attributed to out-migration of the male population from rural to urban areas or even overseas for employment purposes. The increase in female- headed households is more evident in rural than urban areas. Female headship of households is a 20 • Housing Characteristics and Household Population matter of concern for policymakers, particularly those dealing with poverty issues, because it is usually financially difficult for a woman to manage a household alone (Osaki, 1991). Table 2.9 also presents information on the number of members usually living in the household. More than half of the households in Pakistan are composed of two to six members (53 percent), while 46 percent have more than six members and 24 percent have more than nine members. Households in Pakistan tend to be large because of the predominance of the extended and joint family system. Economic pressure can also force middle- and lower-income families to live with their in- laws and other relatives because they cannot afford to build or rent separate dwellings. The 2012-13 PDHS data show that the average household size observed in the survey is 6.8 persons, roughly similar to that in 2006-07. Mean household size is slightly smaller in urban than in rural areas (6.6 persons and 6.9 persons, respectively). The 2012-13 PDHS also collected information on the presence of foster children and orphans in households. Foster children are those under age 18 who are living in households with neither their mother nor their father present, while orphans are children with one parent (single orphans) or both parents (double orphans) dead. Foster children and orphans are of concern because they may be at increased risk of neglect or exploitation with their mothers or fathers not present to assist them. Table 2.9 shows that there is little difference in the distribution of orphans by rural or urban residence. Overall, 10 percent of households have foster and/or orphan children, and the percentage is slightly higher in rural than urban households (11 percent and 10 percent, respectively). Single orphans are present in 6 percent of households, whereas double orphans are present in less than 1 percent of households. 2.6 BIRTH REGISTRATION OF CHILDREN UNDER AGE 5 Formal registering of births is not widely practiced in Pakistan, even though the national registration system was introduced in 1973 and enforced by the directorate general of registration (Alvi, 1993). Table 2.10 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 3 in 10 children (34 percent) under age 5 have been registered, and 32 percent have a birth certificate. Table 2.9 Household composition Percent distribution of households by sex of head of household and by household size, mean size of household, and percentage of households with orphans and foster children under age 18, according to residence, Pakistan 2012-13 Characteristic Residence Total Urban Rural Household headship Male 90.3 88.5 89.1 Female 9.7 11.5 10.9 Total 100.0 100.0 100.0 Number of usual members 1 0.8 1.0 0.9 2 4.4 4.5 4.5 3 7.0 8.1 7.7 4 12.6 11.3 11.8 5 16.0 13.1 14.1 6 16.6 13.6 14.6 7 13.2 11.9 12.3 8 9.3 11.0 10.4 9+ 20.2 25.6 23.7 Total 100.0 100.0 100.0 Mean size of households 6.6 6.9 6.8 Percentage of households with orphans and foster children under age 18 Foster children1 5.1 5.3 5.3 Double orphans 0.6 0.6 0.6 Single orphans2 5.5 6.8 6.4 Foster and/or orphan children 9.5 10.8 10.4 Number of households 4,383 8,560 12,943 Note: Table is based on de jure household members (i.e., usual residents). 1 Foster children are those under age 18 living in households with neither their mother nor their father present. 2 Includes children with one dead parent and an unknown survival status of the other parent Housing Characteristics and Household Population • 21 Table 2.10 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 2012-13 Background characteristic Children whose births are registered Number of children Percentage with a birth certificate Percentage without a birth certificate Percentage registered Age <2 29.8 1.2 30.9 4,411 2-4 33.2 2.0 35.2 7,267 Sex Male 32.3 1.8 34.1 5,894 Female 31.6 1.6 33.1 5,784 Residence Urban 56.7 2.5 59.3 3,460 Rural 21.5 1.3 22.8 8,217 Region Punjab 44.5 1.6 46.1 6,423 Sindh 23.5 1.5 25.1 2,786 Khyber Pakhtunkhwa 8.3 1.3 9.6 1,720 Balochistan 4.3 3.4 7.7 613 ICT Islamabad 69.1 5.2 74.2 45 Gilgit Baltistan 18.3 5.0 23.3 91 Wealth quintile Lowest 4.6 0.4 5.0 2,830 Second 17.3 1.6 18.9 2,420 Middle 31.4 2.4 33.8 2,223 Fourth 50.4 2.2 52.6 2,272 Highest 69.1 2.3 71.4 1,933 Total 31.9 1.7 33.6 11,677 Although the government’s vital registration system requires that a newborn be registered within the shortest possible time after birth, Table 2.10 indicates that children under age 2 are less likely to be registered than children age 2-4 (31 percent and 35 percent, respectively). The registration of older children is primarily driven by the practice of asking parents to produce a child’s birth certificate for school admission. Table 2.10 also shows that birth registration is higher in urban (59 percent) than in rural (23 percent) areas. There is no difference in the extent of birth registration between male and female children. Among the regions, 74 percent of children in ICT Islamabad, 46 percent in Punjab, 25 percent in Sindh, 23 percent in Gilgit Baltistan, 10 percent in Khyber Pakhtunkhwa, and only 8 percent in Balochistan are registered. Children from the highest wealth quintile are more likely to have their births registered (71 percent) than children from the lowest wealth quintile (5 percent). Birth certificates are made mandatory for services such as school enrollment, passports, voter registration, and marriage registration. Local governmental organizations and nongovernmental organizations (NGOs) are participating in birth registration for workplace populations. Rural residents; people living in Balochistan, Khyber Pakhtunkhwa, and Gilgit Baltistan; and those in the lower two wealth quintiles are less likely to have a birth certificate. 2.7 REGISTRATION WITH NADRA Pakistan has a legal and administrative structure stipulating official registration of births according to standard procedures. In 2000, the government established the National Database and Registration Authority (NADRA) to oversee registration of the population. All children under age 18 are registered using the “Bay Form,” and adults age 18 and older are issued a computerized 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 2.11 presents information on the registration status of household members. 22 • Housing Characteristics and Household Population Table 2.11 Registration with NADRA Percentage of the de jure household population registered with NADRA, according to background characteristics, Pakistan 2012-13 Background characteristic Among those under age 18 Among those age 18 or over Among all ages Percentage with Bay Form Number Percentage with CNIC Number Percentage with neither1 Number Sex Male 20.1 20,766 89.8 23,408 43.0 44,175 Female 19.3 19,255 76.9 24,283 48.6 43,542 Residence Urban 36.0 12,085 85.4 16,684 35.4 28,773 Rural 12.7 27,937 82.0 31,007 50.8 58,944 Region Punjab 21.6 21,845 82.3 27,032 44.8 48,879 Sindh 21.4 9,345 82.5 11,645 44.7 20,990 Khyber Pakhtunkhwa 12.5 6,196 86.3 6,408 50.0 12,606 Balochistan 8.9 2,128 87.3 1,985 53.3 4,112 ICT Islamabad 66.5 159 92.7 268 17.1 428 Gilgit Baltistan 34.6 348 86.6 354 39.2 702 Wealth quintile Lowest 2.6 9,132 80.4 8,420 60.1 17,552 Second 9.0 8,676 81.5 8,873 54.3 17,549 Middle 18.2 8,044 81.8 9,491 47.4 17,536 Fourth 29.4 7,540 82.8 10,000 40.2 17,540 Highest 48.2 6,629 88.4 10,908 26.8 17,539 Total 19.7 40,022 83.2 47,692 45.8 87,717 NADRA = National Database and Registration Authority CNIC = computerized national identity card 1 Excludes those who have document appropriate for the other age groups Overall, about 20 percent of the household population under age 18 has a Bay Form (20 percent of males and 19 percent of females). More than four in five adults (age 18 and over) have a CNIC. Forty-six percent of the population does not have any form of registration. Females, rural residents, people living in Khyber Pakhtunkhwa and Balochistan, and those in the lower two wealth quintiles are less likely to be registered with NADRA than other subgroups. Among regions, ICT Islamabad has the highest percentage of residents with a CNIC (93 percent). 2.8 CHILDREN’S LIVING ARRANGEMENTS AND ORPHANHOOD The 2012-13 PDHS collected information on living arrangements and orphanhood among children. Living arrangements should be monitored together with the proportion of foster and orphan children because of their significant effects on children’s comprehensive development. Table 2.12 shows the percent distribution of children under age 18 by living arrangements and survivorship of parents. About 84 percent of children below age 15 and 83 percent of those below age 18 live with both of their parents. Approximately 2 percent of both children less than age 15 and children less than age 18 are not living with their biological parents, even if both are alive. About 4 percent of children younger than age 15 and 5 percent of children younger than age 18 have one or both parent dead. A substantial proportion of children age 15-17 (5 percent) are not living with either parent, even when both parents are alive. This may be due to children moving to a relative’s house to pursue further education or to seek work and shelter. Table 2.12 shows that the percentage of children not living with their parents increases with age. Variation by background characteristics is minimal, except that children in the lowest wealth quintile more often have one or both parent dead. Housing Characteristics and Household Population • 23 Table 2.12 Children’s living arrangements and orphanhood Percent distribution of de jure children under age 18 by living arrangements and survival status of parents, the percentage of children not living with a biological parent, and the percentage of children with one or both parents dead, according to background characteristics, Pakistan 2012-13 Background characteristic 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 bio- logical parent Percent- age with one or both parents dead1 Number of children Father alive Father dead Mother alive Mother dead Both alive Only father alive Only mother alive Both dead Missing informa- tion on father/ mother Age 0-4 85.3 13.1 0.5 0.1 0.2 0.5 0.1 0.0 0.1 0.1 100.0 0.7 0.9 11,677 <2 84.8 13.9 0.3 0.1 0.1 0.5 0.0 0.0 0.2 0.1 100.0 0.7 0.6 4,411 2-4 85.6 12.6 0.6 0.1 0.3 0.5 0.1 0.0 0.1 0.1 100.0 0.7 1.1 7,267 5-9 83.5 11.7 1.8 0.3 1.1 1.0 0.2 0.1 0.2 0.1 100.0 1.6 3.5 11,742 10-14 82.0 9.1 4.2 0.5 1.6 1.5 0.4 0.1 0.3 0.1 100.0 2.4 6.7 10,698 15-17 76.2 8.0 6.7 0.8 2.3 3.6 0.3 0.5 0.8 0.8 100.0 5.2 10.6 5,904 Sex Male 83.3 10.6 2.8 0.4 1.1 1.0 0.2 0.1 0.3 0.2 100.0 1.7 4.6 20,766 Female 81.8 11.1 2.7 0.4 1.2 1.8 0.3 0.2 0.3 0.3 100.0 2.5 4.7 19,255 Residence Urban 86.4 6.8 2.9 0.5 0.9 1.6 0.2 0.2 0.3 0.2 100.0 2.2 4.5 12,085 Rural 80.9 12.6 2.7 0.3 1.3 1.3 0.3 0.1 0.3 0.2 100.0 2.0 4.7 27,937 Region Punjab 81.1 11.9 3.1 0.5 1.1 1.5 0.3 0.2 0.2 0.1 100.0 2.2 4.8 21,845 Sindh 88.7 4.7 2.5 0.3 1.7 1.3 0.2 0.1 0.2 0.2 100.0 1.9 4.7 9,345 Khyber Pakhtunkhwa 74.5 19.9 2.3 0.2 0.9 1.1 0.2 0.1 0.3 0.4 100.0 1.8 3.8 6,196 Balochistan 92.7 1.0 2.7 0.1 1.1 0.7 0.0 0.2 1.0 0.5 100.0 1.9 5.0 2,128 ICT Islamabad 88.4 5.7 1.9 0.2 0.4 2.0 0.1 0.2 0.4 0.5 100.0 2.8 3.1 159 Gilgit Baltistan 84.1 9.3 2.2 0.7 0.6 2.1 0.0 0.3 0.3 0.3 100.0 2.8 3.5 348 Wealth quintile Lowest 85.7 7.8 2.6 0.1 1.9 0.9 0.3 0.2 0.4 0.2 100.0 1.8 5.3 9,132 Second 80.1 12.7 2.8 0.5 1.3 1.4 0.5 0.2 0.3 0.3 100.0 2.3 5.0 8,676 Middle 79.9 13.6 3.1 0.4 0.9 1.4 0.1 0.2 0.3 0.2 100.0 1.9 4.5 8,044 Fourth 81.2 12.1 3.0 0.5 0.9 1.5 0.1 0.1 0.3 0.2 100.0 2.0 4.5 7,540 Highest 86.2 7.8 2.4 0.5 0.6 1.8 0.2 0.2 0.2 0.2 100.0 2.3 3.5 6,629 Total <15 83.6 11.3 2.1 0.3 1.0 1.0 0.2 0.1 0.2 0.1 100.0 1.5 3.6 34,117 Total <18 82.5 10.8 2.8 0.4 1.2 1.4 0.3 0.2 0.3 0.2 100.0 2.1 4.6 40,022 Note: Table is based on de jure members (i.e., usual residents). 1 Includes children with father dead, mother dead, both dead, and one parent dead but missing information on the survival status of the other parent Table 2.13 shows the percent dis- tribution of de jure children age 10-14 by school attendance and survivorship of parents. In all, 57 percent of children with both parents deceased are attending school, as compared with 72 percent of children with both parents alive (and who are living with at least one parent). 2.9 EDUCATIONAL ATTAINMENT AND SCHOOL ATTENDANCE Education is an important socio- economic factor that has multifaceted effects on an individual’s attitudes and behaviors and contributes to promoting economic growth, empowerment of women, and household living standards. In general, the higher a woman’s level of education, the more knowledgeable she is about the use of health facilities, family planning methods, and the health of her children. As part of its commitment to the Table 2.13 School attendance by survivorship of parents Among de jure children age 10-14, the percentage attending school by parental survival, according to background characteristics, Pakistan 2012-13 Background characteristic Percentage attending school by survivorship of parents Both parents deceased Number Both parents alive and living with at least one parent Number Sex Male (69.5) 22 76.9 5,277 Female (27.5) 10 65.2 4,527 Residence Urban * 7 83.8 3,110 Rural (51.7) 25 65.8 6,694 Region Punjab * 14 77.4 5,277 Sindh * 1 59.5 2,316 Khyber Pakhtunkhwa * 7 73.5 1,574 Balochistan (20.8) 10 55.9 506 ICT Islamabad * 0 89.2 42 Gilgit Baltistan * 0 80.9 90 Wealth quintile Lowest * 7 39.6 2,070 Second * 9 66.0 2,185 Middle * 5 78.7 1,961 Fourth * 7 85.6 1,883 Highest * 3 93.7 1,705 Total 56.8 32 71.5 9,804 Note: Table is based only on children who usually live in the household. 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. 24 • Housing Characteristics and Household Population Dakar Framework for Action 2000, Pakistan has adopted an “education for all” strategy. Recently, various measures have been adopted to meet the MDG target of ensuring universal primary education by 2015, whereby all children (and particularly girls, children in disadvantaged situations, and children from ethnic minority groups) have access to compulsory and good-quality primary education (UNICEF, 2006). To cope with the demand for education, the government of Pakistan has encouraged investment in education in the private sector, which has contributed significantly to improving primary-, secondary-, and university-level education (Government of Pakistan, 2010a). The government’s Five-Year Development Plan (2010-2015) has set the priorities of providing free and high-quality basic-level education (grades 1 to 8) and expanding equitable and participatory access to high-quality education to the secondary level (grades 9 to 12). 2.9.1 Educational Attainment of the Household Population In the 2012-13 PDHS, information was collected on the educational attainment and school attendance of household members age 5 to 24. Tables 2.14.1 and 2.14.2, respectively, show the percent distributions of the de facto female and male household populations age 5 and above by highest level of education and background characteristics. Table 2.14.1 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 completed and median years completed, according to background characteristics, Pakistan 2012-13 Background characteristic No education Primary1 Middle2 Secondary3 Higher4 Don’t know/ missing Total Number Median years completed Age 5-9 70.1 29.1 0.0 0.0 0.0 0.7 100.0 5,566 0.0 10-14 28.0 50.8 19.3 1.7 0.1 0.1 100.0 4,977 2.7 15-19 29.5 20.7 20.0 18.5 11.3 0.1 100.0 4,937 5.0 20-24 36.3 17.3 10.8 15.3 20.1 0.1 100.0 4,543 4.7 25-29 45.3 16.3 9.6 12.9 15.8 0.2 100.0 3,660 3.5 30-34 52.8 15.2 7.3 10.8 13.8 0.2 100.0 2,798 0.0 35-39 59.8 15.0 5.9 9.6 9.4 0.2 100.0 2,510 0.0 40-44 68.1 13.9 4.8 6.6 6.6 0.1 100.0 1,895 0.0 45-49 71.6 11.8 3.9 6.9 5.9 0.0 100.0 1,696 0.0 50-54 78.5 10.5 3.7 3.3 3.6 0.4 100.0 1,239 0.0 55-59 82.3 8.1 2.9 3.4 3.0 0.3 100.0 1,316 0.0 60-64 86.9 6.4 2.3 1.5 2.5 0.3 100.0 967 0.0 65+ 91.2 4.1 1.4 1.3 1.4 0.6 100.0 1,623 0.0 Residence Urban 32.9 23.2 12.4 14.4 16.9 0.2 100.0 12,429 4.4 Rural 62.6 21.0 7.5 5.1 3.7 0.2 100.0 25,302 0.0 Region Punjab 46.9 25.2 11.1 9.0 7.7 0.1 100.0 21,476 0.8 Sindh 58.1 16.2 6.4 8.2 11.0 0.2 100.0 8,631 0.0 Khyber Pakhtunkhwa 62.8 18.5 6.9 5.6 5.6 0.6 100.0 5,491 0.0 Balochistan 71.5 16.7 4.5 4.1 2.3 0.8 100.0 1,653 0.0 ICT Islamabad 22.1 20.4 10.7 13.7 32.3 0.9 100.0 182 7.3 Gilgit Baltistan 57.2 18.8 9.8 8.1 5.8 0.3 100.0 299 0.0 Wealth quintile Lowest 86.1 10.9 1.9 0.6 0.2 0.3 100.0 7,170 0.0 Second 68.9 22.0 5.2 2.3 1.3 0.2 100.0 7,524 0.0 Middle 52.9 27.0 10.0 6.2 3.6 0.3 100.0 7,564 0.0 Fourth 37.9 26.8 14.4 12.5 8.2 0.2 100.0 7,690 3.4 Highest 21.1 21.1 13.4 18.3 25.8 0.2 100.0 7,784 7.2 Total 52.8 21.7 9.1 8.1 8.0 0.2 100.0 37,731 0.0 Note: Total includes 3 women with missing information on age. 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. Table 2.14.1 shows that 53 percent of women have never been to school, whereas 22 percent have completed primary school, 9 percent have completed middle school, and 16 percent have a secondary education or higher. A comparison of educational attainment levels with the 2006-07 PDHS shows that although the percentage of women with no education has not changed substantially, the proportion of Housing Characteristics and Household Population • 25 women completing middle school or above has increased over time. The proportion of females with no schooling is lowest in the 10-14 age group and gradually increases in subsequent age groups. Completion of primary, middle, and secondary school is highest in the 15-19 age group, indicating that school attendance and continuation of education up to secondary levels have improved substantially among younger females in recent years. These results may reflect the impact of recent efforts to promote universal primary education, with a particular focus on girls. As expected, the proportion of the female population with no education is higher in rural areas (63 percent) than in urban areas (33 percent). Among regions, Punjab and ICT Islamabad have the lowest percentages of women with no schooling (47 percent and 22 percent, respectively), whereas Balochistan and Khyber Pakhtunkhwa have the highest percentages (72 percent and 63 percent, respectively). Wealth exerts a positive influence on educational attainment. Women in the highest wealth quintile (79 percent) are more likely to be educated than women in the lowest quintile (14 percent). Table 2.14.2 shows that 34 percent of men have no education, 26 percent have completed primary school, 15 percent have completed middle school, 13 percent have a secondary school education, and 12 percent have completed a higher level of education. Men have completed a median of 3.8 years of schooling. There are gender differences in educational attainment, with differences being smaller at the primary level than at other levels. Men are more likely than women to have completed secondary school or more (25 percent versus 16 percent). Table 2.14.2 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 completed and median years completed, according to background characteristics, Pakistan 2012-13 Background characteristic No education Primary1 Middle2 Secondary3 Higher4 Don’t know/ missing Total Number Median years completed Age 5-9 67.8 31.4 0.2 0.0 0.0 0.6 100.0 6,203 0.0 10-14 18.6 58.5 21.7 1.0 0.0 0.2 100.0 5,700 3.1 15-19 17.9 20.2 28.1 22.3 11.5 0.1 100.0 4,964 6.8 20-24 19.1 17.8 16.6 20.4 26.0 0.1 100.0 3,975 7.7 25-29 22.8 18.3 16.7 21.0 21.2 0.0 100.0 3,329 7.2 30-34 25.2 17.3 16.8 21.1 19.5 0.1 100.0 2,606 7.0 35-39 29.8 15.4 14.1 20.9 19.7 0.1 100.0 2,230 6.9 40-44 32.3 18.6 11.9 18.1 19.0 0.1 100.0 1,979 4.9 45-49 40.4 16.4 11.6 17.0 14.4 0.3 100.0 1,808 4.3 50-54 40.2 16.6 12.8 16.0 14.4 0.0 100.0 1,103 4.4 55-59 43.7 18.5 12.4 15.0 10.4 0.0 100.0 1,094 4.0 60-64 49.3 16.3 10.7 11.3 12.3 0.1 100.0 1,116 1.2 65+ 59.5 16.5 7.6 9.0 7.0 0.5 100.0 2,113 0.0 Residence Urban 22.6 24.4 16.1 16.3 20.5 0.1 100.0 12,893 5.8 Rural 40.2 27.0 14.0 11.5 7.2 0.2 100.0 25,329 2.2 Region Punjab 31.1 28.0 17.2 14.2 9.3 0.2 100.0 21,277 4.1 Sindh 38.3 23.6 10.4 10.9 16.8 0.1 100.0 9,326 3.7 Khyber Pakhtunkhwa 35.0 24.7 14.4 13.3 12.3 0.3 100.0 5,336 3.4 Balochistan 50.2 21.0 8.3 11.2 8.5 0.8 100.0 1,781 0.0 ICT Islamabad 12.6 19.5 13.5 16.9 37.0 0.4 100.0 201 9.0 Gilgit Baltistan 38.9 25.9 14.1 11.1 9.3 0.6 100.0 301 2.2 Wealth quintile Lowest 62.4 24.8 6.8 4.1 1.6 0.3 100.0 7,424 0.0 Second 42.5 30.6 13.9 8.7 4.1 0.3 100.0 7,549 1.4 Middle 32.6 28.7 17.1 13.3 8.1 0.2 100.0 7,767 3.8 Fourth 23.3 27.1 19.0 18.3 12.2 0.1 100.0 7,638 5.0 Highest 11.9 19.5 16.4 20.6 31.4 0.2 100.0 7,844 8.5 Total 34.2 26.1 14.7 13.1 11.7 0.2 100.0 38,222 3.8 Note: Total includes one man with missing information on age. 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. 26 • Housing Characteristics and Household Population Variations by age show that educational attainment levels are higher in the younger age groups than the older ones, indicating that school attendance decreases with age. The percentage of males who have completed schooling at all levels is higher in urban than rural areas with the exception of primary education; this indicates that a large proportion of rural residents complete only primary schooling, whereas those in urban areas are more likely to continue their education beyond the primary and middle levels. Eighty-eight percent of males in the highest wealth quintile have attained some level of education (with a median of 8.5 years), as compared with only 38 percent in the lowest quintile (with a median of less than one year), indicating substantial differentials in school attendance by wealth. Tables 2.14.1 and 2.14.2 indicate that, overall, levels of educational attainment are higher in urban than in rural areas; the proportions of men and women with no education are lower in urban than in rural areas, while the proportions with a secondary or higher education are greater in urban areas. On average, men and women living in urban areas have completed almost two more years of schooling than those living in rural areas. A comparison of the 2006-07 and 2012-13 PDHS surveys shows a marked rise in completed median years of schooling, with the median among men increasing from 2.9 to 3.8 years during this period. 2.9.2 School Attendance Ratios The net attendance ratio (NAR) indicates participation in primary schooling for the population age 5-9 and participation in middle/secondary school for the population age 10-14. The gross attendance ratio (GAR) measures participation at each level of schooling among those of any age. The GAR is almost always higher than the NAR for the same level because the GAR includes participation by those who may be older or younger than the official age range for that level. An NAR of 100 percent would indicate that all of those in the official age range are attending at that level. The GAR can exceed 100 percent if there is significant over-age or under-age participation at a given level of schooling. Table 2.15 provides data on NARs and GARs by sex and background characteristics by level of schooling. NARs are 60 percent (63 percent for males and 57 percent for females) at the primary level and 37 percent (40 percent for males and 34 percent for females) at the secondary level. Table 2.15 shows that differences in NAR at the primary and secondary levels by urban-rural residence and gender are large. At the primary level, NARs are 70 percent in urban areas and 56 percent in rural areas, and the gap is even larger for females (69 percent in urban areas and 51 percent in rural areas). At the secondary level, NARs are 50 percent in urban areas and 31 percent in rural areas. Among the regions, ICT Islamabad shows the highest NAR (80 percent) at the primary level, followed by Punjab (67 percent) and Khyber Pakhtunkhwa (57 percent); Balochistan has the lowest NAR (42 percent). Wealth has a positive effect on NARs and GARs at both the primary and secondary levels, showing that poverty is an important factor hindering children from attending school. It is important to note that GARs are much higher than NARs in all socioeconomic categories, indicating that many children either are starting school late or are repeaters at certain grades. Table 2.15 also shows the gender parity index (GPI), which represents the ratio of the NAR and GAR for females to the NAR and GAR for males. It is a more precise indicator of gender differences in school attendance rates. A GPI greater than 1.00 indicates that a higher proportion of females than males attend school. The GPI is close to 1.00 in urban areas, Punjab, and the highest wealth quintiles, indicating a narrow gender gap at both the primary and secondary levels. However, the gender gap is high in Sindh, Khyber Pakhtunkhwa, and Balochistan and in the lowest and second wealth quintiles. Housing Characteristics and Household Population • 27 Table 2.15 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 2012-13 Background characteristic Net attendance ratio1 Gross attendance ratio2 Male Female Total Gender parity index3 Male Female Total Gender parity index3 PRIMARY SCHOOL Residence Urban 71.3 69.0 70.2 0.97 106.5 97.9 102.3 0.92 Rural 59.6 51.1 55.7 0.86 93.8 77.3 86.1 0.82 Region Punjab 68.4 65.0 66.8 0.95 103.6 95.2 99.7 0.92 Sindh 54.8 44.8 50.0 0.82 88.5 66.6 78.1 0.75 Khyber Pakhtunkhwa 62.5 50.8 57.1 0.81 95.1 75.2 85.9 0.79 Balochistan 44.2 38.6 41.6 0.87 77.9 61.9 70.3 0.79 ICT Islamabad 83.1 77.2 80.0 0.93 112.9 101.1 106.7 0.89 Gilgit Baltistan 57.2 55.4 56.3 0.97 101.2 94.6 98.2 0.93 Wealth quintile Lowest 43.9 26.9 35.8 0.61 74.7 41.5 58.9 0.56 Second 60.1 50.0 55.5 0.83 95.5 80.3 88.6 0.84 Middle 65.3 68.5 66.8 1.05 102.5 103.0 102.7 1.00 Fourth 73.3 72.8 73.1 0.99 106.8 106.7 106.8 1.00 Highest 84.4 78.8 81.6 0.93 120.9 104.2 112.5 0.86 Total 62.9 56.5 59.9 0.90 97.3 83.5 90.8 0.86 MIDDLE/SECONDARY SCHOOL Residence Urban 49.5 50.7 50.1 1.03 73.0 74.1 73.5 1.01 Rural 35.3 26.1 31.0 0.74 55.7 39.5 48.1 0.71 Region Punjab 42.0 39.8 41.0 0.95 61.4 58.2 59.9 0.95 Sindh 32.6 25.7 29.3 0.79 52.6 40.2 46.7 0.76 Khyber Pakhtunkhwa 46.6 31.0 39.4 0.66 73.9 44.3 60.1 0.60 Balochistan 22.8 15.9 19.5 0.70 48.6 28.1 38.9 0.58 ICT Islamabad 63.6 67.8 65.6 1.07 92.7 89.7 91.3 0.97 Gilgit Baltistan 37.4 35.8 36.6 0.96 82.6 69.1 76.0 0.84 Wealth quintile Lowest 13.4 5.0 9.5 0.37 26.2 8.2 17.8 0.31 Second 34.6 19.0 27.2 0.55 54.1 27.8 41.8 0.51 Middle 39.8 37.7 38.8 0.95 64.6 57.7 61.4 0.89 Fourth 51.3 49.2 50.3 0.96 76.3 70.4 73.4 0.92 Highest 64.7 66.4 65.5 1.03 90.5 99.5 94.7 1.10 Total 39.7 34.0 37.0 0.86 61.0 50.6 56.1 0.83 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 secondary school is the percentage of the secondary school age (10-14 years) population that is attending secondary school. By definition, the NAR cannot exceed 100 percent. 2 The GAR for primary school is the total number of primary school students expressed as a percentage of the official primary school age population. The GAR for secondary school is the total number of secondary school students expressed as a percentage of the official secondary school age population. If there are significant numbers of over-age and under-age students at a given level of schooling, the GAR can exceed 100 percent. 3 The GPI for primary school is the ratio of the primary school NAR (GAR) for females to the NAR (GAR) for males. The GPI for secondary school is the ratio of the secondary school NAR (GAR) for females to the NAR (GAR) for males. Figure 2.2 shows attendance rates for the de facto population age 5-24. The age-specific pattern clearly shows that school attendance is highest among those age 7-16, with males having an edge over females. 28 • Housing Characteristics and Household Population Figure 2.2 Age-specific attendance rates Table 2.16 shows the percent distribution of the de facto population age 5-24 by reason for dropping out of school, according to sex and place of residence. The major reasons for males dropping out of school are “not interested in studies” (33 percent), “need to work to earn” (28 percent), and high costs (16 percent). Among females, major reasons are high costs (19 percent), “not interested in studies” (17 percent), “got married” (12 percent), and “school too far” (10 percent). The latter reason was reported in particular by females in rural areas. In addition, 13 percent of females dropped out of school because they believed that further education was not necessary. Table 2.16 Reasons for children dropping out of school Percent distribution of de facto household members age 5-24 years who dropped out of school by the main reason for not attending school, according to sex and residence, Pakistan 2012-13 Main reason Residence Total Urban Rural Male Female Male Female Male Female Reasons for not attending school School too far 0.1 2.3 2.4 14.5 1.6 10.2 Transport not available 0.0 0.4 0.8 1.4 0.6 1.0 Further education not necessary 5.1 16.1 2.5 11.2 3.4 12.9 Required for household/farm work 2.4 6.3 6.7 6.5 5.2 6.4 Got married 0.9 15.9 0.3 9.4 0.5 11.7 Costs too much 13.5 19.9 16.5 18.9 15.5 19.2 Not interested in studies 29.4 15.5 34.7 18.4 32.9 17.4 Repeated failure 0.6 0.7 1.5 0.4 1.2 0.5 Did not get admission 1.3 1.6 0.8 0.6 1.0 1.0 Not safe 0.4 1.7 0.2 3.7 0.3 3.0 Need to work to earn 35.4 5.2 24.6 2.0 28.3 3.1 Other 8.5 11.8 7.3 10.8 7.8 11.1 Don’t know/missing 2.2 2.5 1.6 2.3 1.8 2.4 Total 100.0 100.0 100.0 100.0 100.0 100.0 Number 1,685 1,724 3,247 3,115 4,933 4,839 0 10 20 30 40 50 60 70 80 90 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 Percent Age (years) Male Female PDHS 2012-13 Housing Characteristics and Household Population • 29 2.10 MIGRATION STATUS The 2012-13 PDHS collected information on in-migration as well as out-migration among individuals who had lived in the interviewed households in the past 10 years but had since moved to another area. In view of emerging trends in migratory movements within Pakistan, questions on the status of in-migrants and out-migrants were included for the first time to assess the magnitude and characteristics of the migrant population. This provided an opportunity to capture the latest migration status of household members, thereby filling an information gap caused by the lack of availability of recent census data on the issue. Migrants are people who move from their place of birth to another area or change their place of residence for a specific reason. Migration, which may be seasonal, temporary, semi-permanent, or permanent, is an important demographic element that has far-reaching socioeconomic implications for both individuals and society, both in the place of origin and in the destination. Migration is usually related to opportunities for education and employment that motivate people to out-migrate from their place of origin and culture and to geographic hardships that push people to move to a better or safer environment. The 2012-13 PDHS collected information on usual members of the household who migrated elsewhere in the 10 years prior to the survey. Information was collected according to background characteristics, duration and cause of migration, and place of origin. These data provide an opportunity to measure short-term and lifetime migration. Table 2.17 shows in-migration in the past 10 years among usual members of households. Overall, 4 percent of household members have migrated to their current place of residence in the past 10 years (3 percent of males and 5 percent of females). The highest proportions of lifetime in-migrants are in the 21-30 age group (7 percent), live in urban areas (7 percent), are married (5 percent), have a higher education (5 percent), and are in the highest wealth quintile (5 percent). Among those who have migrated, more have done so for 1-5 years (57 percent) and six or more years (30 percent); only small proportions fall in the category of recent migrants of less than one year in duration (13 percent). Table 2.17 also provides information on the place of origin of the in-migrating population. The majority have migrated from rural areas within Pakistan (56 percent), followed by those migrating from cities and urban areas (43 percent); the proportion of individuals in- migrating from overseas is quite small (1 percent). There are substantial variations in migration flows from urban and rural areas by region and wealth quintile. Overall, 18 percent of households have at least one usual member who has migrated in the 10 years preceding the survey (Table 2.18). Nineteen percent of rural households and 16 percent of urban households had at least one out-migrating member. Out-migration is more prevalent in Gilgit Baltistan (30 percent), Khyber Pakhtunkhwa (28 percent), and Punjab (20 percent). Only 5 percent of households in Balochistan had an out-migrated member in the 10 years before the survey. 30 • Housing Characteristics and Household Population Table 2.17 Status of in-migration in households Among usual members of the household, the percentage of in-migrants in the last 10 years and among those who migrated, the duration of migration and place of origin, by background characteristics, Pakistan 2012-13 Background characteristic Percentage of in- migrants Total1 Duration of migration (years) Place of origin Number of migrants2 <1 1-5 6+ City within Pakistan Rural areas within Pakistan Outside countries Sex Male 2.9 44,175 15.6 55.2 29.2 43.3 55.2 1.5 1,295 Female 4.6 43,542 11.4 58.1 30.6 42.9 56.1 1.0 2,008 Age <10 3.5 23,419 17.6 59.6 22.8 51.3 47.2 1.5 818 10-20 3.3 23,033 16.2 60.6 23.2 34.7 64.2 1.1 753 21-30 7.0 15,082 8.9 56.0 35.2 45.3 54.0 0.7 1,054 31-40 3.9 9,805 8.8 51.6 39.6 43.5 54.8 1.7 382 41-50 2.2 6,384 15.7 45.7 38.6 33.0 66.2 0.8 143 51-60 1.4 5,542 9.8 55.1 35.1 25.9 71.1 3.0 79 61-70 1.6 3,006 12.7 50.8 36.5 38.8 58.3 2.9 47 70+ 1.9 1,443 (6.7) (64.1) (29.1) (45.6) (54.2) (0.2) 27 Marital status Never married 2.4 17,694 11.1 57.1 31.7 43.0 55.7 1.3 428 Married 5.2 32,346 11.3 55.7 32.9 40.8 58.4 0.8 1,671 Divorced/separated 1.3 458 * * * * * * 6 Widowed 2.3 3,022 8.8 46.2 45.0 50.9 46.3 2.9 70 Residence Urban 6.5 28,773 11.2 56.4 32.4 50.3 48.2 1.5 1,877 Rural 2.4 58,944 15.4 57.8 26.9 33.5 65.6 0.8 1,426 Region Punjab 4.1 48,879 13.7 55.7 30.7 45.4 54.2 0.4 2,008 Sindh 3.5 20,990 7.9 55.0 37.1 51.5 46.1 2.4 728 Khyber Pakhtunkhwa 3.4 12,606 18.0 67.5 14.5 17.2 80.8 2.0 426 Balochistan 1.1 4,112 13.8 59.2 27.0 51.2 44.3 4.5 45 ICT Islamabad 20.4 428 15.9 50.2 33.9 44.0 51.9 4.1 87 Gilgit Baltistan 1.2 702 14.7 61.6 23.7 20.1 79.9 0.0 8 Education No education 3.3 44,835 16.1 61.6 22.3 39.2 59.3 1.5 1,467 Primary 3.8 18,179 11.4 48.3 40.3 38.5 60.9 0.7 698 Middle 4.0 9,069 10.4 54.6 35.0 39.1 60.4 0.5 360 Secondary 4.6 8,048 10.0 57.7 32.4 56.8 42.4 0.8 371 Higher 5.4 7,427 9.8 56.6 33.5 56.1 41.8 2.0 405 Wealth quintile Lowest 1.6 17,552 23.7 48.8 27.5 24.4 75.6 0.1 287 Second 2.9 17,549 16.1 61.9 22.0 25.3 74.5 0.1 506 Middle 3.5 17,536 15.6 53.1 31.2 37.4 60.9 1.7 619 Fourth 5.6 17,540 10.6 59.7 29.6 47.3 50.9 1.7 985 Highest 5.2 17,539 8.8 56.4 34.8 58.0 40.7 1.3 907 Total 3.8 87,717 13.0 57.0 30.0 43.1 55.7 1.2 3,303 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 Includes 4 cases with missing information on age 2 Includes 2 cases with missing information on marital status and 2 cases with missing information on educational status. Table 2.18 Households with out-migration Percentage of households with at least one out-migrant in the last 10 years, by background characteristics, Pakistan 2012-13 Background characteristic Percentage of households with out-migration Number of households Residence Urban 15.5 4,383 Rural 18.9 8,560 Region Punjab 20.0 7,614 Sindh 8.3 3,004 Khyber Pakhtunkhwa 27.7 1,711 Balochistan 4.6 450 ICT Islamabad 16.5 72 Gilgit Baltistan 30.2 91 Total 17.8 12,943 Housing Characteristics and Household Population • 31 Table 2.19 shows the percentage of out-migrants in the last 10 years by duration of migration and place of destination, according to background characteristics. The largest percentage of out-migration is of 1-5 years in duration (58 percent), followed by six or more years (22 percent) and less than one year (20 percent). These results indicate that one-fifth of out-migration has occurred in the last year, and males outnumber females in this category. Among regions, recent out-migration is more evident in Khyber Pakhtunkhwa and Punjab, although 55 to 64 percent of out-migrants in all regions moved in the past 1-5 years. Table 2.19 also shows that 10 percent of males and 35 percent of females moved to a rural destination, probably, in the case of females, as a result of marriage. In contrast, 33 percent of males out- migrated to another country, as compared with only 10 percent of females. A higher proportion of urban than rural migrants relocate to other countries (29 percent versus 24 percent). This reinforces the fact that men migrate mostly for work opportunities, while women primarily out-migrate due to marriage. Among regions, the percentages of residents migrating to outside countries are the highest in Khyber Pakhtunkhwa (34 percent) and ICT Islamabad (42 percent) and the lowest in Balochistan (15 percent) and Gilgit Baltistan (5 percent). Table 2.19 Status of out-migration Among usual members of the household, the percentage of out-migrants in the last 10 years and among those who migrated, the time since migration and place of destination, by background characteristics, Pakistan 2012-13 Background characteristic Time since out-migration (years) Place of destination Number of out-migrants<1 1-5 6+ City within Pakistan Rural areas within Pakistan Outside countries Sex Male 24.2 57.2 18.5 56.4 10.2 33.3 2,363 Female 12.1 59.7 28.2 55.5 34.7 9.7 1,170 Age at migration <15 16.8 66.9 16.4 56.3 30.0 13.7 341 15-19 14.8 61.6 23.6 66.7 23.4 9.6 731 20-24 20.2 52.6 27.2 52.2 21.6 26.2 994 25-29 21.8 59.1 19.0 48.8 13.1 38.2 647 30-34 22.7 57.8 19.5 56.0 9.0 35.0 310 35-39 28.1 58.8 13.1 50.1 9.3 40.6 194 40-44 32.5 49.6 17.9 58.3 6.5 35.3 124 45-49 14.0 78.5 7.6 52.9 8.3 37.5 68 50+ 35.6 54.2 10.3 64.0 11.8 24.1 81 Missing * * * * * * 42 Residence Urban 15.7 61.3 23.0 49.1 22.3 28.5 1,016 Rural 22.0 56.8 21.2 59.0 16.7 24.3 2,517 Region Punjab 20.7 56.9 22.4 56.6 19.1 24.2 2,321 Sindh 8.5 60.4 31.2 49.5 29.0 21.5 413 Khyber Pakhtunkhwa 26.6 59.9 13.5 56.3 9.7 33.9 689 Balochistan 4.2 63.6 32.2 66.7 17.9 15.4 40 ICT Islamabad 19.2 55.0 25.8 38.7 19.5 41.5 18 Gilgit Baltistan 19.9 62.4 17.7 82.3 12.4 5.3 51 Wealth quintile Lowest 23.9 52.4 23.7 61.8 22.9 15.3 384 Second 25.8 51.7 22.5 62.4 21.3 16.2 704 Middle 19.4 61.7 18.8 68.5 13.3 18.2 824 Fourth 20.1 58.3 21.6 54.8 18.3 26.8 776 Highest 14.8 62.1 23.1 37.5 18.6 43.9 845 Total 20.2 58.1 21.7 56.1 18.3 25.5 3,533 Note: An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. Table 2.20 shows the percentage of migrants according to reasons for both in-migration and out- migration, by sex and urban-rural residence. The most common reason for male out-migration appears to be better economic opportunities (69 percent), followed by job transfer (8 percent) and educational pursuits (8 percent). Female out-migration is mainly due to marriage (66 percent), accompanying or joining family members (22 percent), and educational pursuits (6 percent). 32 • Housing Characteristics and Household Population On the contrary, better economic opportunities are less likely to be reported as a reason for in- migration to one’s current location, since people more often migrated to their current area of residence to accompany or join family members. Table 2.20 Reasons for migration Percent distribution of migrants by reasons for migration, according to background characteristics, Pakistan 2012-13 Reasons for migration In-migration Out-migration Residence Sex Total in- migrants Residence Sex Total out- migrants Urban Rural Male Female Urban Rural Male Female Better economic opportunities 13.1 7.6 25.3 1.3 10.7 28.4 54.6 69.1 2.6 47.1 Accumulate savings 0.0 0.3 0.3 0.0 0.1 0.7 5.0 5.7 0.0 3.8 Transferred 1.3 0.0 1.7 0.1 0.8 4.3 6.3 8.4 0.3 5.7 Schooling 4.8 0.4 4.5 1.8 2.9 10.6 5.6 7.5 6.0 7.0 Better infrastructure 1.2 0.3 1.5 0.4 0.8 0.3 0.3 0.3 0.2 0.3 Accompany family 38.6 34.8 40.0 35.0 37.0 9.5 7.0 4.0 15.3 7.7 Join family 6.6 8.8 8.7 6.8 7.5 4.1 3.6 2.3 6.6 3.7 Escape drought/flood 0.1 0.0 0.0 0.0 0.0 0.0 0.3 0.1 0.5 0.2 Escape war/ violence 2.0 2.4 3.3 1.5 2.2 0.0 0.3 0.2 0.2 0.2 Escape other natural disaster 0.2 0.0 0.3 0.0 0.1 0.0 0.0 0.0 0.0 0.0 Marriage 23.6 34.5 0.8 46.0 28.3 40.3 15.3 0.8 66.4 22.5 Since childhood 0.0 0.3 0.2 0.1 0.2 0.0 0.1 0.1 0.0 0.1 Other 8.2 10.4 13.1 6.6 9.2 1.8 1.6 1.5 1.9 1.6 Don’t know/missing 0.4 0.0 0.2 0.2 0.2 0.0 0.0 0.0 0.0 0.0 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Number 1,877 1,426 1,295 2,008 3,303 1,016 2,517 2,363 1,170 3,533 2.11 HOUSEHOLD POSSESSION OF MOSQUITO NETS Since 1954, USAID has promoted malaria control programs through the Insect Borne Disease Control Program. The malaria eradication program, launched in 1958, reverted to a malaria control program in 1978. In 1993, the World Health Organization initiated the Global Malaria Control Strategy to focus on problem areas (WHO, 2010). Pakistan became a member of the global Roll Back Malaria partnership in 1999, and a project through the partnership was launched in 2001. Pakistan’s government is committed to the control and prevention of malaria. The Pakistan Health Policy of 2001 laid down strategies for combating malaria through early diagnosis and prompt treatment, multiple preventive interventions, communication regarding behavior change, improved detection of and response to epidemics, and development of viable partnerships with national and international organizations (Ministry of Health, 2001). An important strategy in the control of malaria is prevention through indoor residual spraying and use of long-lasting insecticide-treated bed nets (LLINs). This strategy has been implemented through the promotion of personal protection measures, including the use of simple mosquito nets and LLINs. The government of Pakistan recognizes children below age 5 as a high-risk group and recommends that they be protected through sleeping under insecticide-treated nets (ITNs). After the devolution of the Ministry of Health to the provinces and regions in 2010, all efforts to control malaria, including the provision of ITNs, are in the domain of the provinces/regions. The 2012-13 PDHS collected information on the possession and number of mosquito nets in households. Evidence indicates that use of mosquito nets is not common in Pakistan. Table 2.21 shows that about 13 percent of households possess a mosquito net. Only 1 percent of households possess at least one ITN, and the average number of mosquito nets per household is less than one. The availability of mosquito nets is higher in rural areas (15 percent) than in urban areas (11 percent). In addition, mosquito nets are more common in Sindh (22 percent), Balochistan (16 percent), and Khyber Pakhtunkhwa (13 percent) and among households in the lowest wealth quintile (16 percent). ITNs are virtually nonexistent in Pakistan except in Balochistan, where around 3 percent of households have treated nets. Housing Characteristics and Household Population • 33 Table 2.21 Household possession of mosquito nets Percentage of households with at least one mosquito net (treated or untreated) or insecticide-treated net and average number of nets (treated or untreated), by background characteristics, Pakistan 2012-13 Background characteristic Percentage of households with at least one mosquito net Average number of nets per household Number of households Any mosquito net Insecticide- treated mosquito net Any mosquito net Residence Urban 10.5 1.2 0.2 4,383 Rural 14.9 0.9 0.3 8,560 Region Punjab 10.2 0.6 0.2 7,614 Sindh 21.7 1.3 0.5 3,004 Khyber Pakhtunkhwa 13.4 1.5 0.3 1,711 Balochistan 16.4 2.5 0.4 450 ICT Islamabad 6.5 0.7 0.1 72 Gilgit Baltistan 1.2 0.1 0.0 91 Wealth quintile Lowest 15.9 0.5 0.3 2,558 Second 10.2 0.7 0.2 2,601 Middle 14.1 1.1 0.3 2,609 Fourth 15.4 0.9 0.3 2,557 Highest 11.5 1.7 0.2 2,618 Total 13.4 1.0 0.3 12,943 2.12 INDOOR RESIDUAL SPRAYING AGAINST MOSQUITOES Indoor residual spraying (IRS) is considered an effective method of malaria prevention. The insecticides kill mosquitoes for several months, especially in endemic areas. Pakistan is committed to increasing the use of this intervention, although its cost remains a challenge. The 2012-13 PDHS collected information on whether the interior walls of the household’s dwelling had been sprayed in the 12 months preceding the survey and, if so, who sprayed the dwelling. Table 2.22 shows the percentage of households with IRS in the past 12 months and the source of provider, by selected background characteristics. The data show that only 5 percent of households in Pakistan were sprayed in the 12 months preceding the survey. Urban households are three times more likely to have been sprayed than rural households (9 percent and 3 percent, respectively). Regional variations further show that Punjab has the highest proportion of sprayed households (7 percent) followed by ICT Islamabad (4 percent) and Khyber Pakhtunkhwa (3 percent), while in the other regions less than 3 percent of households have been sprayed. These data also indicate that government workers/programs are the major provider (79 percent), as opposed to private companies (12 percent), NGOs (3 percent), and others (2 percent). This is mainly because of the intensive IRS interventions carried out every six months in malaria-endemic regions. Households in the highest wealth quintile are much more likely to have been sprayed within the past 12 months (11 percent) than their counterparts in the lowest three quintiles (less than 5 percent). 34 • Housing Characteristics and Household Population Table 2.22 Indoor residual spraying against mosquitoes Percentage of households in which someone has come into the dwelling to spray the interior walls against mosquitoes (IRS) in the past 12 months, and among households with IRS, the source of provider, by background characteristics, Pakistan 2012-13 Background characteristic Percentage of households with IRS in the past 12 months Number of households Source among households with IRS Government worker/ program Private company NGO Other Don’t know Number of households Residence Urban 9.3 4,383 78.7 17.0 2.2 1.3 4.2 407 Rural 3.2 8,560 80.2 5.1 3.9 2.6 7.7 274 Region Punjab 7.0 7,614 82.7 12.6 1.5 1.3 4.4 536 Sindh 2.7 3,004 75.6 4.9 7.6 0.0 11.8 80 Khyber Pakhtunkhwa 3.0 1,711 62.7 17.0 5.4 9.0 5.3 52 Balochistan 2.4 450 (19.6) (24.5) (25.0) (7.7) (21.7) 11 ICT Islamabad 3.7 72 (85.0) (5.8) (0.0) (7.5) (1.7) 3 Gilgit Baltistan 0.0 91 na na na na na na Wealth quintile Lowest 2.8 2,558 (94.3) (0.0) (2.5) (0.0) (3.1) 73 Second 3.7 2,601 78.0 8.3 4.6 0.0 9.2 95 Middle 3.8 2,609 85.3 3.1 2.5 3.3 7.9 99 Fourth 5.0 2,557 78.4 11.4 4.7 1.5 3.7 129 Highest 10.9 2,618 74.3 20.1 1.7 2.6 5.2 286 Total 5.3 12,943 79.3 12.2 2.9 1.9 5.6 681 Note: Figures in parentheses are based on 25-49 unweighted cases. na = Not applicable 2.13 ANTI-MOSQUITO ACTIONS Use of bed nets is not the only action that Pakistani households take to avoid mosquitoes and their harmful effects. In the 2012-13 PDHS, interviewers inquired about other actions households might have taken to avoid mosquitoes. Table 2.23 shows specific devices or repellents used to avoid mosquitoes by background characteristics. These data indicate that, overall, 30 percent of households are not using any device or repellent to avoid mosquitoes. Among others, about 32 percent of households use coils, 18 percent use mats, 16 percent use smoke, 15 percent use insect repellent, 10 percent use any kind of spray, and 2 percent use electric spray repellents. The most common devices used in urban areas are coils (50 percent), mats (27 percent), sprays (20 percent), and insect repellents (16 percent). On the other hand, smoke and coils are more common (22 percent each) in rural areas, followed by mats and insect repellents (14 percent each) and sprays (5 percent). A large proportion of households not using any anti-mosquito devices are in rural areas (37 percent). Among regions, Gilgit Baltistan has the most households not using any protective device (85 percent), followed by Khyber Pakhtunkhwa (41 percent), Balochistan (40 percent), Punjab (30 percent), and Sindh (22 percent). Households in the higher wealth quintiles are more likely than those in the lower quintiles to use mosquito repellents. Housing Characteristics and Household Population • 35 Table 2.23 Other anti-mosquito actions Percentage of households using specific devices or repellents to avoid mosquitoes, by background characteristics, Pakistan 2012-13 Background characteristic Device or repellent None Coil Mats Spray Electric spray repellent Insect repellent Smoke Other1 Number of households Residence Urban 16.6 50.1 26.5 20.2 4.9 16.1 3.3 4.0 4,383 Rural 37.3 22.0 14.0 5.1 0.8 14.5 22.5 4.6 8,560 Region Punjab 30.1 30.0 22.4 10.5 2.6 20.0 12.3 3.9 7,614 Sindh 21.9 42.9 14.2 11.0 1.8 3.9 23.3 4.7 3,004 Khyber Pakhtunkhwa 41.3 18.8 9.9 8.0 0.9 16.2 19.5 5.2 1,711 Balochistan 39.6 31.0 6.4 5.4 1.8 4.1 21.6 6.8 450 ICT Islamabad 9.8 52.0 30.5 34.5 8.9 15.8 3.2 8.1 72 Gilgit Baltistan 84.6 3.6 3.3 9.2 0.2 0.4 2.2 0.4 91 Wealth quintile Lowest 46.3 7.4 2.6 0.3 0.0 4.8 41.2 5.3 2,558 Second 43.8 22.1 10.5 1.3 0.3 10.2 22.4 4.0 2,601 Middle 31.0 35.9 18.6 5.9 0.8 17.8 11.1 4.2 2,609 Fourth 21.0 45.6 28.3 10.8 2.1 20.2 4.4 2.8 2,557 Highest 9.5 46.3 31.0 32.4 7.7 22.1 1.1 5.5 2,618 Total 30.3 31.5 18.2 10.2 2.2 15.1 16.0 4.4 12,943 1 Includes infrared electric device, membrane, and other methods Characteristics of respondents • 37 CHARACTERISTICS OF RESPONDENTS 3 his chapter presents a demographic and socioeconomic profile of ever-married women and men age 15-49 interviewed in the 2012-13 PDHS. Information on basic characteristics such as age, marital status, education, literacy, employment status, and wealth status is important for a better understanding of the various demographic and health indicators presented in this report. Information is also presented on exposure to mass media, occupation, type of earnings, use of tobacco, and knowledge and attitudes concerning tuberculosis and hepatitis. The 2012-13 PDHS includes results from completed interviews with 13,558 ever-married women and 3,134 ever-married men age 15-49. 3.1 CHARACTERISTICS OF SURVEY RESPONDENTS Basic background characteristics of the interviewed women and men age 15-49 are presented in Table 3.1. Forty percent of women and 25 percent of men are under age 30. The age structure of female respondents remained almost the same in 2012-13 as in the 2006-07 survey. The majority of ever-married women (95 percent) and nearly all ever-married men (98 percent) are currently married. About two-thirds of respondents of both sexes reside in rural areas. Education is an important factor influencing an individual’s knowledge, attitudes, and behavior. Fifty-seven percent of ever-married women and 29 percent of ever-married men age 15-49 have no education, while 20 percent of women and 34 percent of men have completed secondary or higher education. Wealth is another important characteristic that has an impact on the socioeconomic status of the population. Women are almost evenly distributed across the five wealth quintiles, whereas the share of men is slightly higher in the fourth and fifth quintiles than in the three lower quintiles. T Key Findings • Fifty-seven percent of ever-married women and 29 percent of ever-married men age 15-49 have no education. • Television is the most important source of media for women and men in Pakistan, with more than two in five accessing it at least once a week. • About half of women and men have no access to any of the three media sources at least once a week. • Twenty-nine percent of women were employed in the 12 months preceding the survey; 26 percent are currently employed. • Fourteen percent of employed women are not paid for their work, in contrast to less than 1 percent of men. • Four percent each of ever-married women and men age 15-49 have ever been told by a health professional that they had tuberculosis. 38 • Characteristics of respondents Table 3.1 Background characteristics of respondents Percent distribution of ever-married women and men age 15-49 by selected background characteristics, Pakistan 2012-13 Background characteristic Women Men Weighted percent Weighted number Unweighted number Weighted percent Weighted number Unweighted number Age 15-19 4.5 605 567 1.1 36 29 20-24 15.5 2,106 2,048 7.0 219 223 25-29 20.1 2,724 2,723 16.6 521 498 30-34 18.6 2,528 2,438 20.6 646 635 35-39 16.4 2,226 2,300 18.8 588 589 40-44 13.0 1,766 1,808 16.9 530 574 45-49 11.8 1,602 1,674 18.9 594 586 Marital status Married 95.4 12,937 13,010 98.0 3,071 3,085 Divorced/separated 1.7 230 166 1.0 30 18 Widowed 2.9 391 382 1.0 32 31 Residence Urban 33.5 4,536 6,351 35.3 1,107 1,521 Rural 66.5 9,022 7,207 64.7 2,027 1,613 Region Punjab 57.5 7,790 3,800 57.6 1,804 800 Sindh 23.1 3,133 2,941 25.4 796 758 Khyber Pakhtunkhwa 14.1 1,908 2,695 11.1 347 497 Balochistan 4.2 568 1,953 4.8 151 551 ICT Islamabad 0.5 64 953 0.6 18 282 Gilgit Baltistan 0.7 94 1,216 0.6 18 246 Education No education 57.1 7,736 7,625 28.9 905 849 Primary1 15.9 2,156 1,831 20.9 657 536 Middle2 7.3 993 945 16.7 525 423 Secondary3 10.4 1,413 1,470 17.8 557 577 Higher4 9.3 1,260 1,687 15.7 491 749 Wealth quintile Lowest 19.1 2,589 2,486 19.4 607 584 Second 19.7 2,676 2,586 18.3 574 581 Middle 19.9 2,700 2,589 18.1 567 548 Fourth 20.6 2,789 2,657 22.7 713 641 Highest 20.7 2,804 3,240 21.5 673 780 Total 15-49 100.0 13,558 13,558 100.0 3,134 3,134 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. 3.2 EDUCATIONAL ATTAINMENT The educational attainment of a population is an important indicator of the society’s stock of human capital and level of socioeconomic development. Education enhances the ability of individuals to achieve desired demographic and health goals. Tables 3.2.1 and 3.2.2 present differentials in the educational attainment of ever-married women and men by selected background characteristics. Table 3.2.1 shows that 57 percent of ever-married women age 15-49 have never attended school, 16 percent have attended primary school, 7 percent have attended middle school, 10 percent have some secondary education (class 9-10), and 9 percent have reached class 11 or higher. Younger women are more likely than older women to have attended school; about half of those under age 30 have never been to school, while the proportion increases from 55 percent to 72 percent in subsequent age groups. Almost twice as many women age 25-29 as women age 45-49 have a secondary or higher education (24 percent and 13 percent, respectively). Characteristics of respondents • 39 Urban women are far more likely to be educated than rural women. Only 32 percent of ever-married urban women have never been to school, as compared with 70 percent of rural women. On the other hand, 39 percent of urban women have at least some secondary education, as compared with only 10 percent of rural women. Women in the urban areas of Pakistan have a median of 5.4 years of schooling, whereas rural women have a median of zero years. Among the regions, Balochistan has the largest percentage of women who have never attended school (85 percent), followed by Khyber Pakhtunkhwa (72 percent), Gilgit Baltistan (68 percent), Sindh (58 percent), Punjab (51 percent), and ICT Islamabad (16 percent). Fifty-nine percent of ever- married women in ICT Islamabad have a secondary or higher education, as compared with 24 percent of those in Sindh, 20 percent in Punjab, 17 percent in Gilgit Baltistan, 12 percent in Khyber Pakhtunkhwa, and 7 percent in Balochistan. Women in ICT Islamabad have a median of 9.5 years of schooling. Women in the highest wealth quintile are more likely than women in the other wealth quintiles to have a secondary or higher education; 59 percent of women in the highest wealth quintile reached this level, as compared with only 1 percent of those in the lowest quintile. The median number of years of schooling is 9.3 for women in the highest wealth quintile and 4.2 for those in the fourth quintile. Table 3.2.1 Educational attainment: Women Percent distribution of ever-married women age 15-49 by highest level of schooling attended and median years completed, according to background characteristics, Pakistan 2012-13 Background characteristic Highest level of schooling Total Median years completed Number of women No education Primary1 Middle2 Secondary3 Higher4 Age 15-24 49.3 20.4 10.4 12.2 7.6 100.0 0.8 2,711 15-19 53.5 21.7 11.4 8.6 4.6 100.0 0.0 605 20-24 48.1 20.1 10.1 13.3 8.5 100.0 2.0 2,106 25-29 47.8 18.1 10.0 12.3 11.8 100.0 2.0 2,724 30-34 54.8 15.4 6.6 11.3 11.9 100.0 0.0 2,528 35-39 62.3 12.4 5.8 10.6 9.0 100.0 0.0 2,226 40-44 66.4 14.7 4.9 6.5 7.4 100.0 0.0 1,766 45-49 72.0 11.5 3.5 6.9 6.1 100.0 0.0 1,602 Residence Urban 32.1 17.5 11.0 19.5 19.9 100.0 5.4 4,536 Rural 69.6 15.1 5.5 5.9 3.9 100.0 0.0 9,022 Region Punjab 51.1 19.4 9.1 11.8 8.6 100.0 0.0 7,790 Sindh 58.3 12.0 5.3 10.4 13.9 100.0 0.0 3,133 Khyber Pakhtunkhwa 71.9 11.2 4.8 6.3 5.7 100.0 0.0 1,908 Balochistan 84.6 6.0 2.7 4.5 2.2 100.0 0.0 568 ICT Islamabad 16.3 16.2 8.0 18.4 41.0 100.0 9.5 64 Gilgit Baltistan 67.5 8.4 7.2 8.8 8.1 100.0 0.0 94 Wealth quintile Lowest 92.2 6.3 0.9 0.3 0.3 100.0 0.0 2,589 Second 79.6 13.9 3.4 2.3 0.9 100.0 0.0 2,676 Middle 63.5 20.0 7.4 5.7 3.5 100.0 0.0 2,700 Fourth 38.1 24.8 13.1 16.3 7.7 100.0 4.2 2,789 Highest 15.9 13.8 11.3 26.2 32.8 100.0 9.3 2,804 Total 57.1 15.9 7.3 10.4 9.3 100.0 0.0 13,558 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. Table 3.2.2 presents educational attainment among ever-married men age 15-49. It shows that 29 percent of ever-married men have never attended school, while one-third (34 percent) have reached secondary schooling or higher. The proportion of men with no education is highest (39 percent) in the 45- 49 age group, falling to about 25 percent of those under age 40. Forty-three percent of men age 35-39 have a secondary education or higher, the highest proportion of any age group. The median number of years of schooling is 7.5 among men age 35-39 and 7.0 among those age 30-34. The median is below five years in the other age groups with the exception of men age 15-24, among whom it is 5.2 years. 40 • Characteristics of respondents Similar to women, urban men are more likely to be educated than rural men. Eighteen percent of urban ever-married men have never attended school, as compared with 35 percent of rural men. The median number of years of schooling is 7.6 for urban men and 4.5 for rural men. More than half of ever-married men in Balochistan have never been to school, followed by 30 percent each in Sindh and Khyber Pakhtunkhwa, 27 percent in Punjab, 23 percent in Gilgit Baltistan, and 6 percent in ICT Islamabad. Seventy-two percent of ever-married men in ICT Islamabad have at least some secondary education, as compared with only 29 percent of men in Punjab. As expected, wealth is highly related to educational attainment; 60 percent of men in the highest wealth quintile have a secondary or higher education, as compared with only 13 percent of those in the lowest quintile. The proportion of men who have never attended school is high in the lowest wealth quintile and gradually declines in the higher quintiles. The median number of years of schooling is 9.4 among men in the highest wealth quintile, with lower figures in the other quintiles (the median is 0.0 in the lowest quintile). Table 3.2.2 Educational attainment: Men Percent distribution of ever-married men age 15-49 by highest level of schooling attended and median years completed, according to background characteristics, Pakistan 2012-13 Highest level of schooling Total Median years completed Number of men Background characteristic No education Primary1 Middle2 Secondary3 Higher4 Age 15-24 25.8 23.8 25.5 12.9 12.0 100.0 5.2 255 15-19 (29.1) (5.6) (43.2) (13.6) (8.4) 100.0 (7.0) 36 20-24 25.3 26.7 22.6 12.8 12.6 100.0 4.8 219 25-29 27.4 27.9 14.9 17.7 12.2 100.0 4.7 521 30-34 22.7 19.9 18.7 22.0 16.8 100.0 7.0 646 35-39 22.4 16.1 18.4 21.9 21.1 100.0 7.5 588 40-44 34.9 19.1 16.5 13.0 16.6 100.0 4.5 530 45-49 39.3 21.3 11.1 15.5 12.9 100.0 4.2 594 Residence Urban 17.5 20.2 17.3 20.8 24.2 100.0 7.6 1,107 Rural 35.1 21.3 16.5 16.1 11.0 100.0 4.5 2,027 Region Punjab 26.6 23.9 20.9 17.4 11.1 100.0 5.0 1,804 Sindh 30.0 19.5 10.6 17.4 22.4 100.0 5.5 796 Khyber Pakhtunkhwa 30.0 14.4 14.5 20.0 21.0 100.0 6.6 347 Balochistan 51.0 9.4 5.0 17.7 16.8 100.0 0.0 151 ICT Islamabad 6.4 9.0 12.8 21.1 50.6 100.0 10.9 18 Gilgit Baltistan 23.0 19.4 18.4 17.7 21.5 100.0 7.1 18 Wealth quintile Lowest 59.2 19.2 8.4 8.3 4.8 100.0 0.0 607 Second 37.7 25.9 16.1 13.7 6.6 100.0 3.9 574 Middle 28.7 25.3 18.9 16.8 10.3 100.0 4.7 567 Fourth 15.6 21.3 22.3 24.9 15.9 100.0 7.5 713 Highest 8.3 14.3 17.1 22.9 37.5 100.0 9.4 673 Total 15-49 28.9 20.9 16.7 17.8 15.7 100.0 5.1 3,134 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. 3.3 LITERACY Literacy is widely acknowledged as benefiting both individuals and society. It is also associated with a number of positive health and nutrition outcomes. In this survey, literacy status was determined by respondents’ ability to read all or part of a sentence. During data collection, interviewers carried a card on which simple sentences were printed in Urdu or Sindhi to assess respondents’ reading ability. Those who had completed class 9 or higher were not asked to read a sentence. Table 3.3.1 provides results on literacy levels among ever-married women age 15-49. It shows that 43 percent of women are literate, while 56 percent cannot read at all. The literacy rate among ever- Characteristics of respondents • 41 married women in 2012-13 was 8 percentage points higher than the rate reported in the 2007-06 PDHS (35 percent). The results in Table 3.3.1 show that younger women are more likely to be literate than women age 35 and above. Also, urban women are more than twice as likely to be literate as rural women (69 percent and 31 percent, respectively). A regional analysis shows that ICT Islamabad has the highest literacy level among women (81 percent). The literacy level in Punjab is also relatively high (50 percent), with lower levels in Sindh (42 percent), Gilgit Baltistan (36 percent), Khyber Pakhtunkhwa (27 percent), and Balochistan (16 percent). There are wide urban-rural differentials across the provinces. For example, in Sindh, 71 percent of urban women are literate, as compared with only 14 percent of rural women. Rural women in Punjab are more likely to be literate than rural women in other provinces. Literacy levels are strongly related to wealth. For example, only 8 percent of ever-married women age 15-49 in the lowest wealth quintile are literate, as compared with 85 percent of those in the highest quintile. 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 2012-13 Background characteristic Class 9 or higher No schooling or primary school Total Percentage literate1 Number of women Can read a whole sentence Can read part of a sentence Cannot read at all No card with required language Blind/ visually impaired Missing Age 15-24 19.9 24.4 5.1 50.5 0.0 0.0 0.1 100.0 49.4 2,711 15-19 13.3 24.1 5.5 57.0 0.0 0.0 0.2 100.0 42.8 605 20-24 21.8 24.5 5.0 48.6 0.0 0.0 0.1 100.0 51.3 2,106 25-29 24.1 23.9 4.7 47.2 0.0 0.0 0.0 100.0 52.7 2,724 30-34 23.2 17.7 4.9 54.2 0.0 0.0 0.0 100.0 45.7 2,528 35-39 19.6 14.8 4.3 61.2 0.0 0.1 0.0 100.0 38.6 2,226 40-44 14.0 17.4 3.9 64.2 0.0 0.3 0.2 100.0 35.3 1,766 45-49 13.0 13.1 3.2 70.3 0.0 0.2 0.1 100.0 29.4 1,602 Residence Urban 39.4 23.9 5.6 31.0 0.0 0.1 0.0 100.0 68.9 4,536 Rural 9.8 16.9 3.9 69.2 0.0 0.1 0.1 100.0 30.6 9,022 Region Punjab 20.4 24.8 4.7 49.9 0.0 0.1 0.1 100.0 49.9 7,790 Urban 36.9 28.5 5.2 28.3 0.0 0.1 0.1 100.0 71.6 2,526 Rural 12.5 23.1 4.0 60.3 0.0 0.1 0.1 100.0 39.5 5,264 Sindh 24.3 13.6 3.8 58.1 0.0 0.1 0.1 100.0 41.8 3,133 Urban 46.9 19.9 4.4 28.7 0.0 0.1 0.0 100.0 71.2 1,521 Rural 3.1 7.7 3.2 85.9 0.0 0.0 0.1 100.0 14.0 1,612 Khyber Pakhtunkhwa 12.0 10.2 4.6 72.9 0.0 0.1 0.2 100.0 26.8 1,908 Urban 29.4 13.0 6.2 50.9 0.3 0.1 0.0 100.0 48.7 320 Rural 8.5 9.6 4.2 77.4 0.0 0.1 0.2 100.0 22.3 1,588 Balochistan 6.7 5.0 4.0 83.9 0.1 0.0 0.3 100.0 15.7 568 Urban 14.2 10.2 7.3 68.1 0.0 0.0 0.2 100.0 31.7 114 Rural 4.8 3.7 3.1 87.9 0.1 0.0 0.4 100.0 11.7 454 ICT Islamabad 59.5 17.9 4.0 18.1 0.2 0.1 0.3 100.0 81.4 64 Gilgit Baltistan 16.8 10.4 9.0 63.7 0.0 0.0 0.1 100.0 36.2 94 Wealth quintile Lowest 0.7 4.5 2.9 91.9 0.0 0.0 0.1 100.0 8.1 2,589 Second 3.2 12.6 3.9 80.2 0.0 0.0 0.2 100.0 19.6 2,676 Middle 9.1 23.2 5.3 62.1 0.0 0.2 0.1 100.0 37.6 2,700 Fourth 24.0 32.6 6.3 36.8 0.0 0.2 0.1 100.0 62.9 2,789 Highest 59.0 21.9 3.9 15.0 0.0 0.1 0.0 100.0 84.9 2,804 Total 19.7 19.2 4.5 56.4 0.0 0.1 0.1 100.0 43.4 13,558 1 Refers to women who completed class 9 or higher and women who can read a whole sentence or part of a sentence 42 • Characteristics of respondents Table 3.3.2 presents data on the literacy levels of ever-married men age 15-49. The literacy rate is higher among ever-married men than ever-married women. Almost two-thirds (65 percent) of men are literate, as compared with only 43 percent of women. The literacy level is higher among men age 35-39 (74 percent) than among men age 30-34 (70 percent) or 45-49 (57 percent). Urban respondents are more likely to be literate than those in rural areas (76 percent and 60 percent, respectively). ICT Islamabad has the highest literacy rate (95 percent), followed by Gilgit Baltistan (71 percent), Punjab (68 percent), Khyber Pakhtunkhwa (67 percent), Sindh (62 percent), and Balochistan (53 percent). In three of the provinces, at least three-quarters of urban men are literate; in Balochistan, the figure falls to 70 percent. There are considerable differentials in literacy status between women and men by region, with the largest differences in Khyber Pakhtunkhwa and Balochistan (Figure 3.1). Literacy levels increase with increasing wealth quintile, ranging from 37 percent in the lowest quintile to 88 percent in the highest quintile. 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 2012-13 Class 9 or higher No schooling or primary school 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 24.9 32.0 9.7 32.2 0.3 0.9 100.0 66.6 255 15-19 (22.0) (39.3) (16.6) (22.1) (0.0) (0.0) 100.0 (77.9) 36 20-24 25.3 30.9 8.6 33.8 0.4 1.0 100.0 64.8 219 25-29 29.9 26.7 8.4 34.7 0.1 0.3 100.0 64.9 521 30-34 38.8 21.8 9.5 29.5 0.0 0.5 100.0 70.0 646 35-39 43.0 24.6 6.6 25.7 0.0 0.0 100.0 74.3 588 40-44 29.6 21.8 8.2 40.4 0.0 0.0 100.0 59.6 530 45-49 28.3 16.9 11.6 42.5 0.0 0.7 100.0 56.8 594 Residence Urban 45.0 23.2 8.0 23.4 0.0 0.5 100.0 76.1 1,107 Rural 27.1 23.0 9.5 40.1 0.1 0.3 100.0 59.6 2,027 Region Punjab 28.6 31.1 7.8 31.9 0.0 0.6 100.0 67.5 1,804 Urban 36.3 31.5 7.3 24.1 0.0 0.9 100.0 75.1 618 Rural 24.6 30.9 8.1 36.0 0.0 0.5 100.0 63.6 1,186 Sindh 39.9 13.6 7.9 38.5 0.0 0.0 100.0 61.5 796 Urban 56.9 13.4 7.6 22.1 0.0 0.0 100.0 77.9 376 Rural 24.7 13.9 8.2 53.2 0.0 0.0 100.0 46.8 420 Khyber Pakhtunkhwa 41.0 10.2 16.2 32.4 0.2 0.0 100.0 67.4 347 Urban 50.9 11.1 14.2 23.8 0.0 0.0 100.0 76.2 67 Rural 38.7 10.0 16.7 34.4 0.3 0.0 100.0 65.3 281 Balochistan 34.6 7.1 11.1 46.9 0.3 0.0 100.0 52.8 151 Urban 49.2 7.2 13.1 30.5 0.0 0.0 100.0 69.5 32 Rural 30.7 7.0 10.6 51.3 0.4 0.0 100.0 48.3 119 ICT Islamabad 71.7 16.0 6.7 5.5 0.0 0.0 100.0 94.5 18 Gilgit Baltistan 39.2 20.0 12.2 28.4 0.0 0.0 100.0 71.4 18 Wealth quintile Lowest 13.1 14.8 8.5 63.3 0.2 0.0 100.0 36.5 607 Second 20.4 22.2 11.8 45.0 0.0 0.7 100.0 54.3 574 Middle 27.1 25.8 12.8 34.0 0.0 0.3 100.0 65.7 567 Fourth 40.8 30.2 6.4 21.8 0.0 0.8 100.0 77.4 713 Highest 60.4 21.3 6.5 11.9 0.0 0.0 100.0 88.1 673 Total 33.4 23.0 9.0 34.2 0.0 0.3 100.0 65.4 3,134 Note: Figures in parentheses are based on 25-49 unweighted cases. 1 Refers to men who completed class 9 or higher and men who can read a whole sentence or part of a sentence Characteristics of respondents • 43 Figure 3.1 Literacy status of ever-married women and men, by region 50 42 27 16 81 36 68 62 67 53 95 71 Punjab Sindh Khyber Pakhtunkhwa Balochistan ICT Islamabad Gilgit Baltistan Percentage literate Women Men PDHS 2012-13 3.4 ACCESS TO MASS MEDIA Access to information through the media is essential to increase people’s knowledge and awareness of what takes place around them. The 2012-13 PDHS assessed exposure to media by asking respondents if they listened to the radio, watched television, or read newspapers or magazines at least once a week. To plan effective programs to disseminate information about health and family planning, it is important to know which subgroups of the population are most likely to be reached by specific media. Table 3.4.1 presents information on exposure to mass media among ever-married women age 15- 49. It shows that television is by far the most widely accessed medium; 47 percent of women watch television at least once a week, while only 4 percent read a newspaper and 3 percent listen to the radio at least once a week. Less than 1 percent of women are exposed to all three media sources once a week. More than half (51 percent) of women have no exposure to any of the mass media on a weekly basis. Although differences by age group are not large, there is a wide gap in media exposure by urban-rural residence. For example, 8 percent of urban women read a newspaper once a week, as compared with only 2 percent of rural women. Similarly, 71 percent of urban women watch television at least once a week, as compared with 35 percent of rural women. Women living in ICT Islamabad are much more likely than women in other provinces/regions to be exposed to the mass media. In addition, women in Khyber Pakhtunkhwa, Gilgit Baltistan, and Balochistan are less exposed to the media than women in Sindh and Punjab. Media exposure is positively related to educational level and economic status. Regular exposure to mass media is highest among women with a secondary or higher education and those in the highest wealth quintile. 44 • Characteristics of 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, by background characteristics, Pakistan 2012-13 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 1.4 47.0 3.7 0.1 51.2 605 20-24 3.5 47.6 3.4 0.3 50.3 2,106 25-29 4.6 49.0 3.0 0.5 49.4 2,724 30-34 3.8 51.2 2.1 0.2 47.6 2,528 35-39 4.0 45.3 1.9 0.2 53.7 2,226 40-44 4.3 45.4 1.7 0.1 53.4 1,766 45-49 4.3 42.7 2.9 0.3 55.2 1,602 Residence Urban 8.4 71.0 2.9 0.6 27.3 4,536 Rural 1.7 35.3 2.4 0.1 63.2 9,022 Region Punjab 4.0 50.8 2.0 0.2 47.7 7,790 Sindh 4.6 56.1 2.9 0.3 43.0 3,133 Khyber Pakhtunkhwa 3.2 23.9 4.1 0.3 73.5 1,908 Balochistan 1.4 28.1 2.9 0.5 70.8 568 ICT Islamabad 22.0 78.3 7.6 3.0 18.1 64 Gilgit Baltistan 0.8 26.4 1.5 0.2 73.0 94 Education No education 0.0 32.2 2.0 0.0 66.9 7,736 Primary 2.0 55.4 2.2 0.1 43.2 2,156 Middle 4.0 65.5 3.0 0.1 32.5 993 Secondary 10.1 74.5 3.7 0.7 22.5 1,413 Higher 24.7 81.0 5.0 1.9 15.2 1,260 Wealth quintile Lowest 0.3 12.5 1.6 0.0 86.6 2,589 Second 0.4 31.2 1.7 0.0 67.7 2,676 Middle 1.2 47.3 3.1 0.0 50.9 2,700 Fourth 4.0 62.6 2.8 0.4 35.6 2,789 Highest 13.5 79.4 3.6 0.9 18.7 2,804 Total 4.0 47.3 2.6 0.3 51.2 13,558 Table 3.4.2 provides information on exposure to mass media among ever-married men age 15-49. Men are more likely to be exposed to print media than women, perhaps in part due to their higher literacy levels. For example, 17 percent of men read a newspaper at least once a week, as compared with only 4 percent of women. As is true among women, television is the most popular mode of information among men, and their level of exposure is similar to that of women (46 percent). Men are slightly more likely than women to listen to the radio at least once a week (5 percent and 3 percent, respectively). Only 1 percent of ever-married men are exposed to all three types of media. Men in urban areas are more likely to have exposure to media than men in rural areas. Men residing in ICT Islamabad are more likely to be exposed to media than those in other regions. Also, media exposure is higher in Sindh and Balochistan than in other regions. Men with higher levels of education are more likely to be exposed to mass media than those who have less education. Similarly, men in the higher wealth quintiles are more likely to have exposure to media than those in the lower quintiles. Only 18 percent of ever-married men in the highest quintile do not access any of the media at least once a week, as compared with 77 percent of those in the lowest quintile. Characteristics of respondents • 45 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, by background characteristics, Pakistan 2012-13 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 (5.4) (49.6) (9.3) (0.0) (41.1) 36 20-24 10.3 41.2 6.0 1.1 53.8 219 25-29 13.8 45.9 5.8 0.9 48.5 521 30-34 17.5 48.3 2.6 0.6 46.4 646 35-39 21.8 50.2 5.8 1.3 44.2 588 40-44 18.2 47.0 4.0 0.8 46.7 530 45-49 18.0 39.8 7.5 0.9 50.4 594 Residence Urban 27.4 68.2 4.0 1.1 26.8 1,107 Rural 11.7 33.8 5.9 0.8 59.0 2,027 Region Punjab 14.7 46.2 4.5 0.7 48.0 1,804 Sindh 20.7 52.2 6.1 1.3 42.1 796 Khyber Pakhtunkhwa 21.6 28.7 3.3 0.5 61.0 347 Balochistan 16.9 47.6 11.9 1.0 43.1 151 ICT Islamabad 49.2 72.8 11.7 5.3 18.6 18 Gilgit Baltistan 10.5 37.9 7.8 2.3 57.2 18 Education No education 0.7 24.0 5.2 0.0 71.0 905 Primary 9.3 44.3 5.4 0.5 50.1 657 Middle 15.7 51.2 5.5 2.0 44.5 525 Secondary 24.0 52.9 5.6 1.4 37.5 557 Higher 52.4 75.2 4.1 1.3 15.9 491 Wealth quintile Lowest 3.8 13.7 8.0 0.3 77.2 607 Second 9.3 30.4 5.5 1.6 62.7 574 Middle 13.0 43.1 5.3 0.2 49.9 567 Fourth 18.3 58.4 3.5 1.1 36.6 713 Highest 38.7 77.6 4.2 1.2 17.8 673 Total 17.3 46.0 5.2 0.9 47.6 3,134 Note: Figures in parentheses are based on 25-49 unweighted cases. 3.5 EMPLOYMENT Employment is an important source of empowerment of women, especially if it puts them in control of their earnings. Measurement of women’s employment, however, can be difficult because some of the work that women do, especially work on family farms, in family businesses, or in the informal sector, is often not perceived by women themselves as employment and hence is not reported. To avoid underreporting women’s employment, interviewers in the PDHS asked women several questions to probe for their employment status and to ensure complete coverage of employment in both the formal and informal sectors. Respondents were asked a number of questions to elicit their current employment status and continuity of employment in the 12 months prior to the survey. Information was also obtained on the type of work women were doing, whether they worked throughout the year, types of employers, and the form in which they received their earnings (in cash or in-kind). Table 3.5.1 presents results on the employment status of ever-married women age 15-49. At the time of the survey, 26 percent of women were currently employed (Figure 3.2). Three percent were not currently working but had been employed in the 12 months prior to the survey, while 71 percent had not been employed in the previous 12 months. The proportion of women who were currently employed was lowest (19 percent) among those age 15-19 and increased to a peak of 33 percent in the 35-39 age group. Women who were divorced, separated, or widowed were much more likely than currently married women to be employed. Similarly, women with three or more children were more likely to be employed than those with fewer children. 46 • Characteristics of respondents Table 3.5.1 Employment status: Women Percent distribution of ever-married women age 15-49 by employment status, according to background characteristics, Pakistan 2012-13 Background characteristic Employed in the 12 months preceding the survey Not employed in the 12 months preceding the survey Missing/ don’t know Total Number of women Currently employed1 Not currently employed Age 15-19 19.4 5.3 75.4 0.0 100.0 605 20-24 19.5 3.5 77.0 0.1 100.0 2,106 25-29 25.1 3.8 71.1 0.0 100.0 2,724 30-34 26.7 2.6 70.5 0.2 100.0 2,528 35-39 33.0 1.8 65.0 0.2 100.0 2,226 40-44 29.8 2.3 67.9 0.0 100.0 1,766 45-49 26.3 1.8 71.9 0.0 100.0 1,602 Marital status Married 25.7 2.8 71.4 0.1 100.0 12,937 Divorced/separated/ widowed 38.8 3.5 57.7 0.0 100.0 621 Number of living children 0 23.2 4.2 72.6 0.0 100.0 1,828 1-2 22.0 2.7 75.3 0.0 100.0 4,059 3-4 27.3 2.4 70.1 0.2 100.0 3,912 5+ 31.5 2.7 65.7 0.1 100.0 3,760 Residence Urban 18.5 1.9 79.3 0.3 100.0 4,536 Rural 30.2 3.3 66.5 0.0 100.0 9,022 Region Punjab 30.7 2.6 66.7 0.1 100.0 7,790 Sindh 30.1 5.2 64.5 0.2 100.0 3,133 Khyber Pakhtunkhwa 6.6 0.6 92.8 0.0 100.0 1,908 Balochistan 16.7 1.0 82.3 0.0 100.0 568 ICT Islamabad 17.6 2.1 79.6 0.7 100.0 64 Gilgit Baltistan 4.3 0.1 95.5 0.1 100.0 94 Education No education 32.8 3.4 63.8 0.0 100.0 7,736 Primary 21.3 3.2 75.4 0.0 100.0 2,156 Middle 14.5 2.1 83.3 0.1 100.0 993 Secondary 11.6 1.4 86.8 0.2 100.0 1,413 Higher 20.5 1.2 77.8 0.5 100.0 1,260 Wealth quintile Lowest 46.5 4.5 49.0 0.0 100.0 2,589 Second 31.2 4.2 64.7 0.0 100.0 2,676 Middle 24.3 2.6 73.0 0.0 100.0 2,700 Fourth 18.3 2.1 79.6 0.1 100.0 2,789 Highest 13.0 1.0 85.7 0.3 100.0 2,804 Total 26.3 2.8 70.8 0.1 100.0 13,558 1 “Currently employed” is defined as having done work in the past 7 days. Includes persons who did not work in the past 7 days but who are regularly employed and were absent from work for leave, illness, vacation, or any other such reason. Characteristics of respondents • 47 Figure 3.2 Women’s employment status in the past 12 months Currently employed 26% Not currently employed, but worked in last 12 months 3% Did not work in last 12 months 71% PDHS 2012-13 Pakistan has an agro-based economy; therefore, rural women are more likely to be employed than urban women (30 percent versus 19 percent). Substantial variations are found across regions. The proportion of women who are currently employed ranges from 4 percent in Gilgit Baltistan to 31 percent in Punjab. The proportion of women who are currently employed decreases with increasing education, with the exception of women with a higher education; 33 percent of women with no education are employed, as compared with 12 percent of women who have a secondary education. Women in the lowest wealth quintile are more likely to be currently employed (47 percent) than women in other quintiles. The proportion of currently employed women gradually decreases with increasing wealth quintile. Table 3.5.2 presents results on the employment status of ever-married men age 15-49. Ninety-six percent of men reported that they are currently employed. There are only small variations in the employment status of men by background characteristics, with the exception of the low level in Gilgit Baltistan (76 percent). 48 • Characteristics of respondents Table 3.5.2 Employment status: Men Percent distribution of ever-married men age 15-49 by employment status, according to background characteristics, Pakistan 2012-13 Employed in the 12 months preceding the survey Not employed in the 12 months preceding the survey Missing/ don’t know Total Number of men Background characteristic Currently employed1 Not currently employed Age 15-19 (80.7) (15.8) (3.6) (0.0) 100.0 36 20-24 90.1 3.3 6.5 0.1 100.0 219 25-29 95.8 2.0 2.2 0.0 100.0 521 30-34 97.0 2.2 0.8 0.0 100.0 646 35-39 96.9 2.1 1.0 0.0 100.0 588 40-44 96.8 1.0 2.2 0.0 100.0 530 45-49 94.8 2.8 2.4 0.0 100.0 594 Marital status Married 95.7 2.3 2.0 0.0 100.0 3,071 Divorced/separated/ widowed (93.8) (1.8) (4.4) (0.0) 100.0 63 Number of living children 0 93.1 4.0 2.8 0.1 100.0 481 1-2 95.2 2.1 2.6 0.0 100.0 918 3-4 97.0 2.2 0.8 0.0 100.0 936 5+ 96.1 1.5 2.4 0.0 100.0 798 Residence Urban 97.3 1.5 1.2 0.0 100.0 1,107 Rural 94.8 2.7 2.5 0.0 100.0 2,027 Region Punjab 96.4 2.4 1.2 0.0 100.0 1,804 Sindh 96.8 1.5 1.7 0.0 100.0 796 Khyber Pakhtunkhwa 91.1 1.9 7.0 0.0 100.0 347 Balochistan 93.9 4.4 1.5 0.2 100.0 151 ICT Islamabad 95.2 1.6 3.2 0.0 100.0 18 Gilgit Baltistan 75.8 12.9 11.3 0.0 100.0 18 Education No education 96.4 1.8 1.8 0.0 100.0 905 Primary 96.5 2.1 1.5 0.0 100.0 657 Middle 95.0 3.2 1.8 0.0 100.0 525 Secondary 95.6 2.6 1.8 0.0 100.0 557 Higher 93.8 2.2 4.0 0.0 100.0 491 Wealth quintile Lowest 95.4 3.2 1.3 0.0 100.0 607 Second 92.6 2.9 4.5 0.0 100.0 574 Middle 95.3 3.4 1.2 0.1 100.0 567 Fourth 96.0 2.0 2.1 0.0 100.0 713 Highest 98.4 0.2 1.3 0.0 100.0 673 Total 95.7 2.3 2.1 0.0 100.0 3,134 Note: Figures in parentheses are based on 25-49 unweighted cases. 1 “Currently employed” is defined as having done work in the past 7 days. Includes persons who did not work in the past 7 days but who are regularly employed and were absent from work for leave, illness, vacation, or any other such reason. 3.6 OCCUPATION Respondents who worked in the 12 months preceding the survey were further asked about their occupations. Table 3.6.1 presents the distribution of ever-married women by occupation according to background characteristics. Thirty-seven percent of employed women are engaged in an agricultural occupation. The next most common occupation is sales and services (26 percent), followed by unskilled manual work (20 percent). Only 8 percent of employed women are working in professional, technical, or managerial occupations; 6 percent are skilled manual workers; and 4 percent work in domestic service. There has been a shift in the occupational distribution of employed women since the 2006-07 PDHS. Characteristics of respondents • 49 Table 3.6.1 Occupation: Women Percent distribution of ever-married women age 15-49 employed in the 12 months preceding the survey by occupation, according to background characteristics, Pakistan 2012-13 Background characteristic Professional/ technical/ managerial Clerical Sales and services Skilled manual Unskilled manual Domestic service Agriculture Missing Total Number of women Age 15-19 3.4 0.0 18.5 9.2 12.4 0.3 56.2 0.0 100.0 149 20-24 3.3 0.0 26.2 7.0 20.6 0.6 42.2 0.1 100.0 484 25-29 8.2 0.3 31.5 6.7 18.5 2.2 32.5 0.0 100.0 787 30-34 8.1 0.2 27.0 3.7 19.1 3.3 37.9 0.8 100.0 740 35-39 9.4 0.0 23.4 4.8 22.2 4.2 35.0 0.9 100.0 775 40-44 8.4 0.2 26.0 6.6 21.8 6.6 30.5 0.0 100.0 566 45-49 8.7 0.0 20.3 6.5 19.0 5.6 39.1 0.9 100.0 451 Marital status Married 7.7 0.1 25.8 6.1 19.6 3.2 37.0 0.5 100.0 3,689 Divorced/separated/ widowed 7.8 0.0 26.9 2.7 23.6 9.0 29.9 0.1 100.0 263 Number of living children 0 8.6 0.4 29.8 5.2 16.4 0.8 37.8 0.9 100.0 500 1-2 12.1 0.2 26.0 6.1 19.4 2.4 33.1 0.6 100.0 1,003 3-4 8.2 0.1 26.6 5.6 21.0 3.9 34.5 0.2 100.0 1,164 5+ 3.5 0.0 23.6 6.1 20.6 5.1 40.6 0.4 100.0 1,285 Residence Urban 20.3 0.3 45.0 5.7 16.7 9.6 2.2 0.2 100.0 926 Rural 3.9 0.1 20.0 5.9 20.9 1.7 47.1 0.5 100.0 3,026 Region Punjab 7.9 0.1 24.7 1.5 20.1 4.2 40.9 0.6 100.0 2,591 Sindh 5.8 0.2 27.2 16.9 19.0 1.6 29.3 0.0 100.0 1,106 Khyber Pakhtunkhwa 17.9 0.0 30.4 2.4 25.4 9.1 13.4 1.4 100.0 137 Balochistan 3.2 0.0 35.6 1.6 15.9 0.1 43.2 0.4 100.0 101 ICT Islamabad 36.3 1.5 17.9 0.5 25.7 16.5 1.6 0.0 100.0 13 Gilgit Baltistan 77.7 0.6 6.4 7.7 5.7 0.7 1.1 0.0 100.0 4 Education No education 1.0 0.1 19.3 7.0 21.5 4.3 46.5 0.4 100.0 2,801 Primary 1.8 0.0 46.4 3.9 21.4 3.2 22.9 0.3 100.0 530 Middle 10.1 0.0 56.3 1.3 18.6 2.2 10.3 1.2 100.0 165 Secondary 32.0 1.2 47.3 4.7 11.0 0.2 2.4 1.3 100.0 184 Higher 69.9 0.3 20.4 1.5 7.8 0.0 0.1 0.0 100.0 273 Wealth quintile Lowest 0.3 0.1 12.3 8.8 21.5 0.8 55.9 0.2 100.0 1,319 Second 2.7 0.0 21.7 4.6 21.6 3.1 45.1 1.2 100.0 946 Middle 5.6 0.1 37.1 3.6 21.1 7.2 25.1 0.0 100.0 727 Fourth 12.8 0.2 40.3 5.9 18.7 6.4 15.5 0.2 100.0 567 Highest 41.1 0.4 39.9 2.9 9.8 2.7 2.6 0.5 100.0 393 Total 7.7 0.1 25.9 5.8 19.9 3.5 36.6 0.4 100.0 3,952 The 2012-13 PDHS results show a decrease in the proportion of women working in agriculture, sales, and services occupations and an increase in unskilled and skilled manual occupations relative to the previous survey. Younger women are more likely to work in agricultural occupations than older women. More than half (56 percent) of employed women in the 15-19 age group and 42 percent in the 20-24 age group are engaged in agriculture. The proportions of employed women working in unskilled manual and domestic occupations are higher among those who are divorced, separated, or widowed than among those who are currently married. Residence has a strong relationship with type of occupation. As expected, large urban- rural differentials are found among women working in the agriculture sector; 47 percent of rural women work in agriculture, as compared with only 2 percent of urban women. In contrast, 45 percent of employed women residing in urban areas are engaged in sales and services, as compared with 20 percent of rural women. Urban women are also more likely than rural women to be employed in professional, technical, or managerial occupations (20 percent and 4 percent, respectively). An analysis by regions shows variations in occupational distributions. A higher proportion of employed women in Punjab (41 percent) and Balochistan (43 percent) than women in other regions are engaged in agricultural occupations. Interestingly, relative to the other provinces, a much larger proportion 50 • Characteristics of respondents of women in Gilgit Baltistan (78 percent), ICT Islamabad (36 percent), and Khyber Pakhtunkhwa (18 percent) are engaged in professional, technical, or managerial occupations. Education and occupation are also strongly related. As can be seen in Table 3.6.1, the proportion of women employed in agricultural occupations decreases substantially with increasing education, from 47 percent among employed women with no education to less than 1 percent among women with a higher education. The inverse is true for women who work in professional, technical, or managerial occupations; 70 percent of those with a higher education work in such jobs, as compared with 1 percent of women with no education. A majority (56 percent) of employed women in the lowest wealth quintile are engaged in agricultural occupations, as compared with only 3 percent of those in the highest wealth quintile. Women in the higher wealth quintiles are more likely to work in professional, technical, or managerial jobs or sales and services jobs than those in the lower quintiles. Table 3.6.2 presents information on the occupational distribution of ever-married men age 15-49. The results indicate that more

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