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 than half of employed men are engaged in unskilled manual (27 percent) and sales and services (25 percent) jobs. About 20 percent each are engaged in agricultural or skilled manual work, while 9 percent are employed in professional, technical, or managerial jobs. Table 3.6.2 Occupation: Men Percent distribution of ever-married men 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 men Age 15-19 (0.0) (0.0) (26.0) (17.1) (51.9) (0.0) (5.1) (0.0) 100.0 35 20-24 3.7 0.0 23.4 23.5 29.7 0.0 19.7 0.0 100.0 205 25-29 6.4 2.0 20.6 23.0 29.8 0.4 17.5 0.3 100.0 509 30-34 9.1 0.3 25.7 19.2 28.1 0.1 17.4 0.0 100.0 641 35-39 11.1 2.2 27.1 17.4 25.1 0.5 16.2 0.5 100.0 582 40-44 8.5 1.0 22.2 19.5 26.5 0.2 21.9 0.2 100.0 518 45-49 9.1 1.6 26.5 15.8 21.6 0.8 24.5 0.1 100.0 580 Marital status Married 8.5 1.3 24.9 19.1 26.3 0.4 19.2 0.2 100.0 3,009 Divorced/separated/ widowed (3.8) (0.0) (5.6) (21.1) (46.3) (0.0) (23.2) (0.0) 100.0 60 Number of living children 0 9.1 1.2 21.9 24.1 26.7 0.0 16.7 0.3 100.0 467 1-2 8.9 1.4 24.1 20.4 30.1 0.4 14.3 0.2 100.0 894 3-4 9.6 1.2 25.5 19.3 22.3 0.6 21.6 0.0 100.0 929 5+ 6.2 1.2 25.4 14.6 28.1 0.2 24.0 0.3 100.0 779 Residence Urban 12.0 2.2 37.4 25.4 18.9 0.5 3.5 0.1 100.0 1,093 Rural 6.5 0.8 17.4 15.7 31.0 0.3 28.1 0.3 100.0 1,977 Region Punjab 7.4 1.1 24.9 14.8 31.1 0.4 20.2 0.1 100.0 1,782 Sindh 7.4 1.2 24.4 31.6 15.3 0.2 19.9 0.0 100.0 783 Khyber Pakhtunkhwa 15.5 2.6 23.0 18.0 33.0 0.6 6.3 1.0 100.0 323 Balochistan 7.0 0.7 24.7 8.6 19.8 0.4 37.5 1.4 100.0 148 ICT Islamabad 37.1 3.7 19.8 14.7 21.6 1.6 1.5 0.0 100.0 17 Gilgit Baltistan 16.2 2.3 18.3 17.8 35.6 0.0 8.5 1.3 100.0 16 Education No education 2.0 0.2 15.6 17.1 38.9 0.2 26.0 0.0 100.0 889 Primary 3.3 0.5 22.5 22.4 33.6 1.1 16.5 0.0 100.0 647 Middle 3.8 0.3 28.9 23.2 23.2 0.3 20.2 0.0 100.0 515 Secondary 10.3 1.9 32.7 19.7 17.7 0.0 17.0 0.7 100.0 547 Higher 30.7 4.6 29.9 13.5 8.4 0.0 12.3 0.6 100.0 471 Wealth quintile Lowest 2.2 0.1 5.6 19.4 37.1 0.0 35.4 0.3 100.0 599 Second 4.7 0.8 17.3 14.3 38.9 0.5 22.9 0.6 100.0 548 Middle 5.3 1.3 24.8 15.6 31.2 1.0 20.7 0.1 100.0 561 Fourth 11.1 1.8 33.8 21.0 19.6 0.1 12.5 0.0 100.0 698 Highest 17.1 2.2 37.6 24.0 10.9 0.2 7.8 0.1 100.0 664 Total 8.5 1.3 24.5 19.2 26.7 0.3 19.3 0.2 100.0 3,069 Note: Figures in parentheses are based on 25-49 unweighted cases. Characteristics of respondents • 51 There are no substantial variations in the occupational distribution of employed men by age group and number of children. However, there is an urban-rural differential in the occupational distribution; men residing in urban areas are more likely to work in the sales and services sector (37 percent), in skilled manual work (25 percent), or in professional, technical, or managerial jobs (12 percent) than those living in rural areas, who are more likely to be engaged in unskilled manual (31 percent) and agricultural (28 percent) occupations. By region, about two in five (38 percent) ever-married working men in Balochistan are employed in the agricultural sector, as compared with 20 percent each in Punjab and Sindh and less than 10 percent in the other regions. In Khyber Pakhtunkhwa, unskilled manual occupations account for the largest proportion of employed men (33 percent). As expected, those residing in ICT Islamabad (37 percent) are more likely than those living in other regions to have professional, technical, or managerial jobs. The results indicate that men with no education are mostly employed as unskilled manual workers (39 percent), agricultural workers (26 percent), skilled manual workers (17 percent), and sales and services workers (16 percent). Those with a higher education are mostly employed in professional, technical, or managerial jobs (31 percent); sales and services jobs (30 percent); and skilled manual occupations (14 percent). Men in the lowest wealth quintile are more likely to be involved in unskilled manual (37 percent) or agricultural (35 percent) occupations than those in the highest wealth quintile, where most are engaged in professional, technical, or managerial occupations (17 percent); sales and services jobs (38 percent); and skilled manual occupations (24 percent). 3.7 TYPE OF EMPLOYMENT Table 3.7.1 shows the percent distribution of ever-married women employed in the 12 months prior to the survey by type of earnings, type of employer, and continuity of employment, according to whether respondents work in the agricultural or nonagricultural sector. Overall, 71 percent of women receive only cash for their work, while 7 percent receive cash and in-kind payments, 8 percent are paid in-kind only, and 14 percent are not paid. There are considerable variations between women who work in nonagricultural occupations and those who work in the agricultural sector. About three in 10 (29 percent) women working in agriculture are not paid for their work, as compared with 6 percent of those who work in nonagricultural jobs. Similarly, 17 percent of those who work in the agricultural sector are paid in-kind only, as compared with 2 percent of those who work in nonagricultural occupations. More than half (54 percent) of women who work in the agricultural sector receive either cash only or cash and in-kind payments, as opposed to 92 percent of nonagricultural workers (Figure 3.3). Table 3.7.1 Type of employment: Women Percent distribution of ever-married women age 15-49 employed in the 12 months preceding the survey by type of earnings, type of employer, and continuity of employment, according to type of employment (agricultural or nonagricultural), Pakistan 2012-13 Employment characteristic Agricultural work Non- agricultural work Total Type of earnings Cash only 44.3 87.1 71.2 Cash and in-kind 9.6 4.9 6.6 In-kind only 17.2 2.2 7.7 Not paid 28.8 5.7 14.4 Total 100.0 100.0 100.0 Type of employer Employed by family member 46.8 18.9 29.3 Employed by non-family member 39.6 44.5 42.6 Self-employed 13.4 36.4 27.9 Missing 0.2 0.1 0.1 Total 100.0 100.0 100.0 Continuity of employment All year 41.9 60.7 53.9 Seasonal 54.5 21.9 33.7 Occasional 3.7 17.3 12.3 Total 100.0 100.0 100.0 Number of women employed during the last 12 months 1,445 2,490 3,952 Note: Total includes 17 women with missing information on type of employment who are not shown separately. 52 • Characteristics of respondents Figure 3.3 Women’s earnings by type of employment 44 10 17 29 87 5 2 6 71 7 8 14 Cash only Cash and in-kind In-kind only Not paid Percentage Agricultural Nonagricultural Agricultural and nonagricultural Note: Among ever-married women who worked in the 12 months before the survey PDHS 2012-13 Those who were employed were asked for information on type of employer. Overall, 43 percent of employed women work for a non-family member while 29 percent work for a family member and almost the same proportion (28 percent) are self-employed. Women who work in agriculture are much more likely to work for a family member than those who work in nonagricultural jobs (47 percent and 19 percent, respectively). Conversely, those who work in nonagricultural jobs are much more likely to be self- employed (36 percent) than those who work in agriculture (13 percent). A majority of women who work are employed all year (54 percent), while 34 percent work seasonally and 12 percent work occasionally. As expected, those who work in agriculture are more likely to be employed seasonally than those who work in nonagricultural jobs. Table 3.7.2 presents the distribution of employed ever-married men by type of earnings and continuity of employment. Almost all men (95 percent) employed in the nonagricultural sector receive cash only, and 4 percent receive cash and in-kind payments. Among agricultural workers, more than half (52 percent) are paid in cash only, 41 percent receive both cash and in-kind payments, and 5 percent receive in- kind payments only; only 2 percent of these men are not paid for their work. Ninety percent of employed men work throughout the year, with no differences between the agricultural and nonagricultural sectors. 3.8 USE OF TOBACCO Smoking and other forms of tobacco use can cause a wide variety of diseases and can lead to death. Smoking is a risk factor for cardiovascular disease, lung cancer, and other forms of cancer, and it contributes to the severity of pneumonia, emphysema, and chronic bronchitis symptoms. Also, secondhand smoke may adversely affect the health of children and aggravate childhood illnesses. In the 2012-13 PDHS, both women and men were asked a number of questions to ascertain the prevalence of use of Table 3.7.2 Type of employment: Men Percent distribution of ever-married men age 15-49 employed in the 12 months preceding the survey by type of earnings and continuity of employment, according to type of employment (agricultural or nonagricultural), Pakistan 2012-13 Employment characteristic Agricultural work Non- agricultural work Total Type of earnings Cash only 52.3 94.9 86.6 Cash and in-kind 40.8 4.3 11.3 In-kind only 4.9 0.6 1.4 Not paid 2.0 0.2 0.5 Total 100.0 100.0 100.0 Continuity of employment All year 89.5 90.1 89.9 Seasonal 9.4 6.9 7.4 Occasional 1.0 3.0 2.6 Total 100.0 100.0 100.0 Number of men employed during the last 12 months 593 2,470 3,069 Note: Total includes 6 men with missing information on type of employment who are not shown separately. Characteristics of respondents • 53 tobacco products, and cigarette smokers were asked about the number of cigarettes smoked in the last 24 hours. Table 3.8.1 presents information on use of tobacco by ever-married women age 15-49. It is encouraging that almost all (94 percent) of the respondents reported that they do not use tobacco. Only 6 percent of women use any type of tobacco; 1 percent use cigarettes, and 5 percent use other forms of tobacco, including biri (hand-rolled cigarettes). Use of tobacco gradually increases with age. Six percent of pregnant women use some form of tobacco, as do 4 percent of women who are currently breastfeeding. Women residing in rural areas are slightly more likely to use tobacco than women in urban areas. Use of tobacco is particularly high among women in Balochistan, with 5 percent using cigarettes and 26 percent using other types of tobacco. Table 3.8.1 Use of tobacco: Women Percentage of ever-married women age 15-49 who smoke cigarettes or a pipe or use other tobacco products, according to background characteristics and maternity status, Pakistan 2012-13 Background characteristic Uses tobacco Does not use tobacco Number of women Cigarettes Pipe/biri Other tobacco Age 15-19 0.4 0.0 2.5 97.5 605 20-24 0.4 0.0 2.0 97.6 2,106 25-29 0.4 0.1 3.1 96.4 2,724 30-34 1.2 0.3 4.3 94.1 2,528 35-39 2.1 0.3 5.8 92.1 2,226 40-44 2.6 0.4 8.8 88.9 1,766 45-49 2.0 0.8 9.7 88.1 1,602 Maternity status Pregnant 1.2 0.0 4.4 94.4 1,461 Breastfeeding (not pregnant) 0.7 0.1 3.2 95.9 3,535 Neither 1.6 0.4 6.0 92.4 8,562 Residence Urban 0.8 0.0 3.1 95.8 4,536 Rural 1.6 0.4 6.1 92.4 9,022 Region Punjab 1.2 0.4 4.1 94.7 7,790 Sindh 1.6 0.2 6.7 91.4 3,133 Khyber Pakhtunkhwa 0.2 0.0 0.7 99.0 1,908 Balochistan 4.9 0.8 25.5 71.0 568 ICT Islamabad 0.9 0.0 2.3 96.4 64 Gilgit Baltistan 0.2 0.0 0.7 99.2 94 Education No education 2.1 0.5 7.8 90.1 7,736 Primary 0.4 0.0 2.4 97.2 2,156 Middle 0.3 0.0 2.1 97.8 993 Secondary 0.2 0.0 0.8 98.9 1,413 Higher 0.2 0.0 0.2 99.1 1,260 Wealth quintile Lowest 2.5 0.4 10.9 86.9 2,589 Second 1.8 0.7 5.8 92.2 2,676 Middle 1.5 0.2 4.6 94.1 2,700 Fourth 0.7 0.0 3.5 95.7 2,789 Highest 0.2 0.0 1.1 98.4 2,804 Total 1.3 0.3 5.1 93.6 13,558 Women with no education are more likely to use tobacco than those with some education. Use of tobacco decreases gradually with increasing wealth quintile. Thirteen percent of women in the lowest wealth quintile use some type of tobacco, as compared with only 2 percent of those in the highest quintile. Women who smoke cigarettes were asked about the number of cigarettes they smoked during the 24 hours preceding the survey. One-third of the women reported that they smoked 1-2 cigarettes in the last 24 hours, while 30 percent reported that they smoked 10 or more (data not shown). 54 • Characteristics of respondents Table 3.8.2 presents information on use of tobacco by ever-married men age 15-49. Men in Pakistan are more likely to use tobacco in any form than women. Forty-five percent of men reported using some type of tobacco, with 28 percent reporting use of cigarettes and 22 percent using some other type of tobacco. Those who smoked cigarettes were further asked about the number of cigarettes they smoked during the previous 24 hours. A large majority (70 percent) of the respondents smoked 10 or more cigarettes during the 24 hours preceding the survey, while 12 percent smoked 3-5 cigarettes and 10 percent smoked 6-9 cigarettes. Table 3.8.2 Use of tobacco: Men Percentage of ever-married men age 15-49 who smoke cigarettes or a pipe or use other tobacco products and the percent distribution of cigarette smokers by number of cigarettes smoked in preceding 24 hours, according to background characteristics, Pakistan 2012-13 Uses tobacco Does not use tobacco Number of men Percent distribution of men who smoke cigarettes by number of cigarettes smoked in the past 24 hours Total Number of cigarette smokers Background characteristic Cigarettes Pipe/biri Other tobacco 0 1-2 3-5 6-9 10+ Don’t know/ missing Age 15-19 (4.7) 0.0 (13.3) (82.0) 36 * * * * * * 100.0 2 20-24 18.4 0.0 22.7 62.5 219 (0.1) (12.7) (28.1) (19.5) (39.6) (0.0) 100.0 40 25-29 20.1 0.5 23.9 58.6 521 0.1 5.5 21.1 9.1 64.2 0.0 100.0 104 30-34 30.4 0.0 21.5 53.7 646 0.0 5.7 13.3 7.0 74.1 0.0 100.0 196 35-39 23.5 0.0 19.7 60.0 588 3.2 7.1 8.9 10.5 70.3 0.0 100.0 138 40-44 38.3 0.3 18.5 52.5 530 0.8 7.7 8.5 10.1 72.9 0.0 100.0 203 45-49 30.7 0.0 26.2 48.4 594 0.0 4.5 9.9 10.6 72.3 2.6 100.0 182 Residence Urban 27.0 0.1 21.4 56.2 1,107 0.8 7.7 12.3 13.9 64.7 0.6 100.0 299 Rural 28.0 0.1 22.2 55.0 2,027 0.7 5.7 12.4 7.9 72.8 0.5 100.0 568 Region Punjab 30.5 0.1 18.4 56.4 1,804 1.1 6.1 12.3 8.7 71.0 0.8 100.0 550 Sindh 23.6 0.3 28.4 52.5 796 0.0 7.4 11.2 6.1 75.4 0.0 100.0 188 Khyber Pakhtunkhwa 19.1 0.0 24.3 60.6 347 0.0 9.1 19.7 27.3 43.6 0.4 100.0 66 Balochistan 34.6 0.0 25.2 46.4 151 0.0 2.0 7.1 14.9 76.0 0.0 100.0 52 ICT Islamabad 29.0 0.0 10.7 61.4 18 2.0 3.9 12.3 15.2 66.1 0.5 100.0 5 Gilgit Baltistan 24.6 0.0 24.8 58.6 18 0.0 19.2 19.8 7.9 53.1 0.0 100.0 4 Education No education 34.6 0.3 27.4 44.4 905 0.5 5.2 10.4 8.8 74.1 0.9 100.0 313 Primary 27.8 0.0 26.3 52.0 657 0.0 5.5 14.3 7.8 72.3 0.0 100.0 183 Middle 32.2 0.0 18.7 53.4 525 2.7 4.9 13.3 17.6 61.5 0.0 100.0 169 Secondary 20.5 0.2 19.7 64.7 557 0.0 5.6 12.6 5.4 75.0 1.4 100.0 114 Higher 17.9 0.0 12.1 72.0 491 0.0 16.3 13.3 9.7 60.3 0.3 100.0 88 Wealth quintile Lowest 24.9 0.2 27.9 51.1 607 0.0 6.1 15.0 8.8 70.1 0.0 100.0 151 Second 31.2 0.3 24.3 51.8 574 0.0 6.0 9.4 14.1 70.4 0.0 100.0 179 Middle 31.7 0.0 22.5 51.6 567 0.9 4.6 7.5 4.2 81.1 1.6 100.0 180 Fourth 30.7 0.0 17.0 56.5 713 1.0 5.7 15.1 7.7 70.5 0.0 100.0 219 Highest 20.5 0.2 19.3 64.6 673 1.7 10.7 15.3 16.9 54.0 1.4 100.0 138 Total 27.6 0.1 21.9 55.4 3,134 0.7 6.4 12.4 10.0 70.0 0.6 100.0 866 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. It is encouraging that use of tobacco is less common among younger men, with only 18 percent of those age 20-24 smoking cigarettes, in contrast to 38 percent of those age 40-44. Use of other types of tobacco is higher (26 percent) among men age 45-49 than among those in the other age groups. Tobacco use is similar among urban and rural respondents. It is highest among men in Balochistan (54 percent), which also has the highest proportion of cigarette smokers who smoke 10 or more cigarettes a day (76 percent). Use of tobacco is less common in ICT Islamabad and Khyber Pakhtunkhwa than in other provinces. As with women, tobacco use among men decreases with increasing education and wealth. 3.9 KNOWLEDGE CONCERNING TUBERCULOSIS Table 3.9.1 presents results on knowledge concerning tuberculosis (TB) among ever-married women age 15-49. Overall, 95 percent of women have heard of tuberculosis. There are no marked differences in awareness of tuberculosis by women’s background characteristics (i.e., age, residence, region, education, and wealth quintile), except that women in Gilgit Baltistan (68 percent) and those in Balochistan (82 percent) are slightly less aware about it. Characteristics of respondents • 55 Table 3.9.1 Knowledge concerning tuberculosis: Women Percentage of ever-married women age 15-49 who have heard of tuberculosis (TB), and among women who have heard of TB, the percentage who know that TB is spread through the air by coughing, the percentage who believe that TB can be cured, and the percentage who have ever been told by a doctor, nurse, or LHV that they have TB, by background characteristics, Pakistan 2012-13 Among all respondents: Among respondents who have heard of TB: Background characteristic Percentage who have heard of TB Number Percentage who report that TB is spread through coughing Percentage who believe that TB can be cured Percentage who have been told by doctor/ nurse/LHV they have TB Number Age 15-19 89.9 605 31.5 87.1 2.6 544 20-24 94.5 2,106 43.4 92.9 2.2 1,990 25-29 94.8 2,724 50.5 94.3 3.4 2,581 30-34 95.3 2,528 49.1 92.9 3.7 2,409 35-39 93.9 2,226 51.3 94.8 4.4 2,090 40-44 95.6 1,766 50.9 95.0 3.7 1,688 45-49 96.9 1,602 45.2 94.5 4.5 1,552 Residence Urban 96.6 4,536 58.2 96.1 3.9 4,382 Rural 93.9 9,022 42.5 92.5 3.4 8,472 Region Punjab 95.4 7,790 48.8 93.9 3.0 7,436 Urban 96.5 2,526 57.7 95.6 3.5 2,436 Rural 95.0 5,264 44.5 93.1 2.7 4,999 Sindh 97.6 3,133 41.5 95.6 4.8 3,058 Urban 98.0 1,521 57.0 97.0 4.6 1,491 Rural 97.2 1,612 26.7 94.2 4.9 1,567 Khyber Pakhtunkhwa 92.6 1,908 50.1 93.1 3.3 1,767 Urban 94.3 320 61.7 97.0 4.0 302 Rural 92.3 1,588 47.7 92.3 3.1 1,465 Balochistan 82.1 568 61.1 81.2 6.3 467 Urban 89.1 114 70.3 93.1 6.1 102 Rural 80.4 454 58.5 77.9 6.4 365 ICT Islamabad 96.6 64 73.5 98.7 3.0 62 Gilgit Baltistan 68.4 94 58.2 84.9 3.4 64 Education No education 92.7 7,736 39.1 91.3 3.9 7,172 Primary 95.9 2,156 47.4 94.9 4.3 2,068 Middle 97.2 993 53.1 97.0 2.4 965 Secondary 99.0 1,413 62.6 97.9 2.8 1,398 Higher 99.3 1,260 78.0 98.5 2.0 1,251 Wealth quintile Lowest 91.5 2,589 32.0 87.0 4.2 2,369 Second 93.3 2,676 40.4 91.4 3.6 2,497 Middle 94.9 2,700 47.5 95.0 3.3 2,563 Fourth 96.2 2,789 51.7 96.5 3.9 2,683 Highest 97.8 2,804 64.9 97.7 2.9 2,742 Total 94.8 13,558 47.9 93.7 3.6 12,854 LHV = Lady health visitor Women who had heard of tuberculosis were asked about modes of TB transmission, whether they thought that the disease could be cured, and whether they had ever been told by a doctor, nurse, or lady health visitor (LHV) that they had tuberculosis. The results (Table 3.9.1) indicate that 48 percent of ever- married women are aware that tuberculosis can be spread through coughing. Ninety-four percent of women are aware that tuberculosis can be cured, and 4 percent said that they had been told by a medical professional that they had tuberculosis. Younger women (age 15-19) are least likely to know that tuberculosis can be transmitted through coughing (32 percent). Urban women (58 percent) are more likely than rural women (43 percent) to know about transmission of tuberculosis through coughing. Women in Sindh (42 percent), those who have no education (39 percent), and those in the lowest wealth quintile (32 percent) are least likely to know that tuberculosis can be spread through coughing. Almost all respondents, irrespective of their age, residence, region, education, or wealth, believe that tuberculosis can be cured. Young women age 15-19 (87 percent), those in Balochistan (81 percent), 56 • Characteristics of respondents and those in the lowest wealth quintile (87 percent) are slightly less likely to believe that tuberculosis can be cured. Six percent of women in Balochistan reported that they were told by a health provider that they had tuberculosis, the highest percentage among the regions. There is little variation by age and residence, although women with no education or a primary education (4 percent each) and those in the lowest wealth quintile (4 percent) are slightly more likely than other women to report having been told that they had tuberculosis. Table 3.9.2 presents results on knowledge concerning tuberculosis among ever-married men age 15-49. Men are equally as likely as women to be aware of tuberculosis; 96 percent reported that they had heard of tuberculosis, a percentage slightly higher than that among women (95 percent). There were only minimal differences in the proportions of men who had heard of tuberculosis according to background characteristics, with the exception that men in Gilgit Baltistan (82 percent) were less likely than men in other regions to be aware of the disease. Table 3.9.2 Knowledge concerning tuberculosis: Men Percentage of ever-married men age 15-49 who have heard of tuberculosis (TB), and among men who have heard of TB, the percentage who know that TB is spread through the air by coughing, the percentage who believe that TB can be cured, and the percentage who have ever been told by a doctor, nurse, or LHV that they have TB, by background characteristics, Pakistan 2012-13 Among all respondents: Among respondents who have heard of TB: Background characteristic Percentage who have heard of TB Number Percentage who report that TB is spread through coughing Percentage who believe that TB can be cured Percentage who have been told by doctor/ nurse/LHV they have TB Number Age 15-19 (90.1) 36 (29.8) (94.3) (0.0) 32 20-24 90.8 219 48.5 92.8 2.5 199 25-29 95.4 521 51.4 89.1 2.7 497 30-34 96.6 646 52.6 94.8 3.9 624 35-39 95.3 588 60.5 95.6 4.9 560 40-44 97.3 530 52.1 96.3 6.4 516 45-49 97.5 594 60.1 92.7 3.1 579 Residence Urban 97.7 1,107 72.0 94.7 4.4 1,081 Rural 95.0 2,027 45.0 93.2 3.8 1,926 Region Punjab 96.6 1,804 55.0 92.9 4.7 1,743 Urban 98.7 618 72.6 93.2 5.8 610 Rural 95.5 1,186 45.4 92.7 4.1 1,133 Sindh 95.7 796 45.9 94.0 3.2 762 Urban 96.3 376 69.7 96.3 2.5 362 Rural 95.3 420 24.5 91.9 3.9 401 Khyber Pakhtunkhwa 94.5 347 64.3 98.7 2.3 328 Urban 97.3 67 73.8 98.4 2.2 65 Rural 93.8 281 61.9 98.8 2.3 263 Balochistan 94.1 151 77.1 90.1 4.6 142 Urban 95.3 32 87.1 93.8 3.1 30 Rural 93.7 119 74.4 89.1 5.0 111 ICT Islamabad 97.8 18 65.2 99.7 4.5 17 Gilgit Baltistan 82.0 18 38.4 93.0 1.2 15 Education No education 91.9 905 38.8 89.4 5.0 832 Primary 97.4 657 46.7 92.3 4.4 639 Middle 96.5 525 56.5 95.0 4.1 506 Secondary 97.9 557 70.6 95.9 3.4 545 Higher 98.8 491 72.9 99.4 2.5 485 Wealth quintile Lowest 91.6 607 26.8 86.0 3.1 556 Second 95.3 574 42.4 94.3 4.0 547 Middle 96.0 567 54.3 94.9 4.3 545 Fourth 98.3 713 61.5 95.8 3.8 700 Highest 98.0 673 81.6 96.7 4.9 660 Total 96.0 3,134 54.7 93.7 4.0 3,007 Note: Figures in parentheses are based on 25-49 unweighted cases. LHV = Lady health visitor Characteristics of respondents • 57 Among men who had heard of tuberculosis, 55 percent reported that it can be spread through coughing, 94 percent believed that it can be cured, and 4 percent reported that they had been told by a health care provider that they had tuberculosis. The percentage of men aware that tuberculosis can be spread through coughing varied by age group, ranging from 49 percent among those 20-24 to 61 percent among those 35-39. There were urban- rural differentials as well, with 72 percent of men in urban areas and 45 percent in rural areas reporting that tuberculosis can be transmitted through coughing. Only 38 percent of men in Gilgit Baltistan know that tuberculosis can be spread through coughing (the lowest percentage among the regions), as compared with 77 percent of men in Balochistan. Knowledge that tuberculosis can be spread through coughing increases dramatically with increasing education and wealth. Ever-married men with no education and those in the lowest wealth quintile are least likely to know that tuberculosis can be cured. There are only minor differentials in knowledge that tuberculosis can be cured according to other characteristics. Also, there are minimal differences by background characteristics in the proportion of men who have been diagnosed as having tuberculosis. 3.10 KNOWLEDGE CONCERNING HEPATITIS Table 3.10.1 presents data on knowledge concerning hepatitis among ever-married women age 15- 49. Ninety percent of women have heard of hepatitis B or C. Younger women, those in rural areas, those in Gilgit Baltistan and Balochistan, those with no education, and those in the lowest wealth quintile are least likely to have heard of hepatitis B or C. Those respondents who had heard of hepatitis B or C were asked if there was anything a person could do to avoid getting hepatitis B or C and, if so, what. Nineteen percent of women reported that the disease could be prevented by avoiding using contaminated food and water, while 9 percent each cited using disposable syringes and avoiding contact with infected persons; 8 percent reported safe sex as a means of prevention, and 6 percent cited safe blood transfer. Nineteen percent said that there is nothing a person can do to avoid hepatitis or that they do not know of any means. Women who are more knowledgeable about ways to avoid hepatitis B or C include urban women, those in ICT Islamabad, those with more education, and those in the higher wealth quintiles. Table 3.10.2 presents information on knowledge concerning hepatitis B or C among ever-married men age 15-49. Men are slightly more likely to have heard of hepatitis B or C than women. Ninety-two percent of men reported that they have heard of hepatitis B or C (as compared with 90 percent of women). However, among those who have heard of hepatitis B or C, men are much more likely than women to know how hepatitis B or C can be avoided. For example, 32 percent of men reported that avoiding use of contaminated food or water is a way to avoid getting hepatitis B or C, while one-fifth of men reported use of disposable syringes and 15 percent each cited safe sex and safe blood transfer. Sixteen percent of men said that there is nothing a person can do or that they do not know any way of avoiding hepatitis. Differentials by residence are large with respect to knowledge of various ways to avoid hepatitis B or C. Men in urban areas and in ICT Islamabad are the most likely to know the main ways of avoiding hepatitis B or C, while those in Sindh are the least likely. Education is positively correlated with knowledge concerning hepatitis B or C, as is wealth quintile. 58 • Characteristics of respondents Table 3.10.1 Knowledge concerning hepatitis: Women Percentage of ever-married women age 15-49 who have heard of hepatitis B or C, and among women who have heard of hepatitis B or C, the percentages who believe that hepatitis can be avoided by different ways, according to background characteristics, Pakistan 2012-13 Among all respondents: Ways to avoid hepatitis B or C: Background characteristic Percentage who have heard of hepatitis B or C Number Safe sex Safe blood transfer Disposable syringe Avoid contami- nated food/ water Avoid contact with infected person There is nothing a person can do/don’t know Number Age 15-19 84.0 605 4.6 2.2 5.4 12.1 7.2 19.6 508 20-24 89.8 2,106 6.4 4.9 6.5 16.2 9.2 20.0 1,892 25-29 88.9 2,724 7.7 7.0 8.8 17.6 7.0 18.8 2,422 30-34 89.2 2,528 7.6 7.0 10.7 20.9 7.8 17.5 2,256 35-39 90.6 2,226 8.5 6.7 10.5 21.6 9.0 18.9 2,017 40-44 91.9 1,766 7.8 5.7 9.7 20.2 9.2 18.3 1,623 45-49 92.1 1,602 7.4 6.1 8.9 22.5 9.7 17.7 1,476 Residence Urban 92.9 4,536 9.6 10.8 13.5 23.5 7.9 16.2 4,216 Rural 88.4 9,022 6.3 3.7 6.8 17.2 8.8 19.9 7,979 Region Punjab 93.2 7,790 6.7 4.8 6.9 22.3 9.0 16.8 7,259 Urban 95.1 2,526 8.5 9.3 11.0 27.4 8.3 16.0 2,403 Rural 92.2 5,264 5.7 2.6 4.9 19.7 9.3 17.2 4,855 Sindh 84.7 3,133 6.6 7.9 14.0 14.8 3.8 22.4 2,653 Urban 90.0 1,521 10.6 12.0 17.2 17.5 6.2 16.3 1,370 Rural 79.7 1,612 2.4 3.4 10.7 11.9 1.3 28.8 1,284 Khyber Pakhtunkhwa 90.5 1,908 11.1 6.9 9.1 13.8 13.5 19.8 1,727 Urban 93.3 320 11.3 13.2 12.6 17.6 12.2 15.6 299 Rural 90.0 1,588 11.1 5.5 8.3 13.0 13.8 20.7 1,428 Balochistan 79.0 568 12.2 13.1 12.2 16.5 7.3 20.9 449 Urban 86.0 114 16.9 16.0 16.9 17.7 9.2 21.1 98 Rural 77.2 454 10.9 12.3 10.9 16.2 6.7 20.8 350 ICT Islamabad 94.4 64 8.2 20.7 32.5 44.0 5.7 17.5 60 Gilgit Baltistan 49.6 94 1.8 4.7 5.3 32.1 19.8 20.1 47 Education No education 85.9 7,736 5.2 2.6 5.6 16.1 8.1 20.3 6,645 Primary 92.8 2,156 8.2 5.0 6.7 19.0 8.1 20.0 2,000 Middle 95.6 993 7.2 7.1 10.8 19.9 8.0 18.7 949 Secondary 97.1 1,413 9.4 10.5 13.1 23.5 9.7 16.5 1,371 Higher 97.7 1,260 16.3 21.7 26.1 32.7 9.9 9.5 1,231 Wealth quintile Lowest 80.7 2,589 4.4 2.2 4.2 12.6 5.2 21.1 2,090 Second 88.0 2,676 5.8 3.0 6.2 16.9 8.8 21.5 2,355 Middle 91.4 2,700 7.4 3.6 7.1 17.9 9.9 19.5 2,469 Fourth 92.8 2,789 7.7 5.4 8.6 20.6 10.5 17.7 2,589 Highest 96.0 2,804 11.2 15.0 17.7 26.9 7.5 14.3 2,692 Total 89.9 13,558 7.5 6.1 9.1 19.4 8.5 18.6 12,195 Characteristics of respondents • 59 Table 3.10.2 Knowledge concerning hepatitis: Men Percentage of ever-married men age 15-49 who have heard of hepatitis B or C, and among men who have heard of hepatitis B or C, the percentages who believe that hepatitis can be avoided by different ways, according to background characteristics, Pakistan 2012-13 Among all respondents: Ways to avoid hepatitis B or C: Background characteristic Percentage who have heard of hepatitis B or C Number Safe sex Safe blood transfer Disposable syringe Avoid contami- nated food/ water Avoid contact with infected person There is nothing a person can do/don’t know Number Age 15-19 (80.5) 36 * * * * * * 29 20-24 86.6 219 6.4 12.1 17.3 18.3 8.3 24.1 190 25-29 91.5 521 12.0 10.5 16.0 28.7 6.8 19.1 476 30-34 92.1 646 17.4 17.0 20.1 33.1 7.3 14.8 595 35-39 97.2 588 17.9 16.3 22.8 38.2 6.1 13.9 571 40-44 91.9 530 13.3 13.5 18.4 32.2 10.2 16.2 487 45-49 92.0 594 16.6 17.8 22.0 30.2 5.3 13.9 547 Residence Urban 92.7 1,107 24.3 21.4 28.1 34.0 6.8 12.5 1,025 Rural 92.3 2,027 9.8 11.3 15.2 30.5 7.3 18.0 1,870 Region Punjab 93.4 1,804 15.2 13.7 20.2 36.0 7.1 12.6 1,685 Urban 92.9 618 29.8 26.8 35.2 43.3 8.4 4.9 574 Rural 93.7 1,186 7.7 6.9 12.4 32.2 6.4 16.6 1,111 Sindh 89.9 796 12.9 7.0 11.9 22.6 7.7 23.8 716 Urban 92.6 376 16.0 9.6 15.1 18.0 3.7 24.7 348 Rural 87.5 420 9.9 4.6 8.8 27.0 11.6 23.0 368 Khyber Pakhtunkhwa 95.5 347 20.2 36.1 34.3 28.6 3.6 16.0 331 Urban 94.0 67 23.0 31.6 34.0 32.4 6.1 14.4 63 Rural 95.8 281 19.5 37.1 34.3 27.8 3.1 16.4 269 Balochistan 90.2 151 9.8 18.5 19.5 34.6 13.5 18.8 136 Urban 85.1 32 21.2 32.0 27.3 43.7 14.2 13.7 27 Rural 91.6 119 6.9 15.2 17.6 32.3 13.3 20.1 109 ICT Islamabad 98.1 18 22.0 27.1 36.7 47.6 5.2 10.3 17 Gilgit Baltistan 54.2 18 15.3 13.5 15.6 13.0 2.9 19.4 10 Education No education 84.9 905 7.3 5.5 7.6 20.1 6.8 22.1 768 Primary 92.2 657 13.8 11.4 13.0 27.8 6.6 17.2 605 Middle 95.0 525 11.2 14.6 17.9 30.0 8.2 16.0 498 Secondary 96.5 557 22.6 21.8 32.0 44.2 5.9 11.5 537 Higher 99.1 491 24.0 26.8 36.1 43.1 8.6 10.2 486 Wealth quintile Lowest 85.6 607 7.4 3.8 6.3 18.6 5.0 22.1 519 Second 92.7 574 7.3 11.8 13.3 27.8 8.7 20.1 532 Middle 92.9 567 12.5 13.3 20.1 29.3 9.7 15.5 527 Fourth 94.1 713 17.8 17.0 23.6 40.2 6.3 13.6 671 Highest 96.1 673 26.4 25.5 31.7 38.9 6.3 11.0 647 Total 92.4 3,134 15.0 14.9 19.8 31.8 7.1 16.1 2,896 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. Marriage • 61 MARRIAGE 4 his chapter describes marriage patterns. Marriage is one of the factors that regulate the level of fertility because marriage signals the onset of exposure to the risk of pregnancy for most women and, thus, is considered a proximate determinant of fertility. The chapter also includes information on more direct measures of the beginning of exposure to pregnancy and level of exposure, for example, age at first marriage and length of time since last sexual activity. Similarly, information on current marital status, marriage between relatives, and marital union in polygynous relationships is presented. These variables, taken together, determine the length and pace of a woman’s reproductive life, and therefore they are important for understanding fertility dimensions. Marriage in Pakistan is a legal union between a man and a woman. Culturally, it is not only a link between husband and wife but also an alliance between their respective families. In Islamic law (sharia), marriage is a legal bond and social contract between a man and a woman and is highly recommended whenever the individuals feel financially and emotionally ready (Muslim Family Law Ordinance, 1961). 4.1 CURRENT MARITAL STATUS Table 4.1 shows the distribution of all women and men by current marital status, according to age. Sixty-four percent of women and 51 percent of men age 15-49 are currently married. A higher proportion of men (48 percent) than women (33 percent) have never been married. The proportion who are divorced, separated, or widowed is higher among women than men (3 percent and 1 percent, respectively). The results further show that women marry younger than men. For example, a higher proportion of teenage girls age 15-19 (14 percent) are married than teenage boys (2 percent). The proportion of married women increases rapidly from 14 percent among women age 15-19 to 49 percent among those age 20-24 and to 90 percent or above among women age 30-44. A slightly lower percentage of women age 45- 49 are in a union, primarily due to increased widowhood at older ages. Among men, the percentage who are married also increases rapidly from 2 percent in the youngest age group to 21 percent among those age 20-24, 54 percent among those age 25-29, and 81 percent or more among men age 30-49. T Key Findings • There is evidence that age at marriage among women in Pakistan is rising; the median age at first marriage increased from 19.1 years in 2006-07 to 19.5 years in 2012-13. • The percentage of women who were married by age 15 decreases from 10 percent among those age 45-49 to 2 percent among those age 15-19. • Pakistani men marry later than women. The median age at first marriage among women age 25-49 is 20 years. • Pakistan has a high rate of marriages between cousins, with approximately half of all marriages occurring between first cousins (49 percent). However, there has been a decrease of 3 percentage points in the proportion of such marriages since the 2006-07 PDHS. • The proportion of women in a polygynous union declined from 7 percent in 2006-07 to 4 percent in 2012-13. 62 • Marriage Table 4.1 Current marital status Percent distribution of women and men age 15-49 by current marital status, according to age, Pakistan 2012-13 Age Marital status Total Number of respondents Never married Married Divorced Separated Widowed WOMEN 15-19 85.8 13.9 0.0 0.1 0.1 100.0 4,269 20-24 49.7 49.1 0.7 0.4 0.2 100.0 4,183 25-29 20.4 77.8 0.8 0.5 0.5 100.0 3,421 30-34 7.2 90.1 0.9 0.6 1.2 100.0 2,725 35-39 3.0 93.1 0.8 0.7 2.3 100.0 2,296 40-44 2.1 89.6 0.8 0.9 6.5 100.0 1,804 45-49 1.3 87.4 0.8 0.7 9.8 100.0 1,623 Total 33.3 63.7 0.6 0.5 1.9 100.0 20,321 MEN 15-19 97.6 2.4 0.0 0.0 0.0 100.0 1,473 20-24 78.1 20.9 0.0 0.7 0.3 100.0 1,000 25-29 45.5 54.0 0.1 0.2 0.2 100.0 956 30-34 17.2 81.4 0.8 0.4 0.1 100.0 781 35-39 6.2 92.3 0.6 0.2 0.6 100.0 627 40-44 2.6 94.8 0.6 0.4 1.6 100.0 545 45-49 1.3 96.4 0.0 0.0 2.3 100.0 602 Total 47.6 51.3 0.2 0.3 0.5 100.0 5,982 The proportion of women and men who have never married decreases sharply with increasing age in both groups. Among women, the proportion decreases from 86 percent in the 15-19 age group to 3 percent or less among those age 35 and above; among men, it decreases from 98 percent in the 15-19 age group to 6 percent or less in the 35-39 age group and subsequent groups. Among women overall, the proportion who have never been married has decreased slightly over the past six years, from 35 percent in 2006-07 to 33 percent in 2012-13. However, among women age 15-19, the proportion who have never been married has increased slightly (from 84 percent to 86 percent). 4.2 POLYGYNY Marital unions are predominantly of two types, those that are monogamous and those that are polygynous. The distinction has social significance and probable fertility implications. Polygyny, the practice of having more than one wife, has connotations for frequency of sexual intercourse and thus may have an effect on fertility. Nevertheless, the association between type of union and fertility is complex and not well understood. Polygyny is legal in Pakistan; however, according to the Muslim Family Law Ordinance promulgated in 1961, the husband needs to obtain written permission from his existing wife or wives if he wants to marry another woman (Muslim Family Law Ordinance, 1961). The extent of polygyny was measured in the 2012-13 PDHS by asking all currently married female respondents whether their husband had other wives (co-wives) and, if so, how many. Currently married men were also asked whether they had one or more wives. Tables 4.2.1 and 4.2.2, respectively, show the percent distribution of currently married women age 15-49 by number of co-wives and the percent distribution of currently married men by number of wives. The data indicate that the vast majority of Pakistani women and men are in monogamous unions. Only 4 percent of married women and 3 percent of married men are in polygynous unions. The proportion of currently married women in a polygynous union decreased from 7 percent in 2006-07 to 4 percent in 2012- 13. Marriage • 63 Table 4.2.1 Number of women’s co-wives Percent distribution of currently married women age 15-49 by number of co-wives, according to background characteristics, Pakistan 2012-13 Background characteristic Number of co-wives Total Number of women 0 1 2+ Don’t know Missing Age 15-19 98.4 1.6 0.0 0.0 0.0 100.0 594 20-24 97.1 2.5 0.1 0.1 0.2 100.0 2,053 25-29 97.5 2.4 0.1 0.0 0.1 100.0 2,663 30-34 95.4 4.4 0.0 0.0 0.2 100.0 2,454 35-39 94.8 4.6 0.4 0.2 0.1 100.0 2,137 40-44 95.1 4.3 0.5 0.0 0.1 100.0 1,617 45-49 95.6 3.7 0.4 0.2 0.2 100.0 1,419 Residence Urban 96.3 3.1 0.2 0.1 0.2 100.0 4,304 Rural 96.0 3.7 0.2 0.0 0.1 100.0 8,633 Region Punjab 96.5 3.1 0.2 0.1 0.1 100.0 7,374 Sindh 95.6 4.1 0.3 0.0 0.0 100.0 3,002 Khyber Pakhtunkhwa 96.6 3.1 0.0 0.0 0.3 100.0 1,855 Balochistan 91.9 6.8 0.7 0.0 0.6 100.0 553 ICT Islamabad 96.3 3.4 0.0 0.0 0.3 100.0 62 Gilgit Baltistan 96.8 2.9 0.1 0.0 0.1 100.0 91 Education No education 95.5 4.2 0.2 0.1 0.1 100.0 7,347 Primary 96.1 3.4 0.3 0.1 0.0 100.0 2,057 Middle 98.1 1.7 0.1 0.0 0.0 100.0 958 Secondary 96.9 2.5 0.1 0.1 0.4 100.0 1,351 Higher 97.5 2.1 0.4 0.0 0.1 100.0 1,225 Wealth quintile Lowest 95.1 4.5 0.2 0.1 0.1 100.0 2,501 Second 96.0 3.6 0.1 0.1 0.2 100.0 2,533 Middle 95.9 4.0 0.0 0.1 0.0 100.0 2,550 Fourth 96.1 3.3 0.3 0.0 0.2 100.0 2,677 Highest 97.3 2.1 0.3 0.0 0.2 100.0 2,676 Total 96.1 3.5 0.2 0.1 0.1 100.0 12,937 Table 4.2.2 Number of men’s wives Percent distribution of currently married men age 15-49 by number of wives, according to background characteristics, Pakistan 2012-13 Background characteristic Number of wives Total Number of men 1 2+ Missing Age 15-19 (100.0) (0.0) (0.0) 100.0 36 20-24 99.8 0.2 0.0 100.0 209 25-29 96.4 1.9 1.7 100.0 516 30-34 98.2 1.3 0.5 100.0 636 35-39 95.0 4.4 0.7 100.0 579 40-44 95.9 4.1 0.0 100.0 516 45-49 93.1 6.8 0.0 100.0 580 Residence Urban 94.8 4.0 1.1 100.0 1,091 Rural 96.8 3.0 0.2 100.0 1,980 Region Punjab 95.1 4.1 0.9 100.0 1,761 Sindh 97.7 2.3 0.0 100.0 779 Khyber Pakhtunkhwa 98.0 2.0 0.0 100.0 345 Balochistan 94.8 4.4 0.8 100.0 150 ICT Islamabad 97.9 2.1 0.0 100.0 18 Gilgit Baltistan 98.3 1.7 0.0 100.0 18 Education No education 95.2 4.3 0.4 100.0 869 Primary 94.3 3.9 1.9 100.0 652 Middle 96.8 3.2 0.0 100.0 516 Secondary 97.1 2.8 0.0 100.0 548 Higher 98.0 1.9 0.0 100.0 487 Wealth quintile Lowest 96.9 3.0 0.1 100.0 591 Second 96.6 3.4 0.0 100.0 557 Middle 96.0 4.0 0.0 100.0 549 Fourth 94.5 5.1 0.4 100.0 706 Highest 96.6 1.5 1.9 100.0 668 Total 96.1 3.4 0.5 100.0 3,071 Note: Figures in parentheses are based on 25-49 unweighted cases. 64 • Marriage 4.3 AGE AT FIRST MARRIAGE Marriage in Pakistan defines the onset of the socially acceptable time for childbearing. The minimum legal age at marriage in Pakistan is 18 years for males and 16 years for females. Women are considered to be exposed to the risk of pregnancy after marriage. Duration of exposure to the risk of pregnancy depends primarily on the age at which women first marry. Women who marry early, on average, are more likely to have their first child at a young age and give birth to more children overall, contributing to higher fertility. Table 4.3 shows the percentage of women and men who have married by specific ages, according to current age. Age at first marriage is defined as the age at which the respondent began living with her or his first spouse. For women, marriage occurs relatively early in Pakistan; among women age 25-49, 35 percent were married by age 18, and 54 percent were married by age 20. The median age at first marriage among women age 25-49 is 19.5 years. The proportion of women married by age 15 declines from 10 percent among those age 45-49 to 2 percent among those age 15-19, providing clear evidence of a rising age at first marriage. This finding is corroborated by a rise in the median age at first marriage, from 18.5 among women age 45-49 to 20.9 among those age 25-29. Still another indication of rising age at marriage among women is the fact that the median age at first marriage among women age 25-49 increased slightly from 19.1 in 2006-07 to 19.5 in 2012-13. Table 4.3 Age at first marriage Percentage of women and men age 15-49 who were first married by specific exact ages and median age at first marriage, according to current age, Pakistan 2012-13 Current age Percentage first married by exact age: Percentage never married Number of respondents Median age at first marriage 15 18 20 22 25 WOMEN 15-19 1.6 na na na na 85.8 4,269 a 20-24 2.8 21.0 35.3 na na 49.7 4,183 a 25-29 4.8 27.2 43.8 56.3 72.0 20.4 3,421 20.9 30-34 5.5 33.0 50.8 64.4 78.3 7.2 2,725 19.9 35-39 8.7 39.3 59.4 72.7 84.1 3.0 2,296 18.8 40-44 9.8 40.2 62.2 78.7 89.0 2.1 1,804 18.6 45-49 10.1 44.5 62.5 78.3 88.5 1.3 1,623 18.5 20-49 6.1 31.5 48.9 na na 19.3 16,052 a 25-49 7.2 35.2 53.8 67.7 80.6 8.6 11,869 19.5 MEN 15-19 0.2 na na na na 97.6 1,473 a 20-24 0.2 3.1 9.5 na na 78.1 1,000 a 25-29 0.2 5.0 14.0 25.4 41.3 45.5 956 a 30-34 0.9 8.7 16.0 26.7 46.5 17.2 781 25.7 35-39 0.3 6.2 15.1 31.3 52.4 6.2 627 24.7 40-44 0.9 6.5 16.5 31.5 55.4 2.6 545 24.4 45-49 1.3 10.1 23.5 34.3 58.7 1.3 602 24.1 20-49 0.6 6.2 15.1 na na 31.3 4,509 a 25-49 0.7 7.1 16.7 29.2 49.6 18.0 3,510 a 30-49 0.8 7.9 17.6 30.6 52.7 7.7 2,554 24.7 Note: The age at first marriage is defined as the age at which the respondent began living with her/his first spouse. na = Not applicable due to censoring a = Omitted because less than 50 percent of the women or men began living with their spouse for the first time before reaching the beginning of the age group In Pakistan, men marry at a later age than women. Table 4.3 shows that 29 percent of men age 25- 49 are married by age 22, and 50 percent are married by age 25. Only 7 percent of men are married by age 18, compared with 35 percent of women. Among those age 25-29, 41 percent of men as compared with 72 percent of women were married by age 25. The median age at first marriage among men age 30-49 is 24.7 years. Marriage • 65 4.4 DIFFERENTIALS IN AGE AT FIRST MARRIAGE Table 4.4 shows the median age at first marriage among women age 25-49, men age 25-49, and men age 30-49 according to background characteristics. In Pakistan, urban women age 25-49 tend to marry two years later than rural women, and women from ICT Islamabad marry about five years later than women from Gilgit Baltistan. Among the other provinces, the median age at first marriage for women in Punjab is one year later than that in Sindh, Khyber Pakhtunkhwa, and Balochistan. There is a close association between education and median age at first marriage. The median age at first marriage for women age 25-49 with no education is 18.3 years, as compared with 22.3 years for women with a secondary education. A similar pattern is observed between median age at marriage and wealth quintile, with women in the highest wealth quintile marrying more than four years later than those in the lowest quintile. As such, education and wealth clearly are factors related to delayed marriage. Median age at first marriage among men age 25-49 and age 30-49 shows patterns similar to those observed for women in relation to level of education and wealth quintile. Analysis of age at marriage among men age 25-49 by background characteristics is hampered by the relatively late age at first marriage in most of the groups. Therefore, to capture the differentials, Table 4.4 shows additional information for men age 30-49. There seems to be a stronger shift toward later marriage among urban women in Pakistan. There has been an increase in the median age at marriage among urban women age 25-49 over the past six years (from 19.7 years in 2006-07 to 20.7 years in 2012-13). In contrast, there has been no change among rural women (18.8 years in both 2006-07 and 2012-13). 4.5 CONSANGUINITY Pakistan has one of the highest reported rates of consanguineous marriages in the region (NIPS and Macro International, 2008). Table 4.5 provides data on marriages between relatives as reported by ever-married women in the 2012-13 PDHS. The results show that more than half of all marriages (56 percent) are between first and second cousins. First-cousin marriages are more common on the father’s side (28 percent) but also occur between first cousins on the mother’s side (20 percent). Eight percent of marriages are between second cousins, 9 percent are between other relatives, and one-third (35 percent) are between non-relatives. There is evidence that children born in marriages between first cousins have double the risk of congenital anomalies (Chintahpilli, 2013). There is a substantial difference in the prevalence of first-cousin marriages between urban and rural areas (38 percent and 54 percent, respectively). Sindh has the highest proportion of marriages among first cousins (53 percent), followed by Balochistan (51 percent), Punjab (48 percent), Khyber Pakhtunkhwa (45 percent), ICT Islamabad (40 percent), and Gilgit Baltistan (40 percent). Table 4.4 Median age at first marriage by background characteristics Median age at first marriage among women age 25-49, and median age at first marriage among men age 25-49 and 30-49, according to background characteristics, Pakistan 2012-13 Background characteristic Women age 25-49 Men age 25-49 30-49 Residence Urban 20.7 a 25.8 Rural 18.8 24.5 24.1 Region Punjab 20.0 a 24.8 Urban 20.9 a 25.5 Rural 19.4 24.7 24.4 Sindh 18.8 25.0 24.4 Urban 20.6 a 26.3 Rural 17.9 22.3 21.8 Khyber Pakhtunkhwa 18.9 a 25.0 Urban 19.4 a 25.5 Rural 18.8 a 24.7 Balochistan 18.5 24.6 24.1 Urban 19.4 a 25.5 Rural 18.3 24.1 23.7 ICT Islamabad 22.7 a 27.4 Gilgit Baltistan 17.7 23.9 23.3 Education No education 18.3 23.0 22.7 Primary 19.3 24.4 24.4 Middle 20.4 25.0 24.8 Secondary 22.3 a 25.9 Higher a a 28.1 Wealth quintile Lowest 17.8 23.3 23.1 Second 18.6 23.9 23.9 Middle 19.2 24.1 23.3 Fourth 20.2 a 25.9 Highest 22.1 a 26.5 Total 19.5 a 24.7 Note: The age at first marriage is defined as the age at which the respondent began living with her/his first spouse. a = Omitted because less than 50 percent of the respondents began living with their spouse for the first time before reaching the beginning of the age group 66 • Marriage Table 4.5 Marriage between relatives Percent distribution of ever-married women by relationship to their husbands, according to background characteristics, Pakistan 2012-13 Background characteristic First cousin on father’s side First cousin on mother’s side Second cousin Other relationship Not related Missing Total Number of women Age 15-19 30.7 20.6 10.5 10.0 28.1 0.0 100.0 605 20-24 32.3 21.7 7.3 9.4 29.2 0.2 100.0 2,106 25-29 27.4 20.8 7.2 8.9 35.6 0.1 100.0 2,724 30-34 24.4 21.4 8.4 8.6 37.1 0.1 100.0 2,528 35-39 27.6 20.1 8.3 8.6 35.3 0.0 100.0 2,226 40-44 26.4 19.3 8.2 9.6 36.5 0.0 100.0 1,766 45-49 31.5 17.9 7.2 7.6 35.8 0.0 100.0 1,602 Age at marriage <15 27.6 19.2 7.4 10.1 35.7 0.1 100.0 1,040 15 33.6 19.9 7.5 10.5 28.5 0.1 100.0 1,170 16-17 33.5 20.0 9.0 9.4 28.1 0.1 100.0 3,337 18-19 29.2 21.5 9.1 8.0 32.2 0.0 100.0 2,915 20-21 26.6 22.8 6.5 9.1 34.8 0.2 100.0 2,114 22-23 20.6 20.1 6.1 8.8 44.4 0.1 100.0 1,274 24+ 20.2 17.5 7.4 7.2 47.7 0.0 100.0 1,708 Residence Urban 20.2 17.6 7.9 7.9 46.3 0.0 100.0 4,536 Rural 32.1 21.8 7.9 9.4 28.8 0.1 100.0 9,022 Region Punjab 25.6 22.0 6.5 11.5 34.2 0.1 100.0 7,790 Sindh 35.4 17.2 10.5 4.6 32.2 0.0 100.0 3,133 Khyber Pakhtunkhwa 26.9 18.2 8.2 6.3 40.3 0.1 100.0 1,908 Balochistan 28.4 22.7 12.3 5.4 30.7 0.6 100.0 568 ICT Islamabad 22.5 17.0 9.6 7.0 43.9 0.0 100.0 64 Gilgit Baltistan 21.0 19.2 5.4 3.1 51.2 0.0 100.0 94 Education No education 32.6 20.8 8.3 9.2 29.1 0.0 100.0 7,736 Primary 26.7 21.2 7.8 10.6 33.5 0.1 100.0 2,156 Middle 22.7 21.1 6.8 8.5 40.7 0.2 100.0 993 Secondary 21.1 18.5 6.6 7.7 46.0 0.1 100.0 1,413 Higher 15.7 17.6 8.2 5.7 52.9 0.1 100.0 1,260 Wealth quintile Lowest 40.5 20.5 8.3 8.5 22.2 0.1 100.0 2,589 Second 31.6 22.4 8.8 9.4 27.8 0.0 100.0 2,676 Middle 26.8 21.4 7.7 9.9 34.2 0.1 100.0 2,700 Fourth 22.5 19.2 7.8 8.3 42.0 0.2 100.0 2,789 Highest 20.3 18.5 7.1 8.3 45.8 0.0 100.0 2,804 Total 28.1 20.4 7.9 8.9 34.6 0.1 100.0 13,558 First-cousin marriages are far less common among educated women than among women with no education. The proportion of women marrying first cousins falls from 53 percent among those with no education to 33 percent among those with more than a secondary education. The proportion of women who marry a non-relative increases from 29 percent among those with no education to 53 percent among those with higher education. First-cousin marriages are also more common among women in the lowest wealth quintile than among women in the higher wealth quintiles. For example, 61 percent of women in the lowest wealth quintile are married to first cousins, as compared with 39 percent of those in the highest quintile. Overall, the proportion of marriage between first cousins has decreased slightly, from 52 percent of ever-married women in 2006-07 to 49 percent in 2012-13. Marriage • 67 4.6 RECENT SEXUAL ACTIVITY In the absence of contraception, the possibility of pregnancy is positively related to the frequency of sexual intercourse. Thus, information on recent sexual activity is important for refining measurement of exposure to pregnancy. In the 2012-13 PDHS, currently married women were asked how long ago their last sexual contact occurred. Table 4.6 shows the percent distribution of ever-married women age 15-49 by the timing of their last sexual intercourse, according to background characteristics. It can be seen that 70 percent of women had sexual intercourse within the four weeks preceding the survey, whereas 24 percent had sexual intercourse one to 11 months before the survey and 5 percent had their most recent sexual intercourse one or more years prior to the survey. Table 4.6 Recent sexual activity: Women Percent distribution of currently married women age 15-49 by timing of last sexual intercourse, according to background characteristics, Pakistan 2012-13 Timing of last sexual intercourse Total Number of women Background characteristic Within the past 4 weeks Within 1 year1 One or more years Missing Age 15-19 74.7 23.2 1.4 0.7 100.0 594 20-24 72.8 24.5 2.2 0.5 100.0 2,053 25-29 73.7 22.0 3.7 0.6 100.0 2,663 30-34 73.0 22.2 4.0 0.8 100.0 2,454 35-39 73.7 21.2 4.7 0.4 100.0 2,137 40-44 67.2 25.2 7.1 0.5 100.0 1,617 45-49 50.0 36.7 11.9 1.5 100.0 1,419 Marital duration 0-4 years 72.7 24.0 2.6 0.7 100.0 2,898 5-9 years 72.2 23.9 3.4 0.5 100.0 2,488 10-14 years 75.6 19.9 3.6 1.0 100.0 2,139 15-19 years 74.9 20.2 4.5 0.4 100.0 1,856 20-24 years 68.3 25.6 5.8 0.3 100.0 1,635 25+ years 51.0 35.0 12.6 1.4 100.0 1,632 Married more than once 70.8 24.3 4.3 0.6 100.0 289 Residence Urban 72.3 22.4 4.1 1.2 100.0 4,304 Rural 68.9 25.4 5.3 0.4 100.0 8,633 Region Punjab 65.7 28.1 5.5 0.7 100.0 7,374 Sindh 78.2 18.3 2.8 0.7 100.0 3,002 Khyber Pakhtunkhwa 70.0 22.6 7.1 0.3 100.0 1,855 Balochistan 83.5 13.4 1.8 1.3 100.0 553 ICT Islamabad 76.1 19.5 2.4 1.9 100.0 62 Gilgit Baltistan 72.7 24.1 3.1 0.0 100.0 91 Education No education 69.2 25.2 5.0 0.6 100.0 7,347 Primary 67.9 25.2 6.4 0.5 100.0 2,057 Middle 71.9 24.1 3.2 0.8 100.0 958 Secondary 71.7 23.0 4.7 0.7 100.0 1,351 Higher 75.5 19.9 3.1 1.5 100.0 1,225 Wealth quintile Lowest 72.7 23.9 3.0 0.4 100.0 2,501 Second 67.6 27.2 4.9 0.4 100.0 2,533 Middle 69.9 24.2 5.1 0.8 100.0 2,550 Fourth 69.3 23.9 6.1 0.6 100.0 2,677 Highest 70.8 22.7 5.3 1.2 100.0 2,676 Total 70.1 24.4 4.9 0.7 100.0 12,937 1 Excludes women who had sexual intercourse within the last 4 weeks The youngest women (age 15-19) were more likely than older women (age 45-49) to have had sexual intercourse in the past four weeks (75 percent versus 50 percent). The proportion of women who were sexually active during the four weeks preceding the survey shows no consistent pattern with duration of marital union until it begins to decline among those married 20 or more years. There is a difference of 3 68 • Marriage percentage points (72 percent versus 69 percent) between urban and rural women in the proportion who had been sexually active within the past four weeks. Seven in 10 married or cohabiting women had their last sexual encounter in the four weeks preceding the survey. There are large variations by region in the timing of last sexual intercourse. The proportion of women who were sexually active in the past four weeks ranged from 66 percent in Punjab to 84 percent in Balochistan. The relationship between a woman’s education and her sexual activity is more or less positive; women with a primary education are least likely to have been sexually active in the past four weeks (68 percent), and women with a higher education are most likely to have been sexually active (76 percent). Women in the lowest wealth quintile (73 percent) are more likely than women in the other wealth quintiles to have had their most recent sexual intercourse in the four weeks before the survey. Fertility • 69 FERTILITY 5 ertility is one of the three principal components of population dynamics, the others being mortality and migration. Since its inception, Pakistan has been experiencing a high rate of population growth, mainly because of a high fertility rate that remained almost constant at more than six children until the mid-1980s. The first sign of a fertility falloff was evidenced in 1984-85, when the fertility rate decreased to a little below six children (Government of Pakistan, 1987). Subsequent surveys did indicate that there was a fertility transition; however, the pace of this transition remained slow (Feeney and Alam, 2003). On the other hand, the death rate decreased at a much faster pace. Consequently, the population has increased 5.5-fold since 1951 (from 32.5 million to 184.5 million) (Government of Pakistan, 2013). This chapter assesses pregnancy and fertility data collected in the 2012-13 PDHS. Levels, trends, and differentials in pregnancy and fertility are discussed, along with data on cumulative fertility (children ever born and living); birth intervals; postpartum amenorrhea, abstinence, and insusceptibility; menopause; age at first birth; teenage pregnancy and motherhood; and pregnancy outcomes. Pregnancy and fertility data were collected by asking ever-married women of reproductive age (15-49 years) to provide the complete history of all of their live births, stillbirths, miscarriages, and abortions. In order to ensure a complete enumeration of live births, women’s responses to questions about the total number of children currently living with them, those living away, and those who had died were recorded. Moreover, information about total number of lost pregnancies was recorded. Specifically, the following information was collected for each pregnancy loss: date of loss, duration of pregnancy, and whether the pregnancy ended in a miscarriage, an induced abortion, or a stillbirth. In cases of live births, the following information was collected: name, sex, date of birth, survival status, current age (if alive), and age at death (if dead). The 2012-13 PDHS used the conventional practice of recording pregnancies in the pregnancy history starting from the first pregnancy. Although efforts were made during training to impress upon the interviewers the importance of collecting accurate and complete information on pregnancy histories, it is important to note that information collected through the pregnancy history approach has limitations that might bias pregnancy and fertility levels and patterns. For instance, women may include relatives’ children as their own or omit children who died at a young age, while older women may omit F Key Findings • The total fertility rate for the three years preceding the survey is 3.8 births per woman, with rural women having one child more on average than urban women. • Fertility decreased by 1.6 births between 1985-90 and 2010-12 (from 5.4 to 3.8 births per woman). • Childbearing begins early in Pakistan, with 15 percent of women age 25- 49 giving birth by age 18 and 32 percent by age 20. • Eight percent of adolescent women age 15-19 are already mothers or pregnant with their first child. • Sixty-nine percent of births occur within three years of a previous birth, with 37 percent occurring within 24 months. The latter proportion represents an increase of 3 percentage points since 2006-07. • Twelve percent of pregnancies resulted in miscarriages in the five years before the survey, almost 2 percent resulted in an abortion, and 3 percent resulted in a stillbirth. 70 • Fertility grown children who have left home (United Nations, 1983). Accordingly, the results should be viewed with these caveats in mind. 5.1 CURRENT FERTILITY Some current fertility measures are presented in Table 5.1 for the three-year period preceding the survey. Age-specific fertility rates (ASFRs) are calculated by dividing the number of births to women in a specific age group by the number of woman-years lived during a given period.1 The total fertility rate (TFR) is a common measure of current fertility and is defined as the average number of children a woman would have if she went through her entire reproductive period (15-49 years) reproducing at the currently prevailing ASFR. An additional measure of fertility reported in this table is the general fertility rate (GFR), which represents the annual number of births per 1,000 women age 15-44. Table 5.1 shows a TFR of 3.8 children per woman for the three-year period preceding the survey. Fertility is considerably higher in rural areas (4.2 births per woman) than in urban areas (3.2 births per woman), a pattern that is evident at every age. The estimated TFR in the 2006-07 PDHS was 4.1 children, and thus the decrease in the TFR over the past six years is only 0.3 births. The persistence of a disparity in fertility between urban and rural women is most probably due to factors associated with urbanization, such as better education, higher status of women, better access to health and family planning information and services, and later marriage. On the whole, peak fertility occurs at age 25-29, a pattern evident in rural areas as well as urban areas. Fertility falls sharply after age 30-34. Differentials in fertility levels by urban-rural residence, region, educational attainment, and wealth quintile are shown in Table 5.2. As noted above, there is a fertility rate difference of one child between urban and rural areas (3.2 versus 4.2). This difference has shrunk by 0.2 births in the last six years. Among the regions, there are only slight differences in the fertility rates in Gilgit Baltistan and Punjab (3.8 each) and in Sindh and Khyber Pakhtunkhwa (3.9 each). Fertility is highest (4.2) in Balochistan and lowest in ICT Islamabad (3.0). Age-specific fertility rates by region are more or less consistent with regional differentials in TFRs (Appendix Table A5.1). These provincial differentials in fertility are as expected and are closely associated with regional disparities in median age at marriage, age at first birth, and use of family planning methods (see Tables 4.4, 5.10, and 7.4). 1 Numerators for the age-specific rates are calculated by summing the births that occurred during the 1-36 months preceding the survey, classified by the age group of the mother at the time of birth in five-year age groups. The denominators are the numbers of woman-years lived in each five-year age group during the 1-36 months preceding the survey. Because rates must be based on all women and the Pakistan DHS is a survey of ever-married women, the number of women was increased using a factor based on all de facto women listed in the household who had never been married. The “all women” factors were based on age and background information available at the household level. Table 5.1 Current fertility Age-specific and total fertility rates and the general fertility rate for the three years preceding the survey, by residence, Pakistan 2012-13 Age group Residence Total Urban Rural 15-19 27 53 44 20-24 161 206 190 25-29 201 236 224 30-34 158 193 181 35-39 61 107 91 40-44 21 35 30 45-49 2 10 7 TFR (15-49) 3.2 4.2 3.8 GFR 109 144 131 Note: Age-specific fertility rates are per 1,000 women. Rates for the 45-49 age group may be slightly biased due to truncation. Rates are for the period 1-36 months prior to the interview. TFR: Total fertility rate expressed per woman GFR: General fertility rate expressed per 1,000 women age 15-44 Fertility • 71 As expected, women’s level of education is strongly associated with fertility. The TFR decreases consistently and dramatically from 4.4 among women with no education to 2.5 among women with a higher education. Fertility is also strongly associated with wealth. Fertility rates among women in the lower wealth quintiles are higher than rates among those in the higher quintiles. The difference in fertility between women in the lowest and highest wealth quintiles is 2.5 births per woman. Table 5.2 also presents a crude assessment of fertility trends in various subgroups by comparing current fertility with a measure of completed fertility: the mean number of children ever born to women age 40-49. In every category, current fertility falls substantially below lifetime fertility. This provides further evidence that fertility has fallen considerably over time in all of these subgroups. Overall, the table shows that fertility has fallen by about two children per woman in recent periods (from 5.6 to 3.8). Furthermore, Table 5.2 indicates that 7 percent of women were pregnant at the time of the survey. This is likely to be an underestimate, as women in the early stages of pregnancy may be unaware or unsure that they are pregnant, while some may refuse to declare that they are pregnant. Differentials in pregnancy levels are generally consistent with the pattern depicted by the TFR across the various subgroups, except for women in the second wealth quintile. 5.2 FERTILITY TRENDS Table 5.3 presents trends in age-specific fertility rates for successive five-year periods preceding the survey. The data are derived from information on dates of birth in the pregnancy history from the 2012-13 PDHS. It is important to mention here that since only women age 15- 49 are interviewed for the Woman’s Questionnaire, fertility rates in older age groups become progressively more truncated for periods more distant from the survey date. The pattern of age-specific fertility rates in the four five- year periods preceding the survey is similar. Nevertheless, there is a clear indication of fertility declines over the past two decades. Table 5.4 displays trends in fertility by background characteristics and the percentage change from 1990-91 to 2012-13. Overall, the TFR declined from 5.4 children per woman in the six years before the 1990-91 PDHS to 3.8 in the three years before the 2012-13 PDHS. The decrease in fertility has been more rapid in urban than rural areas (decreasing by 35 percent and 25 percent, respectively). Although fertility decreased in all four provinces, the decrease in Sindh (24 percent) was smaller than that in the other provinces. Fertility decreased more among women with at least a secondary education than among women at other educational levels. Table 5.2 Fertility by background characteristics Total fertility rate for the three years preceding the survey, percentage of women age 15-49 currently pregnant, and mean number of children ever born to women age 40-49, by background characteristics, Pakistan 2012-13 Background characteristic Total fertility rate Percentage of women age 15-49 currently pregnant Mean number of children ever born to women age 40-49 Residence Urban 3.2 5.5 5.1 Rural 4.2 8.1 5.9 Region Punjab 3.8 6.7 5.4 Sindh 3.9 7.5 5.8 Khyber Pakhtunkhwa 3.9 7.9 5.8 Balochistan 4.2 10.0 6.6 ICT Islamabad 3.0 5.3 4.2 Gilgit Baltistan 3.8 7.9 6.8 Education No education 4.4 8.3 6.1 Primary 4.1 7.1 5.2 Middle 3.3 6.0 5.3 Secondary 3.2 5.9 3.9 Higher 2.5 5.5 3.3 Wealth quintile Lowest 5.2 10.5 6.5 Second 4.4 8.3 6.2 Middle 3.8 6.2 6.0 Fourth 3.4 6.5 5.4 Highest 2.7 5.0 4.5 Total 3.8 7.2 5.6 Note: Total fertility rates are for the period 1-36 months prior to the interview. Table 5.3 Trends in age-specific fertility rates Age-specific fertility rates for five-year periods preceding the survey, by mother’s age at the time of the birth, Pakistan 2012-13 Mother’s age at birth Number of years preceding survey 0-4 5-9 10-14 15-19 15-19 48 67 88 95 20-24 195 229 253 285 25-29 238 282 287 321 30-34 189 203 243 [267] 35-39 98 132 [167] 40-44 34 [66] 45-49 [8] Note: Age-specific fertility rates are per 1,000 women. Estimates in brackets are truncated. Rates exclude the month of interview. 72 • Fertility Table 5.4 Trends in fertility by background characteristics Total fertility rates for the 1990-91, 2006-07, and 2012-13 PDHS surveys and percent change from the 1990-91 PDHS to the 2012-13 PDHS, by background characteristics Background characteristic 1990-91 PDHS 2006-07 PDHS 2012-13 PDHS Percent change during 1990-91 to 2012-13 1985-90 2004-06 2010-12 Residence Urban 4.9 3.3 3.2 -34.7 Rural 5.6 4.5 4.2 -25.0 Province Punjab1 5.4 3.9 3.8 -29.6 Sindh 5.1 4.3 3.9 -23.5 Khyber Pakhtunkhwa 5.5 4.3 3.9 -29.1 Balochistan 5.8 4.1 4.2 -27.6 Education No education 5.7 4.8 4.4 -22.8 Primary 4.9 4.0 4.0 -18.4 Middle 4.5 3.2 3.2 -28.9 Secondary or higher 3.6 2.7 2.2 -38.9 Total 5.4 4.1 3.8 -29.6 Note: Total fertility rate is per woman. The rates are calculated for the 6 years before the 1990-91 PDHS and for the 3 years before the 2006-07 PDHS and the 2012-13 PDHS. 1 In the 1990-91 PDHS and 2006-07 PDHS, ICT Islamabad was included in Punjab. Table 5.5 and Figure 5.1 indicate trends in fertility from the three PDHS surveys conducted in Pakistan. They show that the TFR decreased from 5.4 children in 1985-90 to 3.8 children in 2010-12. However, the decrease was more rapid between the first and second PDHS surveys than between the second and third surveys. The decrease in TFR is also reflected in the ASFRs, which show more or less a consistent decrease in all age groups. Table 5.5 Trends in age-specific and total fertility rates Age-specific and total fertility rates (TFRs) for the 1990-91, 2006- 07, and 2012-13 PDHS surveys Mother’s age at birth 1990-91 PDHS 2006-07 PDHS 2012-13 PDHS 1985-90 2004-06 2010-12 15-19 84 51 44 20-24 230 178 190 25-29 268 237 224 30-34 229 182 181 35-39 147 106 91 40-44 73 44 30 45-49 40 18 7 TFR 15-49 5.4 4.1 3.8 Note: Age-specific fertility rates are per 1,000 women. The rates are calculated for the 6 years before the 1990-91 PDHS and for the 3 years before the 2006-07 PDHS and the 2012-13 PDHS. Fertility • 73 Figure 5.1 Trends in age-specific fertility rates 0 50 100 150 200 250 300 15-19 20-24 25-29 30-34 35-39 40-44 45-49 Births per 1,000 women Mother's age at birth PDHS 1990-91 (1985-90) PDHS 2006-07 (2004-06) PDHS 2012-13 (2010-12) 5.3 CHILDREN EVER BORN AND CHILDREN SURVIVING Table 5.6 presents the number of children ever born and the mean number of living children for all women and all currently married women age 15-49. The estimates for all women are based on the assumption that all births occur within marriage. Among women age 15-19, 95 percent have never given birth. However, this proportion drops rapidly to 13 percent among women age 30-34, and only 5 percent of women at the end of their reproductive period remain childless, indicating that childbearing among Pakistani women is nearly universal. On average, Pakistani women have borne 6.0 children at the end of their childbearing years. This number is more than two (2.2) children above the TFR (3.8 children per woman), a discrepancy that is attributable to the decline in fertility over time. Table 5.6 Children ever born and living Percent distribution of all women and currently married women age 15-49 by number of children ever born, mean number of children ever born, and mean number of living children, according to age group, Pakistan 2012-13 Age Number of children ever born Total Number of women Mean number of children ever born Mean number of living children 0 1 2 3 4 5 6 7 8 9 10+ ALL WOMEN 15-19 94.6 4.6 0.8 0.1 0.0 0.0 0.0 0.0 0.0 0.0 0.0 100.0 4,269 0.06 0.06 20-24 63.2 15.8 12.9 5.5 2.3 0.2 0.1 0.0 0.0 0.0 0.0 100.0 4,183 0.69 0.63 25-29 31.3 12.9 18.6 16.5 10.8 6.1 2.2 0.9 0.6 0.1 0.0 100.0 3,421 1.99 1.80 30-34 13.2 7.5 12.6 16.5 18.1 13.4 8.7 5.7 2.1 1.1 1.0 100.0 2,725 3.51 3.13 35-39 7.6 4.6 8.7 13.9 17.0 14.9 11.2 10.6 5.5 2.9 3.1 100.0 2,296 4.50 4.03 40-44 6.6 3.0 5.4 11.5 13.2 12.3 13.3 14.3 8.8 5.4 6.4 100.0 1,804 5.29 4.66 45-49 4.5 2.6 4.6 9.0 10.9 12.2 12.7 14.2 9.8 7.8 11.8 100.0 1,623 5.98 5.17 Total 41.7 8.4 9.5 9.4 8.7 6.6 5.0 4.5 2.6 1.6 2.0 100.0 20,321 2.42 2.15 CURRENTLY MARRIED WOMEN 15-19 62.2 31.9 5.5 0.4 0.0 0.0 0.0 0.0 0.0 0.0 0.0 100.0 594 0.44 0.40 20-24 26.7 31.0 26.1 11.1 4.6 0.4 0.2 0.0 0.0 0.0 0.0 100.0 2,053 1.38 1.26 25-29 13.4 15.9 23.6 20.8 13.7 7.8 2.7 1.2 0.8 0.1 0.0 100.0 2,663 2.51 2.27 30-34 5.9 7.9 13.4 17.6 19.9 14.7 9.6 6.3 2.4 1.2 1.1 100.0 2,454 3.83 3.42 35-39 4.6 4.1 8.6 14.3 17.7 15.6 11.8 11.2 5.8 3.1 3.3 100.0 2,137 4.71 4.22 40-44 4.5 1.7 5.4 11.1 13.8 13.0 13.6 15.1 9.1 5.9 6.6 100.0 1,617 5.51 4.85 45-49 3.0 2.3 4.3 8.1 11.7 12.2 13.0 15.3 10.3 7.5 12.5 100.0 1,419 6.17 5.34 Total 12.6 12.3 14.4 14.0 13.3 10.0 7.5 6.8 3.8 2.3 2.9 100.0 12,937 3.63 3.22 74 • Fertility The same pattern is replicated for currently married women, although the proportion of married women age 15-19 who have not borne a child is reduced to 62 percent. Furthermore, currently married women age 45-49 have borne an average of 6.2 children each. The difference in childbearing between all women and currently married women can be explained by the presence of many young unmarried and widowed, divorced, and separated women in the “all women” category. As expected, women above age 40 have much higher parities, with substantial proportions having eight or more births by the end of their childbearing years. The overall picture that emerges from Table 5.6 is that the mean number of children ever born and the number of living children increase with rising age of women, thus presupposing minimal or no recall lapse, which heightens confidence in reported birth histories. Cumulative fertility for all women as well as currently married women has shown a modest but steady downward trend since the 1990-91 PDHS in all age groups (Table 5.7). Overall, the mean number of children ever born decreased from 3.0 in 1990-91 to 2.4 in 2012-13 among all women and from 4.1 to 3.6 among currently married women. Table 5.7 Trends in children ever born Mean number of children ever born for all women and currently married women age 15-49 by age group, 1990-91, 2006-07, and 2012-13 PDHS surveys Mean number of children ever born 1990-91 2006-07 2012-13 ALL WOMEN 15-19 0.2 0.08 0.06 20-24 1.0 0.72 0.69 25-29 2.6 2.14 1.99 30-34 4.3 3.77 3.51 35-39 5.5 4.97 4.50 40-44 6.3 5.57 5.29 45-49 6.4 6.31 5.98 Total 3.0 2.53 2.42 CURRENTLY MARRIED WOMEN 15-19 0.6 0.54 0.44 20-24 1.6 1.52 1.38 25-29 3.1 2.69 2.51 30-34 4.6 4.10 3.83 35-39 5.7 5.21 4.71 40-44 6.5 5.80 5.51 45-49 6.6 6.61 6.17 Total 4.1 3.88 3.63 5.4 BIRTH INTERVALS Previous research has demonstrated that children born too close to a previous birth are at increased risk of dying (NIPS and IRD/Macro International, 1992; NIPS and Macro International, 2008). In the context of this finding, examination of birth intervals is important in providing insights into birth spacing patterns and, subsequently, maternal and child health. Table 5.8 shows the birth intervals of children born to Pakistani women of reproductive age during the five years preceding the survey across selected subgroups. Overall, the median birth interval is 28 months, just one month less than the estimated interval in both 1990-91 and 2006-07. The shortest birth intervals are observed among children born to women age 15-19 (18 months) and children whose preceding sibling died (23 months). The longest intervals occur among children born to women age 40-49 (38 months) and children born to women in Khyber Pakhtunkhwa (32 months). It is also interesting to note that there is no difference in birth intervals after the birth of a female or a male child, and there is only a one-month difference between urban and rural areas. Fertility • 75 Table 5.8 Birth intervals Percent distribution of non-first births in the five years preceding the survey by number of months since preceding birth, and median number of months since preceding birth, according to background characteristics, Pakistan 2012-13 Background characteristic Months since preceding birth Total Number of non-first births Median number of months since preceding birth 7-17 18-23 24-35 36-47 48-59 60+ Age 15-19 (50.3) (13.7) (16.9) (14.1) (4.9) (0.0) 100.0 35 (18.0) 20-29 21.8 22.8 33.8 14.4 4.8 2.5 100.0 4,059 25.4 30-39 15.1 16.5 31.9 17.1 9.6 9.8 100.0 4,393 30.1 40-49 7.9 13.1 24.0 23.5 11.1 20.5 100.0 707 38.4 Sex of preceding birth Male 17.3 18.9 31.4 16.7 8.3 7.4 100.0 4,682 28.2 Female 18.0 19.2 32.8 16.0 6.8 7.3 100.0 4,512 27.8 Survival of preceding birth Living 15.9 19.1 32.6 17.1 7.9 7.6 100.0 8,312 28.6 Dead 34.4 18.7 27.4 9.7 4.4 5.4 100.0 882 23.2 Birth order 2-3 19.8 20.3 32.1 15.6 6.2 6.0 100.0 4,374 26.8 4-6 15.3 17.6 32.2 17.0 8.8 9.1 100.0 3,381 29.5 7+ 16.5 18.6 31.8 17.1 8.8 7.1 100.0 1,439 28.7 Residence Urban 17.1 17.4 30.5 16.7 8.7 9.6 100.0 2,542 28.8 Rural 17.8 19.7 32.7 16.2 7.1 6.5 100.0 6,652 27.7 Region Punjab 21.2 19.1 31.0 15.8 6.2 6.9 100.0 5,202 27.0 Sindh 13.0 19.9 34.1 16.7 8.3 7.9 100.0 2,118 28.4 Khyber Pakhtunkhwa 11.7 16.1 31.7 19.0 11.9 9.7 100.0 1,279 32.0 Balochistan 16.4 22.8 35.7 14.1 7.0 3.9 100.0 492 26.5 ICT Islamabad 15.9 16.3 29.6 18.0 11.4 8.8 100.0 34 31.0 Gilgit Baltistan 12.6 19.1 34.0 18.9 7.7 7.7 100.0 69 29.9 Education No education 17.1 18.9 33.1 16.3 7.7 7.0 100.0 5,679 28.1 Primary 20.2 18.5 31.1 17.6 5.5 7.2 100.0 1,509 27.2 Middle 16.0 20.1 31.7 15.1 8.5 8.6 100.0 646 28.2 Secondary 16.3 19.1 31.2 15.9 9.1 8.4 100.0 792 28.4 Higher 19.8 20.6 26.2 16.3 8.5 8.7 100.0 569 28.1 Wealth quintile Lowest 15.5 21.3 35.7 16.0 6.4 5.2 100.0 2,387 27.6 Second 19.6 18.6 32.3 15.2 7.6 6.8 100.0 2,023 27.4 Middle 18.5 18.7 31.3 17.0 7.2 7.3 100.0 1,798 28.3 Fourth 19.7 17.7 29.3 18.4 6.4 8.5 100.0 1,698 27.6 Highest 14.6 17.7 29.7 15.5 11.7 10.8 100.0 1,287 30.0 Total 17.6 19.0 32.1 16.4 7.5 7.3 100.0 9,194 28.0 Note: First-order births are excluded. The interval for multiple births is the number of months since the preceding pregnancy that ended in a live birth. Figures in parentheses are based on 25-49 unweighted cases. Taken as a whole, 37 percent of Pakistani children are born less than 24 months after a previous birth, an interval perceived to be “too short.” There has been a 3 percentage point increase in this proportion since 2006-07, which should be a cause for concern among population and health policymakers and planners. The largest proportion (53 percent) of children born less than 24 months after a previous birth is observed among children whose preceding sibling died. 5.5 POSTPARTUM AMENORRHEA, ABSTINENCE, AND INSUSCEPTIBILITY Postpartum amenorrhea is defined as the period between childbirth and the resumption of menstruation after childbirth, which generally approximates the return of ovulation. This period is largely determined by the duration and intensity of breastfeeding. The risk of conception in this period is very low. The duration of postpartum amenorrhea and sexual abstinence after birth determines the length of the insusceptibility period. Thus, women are considered insusceptible if they either are abstaining from sex 76 • Fertility after childbirth or are amenorrheic. In the 2012-13 PDHS, women who gave birth in the five years preceding the survey were asked about the duration of amenorrhea and sexual abstinence after each birth. The results are presented in Table 5.9 for the three years before the survey. The results show that almost all women (95 percent) are insusceptible to pregnancy within the first two months after childbirth due to amenorrhea and abstinence. However, after the second month, the proportions of women who are amenorrheic, and especially those who are abstaining, fall sharply. At six to seven months after birth, 31 percent of women are still amenorrheic, but only 6 percent are abstaining. Thus, the principal determinant of the length of the period of insusceptibility is postpartum amenorrhea. Table 5.9 Postpartum amenorrhea, abstinence, and insusceptibility Percentage of births in the three years preceding the survey for which mothers are postpartum amenorrheic, abstaining, and insusceptible, by number of months since birth, and median and mean durations, Pakistan 2012-13 Months since birth Percentage of births for which the mother is: Number of births Amenorrheic Abstaining Insusceptible1 <2 90.4 85.8 94.8 326 2-3 50.3 28.4 61.6 475 4-5 43.1 9.0 47.9 437 6-7 30.7 5.6 32.9 320 8-9 27.9 4.4 30.0 383 10-11 19.8 6.5 23.2 352 12-13 14.1 4.8 17.7 478 14-15 10.3 4.9 14.8 448 16-17 6.4 1.4 7.2 403 18-19 6.2 2.8 9.0 342 20-21 2.9 0.7 3.6 258 22-23 1.7 4.7 6.3 310 24-25 3.2 0.8 3.8 504 26-27 0.9 1.0 1.8 478 28-29 0.9 0.2 1.1 414 30-31 0.0 1.3 1.4 380 32-33 0.6 1.3 1.9 322 34-35 0.7 1.2 1.9 336 Total 17.2 8.8 20.1 6,965 Median 3.6 2.0 4.4 na Mean 6.5 3.6 7.5 na Note: Estimates are based on status at the time of the survey. na = Not applicable 1 Includes births for which mothers are either still amenorrheic or still abstaining (or both) following birth Overall, the median duration of amenorrhea is 3.6 months, the median for abstinence is 2.0 months, and the median for insusceptibility is 4.4 months. The duration of amenorrhea, abstinence, and insusceptibility has decreased slightly since 2006-07, but there has been a major drop, particularly in postpartum amenorrhea (2.7 months), since 1990-91. As breastfeeding duration is closely related to postpartum amenorrhea, the decrease in the mean duration of breastfeeding from 20.0 months in 1990-91 to 18.3 months in 2012-13 could be the major reason for this drop (see Table 11.4). Table 5.10 shows the median durations of postpartum amenorrhea, abstinence, and insusceptibility by respondents’ background characteristics. The median duration of abstinence in Pakistan does not vary much by background characteristics; therefore, insusceptibility varies directly in proportion to the duration of amenorrhea. Older women (age 30-49) have a longer median period of insusceptibility (5.7 months) than those age 15-29 (4.0 months). Women living in rural areas also have a longer median duration of amenorrhea and hence a longer period of insusceptibility than urban women (5.1 and 3.4 months, respectively). Among regions, women in Gilgit Baltistan have the longest duration of postpartum amenorrhea. The median duration of postpartum amenorrhea generally declines as wealth status increases. The poorest women have the longest duration of amenorrhea and insusceptibility but have a shorter duration of abstinence. Fertility • 77 Table 5.10 Median duration of amenorrhea, postpartum abstinence, and postpartum insusceptibility Median number of months of postpartum amenorrhea, postpartum abstinence, and postpartum insusceptibility following births in the three years preceding the survey, by background characteristics, Pakistan 2012- 13 Background characteristic Postpartum amenorrhea Postpartum abstinence Postpartum insusceptibility1 Mother’s age 15-29 3.2 2.0 4.0 30-49 4.5 2.0 5.7 Residence Urban 2.6 2.1 3.4 Rural 4.0 2.0 5.1 Region Punjab 3.4 2.2 4.4 Sindh 4.1 1.7 4.3 Khyber Pakhtunkhwa 4.5 2.0 5.5 Balochistan 1.8 2.0 2.8 ICT Islamabad 3.6 2.2 4.5 Gilgit Baltistan 6.0 2.1 6.1 Education No education 4.5 2.0 5.5 Primary 3.3 2.1 4.1 Middle 2.4 2.0 3.5 Secondary 2.4 2.1 3.4 Higher 2.4 2.0 3.2 Wealth quintile Lowest 8.1 1.7 8.3 Second 3.6 2.3 4.4 Middle 3.8 2.0 4.8 Fourth 2.5 2.1 3.7 Highest 2.5 2.2 3.1 Total 3.6 2.0 4.4 Note: Medians are based on status at the time of the survey (current status). 1 Includes births for which mothers are either still amenorrheic or still abstaining (or both) following birth While the start of infecundity is difficult to determine for an individual woman, there are ways of estimating it for a given population. One indicator of infecundity is the onset of menopause. Menopausal women are defined in the PDHS as women who are neither pregnant nor postpartum amenorrheic and who have not had a menstrual period in the six months before the survey. Table 5.11 shows the percentage of women age 30-49 who are menopausal. Overall, 13 percent of women in the 30-49 age group reported that they were menopausal. This proportion was 12 percent in both 2006-07 and 1990-91. As expected, menopause increases steadily with age, from only 2 percent of women age 30-34 to more than half of women age 45-49. 5.6 AGE AT FIRST BIRTH The onset of childbearing has a direct bearing on fertility. Early initiation into childbearing lengthens the reproductive period, which in turns increases the chances of higher fertility. Bearing children at a young age also entails risks to the health of the mother and the child. Table 5.12 shows the median age at first birth as well as the percentage of women who gave birth by a given exact age, by five-year age groups of women. According to this table, the median age at first birth for women age 25-49 is 22.2 years, an increase of 0.9 years since the 1990-91 PDHS. The largest increase (2.4 years) since 1990-91 in the median age at first birth is among women age 25-29. Table 5.11 Menopause Percentage of women age 30-49 who are menopausal, by age, Pakistan 2012-13 Age Percentage menopausal1 Number of women 30-34 1.7 2,528 35-39 4.5 2,226 40-41 12.5 869 42-43 20.5 653 44-45 29.2 667 46-47 30.1 575 48-49 51.6 603 Total 13.1 8,123 1 Percentage of all women who are not pregnant and not postpartum amenorrheic whose last menstrual period occurred 6 or more months preceding the survey 78 • Fertility Among the age groups for which the median age at first birth can be measured, the age group with the highest median age is 25-29 years. This pattern is in congruence with the declining fertility rate, particularly among younger women (see Tables 5.3 and 5.5). Additional insights into initiation of childbearing can be gained by examining the percentage of women who had a first birth by the given exact ages for various age groups of women. This percentage increases progressively by increasing exact ages; the proportion of women having their first birth by age 18, for instance, is lower among younger women than older women. This observation is consistent with the rising age at first birth. Table 5.12 Age at first birth Percentage of women age 15-49 who gave birth by exact ages, percentage who have never given birth, and median age at first birth, according to current age, Pakistan 2012-13 Current age Percentage who gave birth by exact age Percentage who have never given birth Number of women Median age at first birth 15 18 20 22 25 Age 15-19 0.1 na na na na 94.6 4,269 a 20-24 0.8 8.2 20.5 na na 63.2 4,183 a 25-29 1.6 12.0 25.4 40.5 60.1 31.3 3,421 23.4 30-34 1.3 14.3 31.3 45.6 64.2 13.2 2,725 22.6 35-39 1.8 16.1 33.9 52.6 71.9 7.6 2,296 21.7 40-44 2.2 18.1 39.8 57.6 75.8 6.6 1,804 21.2 45-49 2.3 18.6 37.2 54.0 77.1 4.5 1,623 21.5 20-49 1.5 13.3 29.2 na na 27.7 16,052 a 25-49 1.8 15.2 32.2 48.5 68.0 15.2 11,869 22.2 na = Not applicable due to censoring a = Omitted because less than 50 percent of women had a birth before reaching the beginning of the age group Differentials in age at first birth by socioeconomic and demographic characteristics of women age 25-49 are shown in Table 5.13. A higher median age at first birth is observed in urban areas (23.0 years) than in rural areas (21.8 years). Among the regions, the highest median age at first birth for women age 25-49 is recorded in ICT Islamabad (24.5 years), followed by Punjab (22.5 years), Sindh (21.9 years), Khyber Pakhtunkhwa (21.7 years), and Balochistan (21.3 years); the lowest age was reported in Gilgit Baltistan (21.2 years). This implies that, on average, women in Gilgit Baltistan and Balochistan have their first birth a little over one year earlier than women in Punjab and over three years earlier than women in ICT Islamabad. Intra-provincial differences between urban and rural areas are not marked and more or less follow the pattern evidenced at the national level. Clearly, onset of childbearing is related to women’s education. According to Table 5.13, women with a secondary education begin their childbearing three years later than women with no education (24.2 years and 21.1 years, respectively). Also, wealthier women show delayed onset of childbearing relative to poorer women. 5.7 TEENAGE FERTILITY It is important to examine teenage fertility for various reasons. First, children born to very young mothers are normally prone to a higher risk of illness and death. Second, teenage mothers are more likely to experience complications during pregnancy and are less likely to be prepared to deal with them, putting them at higher risk of maternal death. Third, their early entry into reproduction denies them the opportunity to Table 5.13 Median age at first birth Median age at first birth among women age 25-49, according to background characteristics, Pakistan 2012-13 Background characteristic Women age 25-49 Residence Urban 23.0 Rural 21.8 Region Punjab 22.5 Urban 23.3 Rural 22.1 Sindh 21.9 Urban 22.8 Rural 21.3 Khyber Pakhtunkhwa 21.7 Urban 21.5 Rural 21.8 Balochistan 21.3 Urban 21.9 Rural 21.2 ICT Islamabad 24.5 Gilgit Baltistan 21.2 Education No education 21.1 Primary 21.8 Middle 22.3 Secondary 24.2 Higher a Wealth quintile Lowest 20.8 Second 21.5 Middle 21.7 Fourth 22.5 Highest 24.1 Total 22.2 a = Omitted because less than 50 percent of the women had a birth before reaching the beginning of the age group Fertility • 79 pursue academic goals. This is detrimental to their prospects for good careers and often lowers their status in society. Table 5.14 displays the percentage of women age 15-19 who were mothers or were pregnant with their first child at the time of the 2012-13 PDHS, by selected background characteristics. Overall, teenage fertility has declined; for example, the proportion who have begun childbearing decreased from about 16 percent in 1990-91 to 8 percent in 2012-13. Also, there have been decreases in the proportion of teenage mothers (from 12 percent to 5 percent) and the proportion of young women pregnant with their first child (from 4 percent to less than 3 percent). These findings suggest that there is a trend toward delayed childbearing until at least the completion of the teenage years. Table 5.14 Teenage pregnancy and motherhood Percentage of women age 15-19 who have had a live birth or who are pregnant with their first child, and percentage who have begun childbearing, by background characteristics, Pakistan 2012-13 Background characteristic Percentage of women age 15-19 who: Percentage who have begun childbearing Number of women Have had a live birth Are pregnant with first child Age 15 0.0 0.0 0.0 641 16 0.4 0.5 0.9 937 17 3.4 4.1 7.5 828 18 8.8 3.7 12.5 1,143 19 13.6 3.2 16.8 720 Residence Urban 3.9 1.5 5.5 1,515 Rural 6.2 2.9 9.1 2,776 Region Punjab 4.7 2.7 7.4 2,287 Sindh 5.5 2.5 7.9 1,039 Khyber Pakhtunkhwa 8.0 2.2 10.3 660 Balochistan 5.3 1.5 6.8 188 ICT Islamabad * * * 13 Gilgit Baltistan 5.5 1.0 6.5 40 Education No education 8.7 4.2 12.9 1,328 Primary 7.7 2.8 10.5 682 Middle 2.4 1.2 3.7 1,102 Secondary 2.8 1.9 4.8 776 Higher (2.9) (0.4) (3.2) 445 Wealth quintile Lowest 7.1 4.4 11.5 755 Second 5.9 2.4 8.3 925 Middle 7.6 1.9 9.5 897 Fourth 3.6 2.5 6.1 893 Highest 2.3 1.1 3.3 971 Total 5.4 2.5 7.9 4,269 Note: As the survey was based on an ever-married sample, the number of women was increased using a factor based on all de facto women listed in the household who had never been married. The “all women” factors were based on age in the household and background information available at the household level. Women who have never married are assumed to have never been pregnant. Because the number of all women is not normalized, the weighted numbers will not necessarily sum to the “total.” 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. As expected, the proportion of teenagers who have begun childbearing increases with age. For example, at age 15 no women have begun childbearing, and by age 16 only 1 percent have begun childbearing. This proportion increases to 17 percent by age 19. The percentage of teenagers who have begun childbearing is highest in Khyber Pakhtunkhwa (10 percent) and lowest in Gilgit Baltistan and Balochistan (7 percent each). About 13 percent of teenage women with no education have begun childbearing, as compared with less than 5 percent of women with at least a middle school education. 80 • Fertility Teenagers from the poorest households are more likely (12 percent) to have begun childbearing than those from the wealthiest households (3 percent). Other important factors affecting level of fertility are abortion, miscarriage, and stillbirth. In Pakistan, induced abortion is illegal except in instances in which the life of the mother is at risk. Hence, it is extremely difficult to gather accurate information about the level of induced abortion. In the pregnancy history, women were asked about the outcome of each of their pregnancies (i.e., live birth, stillbirth, or pregnancy lost before full term). In the case of pregnancies that did not end in live births, additional questions were asked about date of termination, duration of pregnancy, and status of termination (induced abortion or miscarriage). Table 5.15 shows that 12 percent of pregnancies resulted in a miscarriage in the five years before the survey; about 2 percent resulted in an abortion, and 3 percent resulted in a stillbirth. Table 5.15 Pregnancy outcomes by background characteristics Percent distribution of pregnancies ending in the five years preceding the survey by type of outcome, according to background characteristics, Pakistan 2012-13 Background characteristic Pregnancy outcome Total Number of pregnancies Live birth Stillbirth Miscarriage Abortion Age at end of pregnancy <20 81.4 3.5 13.7 1.4 100.0 1,335 20-24 85.2 2.7 11.4 0.7 100.0 4,299 25-29 84.1 2.9 11.4 1.6 100.0 4,318 30-34 83.2 2.8 11.5 2.6 100.0 2,789 35-39 81.4 2.4 13.5 2.7 100.0 1,204 40-44 73.4 1.6 18.6 6.4 100.0 363 45-49 71.3 5.4 22.1 1.2 100.0 42 Pregnancy order 1 83.3 4.1 11.9 0.7 100.0 2,840 2 86.0 2.2 10.9 0.9 100.0 2,590 3 85.1 2.3 11.4 1.2 100.0 2,163 4 84.4 2.4 11.0 2.2 100.0 1,744 5+ 81.2 2.7 13.4 2.8 100.0 5,012 Residence Urban 83.1 1.9 12.6 2.4 100.0 4,199 Rural 83.6 3.2 11.8 1.4 100.0 10,151 Region Punjab 83.5 2.7 11.3 2.4 100.0 8,213 Sindh 83.0 3.0 13.3 0.7 100.0 3,301 Khyber Pakhtunkhwa 84.8 2.3 11.8 1.1 100.0 1,951 Balochistan 80.9 3.7 15.2 0.2 100.0 729 ICT Islamabad 80.5 1.5 14.5 3.5 100.0 58 Gilgit Baltistan 89.4 0.7 9.3 0.7 100.0 97 Education No education 83.8 3.2 11.7 1.3 100.0 8,178 Primary 83.4 2.7 12.0 1.9 100.0 2,445 Middle 82.8 2.3 12.9 2.0 100.0 1,093 Secondary 82.7 1.7 12.0 3.7 100.0 1,462 Higher 83.0 1.6 13.8 1.6 100.0 1,172 Wealth quintile Lowest 83.6 3.9 12.3 0.3 100.0 3,426 Second 84.0 3.1 11.9 1.0 100.0 3,018 Middle 85.1 2.6 9.9 2.3 100.0 2,755 Fourth 83.3 2.3 12.3 2.1 100.0 2,819 Highest 80.8 1.6 13.9 3.7 100.0 2,331 Total 83.5 2.8 12.0 1.7 100.0 14,350 Given that induced abortions are illegal, it is likely that some induced abortions are reported as miscarriages. Differences by background characteristics are generally not large except that miscarriages occur 7-11 percent more often among women age 40 and above at the end of their pregnancy than among women age 20-34 at the end of their pregnancy. Fertility Preferences • 81 FERTILITY PREFERENCES 6 nformation on fertility preferences is of fundamental importance to family planning programs and policies. This chapter presents data from the 2012-13 PDHS on fertility preferences and family size norms of Pakistani women and men. The survey collected information from ever-married women and men age 15-49 on a number of aspects of fertility preferences. The resulting data are used to quantify fertility preferences: whether couples want more children, want to cease childbearing altogether, or want to delay the next pregnancy. Ideal number of children is another important indicator of fertility preferences that shows the number of children a woman or man would want if she or he could start afresh. This chapter also includes information on unwanted and mistimed pregnancies and trends in current fertility rates. Moreover, the extent to which fertility preferences differ between Pakistani women and men is assessed. Interpretation of data on fertility preferences is often difficult since it is understood that respondents’ reported preferences are, in a sense, hypothetical and thus subject to change and rationalization. Still, data on fertility preferences indicate the direction of future fertility to the extent that individuals and couples will act to achieve their preferred family sizes. A woman’s fertility preferences may not necessarily predict her reproductive behavior, because childbearing decisions in Pakistani society are not made solely by the woman but are frequently affected by the attitudes of other family members, particularly the husband and the mother-in-law, both of whom may exert a major influence on reproductive decisions. 6.1 DESIRE FOR MORE CHILDREN Information about the desire for more children is important for understanding future reproductive behavior. The provision of adequate and accessible family planning services depends on the availability of such information. In the 2012-13 PDHS, currently married, non-sterilized, non-pregnant women were asked “Would you like to have (a/another) child, or would you prefer not to have any (more) children?” If the response was in the affirmative, they were asked “How long would you like to wait from now before the birth of (a/another) child?” Questions asked of currently married, non-sterilized, pregnant women were phrased in a slightly different manner. These women were asked “After the child you are expecting now, would you like to have another child, or would you prefer not to have any more children?” In the case of an affirmative answer, they were asked “After the birth of the child you are expecting now, how long would you like to wait before the birth of another child?” Table 6.1 presents the distribution of currently married women and men age 15-49 by desire for more children, according to number of living children. The proportion of women and men who want I Key Findings • More than half of currently married women age 15-49 and two-fifths of currently married men age 15-49 want no more children or are sterilized. • Women and men report an ideal family size of more than four children. The mean ideal number of children among currently married women has remained unchanged at 4.1 children in the last two decades. • Overall, Pakistani women have about one child more than their wanted number. This implies that the total fertility rate of 3.8 children per woman is 31 percent higher than it would be if all unwanted births were avoided. • There has been a substantial increase in planned births since 2006-07, from 75 percent to 84 percent. 82 • Fertility Preferences another child generally decreases with increasing number of living children. At the same time, the proportion of women and men who want to stop childbearing (including those sterilized) increases with increasing number of living children. Overall, 23 percent of women and 30 percent of men want to have another child soon (within two years), while 19 percent of women and 21 percent of men want another child two or more years later. More than half of women (including those who are sterilized or whose husbands are sterilized) and two-fifths of men (including those who are sterilized or who say that their wives are sterilized) do not want any more children. Table 6.1 Fertility preferences by number of living children Percent distribution of currently married women and currently married men age 15-49 by desire for children, according to number of living children, Pakistan 2012-13 Desire for children Number of living children Total 15- 49 0 1 2 3 4 5 6+ WOMEN1 Have another soon2 87.0 40.9 25.1 14.1 7.9 4.4 1.6 23.0 Have another later3 1.9 46.2 38.8 22.7 8.8 5.9 2.6 19.1 Have another, undecided when 1.5 3.7 2.0 1.4 0.9 0.4 0.8 1.5 Undecided 1.8 2.7 5.5 4.7 2.9 3.5 2.8 3.5 Want no more 1.7 5.4 25.2 46.7 63.9 68.9 73.2 42.3 Sterilized4 0.0 0.3 1.8 9.0 14.8 16.1 18.2 8.9 Declared infecund 6.1 0.7 1.5 1.0 0.7 0.8 0.7 1.4 Missing 0.0 0.2 0.2 0.4 0.2 0.0 0.1 0.2 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Number 1,326 1,867 2,114 2,006 1,906 1,410 2,307 12,937 MEN5 Have another soon2 87.4 48.9 38.9 24.6 9.2 6.6 5.8 30.0 Have another later3 7.1 44.0 35.6 23.9 12.9 10.2 7.3 20.8 Have another, undecided when 1.6 1.1 1.7 3.0 1.8 1.5 0.0 1.6 Undecided 0.0 2.3 4.0 6.3 10.1 8.0 5.6 5.3 Want no more 0.9 2.9 19.2 39.6 58.3 66.0 69.9 37.5 Sterilized4 0.4 0.1 0.7 2.6 7.0 7.4 10.9 4.2 Declared infecund 2.5 0.6 0.0 0.0 0.5 0.3 0.4 0.5 Missing 0.1 0.0 0.0 0.0 0.2 0.0 0.0 0.0 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Number 346 419 510 487 470 365 474 3,071 1 The number of living children includes the current pregnancy. 2 Wants next birth within 2 years 3 Wants to delay next birth for 2 or more years 4 Includes both female and male sterilization 5 The number of living children includes one additional child if the respondent’s wife is pregnant (or, among men with more than one current wife, if any wife is pregnant). Desire to limit childbearing (including those women who are sterilized or whose husbands are sterilized) increases with increasing number of living children, from 2 percent among women with no children to 91 percent among women with six or more children. A comparison of data from the 2006-07 and 2012-13 PDHS surveys shows no change in the proportion of currently married women who want no more children or have been sterilized (51 percent). In the case of married men, the desire to limit childbearing increases from 1 percent among those with no children to 81 percent among those with six or more children. There are considerable differences between women and men who want more children by number of living children. The proportion of currently married women who want more children decreases from 87 percent among those with one child to 4 percent among those with six or more living children. In contrast, the proportion of currently married men who want more children decreases from 93 percent among those with one child to 13 percent among those with six or more living children. Fertility Preferences • 83 The percentage of women who want to limit childbearing increases rapidly with increasing number of living children, peaking at 89 to 95 percent among women with six or more children in every province except Balochistan, where it peaks at only 60 percent (Appendix Table A6.1.1). Patterns in desire for more children by number of living children among women in Punjab and Khyber Pakhtunkhwa are similar to national patterns, while in Sindh the proportion of women who want more children deceases from 93 percent among those with one child to 8 percent among those with six or more children. Seventy percent of women in Balochistan with one child and 10 percent with six or more children desire more children; however, higher percentages of men than women in every province want more children, with a particularly large differential in Balochistan province (Appendix Table A6.1.2). Balochistan has particularly high proportions of women (22 percent) and men (12 percent) who are undecided about whether or not they want another child. 6.2 DESIRE TO LIMIT CHILDBEARING BY BACKGROUND CHARACTERISTICS Tables 6.2.1 and 6.2.2 provide information on differences in the desire to limit childbearing by background characteristics. Overall, at every parity, urban women are considerably more likely than rural women to want no more children. For example, among women with three children, 66 percent of urban women and 50 percent of rural women want no more children. There is only a slight urban-rural differential in the desire to limit childbearing among women with six or more children (93 percent and 91 percent, respectively), since very few of these women, regardless of area of residence, want another child. At the regional level, women in ICT Islamabad are twice as likely to want to limit childbearing as women in Balochistan (60 percent and 29 percent, respectively). Among other regions, slightly more than half of women in Punjab, Khyber Pakhtunkhwa, and Gilgit Baltistan want no more children. At parity three and four, the proportion of women who want no more children is considerably higher in ICT Islamabad and Punjab than in the other regions. The proportion of men who want no more children is lowest by far in Balochistan and highest in Gilgit Baltistan, ICT Islamabad, and Punjab. Overall, women and men with no education have a greater desire to limit childbearing than those with higher levels of education. However, women and men with two or more children are generally the least likely to want to limit childbearing within each parity (Tables 6.2.1 and 6.2.2). This pattern is likely due to the larger number of children borne by women with no education. The proportion of women and men who want no more children is positively associated with wealth, although there is relatively little difference in the highest three wealth quintiles. 84 • Fertility Preferences Table 6.2.1 Desire to limit childbearing: Women Percentage of currently married women age 15-49 who want no more children, by number of living children, according to background characteristics, Pakistan 2012-13 Background characteristic Number of living children1 Total 0 1 2 3 4 5 6+ Residence Urban 3.7 7.2 35.1 65.5 83.2 93.2 93.4 54.7 Rural 0.8 4.8 22.1 49.9 76.1 81.2 90.8 49.4 Region Punjab 2.3 5.7 27.5 62.1 85.8 90.7 95.4 54.0 Sindh 0.7 5.7 28.3 49.5 69.1 77.7 89.0 46.8 Khyber Pakhtunkhwa 0.9 6.4 26.5 46.9 75.1 87.8 94.9 53.4 Balochistan 0.9 0.9 10.1 21.8 34.1 39.4 59.8 28.9 ICT Islamabad 1.3 7.5 37.3 81.8 90.6 92.1 93.2 60.3 Gilgit Baltistan 2.2 3.6 18.2 43.3 65.9 70.5 86.3 50.8 Education No education 1.4 6.7 21.7 49.1 73.1 82.1 90.7 55.0 Primary 3.7 3.3 23.8 57.9 85.6 91.2 94.6 50.1 Middle 1.1 3.5 26.5 65.2 80.7 84.5 95.0 46.0 Secondary 2.2 6.0 32.5 60.8 90.2 95.2 95.2 45.0 Higher 0.0 5.8 41.2 69.8 86.1 96.0 (98.2) 41.1 Wealth quintile Lowest 0.0 4.7 13.4 32.4 60.4 69.2 85.2 43.8 Second 0.9 4.9 22.6 47.4 75.6 76.0 90.0 49.5 Middle 0.8 4.9 21.4 60.2 78.9 95.3 94.4 55.2 Fourth 2.6 7.3 32.4 60.2 83.6 90.1 95.6 52.4 Highest 3.9 5.7 37.5 69.7 91.3 93.4 97.8 54.8 Total 1.7 5.6 27.0 55.7 78.6 85.0 91.5 51.2 Note: Women who have been sterilized are considered to want no more children. Figures in parentheses are based on 25-49 unweighted cases. 1 The number of living children includes the current pregnancy. Table 6.2.2 Desire to limit childbearing: Men Percentage of currently married men age 15-49 who want no more children, by number of living children, according to background characteristics, Pakistan 2012-13 Background characteristic Number of living children1 Total 0 1 2 3 4 5 6+ Residence Urban 2.5 0.5 28.5 44.9 71.3 79.3 84.7 45.8 Rural 0.7 4.2 13.8 40.4 61.9 68.9 79.4 39.5 Region Punjab 0.6 3.5 19.5 49.7 74.8 81.5 90.6 47.5 Sindh 1.2 0.4 22.5 34.9 55.7 61.9 77.8 35.3 Khyber Pakhtunkhwa 4.5 7.6 20.1 20.0 46.3 77.4 71.3 35.1 Balochistan (1.0) 0.6 7.3 6.0 18.2 22.1 46.2 20.3 ICT Islamabad * (2.2) 26.9 63.5 (90.1) (84.6) * 47.7 Gilgit Baltistan * (0.0) (13.6) (51.4) (74.0) (67.7) (89.4) 50.6 Education No education 1.3 8.3 12.0 41.1 52.1 67.9 79.2 45.2 Primary 0.0 4.1 23.9 37.2 73.9 75.0 84.6 42.8 Middle 3.3 1.8 15.8 42.1 64.4 (89.4) 82.2 41.0 Secondary 1.3 0.0 22.2 42.5 75.0 62.4 82.7 39.9 Higher 0.0 0.1 25.2 49.0 66.0 84.6 75.3 36.9 Wealth quintile Lowest 0.0 4.2 8.3 23.7 42.3 49.6 67.8 30.9 Second 1.7 3.5 9.0 27.0 60.9 66.3 79.5 37.8 Middle (2.3) 6.1 29.5 38.5 56.9 89.5 88.1 48.5 Fourth 2.4 2.1 19.0 56.9 83.6 70.0 86.0 45.4 Highest 0.0 0.1 30.8 49.1 76.1 82.8 92.3 45.1 Total 1.2 3.1 19.9 42.2 65.3 73.4 80.8 41.7 Note: Men who have been sterilized or who state, in response to the question about desire for children, that their wife has been sterilized are considered to want no more children. 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 The number of living children includes one additional child if the respondent’s wife is pregnant (or, among men with more than one current wife, if any wife is pregnant). Fertility Preferences • 85 Fertility preferences depend not only on the total number of living children, but also on the sex composition of the children. One way to measure preference for sons is to examine the proportion of women who want no more children by the number of sons they already have. Because the desire to stop childbearing depends on total number of children as well as sex composition, the data are broken down by number of children (Table 6.3). The results show that there is a strong preference for sons in Pakistan. For example, among women with three children, 60 percent of those with three sons want to have no more children, as compared with only 21 percent of those with three daughters. Similarly, among women with five children, about 90 percent of those with two to four sons say they want no more children, as compared with 73 percent of those with no sons or only one son. The proportion of women who want no more children drops to 76 percent among women with five sons and no daughters, probably because of a desire to have at least one daughter. 6.3 IDEAL FAMILY SIZE The discussion of fertility preferences earlier in this chapter focused on respondents’ current childbearing preferences. These preferences are influenced by the number of children a respondent already has. The 2012-13 PDHS also asked women and men age 15-49 about the total number of children they would like to have in their lifetime if they could choose the exact number to have at the time they had no children. Even though this question is based on a hypothetical situation, it provides two important measures. First, for women and men who have not started a family, the data indicate how many children would be ideal for them to have in the future. Second, for older and high- parity women, the excess of past fertility over the ideal family size provides a measure of unwanted fertility. Four percent of women gave non-numeric answers to the question on ideal number of children, such as “up to God/Allah,” and the proportion of such responses exhibited a curvilinear relationship with number of living children (Table 6.4). The proportion of respondents providing non-numeric responses was higher among men (7 percent). Both ever-married and currently married women and men in Pakistan still prefer four children, on average, as their ideal family size (4.1 children for women and 4.3 children for men). Four in 10 women would want to have four children, and one-third of men would want to have four children. Only 14 percent of women prefer a two-child family, and another 16 percent consider three children as their ideal family size. Among men, 10 percent and 17 percent, respectively, prefer two children and three children as their ideal family size. Table 6.3 Desire to limit childbearing by sex of living children Percentage of currently married, non-pregnant women age 15-49 who want no more children, by number of living children and sons, Pakistan 2012-13 Number of living children and sons Percentage who want no more children or are sterilized Number of women No children 1.7 1,326 One child No sons 5.9 693 One son 7.2 771 Two children No sons 10.7 357 One son 31.6 953 Two sons 37.3 495 Three children No sons 20.5 162 One son 50.5 563 Two sons 71.2 791 Three sons 60.0 212 Four children No sons 43.9 100 One son 71.4 364 Two sons 87.6 675 Three sons 85.0 463 Four sons 77.1 135 Five children No sons/one son 72.7 153 Two sons 90.6 373 Three sons 90.0 449 Four sons 89.9 254 Five sons 76.2 45 More than 5 children No sons/one son 82.0 138 Two sons 89.8 415 Three sons 94.1 581 Four sons 94.8 511 Five sons 95.0 297 Six or more sons 94.6 200 Total 53.6 11,478 86 • Fertility Preferences Table 6.4 Ideal number of children by number of living children Percent distribution of ever-married women and ever-married men age 15-49 by ideal number of children, and mean ideal number of children for all respondents and for currently married respondents, according to the number of living children, Pakistan 2012-13 Number of living children Total Ideal number of children 0 1 2 3 4 5 6+ WOMEN1 0 1.2 0.2 0.5 0.5 0.5 1.4 0.5 0.6 1 3.1 1.4 0.2 0.6 0.3 0.0 0.1 0.7 2 25.3 22.7 22.2 11.2 9.7 6.7 4.4 14.2 3 14.7 20.8 22.0 27.6 8.1 10.3 5.2 15.6 4 36.0 36.7 40.3 40.9 56.0 34.8 30.0 39.3 5 7.0 7.5 5.5 6.2 9.1 22.4 10.9 9.4 6+ 9.0 8.6 7.7 9.8 12.9 18.0 40.2 16.0 Non-numeric responses 3.7 2.0 1.7 3.2 3.3 6.3 8.7 4.2 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Number 1,425 1,989 2,195 2,095 1,958 1,465 2,431 13,558 Mean ideal number of children for:2 Ever-married women 3.5 3.6 3.6 3.8 4.2 4.5 5.3 4.1 Number of ever-married women 1,372 1,949 2,159 2,027 1,893 1,372 2,220 12,992 Currently married women 3.6 3.6 3.6 3.8 4.2 4.5 5.3 4.1 Number of currently married women 1,293 1,842 2,080 1,941 1,844 1,319 2,105 12,425 MEN3 0 1.1 0.7 1.3 2.1 3.7 1.1 3.3 2.0 1 0.7 0.8 0.0 0.4 0.0 0.0 0.0 0.3 2 24.0 13.1 14.9 4.2 6.1 2.8 3.2 9.5 3 17.3 28.1 20.4 25.6 11.1 11.4 5.3 17.2 4 33.4 34.4 38.5 34.3 44.9 24.1 18.8 32.9 5 9.3 9.5 12.4 13.8 12.6 23.4 10.2 12.8 6+ 6.4 8.4 8.6 12.7 16.4 27.4 47.2 18.2 Non-numeric responses 7.7 5.1 3.9 6.9 5.2 9.8 12.2 7.1 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Number 374 432 516 499 470 369 474 3,134 Mean ideal number of children for:2 Ever-married men 3.5 3.7 3.8 4.1 4.3 4.9 5.9 4.3 Number of ever-married men 345 410 496 465 446 333 416 2,910 Currently married men 3.6 3.7 3.8 4.1 4.3 4.9 5.9 4.3 Number of currently married men 330 397 491 457 445 329 416 2,866 1 The number of living children includes the current pregnancy. 2 Means are calculated excluding respondents who gave non-numeric responses. 3 The number of living children includes one additional child if the respondent’s wife is pregnant (or, men with more than one current wife, if any wife is pregnant). It is important to note that the mean ideal number of children reported by women remains unchanged from the 1990-91 PDHS (i.e., 4.1 children). This clearly indicates a preference for large families in Pakistani society. It also is likely to be a contributing factor to the slow pace of fertility decreases in Pakistan. Table 6.4 further shows that mean ideal number of children increases with increasing number of living children, from 3.5 children among both women and men with no children to 5.3 children among women with six or more children and 5.9 children among men with six or more children. Two factors contribute to this positive association between actual and ideal number of children. First, to the extent that women are able to implement their fertility desires, those who want smaller families will tend to achieve smaller families. Second, some women may have difficulty admitting their desire for fewer children if they could begin childbearing again and may in fact report their actual number as their preferred number. Despite this tendency to rationalize, the data provide evidence of unwanted fertility, as the vast majority of women with six or more children reported an ideal family size of less than six children. Table 6.5 presents the mean ideal number of children among currently married women and men age 15-49 by selected background characteristics. The mean ideal number of children increases with increasing age, ranging from 3.7 children among women age 15-24 and 4.0 among men in the same age group to 4.7 among both women and men age 45-49. Mean ideal number of children varies inversely with Fertility Preferences • 87 women and men’s level of education and wealth quintile. Among women, it ranges from 3.2 children for those with a higher education to 4.5 children for those with no education. Similarly, it ranges from 3.4 children among women in the highest wealth quintile to 5.0 children among women in the lowest quintile. A similar pattern is seen among currently married men age 15-49. Table 6.5 Mean ideal number of children Mean ideal number of children for ever-married women and men age 15-49 by background characteristics, Pakistan 2012-13 Background characteristic Women Men Mean Number1 Mean Number2 Age 15-19 3.7 589 (4.0) 34 20-24 3.7 2,059 4.0 211 25-29 3.9 2,648 4.0 493 30-34 4.0 2,437 3.9 590 35-39 4.2 2,131 4.3 533 40-44 4.3 1,652 4.7 493 45-49 4.7 1,476 4.7 557 Residence Urban 3.6 4,385 3.9 1,047 Rural 4.3 8,607 4.5 1,863 Region Punjab 3.8 7,449 3.9 1,636 Sindh 4.5 3,074 4.5 785 Khyber Pakhtunkhwa 4.1 1,765 4.9 308 Balochistan 6.1 549 7.1 147 ICT Islamabad 3.2 62 2.5 17 Gilgit Baltistan 4.8 93 4.4 18 Education No education 4.5 7,311 4.9 824 Primary 3.8 2,101 4.1 601 Middle 3.5 962 4.2 496 Secondary 3.3 1,377 4.0 516 Higher 3.2 1,240 3.9 472 Wealth quintile Lowest 5.0 2,484 5.1 567 Second 4.4 2,548 4.6 506 Middle 4.0 2,570 4.2 523 Fourth 3.7 2,670 3.9 666 Highest 3.4 2,720 3.8 647 Total 4.1 12,992 4.3 2,910 Note: Figures in parentheses are based on 25-49 unweighted cases. 1 Number of women who gave a numeric response 2 Number of men who gave a numeric response The ideal number of children for both women and men is lower by more than half a child in urban areas than in rural areas. Ideal family size among both women and men is highest by far in Balochistan (6.1 and 7.1 children, respectively) and lowest in ICT Islamabad (3.2 and 2.5 children, respectively). The urban-rural differential is particularly large in Sindh (3.7 children in urban areas and 5.1 children in rural areas). Smaller urban-rural differentials are observed in the other provinces (Appendix Table A6.2). As mentioned above, decisions about childbearing are usually made by couples and not by the woman herself. Women who were interviewed in the 2012-13 PDHS were asked if they thought that their husbands wanted the same number of children that they wanted or if they wanted more or fewer children. Table 6.6 shows that a majority of women (58 percent) say that their husbands want the same number of children as they do. However, more than one-fourth of women report that their husbands want more children than they want, while only 5 percent say that their husbands want fewer children than they want. 88 • Fertility Preferences Table 6.6 Couple’s agreement on family size Percent distribution of currently married, non-sterilized women by whether they think their husbands want the same number of children as they want, according to woman’s ideal number of children, Pakistan 2012-13 Ideal number of children Husband’s desire for children Total Number Both want same Husband wants more Husband wants fewer Don’t know/ missing 0 30.3 26.9 1.1 41.7 100.0 73 1 48.0 37.6 2.6 11.8 100.0 81 2 59.8 27.9 2.9 9.5 100.0 1,705 3 66.7 19.9 4.2 9.3 100.0 1,897 4 64.3 21.6 4.5 9.5 100.0 4,616 5 48.0 33.6 5.3 13.0 100.0 1,095 6+ 44.3 36.6 6.1 13.0 100.0 1,850 Non-numeric responses 30.6 33.7 5.8 30.0 100.0 469 Total 57.7 26.3 4.6 11.4 100.0 11,785 6.4 FERTILITY PLANNING Information collected in the 2012-13 PDHS can also be used to estimate levels of unwanted fertility. This information provides insight into the degree to which couples are able to control fertility. Women age 15-49 were asked a series of questions about each child born to them in the preceding five years, as well as any current pregnancy, to determine whether the birth or pregnancy was wanted then (planned), wanted later (mistimed), or not wanted at all (unplanned) at the time of conception. In assessing these results, it is important to recognize that women may declare a previously unwanted birth or current pregnancy as wanted, and this rationalization would result in an underestimate of the true extent of unwanted births. Table 6.7 shows that 8 in 10 births in the five years preceding the survey were planned, 9 percent were mistimed, and 7 percent were unwanted. There has been a substantial increase in planned births since 2006-07, from 75 percent to 84 percent. The proportion of births considered mistimed or unwanted has decreased from 24 percent to 16 percent since 2006-07. The proportion of wanted births decreases and the proportion of unwanted births increases substantially with increasing birth order. A similar pattern was found in the 1990-91 PDHS and 2006-07 PDHS surveys. Moreover, almost all first-order births are wanted, and 17 percent of fourth-order and higher order births are unwanted. A similar pattern is observed for mother’s age at the time of the birth. The proportion of planned births is highest (94 percent) among mothers in the youngest age group and then decreases consistently with increasing age. The percentage of unwanted births increases with mother’s age at the time of the birth, rising from 0.3 percent among those below age 20 to 46 percent among those age 45-49. Table 6.7 Fertility planning status Percent distribution of births to women age 15-49 in the five years preceding the survey (including current pregnancies), by planning status of the birth, according to birth order and mother’s age at birth, Pakistan 2012-13 Planning status of birth Total Number of births Birth order and mother’s age at birth Wanted then Wanted later Wanted no more Missing Birth order 1 98.7 1.0 0.0 0.3 100.0 3,165 2 87.3 12.0 0.5 0.1 100.0 2,726 3 84.5 12.6 2.5 0.4 100.0 2,199 4+ 73.9 9.4 16.5 0.2 100.0 5,349 Mother’s age at birth <20 94.4 4.9 0.3 0.4 100.0 1,205 20-24 90.2 8.5 1.1 0.2 100.0 4,082 25-29 83.4 11.3 5.0 0.2 100.0 4,087 30-34 79.2 8.4 12.1 0.3 100.0 2,627 35-39 72.6 3.7 23.7 0.0 100.0 1,103 40-44 63.0 2.7 33.9 0.4 100.0 295 45-49 52.9 0.6 45.5 1.0 100.0 40 Total 84.2 8.5 7.1 0.2 100.0 13,439 Fertility Preferences • 89 6.5 WANTED FERTILITY RATES The wanted fertility rate measures the potential demographic impact of avoiding unwanted births. It is calculated in the same manner as the total fertility rate but excludes unwanted births from the numerator. A birth is considered wanted if the number of living children at the time of conception is less than the ideal number of children reported by the respondent. The gap between wanted and actual fertility shows the extent to which women are successful in achieving their reproductive intentions. This measure may be an underestimate to the extent that women may not report an ideal family size lower than their actual family size. The total wanted fertility rates in Table 6.8 represent the levels of fertility that would have prevailed in the three years preceding the survey if all unwanted births had been avoided. Overall, Pakistani women have 0.9 children more than their wanted number of 2.9 children. This implies that the total fertility rate (TFR) is 31 percent higher than it would be if unwanted births were avoided. The gap between wanted and observed fertility rates is higher among women in rural areas (1.1 children) than women in urban areas (0.8 children). Similarly, the gap is highest among women in Khyber Pakhtunkhwa (1.3 children), intermediate among women in Punjab, and lowest among women in Sindh, Balochistan, ICT Islamabad, and Gilgit Baltistan (0.8 children each). The gap between wanted and observed total fertility rates decreases with increasing education. Women with no education have 1.1 more children than they want, as compared to 0.4 children among women with a higher education. There is an inverse relationship between wanted fertility rates and wealth quintiles. The gap between wanted and actual fertility rates ranges from 0.5 children among women in the highest wealth quintile to 1.3 children among women in the lowest quintile. Overall, there has been a considerable decrease in the total wanted fertility rate among Pakistani women, from 4.7 children in 1990- 91 to 3.1 in 2006-07 and 2.9 in 2012-13. Table 6.8 Wanted fertility rates Total wanted fertility rates and total fertility rates for the three years preceding the survey, by background characteristics, Pakistan 2012-13 Background characteristic Total wanted fertility rate Total fertility rate Residence Urban 2.4 3.2 Rural 3.1 4.2 Region Punjab 2.8 3.8 Sindh 3.1 3.9 Khyber Pakhtunkhwa 2.6 3.9 Balochistan 3.4 4.2 ICT Islamabad 2.2 3.0 Gilgit Baltistan 3.0 3.8 Education No education 3.3 4.4 Primary 3.1 4.1 Middle 2.5 3.3 Secondary 2.5 3.2 Higher 2.1 2.5 Wealth quintile Lowest 3.9 5.2 Second 3.3 4.4 Middle 2.7 3.8 Fourth 2.6 3.4 Highest 2.2 2.7 Total 2.9 3.8 Note: Rates are calculated based on births to women age 15-49 in the period 1-36 months preceding the survey. The total fertility rates are the same as those presented in Table 5.2. Family Planning • 91 FAMILY PLANNING 7 amily planning activities, introduced in the mid-1950s by the Family Planning Association of Pakistan and other voluntary organizations, were extended through the health infrastructure during the period 1960-1965. An independent family planning unit was established in the public sector in the third five-year plan (1965-1970) through which mass-scale information, education, and communication activities were launched and a service delivery network was created. This was followed by the introduction of a “continuous motivation system” employing male-female teams of workers at the union council level. In the sixth plan period (1983-1988), the role of nongovernmental organizations (NGOs) was institutionalized under an NGO coordinating council, and field activities were designed in a provincial context. During the same period, provincial population welfare departments were established and field activities were transferred to the provinces. Also in that same period, social marketing of contraceptive programs was introduced to expand nonclinical service delivery to the private sector. In 1990, the Population Welfare Division was given the status of a full-fledged ministry. In 1992, the NGO coordinating council was replaced by the National Trust for Population Welfare to further strengthen the participation and involvement of NGOs in population welfare program activities. The Village-based Family Planning Worker Program was introduced in 1993 by the Ministry of Population Welfare (MOPW) to enhance program coverage in rural areas. The Ministry of Health also launched the Prime Minister’s Program for Family Planning and Primary Health Care. Through this program, lady health workers (LHWs) were recruited and trained to provide family planning and basic health services in urban slums and rural areas. In the 1990s, the population welfare program became a major component of the social action program. Following the International Conference on Population and Development (ICPD) held in Cairo in 1994, the scope of family planning in Pakistan was broadened, and the right to reproductive health as an entitlement was made an integral component of the program. In addition, the population program was reorganized, with the Village-based Family Planning Worker Program being brought under the Ministry of Health. An explicit population policy was promulgated in 2002. The 2001-2011 interim population-sector perspective plan was devised with the goal of reaching replacement-level fertility by expanding family planning coverage and high-quality services, reducing infant and maternal mortality, and instituting other programmatic and strategic measures (MOPW, 2002). F Key Findings • Knowledge of contraception is universal in Pakistan. • More than one-third of currently married women of reproductive age are using a method of contraception, with most women using a modern method (26 percent). • The two most popular modern contraceptive methods are the male condom and female sterilization (9 percent each). • The government sector remains the major provider of contraceptive methods, catering to the needs of nearly one in two users (46 percent). • Overall, 37 percent of episodes of contraceptive use were discontinued within 12 months of their initiation. Ten percent of episodes of discontinuation occurred because the woman experienced side effects or had health concerns. • Twenty percent of currently married women have an unmet need for family planning services, with 9 percent having an unmet need for spacing and 11 percent having an unmet need for limiting. 92 • Family Planning In 2010, a major policy shift took place. Under the 18th Amendment of the Constitution, the Ministry of Population Welfare was devolved, and all responsibilities for implementing population program activities were transferred to the provinces. Now Reproductive Health Service Centers (RHSCs) and hospital-based service outlets are the major clinical components of the Population Welfare Program. Mobile Service Units have been established to provide family planning services to remote areas with underserved rural populations. Moreover, “Male Mobilizers” are responsible for encouraging program advocacy among local community leaders, male teachers, shopkeepers, religious leaders, and community-based organizations. Other important components of the service delivery network include registered medical practitioners, hakims and homeopaths, LHWs, public-private partnerships, and NGOs; social marketing of contraceptives is a central component as well (MOPW, 2009). Family planning refers to a conscious effort by a couple to limit or space the number of children they want to have through the use of contraceptive methods. This chapter focuses on currently married women, who have the greatest risk of exposure to pregnancy and the greatest need to regulate their fertility. The chapter begins with an assessment of respondents’ knowledge of different contraceptive methods before moving on to a consideration of current family planning practices. Knowledge of the ovulatory cycle is examined among users of rhythm, while timing of method adoption is assessed among those relying on sterilization. Special attention is focused on sources of contraception, informed choice, nonuse of contraception, reasons for discontinuation, unmet need for family planning, and intention to use contraception in the future. The chapter concludes by examining exposure to media coverage on the topic of family planning and level of contact with family planning providers. These issues are of practical use to program managers and policymakers. Level of contraceptive use provides the most obvious and widely accepted criterion of the success of a family planning program. Examination of contraceptive use in relation to need pinpoints segments of the population for whom intensified service provision efforts are most needed. Although the main focus of this chapter is on women, results from male respondents are also presented because men play an equally important role in the realization of reproductive health and family planning decisions and behaviors. Wherever possible, comparisons are made with findings from previous surveys in order to evaluate changes in family planning in Pakistan over time. 7.1 KNOWLEDGE OF CONTRACEPTIVE METHODS Knowledge of contraceptive methods is an important precursor to their use. The ability to recognize a family planning method when it is described is a simple test of a respondent’s knowledge but not necessarily an indication of the extent of her or his knowledge. The 2012-13 PDHS gathered information on knowledge of contraception by asking respondents whether or not they have heard about 10 modern methods (female and male sterilization, the pill, intrauterine devices [IUDs], injectables, implants, male condoms, the lactational amenorrhea method [LAM], the standard days method [SDM], and emergency contraception) and two traditional methods (rhythm and withdrawal). Respondents were also asked whether they have heard of any other methods in addition to those listed. Table 7.1 shows that knowledge of family planning is universal among both women and men. Modern methods are more widely known than traditional methods; almost all women know of a modern method, while 73 percent know of a traditional method. Family Planning • 93 Table 7.1 Knowledge of contraceptive methods Percentage of ever-married respondents and currently married respondents age 15-49 who have heard of any contraceptive method, by specific method, Pakistan 2012-13 Women Men Method Ever-married women Currently married women Ever-married men Currently married men Any method 98.8 98.9 95.7 95.7 Any modern method 98.7 98.7 94.9 94.8 Female sterilization 91.0 90.9 80.7 81.1 Male sterilization 51.4 51.0 47.1 47.3 Pill 95.2 95.4 84.6 84.8 IUD 86.0 86.0 52.1 52.5 Injectables 95.4 95.5 81.9 82.2 Implants 33.6 33.6 14.5 14.6 Condom 82.2 82.3 88.5 88.6 Lactational amenorrhea (LAM) 65.0 64.9 32.0 32.2 Emergency contraception 24.1 24.2 19.3 19.3 Standard days method (SDM) 5.3 5.2 14.2 14.2 Any traditional method 72.5 72.5 81.1 81.1 Rhythm 41.9 41.9 44.6 44.7 Withdrawal 67.0 67.1 76.3 76.2 Other 1.8 1.8 0.2 0.2 Mean number of methods known by respondents 7.4 7.4 6.4 6.4 Number of respondents 13,558 12,937 3,134 3,071 Female sterilization (91 percent), injectables and the pill (95 percent each), and IUDs (86 percent) are the most commonly known modern methods among women, followed by male condoms (82 percent). More than half of the women are aware of LAM (65 percent) and male sterilization (51 percent). Implants and emergency contraception are known by a much smaller percentage of women (34 percent and 24 percent, respectively). Five percent of women have heard about SDM, a method introduced in Pakistan in May 2007 under the FALAH (Family Advancement for Life and Health) project, which was funded by the U.S. Agency for International Development (USAID) and covered 20 of the country’s districts. The traditional withdrawal and rhythm methods are known by 67 percent and 42 percent of women, respectively. Overall, women are slightly more knowledgeable than men about contraceptive methods. The mean number of methods known to women is 7.4, as compared with 6.4 for men. Because knowledge of at least one method of contraception is nearly universal, there are only minimal differences in knowledge by background characteristics. Among women, level of contraceptive knowledge increases slightly with increasing education and wealth quintile, and a similar pattern is seen among men (data not shown). 7.2 EVER USE OF FAMILY PLANNING METHODS Women who reported that they had heard of a method of family planning were asked whether they had ever used that method to delay or avoid getting pregnant. Table 7.2 shows that more than half (55 percent) of currently married women have ever used a contraceptive method, with 48 percent having used a modern method and 24 percent having used a traditional method. The methods most commonly used by women are the condom (22 percent) and withdrawal (20 percent), followed by injectables (14 percent) and the pill (11 percent). Nine percent each of currently married women have used female sterilization, IUDs, and LAM; 6 percent or fewer report use of other methods. As expected, ever use of any contraceptive method among currently married women rises steadily with age, from 13 percent among those age 15-19 to 67 percent among those age 35-39. Female sterilization is more likely to have been used by older women, while use of condoms is more common among women age 30-34. Withdrawal is popular among women age 25 and older. Ever-married women show similar patterns in use of contraception. 94 • Family Planning Ever use of any contraceptive among currently married women has increased 34 percentage points during the past 22 years, from 21 percent in 1990-91 to 49 percent in 2006-07 and 55 percent in 2012-13. The corresponding figures for ever-married women are 16 percent in 1990-91, 39 percent in 2006-07, and 48 percent in 2012-13. Table 7.2 Ever use of contraception by age Percentage of ever-married and currently married women age 15-49 who have ever used any contraceptive method, by method, according to age, Pakistan 2012- 13 Age Any method Any modern method Female sterili- zation Male sterili- zation Pill IUD Inject- ables Im- plants Con- dom LAM Emer- gency contra- ception Stan- dard days method (SDM) Any tradi- tional method Rhythm With- drawal Other Number of women EVER-MARRIED WOMEN 15-19 13.1 10.6 0.0 0.0 1.1 0.8 2.3 0.0 6.1 2.0 0.5 0.0 7.3 0.3 7.1 0.3 605 20-24 34.5 27.9 0.5 0.0 5.0 2.6 7.5 0.1 15.3 5.5 0.5 0.0 14.3 3.1 12.5 0.4 2,106 25-29 53.3 45.0 2.4 0.1 9.4 6.3 13.4 0.1 23.4 8.7 0.8 0.0 24.2 5.0 21.4 0.7 2,724 30-34 61.8 55.5 7.3 0.6 11.9 11.1 15.9 0.2 29.1 10.0 1.3 0.1 26.5 6.2 23.5 0.6 2,528 35-39 65.4 59.0 14.3 0.3 14.4 14.1 18.4 0.3 25.5 11.2 1.2 0.0 27.3 7.4 22.7 1.3 2,226 40-44 62.2 55.0 16.9 0.6 15.4 14.5 17.6 0.5 21.7 9.7 1.2 0.2 26.3 6.1 23.0 1.2 1,766 45-49 56.5 50.6 17.3 0.4 10.7 11.1 11.3 0.2 16.6 14.0 0.6 0.0 22.0 6.0 17.8 1.1 1,602 Total 53.7 47.0 8.5 0.3 10.5 9.3 13.6 0.2 21.8 9.3 0.9 0.1 22.8 5.4 19.7 0.8 13,558 CURRENTLY MARRIED WOMEN 15-19 13.0 10.4 0.0 0.0 1.1 0.8 2.4 0.0 5.9 2.0 0.5 0.0 7.5 0.3 7.2 0.3 594 20-24 34.6 28.0 0.5 0.0 5.1 2.6 7.5 0.1 15.3 5.6 0.5 0.0 14.5 3.2 12.6 0.4 2,053 25-29 53.8 45.4 2.5 0.1 9.5 6.4 13.3 0.2 23.8 8.6 0.8 0.0 24.5 4.9 21.7 0.8 2,663 30-34 63.3 56.8 7.4 0.6 12.2 11.3 16.3 0.2 29.7 10.3 1.3 0.1 27.3 6.3 24.2 0.6 2,454 35-39 67.1 60.5 14.8 0.3 14.8 14.5 19.0 0.3 26.2 11.4 1.2 0.0 28.2 7.6 23.5 1.4 2,137 40-44 64.4 57.1 17.5 0.7 15.8 14.6 18.5 0.5 22.8 10.0 1.3 0.2 27.2 6.2 23.6 1.3 1,617 45-49 59.3 52.7 18.6 0.2 11.3 11.9 12.0 0.2 17.2 14.5 0.7 0.0 23.4 6.5 18.9 1.2 1,419 Total 54.8 48.0 8.7 0.3 10.8 9.4 13.9 0.2 22.3 9.4 1.0 0.1 23.5 5.5 20.3 0.9 12,937 7.3 CURRENT USE OF CONTRACEPTIVE METHODS The prevalence of current contraceptive use among women is the most widely employed and valuable measure of the success of family planning programs. The contraceptive prevalence rate (CPR) is usually defined as the percentage of currently married women who are using a method of contraception. Table 7.3 shows that 35 percent of currently married Pakistani women are using some method of contraception; 26 percent use modern methods, and 9 percent use traditional methods. Of the modern methods, condoms and female sterilization are used most often (9 percent each). Among traditional methods, withdrawal is the most popular, used by 9 percent of currently married women. Use of withdrawal more than doubled from 4 percent in 2006-07 to 9 percent in 2012-13. Table 7.3 Current use of contraception by age Percent distribution of currently married women age 15-49 by contraceptive method currently used, according to age, Pakistan 2012-13 Any method Any modern method Modern method Any tradi- tional method Traditional method Not cur- rently using Total Number of womenAge Female sterili- zation Male sterili- zation Pill IUD Inject- ables Con- dom LAM Other Rhythm With- drawal Other 15-19 10.3 6.9 0.0 0.0 0.5 0.8 1.1 3.4 0.6 0.5 3.4 0.2 3.2 0.0 89.7 100.0 594 20-24 21.3 14.9 0.5 0.0 1.4 1.0 2.2 7.1 2.6 0.2 6.5 0.5 6.0 0.0 78.7 100.0 2,053 25-29 31.2 21.0 2.5 0.1 1.5 1.8 2.9 9.8 2.2 0.2 10.3 0.5 9.7 0.2 68.8 100.0 2,663 30-34 41.7 31.4 7.4 0.6 1.8 3.8 4.2 11.8 1.8 0.2 10.3 0.6 9.6 0.1 58.3 100.0 2,454 35-39 47.9 36.6 14.8 0.2 1.9 3.7 3.4 11.3 1.2 0.2 11.3 1.1 10.2 0.0 52.1 100.0 2,137 40-44 44.2 33.3 17.5 0.6 2.3 2.1 2.3 7.6 0.7 0.1 10.9 1.2 9.4 0.3 55.8 100.0 1,617 45-49 34.5 26.8 18.6 0.2 0.9 1.6 1.1 4.2 0.2 0.2 7.7 0.4 6.9 0.3 65.5 100.0 1,419 Total 35.4 26.1 8.7 0.3 1.6 2.3 2.8 8.8 1.5 0.2 9.3 0.7 8.5 0.1 64.6 100.0 12,937 Note: If more than one method is used, only the most effective method is considered in this tabulation. LAM = Lactational amenorrhea method Family Planning • 95 In general, use of any contraception increases with age from 10 percent among married women age 15-19 to 48 percent among women age 35-39. Married women at the peak of the childbearing period (age 20-34) prefer to use condoms and injectables, while female sterilization is more often used by older women (age 35-49). One of the Millennium Development Goals for Pakistan is to increase the CPR to 55 percent by 2015 (Planning Commission, 2010). Unless strenuous efforts are made to utilize all available channels in the public, private, and NGO sectors, it is unlikely that this goal will be achieved. 7.4 DIFFERENTIALS IN CONTRACEPTIVE USE BY BACKGROUND CHARACTERISTICS Knowledge of differentials in contraceptive use by background characteristics is important to identify targets for family planning services. Table 7.4 shows that there is a strong positive association between use of family planning methods and number of children. Only 1 percent of women with no living children use contraception. This percentage increases sharply to 29 percent among women with one or two children, rises to 46 percent among women with three to four children, and peaks at 48 percent among women with five and more children. Use of female sterilization is more popular among women with five or more living children (18 percent). These women may have completed their family size and do not want any more children. Use of condoms rises with parity, from less than 1 percent of women with no living children to 12 percent of women with three to four children; it then decreases to 8 percent among women with five or more children. Use of IUDs shows a similar pattern. As can be seen in Table 7.4, married women in urban areas are more likely to use contraception (45 percent) than their rural counterparts (31 percent). More than twice as many urban women (15 percent) as rural women (6 percent) use condoms. Differentials by region are pronounced. Married women in ICT Islamabad have the highest CPR (59 percent), followed by women in Punjab (41 percent), Gilgit Baltistan (34 percent), Sindh (30 percent), and Khyber Pakhtunkhwa (28 percent). The lowest level of family planning use is in Balochistan (20 percent). Differentials in the use of any modern method by region are similar to differentials in the use of any traditional method. Among modern methods, female sterilization is the method of choice in Punjab and Sindh. The most commonly reported method in ICT Islamabad (as well as in the urban sections of Khyber Pakhtunkhwa, Sindh, and Punjab) is the condom. IUDs and injectables are popular in Gilgit Baltistan. Urban-rural differences within regions are most pronounced in Sindh; urban women in this region are two and a half times more likely than rural women to use any contraception (43 percent and 17 percent, respectively). A good deal of the variation is due to much higher use of condoms and withdrawal in urban areas. Table 7.4 also shows that contraceptive use has a positive association with education. The CPR increases from 30 percent among women with no education to 41 percent among women with a primary- and middle-level education and 44 percent among women with a secondary or higher education. Wealth also has a positive association with women’s contraceptive use. The CPR increases as household wealth increases, from 21 percent among women in the lowest wealth quintile to 46 percent among women in the highest quintile. 96 • Family Planning Table 7.4 Current use of contraception by background characteristics Percent distribution of currently married women age 15-49 by contraceptive method currently used, according to background characteristics, Pakistan 2012-13 Background characteristic Any method Any modern method Modern method Any tradi- tional method Traditional method Not cur- rently using Total Number of women Female sterili- zation Male sterili- zation Pill IUD Inject- ables Con- dom LAM Other Rhythm With- drawal Other Number of living children 0 0.9 0.6 0.0 0.0 0.0 0.2 0.0 0.4 0.0 0.0 0.3 0.0 0.3 0.0 99.1 100.0 1,728 1-2 28.8 18.1 1.1 0.0 1.2 0.9 2.3 10.5 1.9 0.2 10.7 0.7 10.0 0.0 71.2 100.0 3,856 3-4 46.4 35.2 11.8 0.5 2.0 3.8 3.5 11.8 1.7 0.2 11.2 0.7 10.2 0.2 53.6 100.0 3,772 5+ 47.6 37.4 17.7 0.4 2.4 3.3 3.8 7.9 1.7 0.2 10.2 0.8 9.2 0.2 52.4 100.0 3,580 Residence Urban 44.8 32.0 9.6 0.4 1.5 2.6 2.5 14.8 0.6 0.1 12.8 1.0 11.7 0.1 55.2 100.0 4,304 Rural 30.7 23.1 8.2 0.2 1.6 2.2 2.9 5.8 2.0 0.2 7.6 0.5 6.9 0.1 69.3 100.0 8,633 Region Punjab 40.7 29.0 10.2 0.4 1.1 2.9 2.0 9.9 2.3 0.2 11.7 1.0 10.6 0.1 59.3 100.0 7,374 Urban 46.9 32.2 10.5 0.7 0.8 3.4 1.9 14.3 0.6 0.1 14.6 1.5 13.1 0.0 53.1 100.0 2,402 Rural 37.7 27.4 10.1 0.3 1.2 2.7 2.0 7.8 3.1 0.3 10.3 0.8 9.4 0.2 62.3 100.0 4,972 Sindh 29.5 24.5 9.7 0.1 1.8 1.2 3.3 8.0 0.2 0.3 5.0 0.1 4.8 0.1 70.5 100.0 3,002 Urban 42.7 32.6 9.8 0.0 2.1 1.3 2.9 15.9 0.4 0.2 10.2 0.2 9.8 0.2 57.3 100.0 1,432 Rural 17.4 17.1 9.6 0.2 1.5 1.0 3.7 0.7 0.0 0.3 0.3 0.1 0.3 0.0 82.6 100.0 1,570 Khyber Pakhtunkhwa 28.1 19.5 2.4 0.0 2.7 1.5 5.2 7.0 0.6 0.0 8.6 0.3 8.1 0.2 71.9 100.0 1,855 Urban 44.0 30.4 3.4 0.0 3.0 2.8 5.4 15.1 0.4 0.3 13.6 0.4 13.2 0.0 56.0 100.0 308 Rural 24.9 17.3 2.2 0.0 2.6 1.3 5.1 5.4 0.6 0.0 7.6 0.2 7.1 0.2 75.1 100.0 1,547 Balochistan 19.5 16.3 4.0 0.0 2.4 2.1 1.7 3.7 2.0 0.4 3.1 0.1 3.0 0.1 80.5 100.0 553 Urban 24.4 20.9 4.9 0.0 3.5 0.4 2.8 6.5 2.0 0.8 3.5 0.0 3.3 0.1 75.6 100.0 110 Rural 18.2 15.2 3.8 0.0 2.1 2.5 1.5 3.1 1.9 0.3 3.0 0.1 2.9 0.1 81.8 100.0 443 ICT Islamabad 59.4 44.1 10.0 0.1 1.8 4.6 1.6 24.9 0.8 0.4 15.4 2.4 12.9 0.0 40.6 100.0 62 Gilgit Baltistan 33.6 28.2 4.6 0.6 3.7 8.4 6.6 3.0 1.4 0.0 5.4 0.5 4.9 0.0 66.4 100.0 91 Education No education 30.2 23.4 9.6 0.2 1.5 2.2 2.9 5.0 1.9 0.2 6.8 0.5 6.1 0.2 69.8 100.0 7,347 Primary 40.8 28.8 9.1 0.6 1.5 2.0 3.2 10.5 1.5 0.3 12.1 0.9 11.1 0.1 59.2 100.0 2,057 Middle 40.7 29.5 7.2 0.3 2.4 3.0 2.3 13.1 0.8 0.3 11.2 1.2 9.9 0.1 59.3 100.0 958 Secondary 43.9 31.1 7.1 0.2 1.8 2.5 2.9 15.7 0.9 0.0 12.9 0.7 12.1 0.1 56.1 100.0 1,351 Higher 43.8 29.7 4.9 0.2 1.3 2.6 1.6 18.1 0.9 0.2 14.2 0.6 13.5 0.0 56.2 100.0 1,225 Wealth quintile Lowest 20.8 18.1 7.5 0.4 1.6 1.2 2.3 1.4 3.6 0.1 2.7 0.2 2.5 0.0 79.2 100.0 2,501 Second 29.7 22.9 7.8 0.1 1.7 2.3 3.8 4.8 2.1 0.3 6.7 0.5 6.1 0.1 70.3 100.0 2,533 Middle 38.2 26.9 9.5 0.2 1.1 2.9 3.4 8.4 1.1 0.3 11.2 0.8 10.1 0.3 61.8 100.0 2,550 Fourth 41.5 30.3 9.1 0.2 2.3 2.4 2.9 13.0 0.4 0.1 11.2 0.9 10.2 0.1 58.5 100.0 2,677 Highest 45.8 31.6 9.3 0.4 1.2 2.7 1.4 15.7 0.6 0.2 14.2 0.8 13.3 0.0 54.2 100.0 2,676 Total 35.4 26.1 8.7 0.3 1.6 2.3 2.8 8.8 1.5 0.2 9.3 0.7 8.5 0.1 64.6 100.0 12,937 Note: If more than one method is used, only the most effective method is considered in this tabulation. LAM = Lactational amenorrhea method 7.5 TRENDS IN CURRENT USE OF FAMILY PLANNING Trends in current use of family planning can be used to monitor the progress of family planning programs over time. Table 7.5 and Figure 7.1 show trends in modern contraceptive use among currently married women from 1990 to 2013. Data from the three DHS surveys conducted in Pakistan over the past two decades show an increase of 17 percentage points in the use of modern contraceptive methods, from 9 percent in 1990-91 to 26 percent in 2012-13. As can be seen in Figure 7.1, changes in the use of pill, IUD, and rhythm over the past 22 years have been small. Use of female sterilization, condoms, and injectables increased slightly since 2006-07, whereas use of withdrawal increased by 5 percentage points. Table 7.5 Trends in the current use of contraception Percent distribution of currently married women age 15-49 by contraceptive method currently used, according to several surveys Method 1990-91 PDHS 2006-07 PDHS 2012-13 PDHS Any method 11.8 29.6 35.4 Any modern method 9.0 21.7 26.1 Female sterilization 3.5 8.2 8.7 Pill 0.7 2.1 1.6 IUD 1.3 2.3 2.3 Injectables 0.8 2.3 2.8 Condom 2.7 6.8 8.8 Other modern method 0.0 0.2 2.0 Any traditional method 2.8 7.9 9.3 Rhythm 1.3 3.6 0.7 Withdrawal 1.2 4.1 8.5 Other 0.3 0.2 0.4 Not currently using 88.2 70.4 64.6 Total 100.0 100.0 100.0 Number of women 6,364 9,556 12,937 Family Planning • 97 Figure 7.1 Trends in contraceptive use among currently married women 12 9 4 1 1 1 3 3 1 1 30 22 8 2 2 2 7 8 4 4 35 26 9 2 2 3 9 9 1 9 ANY METHOD Any modern method Female sterilization Pill IUD Injectables Condom Any traditional method Rhythm Withdrawal Percentage of currently married women 1990-91 PDHS 2006-07 PDHS 2012-13 PDHS 7.6 TIMING OF STERILIZATION Table 7.6 shows the percent distribution of currently married, sterilized women by age at the time of sterilization, according to the number of years since the operation. The results indicate that the median age at sterilization among women in Pakistan is 31.5 years. Median age at sterilization is highest for women who were sterilized between eight and nine years before the survey (33.2 years). The majority of women were sterilized when they were age 30-34. Overall, a gradual decrease has been observed in median age at sterilization, from 32.8 years in 1990-91 to 31.9 years in 2006-07 and 31.5 years in 2012-13. Table 7.6 Timing of sterilization Percent distribution of sterilized women age 15-49 by age at the time of sterilization and median age at sterilization, according to the number of years since the operation, Pakistan 2012-13 Years since operation Age at time of sterilization Total Number of women Median age1 <25 25-29 30-34 35-39 40-44 45-49 <2 7.5 28.0 24.0 23.1 11.1 6.4 100.0 172 31.1 2-3 2.0 21.5 36.9 27.6 10.6 1.4 100.0 212 33.1 4-5 2.9 24.4 28.0 31.8 12.9 0.0 100.0 149 32.9 6-7 4.1 26.8 33.0 25.5 10.7 0.0 100.0 178 31.2 8-9 4.8 27.2 33.7 30.7 3.6 0.0 100.0 94 33.2 10+ 14.3 34.5 40.2 11.1 0.0 0.0 100.0 315 a Total 7.0 27.9 33.8 22.7 7.4 1.2 100.0 1,120 31.5 a = Not calculated due to censoring 1 Median age at sterilization is calculated only for women sterilized before age 40 to avoid problems of censoring. 7.7 SOURCE OF CONTRACEPTION Information on where women obtain their contraceptives is useful for family planning program managers and implementers for logistic planning. In the 2012-13 PDHS, women who reported using a modern contraceptive method were asked where they last obtained the method. Because some respondents 98 • Family Planning may not know exactly in which category the source they use falls (e.g., government hospital, private health center), interviewers were instructed to note the full name of the source or facility. As a means of ensuring accurate reporting, supervisors were instructed to verify that the name and source type were consistent by asking informants in the clusters for the names of local family planning outlets or facilities. Table 7.7 shows the percent distribution of users of modern contraceptive methods by the most recent source. Government facilities provide contraceptives to 46 percent of users. Within the government sector, 31 percent of users obtain their methods from government hospitals (RHSCs) and 10 percent from LHWs. Thirty-five percent of modern contraceptive users obtain their methods from the private sector, primarily from private and NGO hospitals and clinics (19 percent), private pharmacies or chemists (13 percent), and other sources (e.g., shops) (13 percent). Reliance on obtaining contraceptives from the private sector has increased 5 percentage points, from 30 percent in 2006-07 to 35 percent in 2012-13. Two in three female sterilizations are performed in government hospitals (65 percent). Forty-eight percent of pill users obtain their supply from a government source, primarily LHWs (29 percent) and government hospitals (15 percent). Pharmacies or chemists (23 percent) are used by the majority of women who obtain the pill from a private medical source. More than half of IUD insertions took place in a government facility (53 percent), with the majority being performed in a government hospital (RHSC) (27 percent). Four in 10 IUD users had the device inserted in a private facility, primarily at a private or NGO hospital or clinic (36 percent). Fifty-six percent women who use injectables had the injection in a government facility, with 23 percent doing so in a government hospital. Forty percent had the injection in a private facility, primarily from NGO hospital or clinic (24 percent). Pharmacies and shops are the main suppliers of condoms (32 percent and 27 percent, respectively). Table 7.7 Source of modern contraception methods Percent distribution of users of modern contraceptive methods age 15-49 by most recent source of method, according to method, Pakistan 2012-13 Source Female sterilization Pill IUD Injectables Condom Total Public sector 66.5 47.5 53.3 56.3 17.7 45.6 Public government hospital (RHSC) 65.2 15.2 27.3 22.5 2.6 31.3 Rural health center 1.0 0.4 2.9 3.5 0.2 1.1 Family welfare center (FWW) 0.0 2.4 4.8 2.9 0.2 1.0 Mother-child health center 0.2 0.1 3.1 4.1 0.0 0.9 Lady health worker 0.0 28.8 4.3 21.1 13.9 9.7 Lady health visitor 0.0 0.5 6.6 1.8 0.6 1.1 Basic health unit 0.0 0.1 3.3 0.3 0.1 0.4 Other public 0.1 0.0 0.9 0.1 0.1 0.1 Private medical sector 33.0 36.1 40.8 40.0 34.7 35.0 Private/NGO hospital/clinic 33.0 5.6 35.8 23.7 1.7 18.9 Private pharmacy, chemist 0.0 23.1 0.4 2.5 30.9 13.0 Private doctor 0.0 2.2 4.5 6.4 0.5 1.5 Dispensary/compounder 0.0 4.8 0.0 7.4 1.0 1.5 Other private 0.0 0.4 0.0 0.0 0.6 0.2 Other source 0.0 13.5 5.9 3.4 31.9 13.3 Shop 0.0 10.5 0.0 1.4 26.8 10.5 Friend/relative 0.0 3.0 0.2 0.1 4.9 2.0 Hakim 0.0 0.0 0.0 0.0 0.2 0.1 Dai/traditional birth attendant 0.0 0.0 5.7 1.9 0.0 0.8 Other 0.3 1.4 0.0 0.0 8.3 3.2 Don’t know 0.0 1.1 0.0 0.0 6.9 2.5 Missing 0.1 0.5 0.0 0.3 0.5 0.3 Total 100.0 100.0 100.0 100.0 100.0 100.0 Number of women 1,120 204 299 357 1,140 3,160 Note: Total includes 32 women whose husbands are sterilized and 8 women who are using implants and are not shown separately but excludes women using the lactational amenorrhea method (LAM). RHSC = Reproductive health service center FWW = Family welfare worker Family Planning • 99 7.8 USE OF SOCIAL MARKETING CONTRACEPTIVE BRANDS Women age 15-49 who were using oral contraceptives and male condoms were asked for the brand name of the pills and condoms they last used. This information is useful in monitoring and evaluating the success of social marketing programs that promote a specific brand. Social marketing plays an important role in provision of contraceptive methods in Pakistan. Currently the “Greenstar” program, initiated in 1991, is the only component of contraceptive social marketing in Pakistan. The program provides family planning information and services to mainly urban and peri-urban residents at subsidized rates. The range of activities includes advertisements and promotional campaigns; training of doctors, paramedics, and chemists; and sales of condom brands such as Sathi and Touch (National Institute of Population Studies, 2008). Table 7.8 shows that 84 percent of pill users use Nova, Famila 28, or Lo Feminal. Rural women are more likely to use these brands than urban women (87 percent and 77 percent, respectively). Although there are many brands of condoms on the market, the most popular are Sathi and Touch (94 percent). Table 7.8 Use of social marketing brand pills and condoms Percentage of pill and condom users age 15-49 using a social marketing brand, by background characteristics, Pakistan 2012-13 Among pill users Among condom users1 Background characteristic Percentage using Nova, Famila 28, or Lo Feminal Number of women using the pill Percentage using Sathi or Touch Number of women using condoms Residence Urban 76.6 56 93.4 532 Rural 87.0 117 94.1 427 Region Punjab (76.7) 63 93.9 622 Sindh 85.8 50 95.3 192 Khyber Pakhtunkhwa 86.8 44 90.3 114 Balochistan 96.8 13 98.8 17 ICT Islamabad * 1 85.4 12 Gilgit Baltistan (87.9) 2 (81.7) 2 Total 83.6 173 93.7 959 Note: Table excludes 31 pill users and 170 condom users who do not know the brand name. Condom use is based on women’s reports. 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 Among condom users not also using the pill 7.9 INFORMED CHOICE Current users of modern methods who are informed of potential side effects and problems associated with different methods are best able to make an informed choice about the method they would like to use. Current users of various modern contraceptive methods who started the last episode of use within the five years preceding the survey were asked whether, at the time they adopted the particular method, they were informed about possible side effects or problems they might have with the method and what to do if they experienced side effects. Table 7.9 shows that, overall, 34 percent of modern contraceptive users were informed by a health or family planning worker about potential side effects of the method they use, 28 percent were informed about what to do if they experienced side effects, and 28 percent were informed of other methods available that could be used. Users were as likely to receive information about side effects or problems from the public sector (35 percent) as from the private sector (34 percent). They were slightly more likely to receive information 100 • Family Planning about what to do if they experienced side effects from public-sector sources (30 percent) than from private- sector sources (27 percent). Hospitals and clinics are the major source of information about side effects in the private sector (39 percent), whereas LHWs play a major role in the public sector (35 percent). Table 7.9 Informed choice Among current users of selected modern methods age 15-49 who started the last episode of use within the five years preceding the survey, the percentage who were informed about possible side effects or problems of that method, the percentage who were informed about what to do if they experienced side effects, and the percentage who were informed about other methods they could use, by method and initial source, Pakistan 2012-13 Among women who started last episode of modern contraceptive method within five years preceding the survey: Method/source Percentage who were informed about side effects or problems of method used Percentage who were informed about what to do if experienced side effects Percentage who were informed by a health or family planning worker of other methods that could be used Number of women Method1 Female sterilization 27.8 21.5 15.8 454 Pill 24.5 17.3 32.4 177 IUD 47.6 43.0 35.9 244 Injectables 37.1 31.8 37.4 322 Initial source of method2 Public sector 34.8 29.8 29.7 679 Government hospital (RHSC) 31.8 27.4 24.7 449 Family welfare center (23.8) (22.6) (28.1) 20 Lady health worker 34.9 26.8 47.4 121 Private medical sector 33.5 27.0 25.4 471 Private/NGO hospital/clinic 38.9 30.5 27.8 360 Pharmacy, chemist (16.8) (16.2) (11.4) 47 Private doctor (21.7) (24.8) (40.5) 31 Dispensary/compounder (7.6) (6.6) (4.4) 32 Other private sector 27.4 21.8 43.2 44 Total 33.9 28.1 28.2 1,205 Note: Table includes users of only the methods listed individually. Figures in parentheses are based on 25-49 unweighted cases. 1 Total includes users of implants as there are too few users to show separately. 2 Source at start of current episode of use; total include sources with too few users to show separately. 7.10 SIDE EFFECTS OF FAMILY PLANNING METHODS Currently married women who were using a specific modern method of family planning (female sterilization, IUD, injectables, implants, or the pill) were asked whether they had experienced any side effects from their current method. Table 7.10 shows that one-fifth of women experienced side effects. Among these women, 37 percent had irregular menses or no menses, 30 percent had excessive bleeding, and 19 percent gained weight. Forty-five percent of women who used injectables reported experiencing side effects, with 55 percent of these women complaining of irregular menses or no menses. More than half of IUD users reported having excessive bleeding. Rural women are more likely than urban women to report experiencing side effects. With the exception of Khyber Pakhtunkhwa, there are only small regional variations. There is no clear pattern in the reporting of side effects according to level of education, but there is a negative association between wealth quintile and side effects. Women in the lowest wealth quintile are more likely to report side effects than women in the higher quintiles. Family Planning • 101 Table 7.10 Side effects from use of family planning methods Percentage of currently married women 15-49 using a modern method of family planning (includes female sterilization, IUD, injectables, implants, and pill) who ever experienced side effects from use of the current family planning method and, among those experienced side effects, the percentage of women by type of side effects, according to background characteristics, Pakistan 2012-13 Percentage of women who ever experienced side effects Number of women using modern methods of family planning1 Type of side effects Background characteristic Weight gain/ obesity Excessive bleeding Irregular menses/no menses Other2 Number of women who ever experienced side effects Age 15-19 * 14 * * * * 7 20-24 31.1 105 (7.6) (39.2) (51.9) (39.6) 33 25-29 36.8 232 17.3 35.4 40.1 66.2 85 30-34 24.3 422 11.2 24.5 31.5 62.4 102 35-39 18.7 509 20.9 41.9 35.4 64.3 95 40-44 13.7 392 33.3 15.9 39.8 59.6 54 45-49 10.7 314 (37.7) (11.8) (27.4) (59.5) 34 Method3 Female sterilization 11.2 1,120 25.4 29.0 26.4 74.3 125 Pill 25.8 204 20.0 17.1 37.4 72.5 53 IUD 23.8 299 17.1 53.4 15.8 56.0 71 Injectables 44.5 357 15.0 24.2 54.8 48.6 159 Residence Urban 17.3 700 31.9 25.8 32.9 60.5 121 Rural 22.5 1,288 14.1 31.8 38.8 60.6 289 Region Punjab 18.1 1,193 20.3 33.1 31.6 59.9 216 Sindh 19.8 485 20.3 37.2 26.1 60.2 96 Khyber Pakhtunkhwa 39.3 219 15.7 14.6 63.2 63.0 86 Balochistan 12.8 59 (25.6) (31.4) (41.2) (56.0) 8 ICT Islamabad 13.5 11 * * * * 2 Gilgit Baltistan 17.2 21 (4.2) (29.4) (22.6) (54.5) 4 Education No education 21.6 1,197 17.9 29.9 39.2 62.4 259 Primary 20.8 325 20.6 32.1 29.7 57.7 68 Middle 25.8 143 (17.5) (38.9) (35.3) (59.9) 37 Secondary 12.4 193 (27.9) (20.4) (39.3) (55.9) 24 Higher 17.8 129 (25.2) (21.1) (34.9) (54.6) 23 Wealth quintile Lowest 28.3 315 8.7 41.1 33.8 71.9 89 Second 23.2 399 14.7 30.2 44.5 63.0 92 Middle 22.4 434 21.8 24.2 44.0 51.5 97 Fourth 17.2 443 23.6 27.8 27.8 62.7 76 Highest 14.0 396 33.9 25.4 30.3 51.2 55 Total 20.6 1,988 19.3 30.0 37.0 60.6 410 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. Urban and rural disaggregation not shown for region due to few cases. 1 Includes female sterilization, IUD, injectables, implants, and pill 2 Other includes headache, nausea/dizziness, spotting, depression, and other symptoms. 3 Total includes 3 users of implants not shown separately. 7.11 TREATMENT FOR SIDE EFFECTS Women who experienced side effects were asked whether they had been treated. Table 7.11 shows that more than half (56 percent) of women reported that they did not receive any treatment for side effects, while 38 percent received treatment from a skilled health provider (34 percent from a doctor). Differentials by background characteristics are not pronounced. Of the women who received treatment for side effects, two-fifths were treated at public-sector facilities and three-fifths at private-sector or NGO facilities (Figure 7.2). Women in urban areas more often visit private-sector or NGO facilities, while women in rural areas are frequently treated at both public- and private-sector facilities. With respect to reasons for not seeking treatment, 49 percent of women reported that they did not consider it necessary; other reasons included “costs too much” (31 percent), “no time to go for treatment” (11 percent), “source is too far” or “no transport is available” (9 percent each), “no one to accompany” (6 percent), and “did not know where to go for treatment” (5 percent) (data not shown). 102 • Family Planning Table 7.11 Treatment for side effects Percentage of women age 15-49 who experienced side effects from use of current method of family planning by treatment from a service provider, according to background characteristics, Pakistan 2012-13 Provider for side effects Background characteristic Doctor Nurse/ midwife/Lady Health Visitor Lady health worker Dispenser/ compounder/ homeopath/ hakim Other Missing No one Number of women Age 15-19 * * * * * * * 7 20-24 (32.6) (2.8) (8.4) (2.6) (0.0) (0.0) (53.7) 33 25-29 34.3 7.8 0.3 2.0 0.0 0.0 55.9 85 30-34 30.9 2.7 0.0 2.7 2.9 0.0 60.8 102 35-39 42.2 0.9 5.4 6.5 0.0 0.0 47.3 95 40-44 32.0 3.0 0.1 6.5 4.0 1.1 60.2 54 45-49 (19.7) (6.3) (6.9) (3.2) (0.0) (0.0) (69.6) 34 Residence Urban 37.8 3.3 1.7 3.5 0.1 0.5 56.3 121 Rural 31.7 4.5 2.9 4.1 1.8 0.0 56.4 289 Region Punjab 32.7 6.1 3.9 4.5 2.4 0.0 54.1 216 Sindh 42.6 1.0 1.5 2.7 0.0 0.6 51.6 96 Khyber Pakhtunkhwa 24.5 2.7 0.4 4.3 0.1 0.0 68.1 86 Balochistan (43.1) (4.1) (3.0) (2.6) (0.0) (0.0) (48.7) 8 ICT Islamabad * * * * * * * 2 Gilgit Baltistan (32.1) (7.6) (1.0) (0.3) (0.7) (0.0) (59.3) 4 Education No education 34.0 2.0 3.4 4.3 1.2 0.0 57.3 259 Primary 26.9 7.7 0.0 4.6 3.1 0.0 60.7 68 Middle (44.0) (0.0) (0.3) (5.2) (0.0) (0.0) (50.5) 37 Secondary (25.9) (6.3) (0.0) (0.0) (0.0) (0.0) (67.8) 24 Higher (38.0) (22.1) (7.1) (0.0) (0.1) (2.5) (30.7) 23 Wealth quintile Lowest 41.8 1.2 3.8 2.7 0.0 0.0 52.2 89 Second 26.5 2.5 3.0 4.7 0.1 0.0 65.4 92 Middle 30.1 5.0 0.5 5.0 5.2 0.0 56.4 97 Fourth 40.5 8.7 3.2 3.5 0.0 0.0 47.2 76 Highest 28.0 4.1 2.7 3.5 0.0 1.0 60.7 55 Total 33.5 4.2 2.6 3.9 1.3 0.1 56.4 410 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. Figure 7.2 Source of treatment for side effects from use of family planning methods 30 47 42 82 54 62 4 9 8 Urban Rural Total Percent Public sector Private sector/NGO Other PDHS 2012-13Note: Multiple responses possible Family Planning • 103 7.12 CONTRACEPTIVE DISCONTINUATION RATES A major concern for family planning program managers is discontinuation of contraceptive use, either voluntarily or due to method failure. The “Calendar” section of the Woman’s Questionnaire recorded all contraceptive use from 3-62 months prior to the survey. One-year contraceptive discontinuation rates based on the calendar data are presented in Table 7.12. Overall, 37 percent of contraceptive use episodes were discontinued within 12 months for any reason, 10 percent because of side effects or health concerns, 9 percent because the woman wanted to become pregnant, and 6 percent due to method failure. Discontinuation rates vary according to method used. Injectables have the highest discontinuation rate (61 percent), followed by the pill (56 percent) and condoms (38 percent). Side effects or health concerns are the most often cited reason for stopping use of the pill, IUDs, and injectables. Table 7.12 Twelve-month contraceptive discontinuation rates Among women age 15-49 who started an episode of contraceptive use within the five years preceding the survey, the percentage of episodes discontinued within 12 months, by reason for discontinuation and specific method, Pakistan 2012-13 Method Method failure Desire to become pregnant Other fertility- related reasons2 Side effects/ health concerns Wanted more effective method Other method- related reasons3 Other reasons Any reason4 Switched to another method5 Number of episodes of use6 Pill 6.4 8.8 4.6 31.2 1.5 1.3 2.6 56.4 13.8 583 IUD 1.4 1.0 1.2 20.5 0.3 0.0 1.1 25.5 8.5 554 Injectables 1.7 7.4 3.8 35.1 1.5 4.3 6.9 60.7 16.5 1,010 Condom 7.4 12.3 1.8 3.2 1.9 4.9 6.3 37.8 5.7 1,970 Withdrawal 8.8 13.0 2.5 0.8 2.6 0.8 3.5 32.2 4.0 1,573 Other1 4.9 8.1 1.8 1.0 4.9 0.0 12.9 33.5 7.3 937 All methods 5.5 9.1 2.3 10.4 2.1 2.2 5.5 37.1 7.6 7,146 Note: Figures are based on life table calculations using information on episodes of use that began 3-62 months preceding the survey. Female sterilization is excluded as there are no failure cases. 1 Includes LAM and implants not shown separately 2 Includes infrequent sex/husband away, difficult to get pregnant/menopausal, and marital dissolution/separation 3 Includes lack of access/too far, costs too much, and inconvenient to use 4 Reasons for discontinuation are mutually exclusive and add to the total given in this column. 5 The episodes of use included in this column are a subset of the discontinued episodes included in the discontinuation rate. A woman is considered to have switched to another method if she used a different method in the month following discontinuation or if she gave “wanted a more effective method” as the reason for discontinuation and started another method within 2 months of discontinuation. 6 Number of episodes of use includes both episodes of use that were discontinued during the period of observation and episodes of use that were not discontinued during the period of observation. 7.13 REASONS FOR DISCONTINUATION OF CONTRACEPTIVE USE Another perspective on discontinuation of modern contraceptive use is provided in Table 7.13, which shows the percent distribution of contraceptive use discontinuation in the five years preceding the survey by reason, according to method. The most common reason for discontinuing a method is desire to become pregnant (34 percent), followed by side effects or health concerns (22 percent) and becoming pregnant while using (16 percent). Data in Table 7.13 confirm what was presented in Table 7.12: the reason most often cited for discontinuing use of the pill, IUDs, and injectables is side effects or health concerns (45 percent, 64 percent, and 53 percent, respectively). 104 • Family Planning Table 7.13 Reasons for discontinuation Percent distribution of discontinuations of contraceptive methods in the five years preceding the survey by main reason stated for discontinuation, according to specific method, Pakistan 2012-13 Reason Pill IUD Injectables Condom Lactational amenorrhea Rhythm With- drawal All methods Became pregnant while using 12.9 3.2 4.8 20.4 17.3 13.0 25.4 16.2 Wanted to become pregnant 23.5 18.3 18.2 43.9 27.0 53.6 46.6 33.7 Husband disapproved 0.4 1.1 1.5 6.6 0.0 8.9 3.5 3.2 Wanted a more effective method 3.5 1.5 2.7 3.7 15.4 8.6 7.1 5.4 Side effects/health concerns 45.3 63.7 53.1 7.1 1.5 0.0 2.6 22.0 Lack of access/too far 2.1 0.0 4.1 3.0 0.2 0.0 0.3 1.9 Cost too much 0.0 0.4 0.3 0.3 0.0 0.0 0.2 0.2 Inconvenient to use 0.3 2.1 1.0 4.2 0.8 0.0 1.4 2.0 Up to God/fatalistic 1.0 0.3 0.3 0.6 15.2 5.7 1.2 2.5 Difficult to get pregnant/ menopausal 0.8 1.8 0.9 0.8 4.4 0.0 0.5 1.2 Infrequent sex/husband away 6.0 2.2 3.6 4.6 1.8 1.7 6.3 4.3 Marital dissolution/separation 0.0 0.0 0.3 0.0 0.0 0.0 0.1 0.1 Other 1.1 4.5 3.9 1.1 14.0 0.0 1.2 3.4 Don’t know 0.5 0.0 0.5 0.2 0.7 0.0 0.2 0.3 Missing 2.5 0.9 4.8 3.5 1.6 8.3 3.6 3.6 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Number of discontinuations 498 404 819 1,434 552 94 974 4,841 Note: Total includes 66 women who reported discontinuation while using other method not shown separately. 7.14 KNOWLEDGE OF FERTILE PERIOD An elementary knowledge of reproductive physiology provides a useful background for successful practice of coitus-related methods such as the rhythm method. The successful use of such methods depends in part on an understanding of when, during the ovulatory cycle, a woman is most likely to conceive. In the 2012-13 PDHS, respondents were asked “From one menstrual period to the next, are there certain days when a woman is more likely to get pregnant if she has sexual relations?” If the answer was yes, they were further asked whether that time was just before her menstrual period begins, during her period, right after her period has ended, or halfway between two periods. Table 7.14 shows that correct knowledge of the fertile period is negligible among Pakistani women, regardless whether they report themselves as current users of the rhythm method. Only 4 percent of women correctly responded that a woman is most likely to conceive halfway between her menstrual periods; 30 percent believe that the fertile period is right after a woman’s period has ended, 38 percent think that there is no specific fertile time, and 23 percent do not know when the fertile period falls. Table 7.14 Knowledge of fertile period Percent distribution of ever-married women age 15-49 by knowledge of the fertile period during the ovulatory cycle, according to current use of the rhythm method, and percent distribution of ever-married men age 15-49 by knowledge of the fertile period during the ovulatory cycle of women, according to ever use of rhythm method, Pakistan 2012-13 Women Men Perceived fertile period Current users of rhythm method Nonusers of rhythm method All women Ever users of rhythm method Nonusers of rhythm method All men Just before her menstrual period begins 8.3 2.6 2.6 3.0 4.2 4.0 During her menstrual period 5.4 2.9 2.9 0.1 0.6 0.6 Right after her menstrual period has ended 58.7 29.6 29.8 69.2 38.8 42.7 Halfway between two menstrual periods 4.7 4.0 4.0 10.1 6.3 6.8 Other 0.0 0.1 0.1 0.0 0.0 0.0 No specific time 8.8 38.0 37.8 9.0 22.3 20.5 Don’t know 14.1 22.5 22.5 8.6 27.8 25.3 Missing 0.0 0.3 0.2 0.0 0.0 0.0 Total 100.0 100.0 100.0 100.0 100.0 100.0 Number 86 13,472 13,558 408 2,726 3,134 Family Planning • 105 Table 7.14 also shows that 7 percent of men have correct knowledge of the fertile period. Men who have ever used the rhythm method are only slightly more likely than men who have never used the method to provide the correct answer (10 percent and 6 percent, respectively). 7.15 NEED AND DEMAND FOR FAMILY PLANNING SERVICES Data in this section provide information on the extent of need and potential demand for family planning services in Pakistan. The definition of unmet need for family planning has been revised so that levels of unmet need are comparable over time and across surveys (Bradley et al., 2012). In the past, the definition of unmet need was based on information from the contraceptive calendar and other questions that were not included in every survey. Previous PDHS surveys did not use the calendar. The revised definition uses only information that has been collected in every survey so that unmet need can be measured in the same way over time.1 Unmet need for family planning refers to fecund women who are not using contraception but who wish to postpone their next birth (spacing) or stop childbearing altogether (limiting). Specifically, women are considered to have an unmet need for spacing if they are: • At risk of becoming pregnant, not using contraception, and either do not want to become pregnant within the next two years or are unsure if or when they want to become pregnant. • Pregnant with a mistimed pregnancy. • Postpartum amenorrheic for up to two years following a mistimed birth and not using contraception. Women are considered to have an unmet need for limiting if they are: • At risk of becoming pregnant, not using contraception, and want no (more) children. • Pregnant with an unwanted pregnancy. • Postpartum amenorrheic for up to two years following an unwanted birth and not using contraception. Women who are classified as infecund have no unmet need because they are not at risk of becoming pregnant. Women who are using contraception are considered to have a met need. Women using contraception who say they want no (more) children are considered to have a met need for limiting, and women who are using contraception and say they want to delay having a child or are unsure if or when they want a (another) child are considered to have a met need for spacing. Unmet need, total demand, percentage of demand satisfied, and percentage of demand satisfied by modern methods are defined as follows: • Unmet need: the sum of unmet need for spacing and unmet need for limiting • Total demand for family planning: the sum of unmet need and total contraceptive use 1 Unlike the 2012-13 PDHS, the 1990-91 and 2006-07 PDHS surveys did not include the calendar in the Woman’s Questionnaire. In the PDHS, all currently married women, regardless of their sexual activity, were assumed to be exposed to the risk of pregnancy. Questions on recent sexual activity were not asked in the 1990-91 and 2006-07 PDHS surveys. 106 • Family Planning • Percentage of demand satisfied: total contraceptive use divided by the sum of unmet need and total contraceptive use (any method) • Percentage of demand satisfied by modern methods: total modern contraceptive use divided by the sum of unmet need and total contraceptive use (any method) Table 7.15 presents information on unmet need, met need, and total demand for family planning among currently married women according to whether the need or demand is for spacing or limiting births. Overall, 20 percent of currently married women have an unmet need for family planning, 9 percent have an unmet need for spacing, and 11 percent have an unmet need for limiting births. Thirty-five percent of women have a met need for family planning or are using a contraceptive method. If all currently married women who say they want to space or limit their children were to use a family planning method, the CPR would increase to 56 percent. Of the total demand for family planning methods, 64 percent is met by using any method and 47 percent is met by using modern methods. Table 7.15 Need and demand for family planning among currently married women Percentage of currently married women age 15-49 with unmet need for family planning, percentage with met need for family planning, the total demand for family planning, and the percentage of the demand for contraception that is satisfied, by background characteristics, Pakistan 2012-13 Unmet need for family planning Met need for family planning (currently using) Total demand for family planning1 Percentage of demand satisfied2 Percentage of demand satisfied by modern methods3 Number of women Background characteristic For spacing For limiting Total For spacing For limiting Total For spacing For limiting Total Age 15-19 14.6 0.3 14.9 9.6 0.7 10.3 24.2 1.0 25.2 41.0 27.3 594 20-24 18.2 2.4 20.6 16.3 5.1 21.3 34.5 7.5 41.9 50.9 35.5 2,053 25-29 13.5 8.6 22.1 16.5 14.8 31.2 30.0 23.4 53.4 58.5 39.3 2,663 30-34 8.9 12.5 21.4 10.2 31.5 41.7 19.1 44.0 63.0 66.1 49.8 2,454 35-39 3.4 17.7 21.2 4.6 43.3 47.9 8.0 61.0 69.0 69.3 53.0 2,137 40-44 1.1 18.5 19.7 1.0 43.2 44.2 2.1 61.8 63.8 69.2 52.1 1,617 45-49 0.8 13.5 14.3 0.3 34.2 34.5 1.1 47.7 48.8 70.7 55.0 1,419 Residence Urban 7.6 9.5 17.1 12.9 31.9 44.8 20.5 41.4 61.9 72.4 51.7 4,304 Rural 9.4 12.1 21.6 7.4 23.3 30.7 16.8 35.4 52.3 58.8 44.3 8,633 Region Punjab 7.4 10.3 17.7 10.2 30.5 40.7 17.6 40.8 58.3 69.7 49.7 7,374 Urban 7.3 9.3 16.6 12.1 34.7 46.9 19.4 44.0 63.5 73.8 50.8 2,402 Rural 7.4 10.8 18.2 9.3 28.4 37.7 16.7 39.2 55.9 67.5 49.1 4,972 Sindh 10.1 10.7 20.8 8.5 20.9 29.5 18.7 31.6 50.3 58.6 48.6 3,002 Urban 7.3 9.1 16.5 14.5 28.3 42.7 21.8 37.4 59.2 72.2 55.0 1,432 Rural 12.7 12.1 24.7 3.1 14.2 17.4 15.8 26.3 42.1 41.3 40.5 1,570 Khyber Pakhtunkhwa 9.0 16.5 25.5 6.5 21.6 28.1 15.4 38.1 53.6 52.4 36.4 1,855 Urban 9.1 12.8 21.8 12.0 32.0 44.0 21.1 44.7 65.8 66.8 46.2 308 Rural 9.0 17.3 26.2 5.3 19.6 24.9 14.3 36.8 51.1 48.7 33.9 1,547 Balochistan 20.7 10.5 31.2 8.6 10.9 19.5 29.3 21.3 50.6 38.4 32.3 553 Urban 14.1 10.4 24.5 11.0 13.3 24.4 25.1 23.8 48.9 49.8 42.7 110 Rural 22.3 10.5 32.8 8.0 10.2 18.2 30.3 20.7 51.1 35.7 29.8 443 ICT Islamabad 5.1 7.3 12.5 17.9 41.5 59.4 23.0 48.9 71.9 82.7 61.3 62 Gilgit Baltistan 10.9 9.8 20.7 8.3 25.4 33.6 19.2 35.1 54.3 61.9 51.9 91 Education No education 8.1 13.7 21.9 5.7 24.6 30.2 13.8 38.3 52.1 58.0 44.9 7,347 Primary 10.6 8.5 19.1 11.1 29.8 40.8 21.7 38.2 59.9 68.1 48.0 2,057 Middle 10.0 10.3 20.2 13.3 27.4 40.7 23.3 37.7 60.9 66.8 48.3 958 Secondary 9.7 7.0 16.7 15.6 28.3 43.9 25.4 35.3 60.6 72.5 51.2 1,351 Higher 8.1 6.6 14.6 17.4 26.4 43.8 25.5 33.0 58.5 75.0 50.8 1,225 Wealth quintile Lowest 10.3 14.2 24.5 4.9 15.9 20.8 15.2 30.1 45.4 45.9 40.0 2,501 Second 10.0 13.2 23.2 7.4 22.2 29.7 17.5 35.4 52.9 56.1 43.3 2,533 Middle 8.2 10.8 19.0 8.1 30.1 38.2 16.3 40.9 57.1 66.8 47.1 2,550 Fourth 9.0 9.8 18.8 12.0 29.5 41.5 21.0 39.3 60.3 68.8 50.2 2,677 Highest 6.7 8.6 15.3 13.4 32.4 45.8 20.0 41.0 61.1 75.0 51.8 2,676 Total 8.8 11.3 20.1 9.2 26.2 35.4 18.1 37.4 55.5 63.8 47.0 12,937 1 Total demand is the sum of unmet need and met need. 2 Percentage of demand satisfied is met need divided by total demand. 3 Modern methods include female sterilization, male sterilization, pill, IUD, injectables, implants, male condom, and lactational amenorrhea method (LAM). Family Planning • 107 Unmet need for family planning rises with age from 15 percent among women age 15-19 to 22 percent among women age 25-29 and decreases thereafter. Unmet need is higher in rural than in urban areas. Urban-rural variations at the regional level show a similar pattern. Unmet need is highest in Balochistan (31 percent) and lowest in ICT Islamabad (13 percent). In addition, unmet need is highest among women with no education (22 percent) and lowest among those with more than a secondary education (15 percent). Unmet need decreases with increasing wealth, from 25 percent in the lowest wealth quintile to 15 percent in the highest quintile. Demand for family planning is highest among women age 35-39 (69 percent) and lowest among women age 15-19 (25 percent). Urban women have a higher demand of family planning (62 percent) than their rural counterparts (52 percent). A similar pattern is seen by urban and rural residence at the regional level. As expected, demand for family planning is highest in ICT Islamabad (72 percent), while the demand ranges between 50 percent and 58 percent in the other regions. Demand for family planning services increases with increasing education and wealth quintile. For example, it is 52 percent among women with no education and 61 percent among women with a secondary education. Women age 45-49; those who live in urban areas, ICT Islamabad, and Punjab; those with a higher education; and those in the highest wealth quintile have the highest satisfied demand for modern methods. The population policy of Pakistan focuses on strengthening the management and supply of family planning methods to minimize unmet need for family planning services. Figure 7.3 shows that the level of unmet need in Pakistan has decreased from 25 percent in 2006-07 to 20 percent in 2012-13.2 Furthermore, although the total demand for family planning has not increased substantially over the period, the proportion of total demand satisfied has increased from 54 percent in 2006-07 to 64 percent in 2012-13. Demand generation and awareness campaigns need to be further streamlined and improved to address the missing links between supply and demand (MOPW, 2002). Figure 7.3 Trends in unmet need for family planning among currently married women age 15-49, 2006-07 and 2012-13 PDHS 25 30 55 54 20 35 56 64 Unmet need Current use Total demand Proportion of total demand satisfied Percent 2006-07 PDHS 2012-13 PDHS Note: Estimates are based on the revised definition of unmet need. 2 All of the unmet need estimates in Figure 7.3 have been recalculated using the revised definition of unmet need and may differ slightly from figures published in the final reports for each previous survey. 108 • Family Planning 7.16 FUTURE USE OF CONTRACEPTION An important indicator of the changing demand for family planning is the extent to which nonusers of contraception plan to use family planning in the future. In the 2012-13 PDHS, currently married women age 15-49 who were not using a contraceptive method were asked about their intention to use family planning in the future. The results are presented in Table 7.16. Thirty-nine percent of currently married women who reported not using any family planning methods said that they intend to use a family planning method in the future; 44 percent have no intention to use contraception, and 17 percent are unsure. The proportion of women who intend to use contraception increases with increasing number of living children, from 35 percent among those with no children to 45 percent among those with two children. Thereafter, the percentage decreases slightly to 42 percent among women with three children and 35 percent among women with four or more children. Whereas the proportion of women who do not intend to use family planning methods has not changed since 2006-07 (44 and 43 percent, respectively), the proportion of women who do intend to use family planning has decreased by 11 percentage points (50 and 39 percent, respectively). At the same time, indecisive attitudes among women have more than doubled; the proportion of women who are unsure has increased from 7 percent in 2006-07 to 17 percent in 2012-13. Table 7.16 Future use of contraception Percent distribution of currently married women age 15-49 who are not using a contraceptive method by intention to use in the future, according to number of living children, Pakistan 2012-13 Intention to use in the future Number of living children1 Total 0 1 2 3 4+ Intends to use 34.8 44.2 44.9 42.0 34.8 39.2 Unsure 27.9 19.3 15.3 11.9 12.4 16.5 Does not intend to use 37.2 36.4 39.7 45.4 52.4 44.1 Missing 0.1 0.1 0.2 0.7 0.4 0.3 Total 100.0 100.0 100.0 100.0 100.0 100.0 Number of women 1,310 1,520 1,350 1,182 2,994 8,356 1 Includes current pregnancy 7.17 EXPOSURE TO FAMILY PLANNING MESSAGES Information on the level of public exposure to a particular type of media allows family planning program managers to assess the most effective media for various target groups in the population. To gauge the effectiveness of such media in disseminating family planning information, respondents in the 2012-13 PDHS were asked whether they had heard or seen a family planning message on the radio or television or in newspapers or magazines in the past few months preceding the survey. Table 7.17 shows that 74 percent of ever-married women and 48 percent of ever-married men were not exposed to family planning messages through any of the specified media. A small percentage (3 percent) of women and 14 percent of men heard family planning messages on the radio. Men were twice as likely (49 percent) as women (25 percent) to have been exposed to family planning messages through television. Not surprisingly, men were much more likely to see messages in print media than women (22 percent and 4 percent, respectively). There is a sharp urban-rural contrast in exposure to family planning messages through television and print media. For example, 34 percent of women in urban areas are exposed to family planning messages through television, as compared with 20 percent of rural women. The corresponding percentages among men are 60 percent and 42 percent. Exposure of women and men to family planning messages through the media varies by region. For instance, 45 percent of women and 36 percent of men in ICT Islamabad are not exposed to any of the media, as compared with 9 in 10 women and 8 in 10 men in Gilgit Family Planning • 109 Baltistan. Exposure to family planning messages through all types of media increases with increasing education and wealth quintile. Overall, women were less likely to be exposed to media messages through radio (3 percent versus 11 percent) and television (25 percent versus 40 percent) in 2012-13 than in 2006- 07. Table 7.17 Exposure to family planning messages Percentage of ever-married women age 15-49 and ever-married men age 15-49 who heard or saw a family planning message on radio, on television, or in a newspaper or magazine in the past few months, according to background characteristics, Pakistan 2012-13 Women Men Background characteristic Radio Television Newspaper/ magazine None of these three media sources Number of women Radio Television Newspaper/ magazine None of these three media sources Number of men Age 15-19 2.9 18.5 2.5 80.8 605 (13.9) (37.6) (19.3) (59.3) 36 20-24 3.3 24.8 4.9 73.8 2,106 9.1 40.1 17.2 55.8 219 25-29 2.7 26.2 4.7 72.4 2,724 12.2 41.4 17.5 55.8 521 30-34 3.1 27.3 5.4 71.2 2,528 14.2 48.2 22.6 48.2 646 35-39 2.9 25.1 3.6 74.1 2,226 13.0 54.4 26.8 41.4 588 40-44 2.5 24.2 4.5 75.1 1,766 17.1 57.4 21.9 37.9 530 45-49 2.2 20.4 2.4 79.0 1,602 15.0 44.8 20.2 50.1 594 Residence Urban 3.5 34.1 7.5 64.8 4,536 13.0 59.7 28.4 37.0 1,107 Rural 2.5 20.0 2.6 78.9 9,022 14.4 42.3 17.8 53.2 2,027 Region Punjab 2.1 27.4 4.5 71.6 7,790 15.3 55.9 21.4 41.1 1,804 Sindh 3.0 25.2 3.6 74.1 3,133 13.4 38.2 21.0 57.1 796 Khyber Pakhtunkhwa 4.6 15.7 4.0 82.1 1,908 11.0 44.1 28.0 47.9 347 Balochistan 5.8 15.1 4.0 83.0 568 7.4 27.1 11.7 68.6 151 ICT Islamabad 5.5 53.4 16.2 44.8 64 20.8 56.5 28.8 35.6 18 Gilgit Baltistan 1.3 7.6 2.5 91.4 94 2.6 17.0 8.4 80.3 18 Education No education 1.8 15.6 0.3 83.7 7,736 10.7 27.8 1.5 68.8 905 Primary 2.5 29.2 3.8 69.9 2,156 12.6 46.2 14.5 51.6 657 Middle 3.0 30.5 6.8 67.3 993 14.3 58.2 22.4 36.4 525 Secondary 4.4 42.1 11.9 55.9 1,413 17.9 57.7 35.4 37.4 557 Higher 7.9 48.8 19.0 48.6 1,260 16.5 68.9 51.4 25.8 491 Wealth quintile Lowest 1.4 7.9 0.5 91.3 2,589 12.7 19.6 8.7 74.2 607 Second 1.9 16.2 1.2 82.6 2,676 15.9 38.3 16.8 56.2 574 Middle 2.9 25.0 2.7 73.9 2,700 14.3 53.3 19.2 44.2 567 Fourth 3.3 32.0 4.8 66.9 2,789 13.4 61.5 25.9 34.5 713 Highest 4.5 40.9 11.7 57.7 2,804 13.4 65.3 34.7 32.3 673 Total 2.8 24.7 4.3 74.2 13,558 13.9 48.5 21.6 47.5 3,134 Note: Figures in parentheses are based on 25-49 unweighted cases. Tables 7.18.1 and 7.18.2 show the percentages of ever-married women and men age 15-49 who have heard or seen a family planning message on the radio or television or in a newspaper or magazine in the past few months according to type of message received and background characteristics. 110 • Family Planning Table 17.8.1 shows that women have most often heard, seen, or read messages about having less children for a more prosperous life (43 percent), followed by messages about birth spacing (38 percent) and messages promoting the use of contraceptives (30 percent). The results for men differed from those for women. Table 7.18.2 shows that 67 percent of men heard, saw, or read messages about limiting family size, 52 percent were exposed to messages about birth spacing, and 29 percent were exposed to messages about the welfare of the family. Differentials by women’s and men’s background characteristics are not notable. Table 7.18.1 Exposure to specific family planning messages: Women Percentage of ever-married women age 15-49 who heard or saw a family planning message on radio, on television, or in a newspaper or magazine in the past few months by type of message received, according to background characteristics, Pakistan 2012-13 Background characteristic Limiting the family Late marriage Spacing children Use contra- ceptives Welfare of family Maternal and child health Less children mean prosperous life More children mean poverty and starvation Importance of breast- feeding Number of women Age 15-19 16.9 4.6 45.0 32.7 8.6 32.3 37.6 3.8 0.8 116 20-24 18.1 5.4 38.7 31.2 9.6 23.8 36.6 2.1 5.3 551 25-29 24.4 5.9 43.0 30.5 6.3 26.4 43.8 3.8 6.0 753 30-34 28.8 6.4 36.6 29.2 7.5 20.4 42.7 3.8 2.7 729 35-39 24.4 6.6 34.1 26.4 7.5 25.3 52.7 3.4 4.4 577 40-44 27.1 5.2 39.1 30.1 5.7 22.8 42.6 3.7 3.1 440 45-49 18.9 5.6 34.9 30.4 8.1 22.9 42.2 8.1 7.2 337 Residence Urban 22.8 6.3 35.0 24.7 9.0 22.1 45.6 3.4 3.6 1,597 Rural 24.8 5.6 41.1 33.8 6.1 25.6 41.5 4.3 5.3 1,907 Region Punjab 22.8 2.7 38.1 29.5 3.8 22.0 45.1 2.9 4.0 2,209 Sindh 25.2 9.5 39.9 37.1 14.4 25.0 35.6 5.0 2.2 812 Khyber Pakhtunkhwa 23.8 10.3 36.3 17.3 8.7 30.4 49.4 6.1 12.2 342 Balochistan 30.2 31.7 40.0 16.5 22.1 32.6 43.7 9.1 9.1 97 ICT Islamabad 42.2 4.6 30.0 23.0 17.3 31.5 53.1 3.9 1.8 35 Gilgit Baltistan 38.7 15.5 29.2 28.3 15.7 50.2 53.2 6.1 3.6 8 Education No education 20.1 6.3 39.6 31.2 6.1 22.8 36.8 3.7 4.8 1,260 Primary 23.4 3.7 37.1 30.7 5.8 21.0 42.8 3.9 4.3 649 Middle 25.2 5.2 41.3 31.1 8.5 33.1 45.4 3.9 6.5 325 Secondary 26.6 5.7 36.9 26.4 8.2 24.0 49.5 3.9 4.4 623 Higher 28.5 8.0 36.8 28.2 10.3 24.6 49.9 4.2 3.3 647 Wealth quintile Lowest 21.9 5.7 39.7 33.8 8.0 25.3 37.8 6.9 2.1 225 Second 18.7 8.1 40.8 34.0 6.3 29.2 40.0 5.1 7.9 465 Middle 24.2 5.4 41.0 33.3 4.3 22.7 37.8 2.0 5.2 706 Fourth 25.3 4.8 38.1 31.7 7.7 24.9 43.1 4.4 4.6 922 Highest 25.1 6.2 35.6 23.4 9.4 21.7 49.3 3.5 3.2 1,185 Total 23.9 5.9 38.3 29.7 7.4 24.0 43.4 3.9 4.5 3,504 Family Planning • 111 Table 7.18.2 Exposure to specific family planning messages: Men Percentage of ever-married men age 15-49 who heard or saw a family planning message on radio, on television, or in a newspaper or magazine in the past few months by type of message received, according to background characteristics, Pakistan 2012-13 Background characteristic Limiting the family Late marriage Spacing children Use contra- ceptives Welfare of family Maternal and child health Less children mean prosperous life More children mean poverty and starvation Importance of breast- feeding Number of men Age 15-19 * * * * * * * * * 15 20-24 55.7 3.4 48.5 8.8 18.8 6.3 28.8 3.1 0.0 97 25-29 54.1 6.6 56.3 13.1 23.8 17.1 19.8 2.2 3.4 230 30-34 68.6 10.7 55.9 13.0 31.0 8.9 16.1 3.0 0.5 335 35-39 74.7 8.8 53.9 15.9 29.7 11.5 15.9 2.9 1.3 344 40-44 65.7 4.4 48.9 9.2 32.5 11.9 21.6 6.6 0.8 329 45-49 70.8 10.6 44.5 20.3 30.1 10.1 20.5 1.3 1.9 297 Residence Urban 70.5 12.5 52.0 15.4 31.2 11.9 18.3 3.1 0.6 698 Rural 64.2 4.8 51.5 12.8 27.7 10.9 19.7 3.3 1.9 949 Region Punjab 69.2 9.4 62.1 11.8 27.0 8.0 17.3 3.7 0.3 1,062 Sindh 65.9 3.5 36.6 18.9 31.4 13.7 27.9 1.9 0.3 341 Khyber Pakhtunkhwa 57.0 6.7 20.6 14.0 33.6 22.9 15.7 3.7 8.7 181 Balochistan 65.8 17.8 52.3 21.7 45.0 24.4 12.2 2.1 2.7 47 ICT Islamabad 51.6 6.3 32.3 19.3 27.3 14.4 13.0 3.3 6.7 11 Gilgit Baltistan 46.8 0.0 47.1 19.2 35.7 14.9 12.6 1.2 0.0 4 Education No education 62.5 3.4 48.5 11.3 24.2 7.3 16.4 5.5 1.4 282 Primary 61.7 8.3 52.6 9.6 26.7 9.7 23.3 4.6 1.0 318 Middle 63.6 5.0 52.9 12.3 27.0 7.0 21.4 1.3 1.1 334 Secondary 78.9 14.5 56.3 15.6 31.3 13.3 19.2 1.6 0.9 349 Higher 66.3 8.2 47.9 19.3 35.1 18.1 15.5 3.8 2.3 364 Wealth quintile Lowest 51.3 5.0 42.9 11.8 20.9 12.7 23.8 8.8 1.1 157 Second 63.0 5.4 47.6 11.3 23.9 13.6 20.5 3.4 2.7 251 Middle 68.1 4.3 55.2 9.8 32.1 10.0 18.1 4.6 1.8 317 Fourth 67.5 4.9 55.6 13.5 33.0 9.2 16.3 2.5 1.0 466 Highest 73.0 16.5 50.6 19.2 29.0 12.8 20.4 1.1 0.8 456 Total 66.9 8.1 51.7 13.9 29.2 11.4 19.1 3.3 1.4 1,647 Note: An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 7.18 CONTACT OF NONUSERS WITH FAMILY PLANNING PROVIDERS When family planning providers visit women in their home or when women visit health facilities, health providers are expected to discuss reproductive needs and the contraceptive options available and to counsel women on adopting a method of family planning. In Pakistan, family planning services and information are provided by Family Welfare Workers and LHWs. To gain insight into the level of contact between nonusers and health workers, women who were not using contraception were asked whether any fieldworker had visited them during the 12 months preceding the survey and discussed family planning. Women were also asked whether they had visited a health facility in the 12 months preceding the survey for any reason and whether anyone at the facility had discussed family planning with them during the visit. This information is especially useful for determining if nonusers of family planning are being reached by family planning programs. Table 7.19 shows that fieldworkers discussed family planning with only 29 percent of nonusers during the 12 months preceding the survey. Three in four nonusers visited a health facility, but only 6 percent discussed family planning at the facility. Overall, 68 percent of women who could have been exposed to family planning information did not discuss family planning either during a field visit or at a health facility, indicating numerous missed opportunities to inform and educate women about family planning. The low levels of contact between nonusers and family planning providers do not vary substantially by background characteristics. 112 • Family Planning Table 7.19 Contact of nonusers with family planning providers Among women age 15-49 who are not using contraception, the percentage who during the past 12 months were visited by a fieldworker who discussed family planning, the percentage who visited a health facility and discussed family planning, the percentage who visited a health facility but did not discuss family planning, and the percentage who did not discuss family planning either with a fieldworker or at a health facility, by background characteristics, Pakistan 2012-13 Percentage of women who were visited by fieldworker who discussed family planning Percentage of women who visited a health facility in the past 12 months and who: Percentage of women who did not discuss family planning either with fieldworker or at a health facility Number of women Background characteristic Discussed family planning Did not discuss family planning Age 15-19 17.9 2.6 64.5 80.2 543 20-24 28.3 5.1 72.5 69.3 1,668 25-29 36.4 8.1 71.3 60.5 1,893 30-34 32.8 8.3 74.2 62.7 1,506 35-39 29.1 5.6 71.8 68.2 1,204 40-44 26.4 6.5 64.4 70.0 1,051 45-49 21.7 2.8 66.8 76.2 1,113 Residence Urban 22.4 6.4 73.4 73.3 2,607 Rural 32.0 5.9 69.1 65.6 6,370 Region Punjab 36.7 5.3 72.5 60.8 4,790 Sindh 23.1 8.1 81.3 72.0 2,248 Khyber Pakhtunkhwa 20.7 7.0 62.7 76.6 1,387 Balochistan 6.2 1.6 20.9 92.8 461 ICT Islamabad 18.9 8.9 63.8 75.5 27 Gilgit Baltistan 29.2 3.5 48.3 69.7 64 Education No education 27.8 5.6 69.1 69.1 5,515 Primary 34.8 5.8 72.9 63.4 1,316 Middle 30.9 5.9 71.9 66.4 603 Secondary 31.3 8.5 71.6 64.6 819 Higher 25.4 7.6 72.3 70.4 723 Wealth quintile Lowest 26.7 5.3 68.2 70.5 2,068 Second 30.7 5.6 69.7 66.7 1,925 Middle 34.3 6.5 70.3 63.0 1,727 Fourth 32.2 7.0 70.2 64.9 1,679 Highest 21.8 6.1 74.0 74.0 1,578 Total 29.2 6.1 70.3 67.8 8,977 7.19 LADY HEALTH WORKER SERVICES The National Program for Family Planning and Primary Health Care, also known as the Lady Health Worker Program, was launched in 1994 by the government of Pakistan with the objective of reducing poor health conditions through providing essential primary health care services to communities and improving national health indicators. The program contributes to the overall health sector goals of improving maternal, newborn, and child health; provision of family planning services; and integration of other vertical health promotion programs (Ministry of Health, 2013). Table 7.20 shows that 68 percent of women were aware of the existence of LHWs in their respective communities. Among those who were aware of LHWs, services received from these individuals in the 12 months preceding the survey included child vaccinations (20 percent), treatments for minor ailments (7 percent), contraceptive supplies (7 percent), and information on maternal and child health (4 percent). There are only small variations in awareness of the existence of LHWs by age. Rural women (73 percent) are more likely to know about the presence of LHWs than urban women (59 percent). Regional variations by residence are notable, ranging from 29 percent in rural Balochistan to 84 percent in rural Punjab. Variations in awareness of the presence of LHWs by educational level and wealth quintile are small. There is no clear pattern in services received according to age, education, or wealth quintile. Rural women and women living in Punjab and Khyber Pakhtunkhwa are more likely to receive vaccination services than other women. Overall, 22 percent of women who were aware of the presence of LHWs in their area did not receive any services. Family Planning • 113 Table 7.20 Service from lady health worker (LHWs) Percentage of currently married women age 15-49 who know about the presence of LHWs in their area and the percentage of these women by types of services received from LHWs in the last 12 months, according to background characteristics, Pakistan 2012-13 Percentage who know about the presence of LHWs in their area Number of women Among those who know about LHWs, the type of service received in the last 12 months: Background characteristic Information on mother and child health Contra- ceptive supplies Vaccination Treatment of minor ailments Other No service received Number of women Age 15-19 61.5 594 0.9 0.6 7.7 0.8 1.4 20.1 366 20-24 65.1 2,053 3.6 6.2 25.0 5.8 2.3 19.5 1,336 25-29 71.2 2,663 5.8 6.7 24.9 6.8 3.1 24.0 1,895 30-34 68.0 2,454 4.4 8.0 24.0 9.3 3.3 22.6 1,668 35-39 71.0 2,137 4.2 9.3 19.9 8.9 2.9 21.0 1,516 40-44 67.5 1,617 2.7 7.4 14.0 8.0 2.1 24.5 1,092 45-49 68.4 1,419 1.6 2.8 9.3 4.1 1.2 24.1 970 Residence Urban 59.4 4,304 4.6 5.3 14.8 4.5 1.5 22.0 2,558 Rural 72.8 8,633 3.6 7.3 22.2 8.1 3.0 22.6 6,285 Region Punjab 78.4 7,374 4.6 7.2 23.9 7.1 2.3 23.2 5,780 Urban 65.9 2,402 5.6 5.4 16.7 3.5 0.8 22.5 1,584 Rural 84.4 4,972 4.2 7.9 26.7 8.4 2.9 23.5 4,196 Sindh 57.3 3,002 1.8 3.2 7.3 3.5 1.5 26.9 1,721 Urban 46.3 1,432 2.0 3.4 8.0 3.8 1.5 24.4 662 Rural 67.4 1,570 1.8 3.0 6.9 3.3 1.6 28.5 1,058 Khyber Pakhtunkhwa 57.3 1,855 4.0 10.3 23.5 13.2 5.7 12.7 1,064 Urban 75.4 308 5.5 10.6 24.1 12.4 6.1 14.0 232 Rural 53.8 1,547 3.5 10.3 23.3 13.4 5.5 12.3 832 Balochistan 33.6 553 2.8 2.2 5.0 2.6 2.2 13.6 186 Urban 52.3 110 5.0 2.7 9.4 6.3 3.3 15.0 58 Rural 28.9 443 1.9 1.9 3.0 0.9 1.7 13.0 128 ICT Islamabad 44.7 62 2.7 5.6 9.9 3.6 0.6 25.7 28 Gilgit Baltistan 71.0 91 2.0 8.5 10.6 17.8 3.5 19.0 65 Education No education 67.5 7,347 2.5 5.9 20.1 7.2 2.4 22.5 4,962 Primary 73.6 2,057 6.1 8.2 22.5 8.0 3.2 22.5 1,514 Middle 75.0 958 7.1 7.8 18.1 7.1 3.0 20.5 719 Secondary 68.3 1,351 5.1 8.9 18.0 6.8 2.6 23.4 923 Higher 59.2 1,225 4.2 5.6 20.1 4.6 2.5 22.9 725 Wealth quintile Lowest 60.0 2,501 1.2 4.1 20.9 6.9 1.8 26.0 1,500 Second 70.6 2,533 3.8 7.5 21.7 8.6 2.7 23.5 1,789 Middle 78.3 2,550 4.9 7.3 21.9 9.1 3.6 21.5 1,996 Fourth 74.7 2,677 5.2 8.5 20.7 6.7 2.2 20.3 2,001 Highest 58.2 2,676 3.8 5.3 14.4 3.5 2.3 21.8 1,557 Total 68.4 12,937 3.9 6.7 20.1 7.1 2.6 22.4 8,843 7.20 SATISFACTION WITH FAMILY PLANNING SERVICE OUTLETS Client satisfaction is a key component in assessing the services provided at family planning outlets. In the 2012-13 PDHS, women who were aware of outlets that provided family planning services and had ever visited these service outlets were asked how satisfied they were with specific services offered. Table 7.21 shows that overall satisfaction with specific services is high (between 68 percent and 87 percent). Eighty percent or more of women are satisfied with the attitude of staff members, counseling services, timely treatment in case of emergency, follow-up care, staff punctuality, and provision of contraceptives. Women were less satisfied with infection prevention services, handling of complications, and timely referral to other facilities for better care. 114 • Family Planning Overall, respondents were more satisfied with services provided in private and nongovernmental facilities. However, they were more satisfied with provision of contraceptives in public facilities than in private facilities. Table 7.21 Satisfaction with family planning service outlets Among currently married women age 15-49 who know about a service outlet that provides family planning services and have ever visited these outlets, the percentage citing satisfaction towards the specific services by type of service outlet, Pakistan 2012-13 Outlet Overall satisfaction Service Government sector Private/NGO sector Other Provision of contraceptives 86.4 71.4 90.2 80.0 Follow-up care 79.4 87.7 71.4 82.8 Infection prevention 73.8 84.3 65.4 78.1 Counseling services 82.9 92.6 86.4 87.1 Timely treatment 79.3 92.4 69.8 84.8 Attitude of staff 83.2 93.4 74.6 87.4 Punctuality maintained by staff 78.6 87.2 70.8 82.1 Timely referring 67.6 75.4 60.1 70.8 Cooperative 65.9 72.5 51.5 68.4 Handle complications properly 72.8 78.5 56.2 75.0 Number of women 2,208 1,731 77 4,024 Note: Total includes 7 cases with missing information on source of service. 7.21 REASONS FOR NOT VISITING FAMILY PLANNING SERVICE OUTLETS Table 7.22 presents the distribution of women who know of a facility that provides family planning services but have never visited such an outlet, along with their reasons for not visiting the outlet. Fifty-two percent of women have never visited an outlet that provides family planning services. The most commonly cited reasons for not visiting such outlets were “no need” (63 percent), “wanted more children” (32 percent), and services already available at home (16 percent). Sixty percent of women age 15-19 did not visit a family planning outlet because they wanted more children. Women age 30-39 were more likely not to visit a family planning outlet because the services were available at their home. Women’s reported need to visit a family planning outlet decreased with increasing age, with 8 in 10 women age 45-49 not believing that it was necessary to visit a center. Urban women (20 percent) were more likely than their rural counterparts (15 percent) to say that the services were available at home. Rural women were more likely than urban women to mention that they did not visit a family planning outlet because of their desire for more children (36 percent versus 23 percent). This reason was most often cited in rural Sindh (62 percent). Overall, 70 percent or more of women in Punjab, Khyber Pakhtunkhwa, Gilgit Baltistan, and ICT Islamabad said that there was no need to visit an outlet. Women with no education and women in the lowest wealth quintile were more likely than better educated women and women in the higher quintiles to say that they did not visit a family planning outlet because they wanted more children. Family Planning • 115 Table 7.22 Reasons for not visiting family planning service outlets Among currently married women age 15-49 who know of an outlet that provides family planning services, the percentage who have never visited such an outlet and the percentage citing specific reasons for not visiting the outlet, by background characteristics, Pakistan 2012-13 Percentage of women who have never visited an outlet that provides family planning services Number of women who know of an outlet that provides family planning services Reasons for not visiting the outlet Background characteristic Get service at home No need to visit the center Wanted more children Other1 Number of women who have never visited an outlet Age 15-19 76.1 245 3.6 55.3 60.0 6.8 186 20-24 63.9 1,095 13.0 53.7 51.9 9.2 700 25-29 57.1 1,684 19.1 58.7 39.4 12.8 962 30-34 47.9 1,682 20.6 61.2 30.0 18.1 806 35-39 44.7 1,518 19.5 64.8 23.1 20.7 679 40-44 42.9 1,165 15.4 72.5 13.3 22.7 500 45-49 49.9 935 9.5 79.0 11.2 21.0 466 Residence Urban 51.8 2,809 19.6 65.6 23.3 15.2 1,456 Rural 51.5 5,515 14.6 61.6 36.3 16.7 2,842 Region Punjab 42.4 4,948 17.4 72.0 28.7 17.9 2,100 Urban 41.2 1,516 19.6 73.4 24.0 17.8 625 Rural 43.0 3,432 16.5 71.4 30.7 17.9 1,475 Sindh 67.5 2,013 12.9 45.9 43.3 12.6 1,360 Urban 67.4 997 19.0 58.1 24.2 12.6 672 Rural 67.6 1,017 6.9 33.9 62.0 12.6 688 Khyber Pakhtunkhwa 60.7 1,070 20.3 71.1 18.5 19.3 649 Urban 50.3 208 25.4 70.7 9.8 17.9 105 Rural 63.2 862 19.3 71.1 20.2 19.6 545 Balochistan 75.1 190 15.3 53.7 35.5 13.2 143 Urban 69.4 54 14.4 57.1 35.9 10.8 37 Rural 77.3 136 15.6 52.4 35.3 14.1 105 ICT Islamabad 43.6 40 18.2 69.8 14.1 15.2 17 Gilgit Baltistan 46.6 63 10.1 73.7 23.3 12.5 30 Education No education 52.6 4,452 12.7 58.7 35.6 18.2 2,343 Primary 46.9 1,389 20.1 66.4 30.9 15.7 651 Middle 47.9 672 21.2 71.9 23.6 14.1 322 Secondary 50.4 910 22.2 67.9 27.2 10.4 459 Higher 58.0 902 19.7 68.5 25.7 14.7 523 Wealth quintile Lowest 63.6 1,325 7.6 49.2 50.0 16.8 843 Second 51.2 1,565 13.8 57.2 34.0 20.2 801 Middle 46.5 1,754 19.2 68.3 28.9 16.2 815 Fourth 46.9 1,793 19.7 71.9 23.5 12.6 840 Highest 52.9 1,887 20.4 67.4 24.5 15.6 999 Total 51.6 8,324 16.3 63.0 31.9 16.2 4,298 Infant and Child Mortality • 117 INFANT AND CHILD MORTALITY 8 his chapter describes levels of and trends and differentials in early childhood mortality in Pakistan. Infant and child mortality rates are important indicators of a country’s socioeconomic development and quality of life, as well as the population’s health status. Measures of childhood mortality also contribute to a better understanding of the progress of population and health programs and policies. Analyses of mortality measures are useful in identifying promising directions for health and nutrition programs and improving child survival efforts. Disaggregation of mortality measures by socioeconomic and demographic characteristics helps to identify differentials in population subgroups and target high-risk groups for effective programs. Measures of childhood mortality are also useful for population projections. Childhood mortality in general and infant mortality in particular are often used as broad indicators of socioeconomic development or specific indicators of health status. Childhood mortality rates are used for monitoring a country’s progress toward Millennium Development Goal (MDG) 4, which aims for a two-thirds reduction in child mortality by the year 2015 (United Nations Development Programme, 2013). Results from the 2012-13 PDHS can be used to monitor the impact of major national neonatal and child health interventions, strategies, and policies such as Pakistan’s flagship Maternal, Newborn, and Child Health Program (MNCH), which was launched in 2005. The focus of the MNCH program has been twofold: to coordinate, improve, and promote primary health service delivery to end users and to elicit tangible behavior changes that will improve acceptance of, demand for, and utilization of those services. The program is in the process of deploying a new cadre of 12,000 community midwives with the aim of increasing skilled birth attendance in underserved communities and thus lowering neonatal and maternal mortality through early detection and timely referral of obstetric and newborn complications (Government of Pakistan, 2010b). In Pakistan, neonatal, postneonatal, infant, child, and under-five mortality rates are calculated from household surveys because the vital registration system is not complete. The reliability of mortality estimates depends on the accuracy and completeness of reporting and recording of births and deaths. Underreporting and misclassification are common, especially for deaths occurring early in life (World Health Organization, 2006a). The 2012-13 PDHS provides various measures of mortality. The mortality rates presented in this chapter are computed from information gathered in the pregnancy history section of the Woman’s T Key Findings • Infant and under-five mortality rates in the past five years are 74 and 89 deaths per 1,000 live births, respectively. At these mortality levels, 1 in every 14 Pakistani children die before reaching age 1, and 1 in every 11 do not survive to their fifth birthday. • Neonatal mortality has remained unchanged for the last 20 years, whereas infant mortality has decreased by 19 percent and under-five mortality has decreased by 24 percent over the same period. • The neonatal mortality rate in the past five years is 55 deaths per 1,000 live births, which is almost three times the postneonatal mortality rate. The perinatal mortality rate is 75 per 1,000 pregnancies. • Childhood mortality is relatively higher in Balochistan and Punjab than in the other provinces. 118 • Infant and Child Mortality Questionnaire. The 2012-13 PDHS asked all ever-married women age 15-49 to provide a complete history of their pregnancies in chronological order starting with the first pregnancy. Women were asked whether a pregnancy was single or multiple, the sex of the child, the date of birth (month and year), survival status, the age of the child on the date of the interview if alive, and, if not alive, the age at death of each child born alive or the duration in months of a pregnancy that ended before full term. Age at death was recorded in days for children dying in the first month of life, in months for children dying before their second birthday, and in years for children dying at later ages. Since the primary causes of childhood mortality change as children age—from biological factors to environmental factors—childhood mortality rates are expressed in age categories and are customarily defined as follows: • Neonatal mortality (NN): the probability of dying within the first month of life • Postneonatal mortality (PNN): the difference between infant and neonatal mortality • Infant mortality: the probability of dying between birth and the first birthday • Child mortality: the probability of dying between the first and fifth birthday • Under-five mortality: the probability of dying between birth and the fifth birthday All rates are expressed as deaths per 1,000 live births, except in the case of child mortality, which is expressed as deaths between age 1 and age 4 per 1,000 children surviving to age 1. Information on stillbirths and deaths that occurred within seven days of birth is used to estimate perinatal mortality, which is the number of stillbirths and early neonatal deaths per 1,000 stillbirths and live births. 8.1 ASSESSMENT OF DATA QUALITY The accuracy of mortality estimates depends on the sampling variability of the estimates and on nonsampling errors. Sampling variability and sampling errors are discussed in detail in Appendix B. Nonsampling errors depend on the extent to which the date of birth and age at death are accurately reported and recorded and the completeness with which child deaths are reported. Omission of births and deaths affects mortality estimates, displacement of birth and death dates impacts mortality trends, and misreporting of age at death may distort the age pattern of mortality. Typically, the most serious source of nonsampling errors in a survey that collects retrospective information on births and deaths is underreporting of births and deaths of children who were dead at the time of the survey. It may be that mothers are reluctant to talk about their dead children because of the sorrow associated with their death, or they may live in a culture that discourages discussion of the dead. The possible occurrence of these data problems in the 2012-13 PDHS is discussed in Appendix D. Underreporting of births and deaths is generally more severe the further back in time an event occurred. An unusual pattern in the distribution of births by calendar years is an indication of omission of children or age displacement. In the 2012-13 PDHS, the cutoff point for asking health-related questions was January 2007. Appendix Table D.4 shows that the overall percentage of births for which a month and year of birth were reported is almost 100 percent for both children who have died and children who are alive. Furthermore, Table D.4 shows that there is practically no age displacement across the 2007 boundary for either living or dead children. The distribution of living children and the total number of children do not show a deficit in 2007 in relation to 2008 or 2006, as denoted by the calendar year ratios. However, among dead children, there is a slight deficit in 2007. This transference of deceased children out of the five-year period preceding the survey likely leads to an underestimation of the true level of childhood mortality for that period. Infant and Child Mortality • 119 Underreporting of deaths is usually assumed to be higher for deaths that occur very early in infancy. Also, omission of deaths or misclassification of deaths as stillbirths may be more common among women who have had several children or in cases where a death occurred in the distant past. Two indicators are used to assess the impact of such issues on measures of child mortality: the ratio of deaths that occurred within the first seven days of life to deaths that occurred within one month and the ratio of neonatal deaths to infant deaths. It is hypothesized that omissions will be more prevalent among those who died immediately after birth than those who lived longer and more prevalent for events that took place in the distant past than for those that occurred in the more recent past. Table D.5 shows data on age at death for early infant deaths. Selective underreporting of early neonatal deaths would result in an abnormally low ratio of deaths within the first seven days of life to all neonatal deaths. Early infant deaths were not severely underreported in the 2012-13 PDHS, as suggested by the high ratio of deaths in the first seven days of life to all neonatal deaths (79 percent in the five years preceding the survey). Similarly, Table D.6 shows a relatively high proportion (77 percent) of infant deaths in the five years before the survey as occurring in the first month of life (neonatal). Heaping of age at death on certain digits is another problem that is inherent in most retrospective surveys. Misreporting of age at death biases age-specific estimates of mortality if the net result is transference of deaths between age segments for which the rates are calculated; for example, child mortality may be overestimated relative to infant mortality if children who died in the first year of life are reported as having died at age 1 or older. In an effort to minimize misreporting of age at death, interviewers were instructed to record deaths under one month in days and deaths under two years in months. In addition, they were trained to probe deaths reported at exactly one year or 12 months to ensure that they had actually occurred at 12 months. The distribution of deaths under two years during the 20 years prior to the survey by month of death shows that there is some heaping at 6, 12, and 18 months of age, with corresponding deficits in adjacent months (Table D.6). However, heaping at these ages is less pronounced for deaths in the five years preceding the survey, for which the most recent mortality rates are calculated, although there is some heaping at 8 and 18 months of age. 8.2 LEVELS AND TRENDS IN INFANT AND CHILD MORTALITY Table 8.1 presents neonatal, postnatal, infant, child, and under-five mortality rates for three successive five-year periods preceding the survey. The neonatal mortality rate in the most recent period (2008-2012) is 55 deaths per 1,000 live births. This rate is almost three times the postneonatal rate (19 deaths per 1,000 live births) during the same period. Therefore, the risk of dying for any Pakistani child who survived the first month of life is reduced enormously in the remaining 11 months of the first year of life. The infant mortality rate in the five years preceding the survey is 74 deaths per 1,000 live births, and the under-five mortality rate for the same period is 89 deaths per 1,000 live births. This means that 1 in every 14 Pakistani children die before reaching age 1, while 1 in every 11 do not survive to their fifth birthday. Table 8.1 Early childhood mortality rates Neonatal, postneonatal, infant, child, and under-five mortality rates for five-year periods preceding the survey, Pakistan 2012-13 Years preceding the survey Approximate time period of estimated rates Neonatal mortality (NN) Postneonatal mortality (PNN)1 Infant mortality (1q0) Child mortality (4q1) Under-five mortality (5q0) 0-4 2008-2012 55 19 74 17 89 5-9 2003-2007 60 28 88 19 105 10-14 1998-2002 59 33 92 23 113 1 Computed as the difference between the infant and neonatal mortality rates Mortality trends can be examined in two ways: by comparing mortality rates for three successive five-year periods preceding a single survey and by comparing mortality estimates obtained from various 120 • Infant and Child Mortality surveys. However, comparisons between surveys should be interpreted with caution because of variations in quality of data, time references, and sample coverage. In particular, sampling errors associated with mortality estimates are large and should be taken into account when examining trends between surveys. Data from the 2012-13 PDHS show that neonatal mortality decreased by only 7 percent over the 15-year period preceding the survey, from 59 to 55 deaths per 1,000 live births (Table 8.1). The corresponding declines in postneonatal, infant, and under-five mortality over the 15-year period are 42 percent, 20 percent, and 21 percent. Mortality trends can also be observed by comparing data from the 2012-13 PDHS with data from the 1990-91 and 2006-07 PDHS surveys (Figure 8.1). Infant and under-five mortality rates for the five years preceding the three surveys confirm a declining trend in all mortality rates except neonatal mortality. Infant mortality has decreased by 5 percent over the last five years, from 78 deaths per 1,000 live births in 2002-2006 to 74 per 1,000 live births deaths in 2008-2012. An even more impressive decline was observed in postneonatal mortality, which decreased by 21 percent (from 24 to 19 deaths per 1,000 live births) over the same period. Under-five mortality has declined by 5 percent over the last six years, from 94 deaths per 1,000 live births in 2002-2006 to 89 deaths per 1,000 live births in 2008-2012. Figure 8.1 Trends in childhood mortality, 1986-2012 51 39 91 30 117 54 24 78 18 94 55 19 74 17 89 Neonatal mortality Postneonatal mortality Infant mortality Child mortality Under-five mortality Deaths per 1,000 live births PDHS 1990-91 (1986-1990) PDHS 2006-07 (2002-2006) PDHS 2012-13 (2008-2012) Table 8.2 shows the same pattern of increasing neonatal mortality in all of the provinces except Khyber Pakhtunkhwa, where the neonatal mortality rate has decreased from 48 deaths per 1,000 live births to 41 deaths per 1,000 live births. Neonatal mortality has increased from 46 deaths per 1,000 live births to 63 deaths per 1,000 live births in Balochistan, from 44 to 54 deaths per 1,000 live births in Sindh, and from 58 to 63 deaths per 1,000 live births in Punjab. Under-five mortality is highest in Balochistan (111 deaths per 1,000 live births), followed by Punjab (105 deaths per 1,000 live births), Sindh (93 deaths per 1,000 live births), and Khyber Pakhtunkhwa (70 deaths per 1,000 live births). There has been a 10 percent increase in under-five mortality in Balochistan during the last 20 years; in contrast, under-five mortality has decreased by 29 percent in Khyber Pakhtunkhwa, by 21 percent in Punjab, and by 12 percent in Sindh during the same period. Infant and Child Mortality • 121 Table 8.2 Trends in early childhood mortality rates Trends in neonatal, postneonatal, infant, child, and under-five mortality rates for the 10-year periods preceding PDHS surveys by region, Pakistan 2012-13 Region Survey Approximate calendar years Neonatal mortality (NN) Postneonatal mortality (PNN)1 Infant mortality (1q0) Child mortality (4q1) Under-five mortality (5q0) Punjab 2012-13 PDHS 2003-2012 63 25 88 18 105 2006-07 PDHS 1997-2006 58 23 81 18 97 1990-91 PDHS 1981-1990 58 46 104 32 133 Sindh 2012-13 PDHS 2003-2012 54 20 74 20 93 2006-07 PDHS 1997-2006 53 28 81 22 101 1990-91 PDHS 1981-1990 44 36 81 27 106 KPK 2012-13 PDHS 2003-2012 41 17 58 13 70 2006-07 PDHS 1997-2006 41 22 63 13 75 1990-91 PDHS 1981-1990 48 31 80 20 98 Balochistan 2012-13 PDHS 2003-2012 63 34 97 15 111 2006-07 PDHS 1997-2006 30 18 49 11 59 1990-91 PDHS 1981-1990 46 26 72 31 101 1 Computed as the difference between the infant and neonatal mortality rates It is interesting to note that there has been an increase (although small) in neonatal mortality in the past 20 years. In 1990-91 neonatal mortality was estimated at 51 deaths per 1,000 live births during the five years preceding the survey, and in 2012-13 it is estimated to be 55 deaths per 1,000 live births for the five years preceding the survey. This indicates that there has been an 8 percent increase in the neonatal mortality rate over the last 20 years. This increase points to an alarming situation in which neonatal mortality in Pakistan has stagnated at a very high level relative to other neighboring countries. Unless the neonatal mortality rate begins to drop, it will be difficult for Pakistan to achieve MDG 4. With support from a number of donors, the government of Pakistan has invested in maternal health programs to achieve MDG 4 and its target of reducing under-five mortality to 52 per 1,000 live births by 2015 (Planning Commission, 2010). Since 1990, under-five mortality has decreased by 28 deaths per 1,000 (from 117 to 89). The question is, can Pakistan save an additional 37 child deaths in every 1,000 live births to achieve MDG 4 by 2015, given the slow pace the country has observed during the past two decades? Data from the 2012-13 PDHS show increased antenatal care and postnatal visits, improved delivery practices, and improved maternal health care indicators (see Chapter 9). These indicators are directly or indirectly related to neonatal health. Despite these improvements, neonatal mortality has remained the same over the past five years. An in-depth examination of the reasons for the stagnation in neonatal mortality is outside the scope of this report and is suggested for further analysis. 8.3 SOCIOECONOMIC DIFFERENTIALS IN CHILDHOOD MORTALITY Differentials in childhood mortality by socioeconomic characteristics are presented in Table 8.3. The findings must be interpreted with caution given the low precision of mortality estimates due to sampling errors. To minimize sampling errors associated with mortality estimates and to ensure a sufficient number of cases for statistical reliability, the mortality rates shown in the table are calculated for the 10- year period preceding the survey. 122 • Infant and Child Mortality Table 8.3 Early childhood mortality rates by socioeconomic characteristics Neonatal, postneonatal, infant, child, and under-five mortality rates for the 10-year period preceding the survey, by background characteristics, Pakistan 2012-13 Background characteristic Neonatal mortality (NN) Postneonatal mortality (PNN)1 Infant mortality (1q0) Child mortality (4q1) Under-five mortality (5q0) Residence Urban 47 17 63 11 74 Rural 62 26 88 20 106 Region Punjab 63 25 88 18 105 Urban 50 17 67 11 78 Rural 68 28 96 21 115 Sindh 54 20 74 20 93 Urban 42 14 56 14 68 Rural 62 24 86 25 109 Khyber Pakhtunkhwa 41 17 58 13 70 Urban 34 19 53 5 58 Rural 42 16 59 14 72 Balochistan 63 34 97 15 111 Urban 68 25 93 10 102 Rural 62 36 98 16 112 ICT Islamabad 26 9 35 9 43 Gilgit Baltistan 39 32 71 19 89 Mother’s education No education 65 27 92 23 112 Primary 54 25 79 16 93 Middle 48 21 68 4 72 Secondary 47 8 55 2 57 Higher 27 3 30 5 36 Wealth quintile Lowest 62 28 90 32 119 Second 67 30 97 20 115 Middle 63 21 85 15 98 Fourth 55 20 75 10 84 Highest 34 10 44 5 48 1 Computed as the difference between the infant and neonatal mortality rates Table 8.3 shows that mortality rates in all categories are higher in rural areas than in urban areas. For example, infant mortality in rural areas is 88 deaths per 1,000 live births, as compared with 63 deaths per 1,000 live births in urban areas. Rural-urban differences are also substantial in the case of neonatal, postneonatal, child, and under-five mortality rates. Moreover, there are wide differentials in infant and under-five mortality by region, with under-five mortality ranging from 111 deaths per 1,000 live births in Balochistan to 43 deaths per 1,000 live births in ICT Islamabad. Similarly, infant mortality is highest in Balochistan (97 deaths per 1,000 live births) and lowest in ICT Islamabad (35 deaths per 1,000 live births). Neonatal mortality is highest in Punjab and Balochistan (63 deaths per 1,000 live births each), followed by Sindh (54 deaths per 1,000 live births), Khyber Pakhtunkhwa (41 deaths per 1,000 live births), Gilgit Baltistan (39 deaths per 1,000 live births), and ICT Islamabad (26 deaths per 1,000 live births). A detailed analysis of the 1990-91 PDHS showed a similar neonatal mortality pattern, with higher odds of dying among children born in Punjab than among children born in other provinces (Mahmood, 2002). Infant and under-five mortality rates are considerably higher in rural areas than in urban areas in all of the provinces. In Sindh the under-five mortality rate is 60 percent higher in rural areas (109 deaths per 1,000 live births) than in urban areas (68 deaths per 1,000 live births), while in Balochistan it is 10 percent higher in rural than urban areas. The rural-urban difference in mortality is especially large for children age 1-4; in Khyber Pakhtunkhwa, the rate among these children is almost three times as high in rural areas as in urban areas, and in Punjab the rate is almost twice as high in rural as in urban areas. In Sindh, neonatal mortality is 48 percent higher in rural areas than in urban areas (Table 8.3). Infant and Child Mortality • 123 As expected, mother’s education is inversely related to child mortality. Under-five mortality among children born to mothers with no education (112 deaths per 1,000 live births) is almost twice that of children born to mothers with a secondary education (57 deaths per 1,000 live births) and more than three times that of children born to mothers with a higher education (36 deaths per 1,000 live births). Table 8.3 also shows that the risk of dying among children below age 5 gradually decreases with increasing household wealth, from 119 deaths per 1,000 live births in the poorest households to 48 deaths per 1,000 live births in the wealthiest households. 8.4 DEMOGRAPHIC DIFFERENTIALS IN MORTALITY Demographic characteristics of both mother and child play an important role in the survival of children. Table 8.4 shows that neonatal mortality is higher among male children and postneonatal mortality is higher among female children. Male mortality is generally higher than female mortality because, in the first month after birth, males are biologically weaker than females; as children become older, however, females are exposed to higher mortality than males mainly as a result of sociocultural and environmental factors, especially in South Asia (Das Gupta, 1987; Basu, 1989). As expected, the relationship between maternal age at birth and childhood mortality is generally U-shaped, being relatively higher among children born to mothers under age 20 and over age 30 than among children born to mothers in the 20-29 age group. This pattern is especially obvious in the case of neonatal and under-five mortality. In general, mortality rates are higher among first births and births of order seven or above than among births of order two or three. Table 8.4 Early childhood mortality rates by demographic characteristics Neonatal, postneonatal, infant, child, and under-five mortality rates for the 10-year period preceding the survey, by demographic characteristics, Pakistan 2012-13 Demographic characteristic Neonatal mortality (NN) Postneonatal mortality (PNN)1 Infant mortality (1q0) Child mortality (4q1) Under-five mortality (5q0) Child’s sex Male 61 21 82 17 98 Female 54 25 79 18 96 Mother’s age at birth <20 79 24 103 19 120 20-29 52 22 74 19 91 30-39 60 27 88 14 101 40-49 67 8 76 (20) (94) Birth order 1 63 17 80 13 93 2-3 47 20 68 16 82 4-6 52 23 75 21 95 7+ 89 41 130 23 150 Previous birth interval2 <2 years 87 39 126 29 151 2 years 34 18 52 16 67 3 years 36 17 54 7 60 4+ years 36 8 45 8 52 Birth size3 Small/very small 86 25 111 na na Average or larger 48 17 64 na na Note: Figures in parentheses are based on 250-499 unweighted person-years of exposure to the risk of death. na = Not available 1 Computed as the difference between the infant and neonatal mortality rates 2 Excludes first-order births 3 Rates for the five-year period before the survey 124 • Infant and Child Mortality The spacing of births is another factor that has a substantial impact on a child’s chances of survival. A short birth interval does not give the mother sufficient time to recuperate from the birth and to replenish her stores of nutrients used during pregnancy, especially in conditions of malnutrition (Mahmood, 2002). Generally, shorter birth intervals are associated with higher mortality, both during and after infancy. The 2012-13 PDHS data confirm this pattern. All childhood mortality rates show a strong relationship with the length of the previous birth interval. For example, neonatal mortality is two and a half times higher among children born less than two years after a preceding sibling than among children born more than two years after a previous child (87 deaths and 34 deaths per 1,000 live births, respectively). Similarly, under-five mortality is almost three times higher among children born less than two years after a preceding sibling than among children born four or more years after a previous child (151 deaths and 52 deaths per 1,000 live births, respectively). These findings are consistent with observations from other sources (Cecatti et al., 2008; Rutstein, 2005). Studies have shown that children’s birth weight is an important determinant of their survival chances. Since almost half of births in Pakistan occur at home, where children often are not weighed at birth, data on birth weight are available for only a small proportion of children (see Chapter 10). However, mothers in the 2012-13 PDHS were asked whether their child was very large, larger than average, average, smaller than average, or very small at birth, since this has been found to be a good proxy for a child’s weight. This question was asked regarding all children born since 2007. As expected, the size of the baby at birth and mortality are negatively associated. For example, 1 in 9 children regarded as very small or small at birth did not survive to the first year, as compared with 1 in 16 children regarded as average or large in size. 8.5 PERINATAL MORTALITY The 2012-13 PDHS asked women to report on any pregnancy losses that had occurred in the five years preceding the survey. For each pregnancy that did not end in a live birth, the duration of pregnancy was recorded. In this report, perinatal deaths include pregnancy losses of at least seven months’ gestation (stillbirths) and deaths to live births within the first seven days of life (early neonatal deaths). The perinatal mortality rate is the sum of stillbirths and early neonatal deaths divided by the sum of all stillbirths and live births. Information on stillbirths and infant deaths within the first week of life is highly susceptible to omission and misreporting. Nevertheless, retrospective surveys in developing countries provide more representative and accurate perinatal death rates than do vital registration systems and hospital-based studies. The distinction between a stillbirth and an early neonatal death may be a fine one, depending often on the observed presence or absence of faint signs of life after delivery. Table 8.5 shows that of the 12,389 reported pregnancies of at least seven months’ gestation in the five years preceding the survey, 412 were stillbirths and 522 were early neonatal deaths, yielding an overall perinatal mortality rate of 75 per 1,000 pregnancies and indicating only marginal improvement in the last six years.1 Because the rate is subject to a high degree of sampling variation, differences by background characteristics should be interpreted with caution. 1 Caution should be taken in comparing the overall perinatal mortality rate in 2012-13 with the rate in 2006-07 given that, unlike the 2012-13 PDHS, the 2006-07 PDHS did not include an event “calendar” for recording the outcomes of pregnancies in the five years preceding the survey. The revised 2006-07 PDHS result indicates a perinatal mortality rate of 73 per 1,000 pregnancies. Infant and Child Mortality • 125 Table 8.5 Perinatal mortality Number of stillbirths and early neonatal deaths, and the perinatal mortality rate for the five- year period preceding the survey, by background characteristics, Pakistan 2012-13 Background characteristic Number of stillbirths1 Number of early neonatal deaths2 Perinatal mortality rate3 Number of pregnancies of 7+ months’ duration Mother’s age at birth <20 50 69 104 1,136 20-29 251 241 65 7,546 30-39 102 183 84 3,402 40-49 9 30 127 305 Previous pregnancy interval in months4 First pregnancy 125 114 95 2,522 <15 99 131 129 1,784 15-26 106 149 68 3,769 27-38 47 52 42 2,364 39+ 34 75 56 1,951 Residence Urban 74 107 51 3,563 Rural 338 415 85 8,827 Region Punjab 229 317 77 7,088 Sindh 100 121 78 2,840 Khyber Pakhtunkhwa 53 55 63 1,707 Balochistan 29 25 88 619 ICT Islamabad 1 1 43 48 Gilgit Baltistan 1 2 37 88 Mother’s education No education 277 346 87 7,129 Primary 66 82 70 2,105 Middle 24 35 64 929 Secondary 27 40 54 1,235 Higher 19 18 37 991 Wealth quintile Lowest 146 156 101 3,010 Second 96 131 86 2,631 Middle 70 97 69 2,416 Fourth 63 86 62 2,412 Highest 37 51 46 1,920 Total 412 522 75 12,389 1 Stillbirths are fetal deaths in pregnancies lasting 7 or more months. 2 Early neonatal deaths are deaths at age 0-6 days among live-born children. 3 The sum of the number of stillbirths and early neonatal deaths divided by the number of pregnancies of 7 or more months’ duration, expressed per 1,000 4 Categories correspond to birth intervals of <24 months, 24-35 months, 36-47 months, and 48+ months. Pregnancies among the youngest and oldest women are more likely to end in a perinatal death than are pregnancies among women age 20-39. The perinatal mortality rate is highest (127 deaths per 1,000 pregnancies) among older mothers (age 40-49), followed by the youngest mothers (below age 20) (104 deaths per 1,000 pregnancies), and is highest among births that occur less than 15 months after the previous birth (129 deaths per 1,000 pregnancies). The perinatal mortality rate is higher in rural areas (85 deaths per 1,000 pregnancies) than in urban areas (51 deaths per 1,000 pregnancies) and higher in Balochistan than in the other regions. There are marked differences in perinatal mortality by mother’s education. It is more than twice as high among women with no education (87 deaths per 1,000 pregnancies) as among women with a higher education (37 deaths per 1,000 pregnancies). Perinatal mortality is lowest (46 deaths per 1,000 pregnancies) among women in the highest wealth quintile and highest among women in the lowest quintile (101 deaths per 1,000 pregnancies). 126 • Infant and Child Mortality The perinatal mortality rate not only is related to maternal health status but is also a sensitive indicator of the quality of maternal and neonatal health care (Richardus et al., 1997). There is an urgent need to design and implement programs that focus on reducing maternal and perinatal mortality and improving the health status of women. The Pakistan Initiative for Mothers and Newborns (PAIMAN), a project funded by the U.S. Agency for International Development (USAID), was recently implemented in 10 of the country’s districts, and results showed significantly greater reductions in perinatal mortality among women who were exposed to at least one PAIMAN intervention than among women who were not exposed to any of the interventions (Mahmood, 2010). The challenge is to scale up interventions that have the greatest impact on perinatal mortality and create a sustainable framework that will allow women and newborns across the country to reap the benefits of the PAIMAN project’s success. 8.6 HIGH-RISK FERTILITY BEHAVIOR The survival of infants and children depends in part on the demographic and biological characteristics of their mothers. Typically, the probability of dying in infancy is much greater among children born to mothers who are too young (under age 18) or too old (over age 34), children who are too closely spaced (children born less than 24 months after the preceding birth), and children born to mothers of high parity (more than three children). First births may be at increased risk of dying relative to births of other orders; however, this distinction is not included in the risk categories in Table 8.6 because it is not considered avoidable fertility behavior. Also, for the short birth interval category, only children with a preceding interval of less than 24 months are included. Short succeeding birth intervals are not included, even though they can influence the survivorship of a child, because of the problem of reverse causal effect (i.e., a short succeeding birth interval can be the result of the death of a child rather than being the cause of the death of a child). The risk is elevated when a child is born to a mother who has a combination of these risk characteristics. Table 8.6 shows the percentages of births occurring in the five years before the survey that fall into the various risk categories. A total of 58 percent of births in the last five years are in an avoidable high-risk category. In 37 percent of the cases, the risk is higher only because of a single-risk category (mother’s age, birth order, or birth interval), and in 21 percent of cases the risk is higher because of multiple risk categories. The largest groups of children at risk are those who are of a high birth order (20 percent) and those whose preceding birth interval was shorter than 24 months (14 percent). Eleven percent of births occur after an interval shorter than 24 months and at a birth order higher than three. Table 8.6 also shows the relative risk of dying for children born in the last five years by comparing the proportion dead in each risk category with the proportion dead among children with no risk factors. The single most detrimental factors are young age at birth, short birth intervals, and older age at birth. Children in these groups are 2.2 to 2.5 times more likely to die than children not in any risk category. Fortunately, only small percentages of children are born to very young mothers and older mothers; however, a sizable proportion of children are born after short intervals. The combination of a short birth interval and high birth order (above three) results in a risk ratio that is almost four times higher than births not in any high-risk group. Eleven percent of births fall into this category. The combination of an older mother, a short birth interval, and a high birth order also results in a risk ratio that is almost four times higher; however, only 2 percent of births fall into this category. Infant and Child Mortality • 127 Table 8.6 High-risk fertility behavior Percent distribution of children born in the five years preceding the survey by category of elevated risk of mortality, the risk ratio, and percent distribution of currently married women by category of risk if they were to conceive a child at the time of the survey, Pakistan 2012- 13 Births in the 5 years preceding the survey Percentage of currently married women1 Risk category Percentage of births Risk ratio Not in any high-risk category 20.8 1.00 21.2a Unavoidable risk category First-order births between age 18 and age 34 20.8 1.40 10.4 Single high-risk category Mother’s age <18 2.3 2.54 0.5 Mother’s age >34 1.1 2.23 5.4 Birth interval <24 months 14.2 2.32 10.0 Birth order >3 19.6 1.45 13.6 Subtotal 37.3 1.87 29.5 Multiple high-risk category Age <18 and birth interval <24 months2 0.2 (2.86) 0.1 Age >34 and birth interval <24 months 0.2 * 0.2 Age >34 and birth order >3 7.2 1.19 26.6 Age >34 and birth interval <24 months and birth order >3 2.2 3.68 3.0 Birth interval <24 months and birth order >3 11.3 3.75 9.1 Subtotal 21.1 2.89 39.0 In any avoidable high-risk category 58.3 2.24 68.5 Total 100.0 na 100.0 Number of births/women 11,977 na 12,937 Note: Risk ratio is the ratio of the proportion dead among births in a specific high-risk category to the proportion dead among births not in any high-risk category. 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. na = Not applicable 1 Women are assigned to risk categories according to the status they would have at the birth of a child if they were to conceive at the time of the survey: current age less than 17 years and 3 months or above 34 years and 2 months, latest birth less than 15 months ago, or latest birth being of order 3 or higher. 2 Includes the category age <18 and birth order >3 a Includes sterilized women The last column of Table 8.6 presents the distribution of currently married women according to category of increased risk. Women are placed in categories according to the status they would have at the birth of a child conceived at the time of the survey: women who were younger than 17 years and 3 months or older than 34 years and 2 months, women whose most recent birth was less than 15 months before the survey, and women whose most recent birth was of order three or higher. Many women are protected from the risk of pregnancy by contraception, postpartum insusceptibility, and prolonged abstinence; however, for the sake of simplicity, only sterilized women are classified as not being in any risk category. About 7 in 10 married women (69 percent) are susceptible to conceiving a child who will be at an increased risk of dying. Thirty percent of married women fall into a single high-risk category—mainly high-order births or short birth intervals—while 39 percent of women fall into a multiple high-risk category, mainly those who are above age 34 and have had three or more births. The figures in Table 8.6 demonstrate the strong contribution of short birth intervals and high birth order (the number of children the mother has had) to the risk of dying among children under age 5. Thus, infant and child mortality can be reduced substantially in Pakistan by using contraception to space and limit births. 128 • Infant and Child Mortality In view of the above, there is an urgent need to integrate birth spacing into strategies and programs. The Healthy Timings and Spacing of Pregnancies initiative (World Health Organization, 2006b) should be considered a priority in Pakistan because of its significant health benefits for mothers and babies and hence the family and community at large. It is associated with helping women and families make informed decisions about spacing and timing a pregnancy to achieve healthy pregnancy outcomes. The involvement of all stakeholders, especially health care providers, in promoting birth spacing and family planning as health interventions is essential. Therefore, all tiers of the public health care system, including basic health units, rural health centers, Tehsil hospitals, and district hospitals, need to provide family planning services as an integral component of the MNCH program. The USAID-funded Family Advancement for Life and Health (FALAH) project will seek support from health providers and community and religious leaders in promoting messages regarding birth spacing. Evidence shows that promoting birth spacing as a health intervention will also contribute significantly to reducing sociocultural and religious barriers to adoption of contraceptives (Mahmood, 2012). Expected results include increases in contraceptive use, reductions in unmet need, and declines in fertility, all of which will contribute to lowering neonatal mortality and achieving MDGs 4. Reproductive Health • 129 REPRODUCTIVE HEALTH 9 health care system aiming to reduce pregnancy-related morbidity and mortality must focus on maternal and newborn health. Reproductive health care, the care a woman receives before and during pregnancy, at the time of delivery, and soon after delivery, is important for the survival and well-being of the mother and her child. It encompasses the health care dimensions of family planning and prenatal, natal, and postnatal care with the aim of reducing maternal morbidity and mortality (Franny, 2013). The imperatives of reproductive health recognize the importance of a safe pregnancy and childbirth to the health of the mother and the newborn child, as well as recognizing that a healthy start in life is an essential step towards a sound childhood and a productive life. Maternal morbidity and mortality represent the largest and the most persistent gaps in health indicators between the developed and developing world, reflecting the dilapidated state of reproductive health care in some developing countries. Maternal mortality is also recognized as a key human rights issue (Rosenfield et al., 2006). According to the International Conference on Population and Development Action Program (ICPD), every woman has the right to enjoy good reproductive health, and every birth should be safe (United Nations, 1994). The Universal Declaration of Human Rights states that “motherhood and childhood are entitled to special care and assistance.” The importance of maternal health was recognized by the International Conference on Safe Motherhood held in 1987 and continued through the ICPD and the Millennium Development Goals (MDGs). The International Conference on Safe Motherhood included a declaration targeting a reduction in maternal mortality by at least half by the year 2000, while the ICPD targeted a reduction in maternal mortality to one half of the 1990 levels by 2000 and a further one-half reduction by 2015 (World Health Organization [WHO], United Nations Children’s Fund [UNICEF], and United Nations Population Fund [UNFPA], 2004). Unfortunately many developing countries, including Pakistan, are not on track to achieve these targets; Pakistan is unlikely to meet the MDGs in maternal health and child health by 2015. Pakistan’s Maternal, Newborn, and Child Health Program set a goal of reducing the maternal mortality ratio (MMR) to 140 maternal deaths per 100,000 live births by 2015 (Planning Commission, 2010). The MMR in Pakistan is 276 maternal deaths per 100,000 live births (National Institute of Population Studies A Key Findings • More than 7 in 10 mothers receive antenatal care from a skilled provider. • Thirty-seven percent of women make four or more antenatal care visits during their pregnancy. The median duration of pregnancy at the first antenatal visit is 3.7 months. • Sixty-four percent of mothers with a birth in the five years preceding the survey had their last birth protected against neonatal tetanus. • More than half of births in the past five years have been assisted by a skilled provider. • Three-fifths of women giving birth in the two years preceding the survey received postnatal care for their last birth in the first two days after delivery. • More than two in five newborns received a postnatal checkup in the first two days after birth. • More than 6 in 10 women face at least one problem in seeking health care for themselves when they are sick. 130 • Reproductive Health [NIPS] and Macro International Inc., 2008), indicating the dire state of reproductive health care and women’s rights. About 529,000 women are estimated to die every year as a result of problems related to pregnancy and childbirth, nearly all of them in developing countries. These countries also have the highest maternal morbidity and mortality rates (UNICEF, 2004). Moreover, there is evidence that for every woman who dies from a pregnancy-related complication, at least 30 suffer a disability (United States Agency for International Development [USAID], 2005). Further evidence shows that slightly more than half of the maternal deaths that take place in developing countries occur in the sub-Saharan African region, with the next highest number in South Asia. The vast majority of maternal deaths occur around the time of delivery and are attributed to a lack of skilled care at birth, yet about 60 million deliveries worldwide take place at home without skilled care each year (Yasir et al., 2009). Interventions needed to reach these women include provision of skilled birth attendants and emergency obstetric care (Campbell and Graham, 2006; NIPS and Macro International Inc., 2008). Pakistan’s National Health Policy (2009) aims to implement the strategy of protecting the population from hazardous diseases by promoting public health and upgrading curative health care facilities (Ministry of Health, 2009). The policy identifies a series of measures, programs, and projects as the means for enhancing equity, efficiency, and effectiveness in the health sector through focused interventions, including improved safe motherhood services and focused reproductive health services through a life cycle approach. Pakistan introduced a national program for maternal, neonatal, and child health in 2006, and the program was devolved to the provinces in 2010. Under this program, a new cadre of community midwives were introduced and maternal and child health services were strengthened in the public sector. Primary health care services were also extended through the lady health worker (LHW) program, which provides services through home visits in rural areas. LHWs contribute directly to improved hygiene and higher levels of contraceptive use, antenatal care, iron supplementation during pregnancy, growth monitoring of children, and vaccination of mothers and children. Various studies have shown that reproductive health practices and use of reproductive health care are shaped mainly by level of education, place of residence, region of residence, occupation, mobility, and religious beliefs (Maqsood, 2009; Midhet and Becker, 2010; Yasir et al., 2009). This chapter presents findings from the 2012-13 PDHS on reproductive health status and practices, focusing mainly on use of maternal health services. Differentials by women’s background characteristics and comparisons with the 1990-91 and 2006-07 PDHS surveys are also presented where appropriate. 9.1 ANTENATAL CARE Antenatal care (ANC) from a skilled provider is important to monitor pregnancy and reduce the risk of morbidity for the mother and baby during pregnancy and delivery. The quality of antenatal care can be monitored through the content of services received and the kind of information mothers are given during their visits. In 2012-13 PDHS, information on ANC coverage was obtained from all ever-married women who gave birth in the five years preceding the survey. For women with more than one live birth during the five-year period, information was collected on the most recent birth. Table 9.1 shows the percent distribution of mothers in the five years preceding the survey by source of antenatal care received during pregnancy, according to background characteristics. Women were asked to report on all health providers they saw for antenatal care for their most recent birth. However, if a woman saw more than one provider, only the provider with the highest qualification is considered in the table. Younger mothers (age 35 or below) are more likely to receive antenatal care from a skilled health provider than older mothers (age 35-49). The likelihood of receiving ANC from a skilled health provider declines with increasing number of children. More than 8 in 10 mothers receive care from a skilled health provider for their first birth (84 percent), as compared with 57 percent for births of order six and higher. Reproductive Health • 131 Table 9.1 Antenatal care Percent distribution of women age 15-49 who had a live birth in the five years preceding the survey by antenatal care (ANC) provider during pregnancy for the most recent birth and the percentage receiving antenatal care from a skilled provider for the most recent birth, according to background characteristics, Pakistan 2012-13 Antenatal care provider No ANC Total Percentage receiving antenatal care from a skilled provider1 Number of women Background characteristic Doctor Nurse/ midwife/ lady health visitor Lady health worker Dai/ traditional birth attendant Other Missing Mother’s age at birth <20 70.5 5.5 0.0 2.4 0.0 0.4 21.2 100.0 75.9 543 20-34 68.8 6.3 0.2 1.8 0.2 0.1 22.6 100.0 75.1 5,868 35-49 54.1 6.0 0.5 4.1 0.0 0.1 35.1 100.0 60.1 1,035 Birth order 1 78.7 5.6 0.1 1.5 0.1 0.2 13.9 100.0 84.2 1,437 2-3 72.7 5.6 0.1 1.6 0.1 0.1 19.9 100.0 78.3 2,699 4-5 63.3 6.9 0.3 2.2 0.5 0.1 26.7 100.0 70.2 1,737 6+ 49.9 7.3 0.4 3.7 0.1 0.1 38.5 100.0 57.1 1,572 Residence Urban 83.7 4.1 0.2 1.4 0.1 0.3 10.3 100.0 87.8 2,244 Rural 59.6 7.2 0.2 2.4 0.2 0.0 30.3 100.0 66.7 5,202 Region Punjab 69.8 8.0 0.3 2.0 0.1 0.2 19.5 100.0 77.8 4,180 Urban 81.7 5.7 0.2 1.8 0.0 0.5 10.1 100.0 87.4 1,254 Rural 64.7 9.0 0.4 2.1 0.2 0.0 23.5 100.0 73.7 2,927 Sindh 76.2 2.0 0.0 0.6 0.2 0.0 20.9 100.0 78.2 1,714 Urban 90.9 1.3 0.0 0.6 0.1 0.1 6.9 100.0 92.2 719 Rural 65.5 2.5 0.0 0.6 0.3 0.0 31.1 100.0 68.0 995 Khyber Pakhtunkhwa 53.8 6.7 0.2 1.6 0.1 0.1 37.5 100.0 60.5 1,117 Urban 81.1 3.9 0.4 0.7 0.2 0.0 13.7 100.0 85.0 177 Rural 48.7 7.3 0.1 1.8 0.1 0.1 42.0 100.0 55.9 941 Balochistan 27.7 2.9 0.1 12.9 0.5 0.3 55.7 100.0 30.6 348 Urban 49.9 4.0 0.4 5.8 0.0 0.0 39.9 100.0 53.8 68 Rural 22.2 2.7 0.0 14.6 0.6 0.3 59.6 100.0 24.9 280 ICT Islamabad 93.1 1.2 1.0 0.4 0.8 0.3 3.2 100.0 94.3 31 Gilgit Baltistan 46.2 17.7 0.2 1.8 0.0 0.0 33.9 100.0 64.0 56 Education No education 52.9 7.0 0.3 2.9 0.3 0.0 36.6 100.0 59.9 4,155 Primary 74.4 7.0 0.2 2.5 0.0 0.0 16.0 100.0 81.4 1,230 Middle 83.0 8.0 0.0 0.8 0.0 0.4 7.8 100.0 91.0 587 Secondary 91.6 3.7 0.3 0.2 0.0 0.1 4.1 100.0 95.3 792 Higher 95.8 1.4 0.2 0.3 0.0 0.6 1.7 100.0 97.2 682 Wealth quintile Lowest 46.3 4.6 0.0 3.3 0.5 0.1 45.2 100.0 50.9 1,698 Second 53.1 8.5 0.2 2.9 0.2 0.0 35.3 100.0 61.5 1,544 Middle 66.8 9.9 0.6 2.5 0.0 0.0 20.2 100.0 76.7 1,464 Fourth 81.8 5.0 0.1 1.3 0.0 0.2 11.5 100.0 86.9 1,469 Highest 93.7 2.9 0.3 0.3 0.1 0.4 2.3 100.0 96.6 1,272 Total 66.8 6.2 0.2 2.1 0.2 0.1 24.3 100.0 73.1 7,446 Note: If more than one source of ANC was mentioned, only the provider with the highest qualifications is considered in this tabulation. 1 Skilled provider includes doctor, nurse, midwife, and lady health visitor. There are large differences in the use of antenatal care services between urban and rural women. Eighty-eight percent of urban mothers receive antenatal care from a skilled health provider, as compared with only 67 percent of rural mothers. Across regions, the proportion of mothers reporting that they received antenatal care from a skilled health provider varies markedly, ranging from 31 percent in Balochistan to 94 percent in ICT Islamabad ANC coverage is 61 percent in Khyber Pakhtunkhwa and 78 percent in Punjab and Sindh. Very large urban-rural differentials are also observed within regions. For example, in Khyber Pakhtunkhwa 85 percent of women in urban areas were attended by a skilled health provider during ANC visits, as compared with 56 percent of women in rural areas. As the mother’s educational level and wealth increase, so does the likelihood that she will see a skilled health provider for care during pregnancy. Women with more than a secondary education are one and a half times as likely to receive antenatal care from a skilled health provider (97 percent) as women with no education (60 percent). Similarly, women in the highest wealth quintile are almost twice as likely 132 • Reproductive Health to receive care from a skilled health provider (97 percent) as women in the lowest wealth quintile (51 percent). There has been a substantial improvement over the past two decades in the proportion of mothers receiving antenatal care from a skilled health provider, increasing from 26 percent in 1990-91 to 61 percent in 2006-07 and 73 percent in 2012-13. Figure 9.1 shows that 73 percent of mothers receive antenatal care from skilled health providers (67 percent from a doctor and 6 percent from a nurse, midwife, or lady health visitor). Only 2 percent of women receive antenatal care from a traditional birth attendant (dai). Twenty-four percent of women receive no antenatal care at all. Figure 9.1 Source of antenatal care Doctor 67% Nurse/midwife/ lady health visitor 6% Other 3% No ANC 24% PDHS 2012-13 9.1.1 Number and Timing of Antenatal Visits Antenatal care is more beneficial in preventing adverse pregnancy outcomes when it is sought early in the pregnancy and is continued through delivery. The World Health Organization recommends that a woman without pregnancy complications have at least four visits to provide sufficient antenatal care (WHO, 2006c). It is possible during these visits to detect health problems associated with a pregnancy. In the event of complications, more frequent visits are advised and admission to a health facility may be necessary. Table 9.2 shows that more than one-third (37 percent) of pregnant women make four or more antenatal care visits during their pregnancy. Urban women are more likely (62 percent) to have four or more antenatal visits than rural women (26 percent). Forty-two percent of women make their first antenatal care visit during the first trimester of pregnancy. Urban women are almost twice as likely as rural women to start ANC in the first trimester (65 percent and 33 percent, respectively). The overall median length of pregnancy at the first antenatal care visit is 3.7 months (2.9 months in urban areas and 4.3 months in rural areas). Reproductive Health • 133 Appendix Table A9.1 shows, as expected, that women in ICT Islamabad are more likely than women in other regions to have four or more antenatal care visits (82 percent) and to make the first antenatal visit in the first trimester of pregnancy (73 percent). Consequently, the median length of pregnancy at first antenatal visit is lowest in ICT Islamabad (2.8 months). In other regions, the median length ranges from 3.4 months in Khyber Pakhtunkhwa to 4.4 months in Balochistan. The percentage of women with four or more antenatal care visits during their pregnancy has more than doubled over the last 20 years, from 14 percent in 1990-91 to 28 percent in 2006-07 and 37 percent in 2012-13. At the same time, the percentage of women who make their first antenatal visit in the first six months of pregnancy has increased from 20 percent in 1990-91 to 44 percent in 2006- 07 and 57 percent in 2012-13. 9.2 COMPONENTS OF ANTENATAL CARE The components of an antenatal care visit are an essential indicator of the quality of health services provided to pregnant women. Focused antenatal care hinges on the principle that every pregnancy is at risk of complications. Therefore, apart from receiving basic care, every pregnant woman should be assessed for her risk of complications during pregnancy or childbirth. Ensuring that every pregnant woman receives basic information about preexisting health conditions (e.g., anemia, hypertension), potential complications, and birth preparedness should be a routine part of antenatal care. To assess quality of antenatal care, mothers in the 2012-13 PDHS were asked a number of questions about selected types of examinations for their most recent live birth in the five years preceding the survey. Table 9.3 presents information on the percentage of women who took iron tablets or syrup during their last pregnancy in the five years preceding the survey. The table also shows the percentage of women who were informed about signs of pregnancy complications and were examined for such signs (by measuring blood pressure and weight, testing urine and blood, and conducting ultrasound procedures). Among women with a live birth in the past five years, 45 percent took iron tablets or syrup and 3 percent took intestinal parasite drugs. There are substantial variations in iron supplementation by background characteristics. Younger women, women pregnant with their first child, urban women, better educated women, and wealthier women are more likely than other women to have taken iron supplements during pregnancy. For example, 46 percent of both women under age 20 and women age 20-34 took iron supplements during pregnancy, as compared with 38 percent of women age 35-49. Women in ICT Islamabad are most likely to take iron supplements during pregnancy (80 percent); in other regions, the proportion of women who take iron supplements ranges between 17 percent (Balochistan) and 50 percent (Khyber Pakhtunkhwa). Women with more than a secondary education (77 percent) and women in the highest wealth quintile (68 percent) are more likely to have taken iron supplements during their pregnancy than women with less education and those in lower wealth quintiles. There are substantial urban-rural differences in the percentage of pregnant women taking iron supplements within regions. Table 9.2 Number of antenatal care visits and timing of first visit Percent distribution of women age 15-49 who had a live birth in the five years preceding the survey by number of antenatal care (ANC) visits for the most recent live birth, and by the timing of the first visit, and among women with ANC, median months pregnant at first visit, according to residence, Pakistan 2012-13 Number and timing of ANC visits Residence Total Urban Rural Number of ANC visits None 10.6 30.3 24.4 1 7.0 16.1 13.3 2-3 20.6 27.7 25.6 4+ 61.6 25.8 36.6 Don’t know/missing 0.3 0.1 0.1 Total 100.0 100.0 100.0 Number of months pregnant at time of first ANC visit No antenatal care 10.6 30.3 24.4 <4 64.9 32.7 42.4 4-5 13.3 15.0 14.5 6-7 7.6 14.4 12.4 8+ 3.5 7.5 6.3 Don’t know/missing 0.2 0.1 0.1 Total 100.0 100.0 100.0 Number of women 2,244 5,202 7,446 Median months pregnant at first visit (for those with ANC) 2.9 4.3 3.7 Number of women with ANC 2,008 3,623 5,631 134 • Reproductive Health Table 9.3 Components of antenatal care Among women age 15-49 with a live birth in the five years preceding the survey, the percentage who took iron tablets or syrup and drugs for intestinal parasites during the pregnancy of the most recent birth, and among women receiving antenatal care (ANC) for the most recent live birth in the five years preceding the survey, the percentage receiving specific antenatal services, according to background characteristics, Pakistan 2012-13 Among women with a live birth in the past five years, the percentage who during the pregnancy of their last birth: Number of women with a live birth in the past five years Among women who received antenatal care for their most recent birth in the past five years, the percentage with selected services: Number of women with ANC for their most recent birth Background characteristic Took iron tablets or syrup Took intestinal parasite drugs Informed of signs of pregnancy complica- tions Blood pressure measured Urine sample taken Blood sample taken Weighed Ultrasound taken Mother’s age at birth <20 46.2 1.4 543 47.5 81.6 56.4 51.2 38.5 85.7 426 20-34 45.8 2.5 5,868 51.2 86.9 63.0 57.5 54.0 90.0 4,535 35-49 38.0 2.9 1,035 47.0 82.2 49.2 45.8 47.4 82.0 670 Birth order 1 53.2 2.7 1,437 53.5 88.9 71.1 65.0 56.8 92.5 1,235 2-3 47.4 1.9 2,699 52.2 89.0 66.0 62.4 57.6 91.6 2,158 4-5 43.4 3.1 1,737 46.3 83.6 55.5 48.9 49.6 87.1 1,272 6+ 33.8 2.7 1,572 47.6 78.3 43.0 37.5 36.9 79.5 966 Residence Urban 57.2 2.9 2,244 52.3 93.4 80.6 77.1 72.0 94.1 2,008 Rural 39.3 2.3 5,202 49.3 81.8 49.9 43.7 41.0 85.8 3,623 Region Punjab 43.7 3.1 4,180 51.3 83.3 60.6 54.6 52.1 91.6 3,358 Urban 54.4 3.9 1,254 52.9 91.7 80.4 76.4 70.9 95.2 1,121 Rural 39.1 2.8 2,927 50.4 79.1 50.7 43.7 42.7 89.7 2,238 Sindh 49.2 1.6 1,714 42.8 89.9 58.7 57.2 50.2 86.8 1,355 Urban 61.7 1.3 719 49.5 96.0 82.5 80.6 75.3 93.5 669 Rural 40.1 1.8 995 36.3 83.9 35.5 34.4 25.6 80.4 685 Khyber Pakhtunkhwa 50.0 2.1 1,117 59.0 93.9 66.2 59.7 53.9 87.5 697 Urban 68.7 3.0 177 57.1 95.5 77.1 72.5 65.7 94.9 152 Rural 46.5 2.0 941 59.5 93.4 63.1 56.2 50.7 85.4 545 Balochistan 17.1 0.7 348 49.9 69.5 51.9 37.3 48.3 51.4 153 Urban 26.7 0.5 68 50.2 86.5 64.4 51.4 61.8 68.4 41 Rural 14.7 0.8 280 49.8 63.2 47.3 32.1 43.4 45.2 112 ICT Islamabad 79.5 3.3 31 76.2 97.7 92.9 90.3 93.7 96.0 30 Gilgit Baltistan 30.0 1.5 56 66.8 88.9 66.4 60.7 65.5 72.7 37 Education No education 33.8 1.9 4,155 45.1 78.4 43.3 37.3 33.0 82.3 2,632 Primary 47.0 3.7 1,230 50.7 87.7 63.8 55.3 54.9 90.4 1,034 Middle 55.7 2.5 587 54.7 91.3 72.9 66.7 61.8 94.5 539 Secondary 62.4 3.2 792 59.4 95.9 83.3 82.6 78.9 96.2 759 Higher 77.1 2.9 682 57.2 97.2 90.1 88.9 84.5 98.2 667 Wealth quintile Lowest 28.6 1.4 1,698 41.1 71.2 30.4 25.5 21.3 76.7 929 Second 34.5 1.6 1,544 46.7 80.2 43.3 36.0 34.8 81.6 1,000 Middle 43.1 3.2 1,464 48.0 83.5 56.8 48.1 46.5 88.9 1,168 Fourth 55.8 3.3 1,469 56.4 92.3 74.2 68.9 62.4 93.8 1,297 Highest 67.6 3.3 1,272 56.3 97.2 87.6 87.4 83.5 98.1 1,238 Total 44.7 2.5 7,446 50.4 85.9 60.8 55.7 52.1 88.7 5,631 Eighty-nine percent of mothers who received antenatal care reported that they had an ultrasound procedure, and 86 percent had their blood pressure measured. More than half of pregnant women had their weight taken and were informed about pregnancy complications during their antenatal visit, and 56 percent provided a urine sample. Quality of antenatal care is related to women’s residence, education, and wealth. For example, 90 percent of women with a higher education provided urine samples for testing, as compared with 43 percent of women with no education. Similarly, virtually all women with more than a secondary education (98 percent) had an ultrasound, as compared with about 82 percent of women with no education. Large urban- rural differences are also found within regions. In rural Balochistan, 32 percent of women provided a blood sample, while the corresponding proportion in urban Balochistan was 51 percent. Reproductive Health • 135 With regard to information about pregnancy complications, however, there was little variation by residence, wealth quintile, or education. Overall, exactly half of the women were informed about pregnancy complications during their antenatal visit. The overall quality of antenatal care has improved substantially in the past six years. For example, the percentage of women who had blood tests increased from 44 percent in 2006-07 to 56 percent in 2012- 13. At the same time, the proportion of women receiving information about pregnancy complications during their antenatal care visit has doubled, from 25 percent in 2006-07 to 50 percent in 2012-13. 9.3 TETANUS TOXOID VACCINATIONS Neonatal tetanus is the leading cause of infant death in developing countries, where a considerable proportion of deliveries take place at home or at health facilities with poor hygienic conditions. Tetanus toxoid injections are given to women during pregnancy to prevent maternal and neonatal tetanus. For full protection, women should receive at least two doses of tetanus toxoid during their pregnancy. If a woman has been vaccinated during a previous pregnancy, however, she may require only one dose for the current pregnancy if the previous pregnancy occurred within 3 years of the last live birth. Five doses are considered to provide lifetime protection against tetanus. Table 9.4 shows that 59 percent of pregnant women received two or more tetanus injections during their last pregnancy, and 64 percent of women who had a live birth in the five years preceding the survey had their last live birth protected against neonatal tetanus. It is clear that tetanus toxoid vaccination coverage among pregnant women in Pakistan is far from universal. Differentials in tetanus toxoid coverage across subgroups of women are similar to those in other maternal health indicators. Births to younger women, those who are first-time mothers, women in urban areas, better educated women, and those in the highest wealth quintile are most likely to be protected against tetanus. Also, protection against tetanus is highest for births in ICT Islamabad (86 percent) and lowest for births in Balochistan (23 percent). As shown in Table 9.4, the urban-rural difference in women receiving two or more tetanus toxoid injections during their last pregnancy within regions is highest in Balochistan (42 percent in urban areas and 18 percent in rural areas). Table 9.4 Tetanus toxoid injections Among mothers age 15-49 with a live birth in the five years preceding the survey, the percentage receiving two or more tetanus toxoid injections during the pregnancy for the last live birth and the percentage whose last live birth was protected against neonatal tetanus, according to background characteristics, Pakistan 2012-13 Background characteristic Percentage receiving two or more injections during last pregnancy Percentage whose last birth was protected against neonatal tetanus1 Number of mothers Mother’s age at birth <20 53.3 55.5 543 20-34 61.3 67.1 5,868 35-49 45.9 50.2 1,035 Birth order 1 66.3 66.8 1,437 2-3 64.6 71.5 2,699 4-5 57.0 64.0 1,737 6+ 42.8 48.3 1,572 Residence Urban 69.5 75.3 2,244 Rural 53.8 59.0 5,202 Region Punjab 67.9 73.8 4,180 Urban 73.2 78.9 1,254 Rural 65.7 71.7 2,927 Sindh 48.4 53.5 1,714 Urban 69.3 74.6 719 Rural 33.3 38.3 995 Khyber Pakhtunkhwa 51.0 55.6 1,117 Urban 57.1 65.5 177 Rural 49.9 53.7 941 Balochistan 20.9 23.2 348 Urban 38.1 42.3 68 Rural 16.7 18.5 280 ICT Islamabad 75.4 85.8 31 Gilgit Baltistan 45.3 51.8 56 Education No education 45.0 50.3 4,155 Primary 66.9 73.2 1,230 Middle 74.2 79.5 587 Secondary 82.0 86.2 792 Higher 85.1 90.9 682 Wealth quintile Lowest 35.3 40.8 1,698 Second 50.3 54.2 1,544 Middle 63.4 69.5 1,464 Fourth 69.5 75.8 1,469 Highest 81.4 86.5 1,272 Total 58.6 63.9 7,446 1 Includes mothers with two injections during the pregnancy of their last birth or two or more injections (the last within 3 years of the last live birth), three or more injections (the last within 5 years of the last birth), four or more injections (the last within 10 years of the last live birth), or five or more injections at any time prior to the last birth 136 • Reproductive Health Between 2006-07 and 2012-13, the percentage of mothers who received at least two doses of tetanus toxoid for their last birth increased from 53 percent to 56 percent. At the same time, the percentage of most recent births protected against neonatal tetanus increased from 60 percent in 2006-07 to 64 percent in 2012-13. 9.4 PLACE OF DELIVERY Proper medical attention and hygienic conditions during delivery reduce the risk of complications and infections that may cause death or serious illness for the mother, the baby, or both. Hence, an important component in efforts to reduce the health risks of mothers and children is to increase the proportion of babies delivered in a safe and clean environment under the supervision of skilled health professionals. Pakistan’s provincial maternal, neonatal, and child health programs promote skilled birth attendance by introducing trained community midwives in rural areas and providing delivery services by lady health visitors in basic health units and rural health centers. Table 9.5 presents the percent distribution of live births in the five years preceding the survey by place of delivery, according to background characteristics. Forty-eight percent of births in Pakistan take place in a health facility; 15 percent are delivered in a public facility and 34 percent in a private facility. More than half of births (52 percent) take place at home. Delivery in a health facility is more common among mothers under age 35 and urban mothers. More than two-thirds (68 percent) of births in urban areas take place in a health facility, as compared with 40 percent in rural areas. The likelihood of delivering in a health facility increases with increasing number of children, number of antenatal visits, education, and wealth quintile. For example, 65 percent of first-time mothers deliver in a health facility, as compared with 51 percent of mothers with two to three births and 33 percent of mothers with six or more births. Delivery in a health facility also varies by region, ranging from 16 percent in Balochistan to 86 percent in ICT Islamabad. There is a strong association between health facility delivery and mother’s education and wealth quintile. Only 34 percent of births to uneducated mothers occur in a health facility, as compared with 90 percent of births to mothers with a higher education. Similarly, delivery at a health facility is markedly lower among births in the lowest wealth quintile (27 percent) than among those in the highest quintile (84 percent). The urban-rural difference in health facility deliveries within regions is highest in Sindh (78 percent and 47 percent, respectively). In Khyber Pakhtunkhwa, the corresponding proportions are 63 percent in urban areas and 36 percent in rural areas. Reproductive Health • 137 Table 9.5 Place of delivery Percent distribution of live births in the five years preceding the survey by place of delivery and percentage delivered in a health facility, according to background characteristics, Pakistan 2012-13 Health facility Home Other Missing Total Percentage delivered in a health facility Number of births Background characteristic Public sector Private sector Mother’s age at birth <20 16.2 32.6 50.9 0.2 0.2 100.0 48.7 1,086 20-34 14.9 34.3 50.6 0.1 0.1 100.0 49.2 9,614 35-49 10.8 29.6 59.4 0.0 0.1 100.0 40.4 1,277 Birth order 1 17.3 47.1 35.2 0.1 0.2 100.0 64.5 2,783 2-3 16.9 34.3 48.6 0.0 0.2 100.0 51.2 4,374 4-5 12.5 26.6 60.7 0.1 0.1 100.0 39.1 2,564 6+ 9.2 23.6 67.1 0.1 0.1 100.0 32.7 2,256 Antenatal care visits1 None 5.4 11.6 82.5 0.1 0.4 100.0 17.0 1,815 1-3 14.7 33.4 51.8 0.0 0.0 100.0 48.1 2,897 4+ 22.5 55.8 21.6 0.0 0.0 100.0 78.3 2,723 Residence Urban 22.2 45.7 31.7 0.1 0.3 100.0 67.9 3,489 Rural 11.5 28.7 59.7 0.1 0.1 100.0 40.1 8,488 Region Punjab 14.6 34.0 51.3 0.0 0.2 100.0 48.5 6,859 Urban 24.4 40.7 34.3 0.1 0.5 100.0 65.1 2,007 Rural 10.5 31.2 58.3 0.0 0.1 100.0 41.7 4,852 Sindh 14.0 44.6 41.4 0.0 0.0 100.0 58.6 2,740 Urban 17.6 60.0 22.4 0.0 0.0 100.0 77.6 1,070 Rural 11.8 34.7 53.5 0.0 0.0 100.0 46.5 1,670 Khyber Pakhtunkhwa 16.5 24.0 59.3 0.2 0.0 100.0 40.5 1,654 Urban 23.3 39.7 36.9 0.2 0.0 100.0 63.0 267 Rural 15.2 21.0 63.6 0.2 0.0 100.0 36.2 1,388 Balochistan 7.7 8.1 83.1 0.2 0.8 100.0 15.8 590 Urban 14.9 15.7 68.9 0.1 0.4 100.0 30.6 107 Rural 6.2 6.4 86.3 0.2 0.9 100.0 12.6 484 ICT Islamabad 54.7 31.7 12.9 0.0 0.7 100.0 86.4 47 Gilgit Baltistan 23.1 19.5 57.3 0.2 0.0 100.0 42.6 87 Mother’s education No education 10.4 23.6 65.9 0.1 0.1 100.0 34.0 6,852 Primary 16.8 35.2 47.9 0.1 0.1 100.0 52.0 2,039 Middle 22.4 43.8 33.6 0.0 0.3 100.0 66.2 905 Secondary 23.7 52.2 23.8 0.0 0.3 100.0 75.9 1,209 Higher 21.1 68.6 9.6 0.0 0.7 100.0 89.7 973 Wealth quintile Lowest 7.7 19.4 72.8 0.0 0.1 100.0 27.1 2,864 Second 10.3 23.5 66.0 0.1 0.1 100.0 33.8 2,535 Middle 14.5 31.1 54.2 0.1 0.1 100.0 45.6 2,346 Fourth 22.0 41.4 36.3 0.0 0.2 100.0 63.4 2,349 Highest 21.8 62.2 15.6 0.0 0.4 100.0 84.0 1,883 Total 14.6 33.6 51.6 0.1 0.1 100.0 48.2 11,977 Note: Total includes 11 cases with missing information on number of antenatal care visits. 1 Includes only the most recent birth in the 5 years preceding the survey Figure 9.2 shows that there has been significant progress in the percentage of births that take place in a health facility. The proportion has increased by 14 percentage points, from 34 percent in 2006-07 to 48 percent in 2012-13. At the same time, home delivery has declined drastically, from 85 percent in 1990-91 to 65 percent in 2006-07 and 52 percent in 2012-13. 138 • Reproductive Health Figure 9.2 Trends in place of delivery 13 85 34 65 48 52 Delivery at health facility Delivery at home Percentage 1990-91 PDHS 2006-07 PDHS 2012-13 PDHS 9.5 ASSISTANCE DURING DELIVERY Obstetric care provided by a qualified health professional during delivery (skilled birth attendance) is recognized as the most critical factor in reducing maternal and neonatal mortality. Births delivered at home are more likely to be delivered without assistance from a skilled provider, whereas births delivered at a health facility are more likely to be delivered by skilled health professionals. Women who had a live birth in the five years preceding the survey were asked who assisted in the delivery. Interviewers recorded multiple responses if more than one person assisted. However, for tabulation purposes, only the most qualified attendant was considered if there was more than one in attendance. Table 9.6 shows the type of health provider who assisted during delivery by selected background characteristics. A little over half (52 percent) of births take place with the assistance of a skilled health provider (doctor, nurse, midwife, or lady health visitor). Traditional birth attendants assist with less than half (41 percent) of all deliveries, while friends and relatives assist with 6 percent of deliveries. Less than 1 percent of births are delivered with no assistance. Skilled health providers are more likely to deliver births to women less than age 20 and first-order births (55 percent and 68 percent, respectively) than to deliver births to older women (age 35-49) and higher order births (44 percent and 36 percent, respectively). Births in urban areas are much more likely to be assisted by a skilled health provider (71 percent) than births in rural areas (44 percent). As expected, 9 in 10 (88 percent) births in ICT Islamabad are attended by a skilled health provider, as compared with 18 percent in Balochistan. There is a strong positive relationship between mother’s education and delivery by a skilled health provider. Births to women with more than a secondary education are more than twice as likely to receive assistance from a skilled health provider as births to uneducated mothers (92 percent and 38 percent, respectively). Similarly, assistance during delivery by a skilled health provider increases with increasing wealth. Births to women in the highest wealth quintile are almost three times as likely to be assisted by a skilled health provider as births to women in the lowest wealth quintile (85 percent and 30 percent, respectively). There are marked differentials by urban and rural areas within regions in assistance by skilled providers. In all regions, the proportion in urban areas is 20-30 percentage points higher than in rural areas. Reproductive Health • 139 Table 9.6 Assistance during delivery Percent distribution of live births in the five years preceding the survey by person providing assistance during delivery, percentage of births assisted by a skilled provider, and percentage delivered by caesarean section, according to background characteristics, Pakistan 2012-13 Person providing assistance during delivery Total Percentage delivered by a skilled provider1 Percentage delivered by C-section Number of births Background characteristic Doctor Nurse/ midwife/ lady health visitor Traditional birth attendant Relative/ other No one Don’t know/ missing Mother’s age at birth <20 44.2 10.7 37.1 7.2 0.2 0.5 100.0 55.0 13.5 1,086 20-34 42.6 10.3 40.9 5.6 0.2 0.4 100.0 52.9 14.8 9,614 35-49 34.5 9.3 46.7 8.3 0.7 0.4 100.0 43.8 8.9 1,277 Birth order 1 57.4 11.0 28.1 3.0 0.1 0.4 100.0 68.4 22.7 2,783 2-3 45.0 10.2 38.3 5.6 0.2 0.5 100.0 55.3 16.5 4,374 4-5 33.2 10.1 49.6 6.6 0.2 0.3 100.0 43.3 8.6 2,564 6+ 26.6 9.4 53.3 10.0 0.6 0.2 100.0 36.0 4.8 2,256 Antenatal care visits2 None 12.4 8.4 61.3 16.7 0.5 0.8 100.0 20.8 2.1 1,815 1-3 39.0 13.2 42.1 5.0 0.4 0.2 100.0 52.2 10.7 2,897 4+ 72.8 8.6 17.3 1.2 0.1 0.1 100.0 81.4 30.1 2,723 Place of delivery3 Health facility 85.2 13.7 0.6 0.3 0.0 0.2 100.0 99.0 29.2 5,777 Elsewhere 1.5 7.0 79.2 11.5 0.5 0.3 100.0 8.5 0.0 6,183 Residence Urban 64.0 7.0 27.2 1.5 0.0 0.3 100.0 71.0 23.6 3,489 Rural 32.8 11.6 46.9 7.9 0.3 0.4 100.0 44.4 10.2 8,488 Region Punjab 40.9 11.6 45.0 2.0 0.2 0.3 100.0 52.5 16.9 6,859 Urban 60.3 8.2 30.3 0.7 0.0 0.5 100.0 68.5 24.6 2,007 Rural 32.9 13.0 51.1 2.5 0.3 0.2 100.0 45.9 13.8 4,852 Sindh 56.1 4.4 37.3 2.1 0.0 0.0 100.0 60.5 15.4 2,740 Urban 75.8 3.3 20.2 0.7 0.0 0.0 100.0 79.1 26.7 1,070 Rural 43.5 5.1 48.3 3.1 0.0 0.0 100.0 48.6 8.2 1,670 Khyber Pakhtunkhwa 31.6 16.7 23.9 25.5 0.9 1.4 100.0 48.3 4.6 1,654 Urban 57.9 12.3 22.1 7.7 0.0 0.0 100.0 70.2 11.8 267 Rural 26.6 17.5 24.2 29.0 1.1 1.6 100.0 44.1 3.2 1,388 Balochistan 15.8 2.0 70.4 10.8 0.0 1.0 100.0 17.8 1.5 590 Urban 30.0 4.4 61.0 4.3 0.0 0.4 100.0 34.4 2.2 107 Rural 12.7 1.5 72.5 12.3 0.0 1.1 100.0 14.2 1.3 484 ICT Islamabad 84.8 3.3 7.1 3.8 0.0 1.0 100.0 88.1 26.6 47 Gilgit Baltistan 21.4 22.3 9.9 45.8 0.5 0.0 100.0 43.7 3.3 87 Mother’s education No education 27.7 10.0 52.6 8.9 0.4 0.4 100.0 37.7 6.5 6,852 Primary 45.7 11.3 39.7 3.1 0.1 0.1 100.0 57.0 16.0 2,039 Middle 57.9 12.3 27.2 2.4 0.0 0.3 100.0 70.2 20.2 905 Secondary 69.1 11.3 17.0 1.8 0.1 0.9 100.0 80.3 29.4 1,209 Higher 85.3 6.4 6.5 1.0 0.0 0.7 100.0 91.7 38.7 973 Wealth quintile Lowest 23.8 6.0 59.0 10.7 0.4 0.3 100.0 29.8 4.3 2,864 Second 24.9 13.2 51.1 9.7 0.6 0.5 100.0 38.1 6.8 2,535 Middle 36.0 15.1 43.6 4.5 0.2 0.5 100.0 51.2 11.2 2,346 Fourth 57.2 11.7 28.6 2.2 0.1 0.3 100.0 68.9 20.7 2,349 Highest 80.5 4.7 13.4 0.9 0.0 0.5 100.0 85.2 33.9 1,883 Total 41.9 10.2 41.2 6.1 0.2 0.4 100.0 52.1 14.1 11,977 Note: If the respondent mentioned more than one person attending during delivery, only the most qualified person is considered in this tabulation. Total includes 11 cases with missing information on number of antenatal care visits. 1 Skilled provider includes doctor, nurse, midwife, and lady health visitor. 2 Includes only the most recent birth in the five years preceding the survey 3 Excludes 18 cases with missing information on place of delivery In the past six years, there has been an increase of 13 percentage points in births assisted by a skilled provider, from 39 percent in 2006-07 to 52 percent in 2012-13. Table 9.6 shows that 14 percent of births are delivered by caesarean section. Delivery by caesarean section is highest among births to first-time mothers (23 percent), births to women with four or more antenatal visits (30 percent), births delivered in a health facility (29 percent), births to highly educated mothers (39 percent), and births to mothers in the highest wealth quintile (34 percent). 140 • Reproductive Health There are urban-rural differences in deliveries by caesarean section within regions. The difference is highest in Sindh, where 27 percent of births in urban areas and only 8 percent in rural areas are delivered by caesarean section. Figure 9.3 presents the percent distribution of women who gave birth in a health facility in the five years preceding the survey by duration of stay in the facility and type of delivery. Among women who give birth by caesarean section, 78 percent stayed at the hospital for more than three days, as compared with 3 percent of women who had a vaginal birth. The majority (64 percent) of women who had a vaginal birth in a health facility were discharged less than six hours after delivery. Figure 9.3 Mother’s duration of stay in the health facility after giving birth 64 3 14 0 18 18 3 78 Vaginal birth Caesarean birth <6 hours 6-23 hours 1-2 days 3+ days Percentage PDHS 2012-13 9.6 POSTNATAL CARE The postpartum period is particularly important for women, because during this period they may develop serious, life-threatening complications, especially in the interval immediately after delivery. There is evidence that a large proportion of maternal and neonatal deaths occur during the first 48 hours after delivery. Postnatal care visits provide an ideal opportunity to educate a new mother on how to care for herself and her newborn baby. 9.6.1 Timing of First Postnatal Checkup for Mother Table 9.7 shows that in the two years preceding the survey, 60 percent of women received postnatal care for their last birth within the first two days following delivery. One percent of women received postnatal care on the third day or later after delivery. Among women who had postnatal checkups, 54 percent received postnatal care within 4 hours of delivery, 5 percent received care within the first 4-23 hours, and 2 percent received postnatal 1-2 days after delivery. Overall, 38 percent of women had no postnatal checkup. While differences by mother’s age are not pronounced, there are prominent variations in levels of postnatal care by birth order, place of residence, and mother’s education and wealth quintile. Mothers of children of higher birth orders, mothers who did not give birth in a health facility, rural women, women with no education, and women in the lowest wealth quintile are much less likely than other women to have postnatal checkups. Postnatal care also varies widely between urban and rural areas within regions, with the widest gap being observed in Khyber Pakhtunkhwa (64 percent in urban and 33 percent in rural areas). Three in four (76 percent) mothers in Gilgit Baltistan did not receive a postnatal checkup. Reproductive Health • 141 Table 9.7 Timing of first postnatal checkup for the mother Among women age 15-49 giving birth in the two years preceding the survey, the percent distribution of the mother’s first postnatal checkup for the last live birth by time after delivery, and the percentage of women with a live birth in the two years preceding the survey who received a postnatal checkup in the first two days after giving birth, according to background characteristics, Pakistan 2012-13 Time after delivery of mother’s first postnatal checkup No postnatal checkup1 Total Percentage of women with a postnatal checkup in the first two days after birth Number of women Background characteristic Less than 4 hours 4-23 hours 1-2 days 3-6 days 7-41 days Don’t know/ missing Mother’s age at birth <20 53.2 4.0 1.4 1.8 0.0 1.6 38.0 100.0 58.6 350 20-34 54.3 5.2 1.7 0.6 0.5 1.0 36.6 100.0 61.2 3,416 35-49 50.2 2.9 1.9 0.4 0.0 0.1 44.5 100.0 55.0 479 Birth order 1 61.4 6.5 1.9 0.8 0.7 2.0 26.7 100.0 69.8 1,014 2-3 53.3 5.9 2.1 0.6 0.4 1.0 36.7 100.0 61.3 1,611 4-5 50.2 2.3 1.6 0.9 0.5 0.6 44.0 100.0 54.1 913 6+ 48.2 3.3 0.8 0.3 0.3 0.0 47.0 100.0 52.3 707 Place of delivery Health facility 74.3 8.5 1.9 0.6 0.4 1.4 12.9 100.0 84.7 2,295 Elsewhere 29.6 0.6 1.5 0.8 0.5 0.4 66.6 100.0 31.7 1,948 Residence Urban 63.1 8.1 2.7 0.8 1.0 1.0 23.4 100.0 73.9 1,256 Rural 49.8 3.5 1.3 0.6 0.2 1.0 43.6 100.0 54.6 2,990 Region Punjab 58.1 6.2 1.6 0.7 0.3 1.5 31.6 100.0 66.0 2,425 Urban 65.7 9.1 1.8 0.8 0.7 1.4 20.4 100.0 76.6 736 Rural 54.8 4.9 1.5 0.6 0.1 1.5 36.5 100.0 61.3 1,690 Sindh 60.2 4.0 2.0 0.9 0.6 0.0 32.2 100.0 66.3 961 Urban 61.6 8.0 4.4 0.9 1.6 0.0 23.4 100.0 74.0 377 Rural 59.3 1.5 0.4 1.0 0.0 0.0 37.8 100.0 61.3 585 Khyber Pakhtunkhwa 36.3 0.9 0.5 0.4 0.7 0.5 60.7 100.0 37.7 623 Urban 61.4 1.6 1.3 0.3 0.5 1.7 33.2 100.0 64.3 99 Rural 31.6 0.8 0.3 0.4 0.7 0.3 65.9 100.0 32.7 524 Balochistan 28.1 3.4 5.7 0.7 0.0 0.9 61.1 100.0 37.2 187 Urban 32.4 5.0 4.9 0.3 0.3 0.7 56.4 100.0 42.3 32 Rural 27.2 3.0 5.9 0.8 0.0 0.9 62.1 100.0 36.2 156 ICT Islamabad 56.6 17.6 3.8 0.0 0.8 1.4 19.9 100.0 77.9 16 Gilgit Baltistan 15.2 4.2 0.4 1.0 1.9 1.3 75.9 100.0 19.9 33 Education No education 48.0 2.0 1.5 0.6 0.2 1.0 46.6 100.0 51.6 2,304 Primary 53.9 4.6 0.7 0.6 0.5 1.0 38.8 100.0 59.1 741 Middle 58.9 9.3 2.6 0.9 0.7 0.0 27.6 100.0 70.8 346 Secondary 64.2 8.3 2.2 1.1 0.8 1.8 21.7 100.0 74.7 480 Higher 70.3 14.5 3.5 0.6 1.0 0.8 9.3 100.0 88.3 374 Wealth quintile Lowest 39.0 2.1 0.9 1.2 0.0 0.1 56.7 100.0 42.0 934 Second 50.0 2.4 2.1 0.2 0.5 0.8 44.0 100.0 54.5 914 Middle 52.8 3.8 1.1 0.8 0.4 2.2 39.0 100.0 57.6 858 Fourth 64.4 5.9 1.9 0.5 0.7 1.2 25.4 100.0 72.2 873 Highest 66.7 12.0 3.0 0.7 0.7 0.7 16.3 100.0 81.7 667 Total 53.7 4.8 1.7 0.7 0.4 1.0 37.6 100.0 60.3 4,246 Note: Total includes 3 cases with missing information on place of delivery. 1 Includes women who received a checkup after 41 days 9.6.2 Provider of First Postnatal Checkup for Mother Table 9.8 presents information on the type of postnatal care provider by mother’s background characteristics. Among mothers who received postnatal care, 48 percent received care from a skilled health provider and 12 percent from a traditional birth attendant (dai). Differentials in types of providers across subgroups are the same as those for timing of postnatal care. 142 • Reproductive Health Table 9.8 Type of provider of first postnatal checkup for the mother Among women age 15-49 giving birth in the two years preceding the survey, the percent distribution by type of provider of the mother’s first postnatal health check in the two days after the last live birth, according to background characteristics, Pakistan 2012-13 Type of health provider of mother’s first postnatal checkup No postnatal checkup in the first two days after birth Total Number of women Background characteristic Doctor/ nurse/ midwife/LHV Dai/traditional birth attendant Other Mother’s age at birth <20 46.9 11.6 0.0 41.4 100.0 350 20-34 49.3 11.7 0.3 38.8 100.0 3,416 35-49 38.1 16.6 0.3 45.0 100.0 479 Birth order 1 62.2 7.2 0.4 30.2 100.0 1,014 2-3 50.6 10.6 0.2 38.7 100.0 1,611 4-5 38.8 15.1 0.2 45.9 100.0 913 6+ 32.5 19.4 0.4 47.7 100.0 707 Place of delivery Health facility 84.0 0.4 0.3 15.3 100.0 2,295 Elsewhere 5.3 26.2 0.2 68.3 100.0 1,948 Residence Urban 64.5 9.0 0.3 26.1 100.0 1,256 Rural 40.8 13.6 0.3 45.4 100.0 2,990 Region Punjab 50.5 15.0 0.4 34.0 100.0 2,425 Urban 63.5 12.7 0.5 23.4 100.0 736 Rural 44.9 16.0 0.4 38.7 100.0 1,690 Sindh 56.5 9.6 0.1 33.7 100.0 961 Urban 70.6 3.5 0.0 26.0 100.0 377 Rural 47.4 13.6 0.2 38.7 100.0 585 Khyber Pakhtunkhwa 35.3 2.4 0.0 62.3 100.0 623 Urban 62.0 2.4 0.0 35.7 100.0 99 Rural 30.3 2.4 0.0 67.3 100.0 524 Balochistan 12.5 24.7 0.0 62.8 100.0 187 Urban 28.2 14.1 0.0 57.7 100.0 32 Rural 9.3 26.9 0.0 63.8 100.0 156 ICT Islamabad 75.9 1.5 0.5 22.1 100.0 16 Gilgit Baltistan 19.2 0.7 0.1 80.1 100.0 33 Education No education 34.2 17.2 0.2 48.4 100.0 2,304 Primary 48.8 9.8 0.5 40.9 100.0 741 Middle 61.9 8.4 0.5 29.2 100.0 346 Secondary 71.0 3.3 0.4 25.3 100.0 480 Higher 86.8 1.5 0.0 11.7 100.0 374 Wealth quintile Lowest 26.1 15.9 0.0 58.0 100.0 934 Second 37.7 16.5 0.4 45.5 100.0 914 Middle 43.6 13.8 0.3 42.4 100.0 858 Fourth 61.9 9.8 0.6 27.8 100.0 873 Highest 79.2 2.5 0.0 18.3 100.0 667 Total 47.8 12.2 0.3 39.7 100.0 4,246 Note: Total includes 3 cases with missing information on place of delivery. LHV = Lady health visitor 9.7 NEWBORN CARE Newborn care is essential to reduce neonatal problems and death. To identify, manage, and prevent complications, it is recommended that the mother and the newborn have at least three checkups within seven days after delivery (WHO and UNICEF, 2009), which is considered a critical period for neonates and mothers. Table 9.9 shows the percent distribution of last births in the two years preceding the survey by timing of the first postnatal checkup after birth, along with the percentage of newborns with a postnatal checkup in the first two days after birth, according to background characteristics. Reproductive Health • 143 Overall, 43 percent of newborns received their first postnatal checkup within two days after birth. Among these newborns, one in four had a postnatal checkup less than one hour after birth, and 14 percent had a checkup between one and three hours after birth. In all, 41 percent of newborns had a postnatal checkup within 24 hours after birth. Fifty-four percent of newborns did not receive a postnatal checkup. Newborns delivered outside of a health facility were less likely to receive a postnatal checkup within the first week after birth (29 percent) than newborns delivered in a health facility (60 percent). Similarly, postnatal checkups were less likely among births to mothers age 35-49, births of order six and over, births to rural women, and births in Gilgit Baltistan than among births in the other categories. The highest urban-rural difference in percent of newborns having a checkup within two days after birth was found in Khyber Pakhtunkhwa (47 percent and 18 percent in urban and rural areas, respectively). The highest urban-rural differences in no postnatal checkups of the newborns are also in Khyber Pakhtunkhwa (49 percent and 77 percent in urban and rural areas, respectively). Table 9.9 Timing of first postnatal checkup for the newborn Percent distribution of last births in the two years preceding the survey by time after birth of first postnatal checkup, and the percentage of births with a postnatal checkup in the first two days after birth, according to background characteristics, Pakistan 2012-13 Time after birth of newborn’s first postnatal checkup No postnatal checkup1 Total Percentage of births with a postnatal checkup in the first two days after birth Number of births Background characteristic Less than 1 hour 1-3 hours 4-23 hours 1-2 days 3-6 days Don’t know/ missing Mother’s age at birth <20 24.4 7.6 1.9 1.7 2.9 1.9 59.5 100.0 35.6 350 20-34 24.6 15.4 1.5 2.1 2.9 0.6 52.8 100.0 43.7 3,416 35-49 25.7 12.5 0.4 3.5 1.9 0.1 56.0 100.0 42.1 479 Birth order 1 28.1 14.2 1.7 2.5 4.1 0.8 48.7 100.0 46.4 1,014 2-3 23.8 15.6 2.0 2.0 2.4 1.0 53.1 100.0 43.4 1,611 4-5 24.0 14.3 0.6 2.1 2.3 0.2 56.5 100.0 41.0 913 6+ 23.2 12.2 0.7 2.7 2.6 0.0 58.6 100.0 38.8 707 Place of delivery Health facility 32.8 20.8 2.1 2.1 1.7 1.0 39.5 100.0 57.9 2,295 Elsewhere 15.2 7.0 0.6 2.4 4.1 0.2 70.4 100.0 25.2 1,948 Residence Urban 31.3 17.0 2.1 2.0 2.6 0.5 44.5 100.0 52.4 1,256 Rural 22.0 13.3 1.1 2.4 2.9 0.7 57.6 100.0 38.8 2,990 Region Punjab 34.2 14.0 1.5 1.6 2.3 1.1 45.3 100.0 51.3 2,425 Urban 38.4 14.0 2.0 1.0 2.6 0.8 41.3 100.0 55.3 736 Rural 32.4 14.0 1.3 1.9 2.1 1.2 47.0 100.0 49.6 1,690 Sindh 15.4 20.9 1.4 3.4 3.5 0.0 55.4 100.0 41.1 961 Urban 21.9 23.5 2.5 3.8 2.5 0.1 45.7 100.0 51.7 377 Rural 11.3 19.3 0.7 3.1 4.1 0.0 61.6 100.0 34.3 585 Khyber Pakhtunkhwa 11.1 8.5 0.8 2.1 4.7 0.0 72.9 100.0 22.4 623 Urban 26.7 16.5 1.5 1.8 3.8 0.3 49.4 100.0 46.5 99 Rural 8.2 7.0 0.6 2.1 4.8 0.0 77.3 100.0 17.9 524 Balochistan 0.5 6.6 1.8 5.9 0.5 0.0 84.7 100.0 14.8 187 Urban 2.4 10.4 0.8 3.0 0.5 0.0 82.9 100.0 16.6 32 Rural 0.1 5.9 2.0 6.5 0.5 0.0 85.1 100.0 14.4 156 ICT Islamabad 14.2 34.0 3.7 3.1 3.6 0.4 41.0 100.0 55.1 16 Gilgit Baltistan 0.4 1.0 1.0 1.1 2.1 0.8 93.5 100.0 3.5 33 Mother’s education No education 20.7 11.3 0.6 1.8 2.8 0.7 62.0 100.0 34.5 2,304 Primary 27.1 15.7 1.3 3.1 4.3 0.5 48.0 100.0 47.2 741 Middle 27.8 17.1 2.6 1.6 3.3 0.0 47.6 100.0 49.2 346 Secondary 27.6 19.4 3.3 2.6 1.2 1.5 44.4 100.0 52.9 480 Higher 38.5 22.3 2.7 3.3 1.6 0.1 31.5 100.0 66.7 374 Wealth quintile Lowest 12.4 10.6 0.7 3.1 3.3 0.0 70.0 100.0 26.7 934 Second 25.5 10.5 0.9 2.2 3.7 0.6 56.5 100.0 39.1 914 Middle 25.6 13.8 1.0 1.4 2.0 1.4 54.8 100.0 41.8 858 Fourth 29.6 18.8 1.6 2.4 2.2 0.7 44.6 100.0 52.5 873 Highest 33.6 20.3 3.3 2.1 2.7 0.6 37.5 100.0 59.2 667 Total 24.7 14.4 1.4 2.3 2.8 0.6 53.7 100.0 42.8 4,246 Note: Total includes 3 cases with missing information on place of delivery. 1 Includes newborns who received a checkup after the first week 144 • Reproductive Health 9.7.1 Provider of First Postnatal Checkup for Newborn Table 9.10 presents the percent distribution of the most recent births occurring in the two years preceding the survey by type of provider of newborn care during the first two days after delivery, according to background characteristics. Table 9.10 Type of provider of first postnatal checkup for the newborn Percent distribution of last births in the two years preceding the survey by type of provider of the newborn’s first postnatal health check during the two days after the last live birth, according to background characteristics, Pakistan 2012-13 Type of health provider of newborn’s first postnatal checkup No postnatal checkup in the first two days after birth1 Total Number of births Background characteristic Doctor/ nurse/ midwife Auxiliary nurse/midwife Other Mother’s age at birth <20 28.1 7.4 0.0 64.4 100.0 350 20-34 35.5 8.0 0.2 56.3 100.0 3,416 35-49 30.3 11.5 0.3 57.9 100.0 479 Birth order 1 42.9 3.3 0.2 53.6 100.0 1,014 2-3 36.3 7.1 0.0 56.6 100.0 1,611 4-5 28.1 12.5 0.4 59.0 100.0 913 6+ 25.4 12.9 0.5 61.2 100.0 707 Place of delivery Health facility 57.6 0.0 0.2 42.1 100.0 2,295 Elsewhere 6.8 18.1 0.3 74.8 100.0 1,948 Residence Urban 45.8 6.4 0.1 47.6 100.0 1,256 Rural 29.4 9.1 0.3 61.2 100.0 2,990 Region Punjab 39.4 11.7 0.2 48.7 100.0 2,425 Urban 46.1 9.0 0.2 44.7 100.0 736 Rural 36.5 12.9 0.2 50.4 100.0 1,690 Sindh 36.7 4.3 0.1 58.9 100.0 961 Urban 49.0 2.7 0.0 48.3 100.0 377 Rural 28.7 5.4 0.2 65.7 100.0 585 Khyber Pakhtunkhwa 21.0 1.2 0.2 77.6 100.0 623 Urban 45.0 1.6 0.0 53.5 100.0 99 Rural 16.5 1.2 0.3 82.1 100.0 524 Balochistan 3.8 10.4 0.6 85.2 100.0 187 Urban 10.1 6.1 0.4 83.4 100.0 32 Rural 2.5 11.3 0.6 85.6 100.0 156 ICT Islamabad 53.8 1.2 0.0 44.9 100.0 16 Gilgit Baltistan 2.9 0.0 0.6 96.5 100.0 33 Mother’s education No education 23.3 10.9 0.2 65.5 100.0 2,304 Primary 38.4 8.7 0.2 52.8 100.0 741 Middle 41.3 7.4 0.5 50.8 100.0 346 Secondary 50.7 2.2 0.0 47.1 100.0 480 Higher 66.0 0.5 0.3 33.3 100.0 374 Wealth quintile Lowest 17.3 9.2 0.1 73.3 100.0 934 Second 26.4 12.2 0.4 60.9 100.0 914 Middle 32.5 9.3 0.0 58.2 100.0 858 Fourth 44.8 7.2 0.5 47.5 100.0 873 Highest 57.2 2.0 0.0 40.8 100.0 667 Total 34.3 8.3 0.2 57.2 100.0 4,246 Note: Total includes 3 cases with missing information on place of delivery. 1 Includes newborns who received a checkup after the first week Reproductive Health • 145 The findings show that 34 percent of newborns received postnatal care in the two days following birth from a doctor, nurse, or midwife. An additional 8 percent of newborns received care from an auxiliary nurse or midwife. The distribution of newborns who received care from a skilled birth attendant by background characteristics is more or less similar to the pattern described for providers of mothers’ postnatal checkups. Urban-rural differences in types of health providers for postnatal checkups are highest in Khyber Pakhtunkhwa, where newborn babies of urban women are more likely to have checkups from a skilled health provider (45 percent and 17 percent in urban and rural areas, respectively). 9.8 PROBLEMS IN ACCESSING HEALTH CARE In the 2012-13 PDHS, women were asked whether or not each of the following factors would be a serious problem for them in seeking medical care: getting permission to go for treatment, getting money for advice or treatment, distance to a health facility, not wanting to go alone, and management of transportation. The majority of women (63 percent) reported that at least one of these problems would pose a barrier in seeking health care for themselves when they are sick (Table 9.11). More than half (53 percent) of women stated that not wanting to go alone is a problem, while 40 percent cited managing transportation. Thirty-seven percent mentioned distance from a health facility as a problem, while 30 percent cited getting money for advice or treatment. Only 18 percent of women mentioned getting permission to go as a problem. Problems in accessing health care decrease with increasing age, education, and wealth. Women who are employed not for cash are more likely to have problems in accessing health care than women who are not employed and women who are employed for cash (63 percent each). Urban women are much less likely than rural women to mention problems in accessing health care. There are urban-rural differentials in access to health care in all regions. The most pronounced urban-rural differential is in Sindh (46 percent in urban areas and 86 percent in rural areas). 146 • Reproductive Health Table 9.11 Problems in accessing health care Percentage of women age 15-49 who reported that they have serious problems in accessing health care for themselves when they are sick, by type of problem, according to background characteristics, Pakistan 2012-13 Problems in accessing health care Background characteristic Getting permission to go for treatment Getting money for advice or treatment Distance to health facility Not wanting to go alone Management of transport At least one problem accessing health care Number of women Age 15-19 23.9 36.0 52.6 78.0 55.4 83.3 605 20-34 20.2 29.9 38.1 59.7 42.0 67.8 7,359 35-49 13.8 28.8 34.0 41.7 36.6 55.0 5,594 Number of living children 0 21.4 28.0 39.7 66.3 43.2 72.2 1,828 1-2 17.0 26.5 35.3 57.1 37.6 64.6 4,059 3-4 15.7 28.6 35.5 48.0 39.1 59.8 3,912 5+ 18.8 35.1 39.4 47.7 43.1 61.0 3,760 Marital status Married or living together 18.0 29.4 37.5 53.9 40.6 63.6 12,937 Divorced/separated/widowed 12.4 35.6 28.4 37.9 35.0 55.3 621 Employed in last 12 months Not employed 18.0 28.4 36.0 54.0 38.9 62.8 9,606 Employed for cash 16.0 32.9 38.0 49.2 42.9 62.9 3,077 Employed not for cash 20.6 33.5 45.4 56.9 47.7 69.0 873 Residence Urban 10.5 17.1 17.0 37.1 21.0 45.3 4,536 Rural 21.4 36.1 47.1 61.2 50.0 72.3 9,022 Region Punjab 10.3 19.5 25.7 45.1 28.1 55.3 7,790 Urban 9.5 13.8 12.9 34.3 16.2 42.0 2,526 Rural 10.7 22.2 31.8 50.3 33.8 61.7 5,264 Sindh 19.1 32.4 43.5 56.2 51.0 66.5 3,133 Urban 7.7 15.8 18.0 37.4 24.4 45.6 1,521 Rural 29.7 48.0 67.7 73.9 76.1 86.2 1,612 Khyber Pakhtunkhwa 34.2 57.0 63.0 75.1 62.8 85.2 1,908 Urban 19.7 37.7 32.4 52.4 31.1 63.7 320 Rural 37.2 60.9 69.2 79.7 69.1 89.6 1,588 Balochistan 57.1 62.4 69.7 73.1 72.6 81.3 568 Urban 44.4 47.8 52.6 57.4 53.7 67.4 114 Rural 60.3 66.1 74.0 77.1 77.3 84.8 454 ICT Islamabad 6.5 11.3 13.6 25.4 15.9 32.8 64 Gilgit Baltistan 20.2 50.4 57.5 66.2 69.2 76.2 94 Education No education 23.1 39.7 46.5 58.7 50.6 70.7 7,736 Primary 14.3 23.9 32.6 50.8 35.8 61.5 2,156 Middle 11.0 18.8 26.3 50.7 29.8 57.2 993 Secondary 9.4 12.2 21.3 44.4 22.4 50.9 1,413 Higher 5.3 6.5 12.6 34.4 13.8 38.9 1,260 Wealth quintile Lowest 31.9 54.3 65.1 75.5 71.6 87.0 2,589 Second 22.1 41.2 47.9 60.2 52.6 74.4 2,676 Middle 15.7 26.5 35.1 52.0 37.1 62.4 2,700 Fourth 13.1 19.8 25.6 44.9 28.2 54.9 2,789 Highest 7.0 9.2 14.1 35.0 15.0 39.7 2,804 Total 17.7 29.7 37.1 53.1 40.3 63.2 13,558 Note: Total includes 2 cases with missing information on status of employment in the last 12 months. Child Health • 147 CHILD HEALTH 10 ealth is one of the foremost underlying factors that define the welfare of a country’s population, and children, as the building blocks of society, represent the very essence of the health situation prevalent in a country. The overall maternal, neonatal, and child health and family planning effort in Pakistan is well directed and has been a priority in all policies, with resource allocations, unacceptably low in the past, substantially increasing during the last decade (Siddiqi et al., 2004). Pakistan is a signatory to the International Charter for the Achievement of the Millennium Development Goals (MDGs), and it continuously strives for achievement of the MDGs and significant improvements in its performance in areas such as health and nutrition (Government of Punjab, 2013). The past few years have seen landmark constitutional developments establishing a new framework of devolution of power from the federal level to the provinces and enhancing the prospects of better service delivery and greater scope for public participation (Planning Commission and UNICEF, 2012). However, health status indicators in Pakistan remain poorer than in most low-income countries. Although the overall health status of Pakistan’s population has improved over the past few decades, the rate of improvement remains inadequate, largely as a result of poverty, low literacy levels, and lack of civic facilities such as proper sanitation. One characteristic that distinguishes populations in less developed countries from those of industrialized ones is infant mortality. Taking a comprehensive look at the underlying causes of child mortality, it can safely be established that, outside the critical period of childbirth, a large proportion of child deaths are related to infectious diseases. The World Health Organization (WHO) estimates that children under age 15 account for 36 percent of the total number of years of healthy life lost globally, while children under age 5 accounts for 90 percent. A large proportion (60 percent) of these deaths are related to communicable and vaccine-preventable diseases (Bhutta et al., 2004). H Key Findings • There has been a slow improvement in the percentage of fully immunized children age 12-23 months, from 47 percent in 2006-07 to 54 percent in 2012-13. • Only one-third of children age 12-23 months have a vaccination card. • Sixteen percent of children under age 5 showed symptoms of acute respiratory infection in the two weeks before the survey; 64 percent of these children were taken to a health facility or care provider for advice or treatment, and 42 percent received antibiotics. • About 38 percent of children under age 5 had a fever in the two weeks before the survey, and 65 percent of them were taken to a health facility or care provider for advice or treatment. • Twenty-three percent of children under age 5 had diarrhea in the two weeks before the survey. • The proportion of children with diarrhea taken to a health care provider for advice or treatment has increased over time, from 48 percent in 1990- 91 to 61 percent in 2012-13. • The use of ORS among children with diarrhea is not popular; only 38 percent of children who had diarrhea in the two weeks preceding the survey received ORS. 148 • Child Health In order to elaborately evaluate such data, the 2012-13 PDHS synthesized health statistics among children under age 5 through information gathered from mothers on their children’s birth weight, immunization status, and prevalence and treatment of common childhood illnesses such as diarrhea, acute respiratory infection (ARI), and fever. Birth weight data were compiled for all live births in the five years preceding the survey. Analysis of these data will help policymakers in planning appropriate strategies to improve child health. 10.1 CHILD’S WEIGHT AND SIZE AT BIRTH Information on birth weight or size at birth is important for the design and implementation of public health programs aimed at reducing neonatal and infant mortality. A child’s birth weight or size not only indicates the child’s vulnerability to the risk of childhood illnesses but also defines the child’s chances of survival. The 2012-13 PDHS questionnaire recorded birth weight, available from written records or mother’s recall, for births in the five years preceding the survey. Since birth weight may not be known for many babies, the mother’s estimate of the baby’s size at birth was also obtained; responses were categorized as “very small,” “smaller than average,” “average,” “larger than average,” and “very large.” Children whose birth weight is less than 2.5 kilograms and children reported to be very small or smaller than average are considered to have a higher than average risk of early childhood death. Mother’s estimates, even though subjective, can be a useful proxy for the weight of the child. This is particularly true in societies such as Pakistan, where babies are often delivered at home and not weighed at birth. In 2006-07, only 1 in 10 infants had a birth weight recorded, and 26 percent of these infants were reported to have a low birth weight (National Institute of Population Studies and Macro International Inc., 2008). Table 10.1 presents information on children’s weight and size at birth according to background characteristics. Only 12 percent of children born in the past five years were weighed at birth. This is not surprising given that the majority of births do not take place in a health facility and children are less likely to be weighed at birth in a non-institutional setting. Among children born in the five years before the survey with a reported birth weight, one-fourth were of low birth weight (less than 2.5 kg). There is visible variation in the percentage of children of low birth weight by background characteristics. Table 10.1 shows that children of young mothers are more likely to be of low birth weight (29 percent) than children of older mothers (22 percent). Birth order does not exhibit linear variations; children of birth order four or five are more likely to have a low birth weight (31 percent) than children of other birth orders. Birth weight varies by place of residence. The percentage of low birth weight children in rural areas is 33 percent, as compared with 21 percent in urban areas. In case of region, no set pattern is observed with respect to low birth weights. Gilgit Baltistan has the highest incidence of low birth weight (30 percent), followed by Khyber Pakhtunkhwa and Punjab (27 percent each). Children of mothers with no education are most likely to be of low birth weight (40 percent) and children of mothers with a higher education are least likely (16 percent). Similarly, the incidence of low birth weight decreases with increasing wealth, from 67 percent in the lowest wealth quintile to 19 percent in the highest wealth quintile. In the absence of birth weight, a mother’s subjective assessment of the size of her baby at birth may be a useful proxy. Only 4 percent of children were reported to be very small at birth, and 16 percent were reported to be smaller than average. On the other hand, 80 percent of children were reported to be average or larger in size. There were some interesting variations by background characteristics, especially among babies categorized as “very small.” For example, babies of older mothers (age 35-49) were more likely to be reported as very small at birth than babies of mothers age 20-34. Children of birth order six or above were more likely (5 percent) than those of first-order parity (3 percent) to be reported as very small at birth. There were wide variations according to mother’s smoking status; mothers who smoke were more likely to report having very small babies (8 percent) than nonsmokers (4 percent). There was some regional variation, with Punjab and Sindh having the lowest percentage (3 percent each) of very small births and Balochistan (8 percent) and Khyber Pakhtunkhwa (7 percent) having the highest percentages. Children of Child Health • 149 mothers with no education and those from households in the lowest wealth quintile were more likely to be reported as very small than their counterparts in other categories. Table 10.1 Child’s size and weight at birth Percent distribution of live births in the five years preceding the survey by mother’s estimate of baby’s size at birth, percentage of live births in the five years preceding the survey that have a reported birth weight, and among live births in the five years preceding the survey with a reported birth weight, percentage less than 2.5 kg, according to background characteristics, Pakistan 2012-13 Percent distribution of all live births by size of child at birth Percentage of all births that have a reported birth weight1 Number of births Births with a reported birth weight1 Background characteristic Very small Smaller than average Average or larger Don’t know/ missing Total Percentage less than 2.5 kg Number of births Mother’s age at birth <20 4.7 19.6 75.0 0.6 100.0 8.4 1,086 28.8 91 20-34 3.3 15.3 81.0 0.4 100.0 12.9 9,614 25.0 1,236 35-49 5.7 14.8 79.0 0.4 100.0 10.3 1,277 22.2 132 Birth order 1 3.0 16.3 80.2 0.5 100.0 18.1 2,783 24.1 504 2-3 3.3 15.7 80.4 0.6 100.0 14.0 4,374 23.8 614 4-5 3.9 16.0 79.7 0.4 100.0 8.4 2,564 31.0 216 6+ 4.8 14.4 80.7 0.1 100.0 5.6 2,256 24.4 125 Mother’s smoking status Smokes cigarettes/tobacco 8.4 26.9 63.4 1.3 100.0 3.3 118 * 4 Does not smoke 3.6 15.5 80.5 0.4 100.0 12.3 11,840 24.9 1,450 Residence Urban 2.9 11.5 85.0 0.6 100.0 27.8 3,489 21.0 970 Rural 4.0 17.4 78.3 0.4 100.0 5.8 8,488 33.0 488 Region Punjab 2.7 15.7 81.1 0.4 100.0 11.6 6,859 26.6 797 Sindh 2.7 16.6 80.6 0.0 100.0 19.1 2,740 21.7 524 Khyber Pakhtunkhwa 7.3 13.5 78.2 0.9 100.0 5.0 1,654 27.2 82 Balochistan 7.8 16.2 75.0 1.0 100.0 1.2 590 (44.4) 7 ICT Islamabad 6.6 10.0 82.7 0.7 100.0 60.5 47 25.0 28 Gilgit Baltistan 5.3 19.7 74.8 0.1 100.0 22.9 87 29.8 20 Mother’s education No education 4.1 17.9 77.7 0.3 100.0 3.4 6,852 40.2 235 Primary 3.6 13.6 82.4 0.4 100.0 7.9 2,039 31.5 162 Middle 3.5 14.0 81.5 1.0 100.0 21.2 905 35.6 191 Secondary 3.0 10.6 86.1 0.3 100.0 30.4 1,209 19.5 367 Higher 1.7 12.0 85.1 1.2 100.0 51.7 973 15.8 503 Wealth quintile Lowest 4.4 20.2 75.2 0.2 100.0 1.9 2,864 67.1 55 Second 4.0 18.7 76.8 0.5 100.0 3.3 2,535 42.7 84 Middle 4.2 13.8 81.8 0.2 100.0 5.4 2,346 40.0 127 Fourth 2.9 12.0 84.5 0.6 100.0 15.0 2,349 22.8 353 Highest 2.3 11.5 85.5 0.7 100.0 44.5 1,883 19.1 839 Total 3.6 15.7 80.3 0.4 100.0 12.2 11,977 25.0 1,458 Note: Total includes 4 cases with missing information on mother’s smoking status. 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 Based on either a written record or the mother’s recall 10.2 VACCINATION COVERAGE Universal immunization of children under age 1 against major vaccine-preventable diseases (tuberculosis, diphtheria, pertussis, tetanus, hepatitis B, Haemophilus influenzae type B [Hib], poliomyelitis, and measles) is one of the most cost-effective means of reducing infant and child morbidity and mortality. Following the guidelines of the World Health Organization (Hasan et al., 2010), the government of Pakistan initiated a national immunization program, the Expanded Program on Immunization (EPI), three decades ago. The EPI program was launched with all six recommended antigens (BCG; diphtheria, pertussis, and tetanus [DPT]; oral polio vaccine [OPV]; and measles). In 2003, the monovalent hepatitis B (HepB) vaccine was introduced, which was later administered as a single tetravalent (DPT-HepB) injection. In 2009, a vaccination against Hib was included to form pentavalent (DPT-HEpB-Hib) and launched in different phases in the country. 150 • Child Health According to the WHO immunization guidelines, children are considered fully immunized when they have received one dose of the vaccine against tuberculosis (BCG); three doses of the vaccine against diphtheria, pertussis, and tetanus (DPT); three doses of polio vaccine (excluding polio vaccine given at birth); and one dose of measles vaccine. All children should receive the suggested number of doses of BCG, DPT, OPV, and measles vaccines during their first year of life. BCG is given at birth or at first clinical contact; DPT and polio require three doses at approximately age 6, 10, and 14 weeks; and measles vaccine is given soon after age 9 months. All of the vaccines in the routine immunization schedule are provided free of cost in all public health facilities in Pakistan. Data on differences in immunization coverage among subgroups of the population are useful for program planning and targeting resources to areas most in need. Additionally, information on immunization coverage is important for the monitoring and evaluation of the EPI program. The 2012-13 PDHS collected information on immunization coverage for all living children born in the five years preceding the survey. In the 2012-13 PDHS, as in previous PDHS surveys, information on immunization coverage was collected in two ways: from immunization cards shown to the interviewer and from mothers’ verbal reports. If the immunization card was available, the interviewer copied the immunization dates directly onto the questionnaire. When there was no immunization card, or if a vaccine had not been recorded on the card as being administered, the respondent was asked to recall the specific vaccines given to her child. Information on vaccination coverage among children age 12-23 months is shown in Table 10.2 by source of information (i.e., vaccination record or mother’s report). This is the youngest cohort of children who have reached the age by which they should be fully immunized. The table shows the proportion of children age 12-23 months who were immunized at any age up to the time of the survey as well as the proportion who were vaccinated by age 12 months, the age at which vaccination coverage should be complete. Table 10.2 Vaccinations by source of information Percentage of children age 12-23 months who received specific vaccines at any time before the survey, by source of information (vaccination card or mother’s report), and percentage vaccinated by 12 months of age, Pakistan 2012-13 Source of information BCG DPT1 Polio2 Measles All basic vaccina- tions3 No vaccina- tions Number of children 1 2 3 0 1 2 3 Vaccinated at any time before survey Vaccination card 35.9 35.1 33.8 32.2 34.3 35.3 34.0 32.8 28.7 28.1 0.0 748 Mother’s report 49.3 43.7 39.0 33.0 35.2 57.0 55.2 52.5 32.7 25.7 5.4 1,327 Either source 85.2 78.8 72.7 65.2 69.4 92.3 89.2 85.3 61.4 53.8 5.4 2,074 Vaccinated by 12 months of age4 83.2 76.8 70.5 62.5 67.8 90.2 86.4 82.1 49.7 43.0 7.3 2,074 1 DPT vaccinations include DPT/HepB (tetravalent) as well as DPT/HepB/Hib (pentavalent). 2 Polio 0 is the polio vaccination given at birth. 3 BCG, measles, and 3 doses each of DPT and polio vaccine (excluding polio vaccine given at birth) 4 For children whose information is based on the mother’s report, the proportion of vaccinations given during the first year of life is assumed to be the same as for children with a written record of vaccination. Overall, 54 percent of children age 12-23 months had been fully immunized by the time of the survey. With regard to specific vaccines, 85 percent of children had received the BCG immunization and 61 percent had been immunized against measles. Coverage of the first dose of the DPT and polio vaccines was relatively high (79 percent and 92 percent, respectively); however, only 65 percent and 85 percent of these children went on to receive the third dose of DPT and polio, respectively. Thus, there was a large dropout of 14 percent and 7 percent, respectively, between the first and third dose of the DPT and polio vaccines. Five percent of children did not receive any vaccine at all. 10.3 VACCINATION BY BACKGROUND CHARACTERISTICS Table 10.3 presents data on vaccination coverage of children age 12-23 months by background characteristics. Boys are more likely than girls to be fully immunized (56 percent versus 52 percent). Birth Child Health • 151 order varies inversely with immunization coverage; as birth order increases, immunization coverage generally decreases. Sixty-four percent of first-born children have been fully immunized, in contrast to 39 percent of children of birth order six and above. Table 10.3 Vaccinations by background characteristics Percentage of children age 12-23 months who received specific vaccines at any time before the survey (according to a vaccination card or the mother’s report) and percentage with a vaccination card, by background characteristics, Pakistan 2012-13 Background characteristic BCG DPT1 Polio2 Measles All basic vaccina- tions3 No vaccina- tions Percentage with a vaccination card seen Number of children 1 2 3 0 1 2 3 Sex Male 86.3 79.5 74.8 67.2 69.9 93.0 89.3 86.1 63.0 56.0 4.9 36.6 1,050 Female 84.0 78.0 70.6 63.1 69.0 91.7 89.0 84.5 59.7 51.5 5.9 35.5 1,024 Birth order 1 90.4 84.4 79.8 73.0 73.9 93.5 90.8 87.9 70.6 63.5 3.4 40.6 566 2-3 84.3 79.0 72.8 65.8 71.0 91.6 89.9 85.5 60.7 53.7 5.8 38.4 736 4-5 85.8 80.5 73.0 66.0 67.4 91.1 87.7 83.7 60.6 53.3 6.6 36.0 417 6+ 77.9 67.3 61.0 50.3 61.5 93.2 86.7 82.5 49.1 39.3 6.3 23.8 356 Residence Urban 93.0 87.9 85.8 79.0 84.9 93.9 91.1 86.8 74.3 65.8 2.6 45.7 640 Rural 81.7 74.7 66.9 59.0 62.5 91.6 88.3 84.6 55.6 48.4 6.7 31.7 1,434 Region Punjab 91.6 87.2 81.0 76.3 72.0 97.4 95.2 92.4 70.0 65.6 1.5 40.7 1,215 Urban 94.4 90.5 88.9 86.5 86.4 95.3 94.7 91.0 78.1 74.4 1.6 46.6 390 Rural 90.3 85.6 77.2 71.4 65.2 98.3 95.5 93.1 66.2 61.5 1.4 37.9 825 Sindh 78.5 65.1 56.8 38.6 68.9 87.2 82.2 77.5 44.6 29.1 8.5 25.9 437 Urban 92.8 86.3 83.5 66.5 83.9 92.5 85.4 80.1 71.1 51.5 2.8 46.9 178 Rural 68.6 50.5 38.5 19.5 58.6 83.6 80.0 75.8 26.4 13.7 12.4 11.5 260 Khyber Pakhtunkhwa 79.7 77.1 73.9 69.6 70.8 83.6 79.5 75.7 57.8 52.7 12.0 39.7 309 Urban 89.3 82.4 79.3 74.4 82.6 91.2 88.4 84.2 63.1 58.0 4.7 41.2 50 Rural 77.8 76.0 72.9 68.6 68.5 82.2 77.8 74.0 56.8 51.7 13.4 39.4 259 Balochistan 48.9 37.7 33.7 27.1 34.8 78.1 74.9 60.6 37.3 16.4 20.8 8.0 88 Urban 72.2 58.6 56.2 46.2 67.4 81.6 79.3 68.9 49.1 35.9 16.7 22.3 15 Rural 44.1 33.4 29.1 23.2 28.0 77.4 74.0 58.9 34.9 12.3 21.6 5.1 73 ICT Islamabad 96.5 95.1 93.2 91.2 90.9 97.0 89.4 85.6 85.2 73.9 2.7 52.6 9 Gilgit Baltistan 78.6 62.4 62.2 55.3 40.7 89.6 85.2 75.2 51.0 47.0 9.4 29.2 16 Mother’s education No education 78.4 68.3 59.7 50.9 60.8 90.6 86.2 82.0 47.2 39.8 7.2 27.9 1,118 Primary 89.2 86.0 80.0 74.4 74.6 91.7 89.3 85.4 70.0 62.0 5.6 40.1 361 Middle 94.9 91.1 91.1 86.9 78.9 98.2 97.4 93.7 81.2 76.4 0.2 48.0 156 Secondary 94.5 92.7 90.3 84.8 79.9 93.1 92.8 92.0 79.9 73.6 4.0 48.9 249 Higher 97.2 98.1 97.5 88.1 88.7 97.6 95.0 88.7 87.6 75.6 0.5 49.4 190 Wealth quintile Lowest 70.6 52.0 40.9 29.9 51.4 85.9 82.0 76.7 35.1 23.4 12.4 18.5 456 Second 84.3 80.4 73.5 67.1 63.4 92.6 87.6 84.6 60.6 53.9 5.1 27.4 444 Middle 86.7 83.1 77.2 69.2 69.9 94.4 91.6 87.1 62.5 57.4 4.4 41.4 400 Fourth 90.4 87.8 85.0 78.8 77.8 94.6 93.2 89.8 72.1 65.4 2.5 46.3 437 Highest 97.3 95.9 93.7 88.0 90.3 95.1 92.9 89.7 82.8 75.4 1.5 51.5 338 Total 85.2 78.8 72.7 65.2 69.4 92.3 89.2 85.3 61.4 53.8 5.4 36.0 2,074 1 DPT vaccinations include DPT/HepB (tetravalent) as well as DPT/HepB/Hib (pentavalent). 2 Polio 0 is the polio vaccination given at birth. 3 BCG, measles, and 3 doses each of DPT and polio vaccine (excluding polio vaccine given at birth) Urban-rural differences in immunization coverage are quite visible. Children residing in urban areas are more likely to be fully immunized (66 percent) than children in rural areas (48 percent). There are wide differences in coverage by region. ICT Islamabad has the highest percentage of children who are fully immunized (74 percent), followed by Punjab (66 percent) and Khyber Pakhtunkhwa (53 percent); immunization coverage is lowest in Sindh (29 percent) and Balochistan (16 percent). This clearly indicates the need for provincial health departments to revisit their programs. There are marked differences in immunization coverage between children of women with no education (40 percent) and children of women at the middle, secondary, and higher educational levels (74 percent and above). Children from households in the highest wealth quintile (75 percent) are much more likely to be fully immunized than those from households in the lowest quintile (23 percent). 152 • Child Health Table 10.3 also shows that an immunization card was seen for 36 percent of children age 12-23 months. Cards were most likely to be seen for children of birth order one (41 percent), children living in urban areas (46 percent), children living in ICT Islamabad (53 percent), children of mothers with a secondary or higher education (49 percent each), and children of mothers in the highest wealth quintile (52 percent). 10.4 TRENDS IN IMMUNIZATION COVERAGE Trends in vaccination coverage over the past 22 years can be seen by comparing data from the 1990-91, 2006-07, and 2012-13 PDHS surveys (Figure 10.1 and Table 10.4). Full vaccination coverage in Pakistan has been gradually improving over the past two decades, with an increase from 35 percent in 1990-91 to 54 percent in 2012-13. There was 15 percent increase between 2006-07 and 2012-13, as compared with a 34 percent increase between 1990-91 and 2006-07. It is encouraging that the percentage of children not receiving any of the six basic immunizations has decreased substantially since 1990-91, from 28 percent to 5 percent. A marked increase in the coverage of polio vaccine was observed between 1990-91 and 2006-07, but coverage more or less stagnated in 2012-13 for polio 1 and 2. Figure 10.1 Trends in vaccination coverage among children age 12-23 months 70 43 43 50 35 28 80 59 83 60 47 6 85 65 85 61 54 5 BCG DPT3 Polio 3 Measles All None Percentage 1990-91 PDHS 2006-07 PDHS 2012-13 PDHS Table 10.4 Trends in vaccination coverage Percentage of children age 12-23 months who received specific vaccines at any time before the survey (according to a vaccination card or the mother’s report), Pakistan Age in months BCG DPT1 Polio2 Measles All basic vaccina- tions3 No vaccina- tions Percentage with a vaccination card seen Number of children 1 2 3 0 1 2 3 1990-91 PDHS 69.7 64.1 60.0 42.7 na 64.8 60.5 42.9 50.2 35.1 28.3 29.6 1,215 2006-07 PDHS 80.3 74.8 66.5 58.5 56.3 93.0 90.6 83.1 59.9 47.3 6.0 23.7 1,522 2012-13 PDHS 85.2 78.8 72.7 65.2 69.4 92.3 89.2 85.3 61.4 53.8 5.4 36.0 2,074 Note: Information was obtained from the vaccination card or, if there was no written record, from the mother. For children whose information is based on the mother’s report, the proportion of vaccinations given during the first year of life is assumed to be the same as for children with a written record of vaccinations. na = Not available 1 DPT vaccinations include DPT/HepB (tetravalent) as well as DPT/HepB/Hib (pentavalent) for the 2012-13 PDHS. 2 Polio 0 is the polio vaccination given at birth. 3 BCG, measles, and 3 doses each of DPT and polio vaccine (excluding polio vaccine given at birth) Child Health • 153 10.5 PREVALENCE AND TREATMENT OF SYMPTOMS OF ARI Acute respiratory infections, malaria, and dehydration caused by severe diarrhea are major causes of childhood mortality in Pakistan. Each year approximately 91,000 and 53,300 children in the country die from pneumonia and diarrhea, respectively. Diarrhea, pneumonia, and malaria collectively contribute to around 50 percent of deaths in children (Das and Bhutta, 2013). These three diseases thus represent a challenging but surmountable obstacle to achieving the MDG 4 target. Information on the prevalence and treatment of ARIs, including early diagnosis and treatment with antibiotics, is crucial in reducing childhood deaths. ARIs kill more children under age 5 than any other infectious disease, and the children most vulnerable to infection include those with low birth weights and those whose immune systems have been weakened by malnutrition or other diseases. Without early treatment for ARI, children can die very rapidly. Many deaths are the result of failure to take the child to a health center in time or of misdiagnosis by a health care worker. Pneumonia, which is caused by acute respiratory infection, is still a leading cause of death among children under age 5 in Pakistan. The Maternal, Newborn, and Child Health Program (MNCH) has launched the integrated management of newborn and childhood illness (IMNCI) strategy to address the management of diseases such as pneumonia, diarrhea, malaria, and measles, as well as malnutrition, among children age 2 months to 5 years (Atwood et al., 2010). The program follows WHO guidelines on standard ARI case management. Accordingly, all ARI cases assessed by health workers are classified into one of the following categories: severe or very severe pneumonia, pneumonia, or no pneumonia (cough and cold). The IMNCI strategy recognizes the important role of mothers and other caretakers in identifying the difference between the need for home care in the case of cough and cold symptoms that do not result in pneumonia and the need for referral to a health facility in the case of pneumonia and severe pneumonia. In the 2012-13 PDHS, mothers of children under age 5 were asked whether, in the two weeks before the survey, these children had symptoms of ARI (cough with short, rapid breathing), fever, and diarrhea. It should be noted that the data collected on ARI symptoms are subjective because they are based on a mother’s perceptions without validation by medical personnel. Table 10.5 presents the data on ARI symptoms. It shows that 16 percent of children under age 5 exhibited symptoms of ARI in the two weeks preceding the survey. The prevalence of ARI symptoms varies by the age of the child. Children age 6-23 months were more likely to have symptoms of ARI (about 20 percent) than children in the older age groups (13 percent). There is not much difference by sex of the child or mother’s smoking status. ARI symptoms were most likely to be reported for children whose mothers had a primary education and children of mothers in the second wealth quintile (18 percent each), as well as those from rural areas and Khyber Pakhtunkhwa. Children in households where charcoal was used as a cooking fuel (21 percent) were more likely to have symptoms of ARI than children in households using wood or straw (17 percent) and those using liquid petroleum gas (LPG) or natural gas (15 percent). Symptoms of ARI were less common among children in households where animal dung was used (10 percent). In terms of ARI treatment, 64 percent of children with symptoms of ARI were taken to a health facility or health care provider. However, use of health facilities has slightly declined since 2006-07 (69 percent). There were no substantial differences in use of a health facility by age and sex of the child. Treatment at a health facility was most likely to be reported for children less than age 6 months, children in urban areas (75 percent), children residing in Sindh and Gilgit Baltistan (82 percent each), children of mothers with a higher education (83 percent), and children of mothers in the highest wealth quintile (79 percent). Forty-two percent of children with ARI symptoms received antibiotics. Use of antibiotics for ARI treatment did not differ substantially by age and sex of the child or mother’s education or wealth quintile (about 40 percent). Treatment with antibiotics was most likely to be reported in rural areas (43 percent) and in Khyber Pakhtunkhwa (46 percent). 154 • Child Health Table 10.5 Prevalence and treatment of symptoms of ARI Among children under age 5, the percentage who had symptoms of acute respiratory infection (ARI) in the two weeks preceding the survey and among children with symptoms of ARI, the percentage for whom advice or treatment was sought from a health facility or provider and the percentage who received antibiotics as treatment, according to background characteristics, Pakistan 2012-13 Among children under age 5: Among children under age 5 with symptoms of ARI: Background characteristic Percentage with symptoms of ARI1 Number of children Percentage for whom advice or treatment was sought from a health facility or provider2 Percentage who received antibiotics Number of children Age in months <6 15.3 1,164 70.7 41.4 178 6-11 21.2 1,024 62.7 44.1 217 12-23 20.2 2,074 65.5 43.5 420 24-35 15.8 2,277 64.0 40.1 359 36-47 12.9 2,286 60.5 41.8 294 48-59 12.8 2,216 64.9 38.3 283 Sex Male 16.4 5,625 66.4 43.2 921 Female 15.3 5,415 62.3 39.7 830 Mother’s smoking status Smokes cigarettes/tobacco 13.6 114 * * 16 Does not smoke 15.9 10,907 64.3 41.4 1,732 Missing * 19 * * 3 Cooking fuel LPG/natural gas/biogas 15.5 3,602 70.8 39.2 557 Coal/lignite (11.2) 5 * * 1 Charcoal 20.9 222 (68.5) (53.9) 46 Wood/straw3 16.9 6,234 60.9 41.7 1,053 Animal dung 9.5 975 65.4 48.3 93 Residence Urban 14.6 3,281 75.1 38.9 478 Rural 16.4 7,759 60.4 42.5 1,273 Region Punjab 15.8 6,307 72.1 44.3 997 Urban 13.5 1,879 79.3 43.9 253 Rural 16.8 4,428 69.7 44.5 744 Sindh 12.8 2,510 81.6 31.6 320 Urban 14.5 1,015 80.4 28.3 147 Rural 11.6 1,495 82.6 34.4 173 Khyber Pakhtunkhwa 23.4 1,560 29.3 45.9 365 Urban 24.9 252 45.5 43.9 63 Rural 23.1 1,308 25.9 46.3 302 Balochistan 9.7 536 53.5 23.0 52 Urban 12.1 98 77.8 38.9 12 Rural 9.1 438 46.3 18.2 40 ICT Islamabad 8.9 45 66.9 32.8 4 Gilgit Baltistan 15.3 81 81.5 29.1 12 Mother’s education No education 16.2 6,226 58.7 42.2 1,008 Primary 18.1 1,870 63.9 37.9 338 Middle 13.2 851 70.3 41.3 112 Secondary 12.9 1,151 82.1 42.8 149 Higher 15.3 942 83.1 44.2 144 Wealth quintile Lowest 13.4 2,574 56.6 41.8 345 Second 18.1 2,301 57.7 42.3 417 Middle 17.7 2,172 60.3 40.4 385 Fourth 16.3 2,189 74.4 41.5 356 Highest 13.7 1,804 78.8 41.7 248 Total 15.9 11,040 64.4 41.5 1,751 Note: Total includes 1 case with missing information on cooking fuel. Figures in parentheses are based on 25-49 unweighted cases. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 1 Symptoms of ARI (cough accompanied by short, rapid breathing that is chest-related and/or by difficult breathing that is chest-related) are considered a proxy for pneumonia. 2 Excludes pharmacy, shop, homeopath, dispenser, compounder, hakim, and dai/traditional practitioner 3 Includes grass, shrubs, and crop residues LPG = Liquid petroleum gas Child Health • 155 10.6 PREVALENCE AND TREATMENT OF FEVER Fever is a major manifestation of malaria and other acute respiratory infections in young children. Malaria and fever contribute to high levels of malnutrition and mortality. In Pakistan, the major malaria transmission period is from August to November (i.e., post-monsoon) (Directorate of Malaria Control, 2013). The major vectors are Anopheles culicifacies and A. stephensi, both of which are still susceptible to the insecticides in current use. The widely distributed causative organisms are Plasmodium falciparum and P. vivax. Table 10.6 shows the percentage of children under age 5 who had a fever during the two weeks preceding the survey and the percentage receiving various treatments, by selected background characteristics. Thirty-eight percent of children under age 5 had a fever in the two weeks before the survey. The prevalence of fever varied by age and was highest among children age 6-11 (50 percent). Fever prevalence also varied by region, ranging from a low of 23 percent in Balochistan to a high of 44 percent in Khyber Pakhtunkhwa. Children of mothers with a primary education (40 percent) were more likely to have had a fever than children of mothers at other educational levels. There were no visible variations in occurrence of fever by child sex, residence, or wealth quintile. The data also show that 65 percent of children under age 5 with fever had received advice or treatment from a health facility or provider. There is little variation in treatment-seeking behavior by age and sex of the child (62 percent or above). Children residing in urban areas are more likely to receive treatment (75 percent) than those living in rural areas (61 percent), and children from Sindh are more likely to get treatment (78 percent) than those from Balochistan (42 percent) and Khyber Pakhtunkhwa (27 percent). Highly educated mothers are more likely (78 percent) than those with no education (60 percent) to seek treatment for their children. Similarly, children in the highest wealth quintile are more likely to receive treatment (79 percent) than those in the lowest wealth quintile (56 percent). Surprisingly, the percentage of children with fever for whom medical care is sought from a health facility or provider has not changed over the past two decades (65 percent in 1990-91, 66 percent in 2006-07, and 65 percent in 2012-13). Since malaria is a major cause of death in infancy and childhood in many developing countries, presumptive treatment of fever with antimalarial medication is advocated in many countries where malaria is endemic. However, the 2012-13 PDHS fieldwork was carried out from October 2012 to March 2013, almost a month after the rainy season, and thus the use of antimalarial medication may have lower during that period. The data (Table 10.6) show that use of antimalarial drugs was quite low (3 percent) and that there was little variation by sex of child, urban-rural residence, or wealth quintile. Children age 6-11 months, those living in Khyber Pakhtunkhwa, those whose mothers had a primary education, and those in the highest wealth quintile were more likely than other children to receive antimalarial drugs. Table 10.6 also shows that 40 percent of children with fever received antibiotics. Children age 24- 35 months, male children, children residing in rural areas and Punjab, those whose mothers had a higher education, and those in the middle wealth quintile were more likely than other children to receive antibiotics. 156 • Child Health Table 10.6 Prevalence and treatment of fever Among children under age 5, the percentage who had a fever in the two weeks preceding the survey, and among children with fever, the percentage for whom advice or treatment was sought from a health facility or provider, the percentage who took antimalarial drugs, and the percentage who received antibiotics as treatment, by background characteristics, Pakistan 2012-13 Among children under age 5: Among children under age 5 with fever: Background characteristic Percentage with fever Number of children Percentage for whom advice or treatment was sought from a health facility or provider1 Percentage who took antimalarial drugs Percentage who took antibiotic drugs Number of children Age in months <6 33.8 1,164 66.7 2.4 32.0 394 6-11 49.8 1,024 64.9 5.3 41.1 510 12-23 46.4 2,074 66.0 4.0 40.0 962 24-35 39.2 2,277 64.4 3.8 41.7 892 36-47 32.6 2,286 62.3 2.5 41.3 745 48-59 29.3 2,216 64.9 1.9 39.3 650 Sex Male 38.6 5,625 67.3 3.0 41.4 2,174 Female 36.5 5,415 62.0 3.8 38.2 1,979 Residence Urban 36.5 3,281 74.8 4.0 37.2 1,198 Rural 38.1 7,759 60.7 3.1 41.0 2,954 Region Punjab 37.9 6,307 71.9 2.4 43.4 2,388 Urban 37.6 1,879 75.6 4.8 40.6 707 Rural 38.0 4,428 70.4 1.4 44.5 1,681 Sindh 36.0 2,510 77.6 2.5 32.2 904 Urban 34.5 1,015 79.9 1.5 29.6 350 Rural 37.0 1,495 76.2 3.2 33.8 553 Khyber Pakhtunkhwa 44.4 1,560 26.5 7.5 41.9 692 Urban 40.7 252 54.1 5.2 41.4 102 Rural 45.1 1,308 21.7 7.9 42.0 590 Balochistan 22.6 536 42.1 5.5 22.4 121 Urban 25.2 98 65.3 9.7 33.7 25 Rural 22.0 438 36.2 4.4 19.6 96 ICT Islamabad 40.8 45 72.5 3.1 29.0 18 Gilgit Baltistan 35.5 81 76.1 0.0 24.3 29 Mother’s education No education 36.6 6,226 59.5 3.3 39.9 2,280 Primary 40.1 1,870 69.0 4.2 41.1 750 Middle 38.9 851 65.4 4.0 40.1 331 Secondary 38.1 1,151 73.6 2.7 36.2 439 Higher 37.4 942 78.4 2.0 41.7 352 Wealth quintile Lowest 35.0 2,574 56.4 2.4 37.2 901 Second 38.7 2,301 56.5 3.8 41.7 891 Middle 39.1 2,172 63.4 3.1 42.7 850 Fourth 38.8 2,189 72.6 3.3 38.3 848 Highest 36.7 1,804 79.0 4.5 39.5 663 Total 37.6 11,040 64.8 3.4 39.9 4,153 1 Excludes pharmacy, shop, homeopath, dispenser, compounder, hakim, and dai/traditional practitioner Child Health • 157 10.7 PREVALENCE OF DIARRHEA Diarrhea remains a leading cause of childhood morbidity and mortality in developing countries. Un- fortunately, despite simple treatment guidelines, 53,300 children die of diarrhea each year, and there are an average of four to six episodes of diarrhea per child per year. Diarrhea is a major cause of mortality and morbidity among Pakistani children despite decades of concerted efforts and special programs. There have been considerable improvements, however, with the advent of oral rehydration salts (ORS) (Memon, 2012). Because diarrhea causes a rapid loss of body fluids, it leaves children continually at risk of dehydration. If left untreated, dehydration caused by severe diarrhea is a major cause of morbidity among young children. This condition can be easily treated with oral rehydration therapy (ORT), a simple solution prepared by mixing water with a commercially prepared packet of oral rehydration salts or by making a homemade mixture of sugar, salt, and water. Oral rehydration packets are available through health facilities and at shops and pharmacies. In the 2012-13 PDHS, information on diarrhea was gathered by asking mothers whether their child had experienced any episode of diarrhea in the two weeks before the survey. If the child had had diarrhea, the mother was asked about feeding practices during diarrhea, types of treatment, and her knowledge and use of ORS. Table 10.7 shows that 23 percent of children under age 5 suffered from diarrhea in the two weeks preceding the survey. Diarrhea with blood was reported for only a very small proportion of children (2 percent). The prevalence of diarrhea was reported to be 15 percent in 1990-91 and 22 percent in 2006-07. Although diarrhea prevalence varies seasonally, the three PDHS surveys were conducted in more or less the same period, and thus the diarrhea episodes reported in the three surveys depict a realistic trend. The prevalence of diarrhea is highest among children age 6-11 months (35 percent), a span during which solid foods are first introduced into the child’s diet. This period is believed to be associated with increased exposure to illness as a result of weaning and the immature immune systems of children in this age group. Prevalence of diarrhea does not show variations by sex of the child, type of toilet facility, or residence. Diarrhea prevalence is higher among households using a non-improved source of drinking water than among households using an improved source. There are visible variations in the prevalence of diarrhea by region. Khyber Pakhtunkhwa has the highest prevalence (28 percent), followed by Sindh (23 percent) and Punjab (22 percent); the lowest proportion is in Balochistan (12 percent). There are no Table 10.7 Prevalence of diarrhea Percentage of children under age 5 who had diarrhea in the two weeks preceding the survey, by background characteristics, Pakistan 2012-13 Background characteristic Diarrhea in the two weeks preceding the survey Number of children All diarrhea Diarrhea with blood Age in months <6 25.8 1.4 1,164 6-11 35.3 3.4 1,024 12-23 32.9 3.5 2,074 24-35 22.0 2.6 2,277 36-47 16.3 1.5 2,286 48-59 12.0 1.8 2,216 Sex Male 22.7 2.4 5,625 Female 22.3 2.2 5,415 Source of drinking water1 Improved 22.2 2.3 10,170 Not improved 25.5 2.6 796 Other/missing 35.5 0.1 75 Toilet facility2 Improved, not shared 21.9 2.1 6,164 Shared3 23.2 2.3 1,188 Non-improved 23.2 2.7 3,659 Residence Urban 21.9 1.7 3,281 Rural 22.7 2.6 7,759 Region Punjab 21.9 2.5 6,307 Urban 22.5 1.8 1,879 Rural 21.6 2.8 4,428 Sindh 23.1 2.5 2,510 Urban 21.9 1.5 1,015 Rural 23.9 3.1 1,495 Khyber Pakhtunkhwa 27.9 1.9 1,560 Urban 21.6 1.6 252 Rural 29.1 1.9 1,308 Balochistan 12.1 1.2 536 Urban 11.3 0.9 98 Rural 12.2 1.3 438 ICT Islamabad 20.5 0.9 45 Gilgit Baltistan 16.7 1.1 81 Mother’s education No education 22.9 2.4 6,226 Primary 25.0 3.3 1,870 Middle 22.6 2.1 851 Secondary 21.1 1.3 1,151 Higher 16.4 0.9 942 Wealth quintile Lowest 22.8 2.5 2,574 Second 24.3 3.1 2,301 Middle 23.7 2.6 2,172 Fourth 23.6 1.7 2,189 Highest 17.1 1.3 1,804 Total 22.5 2.3 11,040 Note: Total includes 29 cases with missing information on type of toilet facility. 1 See Table 2.1 for definition of categories. 2 See Table 2.2 for definition of categories. 3 Facilities that would be considered improved if they were not shared by two or more households 158 • Child Health substantial variations by mother’s education and wealth quintile, except that children of mothers who have a higher education (16 percent) and children of mothers in the highest wealth quintile (17 percent) are less likely to suffer from diarrhea. 10.8 DIARRHEA TREATMENT The MNCH program focuses on the management of diarrheal diseases among children under age 5. Pakistan is one of the first countries in the region to include zinc in the diarrhea treatment protocol along with low osmolality ORS and oral rehydration therapy. Treatment with zinc is not a substitute for ORT, but, when taken in addition to ORT, it can reduce the severity and duration of diarrhea. This improved treatment, recommended by WHO, has lower amounts of sodium and glucose and, thus, lower osmolality (WHO, 2006d). Pakistan initiated the protocol in 2005, and this newer version of ORS therapy is now available on the market. The government’s standard diarrhea case management strategy includes ORT, counseling on continued feeding, and zinc tablets provided through health service outlets. ORT services have been established in all hospitals, primary health care centers, lady health worker programs, and nongovernment health centers throughout the country. Health facilities and community health volunteers are the primary health providers with responsibility for treating diarrhea with ORS and zinc supplementation. Table 10.8 shows data on the treatment of recent episodes of diarrhea among children under age 5, as reported by their mothers. Overall, 61 percent of children with diarrhea were taken to a medically trained health provider for advice or treatment. Children age 12-23 months, male children, children with bloody diarrhea, children living in urban areas and Sindh, children of mothers with a middle level of education, and children from households in the highest wealth quintile are more likely than other children to visit a health professional or a health facility for diarrhea treatment. Forty-six percent of children with diarrhea were given ORT or increased fluids. Thirty-eight percent of children with diarrhea received ORS packets, while 9 percent were given a recommended homemade fluid. Overall, 42 percent were given either ORS or a recommended homemade fluid. Nine percent of children were given increased liquids. After increasing from 39 percent in 1990-91 to 41 percent in 2006-07, the use of commercially available ORS packets stabilized to 38 percent in 2012-13. The percentage of children receiving homemade fluids increased from 12 percent in 1990-91 to 16 percent in 2006-07 and then decreased to 9 percent in 2012-13. The percentage of children receiving increased fluids has not changed substantially over the past two decades. Only 2 percent of children were treated with zinc. Although not a preferred treatment, 5 percent of children were treated with antimotility drugs. Thirty-three percent of children with diarrhea were given antibiotic drugs. It is also vital to note that 11 percent of children did receive any form of treatment. Use of ORT or increased fluids varies by age, from a low of 34 percent among children less than age 6 months to a high of 51 percent among children age 12-23 months. Use of ORT or increased fluids is more common among male than female children. In addition, there are differences in the use of this treatment by residence (51 percent in urban areas and 44 percent in rural areas) and region (43 percent in Punjab and 77 percent in Gilgit Baltistan). The proportion of children receiving ORT or increased fluids varies by mother’s education as well, ranging from 43 percent of children whose mothers have no education to 59 percent of those whose mothers have a secondary education. Use of ORT or increased fluids is much higher among children in the highest wealth quintile (55 percent). T ab le 1 0. 8 D ia rr he a tre at m en t A m on g ch ild re n un de r a ge 5 w ho h ad d ia rr he a in th e tw o w ee ks p re ce di ng th e su rv ey , t he p er ce nt ag e fo r w ho m a dv ic e or tr ea tm en t w as s ou gh t f ro m a h ea lth fa ci lit y or p ro vi de r, th e pe rc en ta ge g iv en o ra l r eh yd ra tio n th er ap y (O R T) , t he p er ce nt ag e gi ve n in cr ea se d flu id s, th e pe rc en ta ge g iv en O R T or in cr ea se d flu id s, a nd th e pe rc en ta ge g iv en o th er tr ea tm en ts , b y ba ck gr ou nd c ha ra ct er is tic s, P ak is ta n 20 12 -1 3 B ac kg ro un d ch ar ac te ris tic P er ce nt ag e of ch ild re n w ith di ar rh ea fo r w ho m ad vi ce o r t re at m en t w as s ou gh t f ro m a he al th fa ci lit y or pr ov id er 1 O ra l r eh yd ra tio n th er ap y (O R T) In cr ea se d flu id s O R T or in cr ea se d flu id s O th er tr ea tm en ts M is si ng N o tre at m en t N um be r o f ch ild re n w ith di ar rh ea Fl ui d fro m O R S pa ck et s or pr e- pa ck ag ed liq ui d R ec om - m en de d ho m e flu id s (R H F) E ith er O R S or R H F A nt ib io tic dr ug s A nt im ot ili ty dr ug s Zi nc s up pl e- m en ts In tra ve no us so lu tio n H om e re m ed y/ ot he r A ge in m on th s <6 60 .0 25 .9 3. 3 27 .2 7. 9 33 .5 31 .1 0. 6 0. 6 1. 7 59 .5 0. 0 15 .6 30 0 6- 11 60 .8 38 .8 10 .5 42 .7 5. 3 43 .9 35 .7 5. 5 0. 3 5. 0 57 .6 1. 0 11 .7 36 1 12 -2 3 68 .0 44 .4 11 .0 48 .5 8. 2 50 .9 35 .5 4. 7 2. 7 3. 0 62 .4 0. 0 5. 5 68 2 24 -3 5 62 .1 40 .3 8. 3 42 .7 12 .3 47 .8 34 .8 7. 9 1. 8 2. 0 59 .7 0. 0 10 .1 50 1 36 -4 7 51 .8 39 .6 8. 6 42 .8 13 .2 49 .6 31 .3 4. 0 0. 5 2. 1 58 .9 0. 3 13 .4 37 3 48 -5 9 55 .4 27 .8 13 .7 36 .7 7. 3 40 .5 27 .9 4. 1 1. 8 0. 5 58 .7 0. 4 14 .6 26 5 Se x M al e 63 .3 41 .5 9. 3 44 .8 8. 7 48 .6 33 .1 4. 8 1. 1 2. 8 60 .8 0. 2 10 .5 1, 27 4 Fe m al e 58 .6 34 .4 9. 4 38 .6 9. 8 43 .0 33 .8 4. 8 2. 0 2. 3 58 .9 0. 2 11 .0 1, 20 8 Ty pe o f d ia rr he a N on -b lo od y 60 .2 36 .8 8. 9 40 .7 9. 1 44 .7 33 .5 4. 8 1. 6 2. 5 58 .9 0. 2 11 .7 2, 20 4 B lo od y 71 .1 50 .2 14 .7 52 .8 10 .4 57 .1 33 .1 4. 9 1. 0 2. 2 68 .1 0. 0 3. 7 25 6 M is si ng (3 0. 0) (2 3. 1) (0 .0 ) (2 3. 1) (6 .2 ) (2 9. 4) (2 6. 9) (3 .0 ) (0 .0 ) (8 .7 ) (6 0. 2) (8 .1 ) (0 .0 ) 23 R es id en ce U rb an 72 .3 41 .5 14 .0 47 .1 10 .0 50 .8 35 .0 5. 3 1. 5 1. 8 61 .4 0. 0 9. 1 71 9 R ur al 56 .4 36 .6 7. 5 39 .6 8. 9 43 .9 32 .7 4. 6 1. 5 2. 8 59 .3 0. 3 11 .4 1, 76 4 R eg io n P un ja b 68 .6 35 .2 11 .0 40 .2 7. 4 43 .2 33 .7 2. 0 1. 5 2. 0 65 .3 0. 0 10 .6 1, 38 1 S in dh 73 .0 45 .2 8. 3 47 .5 9. 6 52 .9 21 .9 7. 7 1. 0 4. 0 66 .4 0. 3 7. 2 57 9 K hy be r P ak ht un kh w a 23 .0 35 .5 5. 8 37 .6 14 .2 43 .8 48 .8 9. 4 2. 3 1. 7 36 .3 0. 9 14 .8 43 5 B al oc hi st an 43 .4 41 .5 4. 5 43 .0 6. 2 43 .6 30 .3 7. 6 0. 8 6. 4 46 .4 0. 0 17 .6 65 IC T Is la m ab ad 66 .5 53 .9 22 .8 62 .3 23 .2 68 .4 25 .3 4. 5 2. 5 1. 3 57 .9 0. 6 9. 3 9 G ilg it B al tis ta n 69 .5 72 .5 14 .7 75 .8 21 .9 76 .8 22 .0 0. 2 2. 1 0. 0 51 .8 0. 0 7. 2 14 M ot he r’s e du ca tio n N o ed uc at io n 55 .9 35 .0 7. 5 38 .0 9. 4 42 .6 32 .3 5. 5 1. 4 2. 7 59 .0 0. 3 11 .3 1, 42 4 P rim ar y 65 .8 38 .2 10 .8 41 .3 8. 6 44 .4 30 .2 1. 7 2. 6 2. 9 63 .0 0. 0 12 .4 46 8 M id dl e 71 .9 41 .9 17 .1 52 .6 5. 6 55 .2 37 .9 6. 4 0. 0 0. 7 57 .1 1. 0 7. 2 19 2 S ec on da ry 66 .6 48 .7 11 .1 52 .7 13 .6 58 .9 37 .7 4. 1 1. 2 2. 6 62 .9 0. 0 8. 0 24 3 H ig he r 70 .8 44 .2 9. 7 47 .6 7. 2 48 .5 40 .8 6. 8 1. 2 2. 2 57 .5 0. 0 9. 3 15 5 W ea lth q ui nt ile Lo w es t 54 .0 33 .6 7. 7 37 .7 8. 8 43 .0 28 .4 6. 4 2. 2 2. 0 58 .5 0. 4 11 .5 58 6 S ec on d 54 .9 32 .3 5. 0 33 .8 7. 9 37 .5 35 .5 3. 9 1. 0 2. 5 54 .7 0. 7 13 .8 55 9 M id dl e 58 .8 42 .2 10 .5 44 .9 12 .0 49 .7 33 .6 3. 3 1. 6 3. 8 62 .1 0. 0 10 .1 51 4 Fo ur th 68 .3 39 .0 12 .7 46 .0 8. 6 49 .1 30 .4 4. 7 1. 1 2. 5 66 .7 0. 0 8. 5 51 6 H ig he st 76 .8 48 .2 13 .2 52 .0 8. 7 54 .9 43 .7 6. 1 1. 4 1. 5 56 .8 0. 0 8. 6 30 8 To ta l 61 .0 38 .0 9. 4 41 .8 9. 2 45 .9 33 .4 4. 8 1. 5 2. 5 59 .9 0. 2 10 .7 2, 48 2 N ot e: O R T in cl ud es fl ui d pr ep ar ed fr om o ra l r eh yd ra tio n sa lt (O R S ) p ac ke ts , p re -p ac ka ge d O R S flu id , a nd re co m m en de d ho m e flu id s (R H F) . F ig ur es in p ar en th es es a re b as ed o n 25 -4 9 un w ei gh te d ca se s. 1 E xc lu de s ph ar m ac y, s ho p, h om eo pa th , d is pe ns er , c om po un de r, ha ki m , a nd d ai /tr ad iti on al p ra ct iti on er Child Health • 159 160 • Child Health 10.9 FEEDING PRACTICES DURING DIARRHEA Rapid rehydration and realimentation continues to be the cornerstone of treatment of diarrhea. Mothers are thus encouraged to continue feeding children with diarrhea normally and to increase the amount of fluids given. Table 10.9 shows that 54 percent of children who had diarrhea were given the same amount of fluid as usual and 9 percent were given more. A high percentage of children (30 percent) were given somewhat less than the usual amount, and 6 percent were given much less. One percent of children with diarrhea were not given any liquids. Forty percent of children who had diarrhea were given the same amount of food as usual; 33 percent were given somewhat less than the usual amount of food, and 8 percent were given much less than the usual amount. Children age 24-35 and 36-47 months are more likely (43 percent) than those in other age groups to be continually fed and given ORT and/or increased fluids during an episode of diarrhea. Children under age 6 months are least likely (10 percent) to be given ORT and/or increased fluids and fed normally during diarrhea. There are variations in feeding practices by other background characteristics as well. Male children and children suffering from bloody diarrhea, children in urban areas, children residing in Gilgit Baltistan, children of mothers with a secondary education, and children from the highest wealth quintile are more likely than other children to receive ORT and/or increased fluids with continued feeding. The percentage of children with diarrhea given increased fluids and fed continually has declined over the past six years, from 14 percent to 8 percent. Similarly, the practice of giving ORT and/or increased fluids along with continued feeding has decreased over this period, from 52 percent to 36 percent. The results outlined above clearly highlight the need for health program managers to revisit their plans and strategies to improve the health status of children in Pakistan. Ta bl e 10 .9 F ee di ng p ra ct ic es d ur in g di ar rh ea P er ce nt d is tri bu tio n of c hi ld re n un de r a ge 5 w ho h ad d ia rr he a in th e tw o w ee ks p re ce di ng th e su rv ey b y am ou nt o f l iq ui ds a nd fo od o ffe re d co m pa re d w ith n or m al p ra ct ic e, th e pe rc en ta ge o f c hi ld re n gi ve n in cr ea se d flu id s an d co nt in ue d fe ed in g du rin g th e di ar rh ea e pi so de , a nd th e pe rc en ta ge o f c hi ld re n w ho c on tin ue d fe ed in g an d w er e gi ve n or al r eh yd ra tio n th er ap y (O R T) a nd /o r in cr ea se d flu id s du rin g th e ep is od e of d ia rrh ea , b y ba ck gr ou nd c ha ra ct er is tic s, P ak is ta n 20 12 -1 3 A m ou nt o f l iq ui ds g iv en A m ou nt o f f oo d gi ve n P er ce nt ag e gi ve n in cr ea se d flu id s an d co nt in ue d fe ed in g1 P er ce nt ag e w ho c on tin ue d fe ed in g an d w er e gi ve n O R T an d/ or in cr ea se d flu id s1 N um be r of ch ild re n w ith di ar rh ea B ac kg ro un d ch ar ac te ris tic M or e S am e as us ua l S om e- w ha t l es s M uc h le ss N on e D on ’t kn ow / m is si ng To ta l M or e S am e as us ua l S om e- w ha t l es s M uc h le ss N on e N ev er ga ve fo od D on ’t kn ow / m is si ng To ta l A ge in m on th s <6 7. 9 59 .4 19 .2 6. 7 6. 5 0. 2 10 0. 0 0. 9 12 .4 8. 8 6. 9 0. 7 70 .2 0. 0 10 0. 0 1. 0 9. 7 30 0 6- 11 5. 3 53 .7 32 .0 6. 5 1. 5 0. 8 10 0. 0 1. 4 34 .6 23 .5 6. 4 7. 7 25 .5 0. 8 10 0. 0 3. 9 28 .8 36 1 12 -2 3 8. 2 52 .8 31 .3 7. 5 0. 3 0. 0 10 0. 0 2. 7 44 .5 36 .1 9. 9 3. 9 3. 0 0. 0 10 0. 0 7. 0 41 .7 68 2 24 -3 5 12 .3 53 .2 28 .5 5. 3 0. 7 0. 0 10 0. 0 4. 0 45 .5 43 .1 6. 6 0. 4 0. 5 0. 0 10 0. 0 11 .6 43 .1 50 1 36 -4 7 13 .2 48 .0 32 .7 5. 7 0. 2 0. 2 10 0. 0 5. 1 44 .0 42 .1 6. 3 1. 7 0. 6 0. 2 10 0. 0 12 .3 43 .1 37 3 48 -5 9 7. 3 56 .6 31 .0 5. 1 0. 0 0. 0 10 0. 0 8. 8 49 .1 34 .2 6. 8 1. 0 0. 0 0. 0 10 0. 0 6. 3 35 .2 26 5 Se x M al e 8. 7 53 .0 30 .7 6. 6 0. 8 0. 2 10 0. 0 2. 7 38 .9 34 .6 7. 6 2. 8 13 .2 0. 2 10 0. 0 6. 8 37 .9 1, 27 4 Fe m al e 9. 8 54 .0 28 .4 5. 9 1. 7 0. 1 10 0. 0 4. 5 40 .8 31 .5 7. 3 2. 6 13 .2 0. 1 10 0. 0 8. 2 33 .5 1, 20 8 Ty pe o f d ia rr he a N on -b lo od y 9. 1 54 .9 28 .9 5. 7 1. 3 0. 0 10 0. 0 3. 8 40 .3 32 .3 6. 7 2. 6 14 .2 0. 0 10 0. 0 7. 4 35 .1 2, 20 4 B lo od y 10 .4 42 .8 34 .9 10 .6 1. 3 0. 1 10 0. 0 1. 1 36 .0 40 .3 13 .5 3. 5 5. 6 0. 0 10 0. 0 8. 5 41 .9 25 6 M is si ng (6 .2 ) (3 2. 9) (2 9. 7) (1 7. 8) 0. 0 (1 3. 4) 10 0. 0 (8 .3 ) (3 3. 9) (2 6. 6) (1 7. 8) 0. 0 0. 0 (1 3. 4) 10 0. 0 (6 .2 ) (2 6. 7) 23 R es id en ce U rb an 10 .0 57 .8 26 .3 4. 6 1. 1 0. 2 10 0. 0 3. 7 46 .0 30 .1 5. 2 2. 2 12 .6 0. 1 10 0. 0 8. 2 41 .6 71 9 R ur al 8. 9 51 .7 30 .9 7. 0 1. 3 0. 2 10 0. 0 3. 5 37 .2 34 .3 8. 4 2. 9 13 .5 0. 2 10 0. 0 7. 2 33 .4 1, 76 4 R eg io n P un ja b 7. 4 67 .4 22 .6 1. 1 1. 3 0. 2 10 0. 0 4. 3 50 .8 25 .5 1. 3 3. 5 14 .5 0. 2 10 0. 0 6. 2 37 .4 1, 38 1 S in dh 9. 6 34 .8 38 .3 17 .0 0. 2 0. 1 10 0. 0 2. 7 21 .3 41 .0 18 .6 1. 4 14 .9 0. 1 10 0. 0 7. 2 33 .6 57 9 K hy be r P ak ht un kh w a 14 .2 38 .5 38 .7 6. 5 1. 9 0. 3 10 0. 0 2. 3 31 .1 46 .0 10 .6 1. 6 8. 3 0. 2 10 0. 0 11 .7 33 .2 43 5 B al oc hi st an 6. 2 28 .0 39 .1 21 .8 5. 0 0. 0 10 0. 0 3. 0 26 .2 35 .8 20 .8 6. 4 7. 8 0. 0 10 0. 0 3. 8 26 .9 65 IC T Is la m ab ad 23 .2 50 .0 22 .8 3. 8 0. 3 0. 0 10 0. 0 7. 7 55 .8 26 .3 6. 8 0. 0 3. 3 0. 0 10 0. 0 20 .9 62 .8 9 G ilg it B al tis ta n 21 .9 39 .5 33 .4 3. 1 1. 0 1. 2 10 0. 0 4. 5 41 .0 43 .7 4. 0 0. 0 4. 4 2. 4 10 0. 0 20 .3 67 .5 14 M ot he r’s e du ca tio n N o ed uc at io n 9. 4 48 .6 32 .8 8. 2 0. 8 0. 2 10 0. 0 2. 7 36 .9 33 .4 10 .0 2. 6 14 .2 0. 2 10 0. 0 7. 6 30 .7 1, 42 4 P rim ar y 8. 6 61 .7 22 .3 4. 7 2. 6 0. 1 10 0. 0 4. 8 43 .4 30 .2 4. 4 3. 7 13 .6 0. 0 10 0. 0 7. 2 37 .6 46 8 M id dl e 5. 6 65 .7 27 .3 0. 5 0. 8 0. 0 10 0. 0 2. 4 50 .0 31 .4 3. 2 1. 0 11 .9 0. 0 10 0. 0 3. 6 45 .1 19 2 S ec on da ry 13 .6 55 .2 26 .1 4. 0 1. 1 0. 0 10 0. 0 5. 7 40 .2 36 .3 3. 5 3. 2 11 .1 0. 0 10 0. 0 10 .5 49 .2 24 3 H ig he r 7. 2 55 .2 29 .9 4. 5 2. 8 0. 4 10 0. 0 6. 1 42 .0 36 .2 5. 5 2. 4 7. 5 0. 4 10 0. 0 7. 1 43 .8 15 5 W ea lth q ui nt ile Lo w es t 8. 8 44 .3 36 .6 9. 4 0. 8 0. 0 10 0. 0 3. 3 34 .7 35 .4 11 .2 2. 8 12 .6 0. 1 10 0. 0 6. 3 32 .1 58 6 S ec on d 7. 9 51 .0 32 .3 7. 8 0. 8 0. 2 10 0. 0 4. 3 37 .7 32 .3 9. 4 1. 8 14 .3 0. 2 10 0. 0 6. 4 25 .7 55 9 M id dl e 12 .0 55 .4 23 .9 6. 4 1. 7 0. 5 10 0. 0 2. 7 38 .2 32 .4 7. 3 4. 0 14 .9 0. 4 10 0. 0 11 .2 39 .2 51 4 Fo ur th 8. 6 62 .5 26 .1 1. 5 1. 3 0. 0 10 0. 0 3. 1 47 .5 31 .3 3. 1 2. 8 12 .1 0. 0 10 0. 0 6. 7 41 .8 51 6 H ig he st 8. 7 56 .9 26 .4 5. 6 2. 3 0. 2 10 0. 0 5. 0 43 .0 34 .3 4. 4 2. 0 11 .2 0. 2 10 0. 0 6. 9 45 .0 30 8 To ta l 9. 2 53 .5 29 .6 6. 3 1. 3 0. 2 10 0. 0 3. 6 39 .8 33 .1 7. 5 2. 7 13 .2 0. 2 10 0. 0 7. 5 35 .8 2, 48 2 N ot e: It is re co m m en de d th at c hi ld re n sh ou ld b e gi ve n m or e liq ui ds to d rin k du rin g di ar rh ea a nd fo od s ho ul d no t b e re du ce d. F ig ur es in p ar en th es es a re b as ed o n 25 -4 9 un w ei gh te d ca se s. 1 C on tin ue d fe ed in g in cl ud es c hi ld re n w ho w er e gi ve n m or e, th e sa m e as u su al , o r s om ew ha t l es s fo od d ur in g th e di ar rh ea e pi so de . Child Health • 161 Nutrition of Children and Women • 163 NUTRITION OF CHILDREN AND WOMEN 11 ood nutrition is a prerequisite for the national development of countries and for the well-being of individuals. Although problems related to poor nutrition affect the entire population, women and children are especially vulnerable because of their unique physiology and socioeconomic characteristics. Adequate nutrition is essential to children’s growth and development. The period from conception to age 2 is especially important for optimal physical, mental, and cognitive growth, health, and development. However, this period is often marked by protein-energy and micronutrient deficiencies that interfere with optimal growth. Illnesses such as diarrhea and acute respiratory infections are also common among children. A woman’s nutritional status has important implications for her health as well as for the health of her children. Among women, malnutrition results in reduced productivity, increased susceptibility to infections, slow recovery from illness, and a heightened risk of adverse pregnancy outcomes. For example, a woman with poor nutritional status, as indicated by a low body mass index (BMI), short stature, anemia, or other micronutrient deficiencies, has a greater risk of obstructed labor, of having a baby with a low birth weight, of producing low-quality breast milk, of death due to postpartum hemorrhage, and of morbidity for both herself and her baby. This chapter reviews the nutritional status of children and women in Pakistan. Specific issues discussed include child nutrition based on anthropometric measurements, infant and young child feeding practices, and micronutrient intake among children and women. 11.1 NUTRITIONAL STATUS OF CHILDREN The nutritional status of children under age 5 is an important measure of children’s health. The anthropometric data on height and weight collected in the 2012-13 PDHS permit the measurement and evaluation of the nutritional status of young children in Pakistan. G Key Findings • Forty-five percent of children under age 5 are stunted, 11 percent are wasted, and 30 percent are underweight. • Ninety-four percent of children were reported to have been breastfed at some time. • Thirty-eight percent of children less than age 6 months are exclusively breastfed. The median duration of exclusive breastfeeding is less than one month. • Complementary foods are not introduced in a timely fashion for all children. Only 57 percent of breastfed children age 6-9 months received complementary foods. • Overall, only 15 percent of children age 6-23 months are fed appropriately based on recommended infant and young child feeding (IYCF) practices. • Fourteen percent of women are undernourished (BMI <18.5), and 40 percent are overweight or obese (BMI ≥25.0). 164 • Nutrition of Children and Women 11.1.1 Measurement of Nutritional Status among Young Children The 2012-13 PDHS collected data on the nutritional status of children by measuring the height and weight of all children under age 5 in selected households. These data allow the calculation of three indices: height-for-age, weight-for-height, and weight-for-age. Indicators of the nutritional status of children were calculated using growth standards published by the World Health Organization (WHO) in 2006. These growth standards were generated through data collected in the WHO Multicenter Growth Reference Study (WHO, 2006e). The findings of that study, which sampled 8,440 children in six countries (Brazil, Ghana, India, Norway, Oman, and the United States), illustrated how children should grow under optimal conditions. The WHO child growth standards can therefore be used to assess children all over the world, regardless of ethnicity, social and economic influences, or feeding practices. The WHO growth standards replaced the previously used NCHS/CDC/WHO (U.S. National Center for Health Statistics/U.S. Centers for Disease Control and Prevention/World Health Organization) reference standards. It should be noted that the WHO child growth standards are not comparable to the previously used NCHS/CDC/WHO standards. Several changes are evident when the WHO standards rather than the previous standards are used (WHO, 2006e). For example, the level of stunting is higher, and the level of underweight is substantially higher during the first half of infancy (0-6 months) and decreases thereafter. The three nutritional status indices are expressed in standard deviation units from the Multicenter Growth Reference Study median. The height-for-age index is an indicator of linear growth retardation and cumulative growth deficits in children. Children whose height-for-age Z-score is below minus two standard deviations (-2 SD) from the median of the WHO reference population are considered short for their age (stunted), or chronically malnourished. Children who are below minus three standard deviations (-3 SD) from the reference median are considered severely stunted. Stunting reflects failure to receive adequate nutrition over a long period of time and is affected by recurrent and chronic illness. Height-for- age, therefore, represents the long-term effects of malnutrition in a population and is not sensitive to recent, short-term changes in dietary intake. The weight-for-height index measures body mass in relation to height or length and describes current nutritional status. Children with Z-scores below minus two standard deviations (-2 SD) from the reference population median are considered thin (wasted) or acutely malnourished. Wasting represents the failure to receive adequate nutrition in the period immediately preceding the survey and may be the result of inadequate food intake or a recent episode of illness causing loss of weight and the onset of malnutrition. Children with a weight-for-height index below minus three standard deviations (-3 SD) from the reference median are considered severely wasted. The weight-for-height index also provides data on overweight and obesity. Children above two standard deviations (+2 SD) from the reference median are considered overweight or obese. Weight-for-age is a composite index of height-for-age and weight-for-height. It takes into account both acute malnutrition (wasting) and chronic malnutrition (stunting), but it does not distinguish between the two. Children whose weight-for-age is below minus two standard deviations (-2 SD) from the reference population median are classified as underweight. Children whose weight-for-age is below minus three standard deviations (-3 SD) from the reference median are considered severely underweight. Z-score means are also calculated as summary statistics representing the nutritional status of children in a population. These mean scores describe the nutritional status of the entire population without the use of a cutoff. A mean Z-score of less than 0 (i.e., a negative mean value for stunting, wasting, or underweight) suggests that the distribution of an index has shifted downward and that most if not all children in the population suffer from undernutrition relative to the reference population. Nutrition of Children and Women • 165 11.1.2 Data Collection Measurements of height and weight were obtained for children born in the five years preceding the survey (i.e., born in January 2007 or later) in the subsample of households selected for the male survey as listed in the Household Questionnaire. Each team of interviewers carried a scale and measuring board. Measurements were made using lightweight SECA scales (with digital screens) designed and manufactured under the authority of the United Nations Children’s Fund (UNICEF). The measuring boards employed were specially made by Shorr Productions for use in survey settings. Children under age 2 or less than 85 cm (if the age was not known) were measured lying down on the board (recumbent length), and standing height was measured for all other children. Every effort was made to successfully carry out the measurements of the eligible women and children. A total of 4,285 children under age 5 (unweighted) in the PDHS subsample households were eligible for anthropometric measurements. Given the law and order situation of the country during the fieldwork, it was very challenging to carry the instruments to the field and conduct the measurements, especially in Balochistan. There was an overall 12 percent nonresponse rate for children with respect to height and weight measurements. In view of its security situation, the nonresponse in Balochistan for height and weight measurements was 20 percent, and only 41 percent of the measurements carried out in the province were valid. Given the low response rate in Balochistan, the National Institute of Population Studies (NIPS), as a means of assessing the provincial representativeness of the measurements, conducted a validation exercise after the completion of the fieldwork. However, fieldwork conditions had worsened over time, and it was not possible to complete the measurements in all of the proposed clusters. Only 58 percent of the proposed revisits could be completed, and most of these were concentrated in Quetta. This did not allow for a representative validation. Therefore, provincial results on anthropometry for children under age 5 in Balochistan are not presented separately in this report, although they are included in the national estimates. As Balochistan accounts for only 2 percent of the total representative sample of children, there is no substantial effect on overall national estimates. The following analysis focuses on the 3,466 children for whom valid and complete information on date of birth, height (in centimeters), and weight (in kilograms) is available. 11.1.3 Measures of Child Nutritional Status Height-for-age Table 11.1 presents the nutritional status of children under age 5 by various background characteristics. Nationally, 45 percent of children under age 5 are stunted, and 24 percent are severely stunted. Analysis by age groups shows that stunting increases with age, peaking at 53 percent among children age 24-35 months (Figure 11.1). Severe stunting shows a similar pattern, with the highest proportion of severe stunting in children age 24-35 months (31 percent). Stunting is higher in male children (48 percent) than in female children (42 percent). Stunting is higher among children with a preceding birth interval of less than 24 months (47 percent) than among children who were first births and children with a preceding birth interval of 24-47 months or 48 months or more. More than half of children whose perceived size at birth (as reported by the mother) was very small or small are stunted. Mothers’ nutritional status, as measured by their body mass index, also has an impact on the level of stunting in their children. Children whose mothers are thin (BMI less than 18.5) have the highest levels of stunting (55 percent), while those whose mothers are overweight or obese (BMI of 25 or above) have the lowest levels (35 percent). 166 • Nutrition of Children and Women Table 11.1 Nutritional status of children Percentage of children under age 5 classified as malnourished according to three anthropometric indices of nutritional status: height-for-age, weight-for-height, and weight-for-age, by background characteristics, Pakistan 2012-13 Height-for-age 1 Weight-for-height Weight-for-age Number of children Background characteristic Percentage below -3 SD Percentage below -2 SD2 Mean Z-score (SD) Percentage below -3 SD Percentage below -2 SD2 Percentage above +2 SD Mean Z-score (SD) Percentage below -3 SD Percentage below -2 SD2 Percentage above +2 SD Mean Z-score (SD) Age in months <6 12.7 25.5 -0.8 6.1 16.8 7.5 -0.7 7.1 28.7 2.7 -1.1 337 6-8 13.2 27.1 -1.1 8.3 20.0 4.1 -0.8 13.5 29.6 0.7 -1.3 132 9-11 13.2 34.4 -1.3 5.0 18.1 4.8 -0.7 14.2 33.9 0.1 -1.3 186 12-17 23.6 45.6 -1.8 6.8 18.4 3.1 -0.8 13.8 33.9 0.5 -1.5 403 18-23 26.9 48.6 -1.9 2.6 12.9 0.6 -0.6 8.5 29.6 0.0 -1.4 243 24-35 31.0 52.8 -2.1 1.8 7.3 3.0 -0.3 9.3 29.6 0.5 -1.4 740 36-47 26.3 49.3 -2.0 2.5 9.2 2.2 -0.4 10.9 30.0 0.1 -1.4 682 48-59 22.8 45.6 -1.9 1.1 4.8 3.0 -0.4 6.4 27.9 0.3 -1.4 744 Sex Male 26.2 47.9 -1.9 3.8 11.7 3.1 -0.6 10.7 32.8 0.4 -1.5 1,728 Female 21.4 41.7 -1.7 2.8 9.9 3.4 -0.5 8.7 27.1 0.7 -1.3 1,739 Birth interval in months3 First birth4 19.0 41.6 -1.7 3.5 10.0 2.6 -0.5 7.9 27.8 0.5 -1.3 675 <24 26.6 47.3 -1.9 3.0 10.8 3.5 -0.5 9.2 30.1 0.4 -1.4 1,154 24-47 23.8 44.1 -1.7 3.5 10.9 3.3 -0.5 10.4 30.3 0.5 -1.4 1,245 48+ 19.9 43.0 -1.6 1.6 11.2 3.5 -0.6 10.6 28.4 1.5 -1.4 312 Size at birth3,5 Very small 37.6 51.5 -2.1 3.0 17.2 5.3 -0.7 18.9 37.6 0.5 -1.7 99 Small 30.6 55.5 -2.2 4.1 12.8 3.2 -0.7 16.0 40.0 0.0 -1.8 510 Average or larger 21.7 42.5 -1.7 3.0 10.1 3.2 -0.5 8.0 27.4 0.7 -1.3 2,762 Mother’s interview status Interviewed 23.4 44.6 -1.8 3.1 10.7 3.3 -0.5 9.5 29.6 0.6 -1.4 3,385 Not interviewed but in household (49.2) (68.4) (-2.6) (11.6) (21.3) (3.7) (-0.6) (15.0) (53.9) (0.0) (-2.0) 41 Not interviewed and not in the household6 (25.3) (37.3) (-1.7) (5.7) (9.6) (0.6) (-0.7) (17.2) (40.2) (0.0) (-1.4) 40 Mother’s nutritional status7 Thin (BMI <18.5) 32.4 55.4 -2.2 5.2 16.6 0.8 -0.9 17.7 44.2 0.4 -1.9 450 Normal (BMI 18.5-24.9) 24.4 47.2 -1.8 3.5 11.8 2.5 -0.6 9.8 33.2 0.3 -1.5 1,444 Overweight/obese (BMI ≥25) 16.8 35.3 -1.4 2.3 6.4 4.8 -0.2 4.5 18.5 0.8 -1.0 859 Residence Urban 18.7 37.1 -1.5 2.9 9.9 3.8 -0.5 7.3 24.1 0.6 -1.2 1,053 Rural 26.0 48.2 -1.9 3.4 11.2 3.0 -0.5 10.7 32.5 0.5 -1.5 2,413 Region8 Punjab 17.6 39.8 -1.6 2.8 9.5 1.7 -0.5 7.0 26.1 0.4 -1.3 2,155 Urban 13.6 32.4 -1.3 2.2 8.6 1.5 -0.5 5.0 20.4 0.6 -1.1 647 Rural 19.3 42.9 -1.7 3.0 9.9 1.8 -0.5 7.8 28.5 0.4 -1.4 1,509 Sindh 35.1 56.7 -2.2 3.4 13.6 3.7 -0.7 16.7 42.3 0.3 -1.8 799 Urban 28.0 46.1 -1.9 4.3 12.8 7.2 -0.5 12.8 33.6 0.2 -1.5 305 Rural 39.5 63.3 -2.4 2.8 14.0 1.6 -0.7 19.1 47.7 0.4 -2.0 494 Khyber Pakhtunkhwa 25.1 41.9 -1.6 4.5 12.0 5.0 -0.4 9.8 26.1 1.1 -1.2 392 Urban 14.8 31.4 -1.3 1.4 7.2 2.6 -0.2 4.4 19.1 1.3 -0.9 70 Rural 27.3 44.2 -1.7 5.2 13.1 5.5 -0.4 11.0 27.6 1.0 -1.3 322 ICT Islamabad 8.4 22.2 -0.9 3.0 13.1 4.1 -0.6 2.8 14.4 1.3 -0.9 13 Gilgit Baltistan 21.9 35.9 -1.2 3.7 8.1 15.2 0.3 3.1 12.6 5.6 -0.5 25 Mother’s education9 No education 31.2 55.3 -2.1 4.1 13.5 2.5 -0.6 13.6 38.7 0.7 -1.7 1,875 Primary 22.5 45.8 -1.8 2.9 8.5 4.6 -0.4 5.2 27.5 0.0 -1.3 597 Middle 10.5 30.8 -1.3 1.3 8.0 2.0 -0.4 5.5 17.8 0.7 -1.0 287 Secondary 10.3 20.9 -1.1 2.9 7.3 3.8 -0.5 5.3 14.2 0.9 -0.9 370 Higher 8.8 20.7 -0.9 0.5 5.6 6.2 -0.2 2.3 9.9 0.4 -0.7 296 Wealth quintile Lowest 38.4 61.6 -2.5 4.5 17.3 2.9 -0.8 19.4 47.8 0.4 -2.0 762 Second 30.7 55.7 -2.0 3.2 10.5 3.3 -0.5 12.0 34.2 0.7 -1.6 707 Middle 19.6 40.6 -1.7 4.0 9.4 2.6 -0.5 6.0 26.1 0.5 -1.3 642 Fourth 16.6 37.8 -1.5 1.8 7.8 2.9 -0.4 5.9 22.4 0.7 -1.2 793 Highest 10.0 23.0 -1.1 2.9 8.2 4.9 -0.3 3.0 15.6 0.4 -0.8 562 Total 23.7 44.8 -1.8 3.3 10.8 3.2 -0.5 9.7 30.0 0.5 -1.4 3,466 Note: Table is based on children who stayed in the household on the night before the interview. Each of the indices is expressed in standard deviation units (SD) from the median of the WHO child growth standards adopted in 2006. The indices in this table are NOT comparable to those based on the previously used NCHS/CDC/WHO reference. Table is based on children with valid dates of birth (month and year) and valid measurement of both height and weight. Figures in parentheses are based on 25-49 unweighted cases. 1 Recumbent length is measured for children under age 2 and in the few cases when the age of the child is unknown and the child is less than 85 cm; standing height is measured for all other children. 2 Includes children who are below -3 standard deviations (SD) from the WHO child growth standards population median 3 Excludes children whose mothers were not interviewed 4 First-born twins (triplets, etc.) are counted as first births because they do not have a previous birth interval. 5 Excludes 13 children for whom information on size at birth was missing 6 Includes children whose mothers are deceased 7 Excludes children whose mothers were not weighed and measured, children whose mothers were not interviewed, and children whose mothers were pregnant or gave birth within the preceding 2 months. Mother’s nutritional status in terms of BMI (body mass index) is presented in Table 11.8. 8 Balochistan is not shown separately as only 41 percent of the measurements were valid, preventing provincial representation. However, it is included in the total national estimates. 9 For women who were not interviewed, information is taken from the Household Questionnaire. Excludes children whose mothers are not listed in the Household Questionnaire. Nutrition of Children and Women • 167 Children in rural areas are more likely to be stunted (48 percent) than those in urban areas (37 percent), and the pattern is similar for severe stunting (26 percent in rural areas and 19 percent in urban areas). Fifty-seven percent of children in Sindh are stunted followed by Khyber Pakhtunkhwa (42 percent) and Punjab (40 percent). The urban-rural differential is highest in Sindh, with more rural children than urban children being stunted (63 percent and 46 percent, respectively). Mother’s level of education generally has an inverse relationship with stunting; stunting ranges from a low of 21 percent among children whose mothers have a higher education to 55 percent among those whose mothers have no education. A similar inverse relationship is observed between household wealth and stunting. Children in the poorest households are almost three times as likely to be stunted (62 percent) as children in the wealthiest households (23 percent). Weight-for-height Table 11.1 also shows the nutritional status of children less than age 5 as measured by weight-for- height. Overall, 11 percent of children in Pakistan are wasted. Disaggregation of wasting by child’s age shows that wasting is highest (20 percent) among children age 6-8 months and lowest (5 percent) among children age 48-59 months. Male children are more likely to be wasted (12 percent) than female children (10 percent). As expected, the data show a linear relationship between wasting and perceived size of the baby at birth. Wasting is higher (17 percent) among children who were reported to be very small at birth than among those whose perceived size at birth was small, average, or large. Children born to mothers who are thin (BMI less than 18.5) are more than twice as likely to be wasted as those born to mothers who are overweight or obese (BMI of 25 or above). Children residing in urban areas are less likely to be wasted (10 percent) than children in rural areas (11 percent). Wasting is highest in Sindh (not including Balochistan in this comparison), with more rural than urban children in the province being wasted. In general, there is an inverse relationship between mother’s level of education and wasting, with the lowest proportion of wasting among children of mothers with a higher education (6 percent) and the highest proportion among children of mothers with no education (14 percent). There is a similar inverse relationship between household wealth and wasting. Weight-for-age As shown in Table 11.1, 30 percent of children under age 5 are underweight (weight-for-age below -2 SD), and 10 percent are severely underweight. The proportion of underweight children is highest (34 percent) among those age 9-11 months and those age 12-17 months. Male children are more likely to be underweight (33 percent) than female children (27 percent). Similar to wasting, underweight shows a strong relationship with perceived size of the baby at birth. Children reported to be very small or small at birth are much more likely to be underweight (38 percent and 40 percent, respectively) than children reported to be average or large at birth (27 percent). Children born to mothers who are thin (BMI less than 18.5) are more than twice as likely to be underweight (44 percent) as children born to mothers who are overweight or obese (19 percent). Rural children are more likely to be underweight (33 percent) than urban children (24 percent). Forty-two percent of children in Sindh are underweight, with rural children more likely to be underweight than urban children (48 percent and 34 percent, respectively). Only 13 percent of children in Gilgit Baltistan are underweight. 168 • Nutrition of Children and Women Figure 11.1 Nutritional status of children by age 0 10 20 30 40 50 60 70 0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 34 36 38 40 42 44 46 48 50 52 54 56 58 Percent Age (months) Stunted Wasted Underweight Note: Stunting reflects chronic malnutrition; wasting reflects acute malnutrition; underweight reflects chronic or acute malnutrition or a combination of both. Plotted values are smoothed by a five-month moving average. PDHS 2012-13 As with wasting and stunting, mother’s education is associated with underweight. Children born to mothers with no education (39 percent) are almost four times as likely to be underweight as children born to mothers with a higher education (10 percent). A similar inverse relationship is observed between household wealth and percentage of underweight children: children in the poorest households are three times more likely to be underweight (48 percent) than children in the wealthiest households (16 percent). 11.2 BREASTFEEDING AND COMPLEMENTARY FEEDING Feeding practices play a critical role in child development. Poor feeding practices can adversely impact the health and nutritional status of children, which in turn has direct consequences for their mental and physical development. Duration and intensity of breastfeeding also affect a mother’s period of postpartum infertility and, hence, the length of the birth interval and fertility levels. 11.2.1 Initiation of Breastfeeding Early initiation of breastfeeding is important for both the mother and the child. Early suckling stimulates the release of prolactin, which helps in the production of milk, and oxytocin, which is responsible for the ejection of milk. It also stimulates contraction of the uterus after childbirth and reduces postpartum blood loss. The first liquid to come from the breast, known as colostrum, is produced in the first few days after delivery. Colostrum is highly nutritious and contains antibodies that provide natural immunity to the infant. It is recommended that children be fed colostrum immediately after birth (within one hour) and that they continue to be exclusively breastfed even if the regular breast milk has not yet started to flow. Table 11.2 shows the percentage of last-born children born in the two years preceding the survey according to whether they were ever breastfed, when they began breastfeeding, and whether they were fed anything other than breast milk prior to the commencement of breastfeeding. Ninety-four percent of children were reported to have been breastfed at some time. Differences in the proportion of children ever breastfed by background characteristics are minor. One of the goals of the 2008 national IYCF strategy was to increase the percentage of newborns who are breastfed within one hour of birth to 60 percent Nutrition of Children and Women • 169 (Ministry of Health, 2008). However, only 18 percent of children were reported to have been breastfed within one hour of birth. A little over half (58 percent) of children were breastfed within one day of birth. Initiation of breastfeeding within one hour and within one day of birth varies by specific background characteristics. Table 11.2 Initial breastfeeding Among last-born children who were born in the two years preceding the survey, the percentage who were ever breastfed and the percentages who started breastfeeding within one hour and within one day of birth, and among last-born children born in the two years preceding the survey who were ever breastfed, the percentage who received a prelacteal feed, by background characteristics, Pakistan 2012-13 Among last-born children born in the past two years: Among last-born children born in the past two years who were ever breastfed: Background characteristic Percentage ever breastfed Percentage who started breastfeeding within 1 hour of birth Percentage who started breastfeeding within 1 day of birth1 Number of last-born children Percentage who received a prelacteal feed2 Number of last-born children ever breastfed Sex Male 94.5 17.3 56.8 2,168 76.0 2,048 Female 94.3 18.8 59.0 2,078 74.3 1,960 Assistance at delivery Health personnel3 93.5 16.9 58.7 2,444 74.6 2,286 Traditional birth attendant 95.5 17.9 55.2 1,545 77.4 1,476 Other 97.2 29.3 66.1 239 65.7 232 Place of delivery Health facility 93.6 16.3 58.2 2,295 74.6 2,148 At home 95.6 20.1 57.6 1,946 75.8 1,859 Residence Urban 94.6 17.9 59.6 1,256 74.7 1,188 Rural 94.3 18.1 57.1 2,990 75.3 2,820 Region Punjab 92.8 12.7 45.6 2,425 86.3 2,251 Sindh 96.6 19.7 73.6 961 54.3 929 Khyber Pakhtunkhwa 96.5 26.4 72.2 623 74.6 601 Balochistan 96.2 42.1 79.7 187 57.7 180 ICT Islamabad 92.2 19.9 74.7 16 55.5 15 Gilgit Baltistan 98.7 60.4 95.5 33 9.8 32 Mother’s education No education 94.7 18.8 57.8 2,304 73.1 2,182 Primary 94.1 12.3 55.0 741 81.3 698 Middle 91.2 17.6 51.2 346 77.8 316 Secondary 93.5 18.7 57.6 480 80.1 449 Higher 97.2 23.8 70.3 374 67.4 364 Wealth quintile Lowest 94.7 21.7 62.6 934 66.0 884 Second 95.6 17.1 57.7 914 75.0 873 Middle 93.3 17.2 53.1 858 80.8 801 Fourth 92.8 12.8 51.5 873 82.4 810 Highest 95.9 21.9 66.0 667 71.8 640 Total 94.4 18.0 57.9 4,246 75.2 4,008 Note: Table is based on last-born children born in the two years preceding the survey regardless of whether the children were living or dead at the time of the interview. Total includes cases for which assistance at delivery was missing and 4 cases for which no assistance was received and/or place of delivery was “other” or “missing.” 1 Includes children who started breastfeeding within 1 hour of birth 2 Children given something other than breast milk during the first 3 days of life 3 Doctor, nurse/midwife, or lady health visitor The prevalence of early initiation of breastfeeding (within one hour of birth) does not differ by area of residence (18 percent), but variations are evident by region. In Gilgit Baltistan, 60 percent of children were breastfed within one hour of birth, as compared with Punjab, where breastfeeding in the first hour was initiated in only 13 percent of children. There was only a slight difference in the initiation of breastfeeding within one hour of birth among children born in a health facility (16 percent) and those delivered at home (20 percent). Last-born children of mothers with a higher education were more likely to 170 • Nutrition of Children and Women be breastfed within an hour of birth and within the first day than other children. In general, women from the highest wealth quintile initiated breastfeeding sooner than women from other wealth quintiles. The practice of providing a prelacteal feed is discouraged because it limits the frequency of suckling by the infant and exposes the baby to the risk of infection. The data show that 75 percent of newborns were given something other than breast milk (prelacteal feed) during the first three days of life. There is no difference among children who are given a prelacteal feed by place of birth. Prelacteal feeding is more common among newborns whose mothers have a primary education (81 percent) than among newborns whose mothers have a higher education (67 percent). Prelacteal feeding is most common (82 percent) among children in the fourth wealth quintile and least prevalent among those in the lowest quintile (66 percent). The practice of giving a prelacteal feed has increased from 68 percent in 2006-07 to 75 percent in 2012-13.1 11.3 BREASTFEEDING STATUS BY AGE UNICEF and WHO recommend that children be exclusively breastfed (no other liquid, solid food, or plain water) during the first six months of life (WHO/UNICEF, 2002; Pan American Health Organization [PAHO]/WHO, 2003). Pakistan’s national nutrition strategy promotes exclusive breastfeeding through age 6 months and, thereafter, the introduction of semisolid or solid foods along with continued breast milk until the child is at least age 2 (Ministry of Health, 2004). Introducing breast milk substitutes to infants before age 6 months can displace exclusive breastfeeding. Substitutes such as formula, other kinds of milk, and porridge are often watered down and provide too few calories. Furthermore, possible contamination of these substitutes exposes infants to the risk of illness. After six months, a child requires adequate complementary foods for normal growth. Lack of appropriate complementary feeding may lead to undernutrition and frequent illness, which in turn may lead to death. However, even with complementary feeding, children should continue to be breastfed for two years or more. The 2012-13 PDHS used a 24-hour recall method to collect data on infant and young child feeding for all last-born children under age 2 living with their mothers. Table 11.3 shows the percentage of youngest children under age 2 by breastfeeding status and the percentage using a bottle with a nipple, according to age in months. Although the prevalence of breastfeeding in Pakistan is high, it is not universal and has not increased since 2006 (NIPS and Macro International Inc., 2008). The 2008 national IYCF strategy (Ministry of Health, 2008) set a target of increasing the percentage of infants less than age 6 months who are exclusively breastfed from 37 percent to 55 percent. However, Table 11.3 shows that the proportion of children under age 6 months who are exclusively breastfed has remained unchanged in the past six years (38 percent). As can be seen in Figure 11.2 and Table 11.3, supplementing breast milk with other liquids or foods starts at an early age in Pakistan. Contrary to the recommendation of exclusive breastfeeding, 17 percent of children under age 6 months were given plain water, 28 percent received other milk, and 10 percent were fed complementary foods in addition to breast milk. 1 The data for the 2006-07 PDHS were rerun to allow a comparison of this indicator. In 2006-07 this information was derived for children born in the five years preceding the survey, whereas in 2012-13 it was calculated for last-born children in the two years preceding the survey. Nutrition of Children and Women • 171 Table 11.3 Breastfeeding status by age Percent distribution of youngest children under age 2 who are living with their mother by breastfeeding status and the percentage currently breastfeeding, and the percentage of all children under age 2 using a bottle with a nipple, according to age in months, Pakistan 2012-13 Not breast- feeding Breastfeeding status Total Percentage currently breast- feeding Number of youngest children under age 2 living with their mother Percentage using a bottle with a nipple Number of all children under age 2 Age in months Exclusively breastfed Breast- feeding and consuming plain water only Breast- feeding and consuming non-milk liquids1 Breast- feeding and consuming other milk Breast- feeding and consuming comple- mentary foods 0-1 4.3 54.7 13.7 0.7 23.5 3.1 100.0 95.7 299 22.7 302 2-3 6.3 38.7 15.8 0.0 34.3 4.8 100.0 93.7 452 39.3 454 4-5 9.6 24.1 21.1 0.7 25.0 19.4 100.0 90.4 401 35.1 408 6-8 15.9 5.7 10.8 0.7 11.8 55.0 100.0 84.1 455 43.4 466 9-11 17.3 3.8 6.5 0.6 6.0 65.7 100.0 82.7 554 45.5 557 12-17 24.6 1.3 3.0 0.3 1.0 69.7 100.0 75.4 1,167 43.9 1,238 18-23 38.9 0.5 0.7 0.3 1.1 58.4 100.0 61.1 679 47.7 837 0-3 5.5 45.1 15.0 0.3 30.0 4.1 100.0 94.5 750 32.7 756 0-5 7.0 37.7 17.1 0.4 28.3 9.5 100.0 93.0 1,151 33.5 1,164 6-9 16.2 5.3 10.4 0.5 11.1 56.6 100.0 83.8 665 44.0 677 12-15 19.4 1.5 3.6 0.4 1.2 74.0 100.0 80.6 831 41.9 864 12-23 29.9 1.0 2.2 0.3 1.1 65.6 100.0 70.1 1,846 45.4 2,074 20-23 43.9 0.3 0.5 0.0 0.5 54.7 100.0 56.1 396 51.3 518 Note: Breastfeeding status refers to a “24-hour” period (yesterday and last night). Children who are classified as breastfeeding and consuming plain water only consumed no liquid or solid supplements. The categories of not breastfeeding, exclusively breastfed, breastfeeding and consuming plain water, non-milk liquids, other milk, and complementary foods (solids and semisolids) are hierarchical and mutually exclusive, and their percentages sum to 100 percent. Thus, children who receive breast milk and non-milk liquids and who do not receive other milk and who do not receive complementary foods are classified in the non-milk liquid category even though they may also get plain water. Any children who get complementary food are classified in that category as long as they are breastfeeding as well. 1 Non-milk liquids include juice, juice drinks, clear broth, or other liquids. Figure 11.2 Infant feeding practices by age 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% <2 2-3 4-5 6-7 8-9 10-11 12-13 14-15 16-17 18-19 20-21 22-23 Percentage Age group in months Not breastfeeding Complementary foods Other milk Non-milk liquids/juice Plain water only Exclusively breastfed PDHS 2012-13 Table 11.3 also shows complementary feeding practices among breastfeeding children of different ages. Three percent of children age 0-1 month, 5 percent of children age 2-3 months, and 19 percent of children age 4-5 months are given complementary foods in addition to breast milk. Although children age 172 • Nutrition of Children and Women 6-8 months should receive solid/semisolid foods, Table 11.3 shows that 45 percent of breastfeeding children in this age group did not receive complementary foods the day or night preceding the survey. The data show that 34 percent of infants less than age 6 months are fed using a bottle with a nipple, which is 7 percentage points higher than in 2006-07. Figure 11.3 shows the 2012-13 PDHS results for key IYCF breastfeeding practices among children under age 2 who are living with their mothers. Although 38 percent of children under age 6 months are exclusively breastfed, only 24 percent of those age 4-5 months are exclusively breastfed. Four in five children (81 percent) continue breastfeeding at age 1, and 56 percent continue to breastfeed until age 2. Sixty-six percent of children start receiving complementary foods at an appropriate age. Fifty-six percent of children age 0-23 months are breastfed appropriately for their age (i.e., exclusive breastfeeding for children age 0-5 months and continued breastfeeding along with complementary foods for children age 6-23 months). Fifty-five percent of children are predominantly breastfed (breast milk and only plain water or non-milk liquids such as juice, clear broth, and other liquids); 42 percent of children under age 2 are bottle fed. Figure 11.3 IYCF indicators on breastfeeding status 38 24 81 66 56 56 55 42 Exclusive breastfeeding under age 6 months Exclusive breastfeeding at age 4-5 months Continued breastfeeding at 1 year Introduction of solid, semisolid, or soft foods (6-8 months) Continued breastfeeding at 2 years Age-appropriate breastfeeding (0-23 months) Predominant breastfeeding (0-5 months) Bottle feeding (0-23 months) Percentage of children PDHS 2012-13 11.4 DURATION OF BREASTFEEDING Table 11.4 provides information on the median duration of any breastfeeding, exclusive breastfeeding, and predominant breastfeeding among children born in the three years preceding the survey by selected background characteristics. The median duration of any breastfeeding in Pakistan is 19.0 months, similar to the duration reported in the 2006-07 PDHS (18.9 months). Median duration of breastfeeding is slightly higher for male children (20.3 months), children residing in rural areas (19.6 months), children of mothers with no education (20.6 months), and children in the lowest wealth quintile (20.8 months). The mean duration of breastfeeding for all children is 18.3 months. Table 11.4 shows that the median duration of exclusive breastfeeding is only 0.7 months. Median duration varies between less than a month (0.7) for male children and 1 month for female children and is less than a month among infants in both urban and rural areas (0.9 and 0.7 months, respectively). The median duration of predominant breastfeeding has remained unchanged in Pakistan over the past six years at 2.7 months. Nutrition of Children and Women • 173 Table 11.4 Median duration of breastfeeding Median duration of any breastfeeding, exclusive breastfeeding, and predominant breastfeeding among children born in the three years preceding the survey, by background characteristics, Pakistan 2012-13 Background characteristic Median duration (months) of breastfeeding among children born in the past three years1 Any breastfeeding Exclusive breastfeeding Predominant breastfeeding2 Sex Male 20.3 0.7 2.7 Female 18.4 1.0 2.6 Residence Urban 18.2 0.9 2.3 Rural 19.6 0.7 2.8 Region Punjab 17.5 (0.7) 1.5 Sindh 20.6 1.3 3.9 Khyber Pakhtunkhwa 21.0 3.3 4.9 Balochistan 19.6 * 1.6 ICT Islamabad 14.5 (1.9) * Gilgit Baltistan (20.1) (3.5) 4.3 Mother’s education No education 20.6 0.7 3.4 Primary 17.4 1.0 2.4 Middle (17.5) * 2.4 Secondary 17.7 1.3 1.4 Higher 18.1 * * Wealth quintile Lowest 20.8 (0.7) 4.4 Second 19.9 (0.7) 2.6 Middle 19.1 1.2 2.9 Fourth 19.2 (0.7) 1.4 Highest 17.2 1.0 1.3 Total 19.0 0.7 2.7 Mean for all children 18.3 3.1 4.7 Note: Median and mean durations are based on the distributions at the time of the survey of the proportion of births by months since birth. Includes children living and deceased at the time of the survey. 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 It is assumed that non-last-born children and last-born children not currently living with the mother are not currently breastfeeding. 2 Either exclusively breastfed or received breast milk and plain water and/or non- milk liquids only 11.5 TYPES OF COMPLEMENTARY FOODS It is recommended that complementary foods (solid or semisolid foods fed to infants in addition to breast milk) be started at age 6 months. The reason is that, at this age, breast milk alone is no longer sufficient to maintain the child’s recommended daily nutritional requirements and enhance growth. Children are fed small quantities of solid and semisolid foods while continuing to breastfeed up to age 2 or beyond. The amount of food is increased gradually from 6 to 23 months, the period of transition to eating the regular family diet. This period is characterized by an increase in the prevalence of malnutrition because of poor feeding practices and infections. Table 11.5 shows the percentage of youngest children under age 2 who are living with their mother by types of foods consumed in the day or night preceding the interview, according to breastfeeding status and age. The data show that, contrary to WHO recommendations, the practice of feeding children with solid or semisolid foods starts early in life. Five percent of breastfeeding children have received some kind of solid or semisolid food by age 2-3 months, and this proportion increases to 22 percent by age 4-5 months. 174 • Nutrition of Children and Women Overall, 85 percent of breastfed children age 6-23 months received solid or semisolid complementary foods in addition to breast milk. These complementary foods included fortified baby foods (16 percent), foods made from grains (70 percent), fruits and vegetables rich in vitamin A (19 percent), other fruits and vegetables (32 percent), and food made from roots and tubers (41 percent). Children were also fed protein-rich foods such as legumes and nuts (6 percent); meat, fish, and poultry (16 percent); and eggs (24 percent). Twelve percent of children age 6-23 months were given cheese, yogurt, and other milk products. In addition, 41 percent of children in this age group were given other milk, and 19 percent were given other liquids. Use of infant formula was minimal (4 percent). Table 11.5 Foods and liquids consumed by children in the day or night preceding the interview Percentage of youngest children under age 2 who are living with the mother by type of foods consumed in the day or night preceding the interview, according to breastfeeding status and age, Pakistan 2012-13 Liquids Solid or semisolid foods Any solid or semi- solid food Number of children Age in months Infant formula Other milk1 Other liquids2 Fortified baby foods Food made from grains3 Fruits and vege- tables rich in vitamin A4 Other fruits and vege- tables Food made from roots and tubers Food made from legumes and nuts Meat, fish, poultry Eggs Cheese, yogurt, other milk products BREASTFEEDING CHILDREN 0-1 10.3 16.8 3.8 0.5 2.4 1.2 0.4 2.3 0.1 0.3 0.0 0.4 3.2 286 2-3 8.4 31.3 2.3 1.8 1.8 0.3 0.4 1.0 0.2 0.0 0.9 1.2 5.1 423 4-5 3.7 32.6 3.3 6.8 6.9 0.9 3.6 2.5 0.2 0.1 6.1 2.7 21.5 362 6-8 5.6 35.3 8.6 22.4 45.8 9.7 17.5 25.5 1.4 8.2 17.0 10.0 65.5 383 9-11 5.8 36.4 18.2 18.9 58.3 11.4 25.8 28.8 1.5 8.8 17.1 11.4 79.5 458 12-17 2.2 44.3 21.7 13.7 78.3 22.5 36.0 47.2 7.2 19.4 27.2 12.7 92.5 880 18-23 2.2 46.5 24.8 9.4 86.5 27.8 41.1 55.1 10.5 25.1 30.7 14.1 95.6 414 6-23 3.6 41.4 19.2 15.5 69.7 18.8 31.5 40.9 5.6 16.2 23.9 12.2 85.4 2,135 Total 4.8 36.9 13.8 11.4 47.7 12.8 21.5 27.8 3.8 10.8 16.7 8.6 60.3 3,206 NONBREASTFEEDING CHILDREN 0-5 42.0 60.5 3.7 9.9 8.1 0.5 7.4 0.1 0.0 3.7 2.5 2.5 22.1 81 6-8 21.4 67.1 6.7 25.2 42.7 4.7 25.2 19.3 1.6 8.2 10.9 15.5 70.8 72 9-11 24.1 73.8 15.0 20.9 75.9 21.0 36.0 32.9 3.5 14.0 27.5 15.9 89.3 96 12-17 10.1 75.7 21.4 15.7 83.6 14.7 41.2 42.7 6.0 21.7 26.8 15.3 95.2 287 18-23 9.4 70.7 28.6 8.1 87.2 31.3 45.2 53.7 11.2 31.5 33.7 21.5 96.8 264 6-23 12.9 72.7 21.7 14.6 79.8 20.6 40.4 43.1 7.1 22.9 27.8 17.7 92.5 720 Total 16.1 71.5 19.9 14.1 72.7 18.6 37.1 38.8 6.4 20.9 25.3 16.1 85.5 800 Note: Breastfeeding status and food consumed refer to a “24-hour” period (yesterday and last night). 1 Other milk includes fresh, tinned, and powdered cow or other animal milk. 2 Does not include plain water 3 Includes fortified baby food 4 Includes pumpkin, squash, carrots, red sweet potatoes, dark green leafy vegetables, mangoes, papayas, and other locally grown fruits and vegetables that are rich in vitamin A More than 90 percent of nonbreastfeeding children age 6-23 months received solid or semisolid foods. With the exception of fortified baby foods, consumption of different types of food was higher among nonbreastfeeding children than among breastfeeding children. 11.6 INFANT AND YOUNG CHILD FEEDING (IYCF) PRACTICES Appropriate IYCF practices include timely initiation of feeding solid or semisolid foods at age 6 months and increasing the amount and variety of foods and frequency of feeding as the child gets older while maintaining frequent breastfeeding (WHO, 2008). Guidelines have been established for IYCF practices among children age 0-23 months (PAHO/WHO, 2003; WHO, 2005; WHO, 2008). Although breastfeeding is recommended for infants up to age 2, some infants have stopped breastfeeding before reaching age 2 because, for example, their mother is HIV positive or has died; guidelines on feeding this group of children have also been developed (WHO, 2005). Appropriate nutrition includes feeding children age 6-23 months a variety of foods a desired number of times to ensure that their nutrient and caloric requirements are met. Minimum dietary diversity Nutrition of Children and Women • 175 refers to feeding the child food from at least four food groups, a cutoff selected because of its association with better-quality diets for both breastfed and nonbreastfed children. Studies have shown that plant-based complementary foods by themselves are insufficient to meet the needs for certain micronutrients (WHO and UNICEF, 1998). Therefore, it is recommended that meat, poultry, fish, and eggs be eaten daily or as often as possible. Fruits and vegetables rich in vitamin A should be consumed daily to achieve the proven health benefits associated with vitamin A (Allen and Gillespie, 2001). Children’s diets should include an adequate fat content, because fat provides essential fatty acids, facilitates absorption of fat-soluble vitamins (such as vitamin A), and enhances dietary energy density. It is highly likely that children consuming foods from at least four groups are consuming at least one animal source of food and at least one fruit or vegetable in addition to a staple food (grains, roots, or tubers) (WHO, 2008). These four food groups should come from the following seven categories: grains, roots, and tubers; legumes and nuts; dairy products (milk, yogurt, cheese); flesh foods (meat, fish, poultry, liver/organ meat); eggs; vitamin A-rich fruits and vegetables; and other fruits and vegetables. The minimum dietary diversity may be reported separately for breastfed and nonbreastfed children. However, diversity scores for breastfed and nonbreastfed children should not be directly compared, because breast milk is not counted in any of the above stated food groups. The recommended numbers of feedings are as follows: • Breastfed children age 6-23 months should receive animal-source foods and vitamin-A rich fruits and vegetables daily (PAHO/WHO, 2003). Breastfed infants age 6-8 months should be fed meals of complementary foods two to three times per day, with one to two snacks as desired; breastfed children age 9-23 months should be fed meals three to four times per day, with one to two snacks. • Nonbreastfed children age 6-23 months should receive milk products at least twice a day to ensure that their calcium needs are met. In addition, they need animal-source foods and vitamin A-rich fruits and vegetables. Therefore, four food groups are considered the minimum acceptable number for nonbreastfed children. Nonbreastfed children should be fed meals four to five times per day, with one to two snacks as desired (WHO, 2005). Meal frequency is considered a proxy for energy intake from foods other than breast milk; therefore, the feeding frequency indicator for nonbreastfed children includes both milk feeds and solid/semisolid feeds (WHO, 2008). These minimum feeding frequencies are based on the energy needs estimated from age-specific total daily energy requirements. Infants with low breast milk intake would need to be fed more frequently. However, overly frequent feeding may lead to displacement of breast milk (PAHO/WHO, 2003). Table 11.6 and Figure 11.4 show IYCF practices according to breastfeeding status. The IYCF recommendations for children age 6-23 months take into account feeding practices that meet minimum standards with respect to: • Food diversity (the number of food groups consumed) • Feeding frequency (the number of times the child is fed) • Consumption of breast milk or other types of milk or milk products 176 • Nutrition of Children and Women Table 11.6 shows that 20 percent of breastfed children age 6-23 months were fed foods from four or more food groups in the 24 hours preceding the survey. A little over one fourth (27 percent) of breastfed children residing in urban areas were given foods from four or more food groups, as compared with 17 percent of breastfed children living in rural areas. Children living in ICT Islamabad (38 percent), children of mothers with a higher education (43 percent), and children from the wealthiest households (36 percent) were more likely than their counterparts to receive foods from four or more food groups along with breast milk. More than half of breastfed children (55 percent) were fed the minimum number of times in the preceding day and night of the survey. Only 16 percent of breastfed children were fed in accord with the recommended guidelines, that is, given foods from four or more groups and fed the minimum number of times each day. The proportion of breastfeeding children age 6-23 months fed the recommended variety of foods at least three times daily increased with mother’s level of education and wealth. Table 11.6 Infant and young child feeding (IYCF) practices Percentage of youngest children age 6-23 months living with their mother who are fed according to three IYCF feeding practices based on breastfeeding status, number of food groups, and times they are fed during the day or night preceding the survey, by background characteristics, Pakistan 2012-13 Among breastfed children 6-23 months, percentage fed: Number of breast- fed children 6-23 months Among non-breastfed children 6-23 months, percentage fed: Number of non- breastfed children 6-23 months Among all children 6-23 months, percentage fed: Number of all children 6-23 months Background characteristic 4+ food groups1 Minimum meal frequency2 Both 4+ food groups and minimum meal frequency Milk or milk products3 4+ food groups1 Minimum meal frequency4 With 3 IYCF practices5 Breast milk, milk, or milk products6 4+ food groups1 Minimum meal frequency7 With 3 IYCF practices Age in months 6-8 12.8 56.1 12.5 383 73.1 10.8 76.4 1.9 72 95.7 12.5 59.4 10.8 455 9-11 9.3 39.0 7.6 458 84.4 22.6 89.6 10.8 96 97.3 11.6 47.8 8.2 554 12-17 23.2 57.8 17.8 880 76.1 25.7 84.9 7.8 287 94.1 23.8 64.4 15.4 1,167 18-23 30.4 67.3 26.8 414 70.0 41.4 84.7 14.0 264 88.3 34.7 74.1 21.8 679 Sex Male 20.7 54.5 16.4 1,106 73.4 35.4 84.0 9.9 349 93.6 24.2 61.5 14.9 1,455 Female 18.8 56.2 16.4 1,029 75.8 23.9 85.2 9.9 371 93.6 20.1 63.9 14.7 1,400 Residence Urban 26.5 61.0 23.3 587 85.1 38.6 90.6 13.6 285 95.1 30.5 70.6 20.2 872 Rural 17.2 53.2 13.8 1,548 67.9 23.6 80.7 7.5 435 92.9 18.6 59.2 12.4 1,983 Region Punjab 19.3 48.8 15.4 1,143 83.7 29.3 87.2 11.2 467 95.3 22.2 59.9 14.2 1,609 Urban 26.9 54.5 23.2 325 89.1 40.5 92.8 13.8 193 95.9 31.9 68.8 19.7 518 Rural 16.3 46.6 12.3 818 79.9 21.4 83.2 9.4 273 95.0 17.6 55.7 11.5 1,091 Sindh 23.7 63.8 20.6 494 70.8 29.1 84.0 9.4 118 94.4 24.8 67.7 18.4 612 Urban 26.2 69.7 24.2 193 82.3 33.5 89.3 12.1 60 95.8 27.9 74.3 21.4 253 Rural 22.2 60.1 18.2 301 59.1 24.7 78.6 6.7 59 93.3 22.6 63.1 16.3 359 Khyber Pakhtunkhwa 17.9 61.5 15.2 371 40.3 35.5 77.6 6.7 95 87.8 21.5 64.8 13.5 467 Urban 29.2 69.2 23.1 48 66.6 41.3 79.3 19.3 22 89.4 33.0 72.4 21.9 70 Rural 16.2 60.3 14.1 324 32.4 33.8 77.1 2.9 73 87.5 19.4 63.4 12.0 397 Balochistan 8.8 61.3 8.8 101 63.4 10.1 73.3 1.0 31 91.4 9.1 64.1 7.0 131 Urban 13.6 57.4 13.6 14 60.7 12.1 79.3 4.6 7 87.8 13.1 64.2 10.8 21 Rural 8.1 62.0 8.1 86 64.1 9.5 71.7 0.0 24 92.1 8.4 64.1 6.3 110 ICT Islamabad 37.5 76.4 35.0 8 83.9 50.6 88.9 14.2 5 93.7 42.6 81.3 26.9 12 Gilgit Baltistan 26.8 61.7 25.3 19 29.7 46.3 55.3 14.5 4 86.8 30.5 60.5 23.2 23 Mother’s education No education 14.7 54.0 12.2 1,223 62.3 20.1 76.2 5.3 334 91.9 15.9 58.7 10.7 1,557 Primary 19.5 51.9 16.0 362 79.0 28.9 91.3 9.6 123 94.7 21.9 61.9 14.4 485 Middle 20.8 53.5 18.1 143 91.5 36.5 94.5 15.1 77 97.0 26.3 67.8 17.1 221 Secondary 28.5 59.1 22.8 233 86.0 48.4 92.6 15.4 90 96.1 34.0 68.4 20.7 323 Higher 42.8 68.1 36.8 174 87.7 39.9 89.8 17.1 95 95.6 41.8 75.8 29.8 269 Wealth quintile Lowest 11.6 54.6 9.8 502 50.7 13.5 69.0 2.8 101 91.8 11.9 57.0 8.6 603 Second 15.7 49.5 11.5 499 71.3 17.8 83.5 3.3 138 93.8 16.2 56.8 9.7 637 Middle 18.1 53.2 14.5 433 73.8 30.2 82.7 11.4 139 93.6 21.0 60.4 13.7 571 Fourth 25.1 55.8 21.5 417 78.6 33.9 89.4 13.0 176 93.7 27.7 65.8 19.0 593 Highest 35.8 69.1 32.3 284 88.4 43.7 91.4 15.2 167 95.7 38.7 77.4 26.0 451 Total 19.7 55.3 16.4 2,135 74.7 29.5 84.6 9.9 720 93.6 22.2 62.7 14.8 2,855 1 Food groups: a. infant formula, milk other than breast milk, cheese or yogurt or other milk products; b. foods made from grains, roots, and tubers, including porridge and fortified baby food from grains; c. vitamin A-rich fruits and vegetables (and red palm oil); d. other fruits and vegetables; e. eggs; f. meat, poultry, fish, and shellfish (and organ meats); g. legumes and nuts. 2 For breastfed children, minimum meal frequency is receiving solid or semisolid food at least twice a day for infants age 6-8 months and at least 3 times a day for children age 9-23 months. 3 Includes 2 or more feedings of commercial infant formula; fresh, tinned, and powdered animal milk; and yogurt 4 For nonbreastfed children age 6-23 months, minimum meal frequency is receiving solid or semisolid food or milk feeds at least 4 times a day. 5 Nonbreastfed children age 6-23 months are considered to be fed with a minimum standard of 3 infant and young child feeding practices if they receive other milk or milk products at least twice a day, receive the minimum meal frequency, and receive solid or semisolid foods from at least 4 food groups not including the milk or milk products food group. 6 Breastfeeding, or not breastfeeding and receiving 2 or more feedings of commercial infant formula; fresh, tinned, and powdered animal milk; and yogurt 7 Children are fed the minimum recommended number of times per day according to their age and breastfeeding status as described in notes 2 and 4. Nutrition of Children and Women • 177 Overall, Table 11.6 shows that most breastfed and nonbreastfed children age 6-23 months are given breast milk or other milk products (94 percent). Only one in five children are given the appropriately diverse diet, and 63 percent of children are fed the recommended number of times with solid or semisolid foods. Only 15 percent of children are fed in compliance with the IYCF recommendations of consuming breast milk or other milk products, having the minimum dietary diversity, and having the minimum meal frequency. The targets identified in the 2008 national IYCF strategy do not seem to be nearing achievement. The proportion of children age 6-23 months who are fed according to all three IYCF recommendations does not vary between boys and girls, but there are differences across other background characteristics. Children living in urban areas (20 percent) are more likely to be fed according to the recommendations than their rural counterparts (12 percent). Children living in Balochistan are least likely to be fed according to all three IYCF practices (7 percent); in other regions, the proportion ranges from 14 percent (Khyber Pakhtunkhwa and Punjab) to 27 percent (ICT Islamabad). There is a positive relationship between infant and child feeding practices and mother’s education and wealth. Figure 11.4 IYCF indicators on minimum acceptable diet 20 55 16 30 85 10 22 63 15 IYCF 5: Minimum dietary diversity IYCF 6: Minimum meal frequency IYCF 7: Minimum acceptable diet Percent Among breastfed children Among nonbreastfed children Among all children 6-23 months PDHS 2012-13 11.7 MICRONUTRIENT INTAKE AMONG CHILDREN Micronutrient deficiency is a major contributor to childhood morbidity and mortality. Children can receive micronutrients from foods, food fortification, and direct supplementation. The 2012-13 PDHS collected information on consumption of foods rich in vitamin A and iron and the status of children receiving vitamin A capsules, iron supplements, and deworming medication during national campaigns. 178 • Nutrition of Children and Women Table 11.7 Micronutrient intake among children Among youngest children age 6-23 months who are living with their mother, the percentages who consumed vitamin A-rich and iron-rich foods in the day or night preceding the survey, and among all children age 6-59 months, the percentages who were given vitamin A supplements in the six months preceding the survey, who were given iron supplements in the past seven days, and who were given deworming medication in the six months preceding the survey, by background characteristics, Pakistan 2012-13 Among youngest children age 6-23 months living with the mother: Number of children Among all children age 6-59 months: Number of children Background characteristic Percentage who consumed foods rich in vitamin A in last 24 hours1 Percentage who consumed foods rich in iron in last 24 hours2 Percentage given vitamin A supplements in last 6 months Percentage given iron supplements in last 7 days Percentage given deworming medication in last 6 months3 Age in months 6-8 25.3 21.5 455 67.5 7.8 7.5 466 9-11 32.0 23.5 554 65.5 9.3 10.9 557 12-17 50.0 38.6 1,167 71.5 7.0 14.8 1,238 18-23 58.1 45.4 679 74.4 8.7 19.0 837 24-35 na na na 73.1 7.0 30.8 2,277 36-47 na na na 72.3 7.6 37.3 2,286 48-59 na na na 72.8 7.6 36.1 2,216 Sex Male 45.6 35.2 1,455 72.1 8.0 27.6 5,026 Female 43.3 33.9 1,400 72.0 7.2 29.0 4,851 Breastfeeding status Breastfeeding 42.7 33.0 2,135 70.1 7.9 15.0 2,571 Not breastfeeding 49.8 39.1 719 72.8 7.5 33.0 7,266 Missing * * 1 (60.7) (0.0) (22.7) 39 Mother’s age at birth 15-19 39.2 25.7 104 65.3 7.2 13.1 163 20-29 43.7 34.6 1,646 72.8 7.7 27.1 5,072 30-39 45.1 35.4 986 71.0 7.6 30.2 4,020 40-49 54.4 35.1 119 74.9 6.5 29.7 622 Residence Urban 52.5 46.0 872 68.0 9.1 21.4 2,943 Rural 41.0 29.5 1,983 73.8 7.0 31.2 6,933 Region Punjab 41.4 36.0 1,609 77.9 8.8 36.8 5,623 Urban 51.3 45.4 518 76.3 10.0 25.1 1,692 Rural 36.7 31.5 1,091 78.6 8.3 41.8 3,931 Sindh 47.6 35.5 612 59.9 3.9 12.2 2,219 Urban 54.4 47.6 253 52.1 5.3 14.1 902 Rural 42.9 26.9 359 65.2 2.9 10.8 1,318 Khyber Pakhtunkhwa 54.9 32.0 467 81.2 11.0 27.3 1,423 Urban 58.2 49.0 70 81.5 19.7 28.5 225 Rural 54.3 29.0 397 81.2 9.3 27.0 1,197 Balochistan 26.4 17.6 131 45.3 1.7 8.4 496 Urban 34.8 26.1 21 52.1 4.5 10.4 90 Rural 24.7 16.0 110 43.8 1.1 8.0 407 ICT Islamabad 63.5 58.8 12 50.6 8.5 20.0 42 Gilgit Baltistan 55.3 45.3 23 8.8 2.0 18.1 73 Mother’s education No education 38.2 25.3 1,557 70.4 5.8 25.6 5,626 Primary 40.9 33.2 485 75.9 7.4 32.5 1,646 Middle 44.7 39.6 221 76.5 8.1 31.8 746 Secondary 62.8 56.9 323 72.6 11.3 35.2 1,018 Higher 64.9 59.8 269 70.9 15.1 25.8 841 Wealth quintile Lowest 32.6 19.5 603 62.9 3.9 17.6 2,316 Second 39.5 25.3 637 76.7 4.7 29.6 2,070 Middle 44.6 34.9 571 77.3 9.7 37.5 1,935 Fourth 49.5 43.0 593 74.6 10.2 33.1 1,951 Highest 60.6 56.2 451 69.7 11.1 24.9 1,605 Total 44.5 34.6 2,855 72.1 7.6 28.3 9,877 Note: Information on vitamin A is based on both mother’s recall and the immunization card (where available). Information on iron supplements and deworming medication is based on the mother’s recall. 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. na = Not applicable 1 Includes meat (and organ meat), fish, poultry, eggs, pumpkin, red or yellow yams or squash, carrots, red sweet potatoes, dark green leafy vegetables, mango, papaya, and other locally grown fruits and vegetables that are rich in vitamin A 2 Includes meat (and organ meat), fish, poultry, and eggs 3 Deworming for intestinal parasites is commonly done for helminthes and for schistosomiasis. Nutrition of Children and Women • 179 Vitamin A is an essential micronutrient for the immune system that plays an important role in maintaining the epithelial tissue in the body. Severe vitamin A deficiency (VAD) can cause eye damage. VAD can also increase the severity of infections, such as measles and diarrheal diseases in children, and slow recovery from illness. Vitamin A is found in breast milk, other milk, liver, eggs, fish, butter, mangoes, papayas, carrots, pumpkins, and dark green leafy vegetables. The liver can store an adequate amount of the vitamin for four to six months. Table 11.7 shows that 45 percent of children age 6-23 months consumed foods rich in vitamin A the day or night preceding the survey. The proportion of children consuming vitamin A-rich foods increases with age. There are only slight differences in consumption by sex. Nonbreastfeeding children (50 percent) are more likely to consume foods rich in vitamin A than breastfeeding children (43 percent). Urban children are more likely to consume vitamin A-rich foods (53 percent) than children in rural areas (41 percent). Children residing in ICT Islamabad are most likely to consume vitamin A-rich foods (64 percent) and children in Balochistan (26 percent) are least likely. Mother’s education has a positive relationship with consumption of vitamin A-rich foods: 38 percent of children whose mothers have no education consume vitamin A-rich foods, as compared with 65 percent of children whose mothers have a higher education. Children born to families in the highest wealth quintile are almost twice as likely as children born to families in the lowest wealth quintile to consume vitamin A-rich foods (61 percent versus 33 percent). Iron is essential for cognitive development, and low iron intake can contribute to anemia. Iron requirements are greatest at age 6-23 months, when growth is extremely rapid. The results of the 2012-13 PDHS (Table 11.7) show that 35 percent of children age 6-23 months consumed foods rich in iron in the 24 hours prior to the survey. Consumption of iron-rich foods is highest among children age 18-23 months, children in urban areas, children in ICT Islamabad, and children in the highest wealth quintile. Children whose mothers have a higher education (60 percent) are more likely to consume iron-rich foods than those whose mothers have no education (25 percent). Periodic dosing (usually every six months) of vitamin A supplements is one method of ensuring that children at risk do not develop VAD. In Pakistan, campaigns are in place for semiannual mass supplementation with vitamin A capsules. The 2012-13 PDHS collected data on vitamin A supplements for children under age 5. Table 11.7 shows that 72 percent of children age 6-59 months were given vitamin A supplements in the six months before the survey. Children age 18-23 months (74 percent), those living in rural areas (74 percent), and those born to older mothers are more likely to receive vitamin A supplementation. There are substantial differences in the proportion of children receiving vitamin A supplements by geographical area, with the coverage in Khyber Pakhtunkhwa being nine times higher (81 percent) than that in Gilgit Baltistan (9 percent). Mother’s education and wealth do not have any marked impact on use of vitamin A supplementation. As a means of assessing iron supplementation coverage, mothers were asked if their children under age 5 had received an iron tablet in the seven days prior to the survey. Table 11.7 shows that, overall, only 8 percent of children age 6-59 months received iron supplementation. Certain types of intestinal parasites can cause anemia. Periodic deworming for organisms such as helminthes can improve children’s micronutrient status. Table 11.7 shows that 28 percent of children age 6-59 months received deworming medication in the six months before the survey. Children in rural areas were more likely than children in urban areas to receive deworming medication. Likelihood of receiving deworming medication increased with child’s age, mother’s education, and mother’s wealth. More children in Punjab (37 percent) than in Balochistan (8 percent) received deworming medication. 180 • Nutrition of Children and Women 11.8 NUTRITIONAL STATUS OF WOMEN The nutritional status of women was assessed with two anthropometric indices: height and body mass index. To derive these indices, the 2012-13 PDHS took height and weight measurements among women age 15-49 in every third household that was selected for a male interview. Women who were pregnant and women who had given birth in the two months preceding the survey were excluded from the analysis. Short stature is associated with poor socioeconomic conditions and inadequate nutrition during childhood and adolescence. In a woman, short stature is a risk factor for poor birth outcomes and obstetric complications. For example, short stature is associated with small pelvic size, which increases the likelihood of difficulty during delivery and the risk of bearing low birth weight babies. A woman is considered to be at risk if her height is below 145 cm. According to Table 11.8, 5 percent of women are shorter than 145 cm. Women in rural areas are slightly more likely to be below 145 cm than women in urban areas. Women in Sindh are most likely to be shorter than 145 cm (7 percent), while women in ICT Islamabad and Gilgit Baltistan are least likely (3 percent each). Likelihood of short stature decreases with increasing education and wealth quintile. BMI (expressed as the ratio of weight in kilograms to the square of height in meters [kg/m2]) is used to measure thinness or obesity. A BMI below 18.5 kg/m2 indicates thinness or acute undernutrition, and a BMI of 25.0 kg/m2 or above indicates overweight or obesity. A BMI below 16 kg/m2 indicates severe undernutrition and is associated with increased mortality. Low pre-pregnancy BMI, as with short stature, is associated with poor birth outcomes and obstetric complications. Table 11.8 Nutritional status of women Among women age 15-49, the percentage with height under 145 cm, mean body mass index (BMI), and the percentage with specific BMI levels, by background characteristics, Pakistan 2012-13 Background characteristic Height Body mass index1 Mean BMI Normal Thin Overweight/obese Number of women Percentage below 145 cm Number of women 18.5-24.9 (total normal) <18.5 (total thin) 17.0-18.4 (mildly thin) <17 (moderate- ly and severely thin) ≥25.0 (total over- weight or obese) 25.0-29.9 (over- weight) ≥30.0 (obese) Age 15-19 6.1 222 20.7 73.0 20.3 15.5 4.8 6.7 6.6 0.2 163 20-29 5.3 1,729 22.7 52.4 20.3 13.8 6.4 27.3 19.3 8.1 1,326 30-39 4.0 1,605 25.0 43.0 10.3 6.7 3.6 46.7 29.0 17.7 1,451 40-49 4.6 1,242 25.8 38.8 10.4 6.7 3.7 50.8 29.7 21.1 1,231 Residence Urban 3.7 1,596 26.1 38.2 7.4 4.5 2.9 54.3 31.8 22.5 1,403 Rural 5.3 3,203 23.4 49.9 17.1 11.7 5.4 33.0 21.9 11.1 2,767 Region Punjab 4.0 2,801 24.6 43.6 13.9 9.2 4.6 42.5 25.0 17.5 2,455 Sindh 7.0 1,106 22.9 51.0 19.6 12.8 6.8 29.4 20.4 9.0 948 Khyber Pakhtunkhwa 4.0 657 25.4 43.4 6.3 5.0 1.3 50.3 33.9 16.4 572 Balochistan 5.9 181 24.0 55.9 9.0 6.5 2.5 35.1 28.1 6.9 150 ICT Islamabad 2.8 20 26.7 35.4 5.5 2.7 2.8 59.1 32.4 26.7 17 Gilgit Baltistan 2.9 33 22.5 79.9 5.4 3.6 1.8 14.7 11.8 2.9 29 Education No education 5.6 2,719 23.6 49.0 16.8 11.0 5.8 34.1 22.5 11.6 2,392 Primary 6.3 800 24.8 41.7 13.1 9.9 3.2 45.2 25.0 20.2 689 Middle 2.5 341 24.7 48.6 10.5 6.4 4.1 41.0 25.0 16.0 286 Secondary 1.7 490 26.0 37.4 8.0 5.7 2.3 54.5 33.9 20.6 423 Higher 1.7 448 26.0 41.6 5.8 3.6 2.3 52.5 33.1 19.5 381 Wealth quintile Lowest 6.8 894 21.3 56.2 27.0 17.3 9.7 16.8 12.7 4.0 755 Second 6.5 922 22.7 56.5 18.0 11.4 6.6 25.5 18.2 7.3 786 Middle 4.3 930 24.3 46.1 13.8 11.6 2.2 40.1 25.9 14.2 823 Fourth 4.1 1,067 25.6 38.8 8.7 5.0 3.7 52.5 32.0 20.5 930 Highest 2.3 985 27.1 35.0 4.4 2.9 1.5 60.6 34.4 26.2 876 Total 4.7 4,798 24.3 45.9 13.9 9.3 4.6 40.2 25.2 15.0 4,170 Note: Body mass index is expressed as the ratio of weight in kilograms to the square of height in meters (kg/m2). 1 Excludes pregnant women and women with a birth in the preceding 2 months Nutrition of Children and Women • 181 Table 11.8 shows that the mean BMI among women age 15-49 is 24.3 kg/m2. Mean BMI generally increases with age. Urban women have a slightly higher mean BMI (26.1 kg/m2) than rural women (23.4 kg/m2). There are only small differences among women living in the different regions, although women in ICT Islamabad have a better mean BMI (26.7 kg/m2). Women with no education are more likely to have a lower mean BMI than those with a secondary or higher education (23.6 kg/m2 and 26.0 kg/m2, respectively). Mean BMI shows a steady increase with increasing wealth, from 21.3 kg/m2 among women in the lowest wealth quintile to 27.1 kg/m2 among those in the highest quintile. Fourteen percent of women of reproductive age are thin or undernourished (BMI less than 18.5 kg/m2). The proportions of mild thinness (17.0-18.4 kg/m2) and moderate and severe thinness (less than 17 kg/m2) are 9 percent and 5 percent, respectively. Women age 15-19 and 20-29 are more likely to be thin (20 percent each) than older women. Rural women are more likely to be thin (17 percent) than urban women (7 percent). Women in Sindh are four times as likely to be thin (20 percent) as women in Gilgit Baltistan (5 percent). One quarter (25 percent) of women are overweight (BMI of 25-29 kg/m2), and 15 percent are obese (BMI of 30 kg/m2 or above). Recent estimates from WHO suggest that 26 percent of women in Pakistan are obese (Associated Press of Pakistan, 2013). Obesity is emerging in Pakistan as a public health problem even as the country attempts to cope with the more traditional problems of undernutrition and infectious diseases (Nanan, 2002). According to James and Ralph (1999; as cited in Nanan, 2002), the situation in Pakistan is similar to other countries undergoing a number of transitions, with obesity initially affecting urban middle-aged women and then, with increasing urbanization and lifestyle changes (including changes in diet and physical activity), having an impact among younger women. Variations in overweight or obesity among women are apparent by background characteristics. The prevalence of overweight and obesity among women of reproductive age increases with age and is higher in urban areas. Almost 50 percent of women age 15-49 in Khyber Pakhtunkhwa and ICT Islamabad are either overweight or obese. As one would expect, overnutrition is more prevalent in wealthier households. Women in the highest wealth quintile (26 percent) are more than six times as likely to be obese as women in the lowest quintile (4 percent). 11.9 MICRONUTRIENT INTAKE AMONG MOTHERS Adequate micronutrient intake by women has important benefits for both women and their children. Breastfeeding children benefit from micronutrient supplementation that mothers receive, especially vitamin A. Iron supplementation of women during pregnancy protects the mother and infant against anemia, which is considered a major cause of perinatal and maternal mortality. Anemia also results in an increased risk of premature delivery and low birth weight. Finally, iodine deficiency is related to a number of adverse pregnancy outcomes including abortion, fetal brain damage and congenital malformation, stillbirth, and prenatal death. In Pakistan, micronutrient deficiency among pregnant and lactating mothers is a common public health problem. Thus, the 2012-13 PDHS collected data on the use of vitamin A and iron-folic acid supplements among women age 15-49 with a child born in the past five years, as well as the use of deworming medication during the last pregnancy. A single dose of vitamin A is typically given to women within 45 days of childbirth, aimed at increasing the mother’s vitamin A level and the content of the vitamin in her breast milk for the benefit of her child. Because of the risk of teratogenesis (abnormal development of the fetus) resulting from high doses of vitamin A during pregnancy, the supplement should not be given to pregnant women. Table 11.9 includes measures that are useful in assessing micronutrient intake by women during pregnancy and the two months after delivery (postpartum period). The findings show that only 14 percent of women received a vitamin A dose during the postpartum period, which is a lower proportion than in 182 • Nutrition of Children and Women 2006-07 (20 percent). There is substantial variation across geographical areas, with the highest proportion in ICT Islamabad (32 percent) and the lowest in Gilgit Baltistan (4 percent). The proportion of women receiving postpartum vitamin A also differs by urban and rural residence (19 percent and 11 percent, respectively). Women with a higher education were more than three times as likely as mothers with no education to have received a vitamin A supplement (27 and 9 percent, respectively). The prevalence of postpartum vitamin A supplementation increases with increasing wealth, from 7 percent in the lowest quintile to 26 percent in the highest quintile. Table 11.9 Micronutrient intake among mothers Among women age 15-49 with a child born in the past five years, the percentage who received a vitamin A dose in the first two months after the birth of the last child, the percent distribution by number of days they took iron tablets or syrup during the pregnancy of the last child, and the percentage who took deworming medication during the pregnancy of the last child, Pakistan 2012-13 Among women with a child born in the past five years: Percentage who received vitamin A dose postpartum1 Number of days women took iron tablets or syrup during pregnancy of last birth Percentage of women who took deworming medication during pregnancy of last birth Number of women Background characteristic None <60 60-89 90+ Don’t know/ missing Total Age 15-19 11.5 52.5 17.9 6.5 22.0 1.0 100.0 1.0 229 20-29 14.2 54.0 14.5 8.1 22.1 1.4 100.0 2.5 3,696 30-39 13.6 54.0 13.4 7.7 23.5 1.4 100.0 2.6 2,961 40-49 8.6 65.9 12.3 6.0 14.8 1.0 100.0 2.5 560 Residence Urban 19.3 42.0 16.0 8.1 32.4 1.5 100.0 2.9 2,244 Rural 10.9 60.4 13.1 7.5 17.7 1.3 100.0 2.3 5,202 Region Punjab 11.5 55.7 14.2 7.1 22.1 0.9 100.0 3.1 4,180 Sindh 17.4 50.6 14.9 9.8 23.9 0.9 100.0 1.6 1,714 Khyber Pakhtunkhwa 16.9 49.8 13.9 8.6 24.3 3.5 100.0 2.1 1,117 Balochistan 6.1 82.7 7.5 2.2 5.0 2.7 100.0 0.7 348 ICT Islamabad 32.2 20.2 16.5 9.4 52.7 1.1 100.0 3.3 31 Gilgit Baltistan 4.2 70.0 11.9 4.7 13.4 0.0 100.0 1.5 56 Education No education 8.6 65.9 12.6 6.3 14.2 1.0 100.0 1.9 4,155 Primary 15.5 52.9 15.8 9.0 21.3 1.1 100.0 3.7 1,230 Middle 16.8 43.5 15.2 9.4 30.3 1.7 100.0 2.5 587 Secondary 21.2 37.1 17.3 10.6 33.6 1.5 100.0 3.2 792 Higher 27.4 21.2 14.5 9.3 51.5 3.4 100.0 2.9 682 Wealth quintile Lowest 6.9 71.3 10.9 5.4 11.5 0.8 100.0 1.4 1,698 Second 7.5 65.2 13.5 6.9 13.1 1.3 100.0 1.6 1,544 Middle 12.6 56.9 14.5 8.2 19.0 1.4 100.0 3.2 1,464 Fourth 17.3 42.8 16.1 10.4 28.4 2.2 100.0 3.3 1,469 Highest 26.0 31.9 15.6 8.0 43.4 1.1 100.0 3.3 1,272 Total 13.5 54.8 14.0 7.7 22.1 1.4 100.0 2.5 7,446 1 In the first 2 months after delivery of last birth Nutritional deficiencies such as anemia are often exacerbated during pregnancy because of the additional nutrient demands associated with fetal growth. Iron status can be enhanced by including iron supplements in food consumed by women, improving women’s diets, and controlling parasites. Iron supplementation is necessary for pregnant women because their needs are usually too high to be met solely by food intake. According to Table 11.9, 22 percent of women took iron tablets daily for 90 or more days during their last pregnancy. Eight percent took iron supplements for 60 to 89 days, and 14 percent took supplements for fewer than 60 days. Fifty-five percent of pregnant women did not take iron supplements at all. The proportion of women taking daily iron supplements for 90 or more days differs substantially between urban and rural areas (32 percent and 18 percent, respectively). Pregnant women in ICT Islamabad are more likely to take iron supplements daily for 90 or more days (53 percent) than those in Nutrition of Children and Women • 183 Balochistan (5 percent). Women with a higher education are more likely to take iron tablets for 90 or more days (52 percent) than women with no education (14 percent). Women in the highest wealth quintile are more than three times as likely to take iron tablets for 90 or more days (43 percent) as those in the lowest wealth quintile (12 percent). Infections caused by helminthes (intestinal parasites) are one of the factors contributing to anemia among pregnant women. Deworming during pregnancy is a cost-effective intervention against intestinal worms that allows better absorption of nutrients and iron, thus reducing the prevalence of anemia. Table 11.9 shows that 3 percent of women took deworming medication during their last pregnancy. There is no difference in use of deworming medication by residence, region, education, or wealth quintile. HIV/AIDS-Related Knowledge, Attitudes, and Behavior • 185 HIV/AIDS-RELATED KNOWLEDGE, ATTITUDES, AND BEHAVIOR 12 cquired immunodeficiency syndrome (AIDS) is one of the most serious public health and development challenges facing the world today. AIDS is caused by the human immunodeficiency virus (HIV). HIV weakens the immune system, making the body susceptible to secondary infections and opportunistic diseases. Without treatment, HIV infection leads to AIDS, which is invariably fatal. The predominant mode of HIV transmission is sexual contact. Other modes of transmission are unsafe injections, use of tainted blood supplies during blood transfusions, and mother-to-child transmission (in which the mother passes HIV to her child during pregnancy, delivery, or breastfeeding). Internationally, AIDS was first recognized in 1981. According to the Joint United Nations Programme on HIV/AIDS (UNAIDS), an estimated 34 million adults and children around the world were living with HIV and AIDS in 2011 (UNAIDS, 2012). A large proportion of those who are infected with HIV die within 5-10 years (Munoz et al., 1997). The HIV/AIDS pandemic is one of the most serious health concerns in the world today because of its high case fatality rate and the lack of a curative treatment or vaccines. HIV cannot be transmitted through food, water, insect vectors, or casual contact. The first case of HIV in Pakistan was diagnosed in 1987. As of February 2013, a total of approximately 7,750 cases had been diagnosed, based on reports from National AIDS Control Program (NACP) treatment centers (NACP, 2013). However, because the infection remains asymptomatic for many years, most infected individuals are unaware that they are infected; therefore, the actual number of people infected with HIV in Pakistan may be much larger. Indeed, NACP, UNAIDS, and the Ministry of National Health Services, Regulation and Coordination estimate that approximately 112,000 people are currently living with HIV in Pakistan (NACP, 2013). Limited data suggest that infection is extremely common among sex workers and highly uncommon among the general population. There have been various efforts by both the government and nongovernmental organizations to prevent HIV transmission, including public health education through the media. In particular, information, education, and communication efforts are directed at increasing awareness of issues related to prevention. The findings of the 2012-13 PDHS will be helpful in shaping these initiatives. The survey included a section on HIV/AIDS in order to assess respondents’ knowledge of the modes of HIV transmission and the ways in which HIV can be prevented, as well as their attitudes toward persons living with AIDS. The survey also included questions on sexually transmitted infections and injection safety practices. A Key Findings • Four in 10 ever-married women and 7 in 10 ever-married men age 15-49 have heard of AIDS. • Comprehensive knowledge of AIDS is not widespread among either women (7 percent) or men (12 percent). • Only 12 percent of women and 18 percent of men know of ways to prevent mother-to-child transmission of HIV. • Only 17 percent of women and 15 percent of men express accepting attitudes toward people living with AIDS. • Thirty-six percent of men and 11 percent of women know of a place where they can go to get an HIV test. • Sixty-one percent of women and 53 percent of men reported receiving a medical injection from a health worker during the 12-month period preceding the survey. 186 • HIV/AIDS-Related Knowledge, Attitudes, and Behavior 12.1 KNOWLEDGE OF AIDS The 2012-13 PDHS included a series of questions to gauge respondents’ knowledge and attitudes about AIDS. Ever-married women and men age 15-49 were first asked whether they had heard of AIDS. Those who reported having heard of AIDS were asked a number of additional questions about various modes of prevention, including whether it is possible to reduce the chance of getting the AIDS virus by having just one faithful sex partner and using a condom during every sexual encounter. To allow an assessment of the level of possible misconceptions, respondents were also asked whether they think it is possible for a healthy- looking person to have the AIDS virus and whether a person can contract AIDS from mosquito bites, by sharing food with a person who has AIDS, or through supernatural means. Table 12.1 shows that 42 percent of women and 69 percent of men have heard of AIDS. Knowledge of AIDS among women varies by age and marital status, with women in the 15- 24 and 40-49 age groups and women who are divorced, separated, or widowed being less likely to know about AIDS than women who are 25-39 and women who are married. Knowledge of AIDS is higher among urban women than rural women (69 percent and 28 percent, respectively). A similar urban-rural pattern is observed among men, although the differential is smaller. Across regions, knowledge of AIDS ranges from a high of 83 percent among women in ICT Islamabad to a low of 12 percent among women in Gilgit Baltistan. There are large urban- rural differentials within regions. The percentage of women who have heard of AIDS in urban areas of Punjab and Khyber Pakhtunkhwa is twice that of their counterparts living in rural areas of these regions. Likewise, women in urban Balochistan and Sindh are much more likely than their rural counterparts to have heard of AIDS. Similar patterns are observed among men within each region. Nearly all women with a higher education have heard of AIDS, as compared with only 18 percent of women with no education. The proportion of women who have heard of AIDS increases with increasing wealth. Men show similar patterns of knowledge of AIDS by education and wealth, although the differentials are not as marked as for women. 12.2 KNOWLEDGE OF HIV PREVENTION METHODS Pakistan’s National AIDS Control Program seeks to reduce sexual transmission of the AIDS virus by promoting HIV/AIDS prevention programs. These programs focus on health education messages related to two important aspects of HIV/AIDS prevention behaviors: limiting sexual intercourse to one uninfected partner and using condoms. To ascertain whether programs have effectively communicated these messages, respondents were asked specific questions about whether it is possible to reduce the Table 12.1 Knowledge of AIDS Percentage of ever-married women and ever-married men age 15-49 who have heard of AIDS, by background characteristics, Pakistan 2012- 13 Women Men Background characteristic Has heard of AIDS Number of women Has heard of AIDS Number of men Age 15-24 33.6 2,711 53.5 255 15-19 20.4 605 (28.5) 36 20-24 37.4 2,106 57.6 219 25-29 48.4 2,724 67.7 521 30-39 45.5 4,755 72.6 1,234 40-49 38.1 3,368 67.7 1,124 Marital status Married 42.1 12,937 69.2 3,071 Divorced/separated/ widowed 36.8 621 (31.3) 63 Residence Urban 69.1 4,536 84.0 1,107 Rural 28.2 9,022 60.0 2,027 Region Punjab 45.7 7,790 73.1 1,804 Urban 68.2 2,526 81.2 618 Rural 34.9 5,264 68.8 1,186 Sindh 43.6 3,133 59.1 796 Urban 75.5 1,521 88.1 376 Rural 13.5 1,612 33.1 420 Khyber Pakhtunkhwa 29.3 1,908 70.9 347 Urban 53.6 320 86.5 67 Rural 24.4 1,588 67.2 281 Balochistan 21.8 568 58.2 151 Urban 45.6 114 80.6 32 Rural 15.8 454 52.2 119 ICT Islamabad 82.9 64 91.2 18 Gilgit Baltistan 12.1 94 43.9 18 Education No education 18.4 7,736 35.8 905 Primary 50.2 2,156 67.5 657 Middle 72.9 993 79.2 525 Secondary 87.4 1,413 87.3 557 Higher 96.0 1,260 97.2 491 Wealth quintile Lowest 6.5 2,589 32.6 607 Second 18.0 2,676 58.4 574 Middle 37.7 2,700 70.7 567 Fourth 59.1 2,789 83.0 713 Highest 84.2 2,804 92.2 673 Total 41.9 13,558 68.5 3,134 Note: Figures in parentheses are based on 25-49 unweighted cases. HIV/AIDS-Related Knowledge, Attitudes, and Behavior • 187 chance of getting the AIDS virus by using a condom during every sexual encounter and by limiting sexual intercourse to one uninfected partner. Table 12.2 presents knowledge of HIV prevention methods among ever-married women and men age 15-49, by background characteristics. Since only women and men who had heard of AIDS were asked questions about how HIV can be prevented, knowledge levels are low, especially among women. Only 32 percent of women are aware that the risk of contracting the AIDS virus can be reduced by limiting sexual intercourse to one uninfected partner who has no other partners; 22 percent know that using condoms every time they have sexual intercourse reduces the risk of getting the AIDS virus. Twenty percent of women are aware of both means of reducing the risk of AIDS virus transmission. Table 12.2 Knowledge of HIV prevention methods Percentage of ever-married women and ever-married men age 15-49 who, in response to prompted questions, say that people can reduce the risk of getting the AIDS virus by using condoms every time they have sexual intercourse, and by having one sex partner who is not infected and has no other partners, by background characteristics, Pakistan 2012-13 Women Men Percentage who say HIV can be prevented by: Number of women Percentage who say HIV can be prevented by: Number of men Background characteristic Using condoms1 Limiting sexual intercourse to one uninfected partner2 Using condoms and limiting sexual intercourse to one uninfected partner1,2 Using condoms1 Limiting sexual intercourse to one uninfected partner2 Using condoms and limiting sexual intercourse to one uninfected partner1,2 Age 15-24 16.1 23.7 14.0 2,711 27.5 44.6 26.3 255 15-19 6.2 11.0 4.3 605 (19.0) (28.5) (19.0) 36 20-24 19.0 27.3 16.7 2,106 28.9 47.3 27.4 219 25-29 25.4 35.7 22.0 2,724 40.4 57.0 38.3 521 30-39 24.7 35.4 22.3 4,755 42.3 61.7 39.3 1,234 40-49 19.9 29.8 18.0 3,368 37.1 55.8 35.1 1,124 Marital status Married 22.1 32.0 19.7 12,937 39.3 58.1 37.0 3,071 Divorced/separated/ widowed 18.3 24.9 15.9 621 (20.0) (24.2) (17.1) 63 Residence Urban 37.6 55.2 34.3 4,536 54.8 75.4 52.7 1,107 Rural 14.1 19.9 12.1 9,022 30.3 47.6 27.8 2,027 Region Punjab 25.1 34.8 22.4 7,790 38.5 60.4 36.8 1,804 Urban 38.7 54.0 34.9 2,526 53.7 73.3 52.9 618 Rural 18.6 25.6 16.4 5,264 30.7 53.7 28.4 1,186 Sindh 21.4 34.1 19.4 3,133 39.4 53.2 37.3 796 Urban 38.5 61.4 36.0 1,521 56.3 79.1 52.5 376 Rural 5.2 8.4 3.8 1,612 24.3 30.1 23.8 420 Khyber Pakhtunkhwa 12.5 19.6 10.3 1,908 44.7 57.2 39.7 347 Urban 27.6 40.5 24.1 320 62.0 79.4 58.6 67 Rural 9.5 15.4 7.5 1,588 40.6 51.9 35.3 281 Balochistan 11.8 16.1 10.1 568 27.7 44.6 22.2 151 Urban 24.3 36.1 20.4 114 42.9 64.1 37.0 32 Rural 8.6 11.0 7.5 454 23.7 39.3 18.2 119 ICT Islamabad 54.0 70.5 49.5 64 58.4 81.4 56.2 18 Gilgit Baltistan 8.0 8.4 6.6 94 22.7 35.4 20.5 18 Education No education 8.4 12.1 6.9 7,736 14.0 23.4 11.6 905 Primary 23.6 35.5 20.2 2,156 32.9 54.7 30.5 657 Middle 33.4 52.1 29.4 993 43.2 67.9 41.0 525 Secondary 49.9 71.1 44.6 1,413 56.1 75.4 53.6 557 Higher 62.1 85.4 59.5 1,260 69.0 92.3 66.6 491 Wealth quintile Lowest 3.1 3.9 2.1 2,589 16.5 24.7 14.9 607 Second 7.9 11.8 6.6 2,676 26.7 46.2 23.8 574 Middle 17.8 26.0 15.4 2,700 34.9 55.7 33.4 567 Fourth 29.1 44.0 25.7 2,789 51.5 70.5 47.6 713 Highest 49.6 69.7 45.7 2,804 59.6 84.1 58.0 673 Total 15-49 22.0 31.7 19.5 13,558 38.9 57.4 36.6 3,134 Note: Figures in parentheses are based on 25-49 unweighted cases. 1 Using condoms every time they have sexual intercourse 2 Partner who has no other partners 188 • HIV/AIDS-Related Knowledge, Attitudes, and Behavior Knowledge of HIV prevention methods among men is greater than that among women. Thirty- nine percent of men know that the risk of transmitting the AIDS virus can be reduced by using condoms, and 57 percent know that transmission risk can be reduced by limiting sexual intercourse to one uninfected partner. Over one-third of men (37 percent) know both means of reducing transmission. Women and men age 15-19 and 40-49 are less knowledgeable about methods of HIV prevention than respondents in other age groups. Female and male respondents living in urban areas are more knowledgeable about HIV prevention methods than those living in rural areas; 34 percent of urban women and 53 percent of urban men know that that the risk of transmitting the AIDS virus can be reduced by using condoms and limiting sexual intercourse to one uninfected partner, whereas only 12 percent of rural women and 28 percent of rural men know both means of prevention. A similar pattern is observed in urban-rural areas within regions. Among both women and men, knowledge of prevention methods is positively correlated with education and wealth. 12.3 COMPREHENSIVE KNOWLEDGE ABOUT AIDS As part of the effort to assess knowledge regarding AIDS, the 2012-13 PDHS collected information on common misconceptions about HIV transmission. As noted above, respondents were asked whether they think it is possible for a healthy-looking person to have the AIDS virus and whether they believe the AIDS virus can be transmitted through mosquito bites, supernatural means, or sharing food with a person who has the AIDS virus. Comprehensive knowledge of HIV/AIDS is defined as follows: (1) knowing that consistent condom use and having just one faithful partner can reduce the chance of getting the AIDS virus, (2) knowing that a healthy-looking person can have the AIDS virus, and (3) rejecting the two most common local misconceptions about HIV transmission—that the AIDS virus can be transmitted through mosquito bites and by sharing food. As shown in Tables 12.3.1 and 12.3.2, many Pakistani adults lack accurate knowledge about the ways through which the AIDS virus can and cannot be transmitted. Table 12.3.1 shows that only 28 percent of ever-married women know that a healthy-looking person can have the AIDS virus, 21 percent know that the AIDS virus cannot be transmitted through mosquito bites, and 30 percent know that the AIDS virus cannot be transmitted by supernatural means. Twenty-one percent of women correctly believe that a person cannot become infected by sharing food with a person who has the AIDS virus. Only 7 percent of women have comprehensive knowledge about AIDS. Comprehensive knowledge about AIDS among women varies little by age, with the exception that only 1 percent of women age 15-19 have comprehensive knowledge of AIDS. Urban women (15 percent) and those living in ICT Islamabad (25 percent) are much more likely than women from rural areas (3 percent) or other regions (3-9 percent) to have comprehensive knowledge about AIDS. Comprehensive knowledge about AIDS increases with increasing education and wealth, rising from 1 percent among women with no education to 34 percent among women with a higher education and from less than 1 percent among women in the lowest wealth quintile to 21 percent among those in the highest quintile. HIV/AIDS-Related Knowledge, Attitudes, and Behavior • 189 Table 12.3.1 Comprehensive knowledge about AIDS: Women Percentage of ever-married women age 15-49 who say that a healthy-looking person can have the AIDS virus and who, in response to prompted questions, correctly reject local misconceptions about transmission or prevention of the AIDS virus, and the percentage with comprehensive knowledge about AIDS, by background characteristics, Pakistan 2012-13 Percentage of respondents who say that: Percentage who say that a healthy-looking person can have the AIDS virus and who reject the two most common local misconceptions1 Percentage with comprehensive knowledge about AIDS2 Number of women Background characteristic A healthy-looking person can have the AIDS virus The AIDS virus cannot be transmitted by mosquito bites The AIDS virus cannot be transmitted by supernatural means A person cannot become infected by sharing food with a person who has AIDS Age 15-24 22.3 15.4 24.3 14.6 6.6 4.2 2,711 15-19 11.2 8.5 14.6 5.6 2.3 0.6 605 20-24 25.5 17.4 27.1 17.2 7.8 5.2 2,106 25-29 32.4 25.2 34.9 24.4 12.8 8.7 2,724 30-39 30.3 22.5 32.8 23.0 11.0 7.5 4,755 40-49 26.1 18.3 25.7 19.2 10.1 6.5 3,368 Marital status Married 28.3 20.8 30.2 21.0 10.5 7.0 12,937 Divorced/separated/ widowed 22.9 16.1 20.5 14.3 6.4 4.6 621 Residence Urban 47.3 38.2 52.8 39.6 21.1 14.7 4,536 Rural 18.4 11.7 18.2 11.1 4.8 2.9 9,022 Region Punjab 30.9 21.2 32.3 21.1 10.2 7.1 7,790 Sindh 30.4 25.4 32.3 25.2 13.8 9.4 3,133 Khyber Pakhtunkhwa 17.9 12.7 19.4 13.7 5.9 2.6 1,908 Balochistan 10.8 9.7 14.2 10.8 4.5 2.8 568 ICT Islamabad 60.7 58.9 72.5 57.4 35.1 24.5 64 Gilgit Baltistan 8.3 7.9 11.3 7.5 4.2 3.0 94 Education No education 11.0 6.3 10.4 6.0 2.1 1.1 7,736 Primary 31.0 19.3 33.2 18.7 7.8 4.5 2,156 Middle 47.6 32.2 51.4 34.9 13.3 7.8 993 Secondary 61.6 49.5 68.1 49.2 24.9 17.1 1,413 Higher 75.1 68.4 82.5 70.4 45.9 33.8 1,260 Wealth quintile Lowest 4.0 2.4 3.9 1.9 0.5 0.2 2,589 Second 10.8 7.7 10.4 6.1 2.5 1.4 2,676 Middle 23.6 14.3 23.4 14.0 5.6 3.1 2,700 Fourth 39.5 24.2 40.2 25.6 11.3 7.5 2,789 Highest 59.8 52.0 67.9 53.4 30.2 21.2 2,804 Total 28.1 20.6 29.8 20.7 10.3 6.8 13,558 1 Two most common local misconceptions: a person can become infected by sharing food with someone who has AIDS and the AIDS virus can be transmitted through mosquito bites. 2 Comprehensive knowledge means knowing that consistent use of condoms 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 AIDS transmission or prevention. Table 12.3.2 shows that 46 percent of ever-married men age 15-49 know that a healthy-looking person can have the AIDS virus, 40 percent know that the AIDS virus cannot be transmitted through mosquito bites, and 55 percent know that the AIDS virus cannot be transmitted by supernatural means. Thirty-four percent of men correctly believe that a person cannot become infected by sharing food with a person who has the AIDS virus. Men are more likely than women to have comprehensive knowledge about AIDS (Figure 12.1). As was observed among women, comprehensive knowledge about AIDS among men increases with increasing education and wealth quintile. 190 • HIV/AIDS-Related Knowledge, Attitudes, and Behavior Table 12.3.2 Comprehensive knowledge about AIDS: Men Percentage of ever-married men age 15-49 who say that a healthy-looking person can have the AIDS virus and who, in response to prompted questions, correctly reject local misconceptions about transmission or prevention of the AIDS virus, and the percentage with comprehensive knowledge about AIDS, by background characteristics, Pakistan 2012-13 Percentage of respondents who say that: Percentage who say that a healthy-looking person can have the AIDS virus and who reject the two most common local misconceptions1 Percentage with comprehensive knowledge about AIDS2 Number of men Background characteristic A healthy-looking person can have the AIDS virus The AIDS virus cannot be transmitted by mosquito bites The AIDS virus cannot be transmitted by supernatural means A person cannot become infected by sharing food with a person who has AIDS Age 15-24 29.5 22.8 38.7 22.7 7.1 5.2 255 15-19 (16.4) (17.2) (19.9) (16.3) (5.4) (5.4) 36 20-24 31.7 23.7 41.8 23.7 7.4 5.2 219 25-29 46.7 41.3 53.4 35.4 19.4 14.5 521 30-39 49.2 45.0 59.3 37.8 19.7 13.3 1,234 40-49 45.8 38.1 54.5 32.9 16.4 10.3 1,124 Marital status Married 46.6 40.7 55.7 34.8 17.7 12.0 3,071 Divorced/separated/ widowed (16.6) (11.0) (19.1) (16.0) (5.6) (3.0) 63 Residence Urban 55.3 57.0 69.5 48.1 22.9 15.9 1,107 Rural 40.9 30.8 47.0 26.9 14.5 9.6 2,027 Region Punjab 52.1 39.3 58.0 34.1 18.7 12.4 1,804 Sindh 34.1 39.7 46.2 30.9 12.0 8.4 796 Khyber Pakhtunkhwa 47.8 43.0 58.7 38.8 19.0 15.4 347 Balochistan 31.1 42.0 53.8 41.9 24.1 12.2 151 ICT Islamabad 68.2 70.7 85.0 73.8 49.4 32.8 18 Gilgit Baltistan 26.9 29.6 41.2 26.3 15.4 7.6 18 Education No education 19.0 15.2 23.7 13.1 4.2 2.2 905 Primary 42.9 33.2 51.1 33.5 12.2 6.7 657 Middle 51.4 41.4 63.3 34.5 17.2 12.1 525 Secondary 62.9 61.9 73.0 43.6 27.5 20.8 557 Higher 74.8 68.9 88.1 64.3 37.6 25.6 491 Wealth quintile Lowest 21.4 11.0 22.5 8.4 4.4 2.1 607 Second 36.7 30.0 43.7 22.0 9.1 4.8 574 Middle 46.7 36.2 52.0 32.1 16.1 10.7 567 Fourth 56.6 46.2 68.6 44.5 21.9 16.8 713 Highest 64.2 71.7 81.6 59.6 32.7 22.1 673 Total 46.0 40.1 54.9 34.4 17.4 11.8 3,134 Note: Figures in parentheses are based on 25-49 unweighted cases. 1 Two most common local misconceptions: a person can become infected by sharing food with someone who has AIDS and the AIDS virus can be transmitted through mosquito bites. 2 Comprehensive knowledge means knowing that consistent use of condoms 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 AIDS transmission or prevention. HIV/AIDS-Related Knowledge, Attitudes, and Behavior • 191 Figure 12.1 Comprehensive knowledge about AIDS among ever-married women and men age 15-49 28 21 21 10 7 46 40 34 17 12 A healthy-looking person can have the AIDS virus AIDS cannot be transmited by mosquito bites A person cannot become infected by sharing food with a person who has the AIDS virus Percentage who say that a healthy-looking person can have the AIDS virus and who reject the two most common local misconceptions Percentage with comprehensive knowledge about AIDS Percentage Women Men PDHS 2012-13 12.4 KNOWLEDGE OF MOTHER-TO-CHILD TRANSMISSION OF HIV Knowledge about how to prevent mother-to-child transmission (MTCT) of HIV is critical in the fight against HIV/AIDS. To assess MTCT knowledge, ever-married women and men age 15-49 were asked whether HIV can be transmitted from a mother to a child through breastfeeding and whether a mother can reduce the risk of transmitting HIV to her child during pregnancy by taking antiretroviral drugs. Table 12.4 shows that 27 percent of women know that HIV can be transmitted through breastfeeding and 13 percent know that risk of mother-to-child transmission can be reduced through mothers taking special drugs during pregnancy. Only 12 percent of women are knowledgeable regarding both of these ways of preventing mother-to-child transmission of HIV. Although knowledge of prevention of MTCT varies little by current marital status, it is higher among urban women than rural women and higher among those living in ICT Islamabad than those in other regions. Knowledge of prevention of MTCT increases with increasing education and wealth. Table 12.4 also shows that 40 percent of men know that HIV can be transmitted through breastfeeding and 22 percent know that the risk of mother-to-child transmission can be reduced by mothers taking special drugs during pregnancy. Variations by background characteristics in knowledge of prevention of MTCT are similar to those observed for women. 192 • HIV/AIDS-Related Knowledge, Attitudes, and Behavior Table 12.4 Knowledge of prevention of mother-to-child transmission of HIV Percentage of ever-married women and men age 15-49 who know that HIV can be transmitted from mother to child by breastfeeding and that the risk of mother- to-child transmission (MTCT) of HIV can be reduced by the mother taking special drugs during pregnancy, by background characteristics, Pakistan 2012-13 Women Men Percentage who know that: Number of women Percentage who know that: Number of men Background characteristic HIV can be transmitted by breastfeeding Risk of MTCT can be reduced by mother taking special drugs during pregnancy HIV can be transmitted by breastfeeding and risk of MTCT can be reduced by mother taking special drugs during pregnancy HIV can be transmitted by breastfeeding Risk of MTCT can be reduced by mother taking special drugs during pregnancy HIV can be transmitted by breastfeeding and risk of MTCT can be reduced by mother taking special drugs during pregnancy Age 15-24 20.7 10.7 9.6 2,711 26.9 14.4 12.0 255 15-19 10.3 4.2 3.7 605 (19.9) (8.6) (5.5) 36 20-24 23.7 12.6 11.2 2,106 28.0 15.4 13.1 219 25-29 31.1 15.8 13.4 2,724 36.3 22.4 18.4 521 30-39 28.6 13.4 12.2 4,755 43.3 23.7 19.0 1,234 40-49 24.2 12.7 11.4 3,368 41.5 22.2 18.5 1,124 Marital status Married 26.5 13.3 11.8 12,937 40.5 22.4 18.2 3,071 Divorced/separated/ widowed 25.1 11.5 10.5 621 (22.0) (14.5) (14.3) 63 Currently pregnant Pregnant 24.0 11.7 10.3 1,461 na na na na Not pregnant or not sure 26.7 13.4 11.9 12,097 na na na na Residence Urban 42.5 21.4 18.5 4,536 47.9 25.6 20.6 1,107 Rural 18.4 9.1 8.3 9,022 35.9 20.3 16.8 2,027 Region Punjab 30.1 15.4 14.0 7,790 44.1 21.1 18.8 1,804 Sindh 25.4 14.0 11.7 3,133 36.9 18.6 14.9 796 Khyber Pakhtunkhwa 17.4 6.0 5.2 1,908 38.7 36.7 26.9 347 Balochistan 12.9 3.4 3.2 568 14.4 19.8 7.5 151 ICT Islamabad 48.4 23.5 18.8 64 45.5 50.6 31.0 18 Gilgit Baltistan 6.8 4.4 3.5 94 20.1 8.6 6.8 18 Education No education 11.8 5.8 5.4 7,736 19.3 8.4 7.4 905 Primary 31.3 16.2 14.8 2,156 37.8 20.1 17.5 657 Middle 44.5 21.1 19.9 993 45.4 23.0 19.1 525 Secondary 55.5 26.3 23.1 1,413 55.4 31.7 25.6 557 Higher 61.2 32.5 25.9 1,260 58.7 38.7 29.3 491 Wealth quintile Lowest 4.4 2.4 2.4 2,589 20.5 6.9 6.0 607 Second 12.7 5.0 4.8 2,676 33.0 21.0 16.6 574 Middle 24.3 12.1 10.9 2,700 41.4 27.7 23.3 567 Fourth 37.4 17.8 16.6 2,789 47.5 26.3 22.2 713 Highest 51.1 27.4 22.8 2,804 55.0 28.0 21.7 673 Total 26.5 13.2 11.7 13,558 40.1 22.2 18.1 3,134 Note: Figures in parentheses are based on 25-49 unweighted cases. na = Not applicable 12.5 ACCEPTING ATTITUDES TOWARD THOSE LIVING WITH HIV AND AIDS The HIV/AIDS epidemic has generated fear, anxiety, and prejudice against people living with HIV and AIDS, and people who are HIV positive face widespread stigma and discrimination. These societal attitudes can adversely affect both people’s willingness to be tested for HIV and their initiation of and adherence to antiretroviral therapy. Reducing stigma and discrimination is therefore an important factor in the prevention, management, and control of the HIV epidemic. In the 2012-13 PDHS, ever-married women and men age 15-49 who had heard of AIDS were asked a number of questions to assess the level of stigma associated with HIV and AIDS. Results for women and men are shown in Tables 12.5.1 and 12.5.2, respectively. Similar proportions of women and men reported that they would be willing to take care of a family member with HIV at home (92 percent and 90 percent, respectively) and that they would buy fresh vegetables from a shopkeeper who has HIV HIV/AIDS-Related Knowledge, Attitudes, and Behavior • 193 (47 percent each). However, women were much more likely than men to think that a female teacher with HIV should be allowed to continue teaching (65 percent versus 52 percent). Differences between women and men were minimal regarding the desire to keep secret a family member’s HIV infection status (42 percent versus 38 percent, respectively). Overall, 17 percent of women and 15 percent of men express accepting attitudes regarding all four situations. Among both women and men, accepting attitudes toward those living with HIV/AIDS increase with increasing education and wealth. Except for women in Balochistan and men in Balochistan and Sindh, accepting attitudes toward people with HIV/AIDS are more or less similar in all regions. Table 12.5.1 Accepting attitudes toward those living with HIV/AIDS: Women Among ever-married women age 15-49 who have heard of AIDS, percentage expressing specific accepting attitudes toward people with HIV/AIDS, by background characteristics, Pakistan 2012-13 Percentage of women who: Percentage expressing accepting attitudes on all four indicators Number of women who have heard of AIDS Background characteristic Are willing to care for a family member with AIDS in the respondent’s home Would buy fresh vegetables from shopkeeper who has the AIDS virus Say that a female teacher who has the AIDS virus but is not sick should be allowed to continue teaching Would not want to keep secret that a family member got infected with the AIDS virus Age 15-24 93.2 46.4 68.7 40.0 15.9 911 15-19 92.5 45.6 68.8 26.1 10.0 123 20-24 93.3 46.5 68.7 42.2 16.8 787 25-29 92.6 49.5 68.1 39.8 17.2 1,318 30-39 91.9 46.7 63.0 42.9 16.8 2,164 40-49 91.1 43.1 60.5 45.2 15.7 1,282 Marital status Married 92.1 46.6 64.7 42.1 16.5 5,447 Divorced/separated/ widowed 91.4 43.3 62.3 44.4 15.9 229 Residence Urban 91.4 49.9 65.2 42.4 17.3 3,135 Rural 92.9 42.3 63.8 42.1 15.6 2,540 Region Punjab 92.8 45.2 65.3 43.8 17.1 3,562 Sindh 91.9 48.9 63.7 38.6 15.2 1,365 Khyber Pakhtunkhwa 90.8 47.6 63.6 44.4 17.6 560 Balochistan 78.3 49.8 53.8 27.8 9.5 124 ICT Islamabad 90.6 55.7 72.9 37.8 18.5 53 Gilgit Baltistan 94.6 38.9 51.0 53.2 15.7 11 Education No education 90.9 36.3 55.0 38.6 10.7 1,424 Primary 93.9 38.2 61.1 43.1 14.4 1,083 Middle 93.5 43.9 64.9 42.1 16.4 723 Secondary 91.4 51.7 67.2 45.8 18.9 1,235 Higher 91.8 62.2 76.1 42.1 22.9 1,210 Wealth quintile Lowest 87.8 30.4 47.3 32.5 8.9 168 Second 92.2 36.5 60.7 40.6 13.1 482 Middle 92.2 43.6 65.1 43.3 16.9 1,017 Fourth 92.2 42.4 60.3 44.0 16.0 1,648 Highest 92.2 53.8 69.3 41.6 17.9 2,361 Total 92.1 46.5 64.6 42.2 16.5 5,675 194 • HIV/AIDS-Related Knowledge, Attitudes, and Behavior Table 12.5.2 Accepting attitudes toward those living with HIV/AIDS: Men Among ever-married men age 15-49 who have heard of HIV/AIDS, percentage expressing specific accepting attitudes toward people with HIV/AIDS, by background characteristics, Pakistan 2012-13 Percentage of men who: Percentage expressing accepting attitudes on all four indicators Number of men who have heard of AIDS Background characteristic Are willing to care for a family member with AIDS in the respondent’s home Would buy fresh vegetables from shopkeeper who has the AIDS virus Say that a female teacher who has the AIDS virus but is not sick should be allowed to continue teaching Would not want to keep secret that a family member got infected with the AIDS virus Age 15-24 87.9 51.0 53.8 30.5 10.6 136 15-19 * * * * * 10 20-24 86.9 55.1 57.3 33.0 11.4 126 25-29 93.5 50.5 54.8 38.9 19.0 352 30-39 89.3 48.6 53.3 36.7 14.4 896 40-49 89.6 43.5 48.4 39.3 15.0 761 Marital status Married 90.1 47.2 51.9 37.4 15.2 2,127 Divorced/separated/ widowed * * * * * 20 Residence Urban 94.1 56.0 60.2 32.8 16.3 929 Rural 86.9 40.6 45.4 41.2 14.2 1,217 Region Punjab 87.7 45.4 52.1 45.7 18.0 1,318 Sindh 99.1 50.8 50.8 19.6 8.1 471 Khyber Pakhtunkhwa 94.3 54.2 52.2 31.5 15.1 246 Balochistan 62.7 34.5 49.9 26.7 8.9 88 ICT Islamabad 92.4 68.1 71.2 42.0 24.4 16 Gilgit Baltistan 88.3 23.6 39.8 49.7 4.8 8 Education No education 87.5 35.8 37.8 38.7 9.6 324 Primary 87.8 40.9 44.2 42.9 11.8 443 Middle 91.5 46.9 53.7 36.9 15.6 416 Secondary 89.4 53.1 57.5 38.1 17.7 486 Higher 93.0 55.3 61.0 31.9 18.9 477 Wealth quintile Lowest 82.8 31.3 31.8 36.3 9.8 198 Second 88.1 35.2 39.9 39.4 8.6 335 Middle 86.7 43.2 51.1 43.2 16.6 401 Fourth 93.1 50.0 56.1 39.6 20.1 592 Highest 92.5 58.9 61.0 31.4 14.7 621 Total 90.0 47.3 51.8 37.6 15.1 2,146 Note: An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 12.6 KNOWLEDGE ABOUT TESTING FOR HIV The Pakistan National AIDS Control Program developed HIV counseling and testing guidelines in 2005. Voluntary counseling and testing services that adhere to these guidelines are provided in 18 NACP treatment centers (Ministry of Health, 2005). Ever-married women and men age 15-49 were asked whether they know of a place where people can go to get tested for the AIDS virus. As shown in Table 12.6, men are more likely than women to know of a place where they can go to get an HIV test (36 percent and 11 percent, respectively). Knowledge of facilities offering HIV testing differs by respondents’ background characteristics. Among both women and men, knowledge about where one can get an HIV test generally increases with age. Urban residents are much more likely than rural residents to know where one can get tested; 17 percent of urban women and 48 percent of urban men know of a testing facility, as compared with only 8 percent of rural women and 30 percent of rural men. Respondents from ICT Islamabad are more knowledgeable regarding where to go to get an HIV test than their counterparts in other regions. Among both women and men, knowledge of a place offering HIV testing increases steadily with increasing education and wealth. HIV/AIDS-Related Knowledge, Attitudes, and Behavior • 195 Table 12.6 Knowledge on where to get HIV testing Percentage of ever-married women and ever-married men age 15-49 who know where to get an HIV test, according to background characteristics, Pakistan 2012-13 Women Men Background characteristic Percentage who know where to get an HIV test Number of women Percentage who know where to get an HIV test Number of men Age 15-24 8.4 2,711 23.2 255 15-19 4.6 605 (12.2) 36 20-24 9.4 2,106 25.0 219 25-29 12.2 2,724 31.7 521 30-39 11.5 4,755 39.9 1,234 40-49 10.7 3,368 37.2 1,124 Marital status Married 10.9 12,937 36.6 3,071 Divorced/separated/ widowed 10.7 621 (19.2) 63 Residence Urban 16.8 4,536 48.2 1,107 Rural 7.9 9,022 29.7 2,027 Region Punjab 12.0 7,790 39.6 1,804 Sindh 10.7 3,133 26.5 796 Khyber Pakhtunkhwa 7.2 1,908 41.7 347 Balochistan 5.8 568 35.2 151 ICT Islamabad 38.5 64 49.1 18 Gilgit Baltistan 4.4 94 14.9 18 Education No education 3.9 7,736 11.8 905 Primary 11.8 2,156 31.7 657 Middle 17.5 993 42.9 525 Secondary 22.2 1,413 48.9 557 Higher 33.8 1,260 65.7 491 Wealth quintile Lowest 1.9 2,589 10.1 607 Second 4.3 2,676 27.8 574 Middle 10.2 2,700 37.3 567 Fourth 12.8 2,789 45.5 713 Highest 24.1 2,804 56.3 673 Total 15-49 10.8 13,558 36.2 3,134 Note: Figures in parentheses are based on 25-49 unweighted cases. 12.7 SELF-REPORTING OF SEXUALLY TRANSMITTED INFECTIONS (STIS) Information about the prevalence of sexually transmitted infections (STIs) is useful not only as a marker of unprotected sexual intercourse but also as a cofactor for HIV transmission. STIs are closely associated with HIV because they increase the likelihood of contracting HIV and share similar risk factors. The 2012-13 PDHS asked ever-married women and men age 15-49 whether, in the past 12 months, they had contracted a disease through sexual contact. Women were also asked if they had symptoms of an STI (a bad-smelling, abnormal discharge from the vagina or a genital sore or ulcer). It should be noted that although these symptoms are useful in identifying STIs, they may be misinterpreted in women because women may experience reproductive tract infections unrelated to STIs that produce a genital discharge. Table 12.7 shows that the prevalence of self-reported STIs among women and men in Pakistan is small. Two percent of women and a negligible proportion (0.4 percent) of men report having had an STI in the 12 months prior to the survey. It is likely that these figures underestimate the actual prevalence of STIs among the sexually active population in Pakistan, as many STI symptoms are not easily recognized and many STIs do not have visible symptoms. 196 • HIV/AIDS-Related Knowledge, Attitudes, and Behavior Table 12.7 Self-reported prevalence of sexually transmitted infections (STIs) and STI symptoms Among ever-married women and ever-married men age 15-49 who ever had sexual intercourse, the percentage reporting having an STI and/or symptoms of an STI in the past 12 months, by background characteristics, Pakistan 2012-13 Percentage of women who reported having in the past 12 months: Percentage of men who reported having in the past 12 months: Background characteristic STI Bad-smelling/ abnormal genital discharge Genital sore/ulcer STI/genital discharge/ sore or ulcer Number of women STI Number of men Age 15-24 2.3 12.8 7.5 15.4 2,711 1.7 255 15-19 2.1 11.2 7.1 13.5 605 (3.0) 36 20-24 2.3 13.2 7.6 16.0 2,106 1.4 219 25-29 2.4 14.3 5.9 16.3 2,724 0.1 521 30-39 2.2 17.0 7.8 19.4 4,755 0.5 1,234 40-49 1.4 11.7 6.2 14.1 3,368 0.3 1,124 Marital status Married 2.1 14.6 7.1 17.0 12,937 0.4 3,071 Divorced/separated/ widowed 0.3 8.5 3.3 9.4 621 (3.1) 63 Male circumcision Don’t know/missing na na na na na 0.4 3,134 Residence Urban 1.7 13.3 7.1 16.2 4,536 0.6 1,107 Rural 2.2 14.8 6.9 17.0 9,022 0.4 2,027 Region Punjab 1.2 13.4 6.1 16.1 7,790 0.3 1,804 Sindh 0.7 6.8 3.2 8.4 3,133 0.7 796 Khyber Pakhtunkhwa 8.3 27.0 16.4 29.9 1,908 0.4 347 Balochistan 0.7 23.9 8.2 25.1 568 1.1 151 ICT Islamabad 2.5 21.0 11.4 26.6 64 1.2 18 Gilgit Baltistan 0.0 14.6 2.4 15.5 94 0.0 18 Education No education 2.1 14.3 7.0 16.5 7,736 0.0 905 Primary 2.0 13.9 8.1 16.8 2,156 0.4 657 Middle 2.4 13.2 6.8 16.6 993 1.0 525 Secondary 1.9 16.2 7.3 19.2 1,413 0.1 557 Higher 1.8 13.2 4.8 15.2 1,260 1.0 491 Wealth quintile Lowest 1.4 13.6 5.9 15.8 2,589 0.2 607 Second 3.1 17.0 9.0 19.6 2,676 0.4 574 Middle 2.3 14.1 6.3 15.7 2,700 0.9 567 Fourth 1.8 14.0 7.2 17.0 2,789 0.3 713 Highest 1.6 12.7 6.5 15.5 2,804 0.4 673 Total 2.0 14.3 7.0 16.7 13,558 0.4 3,134 Note: Figures in parentheses are based on 25-49 unweighted cases. na = Not applicable Seventeen percent of women report having had an STI and/or symptoms of an STI in the 12 months prior to the survey. Women who report STI symptoms are more likely to say they have had a bad- smelling or abnormal genital discharge (14 percent) than a genital ulcer or sore (7 percent). The percentage of women reporting an STI and/or STI symptoms is highest in Khyber Pakhtunkhwa (30 percent) and lowest in Sindh (8 percent). When respondents reported having an STI or STI symptoms in the past 12 months, they were asked whether they sought any advice or treatment. Figure 12.2 shows that 51 percent of women sought no advice or treatment, while 41 percent sought advice or treatment from a clinic, hospital, private doctor, or other health professional. The figure excludes the findings for men as the results were based on few cases and were not representative. HIV/AIDS-Related Knowledge, Attitudes, and Behavior • 197 Figure 12.2 Women seeking treatment for STIs 41 2 6 51 Clinic/hospital/private doctor/other health professional Advice or medicine from shop/pharmacy Advice or treatment from any other source No advice or treatment Percentage PDHS 2012-13 12.8 PREVALENCE OF MEDICAL INJECTIONS Use of non-sterile injections in a health care setting can contribute to the transmission of blood- borne pathogens. To measure the potential risk of transmission of HIV and other diseases associated with medical injections, respondents in the 2012-13 PDHS were asked whether they had received an injection in the past 12 months; if so, they were asked how many injections they had received and whether their last injection was given with a syringe from a newly opened package. Table 12.8 shows the reported prevalence of medical injections among ever-married women and men age 15-49. Sixty-one percent of women and 53 percent of men reported receiving a medical injection from a health worker (doctor, nurse, pharmacist, dentist, or other health professional) during the 12-month period preceding the survey. On average, both women and men received five medical injections during the 12-month period. The vast majority of women (85 percent) and men (90 percent) reported that the last injection was given with a syringe from a newly opened package. Differentials by background characteristics among both women and men are generally small with the exception of differentials by region. Respondents in Gilgit Baltistan were least likely to receive a medical injection in the last 12 months (24 percent of women and 16 percent of men) and received the fewest average number of injections. Respondents in Balochistan were least likely to report having received their last injection from a syringe and needle taken from a new, unopened package (68 percent of women and 58 percent of men). 198 • HIV/AIDS-Related Knowledge, Attitudes, and Behavior Table 12.8 Prevalence of medical injections Percentage of ever-married women and men age 15-49 who received at least one medical injection in the last 12 months, the average number of medical injections per person in the last 12 months, and among those who received a medical injection, the percentage of last medical injections for which the syringe and needle were taken from a new, unopened package, by background characteristics, Pakistan 2012-13 Women Men Background characteristic Percentage who received a medical injection in the last 12 months Average number of medical injections per person in the last 12 months Number of respondents For last injection, syringe and needle taken from a new, unopened package Number of respondents receiving medical injections in the last 12 months Percentage who received a medical injection in the last 12 months Average number of medical injections per person in the last 12 months Number of respondents For last injection, syringe and needle taken from a new, unopened package Number of respondents receiving medical injections in the last 12 months Age 15-24 66.1 4.9 2,711 83.3 1,791 50.6 4.9 255 90.0 129 15-19 63.8 4.5 605 82.2 386 (25.9) (3.2) 36 * 9 20-24 66.7 5.0 2,106 83.6 1,405 54.7 5.1 219 90.5 120 25-29 61.7 4.5 2,724 86.2 1,680 56.9 5.4 521 89.3 296 30-39 60.4 5.4 4,755 84.8 2,872 50.6 4.2 1,234 90.1 624 40-49 55.7 6.7 3,368 86.4 1,875 54.0 5.5 1,124 91.1 608 Marital status Married 61.0 5.4 12,937 85.0 7,888 53.2 4.9 3,071 90.3 1,633 Divorced/separated/ widowed 53.1 7.3 621 87.2 330 (38.2) (3.4) 63 (88.8) 24 Residence Urban 58.5 4.7 4,536 91.4 2,656 49.9 4.4 1,107 93.0 553 Rural 61.6 5.8 9,022 82.1 5,562 54.5 5.2 2,027 89.0 1,104 Region Punjab 59.5 5.5 7,790 89.8 4,635 51.1 4.9 1,804 96.0 922 Sindh 66.3 4.7 3,133 81.6 2,076 55.1 5.3 796 79.9 439 Khyber Pakhtunkhwa 68.0 7.9 1,908 76.0 1,297 63.3 4.8 347 97.4 220 Balochistan 27.5 2.0 568 68.0 156 46.0 4.3 151 58.3 69 ICT Islamabad 49.8 3.3 64 91.1 32 25.8 1.2 18 96.2 5 Gilgit Baltistan 23.7 1.0 94 85.0 22 15.9 0.5 18 (94.5) 3 Education No education 59.4 6.0 7,736 79.8 4,595 54.0 6.7 905 83.0 488 Primary 65.7 5.4 2,156 89.1 1,416 56.2 4.6 657 88.6 369 Middle 64.7 5.2 993 91.8 643 57.1 5.2 525 94.7 300 Secondary 62.8 4.8 1,413 92.9 888 51.5 3.9 557 97.2 287 Higher 53.7 3.0 1,260 96.0 677 43.3 2.9 491 94.4 213 Wealth quintile Lowest 59.9 5.0 2,589 73.1 1,550 58.5 5.7 607 75.3 355 Second 61.0 6.2 2,676 79.5 1,633 55.2 5.8 574 91.6 317 Middle 61.8 5.8 2,700 86.7 1,669 50.5 4.4 567 93.4 287 Fourth 63.2 5.9 2,789 91.7 1,763 54.0 4.8 713 97.1 385 Highest 57.1 4.3 2,804 93.6 1,602 46.6 4.0 673 94.8 314 Total 60.6 5.4 13,558 85.1 8,218 52.9 4.9 3,134 90.3 1,657 Note: Medical injections are those given by a doctor, nurse, pharmacist, dentist, or other health worker. 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. Women’s Empowerment and Demographic and Health Outcomes • 199 WOMEN’S EMPOWERMENT AND DEMOGRAPHIC AND HEALTH OUTCOMES 13 he concept of women’s empowerment has recently gained the attention of development partners, policymakers, planners, and researchers all over the world. It is unanimously agreed that balanced growth is not attainable without empowering women, who constitute half of the world’s population. In the 2012-13 PDHS, efforts were made to understand women’s empowerment with respect to health outcomes. Empowerment is a blend of agency, resources, and achievements (Kabeer, 1999). Although the terms “empowerment” and “autonomy” are often used interchangeably, some differentiate the two by defining autonomy as the freedom to do certain things and empowerment as resisting denial of one’s rights (Dixon-Mueller, 1998). Others define empowerment as the process of being able to take charge of one’s own life (Malhotra and Mather, 1997). According to the 1994 International Conference on Population and Development, “advancing gender equality and equity and the empowerment of women and the elimination of all kinds of violence against women, and ensuring women’s ability to control their own fertility…are cornerstones of population and development-related programs” (United Nations, 1994). In addition, Article 34 of the Constitution of Pakistan states that “steps shall be taken to ensure full participation of women in all spheres of national life” (Government of Pakistan, 1973). The 2012-13 PDHS collected data on the status of women including information on gender differences in access to and control over cash earnings, ownership of assets, relative earnings of husbands and wives, participation in household decisionmaking, and women’s attitudes toward wife beating. The data discussed in Chapter 3 showed that women in Pakistan are predominantly engaged in agricultural work and are much less likely than men to have skilled manual jobs. Furthermore, women lag behind men in educational attainment, literacy, and exposure to mass media, all of which are critical contributors to women’s empowerment. Two separate indices were developed to assess women’s empowerment status, one based on the number of household decisions in which women participate and the other based on the number of situations in which they believe wife beating is justified. Women’s rankings on these two indices are examined with respect to selected demographic and health outcomes including contraceptive use, ideal T Key Findings • More than half of currently married women who earn cash make independent decisions about how to use their earnings, while only 9 percent say they decide solely about using their husband’s earnings. • Only 11 percent of ever-married women own a house, either alone or jointly, and only 4 percent own land. • Only 38 percent of currently married women participate jointly with their husbands in making decisions pertaining to their own health care, major household purchases, and visits to their family or relatives. • Contraceptive use is positively associated with women’s empowerment. • Unmet need for family planning decreases with increasing women’s empowerment. • Access to antenatal care, delivery assistance from a skilled provider, and postnatal care within the first two days after delivery increase with increasing women’s empowerment. 200 • Women’s Empowerment and Demographic and Health Outcomes family size, unmet need for contraception, early childhood mortality, and receipt of health care services during pregnancy, at delivery, and in the postnatal period. 13.1 EMPLOYMENT AND FORM OF EARNINGS Economic empowerment gives women an opportunity for increased participation in family decisionmaking, and it is expected that women who are employed and who receive cash earnings are more likely to have control over household resources. Table 13.1 shows the percentage of currently married women and men age 15-49 who were employed at any time in the 12 months preceding the survey and the percent distribution of employed women and men by the type of earnings they received (cash only, cash and in-kind, in-kind only), if any. It can be seen that 29 percent of women were employed in the 12 months preceding the survey, as compared with 98 percent of men. Women age 15-24 are slightly less likely than older women to be employed, while there is not much variation by age among men. Employed women and men differ greatly in the types of earnings they receive for their work. Eighty-seven percent of men receive cash only and 12 percent receive cash and in-kind payment, as compared with 71 percent of women receiving cash only and 6 percent receiving cash and in-kind payment. Fifteen percent of women are not paid for their work at all, as compared with less than 1 percent of men. Thus, not only are currently married women much less likely than currently married men to be employed, they are also much less likely to be paid for the work they perform. It is encouraging to note that the proportion of women who are employed has increased from 25 percent in 2006-07 to 29 percent in 2012-13 (National Institute of Population Studies [NIPS] and Macro International Inc., 2008). Table 13.1 Employment and cash earnings of currently married women and men Percentage of currently married women and men age 15-49 who were employed at any time in the past 12 months and the percent distribution of currently married women and men employed in the past 12 months by type of earnings, according to age, Pakistan 2012-13 Among currently married respondents: Percent distribution of currently married respondents employed in the past 12 months, by type of earnings Total Number of respondentsAge Percentage employed in past 12 months Number of respondents Cash only Cash and in- kind In-kind only Not paid Missing/don’t know WOMEN 15-19 24.5 594 57.8 9.7 14.6 17.9 0.0 100.0 145 20-24 22.8 2,053 69.0 6.8 6.8 17.3 0.0 100.0 467 25-29 28.8 2,663 76.4 5.9 6.4 11.3 0.0 100.0 766 30-34 28.3 2,454 70.4 6.0 9.7 13.8 0.0 100.0 695 35-39 34.1 2,137 69.5 8.1 9.7 12.5 0.3 100.0 729 40-44 30.3 1,617 72.2 5.8 6.7 15.2 0.0 100.0 490 45-49 27.9 1,419 70.8 4.3 4.2 20.6 0.0 100.0 396 Total 28.5 12,937 71.1 6.4 7.9 14.6 0.1 100.0 3,689 MEN 15-19 (96.4) 36 (86.1) (13.9) (0.0) (0.0) (0.0) 100.0 35 20-24 93.5 209 77.9 14.9 3.6 3.5 0.0 100.0 195 25-29 97.7 516 88.2 10.4 0.6 0.6 0.2 100.0 504 30-34 99.2 636 88.1 9.8 2.1 0.0 0.0 100.0 631 35-39 99.1 579 87.4 11.8 0.8 0.0 0.0 100.0 574 40-44 97.9 516 86.9 11.4 1.0 0.7 0.0 100.0 505 45-49 97.6 580 85.3 13.1 1.6 0.0 0.0 100.0 566 Total 98.0 3,071 86.6 11.5 1.4 0.5 0.0 100.0 3,009 Note: Figures in parentheses are based on 25-49 unweighted cases. Women’s Empowerment and Demographic and Health Outcomes • 201 13.2 WOMEN’S CONTROL OVER THEIR OWN EARNINGS AND RELATIVE MAGNITUDE OF WOMEN’S EARNINGS Women’s equal access to financial resources has become a human rights issue and is considered to be an important mechanism for reducing women’s poverty; consequently, it has been an explicit focus of a variety of human rights instruments. Control over cash earnings is another dimension of empowerment. In the 2012-13 PDHS, currently married women who earn cash for their work were asked who the main decisionmaker is regarding the use of their earnings. They were also asked about the relative magnitude of their earnings compared with their husband’s earnings. This information provides insight into women’s empowerment within the family and the extent of their control over resources. Table 13.2.1 Control over women’s cash earnings and relative magnitude of women’s cash earnings Percent distribution of currently married women age 15-49 who received cash earnings for employment in the 12 months preceding the survey by person who decides how wife’s cash earnings are used and by whether she earned more or less than her husband, according to background characteristics, Pakistan 2012-13 Person who decides how the wife’s cash earnings are used: Total Wife’s cash earnings compared with husband’s cash earnings: Total Number of women Background characteristic Mainly wife Wife and husband jointly Mainly husband Other Missing More Less About the same Husband has no earnings Don’t know/ missing Age 15-19 49.3 24.7 4.5 20.1 1.4 100.0 0.0 35.8 6.2 56.6 1.4 100.0 98 20-24 44.9 31.5 14.0 9.4 0.1 100.0 3.5 54.6 10.2 30.9 0.9 100.0 354 25-29 50.5 35.4 10.6 3.2 0.3 100.0 6.4 73.6 4.8 14.6 0.6 100.0 630 30-34 51.5 37.2 9.8 1.6 0.0 100.0 6.8 74.2 7.1 11.3 0.5 100.0 531 35-39 51.5 38.5 8.8 0.8 0.4 100.0 6.0 78.2 8.5 6.9 0.4 100.0 566 40-44 58.5 33.5 7.6 0.0 0.5 100.0 11.8 74.4 8.1 4.8 0.9 100.0 382 45-49 55.6 33.6 9.0 1.1 0.7 100.0 10.7 70.2 9.6 8.2 1.2 100.0 298 Number of living children 0 46.9 30.2 8.6 13.7 0.6 100.0 3.6 50.1 6.1 39.0 1.2 100.0 355 1-2 49.1 34.4 12.5 3.9 0.0 100.0 7.4 67.0 9.1 16.2 0.2 100.0 745 3-4 55.6 36.1 6.7 0.9 0.6 100.0 7.8 77.0 6.5 7.6 1.1 100.0 867 5+ 52.1 36.4 10.8 0.5 0.2 100.0 7.2 76.0 8.1 8.2 0.6 100.0 893 Residence Urban 63.8 29.0 4.9 1.9 0.5 100.0 8.9 70.2 9.5 10.3 1.1 100.0 781 Rural 47.2 37.3 11.6 3.6 0.3 100.0 6.3 70.9 6.9 15.3 0.6 100.0 2,079 Region Punjab 52.5 37.9 5.8 3.4 0.3 100.0 6.9 70.0 9.1 13.3 0.7 100.0 1,768 Sindh 52.2 31.7 13.9 2.2 0.1 100.0 7.1 73.1 4.6 14.9 0.3 100.0 892 Khyber Pakhtunkhwa 57.8 23.1 12.8 4.1 2.3 100.0 6.5 69.0 6.4 15.5 2.5 100.0 112 Balochistan 17.7 24.0 51.6 5.9 0.8 100.0 6.0 64.0 10.9 15.3 3.8 100.0 72 ICT Islamabad 51.6 38.3 8.6 1.4 0.0 100.0 13.7 61.1 18.9 5.6 0.7 100.0 11 Gilgit Baltistan 39.3 44.2 2.4 9.6 4.5 100.0 25.5 52.0 2.9 15.1 4.5 100.0 4 Education No education 47.5 37.2 11.8 3.1 0.4 100.0 5.4 73.2 7.6 12.9 0.8 100.0 1,930 Primary 61.8 27.2 7.0 3.5 0.5 100.0 3.8 70.1 6.2 19.5 0.5 100.0 395 Middle 54.0 37.8 7.5 0.3 0.5 100.0 9.0 68.9 10.4 11.2 0.6 100.0 120 Secondary 66.5 27.6 2.0 3.8 0.0 100.0 11.8 67.1 5.5 15.6 0.0 100.0 159 Higher 57.5 33.9 4.6 3.8 0.1 100.0 20.2 56.1 9.8 12.9 1.0 100.0 256 Wealth quintile Lowest 40.3 38.6 17.6 3.2 0.2 100.0 4.0 73.6 8.7 13.0 0.7 100.0 918 Second 51.6 38.3 7.3 2.4 0.4 100.0 7.8 72.0 7.1 12.7 0.4 100.0 642 Middle 56.2 36.2 6.1 1.2 0.3 100.0 6.5 70.5 6.1 16.0 1.0 100.0 534 Fourth 59.4 27.2 5.8 6.8 0.9 100.0 7.6 67.6 6.8 17.0 0.9 100.0 436 Highest 66.4 27.4 3.6 2.5 0.0 100.0 13.9 64.9 9.3 11.3 0.6 100.0 329 Total 51.7 35.0 9.7 3.1 0.3 100.0 7.0 70.7 7.6 13.9 0.7 100.0 2,860 Table 13.2.1 shows the percent distribution of currently married women who received cash earnings in the 12 months before the survey, according to the person who controls their earnings and their perception of the magnitude of their earnings relative to those of their husband. A little over half (52 percent) of currently married women who earn cash said that they themselves mainly decide on how their earnings are spent, while more than one-third indicated that the decision is made jointly with their husbands and 10 percent reported that their husbands mainly make the decision alone. The proportion of married women who mainly decide themselves how to use their earnings shows a slight tendency to increase with the age of the woman. Women with three to four children are more likely 202 • Women’s Empowerment and Demographic and Health Outcomes to mainly decide how to use their cash earnings than women with one to two children and those with no children. Women’s primary participation in the use of their own earnings varies by 17 percentage points between urban and rural areas. Educated women and those in the higher wealth quintiles are more likely than women with no education and those in the lower wealth quintiles to mainly make decisions on using their cash earnings. There are regional variations in who makes decisions on how women’s cash earnings are used. The proportion of married women who mainly decide on the use of their earnings is highest in Khyber Pakhtunkhwa (58 percent) and lowest in Balochistan (18 percent). More than half of married women in Balochistan who earn cash for their work say that their husbands are the ones who mainly decide how their earnings are used. Table 13.2.1 also shows women’s perceptions of their cash earnings relative to their husbands’ earnings. Among currently married women who earn cash, 71 percent say that they earn less than their husbands, 7 percent say that they earn more than their husbands, and 8 percent say that they earn about the same amount as their husbands. Thus, 15 percent of women who have cash earnings in Pakistan earn about the same as or more than their husbands. Fourteen percent of women say their husbands have no earnings. The proportion of currently married women who are employed for cash and earn about the same as or more than their husbands generally increases with increasing age, wealth, and education and is higher among urban than rural women. ICT Islamabad has the highest proportion of married women earning the same as or more than their husbands (33 percent), followed by Gilgit Baltistan (28 percent). 13.3 CONTROL OVER HUSBANDS’ EARNINGS Currently married men age 15-49 who receive cash earnings were asked who—the men themselves, their wife, the husband and wife jointly, or someone else—mainly decides how their own cash earnings are used. In addition, currently married women were asked who decides how their husbands’ cash earnings are used. Table 13.2.2 shows that 38 percent of men who receive cash earnings report that they decide jointly with their wives on how their earnings will be used, while 35 percent say they mainly make these decisions themselves. A small percentage of men say that decisions on how their earnings are used are mainly made by their wives (6 percent). The proportion of men who have earnings and who say that they make decisions about the use of their earnings jointly with their wives increases from 18 percent in the 20-24 age group to 47 percent in the 35-39 age group and remains more or less constant in the older age cohorts. The proportion of men making decisions alone about the use of their income is higher in rural areas (39 percent) than in urban areas (28 percent). Men with a higher education and those in the highest wealth quintile tend to more often allow their wife to mainly make decisions or make decisions jointly with their wife rather than on their own. The main decisionmaker regarding the use of men’s earnings varies greatly by region. Decisionmaking by men alone is highest in Balochistan (71 percent), followed by Khyber Pakhtunkhwa (68 percent). It is interesting to note that 16 percent of men in Sindh reported that the prime decisionmakers on spending of their earnings are their wives, the highest proportion among all regions. Table 13.2.2 also shows women’s responses about who mainly makes decisions about how to use their husbands’ earnings. Only currently married women whose husbands had cash earnings are included in this assessment. Nearly half (48 percent) of women whose husbands receive cash earnings say that they decide jointly with their husband about the use of his cash earnings, 9 percent say that they mainly decide by themselves, 40 percent say that their husband mainly decides alone, and 2 percent say that someone else decides. Women’s Empowerment and Demographic and Health Outcomes • 203 Table 13.2.2 Control over men’s cash earnings Percent distributions of currently married men age 15-49 who receive cash earnings and of currently married women age 15-49 whose husbands receive cash earnings, by person who decides how husband’s cash earnings are used, according to background characteristics, Pakistan 2012-13 Men Women Person who decides how husband’s cash earnings are used: Total Number of men Person who decides how husband’s cash earnings are used: Total Number of women Background characteristic Mainly wife Husband and wife jointly Mainly husband Other1 Missing Mainly wife Husband and wife jointly Mainly husband Other1 Missing Age 15-19 (0.0) (5.1) (18.2) (76.7) (0.0) 100.0 35 4.7 39.4 46.6 9.3 0.0 100.0 263 20-24 0.4 17.7 28.0 53.9 0.0 100.0 181 4.5 50.3 42.2 2.9 0.1 100.0 1,137 25-29 3.3 27.6 26.0 43.0 0.0 100.0 497 7.0 48.1 43.8 1.0 0.1 100.0 1,853 30-34 4.7 32.1 37.0 26.2 0.0 100.0 618 10.2 45.4 43.3 0.8 0.3 100.0 2,035 35-39 4.5 46.9 36.4 12.0 0.2 100.0 569 10.8 49.0 38.8 1.2 0.2 100.0 1,921 40-44 7.8 46.3 37.2 8.6 0.0 100.0 496 10.7 52.5 34.8 1.9 0.1 100.0 1,546 45-49 9.7 46.3 40.2 3.9 0.0 100.0 557 12.8 47.6 36.7 2.9 0.0 100.0 1,345 Number of living children 0 3.6 22.8 22.8 50.9 0.0 100.0 423 5.1 43.6 47.4 3.8 0.1 100.0 901 1-2 4.7 35.5 30.2 29.6 0.0 100.0 861 8.1 49.6 40.3 1.9 0.1 100.0 2,649 3-4 5.4 45.0 36.6 12.9 0.1 100.0 905 11.2 49.3 37.9 1.3 0.2 100.0 3,214 5+ 8.0 41.2 44.9 5.9 0.0 100.0 764 9.7 47.8 40.7 1.7 0.1 100.0 3,334 Residence Urban 12.3 42.7 27.5 17.4 0.0 100.0 1,075 11.5 51.2 35.8 1.2 0.4 100.0 3,488 Rural 1.7 35.4 39.2 23.7 0.0 100.0 1,878 8.2 46.9 42.7 2.1 0.0 100.0 6,611 Region Punjab 2.1 49.5 25.5 22.8 0.0 100.0 1,713 10.4 56.3 31.3 1.9 0.1 100.0 5,767 Sindh 16.1 26.9 35.3 21.7 0.0 100.0 749 7.5 42.7 48.7 0.8 0.3 100.0 2,391 Khyber Pakhtunkhwa 2.0 13.1 67.9 16.9 0.0 100.0 313 11.3 34.5 50.8 3.3 0.0 100.0 1,319 Balochistan 0.4 15.4 71.1 12.5 0.6 100.0 146 1.3 24.2 73.7 0.7 0.2 100.0 488 ICT Islamabad 4.3 34.9 35.6 25.2 0.0 100.0 17 10.2 50.8 37.6 0.6 0.8 100.0 54 Gilgit Baltistan 3.2 27.1 47.6 22.0 0.0 100.0 15 3.0 22.0 64.6 10.2 0.1 100.0 79 Education No education 4.1 39.2 37.6 19.0 0.1 100.0 832 8.6 45.8 43.5 2.0 0.1 100.0 6,017 Primary 6.7 38.0 31.9 23.4 0.0 100.0 626 10.3 51.7 36.3 1.7 0.0 100.0 1,508 Middle 3.1 39.3 35.2 22.4 0.0 100.0 496 11.3 51.0 36.6 0.9 0.2 100.0 686 Secondary 5.1 33.4 38.8 22.8 0.0 100.0 535 10.1 51.0 36.6 2.0 0.3 100.0 983 Higher 10.0 40.1 29.3 20.6 0.0 100.0 464 10.4 54.6 33.1 1.2 0.7 100.0 905 Wealth quintile Lowest 0.6 31.0 44.6 23.7 0.0 100.0 561 5.0 38.8 54.0 2.2 0.0 100.0 2,072 Second 2.5 41.6 36.9 18.9 0.2 100.0 521 8.7 50.4 39.4 1.6 0.0 100.0 2,033 Middle 4.4 38.5 34.1 23.0 0.0 100.0 530 10.6 51.3 36.0 2.1 0.1 100.0 1,948 Fourth 6.9 37.1 35.8 20.2 0.0 100.0 689 12.1 48.8 37.1 1.9 0.1 100.0 1,963 Highest 12.0 41.9 24.6 21.5 0.0 100.0 652 10.6 52.7 34.8 1.4 0.4 100.0 2,084 Total 5.6 38.1 34.9 21.4 0.0 100.0 2,953 9.4 48.4 40.3 1.8 0.1 100.0 10,099 Note: Figures in parentheses are based on 25-49 unweighted cases. 1 Includes family elders A comparison between women’s responses about the main decisionmaker regarding the use of their husbands’ earnings and men’s responses about the use of their own earnings shows variations. Men are much more likely than women to report that someone else in the family makes the decision on using their income (21 percent and 2 percent, respectively). In general, wives’ participation in decisionmaking increases with increasing age, education, and wealth and is higher in urban areas. The level of women’s earnings relative to their husbands’ earnings is expected to be associated with women’s control over their own and their husbands’ earnings. To examine this association, Table 13.3 shows the percent distribution of currently married women with cash earnings by the person who has the main say in the use of their earnings and the distribution of currently married women by the person who has the main say in the use of their husbands’ earnings, according to women’s perception of the size of their own earnings relative to their husbands’ earnings. Table 13.3 shows that women’s participation in the use of their own and their husbands’ earnings varies by their relative earnings; however, the variation is not necessarily as expected. Women who earn about the same as their husbands are more likely to jointly decide about the use of their own earnings (63 percent) and their husbands’ earnings (67 percent) than women in other categories. Women who earn more 204 • Women’s Empowerment and Demographic and Health Outcomes than their husbands are more likely than other women to be the main decisionmaker about the use of their husbands’ earnings (17 percent), but it is surprising to note that women who earn more and women who earn less than their husbands are about equally likely to be the main decisionmakers about their own earnings (51 percent versus 54 percent, respectively). Women who worked but had no cash earnings and women who did not work are far less likely to have a say in how their husbands’ earnings are used; close to half of these women say that their husbands mainly decide alone how to use their earnings. Table 13.3 Women’s control over their own earnings and over those of their husbands Percent distribution of currently married women age 15-49 with cash earnings in the last 12 months by person who decides how the wife’s cash earnings are used and percent distribution of currently married women age 15-49 whose husbands have cash earnings by person who decides how the husband’s cash earnings are used, according to the relation between wife’s and husband’s cash earnings, Pakistan 2012-13 Person who decides how the wife’s cash earnings are used: Total Number of women Person who decides how husband’s cash earnings are used: Total Number of women Women’s earnings relative to husband’s earnings Mainly wife Wife and husband jointly Mainly husband Other Missing Mainly wife Wife and husband jointly Mainly husband Other Missing More than husband 50.5 36.0 12.3 1.1 0.0 100.0 200 16.7 48.7 31.6 3.0 0.0 100.0 200 Less than husband 54.2 35.1 10.1 0.6 0.0 100.0 2,023 9.2 56.5 34.1 0.3 0.0 100.0 2,023 Same as husband 24.5 62.7 11.6 1.2 0.0 100.0 218 8.5 66.9 24.3 0.3 0.0 100.0 218 Husband has no cash earnings or did not work 56.3 20.5 5.2 17.9 0.0 100.0 398 na na na na na na 0 Woman worked but has no cash earnings na na na na na na 0 5.1 44.2 48.1 2.5 0.0 100.0 652 Woman did not work na na na na na na 0 9.6 45.9 42.1 2.2 0.2 100.0 6,986 Total1 51.7 35.0 9.7 3.1 0.3 100.0 2,860 9.4 48.4 40.3 1.8 0.1 100.0 10,099 na = Not applicable 1 Includes cases where a woman does not know whether she earned more or less than her husband 13.4 WOMEN’S AND MEN’S OWNERSHIP OF SELECTED ASSETS Ownership of assets, particularly high-value assets, has many beneficial effects for households, including protection against financial ruin. Women’s individual ownership of assets provides economic empowerment and protection in the case of marital dissolution or abandonment. The 2012-13 PDHS collected information on women’s and men’s ownership (alone, jointly, and alone and jointly) of two high- value assets, namely land and a house. As shown in Table 13.4.1, 89 percent of ever-married women age 15-49 do not own a house, and 96 percent do not own any land. Two percent each of women own a house alone and land alone, with the percentage of land ownership similar to that found in a NIPS study focusing on the status of women (NIPS, 2007). Women who own houses tend to own them jointly with someone else. Overall, only 11 percent of ever-married women in Pakistan own a house alone or jointly. The proportion of women who do not own a house shows little variation by age and residence, although it tends to decline slightly as education and wealth quintile increase. Variation by region, however, is strong. Women in Khyber Pakhtunkhwa and Gilgit Baltistan are far more likely to own a house (mainly jointly) than women in other regions. A higher proportion of men than women in Pakistan own a house or land. As shown in Table 13.4.2, 40 percent of ever-married men age 15-49 own a house alone, and 34 percent own a house jointly with someone else (as compared with only 2 percent and 7 percent of women, respectively). Similarly, 31 percent of men own land either alone or jointly, as compared with only 4 percent of women. Women’s disadvantage relative to men in asset ownership is evident in every demographic and socioeconomic category (Tables 13.4.1 and 13.4.2). Women’s Empowerment and Demographic and Health Outcomes • 205 Table 13.4.1 Ownership of assets: Women Percent distribution of ever-married women age 15-49 by ownership of housing and land, according to background characteristics, Pakistan 2012-13 Percentage who own a house: Percentage who do not own a house Missing Total Percentage who own land: Percentage who do not own land Missing Total Number of women Background characteristic Alone Jointly Alone and jointly Alone Jointly Alone and jointly Age 15-19 1.7 8.7 1.5 88.2 0.0 100.0 2.1 2.4 0.0 95.4 0.1 100.0 605 20-24 1.0 6.6 1.1 91.3 0.1 100.0 1.6 1.2 0.2 96.9 0.1 100.0 2,106 25-29 1.0 7.0 0.8 91.2 0.0 100.0 1.5 1.7 0.0 96.7 0.1 100.0 2,724 30-34 2.0 6.5 1.7 89.6 0.2 100.0 2.5 1.5 0.2 95.6 0.2 100.0 2,528 35-39 1.8 7.4 1.3 89.3 0.2 100.0 1.2 2.5 0.2 95.9 0.2 100.0 2,226 40-44 4.2 8.3 1.3 86.1 0.0 100.0 2.8 1.9 0.1 95.2 0.1 100.0 1,766 45-49 3.2 9.3 2.1 85.4 0.1 100.0 2.7 2.0 0.0 95.0 0.2 100.0 1,602 Residence Urban 3.1 6.7 1.4 88.5 0.3 100.0 1.8 1.1 0.1 96.6 0.3 100.0 4,536 Rural 1.5 7.8 1.3 89.4 0.0 100.0 2.0 2.1 0.1 95.6 0.1 100.0 9,022 Region Punjab 2.2 0.8 1.1 95.9 0.1 100.0 2.8 0.4 0.0 96.7 0.1 100.0 7,790 Sindh 2.2 5.8 2.3 89.5 0.2 100.0 0.6 0.6 0.1 98.5 0.2 100.0 3,133 Khyber Pakhtunkhwa 1.5 36.7 0.7 61.0 0.1 100.0 1.0 7.1 0.3 91.5 0.1 100.0 1,908 Balochistan 0.9 5.3 1.1 92.6 0.0 100.0 1.2 4.9 0.9 92.9 0.1 100.0 568 ICT Islamabad 3.9 4.2 4.8 86.4 0.7 100.0 6.4 2.0 0.6 90.1 0.9 100.0 64 Gilgit Baltistan 1.0 33.9 0.0 65.1 0.0 100.0 1.1 33.1 0.0 65.7 0.0 100.0 94 Education No education 1.3 7.8 1.3 89.6 0.0 100.0 1.3 2.0 0.1 96.5 0.1 100.0 7,736 Primary 1.9 5.4 1.5 91.2 0.0 100.0 1.7 1.3 0.0 96.8 0.2 100.0 2,156 Middle 2.4 5.2 1.1 91.3 0.1 100.0 2.2 1.7 0.1 96.0 0.1 100.0 993 Secondary 3.2 7.9 1.3 87.4 0.2 100.0 2.9 1.5 0.2 95.2 0.2 100.0 1,413 Higher 5.4 9.9 1.3 82.9 0.5 100.0 5.2 1.9 0.2 92.2 0.5 100.0 1,260 Wealth quintile Lowest 0.6 5.2 0.8 93.4 0.0 100.0 1.0 1.9 0.2 96.9 0.0 100.0 2,589 Second 1.8 9.1 2.2 86.8 0.0 100.0 2.0 2.4 0.0 95.4 0.1 100.0 2,676 Middle 1.8 7.7 1.2 89.2 0.0 100.0 1.2 1.3 0.2 97.1 0.1 100.0 2,700 Fourth 1.6 6.3 1.0 91.0 0.1 100.0 1.2 1.6 0.1 97.0 0.1 100.0 2,789 Highest 4.2 8.7 1.4 85.4 0.3 100.0 4.3 1.7 0.2 93.5 0.3 100.0 2,804 Total 2.0 7.4 1.3 89.1 0.1 100.0 2.0 1.8 0.1 96.0 0.1 100.0 13,558 Table 13.4.2 Ownership of assets: Men Percent distribution of ever-married men age 15-49 by ownership of housing and land, according to background characteristics, Pakistan 2012-13 Percentage who own a house: Percentage who do not own a house Missing Total Percentage who own land: Percentage who do not own land Missing Total Number Background characteristic Alone Jointly Alone and jointly Alone Jointly Alone and jointly Age 15-19 (16.7) (42.2) (2.8) (38.3) (0.0) 100.0 (0.0) (13.0) (0.0) (87.0) (0.0) 100.0 36 20-24 24.4 43.3 1.5 30.7 0.1 100.0 4.6 21.6 0.6 73.0 0.1 100.0 219 25-29 23.9 45.3 1.6 29.1 0.0 100.0 5.2 20.7 1.2 72.8 0.0 100.0 521 30-34 35.6 37.1 1.6 25.7 0.0 100.0 12.9 17.3 1.3 68.5 0.0 100.0 646 35-39 38.4 36.1 1.6 23.9 0.0 100.0 10.6 17.5 0.8 71.1 0.0 100.0 588 40-44 51.0 26.6 1.0 21.5 0.0 100.0 21.1 15.4 0.8 62.7 0.0 100.0 530 45-49 56.8 22.2 0.9 20.2 0.0 100.0 21.0 10.4 0.5 68.0 0.0 100.0 594 Residence Urban 27.2 34.3 1.5 37.0 0.0 100.0 9.2 9.0 0.6 81.2 0.0 100.0 1,107 Rural 46.7 34.1 1.3 17.9 0.0 100.0 15.7 20.7 1.1 62.6 0.0 100.0 2,027 Region Punjab 39.3 35.8 0.6 24.3 0.0 100.0 14.8 16.7 0.1 68.4 0.0 100.0 1,804 Sindh 39.3 32.1 0.9 27.7 0.0 100.0 7.1 13.4 0.5 79.0 0.0 100.0 796 Khyber Pakhtunkhwa 36.9 37.0 4.5 21.6 0.0 100.0 11.6 22.4 4.5 61.6 0.0 100.0 347 Balochistan 54.8 18.9 5.5 20.5 0.2 100.0 31.3 14.4 3.6 50.5 0.2 100.0 151 ICT Islamabad 39.1 29.1 2.6 28.6 0.6 100.0 12.2 26.5 3.2 57.8 0.3 100.0 18 Gilgit Baltistan 47.2 35.0 0.3 17.5 0.0 100.0 38.4 36.9 0.6 24.2 0.0 100.0 18 Education No education 47.4 26.0 0.8 25.8 0.0 100.0 15.6 10.8 0.6 73.0 0.0 100.0 905 Primary 42.0 33.4 1.1 23.4 0.0 100.0 11.3 16.3 0.8 71.6 0.0 100.0 657 Middle 32.0 41.1 1.4 25.5 0.0 100.0 15.5 17.8 0.8 65.9 0.0 100.0 525 Secondary 35.6 40.2 2.0 22.1 0.0 100.0 11.8 22.5 0.9 64.8 0.0 100.0 557 Higher 35.8 36.1 2.0 26.1 0.0 100.0 11.6 19.4 1.7 67.3 0.0 100.0 491 Wealth quintile Lowest 51.3 26.0 0.7 22.0 0.0 100.0 17.4 12.7 0.3 69.5 0.0 100.0 607 Second 46.7 28.1 0.6 24.6 0.0 100.0 15.4 15.8 0.8 68.0 0.0 100.0 574 Middle 43.7 32.6 2.1 21.5 0.1 100.0 13.1 17.8 1.3 67.7 0.1 100.0 567 Fourth 35.8 37.6 1.4 25.2 0.0 100.0 8.8 20.5 0.9 69.8 0.0 100.0 713 Highest 24.5 44.4 1.9 29.2 0.0 100.0 13.2 15.4 1.1 70.3 0.0 100.0 673 Total 39.8 34.2 1.4 24.7 0.0 100.0 13.4 16.5 0.9 69.2 0.0 100.0 3,134 Note: Figures in parentheses are based on 25-49 unweighted cases. 206 • Women’s Empowerment and Demographic and Health Outcomes Ownership of land and a house among men increases with age. The proportions of older women and older men owning these high-value assets alone are vastly different. For example, only 3 percent of women age 45-49 own a house and/or land alone (Table 13.4.1), whereas 57 percent of men age 45-49 own a house alone and 21 percent own land alone. Rural men are more likely than urban men to own either asset. Men in rural areas are more likely than men in urban areas to solely own a house (47 percent) and land (16 percent). Men’s sole ownership of a house decreases considerably with increasing education (from 47 percent among those with no education to 36 percent among those with a higher education), while joint ownership rises. This pattern is not evident in the case of land ownership. While sole ownership of a house decreases with wealth, joint ownership increases. Sole ownership of a house among men is highest in Balochistan (55 percent), and sole ownership of land is highest in Gilgit Baltistan (38 percent). 13.5 WOMEN’S PARTICIPATION IN DECISIONMAKING The ability of women to make decisions that affect their personal circumstances is an essential element of their empowerment and serves as an important contributor to their overall development. To assess currently married women’s decisionmaking autonomy, the 2012-13 PDHS collected information on their participation in three types of decisions: their own health care, making major household purchases, and visits to family or relatives. To provide an understanding of gender differences in household decisionmaking, currently married men were asked about their participation in decisions about their own health care and major household purchases. Table 13.5 shows the percent distribution of currently married women and men according to the person in the household who usually makes decisions concerning these matters. Women are considered to participate in decisionmaking if they make decisions alone or jointly with their husbands. Table 13.5 Participation in decisionmaking Percent distribution of currently married women and currently married men age 15-49 by person who usually makes decisions about various issues, Pakistan 2012-13 Decision Mainly wife Wife and husband jointly Mainly husband Someone else1 Missing Total Number of women WOMEN Own health care 11.1 40.8 30.5 17.5 0.1 100.0 12,937 Major household purchases 7.8 39.2 28.6 24.3 0.1 100.0 12,937 Visits to her family or relatives 8.7 41.2 26.2 23.8 0.1 100.0 12,937 MEN Own health care 4.5 46.3 28.8 20.3 0.0 100.0 3,071 Major household purchases 1.3 45.4 29.3 24.1 0.0 100.0 3,071 1 Includes family elders As shown in Table 13.5, 11 percent of married women say they mainly make decisions themselves regarding their own health care. On the contrary, 29 percent of men say they mainly make decisions themselves regarding their own health care. Eight percent of women and 29 percent of men say that they alone make decisions about major household purchases. Only 9 percent of women decide on their own regarding visits to their family or relatives. This finding depicts the typical Pakistani culture wherein the role of the family is very important and the practice of men and women making sole decisions is rare. About two in five women and men reported making joint decisions with their spouse regarding health care, the purchase of major household items, and, in the case of women, visits to her family and relatives. The role of other family members in such decisionmaking is also quite prominent. Women may have a say in some but not other decisions. The total number of decisions in which a woman participates (i.e., she mainly makes decisions or does so jointly with her husband) is one simple measure of her empowerment. Figure 13.1 presents the percentage of currently married women according to the number of decisions in which they participate. Thirty-nine percent of married women say they do not participate in any of the three decisions, while 12 percent participate in only one decision, 11 percent participate in two decisions, and 38 percent participate in all three decisions. Women’s Empowerment and Demographic and Health Outcomes • 207 Figure 13.1 Number of decisions in which currently married women participate 39 12 11 38 0 1 2 3 Number of decisions Percent of women PDHS 2012-13 Table 13.6.1 shows how currently married women’s participation (alone or jointly) in decisionmaking varies by background characteristics. The table presents the results for the three specific types of decisions asked about, namely the woman’s own health care, making major household purchases, and visits to her family or relatives. In addition, the table includes two summary indicators: the proportion of women involved in making all three decisions and the proportion not involved in making any of the three decisions. Table 13.6.1 shows that, overall, about half of married women participate in decisions regarding their own health care and visits to their family or relatives, and 47 percent participate in making major household purchases; however, only 38 percent report taking part in all three decisions. The percentage of married women participating in all three decisions tends to increase with age (from 10 percent to 56 percent). Half of women who are employed for cash take part in all three decisions, while women who are employed but do not earn cash (32 percent) and women who are not employed (35 percent) are less likely take part in all three decisions. Women in urban areas are more likely to participate in all three decisions (46 percent) than women in rural areas (35 percent). Women’s participation in all three decisions ranges from a low of 18 percent in Balochistan to a high of 45 percent in ICT Islamabad. Differentials by number of children show that participation of women in all three decisions increases with increasing number of children, from 19 percent among women with no children to 47 percent among women with five or more children. Participation in all three decisions varies minimally by education, although it is higher among women with a higher education. Forty-four percent of women in the highest wealth quintile participate in all three decisions, as compared with 29 percent of women in the lowest wealth quintile. At the provincial level, there is little urban-rural variation in women’s participation in decisionmaking in Punjab and Khyber Pakhtunkhwa (Table 13.6.1). However, differences with respect to participating in all three decisions are more prominent in Sindh (49 percent in urban areas versus 23 percent in rural areas) and Balochistan (26 percent in urban areas versus 16 percent in rural areas). 208 • Women’s Empowerment and Demographic and Health Outcomes Table 13.6.1 Women’s participation in decisionmaking by background characteristics Percentage of currently married women age 15-49 who usually make specific decisions either by themselves or jointly with their husband, by background characteristics, Pakistan 2012-13 Specific decisions All three decisions None of the three decisions Number of women Background characteristic Woman’s own health care Making major household purchases Visits to her family or relatives Age 15-19 25.7 14.9 18.2 9.6 65.5 594 20-24 35.3 27.8 30.4 21.1 57.1 2,053 25-29 45.6 38.4 39.9 29.1 44.8 2,663 30-34 53.5 48.3 52.1 38.8 36.4 2,454 35-39 60.5 56.7 60.4 48.0 29.9 2,137 40-44 66.2 66.4 68.3 56.2 23.4 1,617 45-49 66.9 65.2 69.9 55.3 22.4 1,419 Employment (last 12 months) Not employed 48.8 43.7 46.7 35.2 41.9 9,235 Employed for cash 64.8 59.6 62.0 49.8 25.2 2,860 Employed not for cash 42.8 40.4 44.9 32.2 46.3 828 Number of living children 0 33.4 23.7 27.2 18.5 59.3 1,728 1-2 47.0 40.7 42.3 32.2 44.1 3,856 3-4 58.6 54.9 57.7 45.1 31.3 3,772 5+ 59.1 56.7 60.9 46.9 30.0 3,580 Residence Urban 60.7 55.2 58.3 45.6 29.5 4,304 Rural 47.5 42.9 45.8 34.5 43.0 8,633 Region Punjab 58.3 54.7 56.4 44.1 31.0 7,374 Urban 61.3 58.5 60.5 47.5 27.3 2,402 Rural 56.8 52.8 54.4 42.5 32.8 4,972 Sindh 51.7 41.4 48.0 35.1 40.2 3,002 Urban 67.1 56.5 61.3 48.8 25.6 1,432 Rural 37.5 27.6 35.9 22.6 53.5 1,570 Khyber Pakhtunkhwa 35.3 33.5 34.9 25.8 56.3 1,855 Urban 35.4 31.6 34.5 23.0 55.1 308 Rural 35.3 33.9 34.9 26.4 56.5 1,547 Balochistan 24.8 21.3 24.5 18.0 70.3 553 Urban 34.1 30.3 33.2 26.2 59.6 110 Rural 22.5 19.0 22.3 15.9 72.9 443 ICT Islamabad 60.9 61.2 62.6 45.1 22.9 62 Gilgit Baltistan 41.4 31.1 44.7 25.0 49.2 91 Education No education 48.6 44.8 47.7 37.0 42.3 7,347 Primary 51.7 47.8 51.6 38.0 36.8 2,057 Middle 54.8 46.8 49.6 38.5 37.4 958 Secondary 57.6 48.8 51.4 38.4 33.0 1,351 Higher 63.6 56.7 58.9 45.0 25.7 1,225 Wealth quintile Lowest 41.5 36.0 39.8 29.2 50.2 2,501 Second 49.9 46.3 49.3 38.0 40.1 2,533 Middle 52.7 48.8 50.2 39.3 37.8 2,550 Fourth 54.1 48.5 51.5 39.9 36.6 2,677 Highest 60.8 54.7 58.1 44.0 28.7 2,676 Total 51.9 47.0 49.9 38.2 38.5 12,937 Note: Total includes 14 cases with missing information on employment status in the last 12 months. Table 13.6.2 presents data on currently married men’s participation (alone or jointly) in two types of decisions—their own health care and making major household purchases—by background characteristics. The table shows that three-fourths of men participate in decisions about their own health care and in decisions about major household purchases, while one-fifth do not participate in either of the two decisions. Overall, 70 percent of men participate in both of these decisions. The proportion of currently married men participating in both decisions increases sharply with age and number of living children, but there is a mixed pattern with respect to education and wealth. Men employed for cash are most likely to participate in both decisions, followed by those who are employed but do not earn cash and Women’s Empowerment and Demographic and Health Outcomes • 209 those who are not employed. Men’s participation in both decisions is very similar in rural and urban areas. By region, participation in both decisions ranges from 62 percent among men in ICT Islamabad to 77 percent among those in Balochistan. Table 13.6.2 Men’s participation in decisionmaking by background characteristics Percentage of currently married men age 15-49 who usually make specific decisions either alone or jointly with their wife, by background characteristics, Pakistan 2012-13 Specific decisions Both decisions Neither of the two decisions Number of men Background characteristic Man’s own health Making major household purchases Age 15-19 (21.4) (25.5) (19.1) (72.2) 36 20-24 43.1 40.6 36.5 52.8 209 25-29 55.1 52.7 47.3 39.5 516 30-34 71.9 72.0 65.9 22.0 636 35-39 85.7 84.8 81.1 10.6 579 40-44 88.0 86.4 83.7 9.4 516 45-49 89.4 91.7 86.9 5.8 580 Employment (last 12 months) Not employed 61.7 58.5 55.9 35.8 62 Employed for cash 75.5 75.1 70.5 19.8 2,953 Employed not for cash 72.8 67.2 66.2 26.1 55 Number of living children 0 48.6 45.4 41.0 47.0 453 1-2 67.6 66.1 60.3 26.6 900 3-4 83.3 84.1 80.1 12.7 924 5+ 89.3 89.9 86.0 6.8 794 Residence Urban 74.6 79.1 70.6 16.9 1,091 Rural 75.4 72.2 69.8 22.2 1,980 Region Punjab 76.7 75.6 73.5 21.1 1,761 Urban 80.0 80.6 78.1 17.5 609 Rural 75.0 73.0 71.0 23.1 1,152 Sindh 67.2 74.0 63.2 22.0 779 Urban 63.1 78.9 58.8 16.8 371 Rural 71.0 69.6 67.3 26.7 408 Khyber Pakhtunkhwa 82.0 69.1 65.7 14.5 345 Urban 83.9 67.7 65.0 13.4 65 Rural 81.6 69.4 65.8 14.8 280 Balochistan 81.8 80.4 76.8 14.6 150 Urban 87.3 82.3 80.7 11.2 32 Rural 80.3 79.9 75.7 15.5 119 ICT Islamabad 67.1 68.8 62.2 26.3 18 Gilgit Baltistan 82.3 69.5 67.6 15.7 18 Education No education 79.6 78.3 75.7 17.8 869 Primary 71.3 72.4 66.2 22.5 652 Middle 75.2 71.6 68.2 21.5 516 Secondary 71.9 73.3 67.9 22.7 548 Higher 75.8 75.9 69.5 17.8 487 Wealth quintile Lowest 78.3 74.9 74.0 20.8 591 Second 78.0 74.8 72.1 19.3 557 Middle 74.4 71.3 67.6 21.8 549 Fourth 75.4 76.8 72.4 20.2 706 Highest 70.2 74.8 64.4 19.5 668 Total 15-49 75.1 74.6 70.1 20.3 3,071 Note: Total includes 2 cases with missing information on employment status in the last 12 months. Figures in parentheses are based on 25-49 unweighted cases. 210 • Women’s Empowerment and Demographic and Health Outcomes 13.6 ATTITUDES TOWARD WIFE BEATING The critical problems that women face are many and diverse. Among the most serious is violence, and Pakistan is no exception in this regard. One of the most common forms of violence against women worldwide is abuse by their husband or partner (Heise et al., 1999). The 2012-13 PDHS gathered information on women’s attitudes toward wife beating by asking ever-married women whether a husband is justified in hitting or beating his wife under a series of six circumstances: if she burns the food, if she argues with him, if she goes out without telling him, if she neglects the children, if she refuses to have sexual intercourse with him, and if she neglects her in-laws. A woman’s attitude toward wife beating is considered a proxy for her perception of women’s status. A lower score on the “number of reasons wife beating is justified” empowerment indicator signals a greater sense of entitlement, self-esteem, and status and reflects positively on a woman’s sense of empowerment. Agreement with wife beating as justified indicates that a woman generally accepts the right of a man to control her behavior even by means of violence. Such a perception could act as a barrier to accessing health care for her children and herself and could have an impact on her general well-being. Table 13.7.1 shows the percentage of ever-married women age 15-49 who agree that a husband is justified in hitting or beating his wife for specific reasons, by background characteristics. Forty-three percent of women agree that a husband is justified in beating his wife for at least one of the reasons listed. The most widely accepted reason for wife beating among women in Pakistan is arguing with the husband (34 percent), followed closely by neglecting the children (31 percent), refusing to have sexual intercourse (31 percent), and going out without telling the husband (30 percent). Twenty-eight percent of women agree that a husband is justified in beating his wife if she neglects her in-laws. Similarly, 18 percent of women agree that a husband is justified in beating his wife if she burns the food. Women age 15-19 are more likely to agree with at least one reason for wife beating than older women. Agreement with at least one reason for wife beating does not differ by marital status. Women who are not employed (42 percent), those who reside in urban areas (28 percent) and ICT Islamabad (23 percent), those who have a higher education (15 percent), and those in the highest wealth quintile (19 percent) are least likely to agree with at least one reason for wife beating. With regard to urban-rural differentials within provinces, it is apparent that rural women in Khyber Pakhtunkhwa are most likely to agree that a husband is justified in beating his wife for at least one of the specified reasons (76 percent). High urban-rural differentials are also found in Punjab (25 percent and 42 percent, respectively) and Sindh (22 percent and 51 percent, respectively). Ever-married men were asked similar questions on wife beating to elicit their perceptions on domestic violence. The results are presented in Table 13.7.2. Overall, men are less likely than women to agree with at least one specified reason to justify wife beating (34 percent and 43 percent, respectively). Similar to the pattern among women, men are least likely to agree that burning the food is a valid reason to justify wife beating. They also show similar levels of support for the other five reasons (16-20 percent), although at much lower levels than among women. Among men, there is little variation by age in agreement with at least one reason for wife beating. Men who are employed and paid in cash (33 percent), those who reside in urban areas (25 percent) and ICT Islamabad (25 percent), those with a higher education (23 percent), and those in the highest wealth quintile (20 percent) are less likely than other men to agree with at least one reason for wife beating. Men in Khyber Pakhtunkhwa (73 percent) and Balochistan (67 percent) are most likely to justify wife beating for at least one of the specified reasons. The urban-rural differential within provinces regarding attitudes toward wife beating is highest in Sindh (25 percent and 59 percent, respectively). Women’s Empowerment and Demographic and Health Outcomes • 211 Table 13.7.1 Attitude toward wife beating: Women Percentage of ever-married women age 15-49 who agree that a husband is justified in hitting or beating his wife for specific reasons, by background characteristics, Pakistan 2012-13 Husband is justified in hitting or beating his wife if she: Percentage who agree with at least one specified reason Number of women Background characteristic Burns the food Argues with him Goes out without telling him Neglects the children Refuses to have sexual intercourse with him Neglects the in-laws Age 15-19 25.0 43.2 37.8 39.4 38.0 37.9 52.8 605 20-24 19.3 34.5 31.4 33.0 31.2 31.2 43.3 2,106 25-29 17.9 33.5 28.2 30.1 30.0 27.3 42.2 2,724 30-34 17.9 31.5 28.8 29.6 29.3 25.2 40.9 2,528 35-39 16.6 32.5 29.3 30.0 29.0 24.6 41.7 2,226 40-44 17.2 33.3 28.4 30.5 30.1 26.3 41.6 1,766 45-49 19.9 34.9 29.6 31.7 32.5 29.0 42.8 1,602 Employment (last 12 months) Not employed 16.9 33.0 29.3 30.8 29.8 27.2 41.7 9,594 Employed for cash 21.3 34.1 29.4 30.2 31.5 27.3 42.9 3,077 Employed not for cash 23.9 40.7 34.1 37.8 36.1 33.1 50.5 873 Number of living children 0 16.9 31.1 27.4 27.8 28.3 26.0 40.2 1,828 1-2 16.9 31.2 27.8 29.0 28.2 26.0 39.1 4,059 3-4 17.7 32.5 28.2 30.0 29.9 26.8 42.2 3,912 5+ 21.4 38.9 34.1 36.1 35.0 31.0 47.6 3,760 Marital status Married 18.2 33.8 29.5 31.1 30.5 27.6 42.5 12,937 Divorced/separated/ widowed 22.8 31.3 31.0 30.5 31.7 27.0 41.8 621 Residence Urban 8.9 18.8 16.6 16.9 16.6 14.0 27.5 4,536 Rural 23.1 41.2 36.2 38.2 37.6 34.4 50.1 9,022 Region Punjab 16.6 27.0 22.5 25.7 24.1 22.6 36.3 7,790 Urban 8.7 15.4 14.3 15.0 13.9 12.2 25.0 2,526 Rural 20.4 32.5 26.4 30.9 28.9 27.6 41.7 5,264 Sindh 18.1 29.9 27.6 26.2 28.9 23.4 37.0 3,133 Urban 7.0 15.7 13.0 12.5 13.9 10.3 22.4 1,521 Rural 28.6 43.2 41.3 39.2 43.1 35.7 50.7 1,612 Khyber Pakhtunkhwa 25.7 64.9 59.5 59.1 58.9 54.4 73.5 1,908 Urban 17.8 53.6 45.3 47.0 45.2 40.4 62.1 320 Rural 27.2 67.2 62.4 61.5 61.7 57.2 75.8 1,588 Balochistan 16.6 39.9 34.0 33.9 30.9 25.7 51.3 568 Urban 14.5 38.2 32.3 31.1 31.0 26.0 51.1 114 Rural 17.1 40.3 34.4 34.6 30.9 25.6 51.3 454 ICT Islamabad 6.2 14.2 11.4 13.6 9.6 11.0 23.1 64 Gilgit Baltistan 46.8 62.9 64.3 63.1 61.4 63.1 76.4 94 Education No education 25.1 44.0 38.6 40.0 40.2 36.4 52.4 7,736 Primary 14.7 27.6 25.9 27.5 26.4 23.9 40.8 2,156 Middle 10.5 24.5 22.2 23.0 19.4 18.6 32.5 993 Secondary 6.0 15.2 11.2 13.4 12.5 10.5 22.8 1,413 Higher 3.4 9.0 7.1 8.6 7.8 6.0 14.7 1,260 Wealth quintile Lowest 28.2 45.5 41.1 42.5 43.2 38.2 53.6 2,589 Second 26.5 48.2 41.6 45.2 44.7 40.6 57.0 2,676 Middle 20.9 38.3 34.4 34.6 33.9 32.8 48.3 2,700 Fourth 13.3 25.9 22.6 24.3 22.9 20.2 36.0 2,789 Highest 4.2 12.3 10.0 10.6 9.8 7.8 19.2 2,804 Total 18.4 33.7 29.6 31.1 30.6 27.6 42.5 13,558 Note: Total includes 14 cases with missing information on employment status in the last 12 months. 212 • Women’s Empowerment and Demographic and Health Outcomes Table 13.7.2 Attitude toward wife beating: Men Percentage of ever-married men age 15-49 who agree that a husband is justified in hitting or beating his wife for specific reasons, by background characteristics, Pakistan 2012-13 Husband is justified in hitting or beating his wife if she: Percentage who agree with at least one specified reason Number Background characteristic Burns the food Argues with him Goes out without telling him Neglects the children Refuses to have sexual intercourse with him Neglects the in-laws Age 15-19 (10.4) (26.6) (28.0) (23.2) (23.4) (24.3) (33.3) 36 20-24 6.4 22.2 29.0 25.5 22.5 23.7 42.1 219 25-29 4.8 18.9 19.1 17.4 17.0 17.7 33.5 521 30-34 4.8 18.9 19.8 16.3 16.5 17.2 33.8 646 35-39 5.6 18.7 19.6 17.2 13.6 17.8 33.1 588 40-44 4.7 17.6 18.7 20.6 15.7 16.2 34.6 530 45-49 4.6 18.3 17.6 18.3 15.7 14.9 31.8 594 Employment (last 12 months) Not employed 5.9 21.8 26.6 24.6 19.6 12.7 43.3 64 Employed for cash 4.9 18.6 19.0 17.9 15.7 16.8 33.0 3,008 Employed not for cash 15.8 27.8 49.6 41.2 37.7 47.7 70.0 60 Number of living children 0 4.5 17.9 19.5 16.0 18.4 16.8 30.3 481 1-2 4.2 17.3 18.7 18.2 15.3 16.3 32.3 918 3-4 3.0 15.0 18.2 14.7 13.0 13.4 30.5 936 5+ 9.0 25.7 23.0 24.7 19.9 23.4 42.0 798 Marital status Married 5.2 18.8 19.8 18.7 16.3 17.5 34.0 3,071 Divorced/separated/ widowed (1.2) (22.0) (18.1) (9.1) (17.1) (9.5) (30.5) 63 Residence Urban 2.8 13.4 12.3 12.4 9.1 11.0 25.1 1,107 Rural 6.4 21.8 23.9 21.8 20.2 20.8 38.8 2,027 Region Punjab 2.1 9.9 9.9 8.9 3.1 8.2 19.7 1,804 Urban 1.1 9.0 7.4 8.6 2.4 8.2 19.2 618 Rural 2.6 10.3 11.2 9.0 3.5 8.3 19.9 1,186 Sindh 8.6 29.6 25.8 22.5 26.8 21.8 42.9 796 Urban 3.1 15.9 13.5 11.5 11.5 7.5 25.1 376 Rural 13.4 41.8 36.9 32.3 40.4 34.6 58.8 420 Khyber Pakhtunkhwa 2.8 30.9 50.3 53.3 44.3 45.3 72.9 347 Urban 5.4 29.4 42.7 44.3 34.9 45.3 62.1 67 Rural 2.1 31.3 52.2 55.4 46.6 45.3 75.4 281 Balochistan 28.7 40.9 36.3 33.1 53.1 37.5 66.5 151 Urban 26.4 36.2 29.5 29.4 54.0 31.9 60.7 32 Rural 29.4 42.1 38.1 34.1 52.9 38.9 68.0 119 ICT Islamabad 3.0 8.6 8.9 7.3 9.5 9.4 24.8 18 Gilgit Baltistan 3.6 36.3 28.0 19.1 28.9 27.9 54.9 18 Education No education 8.8 28.5 24.8 25.8 25.7 25.7 44.9 905 Primary 5.1 19.2 20.9 18.4 13.7 15.9 34.3 657 Middle 2.7 12.3 15.0 13.5 8.9 13.5 26.2 525 Secondary 3.8 17.0 19.5 17.0 15.4 15.5 32.8 557 Higher 2.3 9.8 14.5 12.0 11.3 9.9 22.9 491 Wealth quintile Lowest 12.0 33.8 34.0 29.0 33.7 32.9 54.1 607 Second 7.8 26.7 27.9 29.4 23.0 22.4 43.3 574 Middle 3.9 17.8 18.3 20.2 15.0 15.9 34.1 567 Fourth 1.3 11.0 11.9 10.3 6.6 9.7 22.8 713 Highest 1.6 7.9 9.6 6.8 6.2 8.3 19.6 673 Total 5.1 18.9 19.8 18.5 16.3 17.3 34.0 3,134 Women’s Empowerment and Demographic and Health Outcomes • 213 13.7 WOMEN’S EMPOWERMENT INDICATORS The two sets of empowerment indicators—women’s participation in making household decisions and their attitude toward wife beating—can be summarized into two separate indices. The first index shows the number of decisions (see Table 13.5 for the list of decisions) in which women participate alone or jointly with their husband. This index ranges from 0 to 3 and is positively related to women’s empowerment. It reflects the degree of decisionmaking control that women are able to exercise in areas that affect their own lives and environments. The second indicator, which ranges from 0 to 6, is the total number of reasons (see Table 13.7.1 for the list of reasons) for which the respondent feels that a husband is justified in beating his wife. A lower score on this indicator is interpreted as reflecting a greater sense of entitlement and self-esteem and higher status. Table 13.8 Indicators of women’s empowerment Percentage of currently married women age 15-49 who participate in all decisionmaking and the percentage who disagree with all of the reasons justifying wife beating, by value on each of the indicators of women’s empowerment, Pakistan 2012-13 Empowerment indicator Percentage who participate in all decisionmaking Percentage who disagree with all reasons justifying wife beating Number of women Number of decisions in which women participate1 0 na 46.8 4,983 1-2 na 59.7 3,016 3 na 67.5 4,938 Number of reasons for which wife beating is justified2 0 44.8 na 7,434 1-2 31.6 na 1,426 3-4 30.6 na 1,409 5-6 27.3 na 2,668 na = Not applicable 1 See Table 13.6.1 for the list of decisions. 2 See Table 13.7.1 for the list of reasons. In general, it is expected that women who participate in making household decisions are more likely to have gender-egalitarian beliefs and to reject wife beating. Table 13.8 provides an overview of how these two basic empowerment indices (number of decisions in which women participate and number of reasons for which wife beating is justified) relate to one another. As expected, women’s rejection of all reasons for wife beating increases with the number of decisions they participate in. Specifically, 47 percent of married women who participate in none of the decisions reject all of the reasons for wife beating, as compared with 68 percent of women who participate in all three decisions. Also, the proportion of women who participate in all three decisions varies uniformly with the number of reasons for which wife beating is justified. As expected, the percentage of women who participate in all three decisions is highest (45 percent) among those who do not agree with any reason for wife beating and falls to 27 percent among those who agree with five to six reasons for wife beating. 13.8 CURRENT USE OF CONTRACEPTION BY WOMEN’S EMPOWERMENT A woman’s desire and ability to control her fertility and the contraceptive method she chooses are likely to be affected by her status in the household, her self-image, and her sense of empowerment. A woman who feels that she is unable to control other aspects of her life may be less likely to feel that she can make and carry out decisions about her fertility. She may also feel the need to choose methods that can be hidden from others or that do not depend on her husband’s cooperation. Table 13.9 presents the 214 • Women’s Empowerment and Demographic and Health Outcomes distribution of currently married women age 15-49 by contraceptive method used, according to the two empowerment indices. Contraceptive use is positively associated with women’s participation in household decisionmaking. In particular, use of any method and use of any modern method are more prevalent among women who participate in all three decisions (44 percent and 33 percent, respectively) than among women who participate in none of the decisions (25 percent and 19 percent, respectively). Contraceptive use is inversely associated with the number of reasons for which women believe wife beating is justified. Specifically, use of any method and use of any modern method are more prevalent among women who reject wife beating (38 percent and 28 percent, respectively) than among women who cite five to six reasons for which wife beating is justified (27 percent and 20 percent, respectively). Table 13.9 Current use of contraception by women’s empowerment Percent distribution of currently married women age 15-49 by current contraceptive method, according to selected indicators of women’s status, Pakistan 2012-13 Any method Modern methods Any traditional method Not currently using Total Number of women Empowerment indicator Any modern method1 Female sterilization Male sterilization Temporary modern female methods1 Male condom Number of decisions in which women participate2 0 25.3 18.8 4.7 0.0 7.4 6.6 6.5 74.7 100.0 4,983 1-2 37.7 26.7 9.1 0.2 8.5 8.9 11.1 62.3 100.0 3,016 3 44.2 33.1 12.4 0.5 9.3 11.0 11.0 55.8 100.0 4,938 Number of reasons for which wife beating is justified3 0 38.0 28.0 9.1 0.2 7.9 10.9 10.0 62.0 100.0 7,434 1-2 40.2 29.7 9.7 0.4 10.7 8.8 10.5 59.8 100.0 1,426 3-4 32.3 24.3 8.5 0.9 7.7 7.2 8.0 67.7 100.0 1,409 5-6 27.4 19.9 7.1 0.1 8.9 3.9 7.5 72.6 100.0 2,668 Total 35.4 26.1 8.7 0.3 8.4 8.8 9.3 64.6 100.0 12,937 Note: If more than one method is used, only the most effective method is considered in this tabulation. 1 Pill, IUD, injectables, implants, female condom, diaphragm, foam/jelly, and lactational amenorrhea method 2 See Table 13.6.1 for the list of decisions. 3 See Table 13.7.1 for the list of reasons. 13.9 IDEAL FAMILY SIZE AND UNMET NEED BY WOMEN’S EMPOWERMENT The ability of women to make decisions effectively has important implications for their fertility preferences and for meeting their family-size goals. It is expected that more empowered women will want smaller families and be better able to negotiate decisions regarding fertility and family planning. Hence, unmet need for family planning, which reflects women’s unsatisfied need for contraception, should be lower among more empowered women. An increase in women’s status and empowerment is recognized as important for efforts to reduce fertility through at least two main pathways: its negative association with desired family size and its positive association with a woman’s ability to meet family-size goals through the effective use of contraception. Table 13.10 shows how women’s ideal family size and their unmet need for family planning vary by the two indicators of women’s empowerment: number of decisions in which the woman participates and number of reasons for which the woman feels a husband is justified in beating his wife. Although mean ideal family size shows no uniform variation by the number of decisions in which women participate, it increases uniformly with the number of reasons for which women feel wife beating is justified. Women who agree that wife beating is not justified at all have a mean ideal family size of 3.9 Women’s Empowerment and Demographic and Health Outcomes • 215 children, as compared with 4.5 children among women who agree that wife beating is justified for five to six reasons. There is an association between participation in decisionmaking and unmet need for family planning. Women who participate in no household decisions have a higher unmet need for family planning (22 percent) than women who participate in one to two decisions or three decisions (19 percent and 18 percent, respectively). Unmet need is lowest among women who agree with one to two reasons for wife beating (17 percent) and increases to 25 percent among women who agree with five to six reasons. Table 13.10 Ideal number of children and unmet need for family planning by women’s empowerment Mean ideal number of children for women age 15-49 and the percentage of currently married women age 15-49 with an unmet need for family planning, by indicators of women’s empowerment, Pakistan 2012-13 Empowerment indicator Mean ideal number of children1 Number of women Percentage of currently married women with an unmet need for family planning Number of currently married women For spacing For limiting Total Number of decisions in which women participate2 0 4.3 4,756 12.7 9.7 22.4 4,983 1-2 3.9 2,874 8.5 10.9 19.4 3,016 3 4.0 4,794 5.1 13.0 18.1 4,938 Number of reasons for which wife beating is justified3 0 3.9 7,555 8.7 9.9 18.7 7,434 1-2 4.1 1,437 7.1 9.9 17.0 1,426 3-4 4.3 1,360 9.2 12.6 21.7 1,409 5-6 4.5 2,641 9.8 15.0 24.8 2,668 Total 4.1 12,992 8.8 11.3 20.1 12,937 1 Mean excludes respondents who gave non-numeric responses. 2 Restricted to currently married women. See Table 13.6.1 for the list of decisions. 3 See Table 13.7.1 for the list of reasons. 13.10 REPRODUCTIVE HEALTH CARE BY WOMEN’S EMPOWERMENT Table 13.11 examines whether empowered women are more likely to access antenatal, delivery, and postnatal care services from a skilled health provider. In societies where health care is widespread, women’s empowerment may not affect their access to reproductive health services. In other societies, however, increased empowerment is likely to enhance women’s ability to seek out and use health services from qualified health providers to better meet their own reproductive health goals, including the goal of safe motherhood. In Pakistan, skilled health providers include doctors, nurses, midwives, and lady health visitors, all of whom are qualified to provide antenatal care, delivery, and postnatal care services. The table includes only women who had a birth in the five years preceding the survey. Both indicators of women’s empowerment are related to women’s access to reproductive health care for their most recent birth. For example, the proportion of women receiving antenatal care from a skilled health provider increases from 69 percent among women who participate in no decisions to 80 percent among women who participate in one to two decisions before decreasing to 74 percent among women who participate in all three decisions. A similar pattern is observed among women receiving delivery assistance from a skilled provider. There is an increase of about 6 percentage points in the proportion of women who received postnatal care within two days of delivery between those with the lowest and highest values on the decisionmaking index. Women’s attitudes toward wife beating are also related to their use of all three health services. The proportions of women receiving all three types of care decline uniformly as the number of reasons they believe wife beating is justified increases. For example, women who believe that wife beating is not justified for any reason are more likely to receive skilled antenatal care than women who accept five to six 216 • Women’s Empowerment and Demographic and Health Outcomes reasons for wife beating (78 and 63 percent, respectively). There is an even larger decline among women receiving delivery care from a skilled provider, from 63 percent of those who reject wife beating to 42 percent of those who agree with wife beating for five to six reasons. Women who agree with five to six reasons justifying wife beating are also less likely to have receive postnatal care (46 percent) within the first two days of delivery from health personnel than women who reject all of the reasons for wife beating (65 percent). Table 13.11 Reproductive health care by women’s empowerment Percentage of women age 15-49 with a live birth in the five years preceding the survey who received antenatal care, delivery assistance, and postnatal care from health personnel for the most recent birth, by indicators of women’s empowerment, Pakistan 2012-13 Empowerment indicator Percentage receiving antenatal care from a skilled provider1 Percentage receiving delivery care from a skilled provider1 Received postnatal care from health personnel within the first two days after delivery2 Number of women with a child born in the last five years Number of decisions in which women participate3 0 68.5 51.9 54.0 3,166 1-2 79.9 59.2 60.7 1,744 3 74.4 56.3 60.3 2,440 Number of reasons for which wife beating is justified4 0 77.6 62.5 64.5 4,167 1-2 75.8 53.8 53.7 816 3-4 68.8 46.1 50.8 794 5-6 62.5 42.1 45.8 1,669 Total 73.1 55.2 57.7 7,446 1 “Skilled provider” includes doctor, nurse, midwife, or lady health visitor. 2 Includes women who received a postnatal checkup from a doctor, nurse, midwife, community health worker, or traditional birth attendant in the first 2 days after the birth. Includes women who gave birth in a health facility and those who did not give birth in a health facility. 3 Restricted to currently married women. See Table 13.6.1 for the list of decisions. 4 See Table 13.7.1 for the list of reasons. 13.11 INFANT AND CHILD MORTALITY AND WOMEN’S EMPOWERMENT The abilities of women to access information, make decisions, and act effectively in their own interests or in the interests of those who depend on them are essential aspects of empowerment. It follows that if women, who are the primary caretakers of children, are empowered, the health and survival of their children will be enhanced. In fact, maternal empowerment fits into the Mosley-Chen framework on child survival as an intervening individual-level variable that affects child survival through proximate determinants (Mosley and Chen, 1984). Table 13.12 presents information on the impact on infant and child mortality of women’s empowerment as measured by the two empowerment indicators (participation in household decisionmaking and reasons justifying wife beating). It shows that infant and under-five mortality rates decrease as women’s participation in decisionmaking increases. For example, infant mortality is 86 deaths per 1,000 live births and under-five mortality is 103 deaths per 1,000 live births in the case of women who make no decisions, while the corresponding figures are 77 and 90 deaths per 1,000 live births for women who participate in all three decisions. Similarly, infant mortality and under-five mortality tend to rise with the number of reasons women cite to justify wife beating. Among women who do not agree with any reason for wife beating, infant mortality and under-five mortality are 78 and 91 per 1,000 live births, respectively, as compared with 95 and 115 among women who agree with three to four reasons for wife beating. Women’s Empowerment and Demographic and Health Outcomes • 217 Table 13.12 Early childhood mortality rates by women’s status Infant, child, and under-five mortality rates for the 10-year period preceding the survey, by indicators of women’s empowerment, Pakistan 2012-13 Empowerment indicator Infant mortality (1q0) Child mortality (4q1) Under-five mortality (5q0) Number of decisions in which women participate1 0 86 19 103 1-2 79 20 97 3 77 14 90 Number of reasons for which wife beating is justified2 0 78 14 91 1-2 78 15 92 3-4 95 22 115 5-6 82 25 105 1 Restricted to currently married women. See Table 13.6.1 for the list of decisions. 2 See Table 13.7.1 for the list of reasons. Domestic Violence • 219 DOMESTIC VIOLENCE 14 omestic violence, also known as domestic abuse, spousal violence, family violence, and intimate partner violence, is broadly defined as a pattern of abusive behaviors by one or both partners in an intimate relationship. Domestic violence, so defined, has many forms, including physical aggression (hitting, kicking, biting, shoving, restraining, slapping, or throwing objects) as well as threats, sexual and emotional abuse, controlling or domineering behaviors, intimidation, stalking, and passive or covert abuse (e.g., neglect or economic deprivation). The United Nations defines domestic violence as “any act of gender-based violence that results in physical, sexual or mental harm or suffering to women including threats of such acts, coercion or arbitrary deprivation of liberty, whether occurring in public or in private life” (United Nations, 1993; United Nations, 1995). The same definition has been adopted by Pakistan’s Ministry of Law and Justice and Human Rights. In 2012-13, a domestic violence module was included in the PDHS for the first time. Domestic violence is an endemic problem in Pakistan and may be the most underreported form of violence against women residing in the country, with only 608 cases reported nationwide in 2009. The problem persists despite several laws designed to protect women from domestic violence. 14.1 VALID MEASURES OF DOMESTIC VIOLENCE Collecting accurate gender-disaggregated data is an issue in most countries, and Pakistan is no exception. Collection of valid, reliable, and ethical data on domestic violence involves particular challenges because what constitutes violence or abuse varies across cultures and individuals, and a culture of silence usually affects reporting of violence. Moreover, the sensitivity of the topic must be addressed. Responses to these challenges in the 2012-13 PDHS are described below. 14.1.1 Use of Valid Measures of Violence In the 2012-13 PDHS, information was obtained from ever-married women age 15-49 on violence committed by their current and former spouses and by others. Since international research shows that intimate partner violence is one of the most common forms of violence against women, spousal violence was measured in more detail than violence committed by other perpetrators. These detailed measurements D Key Findings • Thirty-two percent of ever-married women age 15-49 have experienced physical violence at least once since age 15, and 19 percent experienced physical violence within the 12 months prior to the survey. • Overall, 39 percent of ever-married women age 15-49 report ever having experienced physical and/or emotional violence from their spouse, and 33 percent report having experienced it in the past 12 months. • Among ever-married women who had experienced spousal physical violence in the past 12 months, 35 percent reported experiencing physical injuries. • One in 10 women reported experiencing violence during pregnancy. • Fifty-two percent of Pakistani women who experienced violence never sought help or never told anyone about the violence they had experienced. 220 • Domestic Violence were made using a shortened and modified version of the Conflict Tactics Scale (Straus, 1990). Specifically, spousal physical violence by the husband for currently married women and the most recent husband for formerly married women was measured by asking all ever-married women the following set of questions. Does (did) your (last) husband ever: (a) Push you, shake you, or throw something at you? (b) Slap you? (c) Twist your arm or pull your hair? (d) Punch you with his fist or with something that could hurt you? (e) Kick you, drag you, or beat you up? (f) Try to choke you or burn you on purpose? (g) Threaten or attack you with a knife, gun, or any other weapon? For every question that a woman answered “yes,” she was asked about the frequency of the act in the 12 months preceding the survey. A “yes” answer to one or more of items (a) to (g) above constitutes evidence of physical violence. Similarly, emotional violence among ever-married women was measured with the following questions. Does (did) your (last) husband ever: (a) Say or do something to humiliate you in front of others? (b) Threaten to hurt or harm you or someone close to you? (c) Insult you or make you feel bad about yourself? This approach of asking about specific acts to measure different forms of violence has the advantage of not being affected by different understandings of what constitutes a summary term such as violence. By including a wide range of acts, the approach has the additional advantage of giving the respondent multiple opportunities to disclose any experience of violence. In addition to these questions, women were asked about physical violence from persons other than the current or most recent spouse. Respondents who answered this question in the affirmative were asked who committed the violence against them and the frequency of such violence during the 12 months preceding the survey. Although this approach to questioning is generally considered to be optimal, the possibility of underreporting of violence cannot be entirely ruled out in any survey, and this survey is no exception. 14.1.2 Ethical Considerations in the 2012-13 PDHS In recognition of the challenges in collecting data on violence, the interviewers in the 2012-13 PDHS were given special training. The training focused on how to ask sensitive questions, ensure privacy, and build rapport between interviewer and respondent. Rapport with the interviewer, confidentiality, and privacy are all keys to building respondents’ confidence so that they can safely share their experiences with the interviewer. Also, placement of the violence questions at the end of the questionnaire provided time for the interviewer to develop a certain degree of intimacy that should have further encouraged respondents to share their experiences of violence, if any. In addition, the following protections were built into the survey Domestic Violence • 221 in keeping with the World Health Organization’s ethical and safety recommendations for research on domestic violence (WHO, 2001): 1. Only one woman per household was administered the questions on violence to maintain confidentiality. One in every three households was preselected for an interview on violence, and in the selected household one female respondent was randomly selected to be administered the questions on domestic violence. The random selection of one woman was done through a simple selection procedure based on the Kish grid, which was built into the Household Questionnaire (Kish, 1965). 2. As a means of obtaining additional consent beyond the initial consent provided at the start of the interview, the respondent was informed that the questions could be sensitive and was reassured regarding the confidentiality of her responses. 3. The violence module was implemented only if privacy could be obtained. The interviewers were instructed to skip the module, thank the respondent, and end the interview if they could not maintain privacy. 4. A brochure that includes information on domestic violence and contact information for service centers across the country is generally prepared to be given to all eligible women selected for the domestic violence module. However, in the case of Pakistan, it was not deemed suitable to produce such a brochure for distribution due to the sensitivity of the issue. Instead, supervisors were told during training to identify and locate such centers (if available) in the community and inform the interviewers so that if any respondents who reported violence asked for assistance, the interviewers would be able to provide information on services available. 14.1.3 Subsample for the Violence Module The domestic violence module was implemented only in the subsample of households selected for the men’s survey. Furthermore (as mentioned above), in keeping with ethical requirements, only one woman per household was selected for the module. These restrictions resulted in a total of 3,743 women being eligible for the module, of whom 3,687 were successfully interviewed. Forty-three eligible women were not interviewed because complete privacy could not be obtained. There were 13 missing cases for which information was not collected due to other reasons. Specially constructed weights were used to adjust for the selection of only one woman per household and to ensure that the domestic violence subsample was nationally representative. 14.2 EXPERIENCE OF PHYSICAL VIOLENCE Table 14.1 shows that about one in three (32 percent) women age 15-49 have experienced physical violence since age 15 and that 19 percent experienced physical violence in the 12 months prior to the survey. Overall, 5 percent of women reported that they had experienced physical violence often in the past 12 months, and 14 percent said they had experienced physical violence sometimes during the past 12 months. The experience of physical violence varies substantially by background characteristics. Women age 15-24 are less likely than older women to have experienced physical violence since the age 15. However, women age 15-19 are more likely than other women to have experienced physical violence during the 12 months prior to the survey. Rural women (34 percent) are more likely to have ever experienced physical violence than urban women (28 percent). They are also more likely to have experienced physical violence in the 12 months prior to the survey (21 percent and 16 percent, respectively). Khyber Pakhtunkhwa has the highest 222 • Domestic Violence percentage of women who have ever experienced physical violence (57 percent), followed by Balochistan (43 percent). Reported experience of violence is also relatively high in Punjab and Sindh (29 and 25 percent, respectively) but less prevalent than in ICT Islamabad (32 percent). The regional pattern of women’s experience of physical violence in the 12 months prior to the survey is similar to the pattern among women who have ever experienced physical violence. Table 14.1 Experience of physical violence Percentage of ever-married women age 15-49 who have ever experienced physical violence since age 15 and percentage who have experienced violence during the 12 months preceding the survey, by background characteristics, Pakistan 2012-13 Percentage who have ever experienced physical violence since age 151 Percentage who have experienced physical violence in the past 12 months Number of women Background characteristic Often Sometimes Often or sometimes2 Age 15-19 30.0 7.4 16.8 24.3 133 20-24 28.0 4.1 13.4 17.6 617 25-29 31.5 7.1 15.8 22.9 703 30-39 34.3 4.7 15.0 19.7 1,259 40-49 32.9 4.5 12.0 16.5 976 Residence Urban 28.4 4.1 11.9 16.0 1,216 Rural 34.0 5.6 15.3 20.8 2,471 Region Punjab 28.6 5.3 11.3 16.6 2,139 Urban 29.6 5.5 11.8 17.3 702 Rural 28.1 5.1 11.1 16.2 1,437 Sindh 25.0 1.2 14.6 15.8 835 Urban 21.3 0.9 9.9 10.8 383 Rural 28.2 1.5 18.6 20.1 452 Khyber Pakhtunkhwa 56.6 9.4 23.2 32.6 512 Urban 46.3 6.0 17.5 23.5 83 Rural 58.5 10.1 24.3 34.4 430 Balochistan 42.8 9.7 21.8 31.4 160 Urban 42.0 8.5 23.8 32.3 35 Rural 43.0 10.0 21.2 31.2 124 ICT Islamabad 31.8 8.2 14.6 22.8 15 Gilgit Baltistan 12.1 1.1 8.4 9.5 25 Marital status Married 31.6 4.8 14.3 19.2 3,518 Divorced/separated/ widowed 43.5 10.8 10.3 21.0 169 Number of living children 0 21.3 3.5 5.9 9.5 458 1-2 31.1 4.7 14.5 19.3 1,114 3-4 32.0 5.1 14.9 20.0 1,039 5+ 38.1 6.1 16.5 22.6 1,076 Employment Employed for cash 37.3 5.8 16.5 22.4 889 Employed not for cash 32.1 4.7 13.1 17.8 244 Not employed 30.3 4.9 13.4 18.3 2,551 Education No education 36.8 5.7 16.0 21.7 2,124 Primary 31.8 5.2 15.3 20.5 572 Middle 36.4 5.8 17.2 23.0 257 Secondary 21.8 4.4 8.1 12.5 395 Higher 12.5 1.4 5.3 6.7 339 Wealth quintile Lowest 34.3 3.2 21.6 24.8 690 Second 40.7 9.0 14.2 23.2 730 Middle 37.5 7.8 15.8 23.6 713 Fourth 29.7 3.0 11.9 14.8 820 Highest 19.3 2.8 8.0 10.8 734 Total 32.2 5.1 14.1 19.2 3,687 Note: Total includes 3 cases with missing information on employment status. 1 Includes violence in the past 12 months. For women who were married before age 15 and who reported physical violence by a spouse, the violence could have occurred before age 15. 2 Includes women for whom frequency in the past 12 months is not known. Domestic Violence • 223 Forty-four percent of women who are divorced, separated, or widowed and 32 percent of currently married women have experienced physical violence since age 15. Currently married women are less likely to have experienced physical violence in the past 12 months (19 percent) than formerly married women (21 percent). Experience of physical violence among women increases with the number of living children. While 21 percent of women with no children report having ever experienced physical violence, this percentage increases to 38 percent among women with five or more children. Experience of physical violence in the past 12 months follows a similar pattern, ranging from 10 percent among women with no children to 23 percent among women with five or more children. Women who are employed for cash are more likely than other women to have experienced physical violence since age 15 as well as during the 12 months preceding the survey (37 percent and 22 percent, respectively). Experience of physical violence since age 15 generally shows a decrease with educational attainment, from 37 percent among women with no education to 13 percent among women with a higher education. However, 36 percent of women at the middle educational level report having experienced physical violence. Experience of physical violence in the 12 months preceding the survey shows a similar pattern. The pattern of relationship between wealth and experience of physical violence varies across the wealth quintiles. Experience of physical violence since age 15 increases from 34 percent among women in the lowest wealth quintile to 41 percent among women in the second quintile and then decreases to 19 percent among women in the highest wealth quintile. Women’s experience of physical violence in the past 12 months shows a more or less decreasing trend from the lowest to the highest wealth quintile. 14.3 PERPETRATORS OF PHYSICAL VIOLENCE Table 14.2 shows the percentage of ever-married women reporting any physical violence since age 15 by the person or persons who committed the acts of violence against them. The most commonly reported perpetrator of physical violence among ever- married women is the current husband (79 percent), indicating a high level of spousal violence. Twelve percent of women reported their mother or stepmother as the perpetrator, and 8 percent reported former husbands. Violence from in-laws seems to be quite predominant in Pakistan, with 20 percent of women reporting in- laws as the perpetrators. 14.4 VIOLENCE DURING PREGNANCY Respondents who had ever been pregnant were asked specifically whether they had ever experienced physical violence while pregnant and, if so, who the perpetrators of the violence were. Table 14.3 shows that 11 percent of women experienced physical violence during a pregnancy. Although there is no clear pattern between current age and violence during pregnancy, younger women (age 15-19) are more likely than older women to report having experienced violence during pregnancy. Table 14.2 Persons committing physical violence Among ever-married women age 15-49 who have experienced physical violence since age 15, percentage who report specific persons who committed the violence, Pakistan 2012-13 Person Percentage of ever-married women Current husband 79.4 Former husband 8.0 Father/stepfather 7.0 Mother/stepmother 11.9 Sister/brother 5.6 Daughter/son 0.1 Other relative 1.6 Mother-in-law 6.5 Father-in-law 3.3 Other in-law 9.8 Teacher 0.9 Employer/someone at work 0.1 Police/soldier 0.0 Other 0.5 Number of women who have experienced physical violence since age 15 1,186 224 • Domestic Violence The proportion of women experiencing violence during pregnancy is higher in rural areas (12 percent) than in urban areas (8 percent). Among regions, the percentage is highest in Khyber Pakhtunkhwa (21 percent), followed by Balochistan (19 percent). The prevalence is lower in Punjab, Sindh, and ICT Islamabad, and Gilgit Baltistan has the lowest percentage of women experiencing physical violence during pregnancy (4 percent). Women who are divorced, separated, or widowed are more likely to report experiencing violence during pregnancy (14 percent) than women who are currently married (11 percent). The proportion of physical violence during pregnancy is higher among women with five or more living children (16 percent) than among women with fewer children or no living children (between 8 and 9 percent). Violence during pregnancy shows a varied pattern by educational status. Thirteen percent of both women with no education and women at the middle educational level reported experiencing physical violence during pregnancy, as compared with only 3 percent of women with a higher education. Women in the lowest wealth quintile are more likely than those in the highest wealth quintile to have experienced violence during pregnancy. 14.5 MARITAL CONTROL BY HUSBAND Attempts by husbands to closely control and monitor their wives’ behavior are known to be an important warning sign and precursor of violence in a relationship. A series of questions were included in the 2012-13 PDHS to elicit the degree of marital control exercised by husbands over wives. Controlling behaviors most often manifest themselves in terms of extreme possessiveness, jealousy, and attempts to isolate the wife from her family and friends. To determine the degree of marital control husbands exercise over their wives, ever-married women age 15-49 were asked whether their current or former husband exhibited each of the following controlling behaviors: (1) he is jealous or gets angry if she talks to other men, (2) he frequently accuses her of being unfaithful, (3) he does not permit meetings with female friends, (4) he tries to limit contact with her family, and (5) he insists on knowing where she is at all times. Because the concentration of such behaviors is more significant than the display of any single behavior, the proportion of women whose husbands display at least three of the specified behaviors is highlighted. Table 14.4 presents the percentage of ever-married women whose husbands display each of the listed behaviors, by selected background characteristics. Table 14.3 Experience of violence during pregnancy Among ever-married women age 15-49 who have ever been pregnant, percentage who have ever experienced physical violence during pregnancy, by background characteristics, Pakistan 2012-13 Background characteristic Percentage who experienced violence during pregnancy Number of women who have ever been pregnant Age 15-19 17.4 77 20-24 9.4 535 25-29 10.0 636 30-39 12.4 1,193 40-49 9.9 954 Residence Urban 8.4 1,124 Rural 12.1 2,271 Region Punjab 9.2 1,967 Sindh 7.8 772 Khyber Pakhtunkhwa 20.9 472 Balochistan 18.8 146 ICT Islamabad 8.3 15 Gilgit Baltistan 4.2 23 Marital status Married 10.7 3,243 Divorced/separated/ widowed 14.2 152 Number of living children 0 7.7 166 1-2 9.3 1,114 3-4 7.8 1,039 5+ 16.0 1,076 Education No education 13.4 1,999 Primary 7.0 528 Middle 13.0 232 Secondary 7.9 350 Higher 2.5 285 Wealth quintile Lowest 13.1 645 Second 15.2 666 Middle 12.1 669 Fourth 9.9 747 Highest 4.3 667 Total 10.9 3,395 Domestic Violence • 225 Table 14.4 Marital control exercised by husbands Percentage of ever-married women age 15-49 whose husbands have ever demonstrated specific types of controlling behaviors, by background characteristics, Pakistan 2012-13 Percentage of women whose husband: Background characteristic Is jealous or angry if she talks to other men Frequently accuses her of being unfaithful Does not permit her to meet her female friends Tries to limit her contact with her family Insists on knowing where she is at all times Displays 3 or more of the specific behaviors Displays none of the specific behaviors Number of ever-married women Age 15-19 22.6 5.2 12.4 12.8 18.0 12.2 70.6 133 20-24 27.3 6.2 8.2 4.4 15.7 6.3 67.1 617 25-29 26.5 6.4 8.5 6.9 13.8 9.5 69.4 703 30-39 25.7 5.3 9.5 7.7 16.9 8.6 67.4 1,259 40-49 21.8 4.9 5.6 5.4 16.6 6.0 69.9 976 Residence Urban 18.0 3.7 7.3 5.4 10.6 6.0 76.3 1,216 Rural 28.4 6.4 8.6 7.1 18.7 8.8 64.6 2,471 Region Punjab 20.6 5.6 6.5 4.6 13.7 6.1 73.5 2,139 Sindh 19.0 3.3 8.9 8.6 10.6 7.8 73.4 835 Khyber Pakhtunkhwa 50.4 6.7 12.2 9.2 30.2 13.0 44.2 512 Balochistan 34.7 11.6 13.9 13.6 32.2 15.4 53.0 160 ICT Islamabad 15.8 5.3 6.6 6.0 12.3 5.1 75.1 15 Gilgit Baltistan 25.3 8.1 1.6 6.3 12.5 5.5 70.4 25 Marital status Married 24.7 4.6 7.4 5.9 15.6 7.1 69.0 3,518 Divorced/separated/ widowed 31.2 25.5 24.3 20.0 24.9 22.4 58.0 169 Number of living children 0 18.9 4.0 8.1 6.0 11.3 5.7 75.0 458 1-2 27.5 6.7 8.0 6.3 17.0 8.7 67.3 1,114 3-4 22.4 4.4 6.8 5.6 11.7 6.0 72.2 1,039 5+ 27.5 6.1 9.6 8.0 21.3 9.6 63.4 1,076 Employment Employed for cash 23.7 6.9 8.5 6.4 15.1 8.1 68.9 889 Employed not for cash 25.2 6.7 11.7 11.3 22.9 12.7 66.3 244 Not employed 25.4 4.9 7.7 6.2 15.8 7.3 68.5 2,551 Education No education 28.1 6.3 9.5 7.5 18.6 9.2 64.3 2,124 Primary 25.3 5.5 6.3 6.2 15.3 5.8 67.7 572 Middle 25.5 10.8 9.9 7.8 14.1 11.2 70.6 257 Secondary 17.8 1.6 7.6 4.6 13.7 6.0 77.1 395 Higher 12.9 1.1 2.3 2.3 5.7 2.1 84.4 339 Wealth quintile Lowest 31.0 6.2 10.5 8.7 18.9 10.9 62.1 690 Second 32.5 8.0 9.9 8.1 21.4 10.3 59.8 730 Middle 26.4 7.2 10.9 8.5 18.7 9.6 67.9 713 Fourth 21.5 3.9 5.9 4.9 13.8 5.7 70.5 820 Highest 14.4 2.7 4.1 2.9 8.1 3.3 81.5 734 Woman afraid of husband Afraid most of the time 54.5 21.8 21.7 16.6 39.9 25.8 35.8 554 Sometimes afraid 31.0 4.6 8.7 7.9 19.2 8.2 61.0 1,472 Never 9.7 0.9 3.1 2.0 5.3 1.4 86.2 1,646 Total 25.0 5.5 8.1 6.5 16.1 7.8 68.5 3,687 Note: Husband refers to the current husband for currently married women and the most recent husband for divorced, separated, or widowed women. Total includes 3 cases with missing information on employment status and 15 cases with missing information on women being afraid of their husbands. The main controlling behaviors women experienced from their husbands were jealousy or anger if they talked to other men (25 percent) and husbands insisting on knowing where they are at all times (16 percent). Other common behaviors were trying to limit her contact with female friends (8 percent), trying to limit her contact with her family (7 percent), and frequently accusing her of being unfaithful (6 percent). Eight percent of ever-married women say that their husbands display three or more of these controlling behaviors, and 69 percent say their husbands display none of the behaviors. 226 • Domestic Violence Seven percent of currently married women reported that their husbands display at least three controlling behaviors, as compared with 22 percent women who are divorced, separated, or widowed. The percentage of women whose husband displays at least three controlling behaviors is higher in rural areas and tends to decrease with increasing wealth, whereas there is no consistent pattern according to women’s education. Women who are afraid of their husbands most of the time are more likely to report controlling behavior than women who are never afraid of their husbands. However, variations are minimal and inconsistent according to other background characteristics. Women were also asked whether they had ever initiated physical violence against their husband when he was not beating or physically hurting them. As less than 1 percent of women reported that they had physically hurt their husbands, a detailed assessment by background characteristics is not presented in this report. 14.6 FORMS OF SPOUSAL VIOLENCE Different types of violence are not mutually exclusive, and women may report multiple forms of violence. Research suggests that physical violence in intimate relationships is often accompanied by psychological abuse (Krug et al., 2002). Table 14.5 shows the percentage of ever-married women age 15- 49 who have experienced various forms of violence by their husbands over the course of the marriage and in the 12 months preceding the survey. Women who are currently married reported on violence committed by their current husband, and women who are widowed, divorced, or separated reported on violence committed by their most recent husband. Table 14.5 Forms of spousal violence Percentage of ever-married women age 15-49 who have experienced various forms of violence ever or in the 12 months preceding the survey, committed by their husband, Pakistan 2012-13 Ever In the past 12 months Type of violence Often Sometimes Often or sometimes SPOUSAL VIOLENCE COMMITTED BY CURRENT OR MOST RECENT HUSBAND Physical violence Any physical violence 26.8 4.7 13.3 18.0 Pushed her, shook her, or threw something at her 16.0 2.4 7.3 9.7 Slapped her 25.2 3.7 12.2 15.9 Twisted her arm or pulled her hair 10.9 2.1 4.4 6.5 Punched her with his fist or with something that could hurt her 8.7 1.8 3.5 5.3 Kicked her, dragged her, or beat her up 5.3 1.0 2.0 3.0 Tried to choke her or burn her on purpose 2.1 0.6 0.6 1.2 Threatened her or attacked her with a knife, gun, or other weapon 1.7 0.4 0.6 1.0 Emotional violence Any emotional violence 32.2 10.7 17.6 28.3 Said or did something to humiliate her in front of others 25.9 8.3 13.6 21.9 Threatened to hurt or harm her or someone she cared about 4.8 1.9 1.8 3.8 Insulted her or made her feel bad about herself 27.3 8.5 15.2 23.8 Any form of emotional and/or physical violence 38.5 11.4 21.3 32.8 SPOUSAL VIOLENCE COMMITTED BY ANY HUSBAND Physical violence 27.1 na na 18.0 Number of ever-married women 3,687 3,687 3,687 3,687 Note: Husband refers to the current husband for currently married women and the most recent husband for divorced, separated, or widowed women. na = Not available Domestic Violence • 227 The results show that 27 percent of ever-married women reported ever experiencing physical violence from their husband and that 32 percent reported experiencing emotional violence. Overall, 39 percent of women experienced physical and/or emotional violence from their husband. Twenty-seven percent of women reported having experienced physical violence from any husband (current or former). Slapping is the most common form of spousal violence, experienced by 25 percent of women (Table 14.5 and Figure 14.1). Sixteen percent of women reported having been pushed, been shaken, or had something thrown at them. The most common forms of emotional violence reported by women were insulting them or making them feel bad about themselves (27 percent) and saying something to humiliate them in front of others (26 percent). The majority of women who have ever experienced each of these forms of violence have also experienced the same type of violence in the past 12 months. Thirty-three percent of ever-married women reported experiencing spousal physical and/or emotional violence in the past 12 months, with 21 percent having experienced violence sometimes and 11 percent having experienced it often. Figure 14.1 Forms of spousal violence 27 5 26 2 2 5 9 11 25 16 24 4 22 1 1 3 5 7 16 10 Insulted her or made her feel bad about herself Threatened to hurt or harm her or someone she cared about Said or did something to humiliate her in front of others Threatened her or attacked her with a knife, gun, or other weapon Tried to choke her or burn her on purpose Kicked her, dragged her, or beat her up Punched her with his fist or with something that could hurt her Twisted her arm or pulled her hair Slapped her Pushed her, shook her, or threw something at her Percent Last 12 months Ever PDHS 2012-13 14.7 SPOUSAL VIOLENCE BY BACKGROUND CHARACTERISTICS Table 14.6 shows the percentage of ever-married women age 15-49 who have experienced spousal emotional or physical violence by selected background characteristics. Women’s experience of each type of spousal violence increases with age and number of children. Women who are employed for cash are more likely than other women to have ever experienced either of the two forms of violence. Formerly married women are more likely to have experienced either physical or emotional spousal violence (50 percent) than currently married women (38 percent). Women’s experience of violence differs by urban- rural residence (32 percent and 42 percent, respectively). At the regional level, women in Khyber Pakhtunkhwa are most likely to have experienced physical or emotional violence (57 percent), followed by women in Balochistan (50 percent); the lowest proportion is reported in Gilgit Baltistan (20 percent). 228 • Domestic Violence Table 14.6 Spousal violence by background characteristics Percentage of ever-married women age 15-49 who have ever experienced emotional or physical violence committed by their husband, by background characteristics, Pakistan 2012-13 Background characteristic Emotional violence Physical violence Physical or emotional Number of ever-married women Age 15-19 24.8 24.4 27.8 133 20-24 27.6 22.2 33.0 617 25-29 27.2 24.2 33.0 703 30-39 33.9 29.4 41.2 1,259 40-49 37.5 28.6 43.8 976 Residence Urban 26.6 22.8 32.2 1,216 Rural 35.0 28.8 41.6 2,471 Region Punjab 34.9 23.1 39.3 2,139 Urban 33.0 24.4 37.9 702 Rural 35.8 22.5 40.0 1,437 Sindh 14.4 19.8 23.0 835 Urban 12.2 14.8 17.4 383 Rural 16.3 24.1 27.8 452 Khyber Pakhtunkhwa 47.3 50.7 57.4 512 Urban 35.5 39.2 47.4 83 Rural 49.5 52.9 59.4 430 Balochistan 42.9 39.3 50.1 160 Urban 36.4 40.1 45.2 35 Rural 44.8 39.0 51.4 124 ICT Islamabad 33.9 24.2 38.9 15 Gilgit Baltistan 16.4 10.4 20.0 25 Marital status Married 31.6 26.1 37.9 3,518 Divorced/separated/ widowed 44.4 42.0 49.8 169 Number of living children 0 19.7 15.3 22.6 458 1-2 29.6 25.4 34.7 1,114 3-4 30.3 27.6 39.3 1,039 5+ 42.1 32.5 48.4 1,076 Employment Employed for cash 36.2 31.7 43.9 889 Employed not for cash 36.3 25.1 40.1 244 Not employed 30.5 25.4 36.5 2,551 Education No education 36.5 31.1 43.5 2,124 Primary 33.3 28.0 40.3 572 Middle 28.9 26.8 36.5 257 Secondary 23.0 16.6 26.3 395 Higher 16.3 10.5 19.8 339 Wealth quintile Lowest 33.2 30.1 41.4 690 Second 41.1 34.0 46.9 730 Middle 37.0 33.4 43.8 713 Fourth 31.2 23.1 37.1 820 Highest 18.9 14.5 23.7 734 Total 32.2 26.8 38.5 3,687 Note: Husband refers to the current husband for currently married women and the most recent husband for divorced, separated, or widowed women. Total includes 3 cases with missing information on employment status. Women’s experience of most forms of violence decreases sharply with increasing education. For example, 44 percent of women with no education have experienced spousal physical or emotional violence, as compared with 20 percent of women who have a higher education. The relationship between women’s experience of violence and wealth is not consistent. Both forms of violence are higher among women in the second quintile than among women in the higher or lower quintiles. While women in the highest quintile are consistently less likely than women in any other quintile to experience any form of Domestic Violence • 229 spousal violence, it is important to note that almost 1 in 4 women in the highest quintile have experienced some form of physical or emotional violence. 14.8 VIOLENCE BY SPOUSAL CHARACTERISTICS AND WOMEN’S EMPOWERMENT INDICATORS Table 14.7 presents information on ever-married women’s experience of spousal emotional and physical violence according to husbands’ characteristics and women’s empowerment indicators. The table shows that spousal violence decreases with increasing education of the husband. For example, 44 percent of women whose spouses have no education have experienced physical or emotional forms of violence, as compared with 26 percent of women whose spouses have more than a secondary education. Spousal violence is much higher (45 percent) among couples where both partners are uneducated than among couples where both partners have the same level of education (26 percent). There is a very strong relationship between the experience of emotional and physical violence and the husband’s alcohol use. Women whose husbands get drunk often are 35 percentage points more likely to experience both types of spousal violence than women whose husbands do not drink. Women who are 10 years younger than their spouse are more likely (41 percent) than women who are the same age as or older than their spouse to experience emotional and physical violence (36 percent and 37 percent, respectively). Spousal violence increases linearly with the number of controlling behaviors displayed by the husband. Among women whose husbands exhibit five or six types of controlling behaviors, almost all (96 percent) have experienced one or more forms of violence. In contrast, one-fourth of women (27 percent) whose husbands display none of the six controlling behaviors have experienced some form of spousal violence. There is an inconsistent relationship between women’s participation in household decisions and their experience of violence. Women who participate in one or two decisions (44 percent) are more likely to experience violence than those with no participation in decisionmaking (36 percent) and those who participate in three decisions (37 percent). Women who justify wife beating for any of the six reasons have a higher prevalence of physical or emotional violence; women who reject any of the reasons experience less violence (32 percent) than women who agree with one to two reasons (42 percent), three to four reasons (51 percent), or five to six reasons (50 percent). It is often stated that violence perpetuates violence. As can be seen in Table 14.7, a family history of domestic violence is associated with a respondent’s own experience of domestic violence. Among women whose fathers beat their mothers, 66 percent have experienced emotional or physical violence, as compared with 31 percent of women whose fathers did not beat their mothers. Women who report being afraid of their husbands most of the time are more likely to suffer spousal violence (66 percent) than women who are afraid only sometimes (48 percent) and those who are never afraid (21 percent). 230 • Domestic Violence Table 14.7 Spousal violence by husband’s characteristics and empowerment indicators Percentage of ever-married women age 15-49 who have ever experienced emotional or physical violence committed by their husband, by husband’s characteristics and empowerment indicators, Pakistan 2012-13 Background characteristic Emotional violence Physical violence Physical or emotional Number of women Husband’s education No education 37.1 33.1 44.4 1,212 Primary 33.8 29.5 40.0 629 Secondary 32.1 24.3 37.3 1,234 More than secondary 20.1 15.6 26.2 600 Husband’s alcohol consumption1 Does not drink 30.5 24.8 36.8 3,486 Drinks/never gets drunk * * * 19 Gets drunk sometimes 58.8 58.8 69.2 72 Gets drunk very often 69.4 71.1 71.6 107 Spousal education difference Husband better educated 32.0 26.3 38.7 1,797 Wife better educated 27.3 22.0 31.7 566 Both equally educated 23.8 15.9 26.1 306 Neither educated 37.6 33.2 45.0 1,007 Spousal age difference2 Wife is older 28.9 20.7 36.9 282 Wife is same age 28.2 21.5 36.1 210 Wife is 1-4 years younger 32.1 28.7 38.4 1,267 Wife is 5-9 years younger 29.9 24.8 36.2 1,146 Wife is 10+ years younger 35.9 27.1 40.7 607 Number of marital control behaviors displayed by husband3 0 20.8 16.2 26.5 2,526 1-2 53.8 45.5 62.2 873 3-4 58.2 56.0 63.9 222 5-6 95.9 87.4 95.9 67 Number of decisions in which women participate4 0 30.1 25.7 35.6 1,326 1-2 35.6 30.7 44.2 791 3 30.8 23.9 36.6 1,401 Number of reasons for which wife beating is justified5 0 26.7 20.4 31.8 2,147 1-2 34.6 29.1 41.7 445 3-4 43.2 38.7 50.8 610 5-6 40.6 38.3 49.5 485 Woman’s father beat her mother Yes 54.2 57.5 66.0 763 No 26.4 18.3 31.0 2,729 Does not know/missing 27.0 26.8 35.3 195 Woman afraid of husband Afraid most of the time 57.9 54.6 65.7 554 Sometimes afraid 39.1 34.4 48.0 1,472 Never 17.5 10.8 21.0 1,646 Total 32.2 26.8 38.5 3,687 Note: Husband refers to the current husband for currently married women and the most recent husband for divorced, separated, or widowed women. Total includes 11 cases for which information on husband’s education is not known and 15 cases with missing information on women being afraid of their husbands. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 1 Excludes 3 women with no information on husband’s alcohol consumption status 2 Includes only women who have been married only once. Excludes 7 women with no information on spouse’s age. 3 According to the wife’s report. See Table 14.4 for the list of behaviors. 4 According to the wife’s report. See Table 13.6.1 for the list of decisions. Includes only currently married women. 5 According to the wife’s report. See Table 13.7.1 for the list of reasons. Domestic Violence • 231 14.9 RECENT SPOUSAL VIOLENCE Recent experience of spousal violence is an indicator of the extent to which domestic violence is a current problem. Table 14.8 shows that, overall, 18 percent of ever-married women experienced physical violence perpetrated by their current or most recent husband in the 12 months preceding the survey. Women’s experience of physical violence in the past 12 months decreases with age and increases with number of children. Women employed for cash are more likely than women in the other employment categories to have experienced physical violence in the past 12 months. Urban women are less likely than rural women to have experienced emotional and physical violence in the past 12 months. Also, women in Khyber Pakhtunkhwa and Balochistan are more likely than women in other regions to have experienced violence in the past 12 months. Recent experience of spousal physical violence does not vary consistently with education and wealth, although women with a higher education and those in the highest wealth quintile are least likely to have experienced violence. Moreover, the proportions of women who experienced spousal physical violence are approximately the same among those who are currently married and those who are divorced, separated, or widowed. Women who are never afraid of their husbands are least likely to report recent physical violence from their husbands. 14.10 ONSET OF SPOUSAL VIOLENCE To obtain information on the onset of marital violence, currently married women were asked when the first episode of violence took place, if ever. Table 14.9 shows the interval between marriage and the first episode of physical violence by the current husband. Seventy-four percent of ever-married women have never experienced spousal physical violence from their current husband. The likelihood of experiencing spousal physical violence increases with marital duration. For instance, 90 percent of women who have been married for less than two years have never faced violence from their husbands, as opposed to 71 percent among those who have been married for 10 years or more. Table 14.9 shows that 19 percent of women who had been married for two to four years first experienced spousal physical violence during their second year of marriage. Fourteen percent of women who had been married for more than 10 years first experienced violence during their second year of marriage, and 24 percent first experienced it during their fifth year of marriage. Twenty-seven percent of women who had been married for more than 10 years reported that they first experienced spousal physical violence during the tenth year of marriage. Table 14.8 Physical violence in the past 12 months by any husband Percentage of ever-married women who have experienced physical violence by any husband in the past 12 months, by background characteristics, Pakistan 2012-13 Background characteristic Percentage of women who have experienced physical violence in the past 12 months from any husband Number of ever-married women Age 15-19 21.8 133 20-24 17.3 617 25-29 19.9 703 30-39 18.7 1,259 40-49 15.5 976 Residence Urban 15.1 1,216 Rural 19.4 2,471 Region Punjab 14.9 2,139 Sindh 15.5 835 Khyber Pakhtunkhwa 31.1 512 Balochistan 31.3 160 ICT Islamabad 21.3 15 Gilgit Baltistan 9.5 25 Marital status Married 17.9 3,518 Divorced/separated/ widowed 19.0 169 Number of living children 0 8.7 458 1-2 18.1 1,114 3-4 18.5 1,039 5+ 21.3 1,076 Employment Employed for cash 21.3 889 Employed not for cash 16.5 244 Not employed 17.0 2,551 Education No education 20.3 2,124 Primary 19.1 572 Middle 19.8 257 Secondary 12.1 395 Higher 6.7 339 Wealth quintile Lowest 23.7 690 Second 21.0 730 Middle 22.2 713 Fourth 13.8 820 Highest 10.2 734 Woman afraid of husband Afraid most of the time 42.9 554 Sometimes afraid 23.1 1,472 Never 5.2 1,646 Total 18.0 3,687 Note: Any husband includes all current, most recent, and former husbands. Total includes 3 cases with missing information on employment status and 15 cases with missing information on women being afraid of their husbands. 232 • Domestic Violence Table 14.9 Experience of spousal violence by duration of marriage Among currently married women age 15-49 who have been married only once, the percentage who first experienced physical violence committed by their current husband by specific exact years since marriage according to marital duration, Pakistan 2012-13 Percentage who first experienced spousal physical violence by exact marital duration: Percentage who have not experienced spousal physical violence Number of currently married women who have been married only once Duration of marriage 2 years 5 years 10 years Years since marriage <2 na na na 90.4 318 2-4 18.5 na na 76.9 440 5-9 13.1 22.8 na 75.4 674 10+ 14.1 23.9 27.1 70.6 2,004 Total 14.0 22.3 24.5 74.2 3,437 na = Not applicable 14.11 PHYSICAL CONSEQUENCES OF SPOUSAL VIOLENCE In the 2012-13 PDHS, ever-married women age 15-49 were asked whether they had sustained some form of injury as a result of physical violence inflicted by their husband. Among women who had experienced any physical violence from their spouse, 29 percent reported that they suffered cuts, bruises, or aches; 10 percent had eye injuries, sprains, dislocations, or burns; and 6 percent had deep wounds, broken bones, broken teeth, or other serious injuries (Table 14.10). Overall, 31 percent of women who had ever experienced spousal physical violence suffered one or more of these injuries. The prevalence of all forms of injuries was higher among women who had experienced violence in the past 12 months than among women who had ever experienced spousal violence. Table 14.10 Injuries to women due to spousal violence Percentage of ever-married women age 15-49 who have experienced specific types of spousal violence by types of injuries resulting from the violence, according to the type of violence and whether they experienced the violence ever and in the 12 months preceding the survey, Pakistan 2012-13 Type of violence Cuts, bruises, or aches Eye injuries, sprains, dislocations, or burns Deep wounds, broken bones, broken teeth, or any other serious injury Any of these injuries Number of ever-married women who have ever experienced any physical violence Experienced physical violence1 Ever2 28.9 9.6 5.5 30.6 990 In the past 12 months 32.7 13.1 7.1 34.8 663 Note: Husband refers to the current husband for currently married women and the most recent husband for divorced, separated, or widowed women. 1 Excludes women who reported violence only in response to a direct question on violence during pregnancy 2 Includes in the past 12 months 14.12 HELP-SEEKING BEHAVIOR BY WOMEN WHO EXPERIENCE VIOLENCE Table 14.11 shows the percent distribution of women who have ever experienced physical violence committed by anyone, according to whether they sought help to stop the violence and, among those who did not seek help, whether or not they told anyone about the violence. Overall, 52 percent of women who have experienced any type of physical violence have never sought help and never told anyone about the violence. Ten percent never sought help but told someone that they were victims of violence. Only 35 percent of women in Pakistan who have ever experienced any form of physical violence have sought help from any source. Domestic Violence • 233 Table 14.11 Help seeking to stop violence Percent distribution of ever-married women age 15-49 who have ever experienced physical violence by their help-seeking behavior, according to type of violence and background characteristics, Pakistan 2012-13 Background characteristic Sought help to stop violence Never sought help but told someone Never sought help, never told anyone Missing/don’t know Total Number of women who have ever experienced any physical violence Age 15-19 (32.0) (11.8) (51.4) (4.7) 100.0 40 20-24 33.0 7.2 58.0 1.8 100.0 173 25-29 40.5 11.2 47.0 1.3 100.0 221 30-39 33.1 10.5 52.2 4.2 100.0 432 40-49 36.1 10.9 51.3 1.8 100.0 321 Residence Urban 35.9 10.8 52.6 0.7 100.0 345 Rural 35.0 10.1 51.5 3.5 100.0 841 Region Punjab 50.4 7.3 40.6 1.8 100.0 611 Sindh 23.3 15.5 58.9 2.2 100.0 209 Khyber Pakhtunkhwa 16.4 12.4 66.8 4.4 100.0 290 Balochistan 16.9 11.8 66.4 4.8 100.0 68 ICT Islamabad 29.2 19.6 46.8 4.3 100.0 5 Gilgit Baltistan (32.5) (9.5) (58.0) (0.0) 100.0 3 Marital status Married 34.1 9.8 53.5 2.6 100.0 1,113 Divorced/separated/ widowed 52.6 17.9 26.6 2.9 100.0 73 Number of living children 0 35.2 13.1 47.6 4.0 100.0 98 1-2 36.9 10.1 51.6 1.4 100.0 346 3-4 34.9 9.0 52.6 3.5 100.0 332 5+ 34.2 10.8 52.3 2.7 100.0 410 Employment Employed for cash 45.1 10.0 43.7 1.3 100.0 331 Employed not for cash 45.1 3.5 49.3 2.1 100.0 78 Not employed 30.2 11.2 55.3 3.3 100.0 773 Education No education 34.0 10.6 52.4 3.0 100.0 782 Primary 36.3 6.0 56.3 1.4 100.0 182 Middle 46.6 12.0 37.2 4.2 100.0 94 Secondary 35.9 9.6 53.1 1.3 100.0 86 Higher 27.4 20.4 50.7 1.6 100.0 43 Wealth quintile Lowest 32.3 12.2 53.4 2.0 100.0 237 Second 33.5 11.7 51.6 3.1 100.0 297 Middle 40.6 8.0 46.9 4.5 100.0 268 Fourth 36.7 8.8 52.5 2.0 100.0 243 Highest 31.0 11.0 57.5 0.5 100.0 142 Total 35.2 10.3 51.8 2.7 100.0 1,186 Note: Women can report more than one source from which they sought help. Total includes 3 cases with missing information on employment status. Figures in parentheses are based on 25-49 unweighted cases. Help-seeking behavior varies inconsistently with age and number of children. A much higher proportion of divorced, separated, or widowed women (53 percent) than currently married women (34 percent) have ever sought help to stop violence. There are only minimal differences in help-seeking behavior among urban and rural women. Among the regions, the proportion of women seeking help varies from a maximum of 50 percent in Punjab to a minimum of 6 percent in Khyber Pakhtunkhwa. The data suggest that neither education nor wealth results in a greater likelihood of women seeking help: the most educated women and those in the highest wealth quintile are less likely to seek help than less educated or less wealthy women. 234 • Domestic Violence Table 14.12 shows information on sources of help. The most common source of help is the woman’s own family. 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Appendix A • 241 ADDITIONAL TABLES Appendix A Table A2.1 Household drinking water Percent distribution of households by source of drinking water, time to obtain drinking water, and treatment of drinking water, according to region, Pakistan 2012-13 Region Characteristic Punjab Sindh Khyber Pakhtunkhwa Balochistan ICT Islamabad Gilgit Baltistan Source of drinking water Improved source 98.6 93.7 77.5 67.2 94.9 79.5 Piped into dwelling/yard/plot 29.8 37.0 18.2 25.9 25.0 62.3 Public tap/standpipe 6.2 4.4 11.1 10.4 5.4 13.5 Tube well or borehole/hand pump 55.5 44.4 34.9 20.7 30.0 0.2 Protected well 0.6 1.5 8.4 3.8 4.3 2.7 Protected spring/rain water 0.2 0.0 4.5 4.2 0.1 0.5 Bottled water 1.3 4.9 0.1 1.8 8.8 0.1 Filtration plant 5.1 1.4 0.2 0.3 21.3 0.2 Non-improved source 0.6 6.0 21.5 32.7 4.5 20.4 Unprotected well 0.2 2.4 4.7 3.3 1.7 1.1 Unprotected spring 0.0 0.0 11.7 7.2 0.1 3.5 Tanker truck/cart with drum 0.1 2.7 4.1 8.6 2.7 1.4 Surface water 0.3 0.9 1.1 13.6 0.0 14.3 Other source 0.7 0.3 1.0 0.0 0.4 0.1 Total 100.0 100.0 100.0 100.0 100.0 100.0 Time to obtain drinking water (round trip) Water on premises 83.6 69.7 68.0 39.9 49.8 67.7 Less than 30 minutes 12.0 18.6 16.8 18.3 37.8 29.6 30 minutes or longer 4.0 11.5 14.5 40.6 11.4 2.4 Don’t know/missing 0.4 0.3 0.7 1.1 0.9 0.4 Total 100.0 100.0 100.0 100.0 100.0 100.0 Water treatment prior to drinking1 Boiled 5.4 15.0 1.9 2.1 13.5 3.4 Bleach/chlorine added 0.1 0.8 0.1 0.4 0.9 0.0 Strained through cloth 1.1 6.0 1.9 5.3 2.8 0.2 Ceramic, sand, or other filter 0.7 1.2 0.1 0.1 2.9 0.2 Solar disinfection 0.0 0.0 0.1 0.2 0.1 0.0 Other 0.3 0.3 0.6 2.6 0.9 0.3 No treatment 92.6 80.1 95.6 89.3 79.9 95.4 Percentage using an appropriate treatment method2 6.2 16.5 2.1 2.7 16.7 3.5 Number 7,614 3,004 1,711 450 72 91 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. 242 • Appendix A Table A2.2 Household sanitation facilities Percent distribution of households by type of toilet/latrine facilities, according to region, Pakistan 2012-13 Region Type of toilet/latrine facility Punjab Sindh Khyber Pakhtunkhwa Balochistan ICT Islamabad Gilgit Baltistan Improved, not shared facility 58.8 56.9 61.8 46.2 92.1 82.0 Flush/pour flush to piped sewer system 23.4 47.5 8.8 4.5 66.4 0.7 Flush/pour flush to septic tank 22.8 2.1 18.3 5.4 11.5 0.5 Flush/pour flush to pit latrine 12.4 4.6 29.7 8.0 13.3 56.9 Ventilated improved pit (VIP) latrine 0.1 0.4 1.7 6.5 0.0 0.0 Pit latrine with slab 0.2 2.3 3.3 21.8 1.0 23.8 Shared facility1 13.6 7.0 7.4 6.2 3.7 0.9 Flush/pour flush to piped sewer system 3.9 2.6 1.2 0.3 1.7 0.0 Flush/pour flush to septic tank 5.6 1.2 3.3 0.3 1.3 0.0 Flush/pour flush to pit latrine 4.0 2.1 2.0 0.7 0.6 0.5 Ventilated improved pit (VIP) latrine 0.0 0.4 0.2 2.4 0.0 0.0 Pit latrine with slab 0.1 0.7 0.7 2.5 0.0 0.4 Non-improved facility 27.5 36.0 30.7 47.6 4.2 17.1 Flush/pour flush not to sewer/septic tank/pit latrine 8.1 2.0 3.8 4.7 2.3 1.7 Pit latrine without slab/open pit 0.3 5.9 2.4 10.9 0.2 7.1 Bucket 0.0 1.0 1.0 0.9 0.2 0.2 Hanging toilet/hanging latrine 0.0 0.1 1.4 0.0 0.0 0.0 No facility/bush/field 18.7 26.9 21.3 30.2 0.9 7.7 Other 0.2 0.2 0.5 0.3 0.3 0.0 Missing 0.2 0.0 0.3 0.6 0.4 0.4 Total 100.0 100.0 100.0 100.0 100.0 100.0 Number 7,614 3,004 1,711 450 72 91 1 Facilities that would be considered improved if they were not shared by two or more households Appendix A • 243 Table A2.3 Household population by age, sex, and region Percent distribution of the de facto household population by five-year age groups, according to sex and region, Pakistan 2012-13 Punjab Sindh Khyber Pakhtunkhwa Age Male Female Total Sex ratio Male Female Total Sex ratio Male Female Total Sex ratio <5 13.7 13.2 13.5 103.6 12.9 13.6 13.2 94.7 14.1 13.2 13.6 106.3 5-9 13.7 12.3 13.0 111.7 13.2 12.7 13.0 104.3 15.8 14.0 14.9 113.2 10-14 12.7 10.8 11.8 117.8 12.2 11.9 12.1 102.7 14.4 12.3 13.3 117.1 15-19 11.0 11.5 11.3 96.0 11.2 10.8 11.0 104.0 11.9 11.9 11.9 99.9 20-24 8.7 10.6 9.7 82.2 9.8 10.5 10.1 92.8 8.8 9.7 9.2 91.0 25-29 7.2 8.4 7.8 86.4 8.9 8.9 8.9 101.0 6.2 7.7 7.0 80.5 30-34 5.8 6.6 6.2 87.5 6.6 6.4 6.5 103.1 5.2 5.8 5.5 89.8 35-39 5.0 5.8 5.4 86.6 5.4 5.6 5.5 97.2 4.4 6.1 5.2 72.5 40-44 5.0 4.6 4.8 108.2 4.1 4.0 4.0 101.8 3.4 4.3 3.9 79.8 45-49 4.3 3.8 4.1 114.1 3.9 4.3 4.1 90.6 3.6 3.9 3.7 92.3 50-54 2.5 2.8 2.7 86.9 2.5 2.7 2.6 90.3 2.7 2.8 2.8 94.6 55-59 2.3 3.0 2.6 77.9 2.9 3.4 3.2 86.0 2.3 2.9 2.6 80.0 60-64 2.5 2.2 2.4 111.4 2.7 2.3 2.5 117.6 2.5 2.3 2.4 110.2 65-69 1.9 1.7 1.8 112.6 1.7 1.2 1.4 140.3 1.8 1.1 1.5 163.4 70-74 1.6 1.1 1.4 141.9 1.2 1.0 1.1 119.2 1.6 1.2 1.4 132.4 75-79 0.8 0.6 0.7 119.5 0.3 0.3 0.3 128.3 0.5 0.4 0.4 120.3 80 + 1.2 0.9 1.0 136.4 0.5 0.5 0.5 98.5 0.8 0.4 0.6 182.7 Total 100.0 100.0 100.0 - 100.0 100.0 100.0 - 100.0 100.0 100.0 - Number 24,657 24,751 49,408 - 10,706 9,991 20,697 - 6,208 6,328 12,536 - Continued… Table A2.3—Continued Balochistan ICT Islamabad Gilgit Baltistan Age Male Female Total Sex ratio Male Female Total Sex ratio Male Female Total Sex ratio <5 14.4 15.0 14.7 96.4 10.8 10.3 10.6 104.7 13.7 12.1 12.9 112.7 5-9 16.9 15.9 16.4 105.7 9.1 11.2 10.1 81.4 16.5 14.1 15.3 117.0 10-14 13.9 13.8 13.9 101.1 10.4 10.4 10.4 99.7 13.6 14.4 14.0 94.3 15-19 11.3 10.3 10.8 110.1 10.7 10.8 10.7 98.5 13.3 12.0 12.6 111.3 20-24 8.5 10.1 9.3 83.9 10.7 9.8 10.3 109.2 8.1 9.3 8.7 87.1 25-29 8.0 8.9 8.5 90.5 8.2 9.7 8.9 84.5 5.4 7.5 6.5 72.1 30-34 5.6 6.2 5.9 89.9 7.6 6.6 7.1 114.7 4.6 5.6 5.1 82.5 35-39 5.2 5.1 5.2 101.9 6.1 7.2 6.6 83.8 4.2 5.1 4.6 83.2 40-44 4.0 3.4 3.7 118.3 5.6 5.7 5.7 98.5 3.4 3.6 3.5 93.3 45-49 3.5 2.9 3.2 123.1 5.7 4.1 4.9 138.3 3.3 4.1 3.7 78.9 50-54 2.2 3.4 2.7 64.1 3.6 3.9 3.7 90.6 3.0 3.0 3.0 97.6 55-59 2.4 2.2 2.3 107.1 3.3 3.1 3.2 107.4 3.1 3.1 3.1 99.8 60-64 1.8 1.2 1.5 149.2 3.0 3.1 3.0 98.5 2.8 2.1 2.4 136.5 65-69 1.0 0.9 1.0 115.1 2.0 1.4 1.7 151.1 1.8 1.4 1.6 127.7 70-74 0.6 0.4 0.5 137.6 1.4 1.0 1.2 131.2 1.4 0.9 1.2 150.6 75-79 0.2 0.1 0.2 156.2 0.8 0.6 0.7 138.5 0.7 0.7 0.7 109.6 80 + 0.4 0.1 0.3 299.2 1.0 1.0 1.0 107.9 1.0 0.9 0.9 119.8 Total 100.0 100.0 100.0 - 100.0 100.0 100.0 - 100.0 100.0 100.0 - Number 2,082 1,944 4,026 - 225 203 429 - 349 340 689 - 244 • Appendix A Table A5.1 Current fertility Age-specific and total fertility rates and the general fertility rate for the three years preceding the survey, by region, Pakistan 2012-13 Age group Punjab Sindh Khyber Pakhtunkhwa Balochistan ICT Islamabad Gilgit Baltistan 15-19 41 43 62 48 25 54 20-24 194 186 181 198 124 174 25-29 237 201 206 236 221 208 30-34 181 189 173 162 149 172 35-39 75 117 111 111 68 107 40-44 24 34 4 66 1 37 45-49 3 12 11 24 0 13 TFR (15-49) 3.8 3.9 3.9 4.2 3.0 3.8 GFR 131 132 130 144 106 127 Note: Age-specific fertility rates are per 1,000 women. Rates for age group 45-49 may be slightly biased due to truncation. Rates are for the period 1-36 months prior to the interview. TFR: Total fertility rate expressed per woman GFR: General fertility rate expressed per 1,000 women age 15-44 Table A9.1 Number of antenatal care visits and timing of first visit Percent distribution of women age 15-49 who had a live birth in the five years preceding the survey by number of antenatal care (ANC) visits for the most recent live birth, and by the timing of the first visit, and among women with ANC, median months pregnant at first visit, according to residence, Pakistan 2012-13 Region Number and timing of ANC visits Punjab Sindh Khyber Pakhtunkhwa Balochistan ICT Islamabad Gilgit Baltistan Number of ANC visits None 19.7 20.9 37.6 56.0 3.5 33.9 1 15.2 11.9 10.4 9.0 2.1 9.8 2-3 26.6 22.6 27.8 21.9 12.3 25.4 4+ 38.5 44.4 24.0 12.2 82.1 30.9 Don’t know/missing 0.0 0.2 0.2 1.0 0.0 0.0 Total 100.0 100.0 100.0 100.0 100.0 100.0 Number of months pregnant at time of first ANC visit No antenatal care 19.7 20.9 37.6 56.0 3.5 33.9 <4 45.2 41.7 39.7 18.8 73.3 32.7 4-5 14.6 15.7 12.6 12.2 16.6 18.4 6-7 13.7 14.3 6.2 7.3 5.3 10.5 8+ 6.7 7.2 3.7 5.5 1.1 4.5 Don’t know/missing 0.1 0.1 0.2 0.3 0.2 0.0 Total 100.0 100.0 100.0 100.0 100.0 100.0 Number of women 4,180 1,714 1,117 348 31 56 Median months pregnant at first visit (for those with ANC) 3.7 3.8 3.4 4.4 2.8 4.0 Number of women with ANC 3,358 1,355 697 153 30 37 Appendix B • 245 SAMPLE DESIGN AND IMPLEMENTATION Appendix B B.1 INTRODUCTION The 2012-13 Pakistan Demographic and Health Survey (PDHS) is the third DHS in Pakistan, following those implemented in 1990-91 and 2006-07. A nationally representative sample of 14,000 households from 500 primary sampling units (PSUs) was selected. All ever-married women age 15-49 in selected households (both de jure and de facto) were eligible for individual interviews. In the selected households, 14,569 eligible women were identified for individual interviews and 13,558 were successfully interviewed. As with previous PDHS surveys, the main objective of the 2012-13 PDHS was to provide reliable information on fertility and fertility preferences; awareness, approval, and use of family planning methods; maternal and child health; childhood mortality levels; knowledge and attitudes toward HIV/AIDS other sexually transmitted infections (STIs); and knowledge about other illnesses such as tuberculosis, hepatitis B, and hepatitis C. The survey was designed to produce reliable estimates for key indicators at the national and provincial levels, including urban-rural breakdowns, as well as for Gilgit Baltistan and ICT Islamabad. One in three households in the survey was selected for a male survey. In these households, all ever-married men age 15-49 who were usual members of the selected households or who spent the night before the survey in the selected households were eligible for individual interviews. The survey collected information on their basic demographic status and knowledge and attitudes toward HIV/AIDS and other sexually transmitted infections. In the households selected for the male survey, all eligible women age 15- 49 and children under age 5 were measured for their height and weight. B.2 SAMPLE FRAME The universe consists of all of the urban and rural areas of the four provinces of Pakistan, Gilgit Baltistan, and ICT Islamabad, defined as such by 1998 population census and excluding Azad Jammu and Kashmir, the Federally Administered Tribal Areas, and military restricted and protected areas of Pakistan. Each province in Pakistan is subdivided into divisions, each division into districts, each district into Tehsils, and each Tehsil into urban and rural areas. Urban areas are subdivided into municipal committees/town committees/cantonments, which are further divided into urban circles. Urban circles consist of enumeration blocks. Rural areas are subdivided into Qanungo Halqa/Union Council/Tapedar Circle and further subdivided into villages/dehs. The Pakistan Bureau of Statistics (PBS) developed its own urban area frame. All urban areas comprising cities and towns were divided into mutually exclusive small compact areas known as enumeration blocks (EBs), identifiable through sketch maps. Each EB, consisting of about 200-250 households on average, was further categorized into low-, middle-, and high-income groups, keeping in view the socioeconomic status of households in the block. The urban area sampling frame consists of 26,543 EB, a figure that was updated through the economic census conducted in 2003-04. In the case of rural areas, the lists of villages/mouzas/dehs developed through the 1998 population census were used as the sampling frame. In this frame, each village/mouza/deh is identifiable by its name, Had Bast number, and Cadastral map and the name of the Tehsil, district, and province in which it is located. The rural sampling frame, comprising 46,307 mouzas/dehs/villages, was used in drawing the sample for this survey. Details on the urban and rural area frames are provided below: 246 • Appendix B Table B.1 Enumeration areas Distribution of the enumeration areas in the sampling frame by region and residence, Pakistan 2012-13 Region Enumeration blocks No. of villages Urban Rural Punjab 14,549 25,875 Sindh 9,052 5,870 Khyber Pakhtunkhwa 1,936 7,337 Balochistan 618 6,527 ICT Islamabad 324 132 Gilgit Baltistan 64 566 Pakistan 26,543 46,307 B.3 SAMPLE DESIGN AND IMPLEMENTATION A two-stage stratified sample design was adopted for this survey. Enumeration blocks demarcated as part of the urban sampling frame in the urban domain and mouzas/dehs/villages in the rural domain were taken as PSUs. In the first stage, 500 PSUs—248 urban areas and 252 rural areas—were selected using a probability proportional to size sampling scheme with independent selection in each sampling stratum. The number of households in each enumeration block (as per the 2003-04 economic census) and the number in each village/mouza/deh (as per the 1998 population census) were considered as the measure of size. A total of 143 sample points were selected in Punjab, 106 in Sindh, 91 in Khyber Pakhtunkhwa, 67 in Balochistan, 48 in ICT Islamabad, and 45 in Gilgit Baltistan (Table B.2). The PBS staff undertook the task of compiling a fresh listing of households in the selected EBs and villages. Among the 500 sample points, listing operations could not be carried out in two areas of Balochistan (Punjgur and Dera Bugti) due to the law and order situation. The resulting lists of households served as the sampling frame for the selection of households in the second stage. In urban areas, enumeration blocks were considered as PSUs. The sketch map of enumeration blocks demarcated by the PBS for urban areas of Pakistan was used to perform listing activities. In rural areas, villages were treated as PSUs. Large villages with populations above 2,000 (as per the 1998 population census) were split into hamlets and blocks of equal size. One block was selected randomly for data collection. In the case of small villages, the entire village was listed. In the second stage, a fixed number of households (28) were selected from each sample point, adopting a systematic sampling technique with a random start. In this way, 14,000 households were allocated. Households were considered as secondary sampling units. Table B.2 shows the sample allocation of PSUs and households by region, according to residence. Of the allocated households, 6,944 were in urban areas and 7,056 in rural areas. Table B.2 Sample allocation of clusters and households Sample allocation of clusters and households by region, according to residence, Pakistan 2012-13 Region Allocation of clusters Allocation of households Urban Rural Total Urban Rural Total Punjab 58 85 143 1,624 2,380 4,004 Sindh 64 42 106 1,792 1,176 2,968 Khyber Pakhtunkhwa 35 56 91 980 1,568 2,548 Balochistan 33 34 67 924 952 1,876 ICT Islamabad 35 13 48 980 364 1,344 Gilgit Baltistan 23 22 45 644 616 1,260 Pakistan 248 252 500 6,944 7,056 14,000 The provincial population distribution ranges from 5 percent in Balochistan to 55 percent in Punjab. A proportional allocation provides the best precision for national-level indictors but not for provincial/regional-level indicators. Because regions with smaller populations such as ICT Islamabad, Appendix B • 247 Gilgit Baltistan, and Balochistan would be allocated a very small sample size, the sample was not spread geographically in proportion to the population; rather, smaller geographic regions were oversampled. As a result, the final sample allocation was not self-weighting at the national level. Oversampling of urban areas was adjusted to the actual proportions by applying sampling weights during analysis. Sample Implementation Tables B.3 and B.4 present response rates for women and men, respectively, by urban and rural areas and by regions. The male subsample constituted one in three of the households selected for the woman’s sample. Table B.3 Sample implementation: Women Percent distribution of households and eligible women by results of the household and individual interviews, and household, eligible women, and overall women response rates, according to urban-rural residence and region (unweighted), Pakistan 2012-13 Residence Region Total Result Urban Rural Punjab Sindh Khyber Pakhtunkhwa Balochistan ICT Islamabad Gilgit Baltistan Selected households Completed (C) 91.2 94.4 94.5 95.9 94.1 86.2 87.3 93.1 92.8 Household present but no competent respondent at home (HP) 1.6 1.4 2.0 0.4 0.9 3.5 1.3 0.6 1.5 Postponed (P) 0.1 0.2 0.0 0.0 0.0 0.4 0.1 1.0 0.2 Refused (R) 2.9 0.5 0.6 0.9 1.0 2.7 7.6 1.0 1.7 Dwelling not found (DNF) 0.4 0.3 0.2 0.2 0.3 1.4 0.1 0.0 0.4 Household absent (HA) 2.4 2.1 1.7 1.3 2.3 4.2 3.1 2.1 2.2 Dwelling vacant/address not a dwelling (DV) 1.2 0.7 0.7 1.1 0.8 0.6 0.4 2.1 0.9 Dwelling destroyed (DD) 0.1 0.2 0.1 0.1 0.0 0.8 0.0 0.0 0.2 Other (O) 0.1 0.2 0.0 0.0 0.5 0.1 0.1 0.1 0.1 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Number of sampled households 6,944 7,000 4,004 2,968 2,548 1,820 1,344 1,260 13,944 Household response rate (HRR)1 94.8 97.5 97.1 98.4 97.7 91.5 90.5 97.3 96.1 Eligible women Completed (EWC) 91.2 94.8 92.9 93.2 95.1 93.1 85.7 94.9 93.1 Not at home (EWNH) 5.6 4.2 5.6 4.6 3.6 5.9 6.1 3.5 4.9 Postponed (EWP) 0.1 0.1 0.0 0.0 0.0 0.0 0.5 0.6 0.1 Refused (EWR) 2.2 0.4 0.9 1.3 1.0 0.6 6.3 0.1 1.3 Partly completed (EWPC) 0.4 0.1 0.2 0.3 0.2 0.3 0.7 0.0 0.3 Incapacitated (EWI) 0.4 0.2 0.3 0.4 0.1 0.0 0.4 0.5 0.3 Other (EWO) 0.1 0.1 0.1 0.0 0.0 0.1 0.2 0.4 0.1 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Number of women 6,964 7,605 4,089 3,154 2,835 2,098 1,112 1,281 14,569 Eligible women response rate (EWRR)2 91.2 94.8 92.9 93.2 95.1 93.1 85.7 94.9 93.1 Overall women response rate (ORR)3 86.4 92.4 90.2 91.7 92.9 85.2 77.6 92.3 89.5 1 Using the number of households falling into specific response categories, the household response rate (HRR) is calculated as: 100 * C ——————————— C + HP + P + R + DNF 2 The eligible women response rate (EWRR) is equivalent to the percentage of interviews completed (EWC). 3 The overall women response rate (OWRR) is calculated as: OWRR = HRR * EWRR/100 248 • Appendix B Table B.4 Sample implementation: Men Percent distribution of households and eligible men by results of the household and individual interviews, and household, eligible men, and overall men response rates, according to urban-rural residence and region (unweighted), Pakistan 2012-13 Residence Region Result Urban Rural Punjab Sindh Khyber Pakhtunkhwa Balochistan ICT Islamabad Gilgit Baltistan Total Selected households Completed (C) 91.7 95.2 95.2 96.2 93.3 89.5 88.8 92.2 93.4 Household present but no competent respondent at home (HP) 1.3 1.2 1.7 0.2 1.1 2.2 1.3 0.9 1.2 Postponed (P) 0.1 0.2 0.0 0.0 0.0 0.5 0.0 1.1 0.2 Refused (R) 3.1 0.4 0.6 1.1 1.2 2.3 7.8 0.9 1.7 Dwelling not found (DNF) 0.2 0.1 0.0 0.2 0.3 0.6 0.0 0.0 0.2 Household absent (HA) 2.3 2.0 1.7 1.2 2.9 3.4 1.9 2.7 2.1 Dwelling vacant/address not a dwelling (DV) 1.1 0.6 0.7 1.0 0.7 0.9 0.2 2.2 0.9 Dwelling destroyed (DD) 0.1 0.2 0.1 0.0 0.0 0.6 0.0 0.0 0.1 Other (O) 0.0 0.2 0.0 0.0 0.6 0.0 0.0 0.0 0.1 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Number of sampled households 2,476 2,496 1,430 1,060 908 649 475 450 4,972 Household response rate (HRR)1 95.1 98.0 97.6 98.5 97.2 94.2 90.8 97.0 96.6 Eligible men Completed (EMC) 75.8 81.3 72.3 82.6 78.4 83.1 77.7 80.1 78.5 Not at home (EMNH) 20.9 17.5 26.7 15.0 19.6 16.1 15.2 16.0 19.2 Postponed (EMP) 0.0 0.2 0.0 0.0 0.0 0.0 0.3 1.3 0.1 Refused (EMR) 2.7 0.3 0.5 1.5 1.7 0.8 5.5 1.3 1.5 Partly completed (EMPC) 0.2 0.1 0.2 0.1 0.0 0.0 0.6 0.3 0.2 Incapacitated (EMI) 0.2 0.3 0.1 0.5 0.3 0.0 0.0 0.7 0.3 Other (EMO) 0.1 0.3 0.2 0.2 0.0 0.0 0.8 0.3 0.2 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Number of men 2,007 1,984 1,106 918 634 663 363 307 3,991 Eligible men response rate (EMRR)2 75.8 81.3 72.3 82.6 78.4 83.1 77.7 80.1 78.5 Overall men response rate (ORR)3 72.1 79.7 70.6 81.3 76.2 78.3 70.5 77.7 75.8 1 Using the number of households falling into specific response categories, the household response rate (HRR) is calculated as: 100 * C ——————————— C + HP + P + R + DNF 2 The eligible men response rate (EMRR) is equivalent to the percentage of interviews completed (EMC). 3 The overall men response rate (OMRR) is calculated as: OMRR = HRR * EMRR/100 B.4 SELECTION PROBABILITIES AND SAMPLE WEIGHTS Since the PDHS sample is a two-stage stratified cluster sample, sampling weights were calculated based on sampling probabilities separately for each sampling stage and for each EB/village. We use the following notations: P1hi: first-stage sampling probability of the ith PSU in stratum h P2hi: second-stage sampling probability within the ith PSU (households) Let ah be the number of PSUs selected in stratum h, Mhi the number of households according to the sampling frame in the ith PSU, and M hi the total number of households in the stratum. The probability of selecting the ith PSU in the 2012-13 PDHS sample was calculated as follows: M M a hi hih  Appendix B • 249 Let hib be the proportion of households in the selected cluster compared to the total number of households in cluster i in stratum h if the cluster is segmented, otherwise 1=hib . Then the probability of selecting cluster i in the sample is: hi hi hih 1hi b M M a = P × Let hiL be the number of households listed in the household listing operation in cluster i in stratum h, and let hig be the number of households selected in the cluster. The second stage’s selection probability for each household in the cluster is calculated as follows: hi hi hi L g P =2 The overall selection probability of each household in cluster i of stratum h is therefore the product of the two-stage selection probabilities: hihihi PPP 21 ×= The design weight for each household in cluster i of stratum h is the inverse of its overall selection probability: hihi PW /1= Design weights were adjusted for household non-response as well as for individual (women and men) non-response to get the sampling weights. Sampling weights are normalized so that the number of weighted cases equals the number of unweighted cases at the national level for households, women, and men, respectively. Normalized weights are valid for estimating means, proportions, and ratios but are not valid for estimating population totals or for pooled data. Appendix C • 251 ESTIMATES OF SAMPLING ERRORS Appendix C The estimates from a sample survey are affected by two types of errors: non-sampling errors and sampling errors. Non-sampling errors are the results of mistakes made in implementing data collection and data processing, such as failure to locate and interview the correct household, misunderstanding of the questions on the part of either the interviewer or the respondent, and data entry errors. Although numerous efforts were made during the implementation of the 2012-13 Pakistan Demographic and Health Survey (PDHS) to minimize this type of error, non-sampling errors are impossible to avoid and difficult to evaluate statistically. Sampling errors, on the other hand, can be evaluated statistically. The sample of respondents selected in the 2012-13 PDHS is only one of many samples that could have been selected from the same population, using the same design and expected size. Each of these samples would yield results that differ somewhat from the results of the actual sample selected. Sampling errors are a measure of the variability between all possible samples. Although the degree of variability is not known exactly, it can be estimated from the survey results. Sampling error is usually measured in terms of the standard error for a particular statistic (mean, percentage, etc.), which is the square root of the variance. The standard error can be used to calculate confidence intervals within which the true value for the population can reasonably be assumed to fall. For example, for any given statistic calculated from a sample survey, the value of that statistic will fall within a range of plus or minus two times the standard error of that statistic in 95 percent of all possible samples of identical size and design. If the sample of respondents had been selected as a simple random sample, it would have been possible to use straightforward formulas for calculating sampling errors. However, the 2012-13 PDHS sample is the result of a multi-stage stratified design, and, consequently, it was necessary to use more complex formulae. Sampling errors are computed in either ISSA or SAS, using programs developed by ICF International. These programs use the Taylor linearization method of variance estimation for survey estimates that are means, proportions, or ratios. The Jackknife repeated replication method is used for variance estimation of more complex statistics such as fertility and mortality rates. The Taylor linearization method treats any percentage or average as a ratio estimate, r = y x , where y represents the total sample value for variable y and x represents the total number of cases in the group or subgroup under consideration. The variance of r is computed using the formula given below, with the standard error being the square root of the variance: ( ) ( ) 2 2 2 2 1 1 1var 1 hmH h h hi h ih h f m zSE r = r z x m m = =    − = −   −     in which hi hi hiz = y rx− , and h h hz = y rx− where h represents the stratum which varies from 1 to H, hm is the total number of clusters selected in the hth stratum, hiy is the sum of the weighted values of variable y in the ith cluster in the hth stratum, hix is the sum of the weighted number of cases in the ith cluster in the hth stratum, and 252 • Appendix C f is the overall sampling fraction, which is so small that it is ignored. The Jackknife repeated replication method derives estimates of complex rates from each of several replications of the parent sample and calculates standard errors for these estimates using simple formulae. Each replication considers all but one cluster in the calculation of the estimates. Pseudo-independent replications are thus created. In the 2012-13 PDHS, there were 500 non-empty clusters. Hence, 422 replications were created. The variance of a rate r is calculated as follows: ( ) ( ) ( ) ( ) 22 1 1var 1 k i i SE r = r r r k k = = − −  in which ( ) ( )1i ir = kr k r− − where r is the estimate computed from the full sample of 500 clusters, ( )ir is the estimate computed from the reduced sample of 499 clusters (i th cluster excluded), and k is the total number of clusters. In addition to the standard error, the design effect (DEFT) for each estimate is also calculated. The design effect is defined as the ratio between the standard error using the given sample design and the standard error that would result if a simple random sample had been used. A DEFT value of 1.0 indicates that the sample design is as efficient as a simple random sample, while a value greater than 1.0 indicates the increase in the sampling error due to the use of a more complex and less statistically efficient design. Relative standard errors and confidence limits for the estimates are also calculated. Sampling errors for the 2012-13 PDHS are calculated for selected variables considered to be of primary interest. The results are presented in this appendix for the country as a whole, for urban and rural areas, and for each of the six regions. For each variable, the type of statistic (mean, proportion, or rate) and the base population are given in Table C.1. Tables C.2 through C.10 present the value of the statistic (R), its standard error (SE), the number of unweighted (N) and weighted (WN) cases, the design effect (DEFT), the relative standard error (SE/R), and the 95 percent confidence limits (R±2SE) for each selected variable. The DEFT is considered undefined when the standard error considering a simple random sample is zero (when the estimate is close to 0 or 1). The confidence interval (e.g., as calculated for children ever born to women age 40-49) can be interpreted as follows: the overall average from the national sample is 5.619 and its standard error is 0.074. Therefore, to obtain the 95 percent confidence limits, one adds and subtracts twice the standard error to the sample estimate, i.e., 5.619±2×0.074. There is a high probability (95 percent) that the true proportion of women age 40-49 with children ever born is between 5.471 and 5.766. For the total sample, the value of the DEFT, averaged over all variables, is 1.728. This means that, due to multi-stage clustering of the sample, the average standard error is increased by a factor of 1.728 over that in an equivalent simple random sample. Appendix C • 253 Table C.1 List of selected variables for sampling errors, Pakistan 2012-13 Variable Estimate Base population WOMEN Urban residence Proportion Ever-married women 15-49 Literacy Proportion Ever-married women 15-49 No education Proportion Ever-married women 15-49 Secondary education or higher Proportion Ever-married women 15-49 Never married Proportion All women 15-49 Currently married Proportion All women 15-49 Married before age 20 Proportion All women 20-49 Married to first cousin Proportion Ever-married women 15-49 Currently pregnant Proportion All women 15-49 Children ever born Mean All women 15-49 Children surviving Mean All women 15-49 Children ever born to women age 40-49 Mean All women 40-49 Know any contraceptive method Proportion Currently married women 15-49 Know a modern method Proportion Currently married women 15-49 Ever used a contraceptive method Proportion Currently married women 15-49 Currently using any method Proportion Currently married women 15-49 Currently using a modern method Proportion Currently married women 15-49 Currently using a traditional method Proportion Currently married women 15-49 Currently using pill Proportion Currently married women 15-49 Currently using IUD Proportion Currently married women 15-49 Currently using condoms Proportion Currently married women 15-49 Currently using injectables Proportion Currently married women 15-49 Currently using female sterilization Proportion Currently married women 15-49 Currently using rhythm Proportion Currently married women 15-49 Currently using withdrawal Proportion Currently married women 15-49 Used public sector source Proportion Current users of modern method Want no more children Proportion Currently married women 15-49 Want to delay next birth at least 2 years Proportion Currently married women 15-49 Ideal number of children Mean All women 15-49 Mothers received antenatal care for last birth Proportion Women with a live birth in last five years Mothers protected against tetanus for last birth Proportion Women with a live birth in last five years Births with skilled attendant at delivery Proportion Births occurring 1-59 months before survey Had diarrhea in the past 2 weeks Proportion Children under 5 Treated with ORS Proportion Children under 5 with diarrhea in past 2 weeks Sought medical treatment for diarrhea Proportion Children under 5 with diarrhea in past 2 weeks Vaccination card seen Proportion Children 12-23 months Received BCG vaccination Proportion Children 12-23 months Received DPT vaccination (3 doses) Proportion Children 12-23 months Received polio vaccination (3 doses) Proportion Children 12-23 months Received measles vaccination Proportion Children 12-23 months Received all vaccinations Proportion Children 12-23 months Height-for-age (-2 SD) Proportion Children under 5 who are measured Weight-for-height (-2 SD) Proportion Children under 5 who are measured Weight-for-age (-2 SD) Proportion Children under 5 who are measured Body mass index (BMI) <18.5 Proportion All women 15-49 who were measured Accepting attitudes toward people with HIV Proportion All women who have heard of HIV/AIDS Ever experienced any physical violence since age 15 Proportion Ever-married women 15-49 Ever experienced any physical violence by husband Proportion Ever-married women 15-49 Ever experienced any physical violence in the last 12 months Proportion Ever-married women 15-49 Total fertility rate (3 years) Rate Women-years of exposure to childbearing Neonatal mortality rate¹ Rate Children exposed to the risk of mortality Post-neonatal mortality rate¹ Rate Children exposed to the risk of mortality Infant mortality rate¹ Rate Children exposed to the risk of mortality Child mortality rate¹ Rate Children exposed to the risk of mortality Under-five mortality rate¹ Rate Children exposed to the risk of mortality MEN Urban residence Proportion Ever-married men 15-49 Literacy Proportion Ever-married men 15-49 No education Proportion Ever-married men 15-49 Secondary education or higher Proportion Ever-married men 15-49 Never married Proportion All men 15-49 Currently married Proportion All men 15-49 Know any contraceptive method Proportion Currently married men 15-49 Know a modern method Proportion Currently married men 15-49 Want no more children Proportion Currently married men 15-49 Want to delay next birth at least 2 years Proportion Currently married men 15-49 Ideal number of children Mean All men 15-49 1 The mortality rates are calculated for 5 years and 10 years before the survey for the national sample and regional samples, respectively. 254 • Appendix C Table C.2 Sampling errors for national sample, Pakistan 2012-13 Value (R) Standard error (SE) Number of cases Design effect (DEFT) Relative error (SE/R) Confidence limits Variable Unweighted (N) Weighted (WN) R-2SE R+2SE WOMEN Urban residence 0.335 0.009 13558 13558 2.165 0.026 0.317 0.352 Literacy 0.434 0.011 13558 13558 2.519 0.025 0.413 0.455 No education 0.571 0.011 13558 13558 2.574 0.019 0.549 0.592 Secondary education or higher 0.197 0.009 13558 13558 2.701 0.047 0.179 0.216 Never married 0.333 0.013 20286 20321 1.407 0.039 0.307 0.359 Currently married 0.637 0.012 20286 20321 1.368 0.019 0.613 0.661 Married before age 20 0.489 0.007 16094 16052 1.969 0.015 0.475 0.504 Married to first cousin 0.485 0.009 13558 13558 2.193 0.019 0.466 0.504 Currently pregnant 0.072 0.003 20286 20321 1.394 0.039 0.066 0.077 Children ever born 2.416 0.053 20286 20321 1.340 0.022 2.310 2.522 Children surviving 2.145 0.048 20286 20321 1.377 0.022 2.049 2.241 Children ever born to women age 40-49 5.619 0.074 3547 3427 1.567 0.013 5.471 5.766 Know any contraceptive method 0.989 0.002 13010 12937 1.658 0.002 0.986 0.992 Know a modern method 0.987 0.002 13010 12937 1.811 0.002 0.983 0.991 Ever used a contraceptive method 0.548 0.008 13010 12937 1.933 0.015 0.531 0.565 Currently using any method 0.354 0.008 13010 12937 1.976 0.023 0.338 0.371 Currently using a modern method 0.261 0.007 13010 12937 1.786 0.026 0.247 0.275 Currently using a traditional method 0.093 0.004 13010 12937 1.729 0.047 0.084 0.102 Currently using pill 0.016 0.002 13010 12937 1.390 0.096 0.013 0.019 Currently using IUD 0.023 0.002 13010 12937 1.591 0.091 0.019 0.027 Currently using condoms 0.088 0.004 13010 12937 1.716 0.048 0.080 0.097 Currently using injectables 0.028 0.002 13010 12937 1.458 0.076 0.023 0.032 Currently using female sterilization 0.087 0.004 13010 12937 1.694 0.048 0.078 0.095 Currently using rhythm 0.007 0.001 13010 12937 1.680 0.181 0.004 0.009 Currently using withdrawal 0.085 0.004 13010 12937 1.666 0.048 0.077 0.093 Used public sector source 0.456 0.016 3363 3160 1.835 0.035 0.424 0.487 Want no more children 0.512 0.006 13010 12937 1.462 0.013 0.499 0.525 Want to delay next birth at least 2 years 0.191 0.005 13010 12937 1.348 0.024 0.182 0.201 Ideal number of children 4.076 0.037 13000 12992 2.477 0.009 4.003 4.149 Mothers received antenatal care for last birth 0.731 0.011 7461 7446 2.110 0.015 0.709 0.752 Mothers protected against tetanus for last birth 0.639 0.013 7461 7446 2.295 0.020 0.614 0.665 Births with skilled attendant at delivery 0.521 0.016 11763 11977 2.682 0.030 0.490 0.552 Had diarrhea in the past 2 weeks 0.225 0.007 10935 11040 1.722 0.032 0.210 0.239 Treated with ORS 0.380 0.017 2298 2482 1.630 0.045 0.346 0.415 Sought medical treatment for diarrhea 0.610 0.016 2298 2482 1.519 0.027 0.578 0.642 Vaccination card seen 0.360 0.016 2039 2074 1.511 0.044 0.329 0.392 Received BCG vaccination 0.852 0.012 2039 2074 1.573 0.014 0.827 0.876 Received DPT vaccination (3 doses) 0.652 0.020 2039 2074 1.908 0.031 0.612 0.692 Received polio vaccination (3 doses) 0.853 0.013 2039 2074 1.623 0.015 0.827 0.878 Received measles vaccination 0.614 0.017 2039 2074 1.618 0.028 0.579 0.648 Received all vaccinations 0.538 0.019 2039 2074 1.713 0.035 0.500 0.575 Height-for-age (-2 SD) 0.448 0.014 3134 3466 1.402 0.031 0.420 0.475 Weight-for-height (-2 SD) 0.108 0.010 3134 3466 1.884 0.092 0.088 0.128 Weight-for-age (-2 SD) 0.300 0.014 3134 3466 1.581 0.048 0.271 0.328 Body mass index (BMI) <18.5 0.139 0.009 4029 4170 1.766 0.068 0.120 0.158 Accepting attitudes toward people with HIV 0.165 0.008 5906 5675 1.556 0.046 0.150 0.180 Ever experienced any physical violence since age 15 0.322 0.012 3687 3687 1.543 0.037 0.298 0.345 Ever experienced any physical violence by husband 0.271 0.011 3687 3687 1.543 0.042 0.248 0.293 Ever experienced any physical violence in the last 12 months 0.180 0.010 3687 3687 1.537 0.054 0.160 0.199 Total fertility rate (3 years) 3.831 0.061 57239 57617 1.341 0.016 3.709 3.953 Neonatal mortality rate (last 0-4 years) 55.110 3.565 11866 12103 1.515 0.065 47.980 62.239 Post-neonatal mortality rate (last 0-4 years) 18.520 1.816 11875 12144 1.388 0.098 14.888 22.152 Infant mortality rate (last 0-4 years) 73.630 3.730 11881 12120 1.353 0.051 66.170 81.090 Child mortality rate (last 0-4 years) 16.544 1.886 11848 12037 1.709 0.114 12.772 20.315 Under-five mortality rate (last 0-4 years) 88.955 4.471 11948 12196 1.543 0.050 80.013 97.898 MEN Urban residence 0.353 0.016 3134 3134 1.882 0.046 0.321 0.385 Literacy 0.654 0.014 3134 3134 1.643 0.021 0.626 0.682 No education 0.289 0.014 3134 3134 1.729 0.048 0.261 0.317 Secondary education or higher 0.334 0.017 3134 3134 1.979 0.050 0.301 0.368 Never married 0.476 0.057 5712 5982 1.631 0.120 0.362 0.590 Currently married 0.513 0.056 5712 5982 1.633 0.109 0.401 0.626 Know any contraceptive method 0.957 0.006 3085 3071 1.701 0.007 0.944 0.969 Know a modern method 0.948 0.007 3085 3071 1.779 0.007 0.934 0.962 Want no more children 0.417 0.015 3085 3071 1.710 0.036 0.387 0.448 Want to delay next birth at least 2 years 0.208 0.011 3085 3071 1.495 0.053 0.186 0.230 Ideal number of children 4.296 0.055 2971 2910 1.497 0.013 4.186 4.406 Appendix C • 255 Table C.3 Sampling errors for urban areas, Pakistan 2012-13 Value (R) Standard error (SE) Number of cases Design effect (DEFT) Relative error (SE/R) Confidence limits Variable Unweighted (N) Weighted (WN) R-2SE R+2SE WOMEN Urban residence 1.000 0.000 6351 4536 na 0.000 1.000 1.000 Literacy 0.689 0.019 6351 4536 3.190 0.027 0.652 0.726 No education 0.321 0.020 6351 4536 3.393 0.062 0.281 0.361 Secondary education or higher 0.394 0.024 6351 4536 3.877 0.060 0.347 0.442 Never married 0.242 0.013 10390 7103 1.739 0.055 0.216 0.269 Currently married 0.606 0.024 10390 7103 1.378 0.039 0.559 0.653 Married before age 20 0.399 0.010 7907 5588 1.812 0.024 0.380 0.418 Married to first cousin 0.379 0.012 6351 4536 1.978 0.032 0.354 0.403 Currently pregnant 0.055 0.005 10390 7103 1.767 0.086 0.046 0.065 Children ever born 2.149 0.093 10390 7103 1.397 0.043 1.963 2.335 Children surviving 1.960 0.086 10390 7103 1.414 0.044 1.789 2.131 Children ever born to women age 40-49 5.064 0.124 1810 1285 1.993 0.024 4.816 5.312 Know any contraceptive method 0.993 0.002 6071 4304 2.169 0.002 0.988 0.997 Know a modern method 0.992 0.002 6071 4304 2.136 0.002 0.987 0.997 Ever used a contraceptive method 0.651 0.012 6071 4304 2.026 0.019 0.626 0.676 Currently using any method 0.448 0.015 6071 4304 2.355 0.034 0.418 0.478 Currently using a modern method 0.320 0.012 6071 4304 2.068 0.039 0.296 0.345 Currently using a traditional method 0.128 0.008 6071 4304 1.977 0.066 0.111 0.145 Currently using pill 0.015 0.002 6071 4304 1.178 0.122 0.011 0.019 Currently using IUD 0.026 0.005 6071 4304 2.250 0.176 0.017 0.035 Currently using condoms 0.148 0.007 6071 4304 1.571 0.048 0.133 0.162 Currently using injectables 0.025 0.003 6071 4304 1.589 0.128 0.018 0.031 Currently using female sterilization 0.096 0.006 6071 4304 1.583 0.062 0.084 0.108 Currently using rhythm 0.010 0.003 6071 4304 2.243 0.291 0.004 0.015 Currently using withdrawal 0.117 0.008 6071 4304 1.850 0.065 0.102 0.133 Used public sector source 0.349 0.022 1908 1353 2.019 0.063 0.305 0.393 Want no more children 0.547 0.009 6071 4304 1.455 0.017 0.529 0.566 Want to delay next birth at least 2 years 0.185 0.008 6071 4304 1.666 0.045 0.168 0.201 Ideal number of children 3.610 0.041 6082 4385 2.100 0.011 3.528 3.692 Mothers received antenatal care for last birth 0.878 0.014 3278 2244 2.493 0.017 0.849 0.907 Mothers protected against tetanus for last birth 0.753 0.015 3278 2244 1.907 0.019 0.724 0.782 Births with skilled attendant at delivery 0.710 0.022 4970 3489 2.679 0.031 0.665 0.754 Had diarrhea in the past 2 weeks 0.219 0.011 4680 3281 1.744 0.052 0.196 0.242 Treated with ORS 0.415 0.036 934 719 2.145 0.086 0.343 0.487 Sought medical treatment for diarrhea 0.723 0.023 934 719 1.500 0.031 0.678 0.769 Vaccination card seen 0.457 0.025 878 640 1.515 0.056 0.406 0.508 Received BCG vaccination 0.930 0.012 878 640 1.420 0.013 0.905 0.955 Received DPT vaccination (3 doses) 0.790 0.018 878 640 1.326 0.023 0.754 0.827 Received polio vaccination (3 doses) 0.868 0.016 878 640 1.430 0.019 0.835 0.900 Received measles vaccination 0.743 0.022 878 640 1.532 0.030 0.699 0.788 Received all vaccinations 0.658 0.023 878 640 1.421 0.034 0.613 0.703 Height-for-age (-2 SD) 0.371 0.021 1356 1053 1.471 0.057 0.329 0.413 Weight-for-height (-2 SD) 0.099 0.014 1356 1053 1.797 0.142 0.071 0.126 Weight-for-age (-2 SD) 0.241 0.019 1356 1053 1.418 0.079 0.203 0.279 Body mass index (BMI) <18.5 0.074 0.009 1864 1403 1.480 0.118 0.057 0.092 Accepting attitudes toward people with HIV 0.173 0.010 3983 3135 1.697 0.059 0.152 0.193 Ever experienced any physical violence since age 15 0.284 0.019 1734 1216 1.752 0.067 0.246 0.322 Ever experienced any physical violence by husband 0.230 0.020 1734 1216 1.949 0.086 0.190 0.269 Ever experienced any physical violence in the last 12 months 0.151 0.016 1734 1216 1.852 0.106 0.119 0.183 Total fertility rate (3 years) 3.158 0.078 28940 20208 1.654 0.025 3.002 3.314 Neonatal mortality rate (last 0-9 years) 46.730 3.710 10106 6798 1.270 0.079 39.311 54.149 Post-neonatal mortality rate (last 0-9 years) 16.537 2.317 10112 6796 1.825 0.140 11.904 21.170 Infant mortality rate (last 0-9 years) 63.267 4.140 10115 6808 1.367 0.065 54.987 71.548 Child mortality rate (last 0-9 years) 11.477 1.700 10150 6741 1.344 0.148 8.078 14.877 Under-five mortality rate (last 0-9 years) 74.019 4.564 10135 6823 1.348 0.062 64.892 83.146 MEN Urban residence 1.000 0.000 1521 1107 na 0.000 1.000 1.000 Literacy 0.761 0.021 1521 1107 1.960 0.028 0.718 0.804 No education 0.175 0.020 1521 1107 2.094 0.117 0.134 0.216 Secondary education or higher 0.450 0.039 1521 1107 3.042 0.087 0.372 0.528 Never married 0.351 0.047 2393 1706 0.978 0.133 0.258 0.445 Currently married 0.639 0.046 2393 1706 0.975 0.072 0.547 0.732 Know any contraceptive method 0.974 0.010 1498 1091 2.311 0.010 0.955 0.993 Know a modern method 0.974 0.010 1498 1091 2.309 0.010 0.955 0.993 Want no more children 0.458 0.033 1498 1091 2.521 0.071 0.393 0.523 Want to delay next birth at least 2 years 0.198 0.017 1498 1091 1.661 0.086 0.164 0.232 Ideal number of children 3.937 0.092 1456 1047 2.035 0.023 3.753 4.121 na = Not applicable 256 • Appendix C Table C.4 Sampling errors for rural areas, Pakistan 2012-13 Value (R) Standard error (SE) Number of cases Design effect (DEFT) Relative error (SE/R) Confidence limits Variable Unweighted (N) Weighted (WN) R-2SE R+2SE WOMEN Urban residence 0.000 0.000 7207 9022 na na 0.000 0.000 Literacy 0.306 0.012 7207 9022 2.272 0.040 0.281 0.330 No education 0.696 0.013 7207 9022 2.336 0.018 0.671 0.721 Secondary education or higher 0.098 0.008 7207 9022 2.212 0.079 0.083 0.114 Never married 0.381 0.019 10592 13222 1.248 0.049 0.344 0.419 Currently married 0.653 0.014 10592 13222 1.242 0.021 0.625 0.681 Married before age 20 0.539 0.009 8398 10446 1.886 0.017 0.520 0.557 Married to first cousin 0.539 0.012 7207 9022 2.051 0.022 0.515 0.563 Currently pregnant 0.081 0.003 10592 13222 1.211 0.043 0.074 0.088 Children ever born 2.558 0.065 10592 13222 1.227 0.026 2.427 2.689 Children surviving 2.244 0.059 10592 13222 1.263 0.026 2.126 2.362 Children ever born to women age 40-49 5.944 0.090 1735 2145 1.319 0.015 5.765 6.123 Know any contraceptive method 0.987 0.002 6939 8633 1.442 0.002 0.983 0.991 Know a modern method 0.985 0.002 6939 8633 1.628 0.002 0.980 0.989 Ever used a contraceptive method 0.497 0.011 6939 8633 1.865 0.023 0.474 0.519 Currently using any method 0.307 0.010 6939 8633 1.829 0.033 0.287 0.327 Currently using a modern method 0.231 0.009 6939 8633 1.694 0.037 0.214 0.249 Currently using a traditional method 0.076 0.005 6939 8633 1.551 0.065 0.066 0.086 Currently using pill 0.016 0.002 6939 8633 1.377 0.129 0.012 0.020 Currently using IUD 0.022 0.002 6939 8633 1.230 0.099 0.017 0.026 Currently using condoms 0.058 0.005 6939 8633 1.778 0.086 0.048 0.068 Currently using injectables 0.029 0.003 6939 8633 1.347 0.094 0.024 0.034 Currently using female sterilization 0.082 0.006 6939 8633 1.683 0.068 0.071 0.093 Currently using rhythm 0.005 0.001 6939 8633 1.275 0.214 0.003 0.007 Currently using withdrawal 0.069 0.005 6939 8633 1.534 0.067 0.060 0.079 Used public sector source 0.536 0.022 1455 1807 1.669 0.041 0.492 0.579 Want no more children 0.494 0.008 6939 8633 1.376 0.017 0.478 0.511 Want to delay next birth at least 2 years 0.195 0.006 6939 8633 1.184 0.029 0.183 0.206 Ideal number of children 4.314 0.048 6918 8607 2.342 0.011 4.217 4.410 Mothers received antenatal care for last birth 0.667 0.014 4183 5202 1.855 0.020 0.640 0.694 Mothers protected against tetanus for last birth 0.590 0.017 4183 5202 2.247 0.029 0.556 0.624 Births with skilled attendant at delivery 0.444 0.019 6793 8488 2.442 0.042 0.406 0.481 Had diarrhea in the past 2 weeks 0.227 0.009 6255 7759 1.629 0.040 0.209 0.246 Treated with ORS 0.366 0.020 1364 1764 1.408 0.053 0.327 0.405 Sought medical treatment for diarrhea 0.564 0.019 1364 1764 1.347 0.035 0.525 0.603 Vaccination card seen 0.317 0.020 1161 1434 1.431 0.062 0.278 0.357 Received BCG vaccination 0.817 0.017 1161 1434 1.463 0.020 0.783 0.850 Received DPT vaccination (3 doses) 0.590 0.027 1161 1434 1.850 0.046 0.536 0.644 Received polio vaccination (3 doses) 0.846 0.017 1161 1434 1.570 0.020 0.812 0.879 Received measles vaccination 0.556 0.023 1161 1434 1.563 0.041 0.510 0.602 Received all vaccinations 0.484 0.025 1161 1434 1.684 0.051 0.435 0.534 Height-for-age (-2 SD) 0.482 0.017 1778 2413 1.271 0.035 0.448 0.516 Weight-for-height (-2 SD) 0.112 0.013 1778 2413 1.760 0.114 0.086 0.138 Weight-for-age (-2 SD) 0.325 0.018 1778 2413 1.481 0.057 0.288 0.362 Body mass index (BMI) <18.5 0.171 0.013 2165 2767 1.654 0.077 0.145 0.198 Accepting attitudes toward people with HIV 0.156 0.011 1923 2540 1.371 0.073 0.133 0.178 Ever experienced any physical violence since age 15 0.340 0.015 1953 2471 1.398 0.044 0.310 0.370 Ever experienced any physical violence by husband 0.291 0.014 1953 2471 1.330 0.047 0.264 0.318 Ever experienced any physical violence in the last 12 months 0.194 0.012 1953 2471 1.346 0.062 0.170 0.218 Total fertility rate (3 years) 4.195 0.081 29855 37450 1.208 0.019 4.033 4.356 Neonatal mortality rate (last 0-9 years) 61.957 3.117 13819 17007 1.205 0.050 55.723 68.191 Post-neonatal mortality rate (last 0-9 years) 25.746 1.887 13826 17028 1.291 0.073 21.972 29.520 Infant mortality rate (last 0-9 years) 87.703 3.478 13837 17026 1.096 0.040 80.746 94.659 Child mortality rate (last 0-9 years) 20.211 2.283 13887 16921 1.481 0.113 15.646 24.776 Under-five mortality rate (last 0-9 years) 106.142 4.385 13876 17072 1.231 0.041 97.372 114.911 MEN Urban residence 0.000 0.000 1613 2027 na na 0.000 0.000 Literacy 0.596 0.017 1613 2027 1.419 0.029 0.561 0.631 No education 0.351 0.017 1613 2027 1.464 0.050 0.316 0.386 Secondary education or higher 0.271 0.014 1613 2027 1.295 0.053 0.243 0.300 Never married 0.526 0.071 3319 4276 1.538 0.135 0.384 0.668 Currently married 0.463 0.069 3319 4276 1.540 0.150 0.324 0.602 Know any contraceptive method 0.947 0.008 1587 1980 1.422 0.008 0.931 0.963 Know a modern method 0.934 0.009 1587 1980 1.521 0.010 0.915 0.953 Want no more children 0.395 0.016 1587 1980 1.288 0.040 0.363 0.427 Want to delay next birth at least 2 years 0.214 0.014 1587 1980 1.357 0.065 0.186 0.242 Ideal number of children 4.498 0.072 1515 1863 1.316 0.016 4.354 4.642 na = Not applicable Appendix C • 257 Table C.5 Sampling errors for Punjab, Pakistan 2012-13 Value (R) Standard error (SE) Number of cases Design effect (DEFT) Relative error (SE/R) Confidence limits Variable Unweighted (N) Weighted (WN) R-2SE R+2SE WOMEN Urban residence 0.324 0.014 3800 7790 1.789 0.042 0.297 0.351 Literacy 0.499 0.017 3800 7790 2.116 0.034 0.465 0.534 No education 0.511 0.017 3800 7790 2.130 0.034 0.477 0.546 Secondary education or higher 0.204 0.014 3800 7790 2.194 0.070 0.175 0.233 Never married 0.297 0.018 5507 11539 1.281 0.062 0.260 0.334 Currently married 0.639 0.020 5507 11539 1.257 0.031 0.599 0.679 Married before age 20 0.453 0.012 4520 9252 1.713 0.026 0.429 0.476 Married to first cousin 0.477 0.015 3800 7790 1.807 0.031 0.447 0.506 Currently pregnant 0.067 0.004 5507 11539 1.194 0.064 0.059 0.076 Children ever born 2.399 0.084 5507 11539 1.174 0.035 2.231 2.567 Children surviving 2.105 0.076 5507 11539 1.221 0.036 1.953 2.258 Children ever born to women age 40-49 5.433 0.104 995 1974 1.204 0.019 5.224 5.642 Know any contraceptive method 0.996 0.001 3595 7374 1.368 0.001 0.993 0.999 Know a modern method 0.995 0.002 3595 7374 1.344 0.002 0.992 0.998 Ever used a contraceptive method 0.612 0.011 3595 7374 1.393 0.019 0.589 0.635 Currently using any method 0.407 0.013 3595 7374 1.532 0.031 0.382 0.432 Currently using a modern method 0.290 0.010 3595 7374 1.290 0.034 0.270 0.309 Currently using a traditional method 0.117 0.007 3595 7374 1.387 0.064 0.102 0.132 Currently using pill 0.011 0.002 3595 7374 1.137 0.179 0.007 0.015 Currently using IUD 0.029 0.003 3595 7374 1.241 0.120 0.022 0.036 Currently using condoms 0.099 0.007 3595 7374 1.398 0.070 0.085 0.113 Currently using injectables 0.020 0.003 3595 7374 1.204 0.142 0.014 0.025 Currently using female sterilization 0.102 0.006 3595 7374 1.199 0.059 0.090 0.114 Currently using rhythm 0.010 0.002 3595 7374 1.233 0.203 0.006 0.014 Currently using withdrawal 0.106 0.007 3595 7374 1.330 0.065 0.092 0.119 Used public sector source 0.484 0.023 991 1953 1.417 0.047 0.439 0.529 Want no more children 0.540 0.010 3595 7374 1.157 0.018 0.521 0.559 Want to delay next birth at least 2 years 0.169 0.007 3595 7374 1.069 0.040 0.156 0.182 Ideal number of children 3.756 0.061 3632 7449 2.591 0.016 3.635 3.877 Mothers received antenatal care for last birth 0.778 0.014 2008 4180 1.560 0.018 0.750 0.807 Mothers protected against tetanus for last birth 0.738 0.016 2008 4180 1.645 0.022 0.706 0.770 Births with skilled attendant at delivery 0.525 0.024 3266 6859 2.108 0.045 0.478 0.572 Had diarrhea in the past 2 weeks 0.219 0.011 3013 6307 1.350 0.049 0.198 0.240 Treated with ORS 0.352 0.025 659 1381 1.232 0.070 0.303 0.401 Sought medical treatment for diarrhea 0.686 0.020 659 1381 1.019 0.029 0.646 0.726 Vaccination card seen 0.407 0.024 593 1215 1.182 0.059 0.359 0.455 Received BCG vaccination 0.916 0.014 593 1215 1.246 0.016 0.887 0.944 Received DPT vaccination (3 doses) 0.763 0.031 593 1215 1.729 0.040 0.702 0.824 Received polio vaccination (3 doses) 0.924 0.014 593 1215 1.301 0.015 0.896 0.952 Received measles vaccination 0.700 0.026 593 1215 1.389 0.038 0.647 0.753 Received all vaccinations 0.656 0.029 593 1215 1.481 0.044 0.598 0.714 Height-for-age (-2 SD) 0.398 0.020 1044 2155 1.133 0.050 0.358 0.437 Weight-for-height (-2 SD) 0.095 0.015 1044 2155 1.684 0.157 0.065 0.125 Weight-for-age (-2 SD) 0.261 0.021 1044 2155 1.342 0.082 0.218 0.304 Body mass index (BMI) <18.5 0.139 0.014 1207 2455 1.386 0.100 0.111 0.166 Accepting attitudes toward people with HIV 0.171 0.010 1896 3562 1.207 0.061 0.150 0.192 Ever experienced any physical violence since age 15 0.286 0.016 1092 2139 1.201 0.058 0.253 0.319 Ever experienced any physical violence by husband 0.234 0.016 1092 2139 1.225 0.067 0.203 0.266 Ever experienced any physical violence in the last 12 months 0.149 0.013 1092 2139 1.206 0.087 0.123 0.175 Total fertility rate (3 years) 3.765 0.079 15944 33167 1.059 0.021 3.607 3.922 Neonatal mortality rate (last 0-9 years) 63.199 3.753 6486 13551 0.967 0.059 55.692 70.706 Post-neonatal mortality rate (last 0-9 years) 24.881 2.361 6492 13575 1.156 0.095 20.160 29.603 Infant mortality rate (last 0-9 years) 88.080 4.170 6493 13568 0.881 0.047 79.740 96.421 Child mortality rate (last 0-9 years) 18.205 2.801 6382 13303 1.316 0.154 12.604 23.807 Under-five mortality rate (last 0-9 years) 104.682 5.488 6513 13606 1.017 0.052 93.705 115.659 MEN Urban residence 0.342 0.026 800 1804 1.559 0.077 0.290 0.395 Literacy 0.675 0.019 800 1804 1.167 0.029 0.637 0.714 No education 0.266 0.020 800 1804 1.263 0.074 0.227 0.306 Secondary education or higher 0.286 0.026 800 1804 1.605 0.090 0.234 0.337 Never married 0.463 0.097 1524 3358 1.291 0.210 0.268 0.657 Currently married 0.525 0.095 1524 3358 1.292 0.182 0.334 0.715 Know any contraceptive method 0.970 0.008 782 1761 1.325 0.008 0.954 0.986 Know a modern method 0.966 0.009 782 1761 1.338 0.009 0.949 0.983 Want no more children 0.475 0.025 782 1761 1.421 0.053 0.424 0.526 Want to delay next birth at least 2 years 0.174 0.016 782 1761 1.150 0.090 0.143 0.205 Ideal number of children 3.859 0.077 732 1636 1.314 0.020 3.706 4.012 258 • Appendix C Table C.6 Sampling errors for Sindh, Pakistan 2012-13 Value (R) Standard error (SE) Number of cases Design effect (DEFT) Relative error (SE/R) Confidence limits Variable Unweighted (N) Weighted (WN) R-2SE R+2SE WOMEN Urban residence 0.486 0.013 2941 3133 1.425 0.027 0.459 0.512 Literacy 0.418 0.018 2941 3133 1.980 0.043 0.382 0.454 No education 0.583 0.018 2941 3133 2.018 0.031 0.547 0.620 Secondary education or higher 0.243 0.016 2941 3133 2.059 0.067 0.211 0.276 Never married 0.376 0.027 4394 4742 1.091 0.071 0.322 0.429 Currently married 0.633 0.020 4394 4742 1.092 0.032 0.593 0.673 Married before age 20 0.539 0.010 3491 3703 1.354 0.019 0.518 0.560 Married to first cousin 0.527 0.016 2941 3133 1.686 0.029 0.496 0.558 Currently pregnant 0.075 0.005 4394 4742 1.076 0.062 0.066 0.084 Children ever born 2.387 0.094 4394 4742 1.119 0.039 2.200 2.575 Children surviving 2.133 0.084 4394 4742 1.122 0.039 1.966 2.300 Children ever born to women age 40-49 5.800 0.171 776 796 1.562 0.029 5.458 6.141 Know any contraceptive method 0.995 0.002 2809 3002 1.241 0.002 0.991 0.998 Know a modern method 0.995 0.002 2809 3002 1.241 0.002 0.991 0.998 Ever used a contraceptive method 0.441 0.013 2809 3002 1.409 0.030 0.414 0.467 Currently using any method 0.295 0.012 2809 3002 1.448 0.042 0.270 0.320 Currently using a modern method 0.245 0.012 2809 3002 1.482 0.049 0.221 0.269 Currently using a traditional method 0.050 0.004 2809 3002 0.967 0.079 0.042 0.058 Currently using pill 0.018 0.003 2809 3002 1.098 0.153 0.013 0.024 Currently using IUD 0.012 0.003 2809 3002 1.251 0.218 0.007 0.017 Currently using condoms 0.080 0.005 2809 3002 1.060 0.068 0.069 0.090 Currently using injectables 0.033 0.004 2809 3002 1.083 0.111 0.026 0.040 Currently using female sterilization 0.097 0.009 2809 3002 1.572 0.091 0.079 0.114 Currently using rhythm 0.001 0.001 2809 3002 0.904 0.517 0.000 0.002 Currently using withdrawal 0.048 0.004 2809 3002 0.977 0.082 0.040 0.056 Used public sector source 0.411 0.027 729 726 1.486 0.066 0.357 0.465 Want no more children 0.468 0.012 2809 3002 1.244 0.025 0.445 0.492 Want to delay next birth at least 2 years 0.251 0.010 2809 3002 1.191 0.039 0.232 0.271 Ideal number of children 4.455 0.054 2891 3074 1.555 0.012 4.347 4.563 Mothers received antenatal care for last birth 0.782 0.017 1591 1714 1.658 0.022 0.747 0.816 Mothers protected against tetanus for last birth 0.535 0.026 1591 1714 2.123 0.049 0.482 0.588 Births with skilled attendant at delivery 0.605 0.024 2523 2740 1.992 0.040 0.557 0.653 Had diarrhea in the past 2 weeks 0.231 0.011 2328 2510 1.235 0.047 0.209 0.253 Treated with ORS 0.452 0.032 532 579 1.406 0.071 0.388 0.517 Sought medical treatment for diarrhea 0.730 0.019 532 579 0.963 0.026 0.692 0.769 Vaccination card seen 0.259 0.026 417 437 1.202 0.100 0.207 0.311 Received BCG vaccination 0.785 0.028 417 437 1.370 0.036 0.729 0.840 Received DPT vaccination (3 doses) 0.386 0.025 417 437 1.051 0.065 0.335 0.436 Received polio vaccination (3 doses) 0.775 0.035 417 437 1.690 0.045 0.706 0.845 Received measles vaccination 0.446 0.025 417 437 1.029 0.057 0.395 0.496 Received all vaccinations 0.291 0.023 417 437 1.011 0.078 0.245 0.336 Height-for-age (-2 SD) 0.567 0.026 723 799 1.221 0.045 0.515 0.618 Weight-for-height (-2 SD) 0.136 0.015 723 799 1.191 0.110 0.106 0.166 Weight-for-age (-2 SD) 0.423 0.023 723 799 1.150 0.055 0.377 0.470 Body mass index (BMI) <18.5 0.196 0.018 887 948 1.387 0.094 0.159 0.233 Accepting attitudes toward people with HIV 0.152 0.012 1437 1365 1.289 0.080 0.127 0.176 Ever experienced any physical violence since age 15 0.250 0.022 841 835 1.466 0.088 0.206 0.294 Ever experienced any physical violence by husband 0.199 0.018 841 835 1.329 0.092 0.163 0.236 Ever experienced any physical violence in the last 12 months 0.155 0.019 841 835 1.495 0.120 0.118 0.193 Total fertility rate (3 years) 3.908 0.151 12334 13292 1.162 0.039 3.606 4.210 Neonatal mortality rate (last 0-9 years) 53.874 4.150 4872 5286 1.086 0.077 45.574 62.174 Post-neonatal mortality rate (last 0-9 years) 20.123 2.420 4861 5276 1.116 0.120 15.282 24.963 Infant mortality rate (last 0-9 years) 73.997 4.709 4878 5292 1.053 0.064 64.578 83.415 Child mortality rate (last 0-9 years) 20.305 2.780 4899 5320 1.146 0.137 14.744 25.866 Under-five mortality rate (last 0-9 years) 92.799 5.580 4888 5301 1.082 0.060 81.638 103.959 MEN Urban residence 0.472 0.020 758 796 1.101 0.042 0.432 0.512 Literacy 0.615 0.028 758 796 1.580 0.046 0.559 0.671 No education 0.300 0.026 758 796 1.575 0.088 0.247 0.352 Secondary education or higher 0.399 0.025 758 796 1.420 0.063 0.348 0.449 Never married 0.496 0.046 1590 1581 0.866 0.093 0.404 0.588 Currently married 0.493 0.045 1590 1581 0.867 0.091 0.403 0.583 Know any contraceptive method 0.947 0.013 739 779 1.564 0.014 0.922 0.973 Know a modern method 0.929 0.016 739 779 1.677 0.017 0.897 0.961 Want no more children 0.353 0.017 739 779 0.962 0.048 0.319 0.387 Want to delay next birth at least 2 years 0.264 0.020 739 779 1.215 0.075 0.225 0.303 Ideal number of children 4.491 0.077 742 785 1.148 0.017 4.336 4.646 Appendix C • 259 Table C.7 Sampling errors for Khyber Pakhtunkhwa, Pakistan 2012-13 Value (R) Standard error (SE) Number of cases Design effect (DEFT) Relative error (SE/R) Confidence limits Variable Unweighted (N) Weighted (WN) R-2SE R+2SE WOMEN Urban residence 0.168 0.011 2695 1908 1.475 0.063 0.147 0.189 Literacy 0.268 0.019 2695 1908 2.210 0.071 0.230 0.305 No education 0.719 0.020 2695 1908 2.323 0.028 0.679 0.759 Secondary education or higher 0.120 0.012 2695 1908 1.988 0.104 0.095 0.145 Never married 0.419 0.030 4069 2886 1.205 0.071 0.359 0.479 Currently married 0.643 0.022 4069 2886 1.162 0.034 0.599 0.687 Married before age 20 0.537 0.010 3146 2226 1.344 0.019 0.516 0.558 Married to first cousin 0.450 0.015 2695 1908 1.525 0.032 0.421 0.479 Currently pregnant 0.079 0.005 4069 2886 1.133 0.067 0.069 0.090 Children ever born 2.478 0.101 4069 2886 1.165 0.041 2.276 2.681 Children surviving 2.278 0.094 4069 2886 1.179 0.041 2.090 2.467 Children ever born to women age 40-49 5.805 0.104 725 501 1.148 0.018 5.596 6.014 Know any contraceptive method 0.991 0.003 2615 1855 1.536 0.003 0.985 0.996 Know a modern method 0.982 0.007 2615 1855 2.651 0.007 0.969 0.996 Ever used a contraceptive method 0.530 0.027 2615 1855 2.782 0.051 0.476 0.585 Currently using any method 0.281 0.021 2615 1855 2.337 0.073 0.240 0.322 Currently using a modern method 0.195 0.019 2615 1855 2.434 0.097 0.157 0.233 Currently using a traditional method 0.086 0.007 2615 1855 1.308 0.084 0.071 0.100 Currently using pill 0.027 0.005 2615 1855 1.568 0.184 0.017 0.037 Currently using IUD 0.015 0.003 2615 1855 1.161 0.182 0.010 0.021 Currently using condoms 0.070 0.008 2615 1855 1.564 0.111 0.055 0.086 Currently using injectables 0.052 0.007 2615 1855 1.552 0.130 0.038 0.065 Currently using female sterilization 0.024 0.006 2615 1855 2.167 0.272 0.011 0.037 Currently using rhythm 0.003 0.001 2615 1855 1.072 0.404 0.001 0.005 Currently using withdrawal 0.081 0.007 2615 1855 1.328 0.087 0.067 0.096 Used public sector source 0.397 0.035 562 351 1.682 0.088 0.327 0.466 Want no more children 0.534 0.013 2615 1855 1.298 0.024 0.509 0.560 Want to delay next birth at least 2 years 0.188 0.008 2615 1855 1.005 0.041 0.173 0.203 Ideal number of children 4.117 0.060 2483 1765 2.057 0.015 3.997 4.236 Mothers received antenatal care for last birth 0.605 0.036 1532 1117 2.913 0.059 0.534 0.677 Mothers protected against tetanus for last birth 0.556 0.035 1532 1117 2.781 0.063 0.486 0.625 Births with skilled attendant at delivery 0.483 0.034 2270 1654 2.647 0.070 0.416 0.551 Had diarrhea in the past 2 weeks 0.279 0.018 2154 1560 1.733 0.066 0.242 0.316 Treated with ORS 0.355 0.036 570 435 1.682 0.101 0.284 0.426 Sought medical treatment for diarrhea 0.230 0.037 570 435 1.899 0.159 0.157 0.303 Vaccination card seen 0.397 0.032 422 309 1.345 0.080 0.334 0.461 Received BCG vaccination 0.797 0.035 422 309 1.827 0.044 0.726 0.867 Received DPT vaccination (3 doses) 0.696 0.043 422 309 1.960 0.062 0.609 0.783 Received polio vaccination (3 doses) 0.757 0.033 422 309 1.613 0.044 0.691 0.823 Received measles vaccination 0.578 0.036 422 309 1.520 0.062 0.506 0.650 Received all vaccinations 0.527 0.037 422 309 1.534 0.070 0.454 0.600 Height-for-age (-2 SD) 0.419 0.023 550 392 1.016 0.054 0.374 0.464 Weight-for-height (-2 SD) 0.120 0.019 550 392 1.294 0.155 0.083 0.158 Weight-for-age (-2 SD) 0.261 0.030 550 392 1.495 0.114 0.201 0.321 Body mass index (BMI) <18.5 0.063 0.012 798 572 1.385 0.188 0.039 0.087 Accepting attitudes toward people with HIV 0.176 0.021 990 560 1.718 0.118 0.135 0.218 Ever experienced any physical violence since age 15 0.566 0.026 684 512 1.386 0.047 0.513 0.618 Ever experienced any physical violence by husband 0.509 0.027 684 512 1.397 0.053 0.455 0.562 Ever experienced any physical violence in the last 12 months 0.311 0.026 684 512 1.459 0.083 0.260 0.363 Total fertility rate (3 years) 3.919 0.125 11335 8047 1.297 0.032 3.669 4.168 Neonatal mortality rate (last 0-9 years) 41.134 5.681 4683 3430 1.503 0.138 29.773 52.496 Post-neonatal mortality rate (last 0-9 years) 16.728 1.963 4690 3436 1.020 0.117 12.803 20.654 Infant mortality rate (last 0-9 years) 57.863 6.100 4687 3433 1.464 0.105 45.662 70.063 Child mortality rate (last 0-9 years) 12.707 2.953 4718 3462 1.512 0.232 6.800 18.614 Under-five mortality rate (last 0-9 years) 69.835 6.448 4700 3444 1.456 0.092 56.938 82.732 MEN Urban residence 0.192 0.020 497 347 1.122 0.103 0.152 0.232 Literacy 0.674 0.032 497 347 1.497 0.047 0.611 0.737 No education 0.300 0.035 497 347 1.708 0.117 0.230 0.371 Secondary education or higher 0.410 0.030 497 347 1.378 0.074 0.349 0.471 Never married 0.540 0.111 985 755 1.179 0.206 0.318 0.762 Currently married 0.457 0.110 985 755 1.178 0.241 0.236 0.677 Know any contraceptive method 0.962 0.011 492 345 1.319 0.012 0.940 0.985 Know a modern method 0.949 0.017 492 345 1.763 0.018 0.914 0.984 Want no more children 0.351 0.023 492 345 1.083 0.066 0.305 0.398 Want to delay next birth at least 2 years 0.256 0.031 492 345 1.554 0.120 0.194 0.317 Ideal number of children 4.872 0.140 452 308 1.522 0.029 4.592 5.152 260 • Appendix C Table C.8 Sampling errors for Balochistan, Pakistan 2012-13 Value (R) Standard error (SE) Number of cases Design effect (DEFT) Relative error (SE/R) Confidence limits Variable Unweighted (N) Weighted (WN) R-2SE R+2SE WOMEN Urban residence 0.201 0.021 1953 568 2.318 0.105 0.159 0.243 Literacy 0.157 0.018 1953 568 2.129 0.112 0.122 0.192 No education 0.846 0.018 1953 568 2.175 0.021 0.810 0.881 Secondary education or higher 0.067 0.010 1953 568 1.833 0.155 0.046 0.088 Never married 0.327 0.028 2869 858 1.315 0.086 0.271 0.383 Currently married 0.644 0.045 2869 858 1.271 0.070 0.554 0.734 Married before age 20 0.580 0.020 2267 670 2.126 0.034 0.541 0.619 Married to first cousin 0.511 0.026 1953 568 2.305 0.051 0.459 0.563 Currently pregnant 0.100 0.011 2869 858 1.454 0.112 0.078 0.123 Children ever born 2.723 0.225 2869 858 1.385 0.083 2.272 3.174 Children surviving 2.407 0.192 2869 858 1.339 0.080 2.023 2.792 Children ever born to women age 40-49 6.591 0.252 446 114 1.670 0.038 6.087 7.096 Know any contraceptive method 0.860 0.023 1896 553 2.899 0.027 0.814 0.906 Know a modern method 0.856 0.023 1896 553 2.865 0.027 0.810 0.902 Ever used a contraceptive method 0.320 0.028 1896 553 2.654 0.089 0.263 0.377 Currently using any method 0.195 0.020 1896 553 2.247 0.105 0.154 0.236 Currently using a modern method 0.163 0.018 1896 553 2.173 0.113 0.127 0.200 Currently using a traditional method 0.031 0.007 1896 553 1.879 0.241 0.016 0.046 Currently using pill 0.024 0.005 1896 553 1.502 0.220 0.013 0.035 Currently using IUD 0.021 0.008 1896 553 2.354 0.368 0.006 0.037 Currently using condoms 0.037 0.006 1896 553 1.458 0.170 0.025 0.050 Currently using injectables 0.017 0.004 1896 553 1.233 0.213 0.010 0.025 Currently using female sterilization 0.040 0.007 1896 553 1.553 0.174 0.026 0.054 Currently using rhythm 0.001 0.000 1896 553 0.644 0.589 0.000 0.001 Currently using withdrawal 0.030 0.008 1896 553 1.948 0.256 0.014 0.045 Used public sector source 0.463 0.048 335 79 1.759 0.104 0.366 0.559 Want no more children 0.289 0.020 1896 553 1.878 0.068 0.250 0.328 Want to delay next birth at least 2 years 0.163 0.013 1896 553 1.539 0.080 0.137 0.189 Ideal number of children 6.144 0.141 1884 549 2.399 0.023 5.863 6.425 Mothers received antenatal care for last birth 0.306 0.030 1149 348 2.277 0.100 0.245 0.367 Mothers protected against tetanus for last birth 0.232 0.044 1149 348 3.571 0.189 0.144 0.320 Births with skilled attendant at delivery 0.178 0.025 1902 590 2.371 0.143 0.127 0.229 Had diarrhea in the past 2 weeks 0.121 0.013 1738 536 1.612 0.110 0.094 0.147 Treated with ORS 0.415 0.047 209 65 1.259 0.113 0.322 0.509 Sought medical treatment for diarrhea 0.434 0.057 209 65 1.538 0.131 0.320 0.548 Vaccination card seen 0.080 0.023 274 88 1.468 0.288 0.034 0.127 Received BCG vaccination 0.489 0.073 274 88 2.512 0.149 0.343 0.635 Received DPT vaccination (3 doses) 0.271 0.066 274 88 2.545 0.242 0.140 0.402 Received polio vaccination (3 doses) 0.606 0.042 274 88 1.463 0.069 0.523 0.689 Received measles vaccination 0.373 0.074 274 88 2.654 0.200 0.224 0.522 Received all vaccinations 0.164 0.041 274 88 1.930 0.253 0.081 0.246 Body mass index (BMI) <18.5 0.090 0.017 513 150 1.321 0.185 0.057 0.124 Accepting attitudes toward people with HIV 0.095 0.031 562 124 2.511 0.328 0.033 0.158 Ever experienced any physical violence since age 15 0.428 0.051 480 160 2.254 0.120 0.325 0.530 Ever experienced any physical violence by husband 0.397 0.047 480 160 2.109 0.119 0.303 0.492 Ever experienced any physical violence in the last 12 months 0.313 0.039 480 160 1.822 0.124 0.236 0.390 Total fertility rate (3 years) 4.224 0.319 8042 2363 1.872 0.076 3.585 4.863 Neonatal mortality rate (last 0-9 years) 63.145 6.610 4152 1259 1.452 0.105 49.925 76.365 Post-neonatal mortality rate (last 0-9 years) 33.924 4.738 4146 1255 1.386 0.140 24.448 43.399 Infant mortality rate (last 0-9 years) 97.069 9.915 4154 1259 1.674 0.102 77.239 116.898 Child mortality rate (last 0-9 years) 14.887 3.606 4284 1294 1.861 0.242 7.674 22.099 Under-five mortality rate (last 0-9 years) 110.511 10.468 4164 1261 1.667 0.095 89.575 131.446 MEN Urban residence 0.211 0.022 551 151 1.237 0.102 0.168 0.254 Literacy 0.528 0.048 551 151 2.244 0.091 0.432 0.623 No education 0.510 0.050 551 151 2.325 0.098 0.411 0.610 Secondary education or higher 0.346 0.046 551 151 2.255 0.133 0.254 0.437 Never married 0.347 0.035 806 231 0.925 0.100 0.277 0.416 Currently married 0.652 0.035 806 231 0.924 0.053 0.583 0.722 Know any contraceptive method 0.835 0.043 550 150 2.698 0.051 0.749 0.921 Know a modern method 0.832 0.043 550 150 2.678 0.052 0.746 0.918 Want no more children 0.203 0.019 550 150 1.083 0.092 0.166 0.240 Want to delay next birth at least 2 years 0.191 0.030 550 150 1.794 0.158 0.130 0.251 Ideal number of children 7.120 0.309 536 147 1.917 0.043 6.502 7.737 Appendix C • 261 Table C.9 Sampling errors for ICT Islamabad, Pakistan 2012-13 Value (R) Standard error (SE) Number of cases Design effect (DEFT) Relative error (SE/R) Confidence limits Variable Unweighted (N) Weighted (WN) R-2SE R+2SE WOMEN Urban residence 0.612 0.016 953 64 1.003 0.026 0.580 0.644 Literacy 0.814 0.020 953 64 1.565 0.024 0.774 0.853 No education 0.163 0.020 953 64 1.675 0.123 0.123 0.203 Secondary education or higher 0.595 0.027 953 64 1.688 0.045 0.541 0.648 Never married 0.155 0.011 1469 96 1.032 0.073 0.133 0.178 Currently married 0.641 0.030 1469 96 1.011 0.046 0.582 0.700 Married before age 20 0.285 0.014 1245 83 1.125 0.049 0.257 0.313 Married to first cousin 0.395 0.023 953 64 1.460 0.059 0.349 0.441 Currently pregnant 0.053 0.006 1469 96 1.086 0.121 0.040 0.066 Children ever born 2.039 0.110 1469 96 0.999 0.054 1.818 2.259 Children surviving 1.922 0.101 1469 96 0.977 0.053 1.720 2.124 Children ever born to women age 40-49 4.187 0.151 282 19 1.349 0.036 3.886 4.488 Know any contraceptive method 0.995 0.002 915 62 0.964 0.002 0.990 0.999 Know a modern method 0.995 0.002 915 62 0.964 0.002 0.990 0.999 Ever used a contraceptive method 0.776 0.017 915 62 1.263 0.022 0.741 0.810 Currently using any method 0.594 0.020 915 62 1.244 0.034 0.554 0.635 Currently using a modern method 0.441 0.016 915 62 0.999 0.037 0.408 0.473 Currently using a traditional method 0.154 0.012 915 62 1.044 0.081 0.129 0.179 Currently using pill 0.018 0.005 915 62 1.183 0.289 0.008 0.028 Currently using IUD 0.046 0.008 915 62 1.110 0.168 0.030 0.061 Currently using condoms 0.249 0.012 915 62 0.871 0.050 0.224 0.274 Currently using injectables 0.016 0.005 915 62 1.250 0.328 0.005 0.026 Currently using female sterilization 0.100 0.009 915 62 0.878 0.087 0.083 0.118 Currently using rhythm 0.024 0.006 915 62 1.229 0.258 0.012 0.037 Currently using withdrawal 0.129 0.012 915 62 1.087 0.093 0.105 0.154 Used public sector source 0.328 0.033 389 27 1.392 0.101 0.262 0.395 Want no more children 0.603 0.020 915 62 1.247 0.033 0.563 0.644 Want to delay next birth at least 2 years 0.181 0.014 915 62 1.075 0.076 0.154 0.209 Ideal number of children 3.150 0.057 915 62 1.484 0.018 3.035 3.265 Mothers received antenatal care for last birth 0.943 0.013 472 31 1.248 0.014 0.916 0.970 Mothers protected against tetanus for last birth 0.858 0.019 472 31 1.201 0.023 0.819 0.897 Births with skilled attendant at delivery 0.881 0.022 709 47 1.386 0.025 0.838 0.924 Had diarrhea in the past 2 weeks 0.205 0.019 686 45 1.190 0.094 0.166 0.243 Treated with ORS 0.539 0.046 145 9 1.046 0.086 0.446 0.632 Sought medical treatment for diarrhea 0.665 0.040 145 9 0.987 0.061 0.584 0.746 Vaccination card seen 0.526 0.049 142 9 1.137 0.092 0.429 0.623 Received BCG vaccination 0.965 0.015 142 9 0.987 0.016 0.934 0.995 Received DPT vaccination (3 doses) 0.912 0.021 142 9 0.881 0.023 0.870 0.954 Received polio vaccination (3 doses) 0.856 0.034 142 9 1.159 0.040 0.787 0.925 Received measles vaccination 0.852 0.031 142 9 1.033 0.036 0.790 0.914 Received all vaccinations 0.739 0.043 142 9 1.144 0.058 0.654 0.824 Height-for-age (-2 SD) 0.222 0.028 216 13 0.938 0.127 0.166 0.279 Weight-for-height (-2 SD) 0.131 0.027 216 13 1.194 0.205 0.077 0.185 Weight-for-age (-2 SD) 0.144 0.029 216 13 1.217 0.204 0.085 0.203 Body mass index (BMI) <18.5 0.055 0.016 254 17 1.124 0.292 0.023 0.088 Accepting attitudes toward people with HIV 0.185 0.019 778 53 1.370 0.103 0.147 0.223 Ever experienced any physical violence since age 15 0.318 0.044 257 15 1.499 0.138 0.231 0.405 Ever experienced any physical violence by husband 0.242 0.034 257 15 1.259 0.139 0.175 0.310 Ever experienced any physical violence in the last 12 months 0.213 0.034 257 15 1.337 0.161 0.145 0.282 Total fertility rate (3 years) 2.984 0.137 4344 286 0.866 0.046 2.710 3.257 Neonatal mortality rate (last 0-9 years) 26.070 4.451 1376 91 0.943 0.171 17.168 34.972 Post-neonatal mortality rate (last 0-9 years) 9.064 3.192 1382 91 1.293 0.352 2.679 15.448 Infant mortality rate (last 0-9 years) 35.134 5.693 1376 91 1.033 0.162 23.747 46.520 Child mortality rate (last 0-9 years) 8.575 2.760 1372 90 0.993 0.322 3.056 14.094 Under-five mortality rate (last 0-9 years) 43.407 5.625 1377 91 0.926 0.130 32.158 54.657 MEN Urban residence 0.647 0.033 282 18 1.149 0.051 0.581 0.712 Literacy 0.945 0.013 282 18 0.989 0.014 0.918 0.972 No education 0.064 0.018 282 18 1.217 0.277 0.029 0.100 Secondary education or higher 0.717 0.037 282 18 1.384 0.052 0.643 0.792 Never married 0.345 0.079 427 27 1.080 0.228 0.187 0.502 Currently married 0.646 0.078 427 27 1.078 0.120 0.491 0.802 Know any contraceptive method 0.931 0.025 276 18 1.641 0.027 0.880 0.981 Know a modern method 0.924 0.025 276 18 1.567 0.027 0.874 0.974 Want no more children 0.477 0.040 276 18 1.331 0.084 0.397 0.557 Want to delay next birth at least 2 years 0.254 0.037 276 18 1.408 0.146 0.180 0.329 Ideal number of children 2.484 0.211 273 17 1.529 0.085 2.062 2.906 262 • Appendix C Table C.10 Sampling errors for Gilgit Baltistan, Pakistan 2012-13 Value (R) Standard error (SE) Number of cases Design effect (DEFT) Relative error (SE/R) Confidence limits Variable Unweighted (N) Weighted (WN) R-2SE R+2SE WOMEN Urban residence 0.157 0.008 1216 94 0.804 0.053 0.140 0.174 Literacy 0.362 0.042 1216 94 3.007 0.115 0.279 0.445 No education 0.675 0.041 1216 94 3.071 0.061 0.593 0.758 Secondary education or higher 0.168 0.030 1216 94 2.770 0.177 0.109 0.228 Never married 0.338 0.044 2337 152 1.358 0.129 0.250 0.425 Currently married 0.599 0.046 2337 152 0.599 0.077 0.507 0.692 Married before age 20 0.586 0.021 1449 112 1.731 0.036 0.544 0.628 Married to first cousin 0.403 0.041 1216 94 2.937 0.103 0.320 0.486 Currently pregnant 0.079 0.012 2337 152 1.029 0.153 0.055 0.103 Children ever born 2.648 0.220 2337 152 0.631 0.083 2.208 3.087 Children surviving 2.342 0.198 2337 152 0.644 0.085 1.945 2.738 Children ever born to women age 40-49 6.830 0.233 324 26 1.554 0.034 6.363 7.296 Know any contraceptive method 0.945 0.032 1180 91 4.813 0.034 0.880 1.010 Know a modern method 0.945 0.032 1180 91 4.801 0.034 0.880 1.009 Ever used a contraceptive method 0.508 0.057 1180 91 3.870 0.112 0.395 0.621 Currently using any method 0.336 0.038 1180 91 2.735 0.112 0.261 0.412 Currently using a modern method 0.282 0.036 1180 91 2.735 0.127 0.210 0.354 Currently using a traditional method 0.054 0.015 1180 91 2.245 0.273 0.025 0.084 Currently using pill 0.037 0.006 1180 91 1.158 0.173 0.024 0.049 Currently using IUD 0.084 0.015 1180 91 1.828 0.176 0.055 0.114 Currently using condoms 0.030 0.010 1180 91 2.086 0.347 0.009 0.050 Currently using injectables 0.066 0.016 1180 91 2.220 0.244 0.034 0.098 Currently using female sterilization 0.046 0.014 1180 91 2.277 0.304 0.018 0.073 Currently using rhythm 0.005 0.002 1180 91 1.023 0.418 0.001 0.009 Currently using withdrawal 0.049 0.014 1180 91 2.237 0.288 0.021 0.077 Used public sector source 0.515 0.038 357 25 1.445 0.075 0.438 0.591 Want no more children 0.508 0.027 1180 91 1.833 0.053 0.455 0.562 Want to delay next birth at least 2 years 0.271 0.021 1180 91 1.621 0.077 0.229 0.313 Ideal number of children 4.821 0.222 1195 93 4.219 0.046 4.376 5.265 Mothers received antenatal care for last birth 0.640 0.070 709 56 3.900 0.110 0.499 0.780 Mothers protected against tetanus for last birth 0.518 0.066 709 56 3.522 0.127 0.386 0.650 Births with skilled attendant at delivery 0.437 0.072 1093 87 3.803 0.166 0.292 0.582 Had diarrhea in the past 2 weeks 0.167 0.024 1016 81 1.903 0.143 0.119 0.215 Treated with ORS 0.725 0.043 183 14 1.159 0.059 0.640 0.810 Sought medical treatment for diarrhea 0.695 0.056 183 14 1.474 0.080 0.583 0.806 Vaccination card seen 0.292 0.060 191 16 1.884 0.205 0.172 0.412 Received BCG vaccination 0.786 0.056 191 16 1.934 0.071 0.674 0.897 Received DPT vaccination (3 doses) 0.553 0.098 191 16 2.817 0.178 0.357 0.750 Received polio vaccination (3 doses) 0.752 0.070 191 16 2.300 0.093 0.612 0.891 Received measles vaccination 0.510 0.096 191 16 2.729 0.188 0.319 0.701 Received all vaccinations 0.470 0.090 191 16 2.570 0.191 0.290 0.650 Height-for-age (-2 SD) 0.356 0.046 307 25 1.596 0.130 0.264 0.449 Weight-for-height (-2 SD) 0.081 0.023 307 25 1.508 0.281 0.036 0.127 Weight-for-age (-2 SD) 0.126 0.033 307 25 1.741 0.260 0.060 0.191 Body mass index (BMI) <18.5 0.054 0.020 370 29 1.694 0.368 0.014 0.094 Accepting attitudes toward people with HIV 0.157 0.029 243 11 1.232 0.184 0.099 0.215 Ever experienced any physical violence since age 15 0.121 0.032 333 25 1.761 0.261 0.058 0.184 Ever experienced any physical violence by husband 0.112 0.032 333 25 1.814 0.281 0.049 0.175 Ever experienced any physical violence in the last 12 months 0.095 0.031 333 25 1.925 0.328 0.032 0.157 Total fertility rate (3 years) 3.829 0.255 5573 414 1.346 0.067 3.319 4.338 Neonatal mortality rate (last 0-9 years) 38.860 6.046 2356 190 1.385 0.156 26.769 50.951 Post-neonatal mortality rate (last 0-9 years) 32.491 7.008 2367 190 1.806 0.216 18.474 46.508 Infant mortality rate (last 0-9 years) 71.351 11.481 2364 191 1.879 0.161 48.390 94.312 Child mortality rate (last 0-9 years) 19.153 3.828 2382 192 1.211 0.200 11.496 26.810 Under-five mortality rate (last 0-9 years) 89.137 13.014 2369 191 1.908 0.146 63.110 115.165 MEN Urban residence 0.178 0.019 246 18 0.768 0.105 0.140 0.215 Literacy 0.714 0.059 246 18 2.040 0.083 0.596 0.833 No education 0.230 0.057 246 18 2.088 0.246 0.117 0.343 Secondary education or higher 0.392 0.059 246 18 1.887 0.151 0.274 0.510 Never married 0.413 0.064 381 31 1.169 0.155 0.285 0.540 Currently married 0.587 0.064 381 31 1.169 0.109 0.460 0.715 Know any contraceptive method 0.985 0.009 246 18 1.231 0.010 0.966 1.004 Know a modern method 0.985 0.009 246 18 1.231 0.010 0.966 1.004 Want no more children 0.506 0.047 246 18 1.468 0.093 0.412 0.600 Want to delay next birth at least 2 years 0.310 0.043 246 18 1.441 0.138 0.225 0.396 Ideal number of children 4.401 0.151 236 18 1.387 0.034 4.098 4.704 Appendix D • 263 DATA QUALITY TABLES Appendix D Table D.1 Household age distribution Single-year age distribution of the de facto household population by sex (weighted), Pakistan 2012-13 Women Men Women Men Age Number Percent Number Percent Age Number Percent Number Percent 0 1,167 2.7 1,197 2.7 36 451 1.0 401 0.9 1 1,035 2.4 1,118 2.5 37 370 0.8 280 0.6 2 1,204 2.8 1,171 2.6 38 581 1.3 453 1.0 3 1,296 3.0 1,236 2.8 39 255 0.6 234 0.5 4 1,124 2.6 1,283 2.9 40 764 1.8 887 2.0 5 1,126 2.6 1,307 3.0 41 230 0.5 170 0.4 6 1,073 2.5 1,193 2.7 42 440 1.0 463 1.0 7 1,201 2.8 1,360 3.1 43 251 0.6 231 0.5 8 1,244 2.9 1,327 3.0 44 211 0.5 228 0.5 9 922 2.1 1,016 2.3 45 538 1.2 727 1.6 10 1,168 2.7 1,357 3.1 46 255 0.6 252 0.6 11 730 1.7 845 1.9 47 302 0.7 265 0.6 12 1,203 2.8 1,391 3.1 48 315 0.7 332 0.8 13 894 2.1 969 2.2 49 286 0.7 231 0.5 14 982 2.3 1,137 2.6 50 190 0.4 398 0.9 15 968 2.2 1,090 2.5 51 178 0.4 114 0.3 16 1,049 2.4 1,016 2.3 52 395 0.9 283 0.6 17 879 2.0 896 2.0 53 277 0.6 150 0.3 18 1,288 3.0 1,254 2.8 54 199 0.5 157 0.4 19 753 1.7 708 1.6 55 653 1.5 502 1.1 20 1,308 3.0 1,115 2.5 56 251 0.6 206 0.5 21 666 1.5 552 1.2 57 140 0.3 152 0.3 22 1,054 2.4 1,009 2.3 58 204 0.5 167 0.4 23 776 1.8 583 1.3 59 68 0.2 67 0.2 24 739 1.7 716 1.6 60 655 1.5 693 1.6 25 1,057 2.4 1,030 2.3 61 62 0.1 69 0.2 26 741 1.7 690 1.6 62 146 0.3 224 0.5 27 642 1.5 528 1.2 63 60 0.1 63 0.1 28 795 1.8 751 1.7 64 45 0.1 68 0.2 29 425 1.0 331 0.7 65 415 1.0 506 1.1 30 999 2.3 1,016 2.3 66 52 0.1 88 0.2 31 318 0.7 276 0.6 67 60 0.1 80 0.2 32 696 1.6 608 1.4 68 85 0.2 82 0.2 33 384 0.9 382 0.9 69 25 0.1 43 0.1 34 400 0.9 324 0.7 70+ 985 2.3 1,