Pakistan - Demographic and Health Survey - 2008

Publication date: 2008

Pakistan Demographic and Health Survey 2006-07 Pakistan Demographic and Health Survey 2006-07 National Institute of Population Studies Islamabad, Pakistan Macro International Inc. Calverton, Maryland USA June 2008 NIPS This report summarizes the findings of the 2006-07 Pakistan Demographic and Health Survey (PDHS) carried out by the National Institute of Population Studies. The Government of Pakistan provided financial assistance in terms of in-kind contribution of government staff time, office space, and logistical support. Macro International provided financial and technical assistance for the survey through the MEASURE DHS programme, which is funded by the U.S. Agency for International Development (USAID) and is designed to assist developing countries to collect data on fertility, family planning, and maternal and child health. Additional support for the PDHS was received from the United Nations Population Fund (UNFPA)/Pakistan and from UNICEF/Pakistan. The opinions expressed in this report are those of the authors and do not necessarily reflect the views of the donor organisations. Additional information about the survey may be obtained from the National Institute of Population Studies (NIPS), Block 12-A, Capital Inn Building, G-8 Markaz, P.O. Box 2197, Islamabad, Pakistan (Telephone: 92-51-926-0102 or 926-0380; Fax: 92-51-926-0071; Internet:: www.nips.org.pk) Information about the DHS programme may be obtained from MEASURE DHS, Macro International Inc., 11785 Beltsville Drive, Suite 300, Calverton, MD 20705, U.S.A. (Telephone: 1-301-572-0200; Fax: 1-301-572-0999; E-mail: reports@macrointernational.com; Internet: measuredhs.com). Suggested citation: National Institute of Population Studies (NIPS) [Pakistan], and Macro International Inc. 2008. Pakistan Demographic and Health Survey 2006-07. Islamabad, Pakistan: National Institute of Population Studies and Macro International Inc. CONTENTS Page TABLES AND FIGURES . ix FOREWORD . xv ACKNOWLEDGMENTS . xvii SUMMARY OF FINDINGS . xix MAP OF PAKISTAN . xxvi CHAPTER 1 INTRODUCTION Shahid Munir and Khalid Mehmood 1.1 Geography, Climate, and History . 1 1.2 Economy and Population . 2 1.3 Organization and Implementation of the 2006-07 PDHS . 3 1.3.1 Objectives of the Survey . 3 1.3.2 Institutional Framework . 4 1.3.3 Sample Design . 4 1.3.4 Questionnaires . 5 1.3.5 Training of Field Staff . 7 1.3.6 Field Supervision and Monitoring. 7 1.3.7 Fieldwork and Data Processing . 8 1.3.8 Field Problems . 8 1.4 Response Rates . 9 CHAPTER 2 HOUSEHOLD POPULATION AND HOUSING CHARACTERISTICS Aysha Sheraz and Zafar Zahir 2.1 Household Population by Age and Sex . 11 2.2 Household Composition . 14 2.3 Education of the Household Population . 16 2.3.1 Educational Attainment of Household Population . 16 2.3.2 School Attendance Ratios . 18 2.4 Housing Characteristics . 21 2.5 Household Possessions . 24 2.6 Socioeconomic Status Index . 25 2.7 Availability of Services in Rural Areas . 26 2.8 Registration with the National Database and Registration Authority . 27 CHAPTER 3 CHARACTERISTICS OF RESPONDENTS Zahir Hussain and Zafar Iqbal Qamar 3.1 Characteristics of Survey Respondents . 29 3.2 Educational Attainment and Literacy . 30 3.3 Employment . 33 3.3.1 Employment Status . 33 Contents | iii 3.3.2 Occupation . 36 3.3.3 Type of Earnings . 37 3.3.4 Employment before and after Marriage . 37 3.4 Knowledge and Attitudes Concerning Tuberculosis . 39 CHAPTER 4 FERTILITY Syed Mubashir Ali and Ali Anwar Buriro 4.1 Current Fertility . 41 4.2 Fertility Trends . 44 4.3 Children Ever Born and Children Surviving . 46 4.4 Birth Intervals . 48 4.5 Age at First Birth . 49 4.6 Teenage Fertility . 51 CHAPTER 5 FAMILY PLANNING Iqbal Ahmad and Mumtaz Eskar 5.1 Knowledge of Contraceptive Methods . 53 5.2 Ever Use of Family Planning Methods . 55 5.3 Current Use of Contraceptive Methods . 56 5.4 Differentials in Contraceptive Use by Background Characteristics . 58 5.5 Use of Social Marketing Contraceptive Brands . 60 5.6 Timing of Sterilization . 61 5.7 Source of Contraception . 62 5.8 Cost of Contraceptive Methods . 63 5.9 Informed Choice . 64 5.10 Future Use of Contraception . 65 5.11 Reasons for Not Intending to Use . 65 5.12 Exposure to Family Planning Messages . 66 5.13 Contact of Nonusers with Family Planning Providers . 68 CHAPTER 6 OTHER DETERMINANTS OF FERTILITY Mehboob Sultan and Mubashir Baqai 6.1 Marital Status . 69 6.2 Polygyny . 70 6.3 Consanguinity . 70 6.4 Age at First Marriage . 72 6.5 Postpartum Amenorrhoea, Abstinence, and Insusceptibility . 73 CHAPTER 7 FERTILITY PREFERENCES Syed Mubashir Ali and Faateh ud din Ahmad 7.1 Desire for More Children . 77 7.2 Need for Family Planning . 81 7.3 Ideal Number of Children . 83 7.4 Wanted and Unwanted Fertility . 86 iv � Contents CHAPTER 8 INFANT AND CHILD MORTALITY Zulfiqar A. Bhutta, Anne Cross, Farrukh Raza, and Zafar Zahir 8.1 Data Quality . 89 8.2 Levels and Trends in Infant and Child Mortality . 90 8.3 Socioeconomic Differentials in Infant and Child Mortality . 91 8.4 Demographic Differentials in Infant and Child Mortality . 92 8.5 Perinatal Mortality . 93 8.6 High-risk Fertility Behaviour . 95 8.7 Causes of Death of Children Under Five . 96 8.7.1 Methodology . 96 8.7.2 Results . 97 8.8 Causes of Stillbirths . 100 8.9 Implications of the Findings . 100 CHAPTER 9 REPRODUCTIVE HEALTH Rabia Zafar and Anne Cross 9.1 Prenatal Care . 101 9.1.1 Number and Timing of Prenatal Visits . 103 9.1.2 Components of Prenatal Care . 104 9.1.3 Reasons for Not Receiving Prenatal Checkups . 106 9.1.4 Tetanus Toxoid Vaccinations . 107 9.1.5 Complications during Pregnancy . 108 9.2 Delivery Care . 111 9.2.1 Preparedness for Delivery . 111 9.2.2 Place of Delivery . 112 9.2.3 Reasons for Not Delivering in a Facility . 114 9.2.4 Use of Home Delivery Kits . 115 9.2.5 Assistance during Delivery . 116 9.3 Postnatal Care . 118 9.3.1 Timing of First Postnatal Checkups . 118 9.3.2 Complications during Delivery and the Postnatal Period . 120 9.3.3 Fistula . 121 CHAPTER 10 CHILD HEALTH Arshad Mahmood and Mehboob Sultan 10.1 Birth Weight . 123 10.2 Child Immunization . 124 10.2.1 Vaccination Coverage . 125 10.2.2 Differentials in Vaccination Coverage . 126 10.2.3 Trends in Vaccination Coverage . 128 10.3 Childhood Diseases . 129 10.3.1 Prevalence and Treatment of ARI . 129 10.3.2 Prevalence and Treatment of Fever . 131 10.3.3 Prevalence of Diarrhoea . 133 10.3.4 Treatment of Diarrhoea . 134 10.3.5 Feeding Practices during Diarrhoea. 136 Contents | v CHAPTER 11 NUTRITION Syed Mubashir Ali and Mehboob Sultan 11.1 Breastfeeding and Supplementation . 139 11.1.1 Initiation of Breastfeeding . 139 11.1.2 Breastfeeding Patterns. 141 11.1.3 Complementary Feeding . 144 11.2 Micronutrient Intake . 144 11.2.1 Micronutrient Intake among Children . 145 11.2.2 Micronutrient Intake among Women . 145 CHAPTER 12 MALARIA Mehboob Sultan and Syed Mubashir Ali 12.1 Household Ownership of Mosquito Nets . 147 12.2 Use of Mosquito Nets and Other Repellents . 148 12.3 Malaria Prevalence and Treatment during Pregnancy . 151 12.4 Malaria Case Management among Children . 151 CHAPTER 13 KNOWLEDGE OF HIV/AIDS AND OTHER SEXUALLY TRANSMITTED INFECTIONS Faateh ud din Ahmad and Adnan Ahmad Khan 13.1 Knowledge of AIDS . 155 13.2 Knowledge of Ways to Avoid Contracting HIV/AIDS . 157 13.3 Comprehensive Knowledge of HIV/AIDS Transmission . 159 13.4 Knowledge of Mother-to-Child Transmission . 160 13.5 Attitudes towards People Living with HIV/AIDS . 162 13.6 Knowledge of Sexually Transmitted Infections . 163 13.7 Safe Injection Practices. 164 CHAPTER 14 ADULT AND MATERNAL MORTALITY Farid Midhet and Sadiqua N.Jafarey, Dr. Azra Ahsan, Aysha Sheraz 14.1 Introduction . 167 14.2 Methods of Data Collection . 169 14.2.1 Development and Validation of the VA Questionnaire . 169 14.2.2 Implementation of VAs in Sample Households . 170 14.2.3 Review of VA Questionnaires and Assignment of Causes of Death . 171 14.3 Adult Mortality Rates . 172 14.4 Response to the Verbal Autopsy . 174 14.5 Causes of Death Among Women Age 12-49 . 175 14.6 Pregnancy-Related Mortality and Maternal Mortality . 177 14.7 Discussion . 180 REFERENCES . 183 APPENDIX A ADDITIONAL TABLES . 189 vi � Contents Contents | vii APPENDIX B SAMPLING IMPLEMENTATION . 185 APPENDIX C ESTIMATES OF SAMPLING ERRORS . 197 APPENDIX D DATA QUALITY TABLES . 209 APPENDIX E PERSONS INVOLVED IN THE 2006-07 PAKISTAN DEMOGRAPHIC AND HEALTH SURVEY . 215 APPENDIX F QUESTIONNAIRES . 221 TABLES AND FIGURES Page CHAPTER 1 INTRODUCTION Table 1.1 Results of the household and individual interviews . 9 CHAPTER 2 HOUSEHOLD POPULATION AND HOUSING CHARACTERISTICS Table 2.1 Household population by age, sex, and residence . 12 Table 2.2 Household population by age, sex, and province . 13 Table 2.3 Sex ratios by age . 13 Table 2.4 Trends in age distribution of household population . 14 Table 2.5 Household composition . 15 Table 2.6 Children's orphanhood. 16 Table 2.7.1 Educational attainment of the female household population . 17 Table 2.7.2 Educational attainment of the male household population . 18 Table 2.8 School attendance ratios . 19 Table 2.9 Household drinking water . 21 Table 2.10 Household sanitation facilities . 22 Table 2.11 Housing characteristics . 23 Table 2.12 Household durable goods . 25 Table 2.13 Wealth quintiles . 26 Table 2.14 Availability of services in rural areas . 27 Table 2.15 Registration with NADRA . 28 Figure 2.1 Population Pyramid . 12 Figure 2.2 Age-Specific Attendance Rates of the De-Facto Population Age 5 to 24 Years . 20 CHAPTER 3 CHARACTERISTICS OF RESPONDENTS Table 3.1 Background characteristics of respondents . 30 Table 3.2 Educational attainment . 31 Table 3.3 Literacy . 33 Table 3.4 Employment status . 34 Table 3.5 Occupation. 36 Table 3.6 Type of earnings . 37 Table 3.7 Employment before and after marriage . 38 Table 3.8 Knowledge and attitudes concerning tuberculosis . 39 Figure 3.1 Women’s Employment Status in the Past 12 Months . 35 Figure 3.2 Women's Current Employment by Residence and Education . 35 CHAPTER 4 FERTILITY Table 4.1 Current fertility . 42 Tables and Figures | ix Table 4.2 Fertility by background characteristics . 43 Table 4.3 Current marital fertility . 44 Table 4.4 Trends in fertility . 45 Table 4.5 Trends in fertility by background characteristics . 46 Table 4.6 Trends in age-specific fertility rates . 46 Table 4.7 Children ever born and living . 47 Table 4.8 Trends in children ever born . 48 Table 4.9 Birth intervals . 49 Table 4.10 Age at first birth . 50 Table 4.11 Median age at first birth . 50 Table 4.12 Teenage pregnancy and motherhood . 51 Figure 4.1 Total Fertility Rate by Background Characteristics . 44 Figure 4.2 Trends in Total Fertility Rates . 45 CHAPTER 5 FAMILY PLANNING Table 5.1 Knowledge of contraceptive methods . 53 Table 5.2 Knowledge of contraceptive methods by background characteristics . 54 Table 5.3 Trends in knowledge of contraceptive methods . 55 Table 5.4 Ever use of contraception . 56 Table 5.5 Current use of contraception by age . 56 Table 5.6 Current use of contraception by background characteristics . 59 Table 5.7 Use of social marketing brand pills and condoms . 61 Table 5.8 Timing of sterilization . 61 Table 5.9 Source of modern contraception methods . 62 Table 5.10 Cost of modern contraceptive methods . 63 Table 5.11 Informed choice . 64 Table 5.12 Future use of contraception . 65 Table 5.13 Reason for not intending to use contraception in the future . 66 Table 5.14 Exposure to family planning messages . 67 Table 5.15 Family planning messages . 67 Table 5.16 Contact of nonusers with family planning providers . 68 Figure 5.1 Trends in Contraceptive Use . 57 Figure 5.2 Trends in Current Use of Specific Methods among Married Women . 58 Figure 5.3 Differentials in Contraceptive Use .60 CHAPTER 6 OTHER DETERMINANTS OF FERTILITY Table 6.1 Current marital status . 69 Table 6.2 Cohabitation and polygyny . 70 Table 6.3 Marriage between relatives . 71 Table 6.4 Age at first marriage . 72 Table 6.5 Median age at first marriage . 73 Table 6.6 Postpartum amenorrhoea, abstinence, and insusceptibility . 74 Table 6.7 Median duration of postpartum amenorrhoea, abstinence, and insusceptibility . 75 Table 6.8 Menopause . 75 Table 6.9 Pregnancy terminations . 76 x | Tables and Figures CHAPTER 7 FERTILITY PREFERENCES Table 7.1 Fertility preferences by number of living children . 78 Table 7.2 Desire to limit childbearing . 80 Table 7.3 Desire to limit childbearing by sex of living children . 82 Table 7.4 Need and demand for family planning among currently married women . 83 Table 7.5 Ideal number of children . 85 Table 7.6 Mean ideal number of children . 86 Table 7.7 Couple's agreement on family size . 87 Table 7.8 Fertility planning status . 88 Table 7.9 Wanted fertility rates . 89 Figure 7.1 Fertility Preferences of Currently Married Women Age 15-49 . 78 Figure 7.2 Desire to Limit Childbearing among Currently Married Women, by Number of Living Children . 79 Figure 7.3 Percentage of Ever-Married Women with Four Children Who Want No More Children, by Background Characteristics . 81 Figure 7.4 Trends in Unmet Need for Family Planning . 84 Figure 7.5 Mean Ideal Number of Children, by Background Characteristics . 87 Figure 7.6 Total Wanted Fertility Rate and Total Fertility Rate . 89 CHAPTER 8 INFANT AND CHILD MORTALITY Table 8.1 Early childhood mortality rates . 90 Table 8.2 Trends in infant and under-five mortality rates . 91 Table 8.3 Early childhood mortality rates by socioeconomic characteristics . 91 Table 8.4 Early childhood mortality rates by demographic characteristics . 93 Table 8.5 Perinatal mortality . 94 Table 8.6 High-risk fertility behaviour . 96 Table 8.7 Child verbal autopsy response rates . 98 Table 8.8 Causes of child deaths by age . 98 Table 8.9 Causes of under five deaths by sex and residence . 99 Table 8.10 Causes of under five deaths by province . 100 Table 8.11 Causes of stillbirth . 100 Figure 8.1 Differentials in Under-Five Mortality . 92 CHAPTER 9 REPRODUCTIVE HEALTH Table 9.1 Prenatal care . 102 Table 9.2 Number of prenatal care visits and timing of first visit . 104 Table 9.3 Components of prenatal care . 105 Table 9.4 Reasons for not getting prenatal care . 106 Table 9.5 Tetanus toxoid injections . 107 Table 9.6 Pregnancy complications . 109 Table 9.7 Pregnancy complications and place of treatment . 110 Table 9.8 Pregnancy complications and reasons for no treatment . 111 Table 9.9 Preparations for delivery . 112 Table 9.10 Place of delivery . 113 Table 9.11 Reasons for not delivering in a facility . 115 Tables and Figures | xi Table 9.12 Use of home delivery kits . 116 Table 9.13 Assistance during delivery . 117 Table 9.14 Timing of first postnatal checkup . 119 Table 9.15 Type of provider of first postnatal checkup . 120 Table 9.16 Complications during delivery and postnatal period . 121 Table 9.17 Fistula . 122 Figure 9.1 Source of prenatal care . 103 Figure 9.2 Percentage of Births Protected against Tetanus, by Wealth Quintile . 107 Figure 9.3 Complications during Pregnancy for the Most Recent Birth . 110 Figure 9.4 Percentage of Births Delivered at a Health Facility, by Residence, Province, and Mother’s Education . 114 CHAPTER 10 CHILD HEALTH Table 10.1 Child's weight and size at birth . 124 Table 10.2 Vaccinations by source of information . 125 Table 10.3 Vaccinations by background characteristics . 127 Table 10.4 Trends in vaccination coverage . 128 Table 10.5 Prevalence and treatment of symptoms of ARI . 130 Table 10.6 Prevalence and treatment of fever . 132 Table 10.7 Prevalence of diarrhoea . 134 Table 10.8 Diarrhoea treatment . 135 Table 10.9 Feeding practices during diarrhoea . 137 Figure 10.1 Percentage of Children 12-23 Months Who Received Specific Vaccines Any Time Before Survey . 126 Figure 10.2 Percentage of Children Age 12-23 Months Who Are Fully Immunized, by Background Characteristics . 128 Figure 10.3 Prevalence of Acute Respiratory Infection (ARI) and Fever in the Two Weeks Prior to Survey by Age of Child . 131 Figure 10.4 Percentage of Children with Acute Respiratory Infection and Fever Taken to Health Facility . 131 Figure 10.5 Children under Five with Fever . 133 CHAPTER 11 NUTRITION Table 11.1 Initial breastfeeding . 140 Table 11.2 Breastfeeding status by age . 142 Table 11.3 Median duration and frequency of breastfeeding . 143 Table 11.4 Foods and liquids consumed by children . 144 Table 11.5 Micronutrient intake among children . 145 Table 11.6 Micronutrient intake among mothers . 146 Figure 11.1 Among Last Children Born in the Five Years Preceding the Survey Who Ever Received a Prelacteal Liquid, the Percentage Who Received Various Types of Liquids . 141 Figure 11.2 Infant Feeding Practices by Age . 142 xii | Tables and Figures CHAPTER 12 MALARIA Table 12.1 Ownership of mosquito nets . 148 Table 12.2 Use of mosquito nets by children . 149 Table 12.3 Use of mosquito nets by women . 150 Table 12.4 Other anti-mosquito actions . 150 Table 12.5 Prevalence of malaria during pregnancy . 151 Table 12.6 Prevalence and prompt treatment of fever . 152 Table 12.7 Type and timing of antimalarial drugs . 153 CHAPTER 13 KNOWLEDGE OF HIV/AIDS AND OTHER SEXUALLY TRANSMITTED INFECTIONS Table 13.1 Knowledge of AIDS . 156 Table 13.2 Knowledge of HIV prevention methods . 158 Table 13.3 Comprehensive knowledge about AIDS . 160 Table 13.4 Knowledge of prevention of mother-to-child transmission of HIV . 161 Table 13.5 Accepting attitudes towards those living with HIV/AIDS . 162 Table 13.6 Knowledge of sexually transmitted infections (STIs) and STI symptoms . 163 Table 13.7 Prevalence of medical injections . 164 Figure 13.1 Percentage of Ever-Married Women Who Have Heard of AIDS, by Background Characteristics . 157 Figure 13.2 Percentage of Ever-Married Women Who Know of Specific Ways to Prevent HIV/AIDS . 159 Figure 13.3 Source of Last Medical Injection . 165 Figure 13.4 Percentage of Women Whose Last Injection Was Given with a Syringe and Needle Taken from a New, Unopened Package, by Type of Facility Where Last Injection Was Received . 166 CHAPTER 14 ADULT AND MATERNAL MORTALITY Table 14.1 Previous sources of data on the maternal mortality ratio . 168 Table 14.2 Adult mortality . 172 Table 14.3 Adult women verbal autopsy response rates . 174 Table 14.4 Respondents for the adult women verbal autopsies . 175 Table 14.5 Causes of adult female deaths by age group . 175 Table 14.6 Causes of adult female deaths by residence . 176 Table 14.7 Causes of adult female deaths by province . 176 Table 14.8 Pregnancy-related mortality rates and ratios by age . 178 Table 14.9 Maternal mortality rates and ratios by age . 178 Table 14.10 Pregnancy-related mortality rates and ratios by residence . 179 Table 14.11 Maternal mortality rates and ratios by residence . 179 Table 14.12 Causes of maternal deaths . 180 Figure 14.1 Mortality Rates by Age Group for Women and Men Age 15-49 . 173 Figure 14.2 Mortality Rates by Age Group for Women Age 15-49, Pakistan 2005 and 2006-07 . 173 Figure 14.3 Mortality Rates by Age Group for Men Age 15-49, Pakistan 2005 and 2006-07 . 174 Tables and Figures | xiii xiv | Tables and Figures APPENDIX A ADDITIONAL TABLES Table A.1 Educational attainment of the total household population . 189 Table A.2 Household drinking water . 190 Table A.3 Household sanitation facilities, . 191 Table A.4 Housing characteristics . 192 Table A.5 Household durable goods . 193 APPENDIX B SAMPLE IMPLEMENTATION Table B.1 Sample implementation . 195 APPENDIX C ESTIMATES OF SAMPLING ERRORS Table C.1 List of selected variables for sampling errors for the women sample . 200 Table C.2 Sampling errors for national sample . 201 Table C.3 Sampling errors for urban sample . 202 Table C.4 Sampling errors for rural sample . 203 Table C.5 Sampling errors for Punjab sample . 204 Table C.6 Sampling errors for Sindh sample . 205 Table C.7 Sampling errors for NWFP sample . 206 Table C.8 Sampling errors for Balochistan sample . 207 APPENDIX D DATA QUALITY TABLES Table D.1 Household age distribution . 209 Table D.2 Age distribution of eligible and interviewed women . 210 Table D.3 Completeness of reporting . 210 Table D.4 Births by calendar years . 211 Table D.5 Reporting of age at death in days . 212 Table D.6 Reporting of age at death in months . 213 Foreword | xv FOREWORD The 2006-07 Pakistan Demographic and Health Survey (PDHS) is the fifth in a series of demographic surveys conducted by the National Institute of Population Studies (NIPS) since 1990. However, the PDHS 2006-07 is the second survey conducted as part of the worldwide Demographic and Health Surveys programme. The survey was conducted under the aegis of the Ministry of Population Welfare and implemented by the National Institute of Population Studies. Other collaborating institutions include the Federal Bureau of Statistics, the Aga Khan University, and the National Committee for Maternal and Neonatal Health. Technical support was provided by Macro International Inc. and financial support was provided by the United States Agency for International Development (USAID). The United Nations Population Fund (UNFPA) and United Nations Children's Fund (UNICEF) provided logistical support for monitoring the fieldwork for the PDHS. The 2006-07 PDHS supplements and complements the information collected through the censuses and demographic surveys conducted by the Federal Bureau of Statistics. It updates the available information on population and health issues, and provides guidance in planning, implementing, monitoring and evaluating health and population programmes in Pakistan. Some of the findings of the PDHS may seem at variance with data compiled by other sources. This may be due to differences in methodology, reference period, wording of questions and subsequent interpretation. This fact may be kept in mind while analyzing and comparing PDHS data with other sources. The results of the survey assist in the monitoring of the progress made towards meeting the Millennium Development Goals (MDGs). The 2006-07 PDHS includes topics related to fertility levels and determinants, family planning, fertility preferences, infant, child and maternal mortality and their causes, maternal and child health, immunization and nutritional status of mothers and children, knowledge of HIV/AIDS, and malaria. The 2006-07 PDHS also includes direct estimation of maternal mortality and its causes at the national level for the first time in Pakistan. The survey provides all other estimates for national, provincial and urban-rural domains. This being the fifth survey of its kind, there is considerable trend information on reproductive health, fertility and family planning over the past one and a half decades. The survey is the result of concerted effort on the part of various individuals and institutions, and it is with great pleasure that we would like to acknowledge the work that has gone into producing this useful document. The participation and cooperation that was extended by the Technical Advisory Committee during different phases of the survey is greatly appreciated. We would like to extend our appreciation to USAID/Pakistan for providing financial support for the survey. We extend our sincere thanks to Macro International Inc. for their technical support. The earnest effort put forth by the core team of the PDHS in the timely completion of the study is highly appreciated. We would also like to admire the ceaseless efforts of the entire staff of NIPS and their dedication in the successful completion of the 2006-07 PDHS. This report serves not only as a valuable reference but is a call for effective action both for the health and population programmes of the country. (Nayyar Agha) (Khushnood Akhtar Lashari) Secretary, Secretary, Ministry of Population Welfare Ministry of Health ACKNOWLEDGMENTS The 2006-07 Pakistan Demographic and Health Survey (PDHS) is the result of the ceaseless efforts of different individuals and organizations. The survey was conducted under the aegis of the Ministry of Population Welfare and implemented by the National Institute of Population Studies (NIPS). The United States Agency for International Development provided financial support through its mission in Pakistan. The United Nations Population Fund (UNFPA) and United Nations Children Funds (UNICEF) provided logistic support for monitoring the fieldwork of the survey. The Federal Bureau of Statistics (FBS) provided assistance in the selection of the sample and household listing for the sampled primary sampling units. Technical assistance for the survey was provided by Macro International Inc. USA. To all these agencies, NIPS is highly indebted. We express our deep sense of appreciation to the technical experts in the different fields of population and health for their valuable input during various phases of the survey including the finali- zation of questionnaires, training of field staff, reviewing the preliminary results and providing valuable inputs and finalizing the report. The input provided by the Technical Advisory Committee is highly appreciated. The fieldwork of the survey spanned a six-month period during which the entire staff of NIPS and the fieldwork force worked relentlessly with full devotion and commitment. The efforts of the supporting staff including Ms. Rabia Zafar, Questionnaire Coordinator, and Mr. Asif Amin and Mr. Muhammad Arif, Office Coordinators, were instrumental in organizing a disciplined training pro- gramme, dispatching questionnaires to the data collection teams and managing the completed ques- tionnaires and tracking their movement. We acknowledge the contribution of each one of them with appreciation. The administrative and financial staff of the Institute made it possible to release funds on time and make logistic arrangements for the fieldwork. The contribution of Mr. Iqbal Ahmad, Director (HRD), Mr. Amanullah Bhatti, Secretary (Management and Finance) and Mr. Muhammad Hafiz Khokar, Accounts Officer, is appreciated and acknowledged with thanks. Monitoring the fieldwork of the survey was an arduous job assigned to the core team members including Mr. Zahir Hussain, Ms. Aysha Sheraz, Mr. Zafar Zahir, Mr. Zafar Iqbal Qamar, Mr. Ali Anwar Buriro, and Mr. Mubashir Baqai. Each one of them showed full commitment and devotion and we appreciate their contribution in the survey. We appreciate and acknowledge the untiring efforts, interest, and dedication of Mr. Faateh ud din Ahmad and his data processing team, including Mr. Zahid Zaman, Deputy Data Entry Supervisor, Mr. Muhammad Shoaib Khan Lodhi, and Mr. Takasur Amin, Assistant Data Entry Supervisors. Mr. Faateh ud din also contributed in the generation of final tables for the main report. Dr. Tauseef Ahmed, Consultant for Macro International, remained with the project from the initial stage through the completion of the fieldwork and provided immense help, support and tech- nical assistance for which we are highly thankful. Ms. Anne Cross, Macro International, was a source of inspiration and encouragement throughout the survey operation. We acknowledge with deep grati- tude and thanks, the relentless and committed efforts of Ms. Cross who provided immense moral support and technical assistance at each stage of the project. We are thankful to Ms. Jeanne Cushing for all her work on data processing, analysis, production of tables for the report, and training of staff. We would also like to thank Dr. Alfredo Aliaga for computing the sampling error tables and providing technical input in the design of the study. Thanks also go to Ms. Joy Fishel, Ms. Kaye Mitchell, Ms. Melissa McCormack, Dr. Sidney Moore, Mr. Chris Gramer, Mr. Andrew Inglis, and Ms. Avril Acknowledgments | xvii xviii | Acknowledgments Armstrong for assisting with developing, reviewing, editing, formatting, and proofreading this report. We would also like to thank those involved in analyzing the verbal autopsies, including Dr. Zulfiqar Bhutta, Ms. Arjumand Rizvi, Mr. Farrukh Raza, Dr. Sadiqua N. Jafarey, Dr. Farid Midhet, and Dr. Azra Ahsan. Dr. Saeed Shafqat, former Executive Director of the Institute, initiated the project, created an environment of team work at NIPS, brought together health and population experts from all over the country, steered the implementation of the project as a consultative process, and encouraged and facilitated the core team to put in their best and complete the survey on time. We express our gratitude for his sincere leadership and professional approach. We are deeply indebted to Mrs. Sarod Lashari, Additional Secretary, Ministry of Population Welfare/Executive Director, NIPS for her guidance, support, and personal interest needed to maintain the speed of the project. (Mehboob Sultan) Project Director (Syed Mubashir Ali) Principal Investigator SUMMARY OF FINDINGS The 2006-07 Pakistan Demographic and Health Survey (PDHS) is the largest household- based survey ever conducted in Pakistan. Teams visited 972 sample points across Pakistan and collected data from a nationally representative sample of over 95,000 households. Such a large sample size was required to measure the maternal mortality ratio at the national level. In fact, this is the first survey that provides direct estimates of the maternal mortality ratio at the national level. The PDHS is the fifth national survey on demographic and health issues carried out by the National Institute of Population Studies (NIPS) and the second survey as part of the worldwide Demographic and Health Survey (DHS) project. The primary purpose of the 2006-07 PDHS is to furnish policymakers and planners with detailed information on fertility, family planning, infant, child and adult mortality, maternal and child health, nutrition, and knowledge of HIV/AIDS and other sexually transmitted infections. The Woman’s Questionnaire was administered to 10,023 ever-married women of reproductive age. FAMILY PLANNING Nearly all Pakistani women know of at least one method of contraception. Contraceptive pills, injectables, and female sterilization are known to over 85 percent of currently married women, while somewhat lower proportions report know- ing about the IUD and condoms. A higher pro- portion of respondents report knowing a modern method than a traditional method. Almost half of currently married women have ever used a family planning method, with most women having ever used a modern method (39 percent). The methods most commonly ever used by currently married women are condom, withdrawal, and the rhythm method. Three in ten currently married women re- ported using a method of contraception at the time of survey. Nearly three-fourths of these women were using a modern method. The most widely used method is female sterilization (8 percent), followed by the condom (7 percent). Use of male sterilization and the more recently introduced method of implants is negligible. The use of modern contraceptive methods among currently married women increased from 9 percent in 1990-91 to 22 percent in 2006-07. The use of contraception is higher in urban areas and among women with higher levels of education. It also increases with age and parity. Contraceptive use increases from 16 percent of currently married women in the lowest wealth quintile to 43 percent of those in the highest quintile. The government sector remains the major source of contraceptive methods, with 48 percent of users of modern methods going to a public source compared with 30 percent who use private medical sources. Government sources largely supply long-term methods such as female sterilization, IUDs, and injectables. Half of the currently married women who were not using any family planning method at the time of the survey said they intend to use a method in the future. Among currently married nonusers who do not intend to use a method of contraception in the future, a majority cited fertility-related reasons, primarily responses like “it is up to God” or responses related to sub- fecundity or infecundity. Twenty-three percent of women cited opposition to use, especially reli- gious opposition, while 12 percent do not intend to use because of method-related reasons, pri- marily fear of side effects. In spite of an almost threefold increase in the contraceptive prevalence rate over the past 16 years, there continues to be considerable scope for increased use of family planning. Twenty- five percent of currently married women in Pakistan have an unmet need for family planning services, of which 11 percent have a need for spacing and 14 percent have a need for limiting. Overall, 55 percent of Pakistani women have a demand for family planning. In other words, only just over half of the demand for contraception is currently being satisfied. Summary of Findings | xix Family planning information is largely re- ceived through the television, with limited exposure through the radio. Forty-one percent of currently married women saw a family planning message on television in the month before the survey, while 11 percent of women heard such a message on the radio. However, the vast majority of women (84 percent) who were exposed to a family planning message considered it effective. FERTILITY Survey results indicate that there has been a decline in the total fertility rate, from 5.4 children per woman in 1990-91 to 4.1 children in 2006-07, a drop of over one child in the past 16 years. Conspicuous differentials in fertility are found by level of women’s education and wealth quintile. The TFR is 2.5 children lower among women having higher education than among uneducated women. The difference between the poorest and richest women is nearly three chil- dren per woman. Research has demonstrated that children born too close to a previous birth are at increased risk of dying. In Pakistan, one-third of births occur less than 24 months after a previous birth, the same proportion as in 1990-91. AGE AT MARRIAGE In Pakistani society, where sexual activity usually takes place within marriage, marriage signals the onset of a woman’s exposure to the risk of childbearing. The length of time women are exposed to the risk of childbearing affects the number of children women potentially can bear. Thus, in Pakistani society, the age at marriage is an important determinant of fertility levels. Presently, 62 percent of women of child- bearing age are currently married, one-third (35 percent) have never married and the remaining three percent are divorced, separated, or wid- owed. The low proportion (1 percent) of women age 45-49 who have never been married indicates that marriage is still almost universal in Pakistan. Once marriages are commenced, they tend to remain stable. Divorce and separation are so- cially discouraged, and hence are uncommon (1 percent). Though teenage marriages are on the decline, one out of six women age 15-19 is already married. The median age at first marriage has increased by about half a year in the last 16 years, i.e., from 18.6 years in 1990-91 to 19.1 years in 2006-07. Important differentials in median age at first marriage are found on the basis of educational level and wealth quintile. FERTILITY PREFERENCES The study of fertility desires in a population is crucial, both for estimating potential unmet need for family planning and for predicting future fertility. The PDHS data show that more than half of currently married women age 15-49 (52 percent) either do not want another child at any time in the future or are sterilized. Over four in ten women want to have a child at some time in the future—21 percent want one within two years, 20 percent would prefer to wait two or more years, and 2 percent want another but are undecided as to when. Since the 1990-91 PDHS, there has been a substantial increase (12 percentage points) in the proportion of married women who want to limit childbearing (from 40 to 52 percent). Future fertility preferences depend not only on the number of living children, but also on the sex composition of the children. Most couples want to have some children of both sexes; however, in Pakistan, there is a stronger preference for sons over daughters. For example, among women with three children, 65 percent of those with three sons want to have no more children, compared with only 14 percent of those with three daughters. Similarly, among women with five children, 85-90 percent of women with four or five sons say they want no more children, as opposed to only 65 percent of those with no sons or only one son. The mean ideal number of children is 4.1 for both ever-married and currently married women. It increases from 3.7 children among childless women to 5.0 among women with 6 or more children, which could either be due to the fact that those who want larger families tend to achieve their goals or to the fact that women rationalize their larger families by reporting their actual number of children as their ideal number. The mean ideal number of children among ever- married and currently married women has re- mained the same as in 1990-91. xx � Summary of Findings Substantial differences are observed across provinces, ranging from a mean ideal number of children of 3.8 in Punjab to 5.9 in Balochistan. There is a steady decrease in the mean ideal family size as the education and wealth quintile of the woman increases. Whether a birth was planned (wanted then), mistimed (wanted later), or not wanted at all, provides some indication of the extent of unwanted childbearing. Overall, 24 percent of births in the five years preceding the survey were not wanted at the time of conception, with 13 percent wanted at a later time and 11 percent not wanted at all. Overall, the total wanted fertility rate is 24 percent lower than the total fertility rate. Thus, if unwanted births could be eliminated, the total fertility rate in Pakistan would be 3.1 births per woman instead of 4.1 births. INFANT AND CHILD MORTALITY The study of infant and child mortality is critical for assessment of population and health policies and programmes. Infant and child mor- tality rates are also regarded as indices reflecting the degree of poverty and deprivation of a popu- lation. For the most recent five-year period pre- ceding the survey, infant mortality is 78 deaths per 1,000 live births and under-five mortality is 94 deaths per 1,000 live births. The pattern shows that over half of deaths under five occur during the neonatal period, while 26 percent occur during the postneonatal period. Under-five mortality has declined from 117 in 1986-90 to 94 in 2002-06, a 20 percent decline in 16 years. Differentials by place of residence show that the under-five mortality rate is 28 percent higher in rural areas than in urban areas (100 vs. 78 deaths per 1,000 live births). As might be expected, rates are lower in major cities than in other urban areas. Female mortality is lower than that of males for the neonatal period only, while males have the advantage during the postneonatal period up to age five years. As is common in most popula- tions, first births generally have higher mortality rates than later births. The length of birth interval has a significant correlation with a child’s chances of survival, with short birth intervals considerably reducing the chances of survival. For example, the under- five mortality rate is twice as high for children born after an interval of less than 2 years, compared with those born four or more years after a previous sibling (122 vs. 61 deaths per 1,000 live births). Size of the child at birth also has a bearing on the childhood mortality rates. Children whose birth size is small or very small have a 68 percent greater risk of dying before their first birthday than those whose birth size is average or larger. The major causes of death among children under five are birth asphyxia (accounting for 22 percent of deaths), sepsis (14 percent), pneu- monia (13 percent), diarrhoea (11 percent), and prematurity (9 percent). As expected, causes of death are highly correlated with the age at death. Deaths during the neonatal period (first month of life) are almost entirely due to birth asphyxia, sepsis, or prematurity. Deaths in the postneonatal period (age 1-11 months) are mostly due to diarrhoea and pneumonia, while the main causes of deaths to children age 1-4 years are diarrhoea, pneumonia, injuries, measles, and meningitis. These results support a strong focus on addres- sing newborn deaths and a continued focus on reducing deaths from diarrhoea and pneumonia. REPRODUCTIVE HEALTH Promotion of maternal and child health has been one of the most important objectives of the health programme in Pakistan. Prenatal care, care at the time of delivery and postnatal care are the three important components of reproductive health. The quality of prenatal care can be assessed by the type of provider, the number of prenatal visits, and the timing of the first visit. Sixty-one percent of mothers receive pre- natal care from skilled health providers that is, from a doctor, nurse, midwife or Lady Health Visitor. Only 3 percent of women receive pre- natal care from a traditional birth attendant (dai). In addition, one percent of mothers receive pre- natal care from a Lady Health Worker, a dis- penser or compounder, or a hakim. Thirty-five percent of women receive no prenatal care at all. There has been a significant improvement over Summary of Findings | xxi the past ten years in the proportion of mothers who receive prenatal care from a skilled health provider, increasing from 33 percent in 1996 to 43 percent in 2001 to 44 percent in 2003 to 61 percent in 2006-07. The PDHS data show that more than one- fourth (28 percent) of pregnant women make four or more prenatal care visits during their entire pregnancy. Urban women (48 percent) are more than twice as likely as rural women (20 percent) to have four or more prenatal visits. Thirty-one percent of women make their first prenatal care visit before the fourth month of pregnancy. The median duration of pregnancy at the first prenatal care visit is 4.2 months. The percentage of women who made four or more prenatal care visits during their pregnancy has increased during the last ten years, from 16 percent in 1996 to 24 percent in 2003 to 28 percent in 2006-07. Overall, there has been some improvement in the utilization and quality of prenatal care services in recent years. For example, the percentage of mothers who received at least two tetanus toxoid injections during pregnancy has nearly doubled—from 29 percent in 2001 to 53 percent in 2006-07. Only 34 percent of births in Pakistan take place in a health facility; 11 percent are delivered in a public sector health facility and 23 percent in a private facility. Three out of five births (65 percent) take place at home, with a majority of mothers saying the main reason they did not deliver their most recent baby in a health facility is because it is not necessary. The percentage of births that take place in a health facility has doubled in the past ten years, increasing from 17 percent in 1996 to 23 percent in 2000-01 and to 34 percent in 2006-07. Less than two-fifths (39 percent) of births take place with the assistance of a skilled medical provider (doctor, nurse, midwife, or Lady Health Visitor). Traditional birth attendants assist with more than half (52 percent) of deliveries, while friends and relatives assist with 7 percent of deliveries. Prompt checkups following delivery are crit- ical for monitoring complications for both the mother and the baby. In the five years preceding the survey, two-fifths (43 percent) of women received postnatal care for their last birth, mak- ing it far less common than prenatal care (65 percent). More than one-fourth of women re- ceived postnatal care within four hours of delivery, while 6 percent received care within the first 4-23 hours, 7 percent of women received postnatal care two days after delivery and 3 percent of women were seen 3-4 days following delivery. Just over one-quarter of mothers (27 percent) received postnatal care from a skilled health provider, while 16 percent received care from traditional birth attendants. One of the most serious injuries of child- bearing is obstetric fistula, a hole in the vagina or rectum usually caused by prolonged labour with- out treatment. Only 3 percent of ever-married women who have ever given birth have experi- enced the most common symptom of fistula, the constant dribbling of urine. CHILD HEALTH The status of child health in the PDHS is determined by birth weights, level of immuni- zation among children, as well as the prevalence and treatment of a number of common childhood illnesses including diarrhoea, acute respiratory infections and fever. Babies whose birth weight is low not only have lower chances of survival but also face higher risk of morbidity and mortality. In Pakistan, because a large proportion of births occur at home, mothers were asked to report the size of the child at birth. Contrary to expectations, the proportion of births reported by the mother to be very small or smaller than average has increased from 22 percent in 1990- 91 to 31 percent in 2006-07. This implies that it would be very difficult for the Government of Pakistan to achieve the targets for improving low birth weight set for 2010. There has been a steady upward trend in the proportion of children who are fully immunized from 35 percent in 1990-91 to 47 percent in 2006-07. In 2006-07, according to information from the vaccination records and mothers’ recall, 80 percent of children aged 12-23 months have received a BCG vaccination, 75 percent have received the first dose of DPT, and 93 percent have received the first dose of polio vaccine. Coverage declines for subsequent doses of DPT and polio; only 59 and 83 percent of children receive the third doses of DPT and polio, xxii � Summary of Findings respectively. Six percent have not received any vaccinations at all. The PDHS data show that 14 percent of children under age five had symptoms of acute respiratory infection (ARI) in the two weeks preceding the survey and 31 percent had a fever in the same period. About two-thirds of children who showed symptoms of ARI or fever were taken to a health facility or medical provider for treatment. Half of children with ARI received antibiotics. Twenty-two percent of children under five were reported to have had an episode of diarrhoea during the two-week period before the survey and three percent had diarrhoea with bloody stools. Of all children with diarrhoea, two in five were given fluid made from an oral rehydration salt (ORS) packet, 16 percent were given a recommended homemade fluid (RHF), and more than half (55 percent) were given ORS, RHF, or more fluids than usual. Forty-seven percent of children with diarrhoea were given some kind of pill or syrup to treat the disease, while 14 percent were given home remedies or herbs. About one in five children with diarrhoea was not treated at all. The data show that 41 percent of children with diarrhoea were given the same quantity of fluids as usual, while 21 percent received more fluids than usual, and 34 percent received some- what or much less fluid than usual. These results suggest that in Pakistan, about one in three moth- ers still curtail fluid intake when their children have diarrhoea, a very dangerous practice which should be addressed with a national educational campaign. NUTRITION Poor nutritional status is one of the most important health and welfare problems facing Pakistan today and particularly afflicts women and children. Poor breastfeeding and infant feed- ing practices have adverse consequences for the health and nutritional status of children. Fortu- nately, breastfeeding in Pakistan is almost uni- versal and generally of fairly long duration. Nevertheless, only 70 percent of newborns are breastfed within one day after delivery. According to the 2006-07 PDHS, a majority (55 percent) of children under the age of two months are exclusively breastfed. This represents a doubling from the 27 percent of children under two months who were exclusively breastfed in 1990-91, an encouraging trend. Overall, only 37 percent of infants under 6 months are exclusively breastfed, far lower than the recommended 100 percent exclusive breastfeeding for children under 6 months. The median duration of breastfeeding among Pakistani children is 19 months, one month lower than reported in 1990-91, suggesting that during the last decade and a half the patterns have changed only slightly. The median duration of exclusive breastfeeding is estimated at a little less than one month. Ensuring that children between 6 and 59 months receive enough vitamin A may be the single most effective child survival intervention. Survey results show that 60 percent of children age 6-59 months received a vitamin A supple- ment in the six months preceding the survey. Night blindness—an indicator of severe vitamin A deficiency to which pregnant women are especially prone—is common in Pakistan. Five percent of women with a recent birth reported having had difficulty seeing only at night during the pregnancy of the last birth. Overall, only four in ten women take iron or calcium supplements during pregnancy. MALARIA Women who had a live birth in the five years preceding the survey were asked whether they suffered from malaria during pregnancy and if yes, whether they received any treatment. One in five women suffered from malaria during their pregnancy, the vast majority of whom received treatment for the disease. The prevalence of malaria is higher in rural areas (22 percent), in the province of Balochistan (30 percent), among women with no education (22 percent) and among those who are in the lowest (29 percent) and second lowest wealth quintiles (23 percent). Among children under five, 31 percent are reported to have had fever in the two weeks preceding the survey. Of those, only three percent took antimalarial drugs. Summary of Findings | xxiii xxiv � Summary of Findings Mosquito nets are not common in Pakistan; only 6 percent of households have a net. KNOWLEDGE OF HIV/AIDS The HIV/AIDS pandemic is one of the most serious health concerns in the world today be- cause of its high case fatality rate and the lack of a cure. The Ministry of Health and UNAIDS estimate that approximately 80,000 people are currently living with HIV in Pakistan. In spite of vast media campaigns, only four in ten ever-married women age 15-49 in Pakistan have heard about AIDS. Awareness of AIDS has barely increased over the last decade, from 41 percent to 44 percent of ever-married women. Overall, only five percent of women are classified as having comprehensive knowledge about AIDS, i.e., knowing that consistent use of condoms and having just one faithful partner can reduce the chance of getting infected, knowing that a healthy-looking person can be infected, and knowing that AIDS cannot be transmitted by sharing food or by mosquito bites. This low level of knowledge should be a matter of concern to policymakers and for the National AIDS Control Programme. ADULT AND MATERNAL MORTALITY By collecting information to measure not only the maternal mortality ratio, but also causes of adult female deaths through verbal autopsies, the 2006-07 PDHS fulfilled a longstanding desire of reproductive health professionals in Pakistan. Most estimates of the maternal mortality ratio available before this survey were based on mathematical models or indirect estimation. Through its unique design, the 2006-07 PDHS provides a wealth of information about adult female deaths. The maternal mortality ratio as measured in the survey is 276 maternal deaths per 100,000 births. This is slightly lower than the generally accepted previous estimates of around 320 ma- ternal deaths per 100,000 births. Postpartum haemorrhage is the leading direct cause of ma- ternal deaths, followed by puerperal sepsis and eclampsia. Obstetric bleeding (postpartum and antepartum haemorrhage) is responsible for one- third of all maternal deaths. The data imply that roughly 1 in 89 women in Pakistan will die of maternal causes during her lifetime (lifetime risk). Adult female and male mortality rates for ages 15-49 as measured through the survey are plausible. Among adult women, complications of pregnancy and childbirth emerge as the outstand- ing cause of death in the reproductive years, accounting for one-fifth of deaths to women of childbearing age in Pakistan. Cancer, tubercu- losis, and other infectious diseases are the next most important causes of death among women in reproductive ages. xxvi | Map of Pakistan xxvi | Map of Pakistan INTRODUCTION 1 Shahid Munir and Khalid Mehmood Pakistan’s first Demographic and Health Survey was undertaken in 1990-91. Since then, other surveys focusing on fertility and family planning, reproductive health, and status of women were conducted. The current demographic and health survey has special features, including maternal mortality and infant and child health, mortality, and morbidity, in addition to the conventional areas that most demographic and health surveys cover. Before deliberating on the findings of the survey, a short description of the salient features of Pakistan—including its geography, climatic conditions, history, economy, and population size and growth—as well as details regarding the sample size and field operations, is given to enable readers to place the findings of the survey in proper sociodemographic and geographic perspective. 1.1 GEOGRAPHY, CLIMATE, AND HISTORY Pakistan is the “Land of the Indus River,” which flows through the country for 2,500 kilometres (1,600 miles) from the Himalaya and Karakoram mountain ranges to the Arabian Sea. It is a land of snow-covered peaks, hot deserts and barren land, as well as a vast area of irrigated plains. Pakistan is located between 24� and 37� N latitude and between 61� and 75� E longitudes. It occupies a strategically important position. On its east and southeast lies India, to the north and northwest is Afghanistan, to the west is Iran, and in the south is the Arabian Sea. It has a common frontier with China on the border of its Gilgit Agency in the northeast. Tajikistan, formerly in the USSR, is separated from Pakistan by a narrow strip of Afghan territory called Wakhan. Pakistan comprises a total land mass of 796,096 square kilometres. There are three main regions: the mountainous region in North, which has three world famous mountain ranges (the Hindukush, the Karakoram, and the Himalayas); the enormous but sparsely populated plateau of Balochistan; and the Punjab and Sindh plains of the Indus River and its main tributaries. Pakistan is divided into four provinces. Balochistan province is in the southwest, and the Punjab and Sindh provinces are plains with the world’s largest irrigation system. North-West Frontier Province (NWFP) is located in the northwest. Pakistan is strategically located at the crossroads of Asia, where the road from China to the Mediterranean meets the route from India to Central Asia. For thousands of years, this junction has been a melting pot of diverse cultures, attracting warriors, traders and adventurers. Now the old Chinese trade route is reopened, providing access to the spectacular Karakorams and Pamirs, following the ancient Silk Route and entering China over the 4,733 metre (15,528 feet) Khunjerab pass, the highest asphalt border crossing in the world. In the northeastern tip of the country, Pakistan controls about 84,159 square kilometres of the former state of Jammu and Kashmir. This area consists of Azad Kashmir (11,639 square kilometres) and most of the Northern Area (72,520 square kilometres), which includes the ruggedly mountainous and beautiful Gilgit and Baltistan. In fact, the Northern Area has five of the world’s 14 highest mountain peaks, each over 8,000 metres high. It also has extensive glaciers including the Siachen glacier that it is sometimes called the “third pole.” Pakistan enjoys a considerable variety of weather. The north and northwestern high mountain ranges are extremely cold in winter, while the summer months from April to September are very pleasant. The vast plains of the Indus Valley are hot to very hot in summer and have cold weather in winter. The coastal strip in the south has a temperate climate. Although it is in the monsoon region, Introduction | 1 which falls late in summer, the average rainfall varies between 76 and 127 cm. The province of Balochistan is the driest, where on average only 21 cm of rain falls, mostly in winter. Pakistan achieved independence from Britain on the 14th of August 1947 as a result of the long struggle by Muslims of India for a separate homeland of their own. In fact, its foundation was laid when Mohammad Bin Qasim—a Muslim leader of Saudi Arabia—subdued Sindh in 711 AD as a reprisal against sea pirates that had taken refuge in Raja Dahir’s kingdom. But the areas constituting Pakistan have had a historical individuality of their own even before the advent of Islam. Archaeological sites and imposing monuments scattered over the country richly illustrate Pakistan’s 4,000-year history. Brick cities like Moenjodaro and Harrapa from the Indus civilization, which flourished around 2000 BC, stand beside Buddhist ruins contemporaneous with the birth of Christianity. Magnificent Muslim tombs, mosques, and forts built by the mogul emperors from the 12th century to the 16th and 17th centuries are a common site found in this part of the world. 1.2 ECONOMY AND POPULATION Pakistan’s economy continues to gain traction as it experiences the longest spell of its strongest growth in years. The outcomes of the 2006-07 fiscal year indicate that Pakistan’s economic momentum remains on track. Economic growth accelerated to 7 percent in 2006-07 at the back of robust growth in agriculture, manufacturing, and services. Pakistan’s growth performance over the last five years has been striking. Average real gross domestic product (GDP) growth during 2003-07 had the best performance in decades, and it now seems that Pakistan has decisively broken out of the low growth rut that it was in for more than 10 years. Pakistan’s economy continues to perform impressively and its economic fundamentals have gained further strength in the fiscal year 2006-07. The most important achievements of this year include the following: • Strong economic growth of 7 percent despite the pursuance of a tight monetary policy, resulting in an interest rate increase; • Strong recovery in agricultural growth at 5 percent and major crops at 7.6 percent on the heels of the highest ever production of wheat (23.5 million tonnes) in the country’s history and an impressive 23 percent increase in sugar cane production (54.7 million tonnes); • Continued large-scale growth (8.8 percent) in manufacturing, although this is a somewhat less torrid pace than last year; • Continued expansion of the overall service sector at a solid pace of 8 percent; and • Strong average economic growth of over 7.5 percent during the past four years that maintains Pakistan’s position as one of the fastest growing economies in the Asian region along with China, India, and Vietnam. This good economic performance has resulted from a combination of generally sound economic policies, on-going structural reforms, and a benign international economic environment. Based on the performance of half a decade of strong, stable, resilient, and broad-based economic growth, it appears that Pakistan’s economy will continue to be a high mean, low variance economy over the medium-term (Government of Pakistan, 2007). The population of Pakistan is estimated around 160 million as of mid-2007 and is growing at 1.9 percent per annum (Government of Pakistan, 2007). The population growth rate has receded from a record high of 3.7 percent per year in the 1960s. About two-thirds of the population is rural. Pakistan is the sixth most populous country in the world (PRB, 2007) and is adding around three million persons per year (NIPS, 2007b). Forty-one percent of its population is below 15 years of age, 2 | Introduction which is indicative of high fertility in the past. Women of reproductive age constitute almost one- quarter of the total population. Marriage is universal and the fertility rate is far above replacement level. The government’s population policy, promulgated in 2002, aims to reduce fertility to replacement level by 2020 (MOPW, 2002). However, population stabilization would still be two generations away even if replacement-level fertility were attained by that date. The rapid increase in population has resulted in a quadrupling of the population over the past five decades. This has jeopardized economic gains; in spite of a 327-fold increase in the national GDP between 1960 and 2006, the per capita income has increased only nine-fold. Although the literacy rate has increased since the early 1960s, illiterates number more than 52 million. Unemployment has grown by 11 times in the past 35 years, per capita availability of water has declined to below 1,200 cubic metres per year, and an investment of over 7.4 billion US dollars is required to keep the 2006 level of per capita income of US$847 (NIPS, 2006). The rapid increase in population is also adversely affecting health indicators. Huge funds are required to maintain the existing ratio of population per health facility. At present, there is only one hospital available for over 170,000 persons; one rural health centre available for more than 184,000 persons living in rural areas; one basic health unit available for more than 19,000 persons in rural areas; and one maternal and child health centre available for more than 4,400 expecting mothers and newborns. There is only one doctor available for over 1,300 people and one nurse for 4,600 persons. The rapid increase in population constrains economic gains and stretches the already overburdened health facilities (Government of Pakistan, 2007). The population welfare programme has taken a number of initiatives to reduce the rapid increase in population. The programme has been in the process of engaging different stakeholders in the public, private, and nongovernmental sectors to cater to the family planning and reproductive health needs of men and women across Pakistan. The programme aims to provide universal access to modern contraceptive methods by 2010 and reduce the unmet need for family planning. Pakistan's national language is Urdu, which is widely understood in most parts of the country. However, in the provinces, local languages are also spoken. In northern and southern Punjab, the local languages are Punjabi and Saraiki, respectively. Sindhi is widely spoken in Sindh, except in Karachi, where Urdu is the main language. Pushto is the local language of NWFP and the Federally Administered Tribal Areas (FATA), although Hindko is also spoken in certain parts of NWFP. Balochi, Pushto, and Brahvi are widely spoken languages in Balochistan. The official language of the federal and provincial governments is English. The vast majority of the population is Muslim (97 percent). Minorities include Christians, Hindus, Parsis, Marwaris, Mangowars, and Ahmadies. 1.3 ORGANIZATION AND IMPLEMENTATION OF THE 2006-07 PDHS 1.3.1 Objectives of the Survey The 2006-07 Pakistan Demographic and Health Survey (PDHS) was undertaken to address the monitoring and evaluation needs of maternal and child health and family planning programmes. The survey was designed with the broad objective to provide policymakers, primarily in the Ministries of Population Welfare and Health, with information to improve programmatic interventions based on empirical evidence. The aim is to provide reliable estimates of the maternal mortality ratio (MMR) at the national level and a variety of other health and population indicators at national, urban-rural, and provincial levels. More specifically, PDHS had the following objectives: Introduction | 3 • Collect quality data on fertility levels and preference, family planning knowledge and use, childhood—and especially neonatal—mortality levels and awareness regarding HIV/ AIDS and other indicators relevant to the Millennium Development Goals and the Poverty Reduction Strategy Paper; • Produce a reliable national estimate of the MMR for Pakistan, as well as information on the direct and indirect causes of maternal deaths using verbal autopsy instruments; • Investigate factors that impact on maternal and neonatal morbidity and mortality (i.e., antenatal and delivery care, treatment of pregnancy complications, and postnatal care); • Improve the capacity of relevant organizations to implement surveys and analyze and disseminate survey findings. 1.3.2 Institutional Framework The Ministry of Population Welfare executed the 2006-07 PDHS project, whereas the National Institute of Population Studies (NIPS) undertook the responsibility of implementing the project. A Steering Committee, chaired by the Secretary of the Ministry of Population Welfare and co-chaired by the Secretary of the Ministry of Health, included members from federal social sector ministries and provincial health and population departments. The Steering Committee provided guidance, administrative support, and facilitation during the survey process. A Technical Advisory Committee consisting of population professionals, experts, and researchers from relevant fields was formed to provide guidance and support at various stages of the survey. NIPS was responsible for planning, organizing, and overseeing the survey operations, including hosting meetings to discuss the survey with representatives from major users, technical institutions, and international bodies; recruiting, training, and supervising fieldworkers and data processing staff; and analyzing and writing this report. The Federal Bureau of Statistics (FBS) provided the sample design and household listings for the sampled areas across Pakistan. Macro International Inc. provided technical assistance to NIPS for the design and implementation of the PDHS project. Funds for the project were provided by the United States Agency for International Development (USAID), while the United Nations Population Fund (UNFPA) and the United Nations Children’s Fund (UNICEF) provided logistic support for monitoring the survey operations. 1.3.3 Sample Design The 2006-07 PDHS is the largest-ever household based survey conducted in Pakistan. The sample is designed to provide reliable estimates for a variety of health and demographic variables for various domains of interest. The survey provides estimates at national, urban and rural, and provincial levels (each as a separate domain). One of the main objectives of the 2006-07 Pakistan Demographic and Health Survey (PDHS) is to provide a reliable estimate of the maternal mortality ratio (MMR) at the national level. In order to estimate MMR, a large sample size was required. Based on prior rough estimates of the level of maternal mortality in Pakistan, a sample of about 100,000 households was proposed to provide estimates of MMR for the whole country. For other indicators, the survey is designed to produce estimates at national, urban-rural, and provincial levels (each as a separate domain). The sample was not spread geographically in proportion to the population; rather, the smaller provinces (e.g., Balochistan and NWFP) as well as urban areas were over-sampled. As a result of these differing sample proportions, the PDHS sample is not self-weighting at the national level. The sample for the 2006-07 PDHS represents the population of Pakistan excluding the Federally Administered Northern Areas (FANA) and restricted military and protected areas. Although the Federally Administered Tribal Areas (FATA) were initially included in the sample, due to security and political reasons, it was not possible to cover any of the sample points in the FATA. 4 | Introduction In urban areas, cities like Karachi, Lahore, Gujranwala, Faisalbad, Rawalpindi, Multan, Sialkot, Sargodha, Bahawalpur, Hyderabad, Sukkur, Peshawar, Quetta, and Islamabad were considered as large-sized cities. Each of these cities constitutes a stratum, which has further been sub- stratified into low, middle, and high-income groups based on the information collected during the updating of the urban sampling frame. After excluding the population of large-sized cities from the population of respective former administrative divisions, the remaining urban population within each of the former administrative divisions of the four provinces was grouped together to form a stratum. In rural areas, each district in Punjab, Sindh, and NWFP provinces is considered as an independent stratum. In Balochistan province, each former administrative division has been treated as a stratum. The survey adopted a two-stage, stratified, random sample design. The first stage involved selecting 1,000 sample points (clusters) with probability proportional to size—390 in urban areas and 610 in rural areas. A total of 440 sample points were selected in Punjab, 260 in Sindh, 180 in NWFP, 100 in Balochistan, and 20 in FATA. In urban areas, the sample points were selected from a frame maintained by the FBS, consisting of 26,800 enumeration blocks, each including about 200-250 households. The frame for rural areas consists of the list of 50,588 villages/mouzas/dehs enumerated in the 1998 population census. The FBS staff undertook the task of a fresh listing of the households in the selected sample points. Aside from 20 sample points in FATA, the job of listing of households could not be done in four areas of Balochistan due to inability of the FBS to provide household listings because of unrest in those areas. Another four clusters in NWFP could not be covered because of resistance and refusal of the community. In other words, the survey covered a total of 972 sample points. The second stage of sampling involved selecting households. In each sample point, 105 households were selected by applying a systematic random sampling technique. This way, a total of 102,060 households were selected. Out of 105 sampled households, ten households in each sample point were selected using a systematic random sampling procedure to conduct interviews for the Long Household and the Women’s Questionnaires. Any ever-married woman aged 12-49 years who was a usual resident of the household or a visitor in the household who stayed there the night before the survey was eligible for interview. 1.3.4 Questionnaires The following six types of questionnaires were used in the PDHS: • Community Questionnaire • Short Household Questionnaire • Long Household Questionnaire • Women’s Questionnaire • Maternal Verbal Autopsy Questionnaire • Child Verbal Autopsy Questionnaire The contents of the Household and Women’s Questionnaires were based on model questionnaires developed by the MEASURE DHS programme, while the Verbal Autopsy Questionnaires were developed by Pakistani experts and the Community Questionnaire was patterned on the basis of one used by NIPS in previous surveys. NIPS developed the draft questionnaires in consultation with a broad spectrum of technical experts, government agencies, and local and international organizations so as to reflect relevant issues of population, family planning, HIV/AIDS, and other health areas. A number of meetings were organized by NIPS and the inputs received in these meetings were used to finalize survey questionnaires. These questionnaires were then translated into Urdu, Punjabi, Sindhi, and Pushto Introduction | 5 languages. After the pretest, which was done in Peshawar, Rawalpindi, and Hyderabad, the questionnaires were finalized on the basis of feedback of the pretest. The Community Questionnaire, a brief form that was filled out for each sample point in rural areas, included questions about the availability of various kinds of health and family planning facilities and services. Also, information on the availability of transportation, education, and communication facilities was recorded. The geographic coordinates were taken for each sample point using a geographic positioning system (GPS) unit. The Short Household Questionnaire was administered in 92,340 households to list all the usual members and visitors. Likewise, the Long Household Questionnaire was used in the 9,720 households where the Women’s Questionnaire was also administered. In addition to some basic information collected on characteristics like age, sex, marital status, education, and relationship to the head of the household of each person listed, another purpose of the two household questionnaires was to record births and deaths that occurred since January 2003 and, for verbal autopsies, to identify any death of child under age 5 since January 2005 and any death to a woman age 12-49 since January 2003a. In addition, the Long Household Questionnaire collected more details, e.g., current school attendance, survivorship status of parents of children under age 18, and the registration status of each person. It also identified eligible ever-married women age 12-49 for interview with the Women’s Questionnaire. The Long Household Questionnaire also collected information regarding various characteristics of the dwelling unit, such as the source of water; type of toilet facilities; type of cooking fuel; materials used for the floor, roof, and walls of the house; ownership status of various durable goods; ownership of agricultural land; ownership of livestock/farm animals/poultry; and ownership and use of mosquito nets. As mentioned above, the Women’s Questionnaire collected information from ever-married women age 12-49 years on the following topics: • Background characteristics (education, literacy, native language, marriage characteristics, etc.) • Reproductive history • Knowledge and use of family planning methods • Prenatal and postnatal care • Child immunization, health, and nutrition • Fertility preferences • Breastfeeding practices • Woman’s work and husband’s background characteristics • Awareness about HIV/AIDS and other sexually transmitted infections • Other health issues (knowledge of tuberculosis and hepatitis, experience with fistula, use of clean syringes for injections). The Verbal Autopsy Questionnaire for deaths of women was administered in households in which a death of a woman aged 12-49 was reported since 2003. The questionnaire covered details about the woman’s characteristics and the symptoms and circumstances prior to her death. A verbatim history was also recorded so as to help assign a cause of death. Questions were also asked about any treatment or health care that might have been sought before her death. The Child Verbal Autopsy Questionnaire was administered in households in which a death of a child under age five years or a stillbirth was reported in 2005 or later. The questionnaire elicited details about the illness and causes of death from the parents and/or others who were present at the time of death of the child. Separate teams of physicians reviewed both these verbal autopsy questionnaires to assign causes of death. 6 | Introduction 1.3.5 Training of Field Staff The main survey training was held during a three-week period in August and was attended by all interviewers, supervisors, quality control personnel, field coordinators, and data entry staff. The training included lectures, demonstrations, practice interviewing in small groups, and examinations. Separate training was arranged for interviewers selected for collecting information through verbal autopsies for women and children. All teams participated in three days of field practice. 1.3.6 Field Supervision and Monitoring Ensuring high-quality data was a prime objective of the survey and was assured through regular supervision and monitoring of NIPS teams during fieldwork. NIPS designated six professional staff to act as field coordinators who visited the teams assigned to them on a regular basis. From the first week of data collection, all professional NIPS staff followed the field teams to support and facilitate them in using the questionnaires, understanding the sample selection procedures, conducting interviews in all five questionnaires, using field control sheets, assigning interviewers, editing the questionnaire, linking with FBS offices, observing team coordination, and ensuring efficient use of time. The field coordinators visited the teams at least once a month. The quality control interviewers accompanied these field coordinators. Quality control interviewers were deputed to work with various teams for three to four days to undertake several tasks: observe on-going interviews for delivery of questions, verify and validate information recorded by interviewers by revisiting and re-interviewing respondents, review completed interviews/questionnaires, and provide on-the-job training for weaker field staff. They also edited completed questionnaires and reviewed any errors with the team members. Finally, they assisted the teams to resolve any problems. The monitoring checklist was shared with the team members and supervisors to maintain transparency and openness in the process. Close communication was maintained at all times between the NIPS, field supervisors, and interviewers during fieldwork. Team supervisors were responsible for the performance of their teams. Team performance was judged by team cohesion and discipline, timely arrival at primary sampling units (PSUs) and visits and revisits to households to complete all 105 questionnaires, use of supervisory control sheets, and efficient use of time by team members. For supervision of each member of a field team, the NIPS’ field coordinators and quality control interviewers maintained close contact with the teams under their responsibility and with the PDHS core team. Over the period of the survey, all teams were visited five to six times in the field. Monitoring was also undertaken by Agha Khan University colleagues in various districts to see the quality of data being recorded on child death verbal autopsies. The project director, principal investigator, and project consultant visited the field regularly and communicated to team supervisors and team members on a regular basis. A consultant from Macro visited NIPS in November 2006 to meet the PDHS core team and visit field teams across Pakistan to see their work and to review the data coding and entry processes. A set of quality control check tables for critical indicators was produced periodically during the fieldwork using the computerized data at NIPS. Problems that appeared from review of these tables were discussed with the relevant teams and attempts made to ensure that the problems did not persist. Regular meetings of the core staff and field coordinators were held at NIPS to exchange views on progress, performance, problems, solutions, and future strategies. These meetings were helpful in resolving field problems and improving the quality of data collected from the field. NIPS established a comprehensive system to ensure sufficient funds were transferred to team supervisors and interviewers to cover the costs of operating vehicles, communications, and per diem payments to all team members. NIPS also formed a system that ensured that the interviewing teams received necessary materials on a timely basis. Two courier services were contracted for rapid and safe delivery of material to the field and dispatch of completed questionnaires to NIPS. Introduction | 7 1.3.7 Fieldwork and Data Processing Twenty-nine teams collected the survey data. Most teams consisted of six female interviewers and a male supervisor. Data collection using the Short and Long Household Questionnaires, Women’s Questionnaire, Child Verbal Autopsy Questionnaire, and Maternal Verbal Autopsy Questionnaire was assigned to different interviewers in each team. The fieldwork began in early September 2006 and was completed in February 2007. As mentioned earlier, senior DHS technical staff, field coordinators, and quality control teams visited teams regularly to review the work and monitor data quality. The processing of the data entry of the 2006-07 PDHS questionnaires started shortly after the fieldwork commenced. Completed questionnaires were returned regularly from the field to NIPS headquarters in Islamabad, where they were edited and entered by the data processing teams who were specifically trained for this task. The NIPS computer programmer who attended a three-week training course in data entry and editing at Macro’s headquarters in the United States, supervised the data processing. Other data processing personnel included an office coordinator who ensured that the expected number of questionnaires from each cluster was received, several office editors, 20 data entry operators working in two shifts, and secondary editors. A double-entry system was adopted for data entry. The concurrent processing of the data was an advantage because the senior PDHS technical staff and field coordinators were able to advise field teams of problems detected during the data entry. Copies of the verbal autopsies were promptly made and dispatched to the reviewing teams of doctors. Field check tables were timely generated and, as a result, specific feedback was given to the teams to improve performance. The data entry and editing phase of the survey was completed in April 2007. 1.3.8 Field Problems A number of problems were encountered during the fieldwork. Initially, the sample design had included collecting data from the FATA. This, however, was not possible, because the FBS was unable to provide household listings for the selected clusters due to the prevailing unrest in the area. In addition, the FBS was also not able to provide household listings for four clusters in Balochistan province due to the same reasons. In NWFP, the data collection teams experienced hostilities from four communities and hence could not complete data collection or could not carry out the fieldwork in those areas. Hostility at individual households was also experienced in a few places. In all areas of NWFP, the data collection teams had to get permission from village or area elders before starting the fieldwork. This was sometimes possible after hours of deliberations (jirga) with the community leaders, especially in rural areas. However, in most of the areas and especially in rural Sindh and NWFP, teams were offered food and drinks and sometimes gifts to keep up with their traditions because the team members were visiting those households for the first time. A few members of the data collection teams got sick, were hospitalized, or were bitten by dogs. A harsh winter in parts of Balochistan and NWFP also welcomed the data collection teams and resultantly prolonged their working hours. However, the fieldwork was successfully completed in the stipulated time frame. 8 | Introduction Introduction | 9 1.4 RESPONSE RATES Table 1.1 presents household and individual response rates for the survey. A total of 102,037 households were selected for the sample, of which 97,687 were occupied at the time of fieldwork.1 The main reason for the difference is that some of the dwelling units that were occupied during the household listing operation were either vacant or the household was away for an extended period at the time of interviewing. Of the occupied households, 95,441 (98 percent) were successfully interviewed. In the 9,255 households interviewed with the Long Household Questionnaire, a total of 10,601 ever-married women aged 12-49 were identified, of whom 10,023 were successfully interviewed, yielding a response rate of 95 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 are only slightly lower in urban areas than in rural areas.2 Table 1.1 Results of the household and individual interviews Number of households, number of interviews, and response rates, according to residence (unweighted), Pakistan 2006-07 Residence Result Total urban Major city Other urban Rural Total Household interviews (total) Households selected 40,827 21,297 19,530 61,210 102,037 Households occupied 39,060 20,430 18,630 58,627 97,687 Households interviewed 37,909 19,729 18,180 57,532 95,441 Household response rate 97.1 96.6 97.6 98.1 97.7 Household interviews (short questionnaire) Households selected 36,941 19,272 17,669 55,384 92,325 Households occupied 35,278 18,461 16,817 52,961 88,239 Households interviewed 34,223 17,822 16,401 51,963 86,186 Household response rate1 97.0 96.5 97.5 98.1 97.7 Household interviews (long questionnaire) Households selected 3,886 2,025 1,861 5,826 9,712 Households occupied 3,782 1,969 1,813 5,666 9,448 Households interviewed 3,686 1,907 1,779 5,569 9,255 Household response rate1 97.5 96.9 98.1 98.3 98.0 Interviews with ever-married women Number of eligible women 4,104 2,086 2,018 6,497 10,601 Number of eligible women interviewed 3,830 1,929 1,901 6,193 10,023 Eligible women response rate2 93.3 92.5 94.2 95.3 94.5 1 Households interviewed/households occupied 2 Respondents interviewed/eligible respondents 1 In a few clusters, the number of households selected was slightly fewer than the stipulated 105 for various reasons. 2 Because there were only three ever-married women under age 15 (all of whom were 14), they were all made to be age 15. HOUSEHOLD POPULATION AND HOUSING CHARACTERISTICS 2 Aysha Sheraz and Zafar Zahir This chapter provides a summary of the socioeconomic characteristics of households and respondents surveyed, including age, sex, place of residence, and educational status. It also provides information on household facilities and household characteristics, such as source of drinking water, electricity, sanitation facilities, housing construction materials, possession of durable goods, and ownership of a homestead, land, and farm animals. Information was also collected on the type of treatment, if any, used to make the water safe for drinking. Information collected on the characteristics of the households and respondents is important in understanding and interpreting the findings of the survey and also provides indicators of the representativeness of the survey. The information is also useful in understanding and identifying the major factors that determine or influence the basic demographic indicators of the population. The 2006-07 Pakistan Demographic and Health Survey (PDHS) collected information from all usual residents of a selected household (the de jure population) and persons who had stayed in the selected household the night before the interview (the de facto population). Because the difference between these two populations is very small, and to maintain comparability with other DHS reports, all tables in this report refer to the de facto population unless otherwise specified. 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. As mentioned in Chapter 1, the PDHS used two types of Household Questionnaires: one for use in about 90 percent of households—the Short Household Questionnaire—and the other used in a 10-percent subsample—the Long Household Questionnaire. Data on the age, sex, and education distribution of household members is based on information from both types of questionnaire, i.e., from all households, whereas data on current school attendance, orphanhood, and housing characteristics are derived from the long questionnaire and thus are based on a smaller number of households. Nevertheless, these indicators are representative at national, urban-rural. and provincial levels as well. 2.1 HOUSEHOLD POPULATION BY AGE AND SEX Age and sex are important demographic variables and are the primary basis of demographic classification in vital statistics, censuses, and surveys. They are also very important variables in the study of mortality, fertility, and nuptiality. In general, a cross-classification with sex is useful for the effective analysis of all forms of data obtained in surveys. The distribution of the household population in the 2006-07 PDHS is shown in Table 2.1 by five-year age groups, according to urban-rural residence and sex. The total population counted in the survey was 688,937, with males slightly outnumbering females. Two-thirds of the population (67 percent) reside in rural areas. Of the one-third who live in urban areas, the proportion living in a major city slightly exceeds the proportion living in smaller urban areas. Household Population and Housing Characteristics | 11 Table 2.1 Household population by age, sex, and residence Percent distribution of the de facto household population in all households by five-year age groups, according to sex and residence, Pakistan 2006-07 Residence Total urban Major city Other urban Rural Total Age Male Female Total Male Female Total Male Female Total Male Female Total Male Female Total <5 11.8 11.8 11.8 11.4 11.4 11.4 12.3 12.3 12.3 14.5 14.0 14.2 13.6 13.3 13.4 5-9 12.5 12.5 12.5 11.3 12.0 11.7 14.1 13.2 13.6 15.8 14.6 15.2 14.7 13.9 14.3 10-14 12.7 12.4 12.5 12.1 12.0 12.1 13.5 12.8 13.1 13.5 12.7 13.1 13.2 12.6 12.9 15-19 12.5 12.9 12.7 12.5 12.9 12.7 12.5 12.9 12.7 11.3 11.6 11.4 11.7 12.0 11.9 20-24 10.7 11.2 10.9 11.5 11.7 11.6 9.7 10.5 10.1 8.2 9.4 8.8 9.0 10.0 9.5 25-29 8.2 8.5 8.3 8.8 8.7 8.7 7.3 8.2 7.7 6.7 7.8 7.3 7.2 8.1 7.6 30-34 5.8 6.1 5.9 6.1 6.2 6.1 5.4 6.0 5.7 5.1 5.9 5.5 5.4 5.9 5.7 35-39 5.5 5.8 5.6 5.7 5.9 5.8 5.3 5.7 5.5 4.9 5.4 5.2 5.1 5.6 5.3 40-44 4.8 4.7 4.7 5.0 4.9 5.0 4.5 4.3 4.4 4.1 4.1 4.1 4.4 4.3 4.3 45-49 4.1 4.1 4.1 4.3 4.2 4.3 3.8 4.0 3.9 3.6 3.6 3.6 3.8 3.8 3.8 50-54 3.1 3.0 3.1 3.3 3.1 3.2 3.0 2.8 2.9 2.9 2.8 2.8 3.0 2.9 2.9 55-59 2.3 2.1 2.2 2.2 2.1 2.2 2.3 2.2 2.2 2.2 2.2 2.2 2.2 2.2 2.2 60-64 2.2 1.8 2.0 2.2 1.7 1.9 2.2 1.9 2.0 2.3 2.0 2.2 2.3 1.9 2.1 65-69 1.3 1.1 1.2 1.2 1.1 1.1 1.4 1.2 1.3 1.6 1.4 1.5 1.5 1.3 1.4 70-74 1.2 0.9 1.1 1.2 1.0 1.1 1.3 0.9 1.1 1.5 1.1 1.3 1.4 1.0 1.2 75-79 0.5 0.4 0.5 0.5 0.4 0.5 0.6 0.4 0.5 0.7 0.5 0.6 0.6 0.5 0.6 80 + 0.8 0.7 0.7 0.7 0.7 0.7 0.9 0.7 0.8 1.1 0.8 1.0 1.0 0.8 0.9 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Number 117,379 113,225 230,607 66,510 63,492 130,004 50,869 49,733 100,602 230,859 227,464 458,331 348,238 340,689 688,937 Note: Total includes 10 persons whose sex was not stated. The age structure of the household population 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 under 15 years of age. It is evident that the pyramid is broad-based but slightly narrower at the lowest base (age group 0-4 years), a pattern that typically describes a high fertility but with a recent declining trend. Children under 15 years of age account for 41 percent of the population in Pakistan, a feature of populations with high fertility levels. Fifty-five percent of the population are in the age group 15-64 years and 4 percent are over 65. Figure 2.1 Population Pyramid 80+ 75-79 70-74 65-69 60-64 55-59 50-54 45-49 40-44 35-39 30-34 25-29 20-24 15-19 10-14 5-9 0-4 0246810 0 2 4 6 8 10 PDHS 2006-07 Male Percent Female Age 12 | Household Population and Housing Characteristics Table 2.2 indicates that more than half of the population in Pakistan live in Punjab province (58 percent), followed by Sindh (23 percent), North West Frontier Province (NWFP) (14 percent), and Balochistan (4 percent). The age structure of the four provinces indicates that Punjab province has the lowest proportion of children compared with the other three provinces (Table 2.2). For example, the proportion of the population reported to be under age 15 varies from 39 percent in Punjab to 46 percent in Balochistan. Table 2.2 Household population by age, sex, and province Percent distribution of the de facto household population in all households by five-year age groups, according to sex and province, Pakistan 2006-07 Province Punjab Sindh NWFP Balochistan Total Age Male Female Total Male Female Total Male Female Total Male Female Total Male Female Total <5 13.0 12.6 12.8 14.1 14.3 14.2 14.8 13.8 14.3 14.5 15.0 14.7 13.6 13.3 13.4 5-9 13.9 13.1 13.5 15.2 14.8 15.0 15.9 14.7 15.3 17.9 17.7 17.8 14.7 13.9 14.3 10-14 13.0 12.4 12.7 13.0 12.4 12.7 14.5 13.6 14.0 13.6 12.8 13.2 13.2 12.6 12.9 15-19 11.7 12.2 12.0 11.4 11.5 11.4 12.6 12.5 12.5 10.7 10.7 10.7 11.7 12.0 11.9 20-24 9.1 10.1 9.6 9.4 10.3 9.8 8.6 9.5 9.0 8.3 9.1 8.7 9.0 10.0 9.5 25-29 7.1 8.0 7.6 7.9 8.2 8.1 6.2 7.6 6.9 7.5 9.0 8.2 7.2 8.1 7.6 30-34 5.4 6.0 5.7 5.7 6.0 5.9 4.8 5.7 5.2 5.6 5.8 5.7 5.4 5.9 5.7 35-39 5.2 5.8 5.5 5.3 5.3 5.3 4.1 5.2 4.7 5.1 5.0 5.1 5.1 5.6 5.3 40-44 4.6 4.5 4.6 4.2 3.9 4.0 3.9 4.1 4.0 3.7 3.7 3.7 4.4 4.3 4.3 45-49 4.0 3.9 3.9 3.5 3.7 3.6 3.1 3.5 3.3 3.6 3.6 3.6 3.8 3.8 3.8 50-54 3.1 2.9 3.0 2.8 2.8 2.8 2.9 2.8 2.9 2.6 2.3 2.5 3.0 2.9 2.9 55-59 2.3 2.3 2.3 2.1 2.1 2.1 2.2 2.1 2.1 2.1 1.6 1.9 2.2 2.2 2.2 60-64 2.5 2.1 2.3 2.0 1.8 1.9 2.2 1.8 2.0 1.6 1.4 1.5 2.3 1.9 2.1 65-69 1.7 1.5 1.6 1.2 1.1 1.1 1.4 1.3 1.4 1.2 0.7 1.0 1.5 1.3 1.4 70-74 1.6 1.2 1.4 1.1 0.9 1.0 1.2 0.9 1.1 0.8 0.6 0.7 1.4 1.0 1.2 75-79 0.7 0.5 0.6 0.5 0.4 0.4 0.6 0.5 0.5 0.4 0.3 0.4 0.6 0.5 0.6 80 + 1.2 0.9 1.1 0.6 0.5 0.6 1.0 0.6 0.8 0.7 0.6 0.7 1.0 0.8 0.9 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Number 201,669 198,760 400,435 82,612 78,328 160,944 47,945 48,658 96,603 16,012 14,943 30,955 348,238 340,689 688,937 Note: Total includes 10 persons whose sex was not stated. The results indicate an overall sex ratio of 102 males per 100 females, an implausibly high ratio that is most probably due to a tendency to underreport women. The sex ratio is higher in urban areas (104 males per 100 females) than in rural areas (101 males per 100 females). As shown in Table 2.3, the sex ratio varies by age group, being over 100 in the younger and older age groups and under 100 at ages 20-39. The lower ratios in the prime working ages may be due in part to men leaving the country to work overseas or to differential age misreporting by sex. Table 2.3 Sex ratios by age Sex ratios for the house- hold population by five- year age groups, Pakistan 2006-07 Age group Sex ratio1 0-4 105 5-9 108 10-14 107 15-19 100 20-24 93 25-29 91 30-34 93 35-39 94 40-44 105 45-49 102 50-54 106 55-59 104 60-64 119 65 and over 128 Total 102 1 Sex ratio = (males/females)*100 Despite the implausibly high sex ratio in the PDHS, it is lower than that from previous surveys (Table 2.4). Comparison of PDHS results with those from previous surveys and the census show that the reported sex ratio varies from 108 males per 100 females in 1990-91 and 1998 to the current ratio of 102 males per 100 females (Table 2.4). The narrowing of the male- female ratio could be explained by the fact that during the 2006-07 PDHS, the enumeration of household members, especially females, was done in a careful and thorough manner, thus leading to a more plausible sex ratio. Table 2.4 also shows that about half of the total female population falls into the reproductive age group (15-49 years). The fact that this segment has been increasing over the last two decades has an impact, because they are in the childbearing years and hence contribute to overall population growth. Household Population and Housing Characteristics | 13 Table 2.4 Trends in age distribution of household population Percent distribution of household population by five-year age groups, overall sex ratio, and percent of women age 15-49, Pakistan 1990-2007 Age group PDHS 1990-91 PFFPS 1996-97 Census 1998 PRHFPS 2000-01 SWRHFPS 2003 PDHS 2006-07 0-4 13.4 14.4 14.8 13.8 13.1 13.4 5-9 17.4 15.4 15.7 14.3 14.2 14.3 10-14 13.7 13.3 13.0 13.2 13.5 12.9 15-19 10.2 11.4 10.4 11.9 11.5 11.9 20-24 8.1 8.6 9.0 9.3 9.3 9.5 25-29 7.1 7.4 7.4 7.4 7.2 7.6 30-34 5.4 5.6 6.2 5.8 5.6 5.7 35-39 4.6 4.7 4.8 4.9 5.4 5.3 40-44 4.0 3.6 4.4 3.9 4.1 4.3 45-49 3.0 2.9 3.5 2.8 3.5 3.8 50-54 3.2 3.2 3.2 3.6 3.6 2.9 55-59 2.4 2.7 2.2 2.4 2.4 2.2 60-64 2.7 2.6 2.0 2.5 2.5 2.1 65 and over 5.0 4.3 3.5 4.2 4.3 4.1 Total 100.0 100.0 100.0 100.0 100.0 100.0 Sex ratio 108 107 108 103 106 102 Female (15-49) 42.6 44.0 46.2 46.4 47.4 49.7 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 2.2 HOUSEHOLD COMPOSITION In the 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. Changes at the household level, therefore, have repercussions at the aggregate level of a country as a whole. 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 2.5 shows the distribution of households in the survey by the 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 92 percent of households being headed by a male and only 9 percent being headed by a female. The proportion of female-headed households is about the same in rural (9 percent) and urban areas (8 percent). This could be attributed to out-migration of the male population from rural areas to urban areas or even overseas for employment purposes. Female headship of households is of concern to policymakers, particularly those dealing with poverty issues, because it is usually financially difficult for a woman to manage a household alone (Osaki, 1991). The proportion of female-headed households has not changed much over the last two decades (data not shown). 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 2006-07 PDHS data show that the average household size observed in the survey is 7.2 persons (Table 2.5). The household size is slightly smaller in urban areas than in rural areas (7.0 persons versus 7.3 persons, respectively). It is interesting to note that the mean household size in major cities is smaller than that in other urban areas (6.9 persons compared with 7.3 persons, respectively). 14 | Household Population and Housing Characteristics The mean household size in Pakistan has increased from 6.9 in 2003 (NIPS, 2007) to the current size of 7.2 persons. The upward trend in household size could be due to two factors: first, a more complete enumeration of household population in the 2006-07 PDHS and, second, an increasing imbalance between the growth of housing stock and the growth of the population (Zahir, 2003). Table 2.5 Household composition Percent distribution of all households by sex of head of household and household size, and mean size of household, according to residence, Pakistan 2006-07 Residence Characteristic Total urban Major city Other urban Rural Total Household headship Male 91.8 91.2 92.6 91.3 91.5 Female 8.2 8.8 7.4 8.7 8.5 Total 100.0 100.0 100.0 100.0 100.0 Number of usual members 1 1.3 1.3 1.3 1.1 1.2 2 3.7 4.0 3.2 4.0 3.9 3 6.1 6.3 5.8 6.3 6.2 4 9.9 10.4 9.1 9.6 9.7 5 13.6 14.5 12.4 12.1 12.6 6 15.5 16.3 14.6 13.8 14.4 7 13.8 13.4 14.5 13.2 13.4 8 10.8 10.2 11.5 11.2 11.1 9+ 25.3 23.6 27.7 28.6 27.5 Total 100.0 100.0 100.0 100.0 100.0 Mean size of households 7.0 6.9 7.3 7.3 7.2 Number of households 32,547 18,779 13,767 62,894 95,441 Note: Table is based on de jure household members, i.e., usual residents. Detailed information on children’s orphanhood is presented in Table 2.6. In Pakistan, the majority of children under age 18 (95 percent) have both parents alive, 3 percent have only their mother alive, and 2 percent have only their father alive. Overall, 4 percent of children under 18 have one or both parents dead. Differences in children’s orphanhood by background characteristics are quite small, except for age. The proportion with one or both parents dead increases steadily with age, ranging from 1 percent among children 0-4 years old to 10 percent among those age 15-17. Household Population and Housing Characteristics | 15 Table 2.6 Children's orphanhood Percent distribution of de jure children under age 18, by survival status of parents, and the percentage of children with one or both parents dead, according to background characteristics, Pakistan 2006-07 Background characteristic Both alive Mother alive, father dead Father alive, mother dead Both dead Missing information on father/ mother Total Percentage with one or both parents dead Number of children Age 0-4 97.7 0.5 0.5 0.0 1.2 100.0 1.1 8,760 <2 97.8 0.3 0.4 0.0 1.5 100.0 0.7 3,443 2-4 97.6 0.6 0.6 0.1 1.1 100.0 1.3 5,317 5-9 96.4 1.7 1.3 0.1 0.5 100.0 3.1 9,409 10-14 93.2 3.7 2.3 0.4 0.5 100.0 6.3 8,555 15-17 89.0 5.9 3.5 0.4 1.2 100.0 9.9 4,766 Sex Male 94.4 2.8 1.7 0.2 0.9 100.0 4.6 16,146 Female 95.1 2.3 1.7 0.2 0.7 100.0 4.2 15,341 Residence Total urban 94.4 2.8 1.7 0.2 0.9 100.0 4.7 9,847 Major city 95.5 2.3 1.3 0.2 0.7 100.0 3.8 5,207 Other urban 93.2 3.4 2.1 0.2 1.1 100.0 5.7 4,640 Rural 94.9 2.4 1.7 0.2 0.7 100.0 4.3 21,643 Province Punjab 94.8 2.5 1.6 0.2 0.9 100.0 4.3 17,482 Sindh 94.3 2.7 2.2 0.2 0.7 100.0 5.0 7,695 NWFP 94.9 2.6 1.3 0.4 0.7 100.0 4.3 4,792 Balochistan 95.8 2.0 1.1 0.1 0.9 100.0 3.3 1,521 Wealth quintile Lowest 94.8 2.7 1.8 0.2 0.5 100.0 4.7 7,049 Second 94.1 2.7 1.9 0.4 1.0 100.0 4.9 6,642 Middle 94.0 2.6 2.2 0.0 1.2 100.0 4.8 6,428 Fourth 95.3 2.6 1.3 0.1 0.6 100.0 4.0 6,039 Highest 95.8 2.0 1.2 0.2 0.7 100.0 3.5 5,331 Total <15 95.8 1.9 1.4 0.2 0.7 100.0 3.5 26,724 Total <18 94.8 2.6 1.7 0.2 0.8 100.0 4.4 31,490 Note: Table is based on de jure members, i.e., usual residents. Total includes 2 children with sex missing. 2.3 EDUCATION OF THE HOUSEHOLD POPULATION Studies show that education is one of the major social factors that influence a person’s behaviour and attitude. In general, the higher the level of education of a woman, the more knowledgeable she is about the use of health facilities, family planning methods, and the health of her children. In Pakistan, there are several levels of education. Children generally enter primary school at age 5; this level comprises Classes 1 through 5. Middle school consists of Classes 6 through 8, secondary school is Classes 9 and 10, and higher secondary is Classes 11 and 12. Class 13 and above is college and university level education. 2.3.1 Educational Attainment of Household Population Tables 2.7.1 and 2.7.2 show the percent distribution of the de facto female and male household population age five and over by highest level of education attended, according to background characteristics.1 Survey results show that more than half of women and about one-third of men in Pakistan have no education. Overall, females are less educated than males. Twenty-seven percent of females and 33 percent of males have attended primary school only, 8 percent of females and 13 percent of males have attended middle school only, and 7 percent of females and 14 percent of males have attended secondary education only. Overall, 6 percent of females and 10 percent of males 1 A similar table for both sexes combined appears as Table A.1 in the appendix. 16 | Household Population and Housing Characteristics have attended higher than secondary education. The gender differentials in education could be attributed to cultural norms and the social constraints faced by women in Pakistan. When investigating the changes in educational attainment by successive age groups, survey results show that there has been a marked improvement in the educational attainment of both women and men. For example, the proportion of women with no education has declined significantly from 94 percent among women age 65 and over to 30 percent among women age 10-14. A similar pattern is noticeable among men, with the proportion of men with no education declining from 67 percent among those age 65 and over to just 17 percent among those age 10-14. Table 2.7.1 Educational attainment of the female household population Percent distribution of the de facto female household population age five and over by highest level of schooling attended and median years completed, according to background characteristics, Pakistan 2006-07 Education1 Median years completed Background characteristic No education Primary Middle Secondary Higher secondary+ Missing Total Number Age 5-9 35.8 63.9 0.0 0.0 0.0 0.3 100.0 47,494 0.0 10-14 29.5 52.3 16.6 1.5 0.0 0.1 100.0 42,850 2.2 15-19 36.6 20.7 17.1 17.0 8.5 0.1 100.0 40,912 4.4 20-24 42.5 16.5 9.7 14.1 17.1 0.2 100.0 34,037 4.2 25-29 52.8 14.5 7.5 11.9 13.1 0.2 100.0 27,428 0.0 30-34 63.4 12.5 5.6 8.7 9.6 0.2 100.0 20,226 0.0 35-39 69.8 12.4 4.6 6.8 6.3 0.1 100.0 18,914 0.0 40-44 74.0 10.8 4.7 5.6 4.8 0.1 100.0 14,563 0.0 45-49 78.8 9.7 3.4 4.5 3.6 0.1 100.0 12,814 0.0 50-54 82.0 8.1 3.1 3.6 3.0 0.3 100.0 9,723 0.0 55-59 87.0 6.0 2.4 2.5 1.9 0.2 100.0 7,408 0.0 60-64 90.5 4.3 2.0 1.4 1.5 0.3 100.0 6,611 0.0 65+ 94.2 2.9 1.1 0.9 0.5 0.4 100.0 12,404 0.0 Residence Total urban 32.8 28.7 11.9 13.2 13.2 0.2 100.0 99,877 3.3 Major city 28.0 27.2 13.0 15.3 16.3 0.2 100.0 56,276 4.4 Other urban 39.0 30.6 10.6 10.4 9.3 0.2 100.0 43,601 1.2 Rural 61.3 26.4 5.8 3.9 2.3 0.2 100.0 195,622 0.0 Province Punjab 46.0 30.2 9.1 8.1 6.5 0.2 100.0 173,732 0.0 Sindh 56.4 22.7 6.5 6.8 7.3 0.2 100.0 67,107 0.0 NWFP 61.9 24.5 6.2 4.1 3.0 0.2 100.0 41,956 0.0 Balochistan 69.5 19.1 4.9 3.5 2.6 0.5 100.0 12,704 0.0 Wealth quintile2 Lowest 83.2 15.2 0.9 0.2 0.1 0.3 100.0 8,450 0.0 Second 70.2 24.9 3.0 1.1 0.5 0.3 100.0 9,831 0.0 Middle 55.7 32.2 7.1 3.6 1.2 0.2 100.0 9,149 0.0 Fourth 38.7 34.4 12.3 9.3 5.1 0.1 100.0 8,337 1.1 Highest 21.8 28.1 13.8 17.6 18.6 0.2 100.0 8,055 5.0 Total 51.6 27.2 7.9 7.0 6.0 0.2 100.0 295,499 0.0 1 Primary = Class 1-5; middle = Class 6-8; secondary = Class 9-10; higher = Class 11 or more 2 Data refer only to individuals in households interviewed with the Long Household Questionnaire. As expected, the proportion of respondents with no education is much higher among the rural than the urban population. For example, 61 percent of females in rural areas have no education compared with only 33 percent of females in urban areas. Among men, the proportion with no education varies from 36 percent of those in rural areas to 20 percent of those in urban areas. The urban-rural difference in educational attainment is undoubtedly due to a lack of education facilities or their inaccessibility in rural areas. Regarding provincial variation, the proportion of women and men with no education is highest in Balochistan (70 and 46 percent, respectively) and lowest in Punjab (46 and 28 percent, respectively). Educational attainment is strongly associated with wealth; the proportion of both Household Population and Housing Characteristics | 17 women and men with no education is highest among those in the lowest quintiles and decreases steadily with increasing wealth. Eighty-three percent of women in the lowest wealth quintile have no education compared with only 22 percent in the highest quintile. Similarly, 58 percent of men in the lowest quintile have no education compared with 10 percent in the highest quintile. The proportion of women and men with no education has decreased significantly since the 1990-91 PDHS, while the proportions who have attended each level of education have increased. Table 2.7.2 Educational attainment of the male household population Percent distribution of the de facto male household population age five and over by highest level of schooling attended and median years completed, according to background characteristics, Pakistan 2006-07 Education1 Median years completed Background characteristic No education Primary Middle Secondary Higher than secondary Missing Total Number Age 5-9 27.9 71.7 0.1 0.0 0.0 0.3 100.0 51,098 0.0 10-14 16.8 62.3 19.3 1.4 0.1 0.1 100.0 45,995 2.9 15-19 20.0 21.8 26.6 23.5 7.9 0.1 100.0 40,815 6.3 20-24 21.2 16.9 17.8 24.5 19.4 0.2 100.0 31,513 7.4 25-29 24.5 15.2 15.6 24.6 19.9 0.3 100.0 25,008 7.5 30-34 30.1 14.3 13.2 21.9 20.3 0.3 100.0 18,703 7.1 35-39 37.1 15.2 11.4 18.0 18.0 0.3 100.0 17,712 4.8 40-44 41.6 15.0 11.7 16.9 14.6 0.2 100.0 15,230 4.4 45-49 43.3 15.0 10.9 17.8 12.6 0.3 100.0 13,069 4.2 50-54 47.3 14.8 9.7 15.6 12.3 0.4 100.0 10,303 2.8 55-59 50.2 16.1 9.2 13.3 11.0 0.3 100.0 7,696 0.0 60-64 56.5 15.4 8.0 12.2 7.4 0.4 100.0 7,894 0.0 65+ 67.4 13.3 6.6 7.5 4.6 0.5 100.0 15,834 0.0 Residence Total urban 20.2 30.5 14.7 17.4 17.0 0.2 100.0 103,543 4.9 Major city 18.9 28.5 14.8 18.4 19.2 0.2 100.0 58,956 5.7 Other urban 22.0 33.2 14.6 16.0 14.0 0.3 100.0 44,587 4.5 Rural 35.5 34.2 12.8 11.7 5.6 0.2 100.0 197,449 1.4 Province Punjab 27.8 34.1 14.7 14.7 8.4 0.2 100.0 175,516 3.5 Sindh 34.1 31.3 9.9 11.3 12.9 0.4 100.0 70,946 2.3 NWFP 28.9 33.1 15.0 14.1 8.7 0.2 100.0 40,833 2.7 Balochistan 45.7 25.0 10.0 10.3 8.6 0.4 100.0 13,697 0.0 Wealth quintile2 Lowest 57.5 30.6 5.6 4.5 1.4 0.4 100.0 9,018 0.0 Second 40.0 36.2 11.4 8.6 3.3 0.5 100.0 9,970 0.1 Middle 30.0 37.8 13.8 12.8 5.4 0.3 100.0 9,084 2.4 Fourth 20.1 35.8 16.3 17.9 9.5 0.4 100.0 8,522 4.4 Highest 10.2 26.6 15.9 22.9 24.3 0.2 100.0 8,034 7.7 Total 30.3 32.9 13.4 13.6 9.5 0.2 100.0 300,992 2.9 1 Primary = Class 1-5; middle = Class 6-8; secondary = Class 9-10; higher = Class 11 or more 2 Data refer only to individuals in households interviewed with the Long Household Questionnaire. 2.3.2 School Attendance Ratios Data on net attendance ratios (NARs) and gross attendance ratios (GARs) for the de facto household population by school level and sex, according to residence, province, and wealth index, are shown in Table 2.8. The NAR indicates participation in primary schooling for the population age 5-9 and in middle/secondary school for the population age 10-14. The GAR measures participation at each level of schooling among those of any age. The GAR is nearly 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.2 A NAR of 100 percent would indicate that all those in the official age range for the level 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. 2 Students who are over-age for a given level of schooling may have started school over-age, may have repeated one or more grades in school, or may have dropped out of school and later returned. 18 | Household Population and Housing Characteristics Table 2.8 School attendance ratios Net attendance ratios (NAR) and gross attendance ratios (GAR) for the de facto household population by sex and level of schooling; and the gender parity index (GPI), according to background characteristics, Pakistan 2006-07 Net attendance ratio1 Gross attendance ratio2 Background characteristic Male Female Total Gender Parity Index3 Male Female Total Gender Parity Index3 PRIMARY SCHOOL Residence Total urban 78.4 76.4 77.4 0.97 114.4 105.1 109.8 0.92 Major city 81.9 78.7 80.3 0.96 118.0 106.8 112.4 0.90 Other urban 74.7 73.9 74.3 0.99 110.7 103.3 107.1 0.93 Rural 66.4 56.3 61.6 0.85 103.2 83.2 93.7 0.81 Province Punjab 76.5 73.2 75.0 0.96 112.8 102.8 108.1 0.91 Sindh 58.7 49.7 54.4 0.85 87.9 69.3 79.0 0.79 NWFP 72.0 53.0 62.3 0.74 121.5 82.9 101.7 0.68 Balochistan 46.7 37.0 42.2 0.79 86.5 73.7 80.6 0.85 Wealth quintile Lowest 49.2 32.2 41.5 0.65 76.8 49.9 64.6 0.65 Second 64.5 53.3 58.8 0.83 113.4 79.7 96.2 0.70 Middle 75.3 71.6 73.5 0.95 111.8 110.4 111.1 0.99 Fourth 84.4 81.1 82.9 0.96 125.9 115.1 120.8 0.91 Highest 87.7 87.8 87.8 1.00 117.5 109.4 113.5 0.93 Total 69.8 62.2 66.2 0.89 106.3 89.7 98.4 0.84 MIDDLE/SECONDARY SCHOOL Residence Total urban 35.9 40.2 37.9 1.12 62.2 68.3 65.2 1.10 Major city 38.4 43.6 40.9 1.13 65.1 70.6 67.8 1.09 Other urban 32.9 36.0 34.4 1.10 58.9 65.5 62.0 1.11 Rural 25.9 18.0 22.1 0.70 53.3 33.0 43.4 0.62 Province Punjab 31.9 30.6 31.2 0.96 57.4 53.3 55.5 0.93 Sindh 24.9 20.3 22.7 0.82 46.7 33.5 40.2 0.72 NWFP 28.5 17.4 22.9 0.61 67.6 32.7 50.1 0.48 Balochistan 19.4 12.6 16.1 0.65 54.1 32.8 43.8 0.60 Wealth quintile Lowest 12.3 4.9 8.7 0.40 25.6 7.7 16.9 0.30 Second 19.4 9.6 14.7 0.50 46.1 19.3 33.0 0.42 Middle 30.3 22.5 26.5 0.74 58.7 44.6 51.8 0.76 Fourth 37.2 40.3 38.7 1.08 70.1 74.7 72.3 1.07 Highest 50.3 54.4 52.3 1.08 86.0 84.4 85.2 0.98 Total 29.2 25.3 27.3 0.87 56.3 44.5 50.6 0.79 1 The NAR for primary school is the percentage of the primary-school-age (5-9 years) population that is attending primary school. The NAR for middle/secondary school is the percentage of the middle/secondary-school-age (10-14 years) population that is attending secondary school. By definition the NAR cannot exceed 100 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 middle/secondary school is the total number of middle/secondary school students, expressed as a percentage of the official middle/secondary-school-age population. If there are significant numbers of over-age and under-age students at a given level of schooling, the GAR can exceed 100 percent. 3 The Gender Parity Index for primary school is the ratio of the primary school NAR (GAR) for females to the NAR (GAR) for males. The Gender Parity Index for middle/secondary school is the ratio of the middle/secondary school NAR (GAR) for females to the NAR (GAR) for males. Sixty-six percent of primary-school-age children are currently attending primary school. At the same time, only 27 percent of middle/secondary-school-age youths are attending that level. The NAR is higher among males than among females at both primary and middle/secondary levels. Attendance ratios are much lower in rural than urban areas and are the lowest in Balochistan and highest in Punjab. Household Population and Housing Characteristics | 19 The GAR is higher among males than females—106 and 90, respectively, at the primary- school level and 56 and 45, respectively, at the secondary-school level—indicating higher attendance among males than among females. Although the overall GAR at the primary-school level is 98, there are significant levels of over-age and/or under-age participation in the urban areas (110) and also in Punjab (108) and NWFP (102). There is a strong relationship between household economic status and schooling that can be seen at both the primary and middle/secondary levels. For example, the primary- school NAR increases from 42 percent among the student-age population from poorer households (lowest wealth quintile) to 88 percent among those from richer households (highest wealth quintile). Similarly, the middle/secondary school NAR rises from 9 percent of those in the lowest wealth quintile to 52 percent among those in the highest wealth quintile. The Gender Parity Index (GPI) represents the ratio of the GAR for females to the GAR for males. It is presented at both the primary and middle/secondary levels and offers a summary measure of gender differences in school attendance rates. A GPI less than one indicates that a smaller proportion of females than males attends school. In Pakistan, the GPI is less than one (0.8) for both primary and middle/secondary school attendance. There are marked differences in the GPI by place of residence and by province. The primary and middle/secondary school GPI is lower in rural areas than in urban areas, with the difference being more pronounced for middle/secondary school attendance. Looking at provinces, the GPI for both primary and middle/secondary education is highest in Punjab and lowest in NWFP. The age-specific attendance rates for the population age 5-24 years by sex are shown in Figure 2.2. These rates indicate participation in schooling at any level, from primary to higher levels of education. The minimum age for schooling in Pakistan is five. Nevertheless, only half of boys and about four in ten girls age five are attending school, indicating that a significant proportion of children that age in Pakistan have not entered the school system. It is possible that a substantial proportion of the children age five are not attending school because they turned five after the start of the school year and were thus too young to start in that year. Between ages 5 and 11 the proportion of both males and females attending school generally increases, and then it starts declining steadily thereafter. Overall, a higher proportion of males than females attends school for all ages. Figure 2.2 Age-Specific Attendance Rates of the De-Facto Population Age 5 to 24 Years 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 Age 0 20 40 60 80 100 Percent Male Female PDHS 2006-07 20 | Household Population and Housing Characteristics 2.4 HOUSING CHARACTERISTICS The physical characteristics and availability and accessibility of basic household facilities are important in assessing the general welfare and socioeconomic condition of the population. In the 2006-07 PDHS, respondents in the sub-sample in which the Long Household Questionnaire was administered were asked about household drinking water and household sanitation facilities that included questions on the source of drinking water, time taken to travel to the nearest source of water, the person who usually collects drinking water, water treatment before drinking, and questions on sanitation facilities. Table 2.9 presents information on household drinking water. The majority (93 percent) of households in Pakistan have access to an improved source of drinking water with access in urban areas slightly higher than in rural areas (95 and 92 percent, respectively). The most common source of improved drinking water in urban areas is piped water, with 66 percent of households having access to this source, most commonly with a pipe directly into the house or plot. On the other hand, only 24 percent of rural households have access to piped water. The major source of improved drinking water in rural areas is a tubewell, borehole, or hand pump (62 percent). Table 2.9 Household drinking water Percent distribution of households and de jure population by source and time to collect drinking water; and percentage of households and the de jure population by treatment of drinking water, according to residence, Pakistan 2006-07 Households Population Characteristic Total urban Major city Other urban Rural Total Total urban Major city Other urban Rural Total Source of drinking water Improved source1 94.5 92.8 96.9 91.9 92.8 94.0 92.1 96.4 91.9 92.6 Piped into dwelling/yard/plot (piped) 62.3 77.8 41.6 22.0 35.8 61.7 77.9 41.3 23.2 36.3 Public tap/standpipe (piped) 3.6 3.2 4.2 1.8 2.4 3.6 3.2 4.2 1.6 2.3 Tubewell/borehole/hand pump 25.4 8.3 48.4 62.1 49.6 25.9 8.3 48.1 61.0 49.1 Protected dug well 1.3 0.6 2.3 5.0 3.7 1.4 0.7 2.3 5.0 3.8 Protected spring/karez 0.0 0.0 0.1 0.6 0.4 0.1 0.0 0.1 0.8 0.5 Rainwater 0.1 0.0 0.1 0.3 0.2 0.1 0.0 0.1 0.3 0.2 Bottled water 1.7 2.8 0.3 0.0 0.6 1.2 2.1 0.2 0.0 0.4 Non-improved source 4.0 5.4 2.1 7.1 6.1 4.7 6.3 2.6 7.2 6.3 Unprotected dug well 0.0 0.0 0.1 1.8 1.2 0.0 0.0 0.1 1.7 1.1 Unprotected spring 0.0 0.0 0.0 1.7 1.1 0.0 0.0 0.0 1.6 1.1 Tanker truck/cart with tank 2.7 3.7 1.5 0.6 1.3 3.2 4.2 1.9 0.6 1.5 Surface water 1.2 1.8 0.5 3.1 2.5 1.4 2.1 0.6 3.3 2.7 Other 1.3 1.5 0.9 1.0 1.1 1.1 1.2 0.8 0.9 0.9 Missing 0.2 0.3 0.1 0.0 0.1 0.3 0.3 0.2 0.0 0.1 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Time to obtain drinking water (round trip) Water on premises 89.2 89.1 89.2 78.0 81.8 88.9 88.4 89.6 77.9 81.6 Less than 30 minutes 5.6 5.4 5.8 11.4 9.4 5.4 5.6 5.2 11.1 9.2 30 minutes or longer 3.5 3.7 3.2 9.2 7.3 3.7 3.8 3.5 9.4 7.4 Don't know/missing 1.7 1.7 1.7 1.4 1.5 2.0 2.2 1.7 1.7 1.8 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Water treatment2 Boiled 17.9 27.9 4.6 1.2 6.9 16.0 25.0 4.6 1.3 6.2 Bleach/chlorine 1.3 1.9 0.5 0.1 0.5 1.5 2.1 0.6 0.2 0.6 Strained through cloth 3.7 5.2 1.8 1.1 2.0 3.7 5.2 1.7 1.1 2.0 Ceramic, sand or other filter 3.3 5.0 1.2 0.3 1.3 3.1 4.7 1.1 0.3 1.3 Solar disinfection 0.0 0.0 0.1 0.0 0.0 0.1 0.0 0.1 0.0 0.0 Let it stand and settle 1.2 1.7 0.5 0.3 0.6 1.1 1.6 0.5 0.3 0.6 Other 0.1 0.2 0.0 0.1 0.1 0.1 0.2 0.0 0.1 0.1 No treatment 74.8 61.8 92.3 96.9 89.4 76.8 64.5 92.2 96.8 90.0 Percentage using an appropriate treatment method3 24.5 37.4 7.4 2.7 10.1 22.6 34.6 7.4 2.8 9.5 Number 3,159 1,808 1,350 6,096 9,255 22,389 12,485 9,904 43,757 66,145 1 Households using bottled water for drinking are classified as using an improved source. 2 Respondents may report multiple treatment methods so the sum of treatment may exceed 100 percent. 3 Appropriate water treatment methods include boiling, bleaching, straining, filtering, and solar disinfecting. Household Population and Housing Characteristics | 21 More than eight in ten households (82 percent) report having water on their premises. Households not having access on their premises were asked for the time taken to fetch water. About one-tenth of all households take less than 30 minutes to fetch drinking water, while 7 percent take 30 minutes or longer to do so. In the survey, household respondents were asked whether they treat water before drinking. An overwhelming majority of households (89 percent) do not treat drinking water. Urban households (25 percent) are much more likely than rural households (3 percent) to treat drinking water, mostly by boiling. Even in major cities, only 37 percent of the households treat their drinking water appropriately. Appendix Table A.2 presents information on household drinking water by province. Data show that availability of an improved source of drinking water is highest in Punjab (96 percent) and lowest in NWFP (83 percent). On the other hand, the practice of appropriate water treatment is highest in Sindh (22 percent) and lowest in NWFP and Balochistan (3 percent each). The sanitation situation of a household has direct implications on the hygienic and health status of household members. Absence of sanitary disposal of waste exposes people to risk of acquiring infections and other diseases. Table 2.10 presents information on household sanitation facilities by type of toilet/latrine. Three in ten Pakistani households do not have any toilet facility, a statistic that is considerably higher among rural households (43 percent) than urban households (4 percent). Overall, half of households use improved toilets that are not shared with other households. Urban households (78 percent) are more than twice as likely as rural households (36 percent) to have improved toilet facilities. In urban areas, a flush/pour flush to piped sewer system (60 percent) is the major type of improved toilet facility, while in rural areas a flush/pour flush to septic tank facility (16 percent) is the most common type of improved facility. The seriousness of the sanitary situation is evident from the fact that only 28 percent of households have a toilet that flushes into a piped sewer system. As expected, Balochistan has the highest proportion of households with no toilet facility at all (43 percent), while Punjab and Sindh have the lowest (29 percent each; see Appendix Table A.3). Table 2.10 Household sanitation facilities Percent distribution of households and de jure population by type of toilet/latrine facilities, according to residence, Pakistan 2006-07 Households Population Type of toilet/latrine facility Total urban Major city Other urban Rural Total Total urban Major city Other urban Rural Total Improved, not shared facility Flush/pour flush to piped sewer system 59.6 77.0 36.3 11.7 28.0 59.3 77.4 36.5 12.2 28.2 Flush/pour flush to septic tank 11.2 5.1 19.4 16.3 14.6 11.5 5.3 19.3 17.3 15.4 Flush/pour flush to pit latrine 5.7 3.6 8.4 6.0 5.9 6.1 3.9 8.8 6.6 6.4 Ventilated improved pit (VIP) latrine 0.3 0.0 0.7 0.8 0.7 0.4 0.0 0.9 0.8 0.7 Pit latrine with slab 1.0 1.1 0.8 1.0 1.0 1.1 1.3 0.9 1.1 1.1 Non-improved facility Any facility shared with other households 9.3 10.4 8.0 4.9 6.4 8.6 9.6 7.4 4.4 5.9 Flush/pour flush not to sewer/septic tank/pit latrine 2.2 0.8 4.1 2.6 2.5 2.5 0.7 4.8 2.8 2.7 Pit latrine without slab/open pit 0.8 0.1 1.7 3.7 2.7 0.8 0.1 1.7 4.0 2.9 Bucket 0.5 0.2 0.9 1.8 1.3 0.5 0.1 0.9 1.9 1.4 Hanging toilet/hanging latrine 5.3 0.3 11.9 7.4 6.7 5.2 0.3 11.3 7.1 6.5 No facility/bush/field 3.6 0.8 7.2 43.3 29.8 3.4 0.8 6.7 41.2 28.4 Other 0.0 0.0 0.0 0.2 0.1 0.0 0.0 0.0 0.2 0.1 Missing 0.7 0.7 0.6 0.3 0.4 0.7 0.5 0.8 0.2 0.4 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Number 3,159 1,808 1,350 6,096 9,255 22,389 12,485 9,904 43,757 66,145 22 | Household Population and Housing Characteristics Information on housing characteristics such as availability of electricity; type of material used in the floors, roof, and walls; number of rooms used for sleeping; type of fuel used for cooking; place for cooking; and type of fire/stove is shown in Table 2.11. About nine in ten households in Pakistan have electricity, with a strong difference by place of residence. Only 84 percent of households in rural areas have access to electricity compared with 98 percent of urban households. Half of Pakistani households have earth or sand floors and three in ten have cement floors. Rural households are more likely than urban households to have earth, sand, or mud floors, while urban households are more likely than rural households to have floors made with cement. Table 2.11 Housing characteristics Percent distribution of households and de jure population by housing characteristics and percentage using solid fuel for cooking, according to residence, Pakistan 2006-07 Households Population Housing characteristic Total urban Major city Other urban Rural Total Total urban Major city Other urban Rural Total Electricity Yes 98.3 99.6 96.7 84.4 89.2 98.5 99.7 97.0 85.2 89.7 No 1.5 0.3 3.2 15.5 10.7 1.4 0.2 2.9 14.7 10.2 Missing 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Flooring material Earth/sand/mud 13.0 4.2 24.9 67.9 49.2 13.6 4.3 25.3 68.1 49.6 Chips/terrazo 15.7 21.4 8.0 2.3 6.8 15.4 21.2 8.0 2.4 6.8 Ceramic tiles 2.0 2.6 1.1 0.7 1.1 1.8 2.5 1.0 0.6 1.0 Marble 5.7 7.6 3.2 0.7 2.4 5.7 7.4 3.7 0.7 2.4 Cement 49.5 53.4 44.2 19.4 29.6 49.2 54.0 43.1 19.3 29.4 Carpet 1.8 3.0 0.2 0.1 0.7 1.7 2.9 0.2 0.1 0.6 Bricks 11.9 7.1 18.2 8.4 9.6 12.2 7.4 18.3 8.2 9.6 Other/missing 0.4 0.6 0.3 0.5 0.5 0.4 0.5 0.3 0.6 0.6 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Main wall material Mud/stones 5.2 2.0 9.6 29.6 21.3 5.6 1.9 10.3 30.3 22.0 Bamboo/sticks/mud 2.0 0.5 3.9 11.1 8.0 2.1 0.7 3.8 11.0 8.0 Unbaked bricks/mud 2.7 1.2 4.6 6.9 5.5 2.7 1.2 4.5 7.0 5.5 Stone blocks 1.0 0.9 1.1 0.5 0.7 0.9 0.7 1.1 0.5 0.6 Baked bricks 18.7 9.2 31.3 22.2 21.0 19.3 9.4 31.8 22.2 21.2 Cement blocks/cement 70.0 85.4 49.3 28.8 42.9 69.0 85.4 48.2 28.1 41.9 Other/missing 0.5 0.8 0.2 0.9 0.7 0.5 0.7 0.3 1.0 0.8 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Main roof material Thatch/palm leaf 12.7 7.2 20.1 43.8 33.2 12.9 7.4 19.9 44.0 33.5 Iron sheets/asbestos 6.1 8.1 3.4 1.8 3.3 6.3 8.3 3.8 1.8 3.3 T-iron/wood/brick 30.8 17.7 48.5 40.8 37.4 31.2 18.0 47.9 40.7 37.5 Reinforced brick cement/ reinforced concrete cement 49.8 66.5 27.4 13.2 25.7 49.2 66.0 27.9 13.3 25.5 Other/missing 0.5 0.6 0.6 0.3 0.5 0.4 0.4 0.6 0.3 0.4 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Rooms used for sleeping One 31.6 31.9 31.2 38.1 35.9 24.5 24.9 24.0 29.7 27.9 Two 41.4 40.0 43.3 40.4 40.8 40.5 38.2 43.4 40.3 40.4 Three or more 25.9 26.6 25.0 20.8 22.6 34.1 35.5 32.3 29.4 31.0 Missing 1.0 1.5 0.4 0.7 0.8 1.0 1.5 0.4 0.7 0.8 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Cooking fuel Electricity 0.2 0.1 0.3 0.3 0.2 0.2 0.1 0.4 0.2 0.2 Cylinder gas 6.1 3.1 10.0 3.9 4.6 5.7 3.2 8.8 3.3 4.1 Natural gas 70.0 90.2 42.9 3.9 26.5 69.2 89.9 43.1 4.3 26.3 Biogas 1.0 0.4 1.7 1.9 1.6 1.2 0.5 2.1 2.0 1.7 Charcoal 0.1 0.0 0.3 0.6 0.4 0.1 0.0 0.2 0.6 0.4 Wood 18.8 4.2 38.4 67.5 50.9 19.5 4.2 38.7 69.0 52.2 Straw/shrubs/grass 0.9 0.5 1.5 6.5 4.6 1.0 0.7 1.4 5.9 4.3 Agricultural crop 0.4 0.0 0.9 5.5 3.7 0.3 0.0 0.8 5.4 3.7 Animal dung 2.0 0.8 3.5 9.5 6.9 2.4 1.0 4.2 9.1 6.9 No food cooked in household 0.4 0.4 0.3 0.2 0.2 0.1 0.1 0.1 0.0 0.0 Other/missing 0.2 0.2 0.3 0.2 0.2 0.2 0.2 0.2 0.2 0.2 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Percentage using solid fuel for cooking1 22.2 5.4 44.5 89.6 66.6 23.4 6.0 45.3 90.0 67.4 Number of households 3,159 1,808 1,350 6,096 9,255 22,389 12,485 9,904 43,757 66,145 1 Includes charcoal, wood, straw/shrubs/grass, agricultural crops, and animal dung Household Population and Housing Characteristics | 23 More than two in five households use cement blocks or cement for the construction of the main walls of the dwelling, much more so in urban areas (70 percent) than in rural areas (29 percent). Furthermore, one in five households uses either mud and stones or baked bricks for the main walls. Thirty-seven percent of Pakistani households use T-iron, wood, or brick as the main roofing material for their dwellings, while 33 percent use thatch or palm leaves and 26 percent use reinforced brick cement or reinforced concrete cement (RCC). The most commonly used material for con- struction of roofs in urban areas is reinforced brick cement or RCC, while in rural areas it is thatch or palm leaves. Data were also collected on the number of sleeping rooms per household. Forty-one percent of households have two rooms for sleeping, 36 percent have only one room, and 23 percent have three or more rooms for sleeping. There are no major variations in the number of rooms used for sleeping by urban-rural residence. Slightly over half of households (51 percent) use wood for cooking, while more than one in four (27 percent) use natural gas. Wood is the most common form of cooking fuel in rural areas (68 percent), while natural gas is the most common form of cooking in urban areas (70 percent). Sixty- seven percent of the households in Pakistan use solid fuel for cooking (e.g., charcoal, wood, straw/shrubs/grass, agricultural crops, or animal dung) that generates smoke that is unhealthy to breathe. Rural households are much more likely than urban households to use solid fuels for cooking (90 and 22 percent. respectively). Data on housing characteristics by province are shown in Appendix Table A.4. 2.5 HOUSEHOLD POSSESSIONS Information on ownership of durable goods and other possessions is presented in Table 2.12. In general, ownership of household effects, means of transportation, and agricultural land and farm animals is indicative of a household’s social and economic well-being. The survey results show that about one-third (32 percent) of all households have a radio, more than half (56 percent) have a television, 46 percent have a telephone, and 37 percent have a refrigerator. Furthermore, 60 percent of households own a sewing machine, 43 percent own a washing machine, and 39 percent own a water pump. In general, households in rural Pakistan are much less likely to possess consumer items like televisions, telephones, refrigerators, sewing and washing machines, or water pumps than urban households. In general, Pakistanis are not very likely to own a means of transport. Bicycles are the most common means of transport, with 41 percent of households owning a bicycle. Overall, about one-fifth (18 percent) of households own a motorcycle or scooter and 7 percent own a car, truck, or tractor. Urban households are much more likely than rural households to own a motorcycle, a scooter, or a car. A large majority of rural households, in contrast to urban households, own agricultural land (50 and 13 percent, respectively) or farm animals (71 and 17 percent, respectively). 24 | Household Population and Housing Characteristics Table 2.12 Household durable goods Percentage of households and de jure population possessing various household effects, means of transportation, agricultural land, and livestock/farm animals, according to residence, Pakistan 2006-07 Households Population Possession Total urban Major city Other urban Rural Total Total urban Major city Other urban Rural Total Radio 28.8 27.4 30.6 33.2 31.7 29.5 27.8 31.6 35.6 33.5 Television 80.5 87.5 71.1 42.9 55.7 80.8 87.1 72.8 45.4 57.3 Telephone 65.9 72.4 57.2 35.2 45.7 67.2 73.3 59.5 38.7 48.3 Refrigerator 61.7 71.7 48.3 23.7 36.7 62.0 72.1 49.3 25.6 37.9 Room cooler/air conditioner 27.7 29.9 24.7 7.6 14.5 27.3 29.3 24.6 8.4 14.8 Washing machine 71.8 80.8 59.9 27.2 42.5 72.9 81.8 61.8 29.7 44.3 Water pump 53.2 53.6 52.7 31.4 38.8 54.4 55.0 53.6 32.6 40.0 Bed 83.4 83.9 82.7 69.3 74.1 83.5 83.3 83.8 71.0 75.2 Chair 66.4 67.1 65.4 48.9 54.9 66.4 67.3 65.3 49.4 55.2 Cabinet 67.8 77.4 54.9 31.2 43.7 69.3 78.4 57.8 33.8 45.8 Clock 92.2 97.2 85.6 69.3 77.1 92.9 97.6 86.9 71.4 78.7 Sofa 50.0 60.7 35.8 17.5 28.6 50.2 60.8 36.8 19.1 29.6 Sewing machine 75.6 80.2 69.5 52.5 60.4 77.8 82.3 72.2 55.9 63.3 Camera 20.1 24.1 14.9 6.1 10.9 20.6 23.5 17.0 7.2 11.7 Personal computer 18.5 24.4 10.6 2.8 8.1 18.0 23.3 11.2 3.1 8.1 Watch 88.2 90.6 85.0 76.8 80.7 89.3 91.3 86.8 79.7 83.0 Bicycle 37.5 34.6 41.2 42.4 40.7 40.6 38.3 43.5 45.1 43.6 Motorcycle/scooter 28.4 34.3 20.5 13.3 18.4 30.0 35.9 22.6 16.1 20.8 Car/truck/tractor 10.2 13.4 5.8 4.8 6.7 10.5 13.4 6.9 6.2 7.7 Animal-drawn cart 3.3 1.9 5.3 13.2 9.8 3.7 2.0 5.8 15.4 11.4 Boat with a motor 0.2 0.3 0.1 0.2 0.2 0.3 0.3 0.2 0.2 0.2 Ownership of agricultural land 13.1 8.0 19.8 49.7 37.2 14.2 9.1 20.6 51.3 38.7 Ownership of farm animals1 16.6 7.0 29.5 71.2 52.6 19.2 8.6 32.6 74.8 56.0 Number 3,159 1,808 1,350 6,096 9,255 22,389 12,485 9,904 43,757 66,145 1 Buffalo, cows, bulls, camels, donkeys, mules, horses, goats, sheep, chickens 2.6 SOCIOECONOMIC STATUS INDEX One of the background characteristics used throughout this report is an index of socio- economic status. The index used here was recently developed and tested in a large number of countries in relation to inequalities in household income, use of health services, and health outcomes (Rutstein et al., 2000). It is an indicator of the level of wealth that is consistent with expenditure and income measures (Rutstein, 1999). The economic index was constructed using household asset data including ownership of a number of consumer items ranging from a television to a bicycle or car, as well as dwelling characteristics, such as source of drinking water, sanitation facilities, and type of material used for flooring. Each asset was assigned a weight (factor score) generated through principal components analysis, and the resulting asset scores were standardized in relation to a normal distribution with a mean of zero and standard deviation of one (Gwatkin et al., 2000). Each household was then assigned a score for each asset, and the scores were summed for each household; individuals were ranked according to the score of the household in which they resided. The sample was then divided into quintiles from one (lowest) to five (highest). A single asset index was developed for the whole sample; separate indices were not prepared for urban and rural populations. Household Population and Housing Characteristics | 25 Table 2.13 presents data on wealth quintiles by residence and provinces. Overall, by definition, equal proportions of the Pakistani population fall in each quintile (20 percent each). However, the distribution by wealth quintile varies significantly by urban-rural residence. Forty-six percent of the population in urban areas is in the highest wealth quintile in contrast to 7 percent of the rural population. On the other hand, 29 percent of the rural population fall in the lowest quintile compared with only 3 percent of the urban population. The wealth quintile distribution by province shows large variation, with a relatively higher percentage of the population in Sindh and Punjab provinces (the most urbanized provinces) in the higher wealth quintiles and a higher percentage of the population in Balochistan in the lower wealth quintiles. Interestingly, Sindh province has relatively high proportions of population in both the lowest and highest wealth quintiles, implying that the province has relatively fewer middle-class households. Table 2.13 Wealth quintiles Percent distribution of the de jure population by wealth quintiles, according to residence and region, Pakistan 2006-07 Wealth quintile Residence/region Lowest Second Middle Fourth Highest Total Number Residence Total urban 2.9 6.2 15.8 29.2 45.9 100.0 22,369 Major city 0.4 1.9 8.6 29.3 59.8 100.0 12,474 Other urban 6.1 11.6 24.8 29.0 28.4 100.0 9,895 Rural 28.7 27.0 22.2 15.3 6.7 100.0 43,718 Province Punjab 16.5 17.6 23.0 21.5 21.4 100.0 38,134 Sindh 29.0 15.6 12.3 19.7 23.3 100.0 15,697 NWFP 14.7 35.7 19.7 17.7 12.2 100.0 9,213 Balochistan 33.5 25.0 23.4 9.8 8.4 100.0 3,043 Total 20.0 20.0 20.0 20.0 20.0 100.0 66,088 2.7 AVAILABILITY OF SERVICES IN RURAL AREAS The 2006-07 PDHS used a Community Questionnaire that was administered in each of the 610 selected rural sample points. It included questions about the availability of various public services, such as schools, shops, transport, and health facilities. Because the data were provided by community informants and distances were not verified, the data should be viewed with some caution. Table 2.14 shows the percent distribution of rural households by distance to various services. There is a wide range in the distance of services from rural households. As might be expected, the vast majority of rural households are 10 or more kilometres from the district headquarters, ambulance services, ultrasound services for pregnant women, a functioning maternal and child health centre, and a hospital. Banks, rural health centres, and family welfare centres are also not likely to be close to rural households. In fact, the most available health-related personnel are dais (traditional birth attendants), dispensers/compounders of medicines, and hakims and homeopaths. A large majority of rural households are in communities in which primary schools are located; however, it is interesting that primary schools for boys are more likely to be in the community than primary schools for girls. 26 | Household Population and Housing Characteristics Table 2.14 Availability of services in rural areas Percent distribution of rural households by distance to selected services in their communities, Pakistan 2006-07 Number of kilometres to service Service In community1 1-4 km 5-9 km 10+ km Don’t know/ missing Total District headquarters 0.6 1.4 4.0 89.9 4.1 100.0 Medical store 25.4 23.2 18.6 29.1 3.7 100.0 General store or shop 65.4 7.3 8.2 15.6 3.5 100.0 Motorized public transport 63.2 14.5 6.3 11.4 4.5 100.0 Non-motorized public transport 70.2 8.9 3.7 7.8 9.4 100.0 Post office 31.7 22.7 14.3 27.8 3.5 100.0 Bank 12.2 18.0 23.0 41.8 4.9 100.0 Primary school for boys 88.5 7.0 1.2 0.8 2.6 100.0 Primary school for girls 78.2 8.5 5.2 5.6 2.6 100.0 Secondary school for boys 30.9 22.9 20.6 21.6 3.9 100.0 Secondary school for girls 21.1 20.0 21.2 32.8 5.0 100.0 Any ambulance service 8.1 8.4 16.7 60.3 6.4 100.0 Ultrasound services for pregnant women 8.4 9.4 16.2 60.5 5.5 100.0 Dai (traditional birth attendant) 60.5 14.2 8.9 11.5 4.9 100.0 Functioning basic health unit (BHU) 20.8 27.3 22.5 19.5 10.0 100.0 Rural health centre (RHC) 6.0 15.0 24.2 45.8 9.0 100.0 Government dispensary 14.4 18.6 23.5 31.9 11.7 100.0 Functioning maternal and child health (MCH) centre 5.2 9.6 17.4 56.8 10.9 100.0 Private doctor 18.1 20.6 21.3 33.9 6.2 100.0 Dispenser or compounder 54.7 15.6 9.8 13.1 6.8 100.0 Family welfare centre/source of family planning 18.7 14.0 18.5 41.0 7.9 100.0 Hakim or homeopath 39.6 14.1 14.1 27.0 5.2 100.0 Hospital 8.6 14.0 17.9 54.1 5.3 100.0 Note: Table is based on 62,894 rural households 1 Includes responses of “0” kilometres 2.8 REGISTRATION WITH THE NATIONAL DATABASE AND REGISTRATION AUTHORITY In March 2000, the Government of Pakistan established the National Database and Registration Authority (NADRA) to oversee the registration of the population. All children under 18 years are registered using the “Bay Form,” and adults age 18 years and older are issued a computerized national identity card (NIC). These documents are compulsory for obtaining any official document such as a passport or a driver’s license or for admission in schools or being hired in government jobs. In the 2006-07 PDHS, information was collected regarding the registration status of all household members. Results are shown in Table 2.15. Overall, three in ten children under age 18 have a Bay Form, while seven in ten adults have a NIC. This means that altogether four in ten Pakistanis do not have any form of registration. Females, rural residents, people living in NWFP and Balochistan, and those in the lower two wealth quintiles are less likely to be registered with NADRA when compared with other sub-groups. Differences in NADRA registration by sex are all due to a lower proportion of adult women with an identity card, because girls are as likely as boys to have a Bay Form. On the other hand, differences by urban-rural residence are almost entirely due to the differing proportions of children with Bay Forms; there are only minimal differences by residence in the proportion of adults with a NIC. Similarly, differences by province are largely in the registration of children with Bay Forms. Household Population and Housing Characteristics | 27 28 | Household Population and Housing Characteristics Table 2.15 Registration with NADRA Percentage of de jure household population who are registered with NADRA, according to back- ground characteristics, Pakistan 2006-07 Among those under age 18 Among those age 18 or over Among all ages Background characteristic Percentage with Bay Form Number Percentage with NIC Number Percentage with neither1 Number Sex Male 31.5 16,146 83.1 17,226 39.7 33,373 Female 31.2 15,341 63.7 17,430 48.1 32,771 Residence Total urban 38.8 9,847 75.5 12,542 37.1 22,389 Major city 44.6 5,207 76.7 7,278 33.0 12,485 Other urban 32.3 4,640 73.9 5,264 42.3 9,904 Rural 27.9 21,643 72.1 22,114 47.3 43,757 Province Punjab 39.8 17,482 74.7 20,686 38.1 38,168 Sindh 25.3 7,695 72.9 8,016 47.9 15,711 NWFP 15.7 4,792 67.7 4,429 57.4 9,221 Balochistan 13.3 1,521 73.8 1,525 54.6 3,046 Wealth quintile Lowest 20.2 7,049 66.4 6,184 56.4 13,233 Second 22.9 6,642 69.1 6,574 51.7 13,216 Middle 33.2 6,428 71.7 6,811 44.0 13,239 Fourth 38.7 6,039 75.2 7,198 38.1 13,237 Highest 45.8 5,331 82.1 7,890 29.3 13,221 Total 31.3 31,490 73.3 34,656 43.9 66,145 1 Excludes those who have a document appropriate for the other age group NADRA = National Database and Registration Authority (see text) NIC = National identicy card CHARACTERISTICS OF RESPONDENTS 3 Zahir Hussain and Zafar Iqbal Qamar This chapter provides a demographic and socioeconomic profile of ever-married women age 15-49 interviewed in the 2006-07 Pakistan Demographic and Health Survey (PDHS). Information on basic characteristics such as age, level of education, marital status, native language, and wealth status was collected. Literacy status was also examined, and detailed information was collected on employment status, occupation, and earnings. Such background information is important for better understanding the social and demographic findings presented in this report. Understanding how women’s education and employment are related to reproductive attitudes and behaviours can be helpful in promoting change, especially in patriarchal societies like Pakistan where the status of women is generally low. The slowing of the population growth is not only affected by the direct means of fertility management (family planning, age at marriage, duration of breastfeeding, abortion), but also indirectly by motivation to control fertility, which includes many factors. Central among these factors are reduced mortality, education (particularly of women), economic development (particularly poverty reduction), and the general status of women (Ministry of Population Welfare, 2002). 3.1 CHARACTERISTICS OF SURVEY RESPONDENTS Table 3.1 provides information on the background characteristics of the 10,023 ever-married women age 15-49 who were interviewed. This table is important in that it provides the background for interpreting findings presented later in the report. The proportion of ever-married women increases sharply from 6 percent in the 15-19 age group to 20 percent in the 25-29 age group, and falls steadily thereafter to 12 percent for the 45-49 age group. About six in ten (59 percent) women are under age 35. The majority of surveyed women (95 percent) are married, 3 percent are widowed, and 1 percent each are divorced or separated (Table 3.1). Place of residence is another characteristic that determines access to services and exposure to information pertaining to reproductive health and other aspects of life. Two-thirds (67 percent) of ever-married women age 15-49 in Pakistan reside in rural areas, while one-third (33 percent) reside in urban areas. About six in ten women live in Punjab province (58 percent) and one-quarter in Sindh province (24 percent), while the remaining reside in North-West Frontier Province (NWFP) (14 percent) and Balochistan (5 percent). Education is an important factor influencing an individual’s attitude and outlook on various aspects of life. A large majority of ever-married women in Pakistan (65 percent) have no education and only 6 percent have attained Class 11 or higher. Wealth and work status are important characteristics that shed light on the socioeconomic status of women in the society. Surveyed women are distributed almost equally among all five wealth quintiles. Looking at work status, it is important to note that six in ten ever-married women have never worked. One in four women in Pakistan is currently working. Characteristics of Respondents | 29 Table 3.1 Background characteristics of respondents Percent distribution of ever-married women age 15-49 by selected background characteristics, Pakistan 2006-07 Background characteristic Weighted percent Number of women Weighted Unweighted Age 15-19 5.7 569 578 20-24 15.0 1,499 1,560 25-29 20.0 2,006 2,010 30-34 17.8 1,786 1,716 35-39 16.5 1,654 1,649 40-44 13.0 1,301 1,282 45-49 12.1 1,208 1,228 Marital status Married 95.3 9,556 9,580 Divorced 0.5 53 44 Separated 1.0 98 79 Widowed 3.2 316 320 Residence Total urban 33.4 3,350 3,830 Major city 18.9 1,898 1,929 Other urban 14.5 1,452 1,901 Rural 66.6 6,673 6,193 Province Punjab 57.9 5,800 4,263 Sindh 24.0 2,410 2,716 NWFP 13.5 1,351 1,862 Balochistan 4.6 462 1,182 Education No education 65.0 6,511 6,665 Primary 14.2 1,423 1,344 Middle 6.3 634 589 Secondary 8.1 809 759 Higher 6.4 646 666 Wealth quintile Lowest 19.4 1,944 1,956 Second 20.0 2,001 2,036 Middle 19.4 1,944 1,946 Fourth 20.5 2,055 2,028 Highest 20.7 2,078 2,057 Work status1 Currently working 25.9 2,595 2,515 Worked only before marriage 7.5 752 749 Worked only after marriage 2.1 212 217 Worked before and after marriage 4.1 415 418 Never worked 60.2 6,037 6,113 Total 15-49 100.0 10,023 10,023 Note: Education categories refer to the highest level of education attended, whether or not that level was completed. Total includes 12 women missing work status. 1 Categories are mutually exclusive. 3.2 EDUCATIONAL ATTAINMENT AND LITERACY Education plays an important role in a country’s development, and progress can be a good investment for improving the quality of life of the people and for human development in general. National development programmes can be successfully accomplished if the population of the country is educated and adequately provided with knowledge and skills. Islam places great emphasis on acquiring education. Generally, education provides people with new ideas and increases their potential to learn, to respond to new opportunities, to adjust to social and cultural changes occurring around the world, and to participate in the sociocultural and political activities in the country. Education also can redirect the attitudes and behaviours of the population towards improvement in the quality of life. Furthermore, education helps to overcome poverty, increase income, improve health 30 | Characteristics of Respondents and nutrition, and reduce family size. Therefore, its relationship to population growth cannot be underestimated. Table 3.2 shows variations in the level of education among ever-married women, according to background characteristics. Overall, 65 percent of women in Pakistan have no education at all, 14 percent have attended primary school only, and 6 percent have reached middle school only, while 8 percent have some secondary education (Class 9-10) and 6 percent have reached Class 11 or higher. As expected, women in the 45-49 year age group are most likely to have no education. For example, the proportion of uneducated women is 79 percent among ever-married women age 45-49 compared with 55 percent among those aged 25-29. Slightly higher proportions of ever-married women age 15- 19 and 20-24 are uneducated, which can be explained by the fact that uneducated women are more likely to marry at a younger age than educated women. Table 3.2 Educational attainment Percent distribution of ever-married women age 15-49 by highest level of schooling attended or completed, according to background characteristics, Pakistan 2006-07 Education Background characteristic No education Primary (1-5) Middle (6-8) Secondary (9-10) Higher (11+) Total Number of women Age 15-19 65.7 17.8 9.8 5.5 1.2 100.0 569 20-24 57.6 18.1 9.3 9.7 5.3 100.0 1,499 25-29 54.8 16.2 7.1 12.3 9.6 100.0 2,006 30-34 62.7 12.0 6.8 8.9 9.6 100.0 1,786 35-39 70.1 14.1 4.0 5.9 5.8 100.0 1,654 40-44 72.4 11.9 4.5 6.8 4.5 100.0 1,301 45-49 79.0 10.0 4.2 3.3 3.4 100.0 1,208 Residence Total urban 43.1 15.5 10.3 16.1 15.0 100.0 3,350 Major city 35.0 14.6 11.4 19.8 19.1 100.0 1,898 Other urban 53.5 16.8 9.0 11.2 9.6 100.0 1,452 Rural 76.0 13.5 4.3 4.1 2.2 100.0 6,673 Province Punjab 59.7 16.9 7.9 8.9 6.6 100.0 5,800 Sindh 66.8 11.8 4.6 8.7 8.1 100.0 2,410 NWFP 77.4 10.1 3.9 4.9 3.8 100.0 1,351 Balochistan 85.0 4.9 2.6 4.3 3.2 100.0 462 Wealth quintile Lowest 95.1 4.2 0.6 0.1 0.0 100.0 1,944 Second 84.4 11.6 2.4 1.2 0.3 100.0 2,001 Middle 74.8 15.9 4.9 3.0 1.4 100.0 1,944 Fourth 50.1 22.9 10.7 11.0 5.2 100.0 2,055 Highest 23.5 15.8 12.4 24.0 24.3 100.0 2,078 Work status Currently working 74.6 9.6 4.5 4.6 6.7 100.0 2,595 Worked only before marriage 49.7 15.6 6.0 13.4 15.3 100.0 752 Worked only after marriage 63.1 18.8 5.4 4.6 8.2 100.0 212 Worked before and after marriage 76.3 10.5 5.2 2.4 5.7 100.0 415 Never worked 62.0 16.1 7.3 9.4 5.3 100.0 6,037 Total 65.0 14.2 6.3 8.1 6.4 100.0 10,023 Note: Education refers to the highest level attended, whether or not that level was completed. Total includes 12 women for whom work status is missing. As expected, the proportion of uneducated women is much lower in the urban areas than the rural areas (43 and 76 percent, respectively), while the proportion of educated women is higher in urban areas than in rural areas for all levels of education. Generally, women in major cities are better educated than those in other urban areas. Characteristics of Respondents | 31 Provincial variation in educational attainment follows the national pattern of development. Punjab province, being more developed, has the lowest proportion of uneducated women (60 percent), followed by Sindh (67 percent). In comparison, 85 percent of Balochi women and 77 percent of women residing in NWFP have no education. Among ever-married women, the highest proportion of women at every education level is found in Punjab, except for Class 11 and higher, where the highest proportion is found in Sindh. The lowest proportion of women in each education category is found in Balochistan. A clear inverse relationship exists between women’s education and wealth quintile. For example, ever-married women in the lowest quintile are four times more likely to be uneducated (95 percent) than those in the highest quintile (24 percent). Moreover, nearly half the women in the highest wealth quintile have attained secondary or higher education. When looking at the relationship between education and working status of women, it is worth noting that ever-married women who are either currently working or who worked before and after marriage are most likely to be uneducated, while those who worked only before marriage are the least likely to have no education. The overall proportion of uneducated women has decreased significantly from 79 percent in 1990-91 to 65 percent in 2006-07. The distribution of women’s education by age indicates that substantial progress has been made in all age groups since the 1990-91 PDHS. Literacy is widely acknowledged as benefiting the individual and the society and is associated with a number of positive outcomes for health and nutrition. In the 2006-07 PDHS, literacy status was determined based on the respondents’ ability to read all or part of a sentence. During data collection, interviewers carried a card on which simple sentences were printed in all of the major languages for testing a respondent’s reading ability. Only those who had never been to school and those whose highest grade at school was Class 1-8 were asked to read a sentence in the language they were most likely able to read; those who had attained middle school or above were assumed to be literate. Table 3.3 presents the percent distribution of ever-married women age 15-49 by level of schooling and level of literacy, according to background characteristics. Data show that only one-third (35 percent) of ever-married women age 15-49 in Pakistan are literate. The level of literacy increases from 32 percent among women age 15-19 to 45 percent among those age 25-29 and thereafter decreases substantially to 22 percent among women 45-49. Urban women are much more likely to be literate than rural women (58 and 24 percent, respectively), with the highest level of literacy being among women residing in a major city (66 percent). Provincial differences in literacy are marked, with literacy being highest among women in the predominantly urban Punjab province (41 percent) and lowest in the predominantly rural Balochistan province (15 percent). There is also a marked difference in literacy levels by women’s wealth status, ranging from a low of 6 percent among women in the lowest wealth quintile to a high of 75 percent among women in the highest wealth quintile. By work status, the highest level of literacy is found among ever-married women who worked only before marriage (49 percent), while the lowest is among those who worked before and after marriage (26 percent) and those who are currently working (27 percent). 32 | Characteristics of Respondents Table 3.3 Literacy 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 2006-07 No schooling or primary school Background characteristic Class 9 or higher Can read a whole sentence Can read part of a sentence Cannot read at all No card with required language Blind/ visually impaired Missing Total Percent- age literate1 Number Age 15-19 6.8 18.5 6.2 67.9 0.0 0.2 0.4 100.0 31.5 569 20-24 15.0 19.3 8.2 57.2 0.1 0.2 0.1 100.0 42.4 1,499 25-29 21.9 15.9 7.3 54.5 0.0 0.1 0.2 100.0 45.2 2,006 30-34 18.5 13.1 5.9 62.2 0.0 0.1 0.2 100.0 37.5 1,786 35-39 11.7 12.9 6.4 68.7 0.0 0.1 0.2 100.0 31.0 1,654 40-44 11.3 11.6 6.4 70.5 0.1 0.0 0.1 100.0 29.3 1,301 45-49 6.8 9.4 6.0 77.4 0.2 0.1 0.2 100.0 22.1 1,208 Residence Total urban 31.1 19.2 7.9 41.6 0.0 0.1 0.2 100.0 58.1 3,350 Major city 39.0 20.6 6.5 33.7 0.1 0.0 0.2 100.0 66.1 1,898 Other urban 20.8 17.3 9.6 51.9 0.0 0.3 0.2 100.0 47.7 1,452 Rural 6.2 11.7 6.1 75.6 0.1 0.1 0.2 100.0 24.1 6,673 Province Punjab 15.5 18.1 7.3 58.9 0.0 0.1 0.1 100.0 40.9 5,800 Sindh 16.8 10.0 6.5 66.0 0.2 0.2 0.3 100.0 33.3 2,410 NWFP 8.7 9.3 5.1 76.6 0.0 0.0 0.4 100.0 23.0 1,351 Balochistan 7.5 2.5 5.0 84.6 0.1 0.0 0.4 100.0 15.0 462 Wealth quintile Lowest 0.1 2.8 3.0 94.0 0.1 0.0 0.1 100.0 5.9 1,944 Second 1.5 7.7 5.9 84.5 0.2 0.2 0.1 100.0 15.1 2,001 Middle 4.4 14.6 7.1 73.4 0.1 0.1 0.2 100.0 26.2 1,944 Fourth 16.2 24.2 11.2 48.1 0.0 0.1 0.1 100.0 51.6 2,055 Highest 48.3 21.0 6.1 24.2 0.0 0.1 0.3 100.0 75.3 2,078 Work status Currently working 11.3 10.4 5.4 72.7 0.1 0.1 0.1 100.0 27.1 2,595 Worked only before marriage 28.7 14.4 6.3 50.0 0.0 0.3 0.3 100.0 49.4 752 Worked only after marriage 12.8 21.3 6.4 59.5 0.0 0.0 0.0 100.0 40.5 212 Worked before and after marriage 8.0 13.2 4.8 72.0 0.8 0.6 0.5 100.0 26.1 415 Never worked 14.7 15.6 7.5 62.0 0.0 0.1 0.2 100.0 37.8 6,037 Total 14.5 14.2 6.7 64.2 0.1 0.1 0.2 100.0 35.4 10,023 Note: Total includes 12 women for whom work status is missing. 1 Refers to women who completed Class 9 or higher and women who can read a whole sentence or part of a sentence 3.3 EMPLOYMENT 3.3.1 Employment Status Participation in the labour force not only gives women an opportunity to earn income, but also exposes them to the outside world and to authority structures and networks other than kin-based ones (Dixon-Muller, 1993). The empowering effects of employment are dependant on factors such as type of occupation, the continuity of employment, and the type of income. It is generally accepted that women who have a regular job, who earn money, and who perceive that their contribution is a substantial part of total household earnings are more likely to be empowered than other women (Youssef, 1982; Mahmud and Johnston, 1994). The 2006-07 PDHS respondents were asked a number of questions regarding their employment status, including whether they were working in the seven days preceding the survey and, if not, whether they had worked in the 12 months before the survey. Results are shown in Table 3.4. Characteristics of Respondents | 33 Table 3.4 Employment status Percent distribution of ever married women age 15-49 by employment status, according to background characteristics, Pakistan 2006-07 Employed in the 12 months preceding the survey Not employed in the 12 months preceding the survey Background characteristic Currently employed1 Not currently employed Missing/ don't know Total Number of women Age 15-19 23.6 5.2 70.6 0.6 100.0 569 20-24 23.1 5.0 71.7 0.3 100.0 1,499 25-29 22.8 4.6 72.3 0.2 100.0 2,006 30-34 26.4 3.7 69.4 0.5 100.0 1,786 35-39 27.1 3.2 69.4 0.3 100.0 1,654 40-44 30.0 4.4 65.5 0.1 100.0 1,301 45-49 28.9 3.8 67.3 0.0 100.0 1,208 Marital status Married 25.1 4.1 70.5 0.3 100.0 9,556 Divorced/separated/widowed 42.6 5.1 51.9 0.5 100.0 467 Number of living children 0 24.1 5.0 70.5 0.4 100.0 1,349 1-2 22.9 3.8 72.7 0.6 100.0 2,697 3-4 25.7 3.5 70.8 0.0 100.0 2,725 5+ 29.3 4.6 65.9 0.2 100.0 3,252 Residence Total urban 18.9 3.9 76.8 0.3 100.0 3,350 Major city 18.3 3.7 77.9 0.2 100.0 1,898 Other urban 19.8 4.2 75.5 0.5 100.0 1,452 Rural 29.4 4.3 66.0 0.3 100.0 6,673 Province Punjab 26.8 3.7 69.1 0.4 100.0 5,800 Sindh 32.9 6.5 60.3 0.2 100.0 2,410 NWFP 10.6 1.4 87.9 0.1 100.0 1,351 Balochistan 22.3 6.0 71.5 0.1 100.0 462 Education No education 29.8 5.0 65.0 0.3 100.0 6,511 Primary 17.5 3.0 79.3 0.3 100.0 1,423 Middle 18.3 2.5 78.8 0.4 100.0 634 Secondary 14.7 1.8 82.9 0.6 100.0 809 Higher 26.8 3.2 69.9 0.0 100.0 646 Wealth quintile Lowest 40.8 7.1 52.0 0.2 100.0 1,944 Second 31.2 4.3 64.1 0.3 100.0 2,001 Middle 26.6 4.5 68.5 0.4 100.0 1,944 Fourth 18.8 3.3 77.5 0.4 100.0 2,055 Highest 13.2 1.9 84.8 0.1 100.0 2,078 Total 25.9 4.2 69.7 0.3 100.0 10,023 1 "Currently employed" is defined as having done work in the past seven days, but also includes those who did not work in the past seven days but who are regularly employed and were absent from work for leave, illness, vacation, or any other such reason. The data show that, at the time of the survey, only about one-fourth (26 percent) of ever- married women were currently employed and an additional 4 percent were not employed but had worked sometime during the preceding 12 months. An overwhelming majority—seven in ten women—were not employed in the preceding 12 months (Figure 3.1). The proportion of women who are currently employed remains constant at 23-24 percent for age groups 15-19, 20-24, and 25-29, after which it generally increases slightly with age. A much higher proportion of the divorced, widowed, and separated women are currently employed when compared with those who are currently married (43 and 25 percent, respectively). The proportion of women who are working increases slightly with the number of children the woman has. In Pakistan, many women take up jobs because of financial constraints, which generally increase as family size increases. 34 | Characteristics of Respondents There are notable variations in the proportion of women currently employed by place of residence and province. Rural women are more likely to be currently employed than urban women (29 percent and 19 percent, respectively). There is considerable variation by province in the proportion of women who are currently employed. Thirty-three percent of women residing in Sindh are currently employed compared with 11 percent among those residing in NWFP. PDHS 2006-07 Not employed in the 12 months preceding the survey 70% Not currently employed 4% Currently employed 26% Figure 3.1 Women’s Employment Status in the Past 12 Months Current employment and education have an interesting relationship (Figure 3.2 and Table 3.4). The highest proportions of currently employed women are among those with no education (30 percent) and those with higher than secondary education (27 percent), while the lowest proportion is among women with secondary education (15 percent). There is a decrease in the percentage of employed women by wealth quintile, with those in the lowest quintile much more likely to be employed than those in the highest quintile (41 percent and 13 percent, respectively). 19 29 30 18 18 15 27 26 RESIDENCE Total urban Rural EDUCATION No education Primary Middle Secondary Higher Total 0 10 20 30 Percentage employed Fi 40 PDHS 2006-07 gure 3.2 Women's Current Employment by Residence and Education Characteristics of Respondents | 35 When looking at trends over time, the data show that there was an increase in the proportion of ever-married women currently employed, from 17 percent in the 1990-91 PDHS to 20 percent in the 1996-97 Pakistan Fertility and Family Planning Survey (PFFPS). This was followed by a decrease to 16 percent as reported in the 2003 Status of Women, Reproductive Health, and Family Planning Survey (SWRHFPS), and a significant increase thereafter to the current level of 26 percent. 3.3.2 Occupation Respondents who were currently employed or had worked in the 12 months preceding the survey were further asked to specify their occupation. Table 3.5 shows the distribution of employed ever-married women by occupation, according to background characteristics. Forty-two percent of working women are engaged in an agricultural occupation, with the next most common occupation being jobs in sales and services (37 percent). Only 8 percent of employed women work in professional, technical, or managerial jobs, while 6 percent are unskilled manual workers and 4 percent work in domestic service. Table 3.5 Occupation Percent distribution of ever-married women age 15-49 employed in the 12 months preceding the survey, by occupation, according to background characteristics, Pakistan 2006-07 Background characteristic Profes- sional/ technical/ managerial Clerical Sales and services Skilled manual Unskilled manual Domestic service Agricul- ture Missing Total Number of women Age 15-19 3.4 0.0 33.5 1.1 5.6 0.0 56.4 0.0 100.0 164 20-24 5.6 0.0 44.9 1.0 7.5 0.6 39.9 0.4 100.0 420 25-29 7.9 0.0 40.1 2.2 7.9 3.0 38.5 0.4 100.0 550 30-34 12.2 0.0 34.3 2.8 5.9 3.3 41.2 0.2 100.0 537 35-39 8.3 0.3 38.1 2.5 6.1 3.7 40.9 0.2 100.0 501 40-44 7.8 1.9 35.7 2.8 4.3 6.9 40.4 0.1 100.0 447 45-49 6.8 0.2 31.6 2.2 5.3 7.5 46.4 0.0 100.0 395 Marital status Married 7.9 0.2 37.8 2.3 6.0 3.3 42.2 0.2 100.0 2,791 Divorced/separated/widowed 9.2 2.6 30.7 0.8 9.1 10.2 37.3 0.0 100.0 223 Number of living children 0 10.8 0.0 36.2 1.6 5.8 1.9 43.6 0.0 100.0 393 1-2 11.6 0.3 39.3 1.7 7.4 1.9 37.7 0.3 100.0 722 3-4 9.8 0.1 36.0 2.7 5.7 5.6 39.6 0.4 100.0 796 5+ 3.4 0.7 37.3 2.4 5.9 4.5 45.6 0.1 100.0 1,102 Residence Total urban 17.9 1.4 54.2 5.3 7.7 7.5 5.7 0.3 100.0 765 Major city 20.1 2.4 52.3 7.2 8.8 7.8 1.3 0.3 100.0 417 Other urban 15.3 0.3 56.4 3.0 6.4 7.2 11.1 0.3 100.0 348 Rural 4.7 0.0 31.5 1.2 5.7 2.6 54.2 0.2 100.0 2,248 Province Punjab 8.8 0.4 32.8 2.0 5.4 4.7 45.8 0.2 100.0 1,769 Sindh 5.4 0.3 40.7 3.2 8.1 2.6 39.4 0.3 100.0 951 NWFP 16.6 0.6 39.8 0.2 6.9 4.3 31.6 0.0 100.0 162 Balochistan 5.7 0.0 70.2 0.3 2.8 1.0 19.9 0.1 100.0 131 Education No education 0.7 0.0 34.8 2.1 6.6 4.5 51.1 0.2 100.0 2,262 Primary 0.6 0.0 58.2 2.1 5.1 3.7 29.8 0.5 100.0 291 Middle 7.4 5.3 65.2 4.2 6.5 2.8 8.5 0.0 100.0 132 Secondary 38.1 0.7 43.9 4.7 5.6 0.0 6.5 0.5 100.0 134 Higher 84.1 1.0 11.5 0.1 3.1 0.0 0.0 0.2 100.0 194 Wealth quintile Lowest 0.6 0.0 24.5 1.2 7.1 2.2 64.5 0.0 100.0 930 Second 1.5 0.0 32.9 2.7 6.9 4.3 51.4 0.2 100.0 711 Middle 4.5 0.2 46.6 1.6 4.5 5.5 36.5 0.6 100.0 605 Fourth 13.9 1.0 53.7 4.6 6.5 4.5 15.8 0.0 100.0 455 Highest 42.9 1.7 43.4 1.9 5.0 3.5 1.3 0.3 100.0 313 Total 8.0 0.4 37.3 2.2 6.2 3.8 41.9 0.2 100.0 3,013 36 | Characteristics of Respondents The analysis of occupation by background characteristics suggests that the proportion of working women with jobs in sales and services, skilled manual labour, and agriculture is higher among currently married women than among those who are divorced, separated, or widowed. Residence has a strong relationship with the type of occupation. As expected, the largest urban-rural differentials are found among women working in the agricultural sector; 54 percent of women in rural areas work in agriculture compared with only 6 percent in urban areas. More than half (54 percent) of working women residing in urban areas are employed in sales and services compared with only one- third (32 percent) among their rural counterparts. Looking at the provincial variations, 46 percent of working women in Punjab are engaged in the agricultural sector compared with only 20 percent of women in Balochistan. On the other hand, 70 percent of working women residing in Balochistan are engaged in sales and services compared with 33 percent of women residing in Punjab. Interestingly, a much higher proportion of women in NWFP are engaged in professional, technical, or managerial work (17 percent) when compared with women in Punjab (9 percent), Sindh (5 percent), and Balochistan (6 percent). The relationship between education and type of occupation is especially strong. For example, the proportion of employed women who work in agriculture decreases significantly with education, from 51 percent among ever-married women with no education to virtually 0 percent among those with higher education. The reverse is true for women who work in professional, technical, or managerial fields; more than eight in ten (84 percent) women with higher education work in such jobs compared with less than 1 percent of women with no education or only primary education. A large majority (65 percent) of working women in the lowest wealth quintile are engaged in the agricultural sector compared with only 1 percent of women in the highest quintile. On the other hand, the proportion of women working in professional, technical, and managerial fields or in sales and services increases with wealth. 3.3.3 Type of Earnings Table 3.6 shows the percent distribution of ever-married, currently employed women by type of earnings (cash or non-cash), according to type of employment (agricultural or nonagricultural). Overall, 87 percent of currently employed women receive money for their work. As expected, the proportion of women who receive money for their work is much higher in the nonagricultural than in the agricultural sector (95 percent and 76 percent, respectively). Table 3.6 Type of earnings Percent distribution of ever-married women age 15-49 currently employed, by type of earnings, according to type of employment (agricultural or nonagricultural), Pakistan 2006-07 Type of earnings Agricultural work Nonagricultural work Total Receives money 76.4 94.9 86.8 Does not receive money 23.6 5.0 13.2 Total 100.0 100.0 100.0 Number of women currently employed 1,135 1,455 2,595 Note: Total includes 5 women with missing information on type of employment who are not shown separately. 3.3.4 Employment before and after Marriage Table 3.7 presents data on the proportion of ever-married women who worked before and after marriage, according to background characteristics. The data show that 28 percent of ever- married women worked before marriage, 32 percent worked after marriage, and 21 percent worked Characteristics of Respondents | 37 both before and after marriage. However, a large majority (60 percent) of women neither worked before marriage nor after marriage; in other words, they have never worked. Younger women are somewhat more likely than older women to work before marriage, whereas older women are more likely to have worked after marriage. A much higher proportion of divorced, widowed, and separated women work either before or after marriage than currently married women. For example, 52 percent of divorced, separated, or widowed women work after marriage compared with 31 percent of those who are currently married. The proportion of women who work after marriage increases steadily with the number of children the woman has. For example, 27 percent of women with one child worked after marriage compared with 40 percent of women with six or more children. As expected, there are no major variations in the proportion of ever-married women who worked before marriage and the number of children they have. Table 3.7 Employment before and after marriage Percentage of ever-married women age 15-49 who worked before marriage and after marriage, according to background characteristics, Pakistan 2006-07 Percentage who worked Number of ever-married women Background characteristic Before marriage After marriage Neither Both Age 15-19 35.0 27.9 61.4 24.3 569 20-24 31.2 28.5 61.2 20.9 1,499 25-29 30.1 28.7 61.2 19.9 2,006 30-34 27.6 32.2 60.1 19.9 1,786 35-39 24.7 32.2 63.2 20.1 1,654 40-44 26.1 37.3 57.3 20.7 1,301 45-49 26.8 38.4 57.3 22.4 1,208 Marital status Married 28.2 31.1 61.1 20.4 9,556 Divorced/separated/widowed 30.6 51.8 45.3 27.7 467 Number of children ever born 0 33.5 26.6 60.9 21.0 1,223 1 29.5 26.7 63.9 20.1 1,179 2 28.0 27.3 64.0 19.3 1,306 3 27.6 29.8 61.1 18.5 1,266 4 24.4 30.1 63.3 17.8 1,244 5 27.3 36.2 58.7 22.1 1,049 6+ 28.0 39.5 55.8 23.4 2,755 Residence Total urban 22.2 26.0 63.5 11.8 3,350 Major city 21.3 26.0 63.0 10.3 1,898 Other urban 23.4 26.1 64.2 13.8 1,452 Rural 31.3 35.2 58.8 25.2 6,673 Province Punjab 28.8 32.6 59.3 20.6 5,800 Sindh 37.6 42.1 48.9 28.6 2,410 NWFP 8.3 13.0 84.8 6.0 1,351 Balochistan 32.6 30.4 62.1 25.1 462 Education No education 31.2 36.6 57.6 25.4 6,511 Primary 20.9 23.4 68.4 12.7 1,423 Middle 17.7 23.5 69.3 10.5 634 Secondary 19.5 17.1 70.4 7.1 809 Higher 37.1 33.1 49.1 19.2 646 Wealth quintile Lowest 44.4 49.8 44.4 38.7 1,944 Second 31.0 36.6 57.8 25.4 2,001 Middle 27.9 32.5 60.4 20.8 1,944 Fourth 19.5 24.9 67.4 11.8 2,055 Highest 19.7 17.9 70.7 8.3 2,078 Total 28.3 32.1 60.2 20.7 10,023 38 | Characteristics of Respondents There are notable variations in the proportions employed before and after marriage by place of residence and province. Rural women are more likely to have worked either before or after marriage (31 percent and 35 percent, respectively) than urban women (22 percent and 26 percent, respectively). By province, the highest proportion of women who worked either before or after marriage is among those in Sindh (38 percent and 42 percent, respectively), while the lowest is among women who reside in NWFP (8 percent and 13 percent, respectively). Employment before and after marriage varies by education. Women with no education or with higher education are the most likely to have worked before or after marriage. On the other hand, women with middle level education are the least likely to have worked before marriage, while those with secondary level education are the least likely to have worked after marriage. The proportion of women who worked before or after marriage decreases steadily with increase in wealth. 3.4 KNOWLEDGE AND ATTITUDES CONCERNING TUBERCULOSIS The 2006-07 PDHS collected data on women’s knowledge and attitudes concerning tuberculosis (TB). Table 3.8 shows the percentage of women who have heard of TB, and among those who have heard of TB, the percentage who know that TB is spread through air by coughing, the percentage who believe that TB can be cured, and the percentage who have ever been told by a doctor or nurse that they have TB. Table 3.8 Knowledge and attitudes concerning tuberculosis Percentage of 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 or nurse that they have TB, by background characteristics, Pakistan 2006-07 Among respondents who have heard of TB Percentage who report that TB is spread through the air by coughing Percentage who have ever been told by doctor/nurse they have TB Among all respondents Percentage who believe that TB can be cured Background characteristic Percentage who have heard of TB Number of women Number of women Age 15-19 78.1 569 38.6 81.2 1.7 444 20-24 86.0 1,499 47.1 87.2 2.7 1,288 25-29 88.5 2,006 51.5 89.7 2.9 1,775 30-34 87.6 1,786 55.0 89.3 3.5 1,565 35-39 88.2 1,654 55.7 91.0 3.9 1,458 40-44 89.7 1,301 57.7 90.6 4.5 1,167 45-49 90.5 1,208 57.3 87.9 4.6 1,094 Residence Total urban 92.9 3,350 60.4 93.0 3.6 3,111 Major city 95.0 1,898 60.7 95.1 4.4 1,803 Other urban 90.0 1,452 60.0 90.0 2.4 1,307 Rural 85.1 6,673 49.1 86.7 3.4 5,681 Province Punjab 86.5 5,800 49.7 86.8 2.7 5,018 Sindh 90.4 2,410 54.2 94.2 5.4 2,179 NWFP 87.2 1,351 59.4 93.3 3.8 1,178 Balochistan 90.4 462 70.2 75.3 2.8 417 Education No education 83.9 6,511 47.8 85.5 3.8 5,460 Primary 92.6 1,423 52.7 91.2 3.9 1,317 Middle 93.5 634 59.6 96.3 3.8 592 Secondary 97.5 809 65.2 95.8 1.9 789 Higher 98.0 646 77.9 98.5 2.0 634 Wealth quintile Lowest 79.1 1,944 39.9 79.1 4.4 1,538 Second 83.5 2,001 51.0 84.6 3.4 1,671 Middle 87.6 1,944 51.2 89.1 3.6 1,704 Fourth 90.7 2,055 53.7 93.5 3.9 1,864 Highest 97.0 2,078 65.9 95.7 2.4 2,015 Total 87.7 10,023 53.1 88.9 3.5 8,792 Characteristics of Respondents | 39 40 | Characteristics of Respondents Eighty-eight percent of ever-married women in Pakistan have heard of TB. Older women, those who live in urban areas, those who reside in Sindh and Balochistan provinces, those who have secondary or higher education, and those who belong to the highest wealth quintile are more likely to have heard of TB than their counterparts in other categories. Among women who have heard of TB, 53 percent know that TB is spread through the air by coughing. Younger women age 15-19, rural women, women living in Punjab, women with no education, and women in the lowest wealth quintiles are the least likely to know that TB is spread through coughing. Nine in ten respondents who have heard of TB believe that TB can be cured. Among provinces, the percentage of people who believe that TB can be cured ranges from 75 percent of women in Balochistan to 94 percent of women in Sindh. The proportion of women who know that TB can be cured increases with education and wealth. Among women who have heard of TB, only 4 percent indicated that they were ever told by a doctor or nurse that they have TB. FERTILITY 4 Syed Mubashir Ali and Ali Anwar Buriro A major objective of the 2006-07 Pakistan Demographic and Health Survey (PDHS) is to examine fertility levels, trends, and differentials in Pakistan. Fertility is one of the three principal components of population dynamics, the others being mortality and migration. In view of the fast growing population of Pakistan, the government has been trying since the 1960s to reduce the fertility rate through implementation of various population policies. However, the fertility transition in this country only started about two decades ago. Fertility levels that remained more or less constant at more than six children per woman from the 1960s to the mid-1980s started to decline in the late 1980s (Feeney and Alam, 2003; Arnold and Sultan, 1992). The 2006-07 PDHS is another effort to observe and monitor the pace of fertility transition in Pakistan. This chapter presents an analysis of the fertility data collected in the 2006-07 PDHS. It includes a discussion on levels, trends, and differentials in fertility by selected background characteristics; data on lifetime fertility (children ever born and living); and a scrutiny of age at first birth and birth intervals. Thereafter, a brief discussion on teenage fertility, which has become critical to the issue of fertility transition, is also included in this chapter. The fertility data were collected by asking ever-married women of reproductive age (15-49 years) to provide complete birth histories of all of their live births, including those who were currently living with them, those who were living away, and those who had died. In addition, the following information was collected for each live birth: name, sex, date of birth, survival status, current age (if alive), and age at death (if dead). Unlike the previous conventional practice of recording births in the birth history starting from the first birth, in this survey, the order was reversed and started by recording the last birth first, followed by all preceding births. In societies with poor recall of dates, this procedure is thought to result in better reporting of birth dates, because the more recent events are assumed to be recalled more accurately. This lends confidence in the accuracy of current fertility estimates that are based on the births in the three years preceding the survey. Also, during training, efforts were made to impress upon the interviewers the importance of collecting information in the birth history on all live births. However, it is important to mention here that the birth history approach has some limitations that might distort 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 leave out grown children who have left home (UN, 1983). Accordingly, the results should be viewed with these caveats in mind. 4.1 CURRENT FERTILITY Some current fertility measures are presented in Table 4.1 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) 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 number 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 Pakistan is 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. Fertility | 41 reproducing at the prevailing ASFR. Two additional measures of fertility reported in this table are the general fertility rate (GFR), which represents the annual number of births per 1,000 women age 15- 49, and the crude birth rate (CBR), which represents the annual number of births per 1,000 population. The CBR was estimated using the birth history data in conjunction with the household schedule population data. Table 4.1 shows a TFR of 4.1 children per woman for the three-year period preceding the survey. Fertility is considerably higher in the rural areas (4.5 children per woman) than the urban areas (3.3 children per woman), a pattern that is evident at every age. In fact, this urban-rural differential in fertility rates increases as the woman’s age increases. 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. Table 4.1 Current fertility On the whole, peak fertility occurs at age 25-29, a pattern that is also evident in the rural areas as well as total urban, other urban, and major cities. Fertility falls sharply after age group 35-39. Differentials in fertility levels by urban-rural residence, province, educational attainment, and wealth quintile are shown in Table 4.2 and Figure 4.1. Fertility is slightly lower in Punjab province (3.9 children per woman) than the other three provinces (Sindh and NWFP with 4.3 each, and Balochistan with 4.1 children per woman). Except for Balochistan where estimated fertility is expected to be higher than in other provinces,2 these provincial differentials in fertility are as expected and are closely associated with regional disparities in knowledge and use of family planning methods, median age at marriage, age at first birth, and the status of husbands staying elsewhere (see Tables 4.11, 5.2, 5.6, 6.2, and 6.5). Age-specific fertility rates, total fertility rate, the general fertility rate, and the crude birth rate for the three years preceding the survey, by residence, Pakistan 2006-07 Residence Age group Total urban Major city Other urban Rural Total 15-19 39 36 44 58 51 20-24 152 131 178 194 178 25-29 218 213 225 248 237 30-34 161 157 167 194 182 35-39 65 46 95 127 106 40-44 24 19 33 54 44 45-49 7 0 16 23 18 TFR 3.3 3.0 3.8 4.5 4.1 GFR 113 103 127 147 135 CBR 27.6 25.6 30.2 32.3 30.7 Notes: Age-specific fertility rates are per 1,000 women. Rates for age group 45-49 may be slightly biased due to truncation. Rates refer to the 1-36 months preceding the survey. Because rates are based on all women and Pakistan is 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. TFR = Total fertility rate, expressed per woman GFR = General fertility rate, expressed per 1,000 women CBR = Crude birth rate, expressed per 1,000 population As expected, education of women is strongly associated with lower fertility. The TFR decreases consistently and dramatically from 4.8 for women with no education to 2.3 for women with higher than secondary education. Fertility is also strongly associated with wealth. Data show that the lower the wealth quintile, the higher the fertility. The difference in fertility between the poorest and the richest women is close to three children per woman. Table 4.2 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 for all of these subgroups. Overall, the table shows that fertility has fallen by about two children per woman in recent periods (from 5.9 to 4.1). 2 Because of political disturbances in the province of Balochistan, the survey monitoring teams could not visit and perform their duties as frequently as desired. As a result, the data from the birth history section of the Women’s Questionnaire that requires extra effort to complete—especially when the number of children born to a woman is large—was affected. Nevertheless, because Balochistan accounts for only 5 percent of the total population of Pakistan, the fertility estimates will not have any appreciable effect at the national level. 42 | Fertility Furthermore, Table 4.2 indicates that 8 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. Noticeably, differentials in pregnancy levels are generally consistent with the pattern depicted by the TFR across the various subgroups, except for women in the provinces of Balochistan and NWFP and those in the highest wealth quintile. Table 4.2 Fertility by background characteristics Total fertility rate for the three years preceding the survey, percentage of all women age 15-49 currently pregnant, and mean number of children ever born to all women age 40-49 years, by background characteristics, Pakistan 2006-07 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 Total urban 3.3 6.6 5.6 Major city 3.0 6.0 5.3 Other urban 3.8 7.3 6.0 Rural 4.5 8.4 6.1 Province Punjab 3.9 7.1 5.7 Sindh 4.3 8.7 6.3 NWFP 4.3 8.0 6.3 Balochistan 4.1 11.5 6.2 Education No education 4.8 8.9 6.2 Primary 4.0 8.0 5.7 Middle (3.2) 6.3 5.7 Secondary 3.1 6.2 4.1 Higher (2.3) 4.9 3.2 Wealth quintile Lowest 5.8 10.7 6.8 Second 4.5 9.1 6.5 Middle 4.1 7.3 5.9 Fourth 3.4 6.1 5.7 Highest 3.0 6.5 4.9 Total 4.1 7.8 5.9 Note: Total fertility rates are for the period 1-36 months prior to interview. They are based on all women, regardless of marital status (see note on Table 4.1). Total fertility rates in parentheses are based on 500-750 unweighted women. Fertility | 43 3.3 3.0 3.8 4.5 3.9 4.3 4.3 4.1 4.8 4.0 3.2 3.1 2.3 5.8 4.5 4.1 3.4 3.0 RESIDENCE Total urban Major city Other urban Rural PROVINCE Punjab Sindh NWFP Balochistan EDUCATION No education Primary Middle Secondary Higher WEALTH QUINTILE Lowest Second Middle Fourth Highest 0.0 2.0 4.0 6.0 8.0 Number of children PDHS 2006-07 Figure 4.1 Total Fertility Rate by Background Characteristics Table 4.3 shows age-specific marital fertility rates by residence. Marital fertility rates are calculated in the same fashion as the normal age-specific fertility rates except that they are based only on women who are currently married. The table shows a total marital fertility rate (TMFR) of 6.6 children per married woman for the three years preceding the survey. As expected, the marital fertility is slightly higher in rural as opposed to urban areas (6.8 versus 6.4 children per married woman, respectively). A lower marital fertility in urban areas may be due to better access to health and family planning facilities and/or to preferences for fewer children. The age-specific marital fertility rates show a peak at age group 20-24. There has been a decline in marital fertility; for example, the TMFR was reported as 7.6 children per married woman in 1992-96 (Hakim et al., 1998), which represents a decline of one child over the past decade. Table 4.3 Current marital fertility Age-specific marital fertility rates for the three years preceding the survey, by residence, Pakistan 2006-07 Residence Age group Total urban Major city Other urban Rural Total 15-19 366 385 349 280 300 20-24 353 349 356 342 346 25-29 276 270 285 296 289 30-34 178 172 187 211 199 35-39 73 51 106 138 117 40-44 27 20 38 57 47 45-49 6 0 14 26 19 Total marital fertility rate 6.4 6.2 6.7 6.8 6.6 4.2 FERTILITY TRENDS Pakistan is blessed with a wealth of demographic data from surveys and censuses, with several organizations generating data at regular intervals. The Federal Bureau of Statistics (FBS), the National Institute of Population Studies (NIPS), the Pakistan Institute of Development Economics (PIDE), the Population Council (Pakistan), and the Population Census Organization (PCO) are a few organizations that generate demographic data at the national level. Hence, there is a wealth of data available to examine trends over time. Table 4.4 and Figure 4.2 indicate trends in fertility during the last two decades. They show that the TFR declined slowly during the last 15 years of the 20th century, changing from a high of 6.0 children per woman in 1984 to 5.4 children in 1992-96. However, fertility began declining quickly after 1992-96 to reach 4.1 children per woman in 2004-06 (Population Welfare Division, 1986; Hakim et al., 1998). 44 | Fertility Table 4.4 Trends in fertility Age-specific and total fertility rates from selected surveys, Pakistan, 1984 to 2006-07 Survey and approximate calendar period PCPS 1984-85 PDHS 1990-91 PCPS 1994-95 PFFPS 1996-97 PRHFPS 2000-01 SWRHFPS 2003 PDHS 2006-07 Age group 1984 1985-90 1994 1992-96 1997-00 2001-03 2004-06 15-19 64 84 44 83 65 60 51 20-24 223 230 227 249 211 190 178 25-29 263 268 307 278 258 233 237 30-34 234 229 243 215 206 194 182 35-39 209 147 179 148 128 117 106 40-44 127 73 92 75 61 56 44 45-49 71 40 36 24 26 33 18 TFR 6.0 5.4 5.6 5.4 4.8 4.4 4.1 Note: Age-specific fertility rates are per 1,000 women, while the total fertility rate is per woman. PCPS = Pakistan Contraceptive Prevalence Survey 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: PCPS 1984-85: Population Welfare Division, Ministry of Planning and Development, 1986; PDHS 1990-91: NIPS and Macro, 1992; PFFPS 1996-97: Hakim et al., 1998; PRHFPS 2000- 01: NIPS 2001; SWRHFPS 2003: NIPS 2007a Figure 4.2 Trends in Total Fertility Rates 6 5.4 5.6 5.4 4.8 4.4 4.1 1984 (PCPS) 1985-90 (PDHS) 1994 (PCPS) 1992-96 (PFFPS) 1997-00 (PRHFPS) 2001-03 (SWRHFP) 2004-06 (PDHS) 0 1 2 3 4 5 6 7 Percent 6.0 Table 4.5 shows the changes in fertility between the 1990-91 and the 2006-07 PDHS surveys by selected background characteristics. Overall, the TFR declined from 5.4 children per woman in the six years before the 1990-91 PDHS to 4.1 in the three years before the 2006-07 PDHS. Fertility decreased in all four provinces. With respect to education, the data show that fertility declined the most for women who have attained education up to middle level (through Class 8). By place of residence, the decrease in fertility is more conspicuous in urban than rural areas (decline of 33 percent and 20 percent, respectively). Fertility | 45 Table 4.5 Trends in fertility by background characteristics Total fertility rates and percent change according to back- ground characteristics, Pakistan 1990-91 and 2006-07 Background characteristic PDHS 1990-91 PDHS 2006-07 Percent change 1985-90 2004-06 Residence Total urban 4.9 3.3 -32.7 Major city 4.7 3.0 -36.2 Other urban 5.2 3.8 -26.9 Rural 5.6 4.5 -19.6 Province Punjab 5.4 3.9 -27.8 Sindh 5.1 4.3 -15.7 NWFP 5.5 4.3 -21.8 Balochistan 5.8 4.1 -29.3 Education No education 5.7 4.8 -15.8 Primary 4.9 4.0 -18.4 Middle 4.5 3.2 -28.9 Secondary + 3.6 2.7 -25.0 Total 5.4 4.1 -24.1 Note: Age-specific fertility rates are per 1,000 women, while the total fertility rate is per woman. Table 4.6 shows the trends in age-specific fertility rates in Pakistan for five-year periods preceding the 2006-07 PDHS. The data are derived from the information on dates of birth in the birth history from the 2006-07 PDHS only. The declining trend noted earlier (Table 4.4) is also observed here over the past 20 years for all mother’s age-at-birth groups. Table 4.6 Trends in age-specific fertility rates 4.3 CHILDREN EVER BORN AND CHILDREN SURVIVING The number of children ever born and the mean number of living children is presented in Table 4.7 for all women and all currently married women age 15-49 years. The estimates for all women are based on the assumption that all births occur within marriage. Among women age 15-19, 94 percent have never given birth. However, this proportion declines rapidly to 12 percent for women age 30-34 years; only 4 percent of women at the end of their reproductive age remain childless, indicating that childbearing among Pakistani women is nearly universal. On average, Pakistani women attain a parity of 6.3 children per woman at the end of their childbearing. This number is more than two (2.2) children above the TFR (4.1 children per woman), a discrepancy that is attributable to the decline in fertility. Age-specific fertility rates for five-year periods preceding the survey, by mother's age at the time of the birth, Pakistan 2006-07 Mother's age at birth Number of years preceding survey 0-4 5-9 10-14 15-19 15-19 55 81 111 130 20-24 187 250 273 292 25-29 241 297 309 336 30-34 190 236 265 [317] 35-39 114 158 [206] 40-44 46 [89] 45-49 [17] Note: Age-specific fertility rates are per 1,000 women. Estimates in brackets are truncated. Rates exclude the month of interview. 46 | Fertility Table 4.7 Children ever born and living Percent distribution of all women and currently married women by number of children ever born, mean number of children ever born, and mean number of living children, according to age group, Pakistan 2006-07 Mean number of children ever born Number of women Mean number of living children Number of children ever born Age 0 1 2 3 4 5 6 7 8 9 10+ Total ALL WOMEN 15-19 93.5 5.0 1.2 0.3 0.0 0.0 0.0 0.0 0.0 0.0 0.0 100.0 3,551 0.08 0.07 20-24 64.1 13.9 12.5 6.0 2.6 0.8 0.1 0.1 0.0 0.0 0.0 100.0 3,123 0.72 0.66 25-29 29.5 12.2 17.2 16.4 12.6 7.1 3.2 1.5 0.3 0.1 0.0 100.0 2,500 2.14 1.92 30-34 12.4 6.5 12.1 14.8 15.9 15.6 10.0 6.9 3.0 1.2 1.6 100.0 1,916 3.77 3.37 35-39 7.2 3.6 6.3 10.3 15.2 14.5 15.2 11.2 8.8 4.0 3.7 100.0 1,705 4.97 4.44 40-44 6.9 3.4 4.7 9.2 12.2 12.1 11.8 14.1 9.9 7.1 8.6 100.0 1,343 5.57 4.97 45-49 4.4 2.7 3.2 6.2 10.1 11.1 12.8 15.1 11.7 9.2 13.5 100.0 1,225 6.31 5.56 Total 15-49 42.7 7.7 8.5 8.2 8.1 6.8 5.5 4.8 3.2 2.0 2.4 100.0 15,362 2.53 2.25 CURRENTLY MARRIED WOMEN 15-19 58.6 31.6 7.9 1.7 0.0 0.2 0.0 0.0 0.0 0.0 0.0 100.0 559 0.54 0.46 20-24 24.8 28.7 26.2 12.8 5.3 1.7 0.2 0.2 0.0 0.0 0.0 100.0 1,463 1.52 1.38 25-29 12.1 14.6 21.6 20.6 15.9 9.0 4.0 1.8 0.4 0.1 0.0 100.0 1,965 2.69 2.41 30-34 5.5 6.5 12.8 15.8 17.4 17.0 10.9 7.7 3.4 1.3 1.7 100.0 1,729 4.10 3.67 35-39 3.8 3.4 6.3 10.1 15.8 15.2 15.6 11.9 9.4 4.3 4.1 100.0 1,565 5.21 4.67 40-44 3.8 2.8 4.8 9.6 12.5 12.5 12.5 14.7 10.3 7.3 9.1 100.0 1,208 5.80 5.19 45-49 2.7 1.8 2.8 5.5 10.2 10.8 13.0 15.8 12.3 10.2 14.8 100.0 1,067 6.61 5.81 Total 15-49 12.1 11.5 13.2 12.6 12.5 10.5 8.4 7.4 4.9 3.0 3.8 100.0 9,556 3.88 3.47 The same pattern is replicated for currently married women, with the difference that the proportion of married women age 15-19 who have not borne a child is reduced to 59 percent. Further- more, currently married women age 45-49 have, on average, borne 6.6 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 older than 40 years 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 4.7 is that the mean number of children ever born and mean number of living children increases with rising age of women, thus presupposing minimal or no recall lapse, which heightens confidence in the reported birth history. Cumulative fertility for currently married women has shown a decline since the 1994-95 Pakistan Contraceptive Prevalence Survey (PCPS) in almost all age groups of women. The overall mean number of children ever born declined from 4.5 in 1994-95 to 3.9 in 2006-07. Interestingly, the declining trend in the mean number of living children is not as sharp as in the case of children ever born. This trend reflects improvement in child survival because of the improvements in the associated socioeconomic indicators that affect the child survival. As shown in Table 4.8, there has been a modest but steady downward trend since 1990-91 in the mean number of children ever born among all women by age group. Overall, the mean has declined from 3.0 children born per woman in 1990-91 to 2.5 in 2006-07. Fertility | 47 Table 4.8 Trends in children ever born Mean number of children ever born by age group of woman, from selected surveys, Pakistan 1984 to 2006-07 Survey PDHS 1990-91 PFFPS 1996-97 PRHFPS 2000-01 SWRHFPS 2003 PDHS 2006-07 Age group 15-19 0.2 0.1 0.1 0.1 0.1 20-24 1.0 1.0 0.9 0.7 0.7 25-29 2.6 2.8 2.4 2.2 2.1 30-34 4.3 4.6 4.3 4.0 3.8 35-39 5.5 5.6 5.3 5.1 5.0 40-44 6.3 6.5 6.4 5.8 5.6 45-49 6.4 7.2 6.7 6.6 6.3 Total 3.0 2.8 2.6 2.5 2.5 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; PRHFPS 2000-01: NIPS 2001; SWRHFPS 2003: NIPS 2007a 4.4 BIRTH INTERVALS Previous research has demonstrated that children born too close to a previous birth are at increased risk of dying (NIPS and Macro, 1992). In the context of this finding, the examination of birth intervals is important in providing insights into birth spacing patterns and, subsequently, maternal and child health. Table 4.9 provides a glimpse into the birth intervals of children

View the publication

You are currently offline. Some pages or content may fail to load.