Timor-Leste - Demographic and Health Survey - 2018

Publication date: 2018

Timor-Leste Demographic and Health Survey 2016 Tim or-Leste 2016 D em ographic and H ealth S urvey 7LPRU��/HVWH 'HPRJUDSKLF�DQG�+HDOWK�6XUYH\ ���� *HQHUDO�'LUHFWRUDWH�RI�6WDWLVWLFV 0LQLVWU\�RI�3ODQQLQJ�DQG�)LQDQFH�DQG� 0LQLVWU\�RI�+HDOWK 'LOL��7LPRU�/HVWH 7KH�'+6�3URJUDP ,&) 5RFNYLOOH��0DU\ODQG��86$ 'HFHPEHU����� 7LPRU��/HVWH� 'HPRJUDSKLF�DQG�+HDOWK�6XUYH\� ����� � � *HQHUDO�'LUHFWRUDWH�RI�6WDWLVWLFV� 0LQLVWU\�RI�3ODQQLQJ�DQG�)LQDQFH�DQG�0LQLVWU\�RI�+HDOWK� 'LOL��7LPRU�/HVWH� � � 7KH�'+6�3URJUDP� ,&)� 5RFNYLOOH��0DU\ODQG��86$� � � � � �$SULO������ � 7KH� ����� 7LPRU�/HVWH� 'HPRJUDSKLF� DQG� +HDOWK� 6XUYH\� ������ 7/'+6�� ZDV� LPSOHPHQWHG� E\� WKH� *HQHUDO� 'LUHFWRUDWH �RI�6WDWLVWLFV ��0LQLVWU\ �RI�3ODQQLQJ �DQG�)LQDQFH �DQG�0LQLVWU\ �RI�+HDOWK ��7KH� IXQGLQJ �IRU�WKH������ 7/'+6 � ZDV �SURYLGHG �E\�WKH �*RYHUQPHQW �RI�*RYHUQPHQW �RI�7LPRU �/HVWH ��WKH �8QLWHG �6WDWHV �$JHQF\ �IRU� ,QWHUQDWLRQDO �'HYHORSPHQW ��86$,' ���WKH�8QLWHG �1DWLRQV � 3RSXODWLRQ � )XQG � �81)3$ ��� WKH� 8QLWHG � 1DWLRQV� &KLOGUHQ ¶V� )XQG � �81,&() ��� WKH�:RUOG � +HDOWK �2UJDQL]DWLRQ ��:+2���WKH�(XURSHDQ �8QLRQ ��DQG�WKH�:RUOG� %DQN��,&)�SURYLGHG�WHFKQLFDO�DVVLVWDQFH�WKURXJK�7KH�'+6�3URJUDP��D�86$,'�IXQGHG�SURMHFW�SURYLGLQJ�VXSSRUW� DQG�WHFKQLFDO�DVVLVWDQFH�LQ�WKH�LPSOHPHQWDWLRQ � RI�SRSXODWLRQ�DQG�KHDOWK�VXUYH\V�LQ�FRXQWULHV�ZRUOGZLGH�� $GGLWLRQDO� LQIRUPDWLRQ� DERXW� WKH� ����� 7/'+6�PD\� EH� REWDLQHG� IURP� WKH� *HQHUDO� 'LUHFWRUDWH� RI� 6WDWLVWLFV�� 0LQLVWU\�RI�3ODQQLQJ�DQG�)LQDQFH�$LWDUDN�/DUDQ�'RP�$OHL[R��'LOL��7LPRU�/HVWH��7HOHSKRQH���������������� (�PDLO��LQIR#PRI�JRY�WO��,QWHUQHW��ZZZ�PRI�JRY�WO��ZZZ�VWDWLVWLFV�JRY�WO ,QIRUPDWLRQ�DERXW�7KH�'+6�3URJUDP�PD\�EH�REWDLQHG�IURP�,&)������*DLWKHU�5RDG��6XLWH������5RFNYLOOH��0'� �������86$��7HOHSKRQH�������������������)D[�������������������(PDLO�� LQIR#'+6SURJUDP�FRP�� ,QWHUQHW�� ZZZ�'+6SURJUDP�FRP�� � &RYHU�SKRWR�‹�����3HWHU�6KDQNV��8VHG�XQGHU�&UHDWLYH�&RPPRQV��&&�%<������OLFHQVH�� 5HFRPPHQGHG�FLWDWLRQ�� *HQHUDO�'LUHFWRUDWH�RI�6WDWLVWLFV��*'6���0LQLVWU\�RI�+HDOWK� DQG�,&)�������� 7LPRU�/HVWH�'HPRJUDSKLF�DQG� +HDOWK�6XUYH\�������'LOL��7LPRU�/HVWH� DQG�5RFNYLOOH��0DU\ODQG��86$��*'6� DQG�,&)�� Contents • iii CONTENTS TABLES AND FIGURES . ix ACRONYMS AND ABBREVIATIONS . xix READING AND UNDERSTANDING TABLES FROM THE 2016 TLDHS . xxi SUSTAINABLE DEVELOPMENT GOAL INDICATORS . xxix MAP OF TIMOR-LESTE . xxx 1 INTRODUCTION AND SURVEY METHODOLOGY . 1 1.1 Survey Objectives . 1 1.2 Sample Design . 2 1.3 Questionnaires . 2 1.4 Anthropometry and Anemia Testing . 4 1.5 Pretest . 5 1.6 Training of Trainers . 5 1.7 Training of Field Staff . 5 1.8 Fieldwork . 5 1.9 Data Processing . 6 1.10 Response Rates . 6 2 HOUSING CHARACTERISTICS AND HOUSEHOLD POPULATION . 7 2.1 Drinking Water Sources and Treatment . 7 2.2 Sanitation . 8 2.3 Exposure to Smoke inside the Home . 9 2.4 Household Wealth . 9 2.5 Handwashing . 10 2.6 Household Population and Composition . 10 2.7 Children’s Living Arrangements and Parental Survival . 11 2.8 Birth Registration . 11 2.9 Education . 12 2.9.1 Educational Attainment . 12 2.9.2 School Attendance . 13 3 CHARACTERISTICS OF RESPONDENTS . 29 3.1 Basic Characteristics of Survey Respondents . 29 3.2 Education and Literacy . 30 3.3 Mass Media Exposure . 31 3.4 Employment . 32 3.5 Occupation . 33 3.6 Tobacco Use . 33 3.7 Alcohol Consumption . 34 4 MARRIAGE AND SEXUAL ACTIVITY . 55 4.1 Marital Status . 55 4.2 Polygyny . 56 4.3 Age at First Marriage . 56 4.4 Age at First Sexual Intercourse . 57 4.5 Recent Sexual Activity . 58 iv • Contents 5 FERTILITY . 69 5.1 Current Fertility . 69 5.2 Children Ever Born and Living . 70 5.3 Birth Intervals . 71 5.4 Insusceptibility to Pregnancy . 72 5.5 Age at First Birth . 73 5.6 Teenage Childbearing . 73 6 FERTILITY PREFERENCES . 83 6.1 Desire for Another Child . 83 6.2 Ideal Family Size . 84 6.3 Fertility Planning Status . 85 6.4 Wanted Fertility Rates . 86 7 FAMILY PLANNING . 93 7.1 Contraceptive Knowledge and Use . 93 7.2 Source of Modern Contraceptive Methods . 96 7.3 Informed Choice . 96 7.4 Discontinuation of Contraceptives . 96 7.5 Demand for Family Planning . 97 7.6 Contact of Nonusers with Family Planning Providers . 98 8 INFANT AND CHILD MORTALITY . 117 8.1 Infant and Child Mortality . 118 8.2 Biodemographic Risk Factors . 119 8.3 Perinatal Mortality . 120 8.4 High-risk Fertility Behavior . 120 9 MATERNAL HEALTH CARE . 127 9.1 Antenatal Care Coverage . 128 9.1.1 Skilled Providers . 128 9.1.2 Timing and Number of ANC Visits . 128 9.2 Components of ANC Visits . 129 9.3 Protection against Neonatal Tetanus . 129 9.4 Delivery Services . 130 9.4.1 Institutional Deliveries . 130 9.4.2 Skilled Assistance during Delivery . 132 9.4.3 Delivery by Caesarean . 132 9.5 Postnatal Care . 133 9.5.1 Postnatal Health Check for Mothers . 133 9.5.2 Postnatal Health Checks for Newborns . 133 9.6 Problems in Accessing Health Care . 134 10 CHILD HEALTH . 155 10.1 Birth Weight . 155 10.2 Vaccination of Children . 156 10.3 Symptoms of Acute Respiratory Infection . 158 10.4 Fever . 158 10.5 Diarrheal Disease . 158 10.5.1 Prevalence of Diarrhea and Treatment Seeking Behavior . 158 10.5.2 Feeding Practices during an Episode of Diarrhea . 159 10.5.3 Oral Rehydration Therapy and Other Treatments . 159 10.5.4 Knowledge of ORS Packets . 160 Contents • v 10.6 Treatment of Childhood Illness—Summary . 160 10.7 Disposal of Children’s Stools . 161 11 NUTRITION OF CHILDREN AND ADULTS . 179 11.1 Nutritional Status of Children . 179 11.1.1 Measurement of Nutritional Status among Young Children . 179 11.1.2 Data Collection . 180 11.1.3 Malnutrition Prevalence in Children . 181 11.2 Infant and Young Child Feeding Practices . 182 11.2.1 Breastfeeding . 182 11.2.2 Complementary Feeding . 183 11.2.3 Minimum Acceptable Diet . 184 11.3 Anemia Prevalence in Children . 185 11.4 Presence of Iodized Salt in Households . 186 11.5 Micronutrient Intake and Supplementation among Children . 187 11.6 Adults’ Nutritional Status . 187 11.6.1 Malnutrition Prevalence in Women . 187 11.6.2 Malnutrition Prevalence in Men . 188 11.7 Anemia Prevalence in Adults . 189 11.8 Micronutrient Supplementation and Deworming during Pregnancy . 189 12 MALARIA . 211 12.1 Ownership of Insecticide-Treated Nets . 211 12.2 Access to and Use of ITNs . 213 12.3 Use of ITNs by Children and Pregnant Women . 214 12.4 Case Management of Malaria in Children . 215 12.5 Prevalence of Low Hemoglobin in Children . 216 13 HIV/AIDS-RELATED KNOWLEDGE, ATTITUDES, AND BEHAVIOR . 229 13.1 HIV/AIDS Knowledge, Transmission, and Prevention Methods . 229 13.2 Knowledge about Mother-to-Child Transmission . 231 13.3 Discriminatory Attitudes towards People Living with HIV . 232 13.4 Multiple Sexual Partners . 233 13.5 Paid Sex . 233 13.6 Coverage of HIV Testing Services . 233 13.6.1 Awareness of HIV Testing Services and Experience with HIV Testing . 233 13.6.2 HIV Testing of Pregnant Women . 234 13.7 Male Circumcision . 234 13.8 Self-reporting of Sexually Transmitted Infections . 235 13.9 HIV/AIDS-Related Knowledge and Behavior among Young People . 235 13.9.1 Knowledge . 235 13.9.2 First Sex . 236 13.9.3 Premarital Sex . 236 13.9.4 Multiple Sexual Partners . 236 13.9.5 Coverage of HIV Testing Services . 236 14 ADULT AND MATERNAL MORTALITY . 261 14.1 Data . 261 14.2 Direct Estimates of Adult Mortality . 262 14.3 Trends in Adult Mortality . 263 14.4 Direct Estimates of Maternal Mortality . 263 14.5 Trends in Pregnancy-Related Mortality . 264 vi • Contents 15 WOMEN’S EMPOWERMENT . 269 15.1 Married Women’s and Men’s Employment . 270 15.2 Control over Women’s Earnings . 271 15.3 Control over Men’s Earnings . 272 15.4 Women’s and Men’s Ownership of Assets . 272 15.5 Bank Accounts and Mobile Phones . 273 15.6 Participation in Decision Making . 274 15.7 Attitudes toward Wife Beating . 275 15.8 Negotiating Sexual Relations . 276 16 DOMESTIC VIOLENCE . 299 16.1 Measurement of Violence . 299 16.2 Women’s Experience of Physical Violence . 300 16.2.1 Perpetrators of Physical Violence . 301 16.3 Experience of Sexual Violence . 301 16.4 Experience of Different Forms of Violence . 301 16.5 Marital Control by Husband . 302 16.6 Forms of Spousal Violence . 302 16.6.1 Prevalence of Spousal Violence . 302 16.7 Injuries to Women due to Spousal Violence . 304 16.8 Violence Initiated by Women against Husbands . 304 16.9 Help-Seeking among Women Who Have Experienced Violence . 305 16.10 Family Support . 305 16.11 Parental Behavior . 306 17 DISABILITY . 325 17.1 Disability by Domain and Age . 325 17.2 Disability among Adults by Other Background Characteristics . 326 18 NONCOMMUNICABLE DISEASES . 331 18.1 Blood Pressure Screening and Status . 331 18.2 Blood Sugar Screening and Status . 332 18.3 Other NCDs . 332 18.4 Desired Health Care Services . 333 19 TUBERCULOSIS . 347 19.1 Respondents’ Knowledge of Tuberculosis . 347 19.1.1 Awareness of Tuberculosis . 347 19.1.2 Knowledge of Symptoms Associated with Tuberculosis . 348 19.1.3 Knowledge of the Cause of Tuberculosis and Its Mode of Transmission . 348 19.2 Reporting and Seeking Treatment . 349 19.2.1 Reporting a Family Member’s Diagnosis . 349 19.2.2 Treatment Seeking for Tuberculosis Symptoms . 349 20 YOUTH . 357 20.1 Free Time. 357 20.2 Source of Advice and Reproductive Health Information . 358 20.3 Delivery of Reproductive Health Information . 359 20.4 Advice for Beginning Relationships . 359 Contents • vii 21 EARLY CHILDHOOD DEVELOPMENT . 375 21.1 Early Childhood Education . 375 21.2 Childhood Learning . 376 21.2.1 Support for Learning . 376 21.2.2 Children’s Books and Playthings . 377 21.3 Adequate Care for Young Children . 378 21.4 Developmentally On Track . 378 REFERENCES. 387 APPENDIX A SAMPLE DESIGN . 389 A.1 Introduction . 389 A.2 Sampling Frame . 389 A.3 Sampling Procedure and Sample Allocation . 390 A.4 Sampling Probability and Sampling Weights . 391 APPENDIX B ESTIMATES OF SAMPLING ERRORS . 393 APPENDIX C DATA QUALITY TABLES . 413 APPENDIX D SURVEY PERSONNEL . 419 APPENDIX E QUESTIONNAIRES . 423 Tables and Figures • ix TABLES AND FIGURES 1 INTRODUCTION AND SURVEY METHODOLOGY . 1 Table 1.1 Results of the household and individual interviews . 6 Figure 1.1 Questionnaire Content and Sampling . 4 2 HOUSING CHARACTERISTICS AND HOUSEHOLD POPULATION . 7 Table 2.1 Household drinking water . 15 Table 2.2 Availability of water . 16 Table 2.3 Household sanitation facilities . 16 Table 2.4 Household characteristics . 17 Table 2.5 Household possessions . 18 Table 2.6 Wealth quintiles . 18 Table 2.7 Handwashing . 19 Table 2.8 Household population by age, sex, and residence . 20 Table 2.9 Household composition . 21 Table 2.10 Children’s living arrangements and orphanhood . 22 Table 2.11 Birth registration of children under age 5 . 23 Table 2.12.1 Educational attainment of the female household population . 24 Table 2.12.2 Educational attainment of the male household population . 25 Table 2.13.1 Pre-primary school attendance: Females . 26 Table 2.13.2 Pre-primary school attendance: Males . 26 Table 2.14 School attendance ratios . 27 Figure 2.1 Household drinking water by residence . 8 Figure 2.2 Household toilet facilities by residence . 8 Figure 2.3 Household wealth by residence. 10 Figure 2.4 Population pyramid . 11 Figure 2.5 Birth registration by household wealth . 12 Figure 2.6 Secondary school net attendance ratio by household wealth . 14 3 CHARACTERISTICS OF RESPONDENTS . 29 Table 3.1 Background characteristics of respondents . 35 Table 3.2.1 Educational attainment: Women . 36 Table 3.2.2 Educational attainment: Men . 37 Table 3.3.1 Literacy: Women . 38 Table 3.3.2 Literacy: Men . 39 Table 3.4.1 Exposure to mass media: Women . 40 Table 3.4.2 Exposure to mass media: Men . 41 Table 3.5.1 Internet usage: Women . 42 Table 3.5.2 Internet usage: Men . 43 Table 3.6.1 Employment status: Women . 44 Table 3.6.2 Employment status: Men . 45 Table 3.7.1 Occupation: Women . 46 Table 3.7.2 Occupation: Men . 47 Table 3.8 Type of employment: Women . 48 Table 3.9.1 Tobacco smoking: Women . 49 Table 3.9.2 Tobacco smoking: Men . 50 x • Tables and Figures Table 3.10 Average number of cigarettes smoked daily: Men . 51 Table 3.11 Smokeless tobacco use and any tobacco use . 52 Table 3.12.1 Alcohol consumption: Women . 53 Table 3.12.2 Alcohol consumption: Men . 54 Figure 3.1 Education of survey respondents . 30 Figure 3.2 No education by household wealth . 31 Figure 3.3 Literacy by household wealth . 31 Figure 3.4 Exposure to mass media . 31 Figure 3.5 Employment by marital status . 32 Figure 3.6 Occupation . 33 4 MARRIAGE AND SEXUAL ACTIVITY . 55 Table 4.1 Current marital status . 59 Table 4.2.1 Number of women’s co-wives . 60 Table 4.2.2 Number of men’s wives . 61 Table 4.3 Age at first marriage . 62 Table 4.4 Median age at first marriage according to background characteristics . 63 Table 4.5 Age at first sexual intercourse . 64 Table 4.6 Median age at first sexual intercourse according to background characteristics . 65 Table 4.7.1 Recent sexual activity: Women . 66 Table 4.7.2 Recent sexual activity: Men . 67 Figure 4.1 Marital status . 55 Figure 4.2 Polygyny by municipality . 56 Figure 4.3 Women’s median age at marriage by wealth . 57 Figure 4.4 Median age at first sex and first marriage . 57 5 FERTILITY . 69 Table 5.1 Current fertility . 75 Table 5.2 Fertility by background characteristics . 75 Table 5.3 Trends in age-specific fertility rates . 76 Table 5.4 Children ever born and living . 76 Table 5.5 Birth intervals . 77 Table 5.6 Postpartum amenorrhea, abstinence and insusceptibility . 78 Table 5.7 Median duration of amenorrhea, postpartum abstinence and postpartum insusceptibility . 79 Table 5.8 Menopause . 80 Table 5.9 Age at first birth . 80 Table 5.10 Median age at first birth . 81 Table 5.11 Teenage pregnancy and motherhood . 82 Table 5.12 Sexual and reproductive health behaviors before age 15 . 82 Figure 5.1 Trends in fertility . 70 Figure 5.2 Trends in age specific fertility . 70 Figure 5.3 Fertility by household wealth . 70 Figure 5.4 Fertility by municipality . 71 Figure 5.5 Birth intervals . 71 Figure 5.6 Teenage childbearing by education . 73 Figure 5.7 Teenage childbearing by municipality . 74 Tables and Figures • xi 6 FERTILITY PREFERENCES . 83 Table 6.1 Fertility preferences by number of living children . 87 Table 6.2.1 Desire to limit childbearing: Women . 88 Table 6.2.2 Desire to limit childbearing: Men . 89 Table 6.3 Ideal number of children by number of living children . 90 Table 6.4 Mean ideal number of children . 91 Table 6.5 Fertility planning status . 92 Table 6.6 Wanted fertility rates . 92 Figure 6.1 Trends in desire to limit childbearing . 84 Figure 6.2 Desire to limit childbearing by number of living children . 84 Figure 6.3 Ideal family size . 85 Figure 6.4 Fertility planning status . 85 Figure 6.5 Trends in wanted and actual fertility . 86 7 FAMILY PLANNING . 93 Table 7.1 Knowledge of contraceptive methods . 100 Table 7.2 Knowledge of contraceptive methods according to background characteristics 101 Table 7.3 Current use of contraception by age . 102 Table 7.4.1 Current use of contraception by background characteristics . 103 Table 7.4.2 Trends in the current use of contraception . 104 Table 7.5 Knowledge of fertile period . 104 Table 7.6 Knowledge of fertile period by age . 104 Table 7.7 Timing of sterilization . 105 Table 7.8 Source of modern contraception methods . 105 Table 7.9 Informed choice . 106 Table 7.10 Twelve-month contraceptive discontinuation rates . 107 Table 7.11 Reasons for discontinuation . 108 Table 7.12.1 Need and demand for family planning among currently married women . 109 Table 7.12.2 Need and demand for family planning for all women and for sexually active unmarried women . 110 Table 7.13 Decisionmaking about family planning . 112 Table 7.14 Future use of contraception . 113 Table 7.15 Exposure to family planning messages . 114 Table 7.16 Contact of nonusers with family planning providers . 115 Figure 7.1 Contraceptive use . 94 Figure 7.2 Trends in contraceptive use . 94 Figure 7.3 Use of modern methods by household wealth . 95 Figure 7.4 Modern contraceptive use by municipality . 95 Figure 7.5 Demand for family planning . 97 8 INFANT AND CHILD MORTALITY . 117 Table 8.1 Early childhood mortality rates . 122 Table 8.2 Five-year early childhood mortality rates according to background characteristics . 122 Table 8.3 Ten-year early childhood mortality rates according to additional characteristics . 123 Table 8.4 Perinatal mortality . 124 Table 8.5 High-risk fertility behavior . 125 xii • Tables and Figures Figure 8.1 Trends in early childhood mortality rates . 118 Figure 8.2 Under-5 mortality by mother’s education . 119 Figure 8.3 Under-5 mortality by household wealth . 119 Figure 8.4 Under-5 mortality by municipality . 119 Figure 8.5 Under-5 mortality by previous birth interval . 120 9 MATERNAL HEALTH CARE . 127 Table 9.1 Antenatal care . 136 Table 9.2 Number of antenatal care visits and timing of first visit . 137 Table 9.3 Components of antenatal care . 138 Table 9.4 Tetanus toxoid injections . 139 Table 9.5 Place of delivery . 140 Table 9.6 Assistance during delivery . 141 Table 9.7 Caesarean section . 142 Table 9.8 Duration of stay in health facility after birth . 143 Table 9.9 Timing of first postnatal check for the mother . 143 Table 9.10 Type of provider of first postnatal check for the mother . 144 Table 9.11 Timing of first postnatal check for the newborn . 145 Table 9.12 Type of provider of first postnatal check for the newborn . 146 Table 9.12a Skin-to-skin contact . 147 Table 9.12b Instrument to cut the umbilical cord . 148 Table 9.12c Stump care . 149 Table 9.12d Newborn dried and bathed . 150 Table 9.12e Fire for warmth . 151 Table 9.13 Content of postnatal care for newborns . 152 Table 9.14 Problems in accessing and concerns about availability of health care . 153 Figure 9.1 Trends in antenatal care coverage . 129 Figure 9.2 Components of antenatal care . 129 Figure 9.3 Trends in place of birth . 130 Figure 9.4 Institutional deliveries by residence . 131 Figure 9.5 Institutional deliveries by municipality . 131 Figure 9.6 Institutional deliveries by household wealth . 131 Figure 9.7 Delivery assistance. 132 Figure 9.8 Delivery assistance by education . 132 Figure 9.9 Postnatal care by place of delivery . 133 10 CHILD HEALTH . 155 Table 10.1 Child’s size and weight at birth. 162 Table 10.2 Vaccinations by source of information . 163 Table 10.3 Vaccinations by background characteristics . 164 Table 10.4 Possession and observation of vaccination cards, according to background characteristics . 166 Table 10.5 Prevalence and treatment of symptoms of ARI . 167 Table 10.6 Source of advice or treatment for children with symptoms of ARI . 168 Table 10.7 Prevalence and treatment of fever . 169 Table 10.8 Prevalence and treatment of diarrhea . 170 Table 10.9 Feeding practices during diarrhea . 171 Table 10.10 Oral rehydration therapy, zinc and other treatments for diarrhea . 173 Table 10.11 Source of advice or treatment for children with diarrhea . 175 Table 10.12 Knowledge of ORS packets or pre-packaged liquids. 176 Table 10.13 Disposal of children’s stools . 177 Tables and Figures • xiii Figure 10.1 Childhood vaccinations . 156 Figure 10.2 Vaccination coverage by wealth . 157 Figure 10.3 Vaccination coverage by municipality . 157 Figure 10.4 Feeding practices during diarrhea . 159 Figure 10.5 Treatment of diarrhea . 160 Figure 10.6 Prevalence and treatment of childhood illnesses . 160 11 NUTRITION OF CHILDREN AND ADULTS . 179 Table 11.1 Nutritional status of children . 191 Table 11.2 Initial breastfeeding . 193 Table 11.3 Breastfeeding status according to age . 194 Table 11.4 Infant and young child feeding (IYCF) indicators on breastfeeding status . 195 Table 11.5 Median duration of breastfeeding . 195 Table 11.6a Foods and liquids consumed by children in the day or night preceding the interview . 196 Table 11.6b Specific foods and liquids consumed by children in the day or night preceding the interview . 197 Table 11.7 Minimum acceptable diet . 199 Table 11.8 Prevalence of anemia in children . 201 Table 11.9 Presence of iodized salt in household . 202 Table 11.10 Micronutrient intake and deworming among children . 203 Table 11.11 Therapeutic and supplemental foods . 205 Table 11.12.1 Nutritional status of women . 206 Table 11.12.2 Nutritional status of men . 207 Table 11.13.1 Prevalence of anemia in women . 208 Table 11.13.2 Prevalence of anemia in men . 209 Table 11.14 Micronutrient supplementation and deworming during pregnancy . 210 Figure 11.1 Trends in nutritional status of children . 181 Figure 11.2 Stunting in children by household wealth . 181 Figure 11.3 Stunting in children by municipality . 181 Figure 11.4 Breastfeeding practices by age . 183 Figure 11.5 IYCF indicators on minimum acceptable diet (MAD). 185 Figure 11.6 Trends in childhood anemia . 186 Figure 11.7 Anemia prevalence in children by municipality . 186 Figure 11.8 Nutritional status of women and men . 187 Figure 11.9 Trends in women’s nutritional status . 188 Figure 11.10 Trends in anemia in women . 189 12 MALARIA . 211 Table 12.1 Household possession of mosquito nets . 218 Table 12.2 Source of mosquito nets . 219 Table 12.3 Access to an insecticide-treated net (ITN) . 220 Table 12.4 Access to an ITN . 220 Table 12.5 Use of mosquito nets by persons in the household . 221 Table 12.6 Use of existing ITNs . 222 Table 12.7 Use of mosquito nets by children . 223 Table 12.8 Use of mosquito nets by pregnant women . 224 Table 12.9 Prevalence, diagnosis, and prompt treatment of children with fever . 225 Table 12.10 Source of advice or treatment for children with fever . 226 Table 12.11 Hemoglobin lower than 8.0 g/dl in children . 227 xiv • Tables and Figures Figure 12.1 Household ownership of ITNs . 212 Figure 12.2 Trends in household ownership of ITNs . 212 Figure 12.3 ITN ownership by household wealth . 212 Figure 12.4 ITN ownership by municipality . 213 Figure 12.5 Source of ITNs . 213 Figure 12.6 Trends in ITN access and use . 214 Figure 12.7 Access to and use of ITNs . 214 Figure 12.8 ITN Use . 214 Figure 12.9 Types of antimalarial drugs used by children under 5 who had fever . 216 Figure 12.10 Trends in ACT use by children under 5 who had fever . 216 13 HIV/AIDS-RELATED KNOWLEDGE, ATTITUDES, AND BEHAVIOR . 229 Table 13.1 Have heard of HIV or AIDS . 238 Table 13.2 Knowledge of HIV prevention methods . 239 Table 13.3 Comprehensive knowledge about HIV . 240 Table 13.4 Knowledge of prevention of mother-to-child transmission of HIV . 241 Table 13.5 Discriminatory attitudes towards people living with HIV . 242 Table 13.6.1 Multiple sexual partners and higher-risk sexual intercourse in the past 12 months: Women . 244 Table 13.6.2 Multiple sexual partners and higher-risk sexual intercourse in the past 12 months: Men . 246 Table 13.7 Payment for sexual intercourse and condom use at last paid sexual intercourse . 248 Table 13.8.1 Coverage of prior HIV testing: Women . 249 Table 13.8.2 Coverage of prior HIV testing: Men . 250 Table 13.9 Pregnant women counseled and tested for HIV . 251 Table 13.10 Male circumcision . 252 Table 13.11 Self-reported prevalence of sexually-transmitted infections (STIs) and STIs symptoms . 253 Table 13.12 Women and men seeking treatment for STIs . 255 Table 13.13 Comprehensive knowledge about HIV among young people . 255 Table 13.14 Age at first sexual intercourse among young people . 256 Table 13.15 Premarital sexual intercourse among young people . 256 Table 13.16.1 Multiple sexual partners and higher-risk sexual intercourse in the past 12 months among young people: Women . 257 Table 13.16.2 Multiple sexual partners and higher-risk sexual intercourse in the past 12 months among young people: Men . 258 Table 13.17 Recent HIV tests among young people . 259 Figure 13.1 Trends in HIV awareness . 230 Figure 13.2 Trends in HIV prevention knowledge . 230 Figure 13.3 Have heard of HIV or AIDS by municipality . 230 Figure 13.4 Trends in comprehensive HIV knowledge . 231 Figure 13.5 Knowledge of mother-to-child transmission (MTCT) . 232 Figure 13.6 Trends in knowledge of HIV testing locations . 234 Figure 13.7 Source of advice or treatment for STIs . 235 Figure 13.8 First sex before age 18 by level of education . 236 14 ADULT AND MATERNAL MORTALITY . 261 Table 14.1 Adult mortality rates . 266 Table 14.2 Adult mortality probabilities . 266 Table 14.3 Maternal mortality . 266 Table 14.4 Maternal mortality ratio . 267 Tables and Figures • xv Figure 14.1 Adult mortality rates by age . 262 Figure 14.2 Pregnancy-related mortality ratios with confidence intervals . 265 15 WOMEN’S EMPOWERMENT . 269 Table 15.1 Employment and cash earnings of currently married women and men . 278 Table 15.2.1 Control over women’s cash earnings and relative magnitude of women’s cash earnings . 279 Table 15.2.2 Control over men’s cash earnings . 281 Table 15.3 Women’s control over their own earnings and over those of their husbands . 283 Table 15.4.1 Ownership of assets: Women . 284 Table 15.4.2 Ownership of assets; Men . 285 Table 15.5.1 Ownership and use of bank accounts and mobile phones: Women . 286 Table 15.5.2 Ownership and use of bank accounts and mobile phones: Men . 287 Table 15.6 Participation in decision making . 288 Table 15.7.1 Women’s participation in decision making by background characteristics . 289 Table 15.7.2 Men’s participation in decision making by background characteristics . 290 Table 15.8.1 Attitude toward wife beating: Women . 291 Table 15.8.2 Attitude toward wife beating: Men . 292 Table 15.9 Attitudes toward negotiating sexual relations with husband . 293 Table 15.10 Ability to negotiate sexual relations with husband . 295 Table 15.11 Indicators of women’s empowerment . 295 Table 15.12 Current use of contraception by women’s empowerment . 296 Table 15.13 Ideal number of children and unmet need for family planning by women’s empowerment . 296 Table 15.14 Reproductive health care by women’s empowerment . 297 Table 15.15 Early childhood mortality rates by women’s status . 297 Figure 15.1 Employment by age . 270 Figure 15.2 Control over women’s earnings . 271 Figure 15.3 Ownership of assets . 272 Figure 15.4 Women’s participation in decision making. 274 Figure 15.5 Attitudes toward wife beating . 275 16 DOMESTIC VIOLENCE . 299 Table 16.1 Experience of physical violence . 307 Table 16.2 Persons committing physical violence . 308 Table 16.3 Experience of sexual violence. 309 Table 16.4 Persons committing sexual violence . 310 Table 16.5 Age at first experience of sexual violence . 310 Table 16.6 Experience of different forms of violence . 310 Table 16.7 Experience of violence during pregnancy . 311 Table 16.8 Marital control exercised by husbands . 312 Table 16.9 Forms of spousal violence . 313 Table 16.10 Spousal violence by background characteristics . 314 Table 16.11 Spousal violence by husband’s characteristics and empowerment indicators . 315 Table 16.12 Violence by any husband/partner in the last 12 months. 316 Table 16.13 Experience of spousal violence by duration of marriage . 316 Table 16.14 Injuries to women due to spousal violence . 317 Table 16.15 Violence by women against their husband by women’s background characteristics . 318 Table 16.16 Violence by women against their husband by husband’s characteristics and empowerment indicators . 319 Table 16.17 Help seeking to stop violence . 320 xvi • Tables and Figures Table 16.18 Sources for help to stop the violence . 321 Table 16.19 Family support . 322 Table 16.20 Parental behavior . 323 Figure 16.1 Women’s experience of violence by marital status . 301 Figure 16.2 Spousal violence by municipality . 303 Figure 16.3 Spousal violence by husband’s alcohol consumption . 303 Figure 16.4 Help seeking by type of violence experienced . 305 17 DISABILITY . 325 Table 17.1 Disability by domain and age . 327 Table 17.2.1 Disability among adults according to background characteristics: Women . 328 Table 17.2.2 Disability among adults according to background characteristics: Men . 329 18 NONCOMMUNICABLE DISEASES . 331 Table 18.1.1 Blood pressure measured and medicated: Women . 335 Table 18.1.2 Blood pressure measured and medicated: Men . 336 Table 18.2.1 Blood sugar measured and medicated: Women . 337 Table 18.2.2 Blood sugar measured and medicated: Men . 338 Table 18.3 Heart disease and chronic heart condition testing and treatment . 339 Table 18.4 Lung disease and lung heart condition testing and treatment . 340 Table 18.5 Cancer or tumor testing and treatment . 341 Table 18.6 Depression testing and treatment . 342 Table 18.7 Arthritis testing and treatment. 343 Table 18.8 Other chronic diseases testing and treatment . 344 Table 18.9 Cervical cancer . 345 Table 18.10 Desired health care services . 346 Figure 18.1 Blood pressure measured and medicated . 331 Figure 18.2 Blood sugar measured and medicated . 332 Figure 18.3 Other NCDs . 332 19 TUBERCULOSIS . 347 Table 19.1.1 Tuberculosis knowledge: Women . 351 Table 19.1.2 Tuberculosis knowledge: Men . 352 Table 19.2.1 Beliefs about tuberculosis transmission: Women . 353 Table 19.2.2 Beliefs about tuberculosis transmission: Men. 354 Table 19.3.1 Treatment and attitudes towards tuberculosis: Women . 355 Table 19.3.2 Treatment and attitudes towards tuberculosis: Men . 356 Figure 19.1 Trends in knowledge of tuberculosis . 347 Figure 19.2 Have heard of TB by municipality . 348 Figure 19.3 Have heard of TB by education . 348 Figure 19.4 Knowledge of tuberculosis transmission . 349 20 YOUTH . 357 Table 20.1.1 Main use of free time: Women . 360 Table 20.1.2 Main use of free time: Men . 361 Table 20.2 Time spent with friends . 362 Table 20.3.1 Location of time spent with friends: Women . 363 Table 20.3.2 Location of time spent with friends: Men . 364 Table 20.4.1 Source of advice: Women . 365 Table 20.4.2 Source of advice: Men . 366 Tables and Figures • xvii Table 20.5 Information on reproductive health . 367 Table 20.6.1 Source of information on reproductive health: Women . 368 Table 20.6.2 Source of information on reproductive health: Men . 369 Table 20.7.1 Delivery of information on reproductive health: Women . 370 Table 20.7.2 Delivery of information on reproductive health: Men . 371 Table 20.8.1 Advice for beginning relationships: Women . 372 Table 20.8.2 Advice for beginning relationships: Men . 373 Figure 20.1 Use of free time . 357 Figure 20.2 Information about reproductive health by residence . 358 Figure 20.3 Source of reproductive health information . 359 21 EARLY CHILDHOOD DEVELOPMENT . 375 Table 21.1 Early childhood education . 381 Table 21.2 Support for learning . 382 Table 21.3 Learning materials . 383 Table 21.4 Inadequate care . 384 Table 21.5 Early child development index . 385 Figure 21.1 Early childhood education . 376 Figure 21.2 Inadequate care by mother’s education . 378 Figure 21.3 Developmentally on track by household wealth . 379 Figure 21.4 Early childhood development index by household wealth . 379 Figure 21.5 Early childhood development index by municipality . 379 APPENDIX A SAMPLE DESIGN . 389 Table A.1 Number of EAs and average EA size according to municipality and by type of residence (TLPHC 2015) . 389 Table A.2 Number of residential households and percentage share according to municipality and by type of residence (TLPHC 2015) . 390 Table A.3 Distribution of household population and percentage share according to municipality and by type of residence (TLPHC 2015) . 390 Table A.4 Sample allocation of clusters and households according to municipality and by type of residence (TLDHS 2016) . 391 Table A.5 Sample allocation of expected number of completed women and men interviews according to municipality and by type of residence (TLDHS 2016) . 391 APPENDIX B ESTIMATES OF SAMPLING ERRORS . 393 Table B.1 List of selected variables for sampling errors, Timor-Leste DHS 2016 . 395 Table B.2 Sampling errors: Total sample, Timor-Leste DHS 2016 . 396 Table B.3 Sampling errors: Urban sample, Timor-Leste DHS 2016 . 397 Table B.4 Sampling errors: Rural sample, Timor-Leste DHS 2016 . 398 Table B.5 Sampling errors: Aileu sample, Timor-Leste DHS 2016 . 399 Table B.6 Sampling errors: Ainaro sample, Timor-Leste DHS 2016 . 400 Table B.7 Sampling errors: Baucau sample, Timor-Leste DHS 2016 . 401 Table B.8 Sampling errors: Bobonaro sample, Timor-Leste DHS 2016 . 402 Table B.9 Sampling errors: Covalima sample, Timor-Leste DHS 2016 . 403 Table B.10 Sampling errors: Dili sample, Timor-Leste DHS 2016. 404 Table B.11 Sampling errors: Ermera sample, Timor-Leste DHS 2016 . 405 Table B.12 Sampling errors: Lautem sample, Timor-Leste DHS 2016 . 406 Table B.13 Sampling errors: Liquiçá sample, Timor-Leste DHS 2016 . 407 Table B.14 Sampling errors: Manatuto sample, Timor-Leste DHS 2016 . 408 Table B.15 Sampling errors: Manufahi sample, Timor-Leste DHS 2016 . 409 xviii • Tables and Figures Table B.16 Sampling errors: SAR of Oecussi sample, Timor-Leste DHS 2016 . 410 Table B.17 Sampling errors: Viqueque sample, Timor-Leste DHS 2016 . 411 Table B.18 Sampling errors for adult and maternal mortality rates, Timor-Leste DHS 2016, adult mortality probabilities, Timor-Leste DHS 2016 and 2009-10, and pregnancy-related mortality ratios, Timor-Leste DHS 2016 and 2009-10 . 412 APPENDIX C DATA QUALITY TABLES . 413 Table C.1 Household age distribution . 413 Table C.2.1 Age distribution of eligible and interviewed women . 414 Table C.2.2 Age distribution of eligible and interviewed men . 414 Table C.3 Completeness of reporting . 415 Table C.4 Births by calendar years . 415 Table C.5 Reporting of age at death in days . 416 Table C.6 Reporting of age at death in months . 416 Table C.7 Height and weight data completeness and quality for children . 417 Table C.8 Completeness of information on siblings . 418 Table C.9 Sibship size and sex ratio of siblings . 418 Table C.10 Pregnancy-related mortality trends . 418 Acronyms and Abbreviations • xix ACRONYMS AND ABBREVIATIONS ACT artemisinin-based combination therapy AIDS acquired immune deficiency syndrome ANC antenatal care ARI acute respiratory infection ASFR age-specific fertility rate BCG Bacille Calmette-Guérin BMI body mass index CAPI computer-assisted personal interviewing CBR crude birth rate CPR contraceptive prevalence rate CSPro Censuses and Surveys Processing DEFT design effect DHS Demographic and Health Survey DPT diphtheria, pertussis, and tetanus vaccine EA enumeration area GAR gross attendance ratio GDS General Directorate of Statistics, Timor-Leste GFR general fertility rate GP gender parity index HepB hepatitis B Hib Haemophilus influenzae Type B HIV human immunodeficiency virus IFSS internet file streaming system ITN insecticide-treated net IUD intrauterine contraceptive device IYCF infant and young child feeding LAM lactational amenorrhea method LISIO Livrinho Saude Inan ho Oan – Mother and Child Health Booklet LLIN long-lasting insecticidal nets LPG liquid petroleum gas MAD minimum acceptable diet MMR maternal mortality ratio MOH Ministry of Health MTCT mother-to-child transmission NAR net attendance ratio NGO non-governmental organization ORS oral rehydration salts ORT oral rehydration therapy PRMR pregnancy-related mortality ratio xx • Acronyms and Abbreviations RHF recommended home fluids SD standard deviation SDM standard days method SE standard error STI sexually transmitted infection TB tuberculosis TFR total fertility rate TLDHS Timor-Leste Demographic and Health Survey UNFPA United Nations Population Fund UNICEF United Nations Children’s Fund USAID United States Agency for International Development VAD vitamin A deficiency VIP ventilated improved pit latrine WHO World Health Organization Reading and Understanding Tables from the 2016 TLDHS • xxi READING AND UNDERSTANDING TABLES FROM THE 2016 TIMOR-LESTE DHS (TLDHS) he new format of the 2016 TLDHS final report is based on over 250 tables of data. They are located for quick reference through links in the text (electronic version) and at the end of each chapter. Additionally, this more reader-friendly version features over 100 figures that clearly highlight trends, subnational patterns, and background characteristics. Large colorful maps display breakdowns for municipalities in Timor-Leste. The text has been simplified to highlight key points in bullets and to clearly identify indicator definitions in boxes. While the text and figures featured in each chapter highlight some of the most important findings from the tables, not every finding can be discussed or displayed graphically. For this reason, TLDHS data users should be comfortable reading and interpreting tables. The following pages provide an introduction to the organization of TLDHS tables, the presentation of background characteristics, and a brief summary of sampling and understanding denominators. In addition, this section provides some exercises for interpreting TLDHS tables. T xxii • Reading and Understanding Tables from the 2016 TLDHS Example 1: Women’s Exposure to Mass Media A Question Asked of All Survey Respondents Table 3.4.1 Exposure to mass media: Women Percentage of women age 15-49 who are exposed to specific media on a weekly basis, by background characteristics, Timor-Leste DHS 2016 Background characteristic Reads a newspaper at least once a week Watches television at least once a week Listens to the radio at least once a week Accesses all three media at least once a week Accesses none of the three media at least once a week Number of women Age 15-19 7.7 43.1 14.6 3.8 52.2 2,985 20-24 8.9 40.8 15.7 4.6 53.1 2,165 25-29 7.3 36.9 12.8 3.1 58.1 2,011 30-34 7.5 40.7 12.8 3.0 54.1 1,772 35-39 6.2 30.7 14.1 3.2 64.4 1,141 40-44 6.0 32.3 11.3 2.7 63.0 1,438 45-49 4.3 26.9 11.0 1.8 69.1 1,096 Residence Urban 12.5 63.7 19.3 5.9 31.5 4,182 Rural 4.5 24.7 10.6 2.1 70.2 8,425 Municipality Aileu 5.2 21.2 12.4 2.5 73.8 524 Ainaro 1.8 15.1 10.7 0.4 78.8 515 Baucau 4.4 37.5 10.2 1.7 57.6 1,288 Bobonaro 5.4 38.4 17.2 3.8 56.7 946 Covalima 4.4 19.8 9.1 0.9 74.0 750 Dili 11.9 65.9 16.3 4.8 30.4 3,206 Ermera 5.1 12.9 8.1 1.5 80.9 1,178 Lautem 4.6 33.0 12.0 2.6 61.6 645 Liquiçá 10.4 27.0 20.7 8.6 66.3 757 Manatuto 6.3 43.9 14.0 3.9 52.3 555 Manufahi 5.8 37.3 23.7 4.4 55.7 676 SAR of Oecussi 5.4 20.2 7.5 2.9 77.0 778 Viqueque 8.0 28.9 9.1 2.0 64.9 791 Education No education 0.3 12.7 6.0 0.3 84.2 2,741 Primary 3.2 23.6 9.4 1.1 71.4 1,922 Secondary 8.3 46.4 16.1 3.9 48.2 6,561 More than secondary 21.0 65.1 21.9 10.0 28.2 1,383 Wealth quintile Lowest 1.9 5.4 5.3 0.9 91.2 2,085 Second 3.2 11.6 9.2 0.9 81.7 2,287 Middle 5.0 27.1 12.1 2.2 67.2 2,423 Fourth 7.5 54.0 17.0 3.9 40.6 2,771 Highest 15.2 72.8 20.3 7.3 23.4 3,041 Total 7.2 37.6 13.5 3.4 57.4 12,607 Step 1: Read the title and subtitle. They tell you the topic and the specific population group being described. In this case, the table is about women’s exposure to mass media. All female respondents age 15-49 were asked these questions. Step 2: Scan the data column headings—highlighted in green in Example 1.They describe how the information is categorized. In this table, the first three columns of data show different types of media that women access at least once a week. The fourth column shows women who access all three types of media, while the fifth column is women who do not access any of the three media at least once a week. The last column lists the number of women interviewed in the survey. Step 3: Scan the row headings—the first vertical column (called the stub) highlighted in blue in Example 1. These show the different ways the data are divided into categories within certain background characteristics of the respondents. In this case, the table presents women’s exposure to media by age, urban-rural residence, municipality, educational level, and wealth quintile. Most of the data in the TLDHS tables will be organized into these same categories. 1 2 3 4 5 Reading and Understanding Tables from the 2016 TLDHS • xxiii Step 4: Look at the row at the bottom of the table highlighted in pink. These percentages are based on all women age 15-49, the total number of women in the table. In this case, 7.2%* of women age 15-49 read a newspaper at least once a week, 37.6% watch television weekly, and 13.5% listen to the radio weekly. Step 5: To find out what percentage of women with more than secondary education access all three media weekly, draw two imaginary lines, as shown on the table. This shows that 10.0% of women age 15-49 with more than secondary education access all three types of media weekly. By looking at patterns by background characteristics, we can see how exposure to mass media varies across Timor-Leste. Mass media are often used to communicate health messages. Knowing how mass media exposure varies among different groups can help program planners and policy makers determine how to most effectively reach their target populations. *For the purpose of this document, data are presented exactly as they appear in the table including decimal places. However, the text in the remainder of this report rounds data to the nearest whole percentage point. Practice: Use the table in Example 1 to answer the following questions: a) What percentage of women in Timor-Leste do not access any of the three media at least once a week? b) What age group of women are most likely to read a newspaper weekly? c) Compare women in urban areas and women in rural areas—which group is more likely to watch television weekly? d) What is the range (lowest and highest) across municipalities in the percentage of women who do not access any of the three media at least once a week? e) Is there a clear pattern in exposure to television on a weekly basis by education level? f) Is there a clear pattern in exposure to radio on a weekly basis by wealth quintile? Answers: a) 57.4% b) Women age 20-24: 8.9% of women in this age group read a newspaper at least once a week. c) Women in urban areas, 63.7% watch television weekly, compared to 24.7% of women in rural areas. d) 30.4% of women in Dili do not access any of the media on a weekly basis, compared to 80.9% of women in Ermera. e) Watching television on a weekly basis increases with a woman’s level of education; 12.7% of women with no education watch television weekly, compared to 65.1% of women with more than secondary education. f) Listening to the radio on a weekly basis increases as household wealth increases; 5.3% of women in the lowest wealth quintile listen to the radio weekly, compared to 20.3% of women in the highest wealth quintile. xxiv • Reading and Understanding Tables from the 2016 TLDHS Example 2: Prevalence and Treatment of Symptoms of ARI A Question Asked of a Subgroup of Survey Respondents Table 10.5 Prevalence and treatment of symptoms of ARI Among children under age 5, percentage who had symptoms of acute respiratory infection (ARI) in the 2 weeks preceding the survey; and among children with symptoms of ARI in the 2 weeks preceding the survey, percentage for whom advice or treatment was sought, according to background characteristics, Timor-Leste DHS 2016 Among children under age 5: Among children under age 5 with symptoms of ARI: Background characteristic Percentage with symptoms of ARI1 Number of children Percentage for whom advice or treatment was sought2 Percentage for whom treatment was sought same or next day Number of children Age in months <6 1.4 750 * * 10 6-11 2.1 714 * * 15 12-23 2.3 1,456 (65.4) (46.5) 34 24-35 2.4 1,364 (76.5) (43.2) 33 36-47 1.9 1,413 * * 27 48-59 1.4 1,373 * * 19 Sex Male 2.3 3,657 66.5 43.1 82 Female 1.7 3,411 77.3 45.7 57 Mother's smoking status Smokes cigarettes/tobacco 8.9 293 * * 26 Does not smoke 1.7 6,776 71.6 39.6 113 Cooking fuel Electricity or gas 2.6 668 * * 17 Kerosene 3.5 362 * * 13 Charcoal * 4 * * 0 Wood/straw3 1.8 6,034 63.2 34.7 109 Residence Urban 2.6 2,045 (86.0) (60.5) 53 Rural 1.7 5,024 61.6 34.0 86 Municipality Aileu 1.9 271 * * 5 Ainaro 2.9 358 * * 10 Baucau 1.3 727 * * 9 Bobonaro 3.0 617 * * 19 Covalima 1.1 405 * * 5 Dili 2.4 1,596 * * 38 Ermera 1.3 664 * * 8 Lautem 1.2 399 * * 5 Liquiçá 2.2 467 * * 10 Manatuto 1.3 332 * * 4 Manufahi 1.9 360 * * 7 SAR of Oecussi 2.3 438 * * 10 Viqueque 2.0 435 * * 9 Mother's education No education 1.7 1,771 (63.9) (29.0) 31 Primary 2.2 1,292 (76.2) (39.4) 29 Secondary 1.8 3,373 63.3 40.4 59 More than secondary 3.2 633 * * 20 Wealth quintile Lowest 1.9 1,416 (69.6) (25.7) 27 Second 1.6 1,444 * * 23 Middle 1.5 1,389 * * 21 Fourth 2.4 1,424 (73.2) (34.6) 34 Highest 2.5 1,397 (98.4) (86.5) 34 Total 2.0 7,069 70.9 44.1 139 Note: Figures in parentheses are based on 25-49 unweighted cases. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 1 Symptoms of ARI include short rapid breathing which was chest-related and/or by difficult breathing which was chest- related 2 Includes advice or treatment from the following public sources: National hospital, Referral hospital Health post, Community health centre, SISCa post, Mobile clinic, Other public sector and from private medical sources Private hospital/ clinic, Pharmacy, Private doctor, Mobile clinic, Other private medical sector, Shop and other. Excludes advice or treatment from a traditional practitioner 3 Includes grass, shrubs, crop residues Step 1: Read the title and subtitle. In this case, the table is about two separate groups of children: all children under age 5 (a) and children under age 5 who had symptoms of acute respiratory infection (ARI) in the two weeks before the survey (b). 1 2 3 4 a b Reading and Understanding Tables from the 2016 TLDHS • xxv Step 2: Identify the two panels. First, identify the columns that refer to all children under age 5 (a), and then isolate the columns that refer only to children under age 5 who had symptoms of ARI in the two weeks before the survey (b). Step 3: Look at the first panel. What percentage of children under age 5 had symptoms of ARI in the two weeks before the survey? It’s 2.0%. Now look at the second panel. How many children under age 5 are there who had symptoms of ARI in the two weeks before the survey? It’s 139 children or 2.0% of the 7,069 children under age 5 (with rounding). The second panel is a subset of the first panel. Step 4: Only 2.0% of children under age 5 had symptoms of ARI in the two weeks before the survey. Once these children are further divided into the background characteristic categories, there may be too few cases for the percentages to be reliable.  What percentage of children under age 5 in urban areas with symptoms of ARI in the two weeks before the survey sought advice or treatment from a health facility or provider on the same or next day after symptoms of ARI arose? 60.5%. This percentage is in parentheses because there are between 25 and 49 children under age 5 in urban areas who had symptoms of ARI in the two weeks before the survey (unweighted). Readers should use this number with caution—it may not be reliable. (For more information on weighted and unweighted numbers, see Example 4.)  What percentage of children under age 5 in Ainaro with symptoms of ARI the two weeks before the survey sought advice or treatment from a health facility or provider on the same or next day after symptoms of ARI arose? There is no number in this cell—only an asterisk. This is because fewer than 25 children under age 5 in Ainaro had symptoms of ARI in the two weeks before the survey. Results for this group are not reported. The subgroup is too small, and therefore the data are not reliable. Note: When parentheses or asterisks are used in a table, the explanation will be noted under the table. If there are no parentheses or asterisks in a table, you can proceed with confidence that enough cases were included in all categories for the data to be reliable. xxvi • Reading and Understanding Tables from the 2016 TLDHS Example 3: Understanding Sampling Weights in TLDHS Tables A sample is a group of people who have been selected for a survey. In the TLDHS, the sample is designed to represent the national population age 15-49. In addition to national data, most countries want to collect and report data on smaller geographical or administrative areas. However, doing so requires a minimum sample size per area. For the 2016 TLDHS, the survey sample is representative at the national and municipality levels, and for urban and rural areas. To generate statistics that are representative of Timor- Leste as a whole and the 13 municipalities, the number of women surveyed in each municipality should contribute to the size of the total (national) sample in proportion to the size of the municipality. However, if some municipalities have small populations, then a sample allocated in proportion to each municipality’s population may not include a sufficient number of women from each municipality for analysis. To solve this problem, municipalities with small populations are oversampled. For example, let’s say that you plan to interview 12,607 women and want to produce results that are representative of Timor-Leste as a whole and its municipalities (as in Table 3.1). However, the total population of Timor-Leste is not evenly distributed among the municipalities: some municipalities, such as Dili, are heavily populated, while others, such as Aileu, are not. Thus, Aileu must be oversampled. A sampling statistician determines how many women should be interviewed in each municipality in order to get reliable statistics. The blue column (1) in the table above shows the actual number of women interviewed in each municipality. Within the municipalities, the number of women interviewed ranges from 768 in Ainaro to 1,661 in Dili. The number of interviews is sufficient to get reliable results in each municipality. With this distribution of interviews, some municipalities are overrepresented and some municipalities are underrepresented. For example, the population in Dili is about 25% of the Timor-Leste population , while Aileu’s population is 4% of the Timor-Leste population. But as the blue column shows, the number of women interviewed in Dili accounts for only about 13% of the total sample of women interviewed (1,661 /12,607) and the number of women interviewed in Aileu accounts for 8% of the total sample of women interviewed (1,047 /12,607). This unweighted distribution of women does not accurately represent the population. In order to get statistics that are representative of Timor-Leste, the distribution of the women in the sample needs to be weighted (or mathematically adjusted) such that it reflects the true distribution in Timor-Leste. Women from a small municipality, such as Aileu, should contribute a smaller amount to the national estimates based on the total sample. Women from a large municipality, such as Dili, should contribute much more. Therefore, DHS statisticians mathematically calculate a “weight” which is used to adjust the number of women from each municipality so that each municipality’s contribution to the total is proportional to the actual population of the municipality. The numbers in the purple column (2) represent the “weighted” values. The weighted values can be smaller or larger than the unweighted values at the municipality level. The total national sample size of 12,607 women has not changed after weighting, but the distribution of women across municipalities has been changed to reflect their actual contribution to the total population size. Table 3.1 Background characteristics of respondents Percent distribution of women age 15-49 by selected background characteristics, Timor-Leste DHS 2016 Background characteristic Women Weighted percent Weighted number Unweighted number Municipality Aileu 4.2 524 1,047 Ainaro 4.1 515 768 Baucau 10.2 1,288 896 Bobonaro 7.5 946 915 Covalima 5.9 750 852 Dili 25.4 3,206 1,661 Ermera 9.3 1,178 943 Lautem 5.1 645 867 Liquiçá 6.0 757 944 Manatuto 4.4 555 933 Manufahi 5.4 676 1,087 SAR of Oecussi 6.2 778 773 Viqueque 6.3 791 921 Total 15-49 100.0 12,607 12,607 1 2 3 Reading and Understanding Tables from the 2016 TLDHS • xxvii How do statisticians weight each category? They take into account the probability that a woman was selected in the sample. If you were to compare the green column (3) to the actual population distribution of Timor- Leste, you would see that women in each municipality are contributing to the total sample with the same weight that they contribute to the population of Timor-Leste. The weighted number of women in the survey now accurately represents the proportion of women who live in Dili and the proportion of women who live in Aileu. With sampling and weighting, it is possible to interview enough women to provide reliable statistics at national and municipality levels. In general, only the weighted numbers of women (or men or children) are shown in each of the TLDHS tables, so don’t be surprised if some numbers seem low: they may actually represent a larger number of women (or men) interviewed. Sustainable Development Goal Indicators • xxix SUSTAINABLE DEVELOPMENT GOAL INDICATORS Timor-Leste DHS 2016 Sex Total TLDHS table number Indicator Male Female 2. Zero hunger 2.2.1 Prevalence of stunting among children under 5 years of age 48.0 43.0 45.6 11.1 2.2.2 Prevalence of malnutrition among children under 5 years of age 31.0 27.9 29.5 na a) Prevalence of wasting among children under 5 years of age 25.6 22.4 24.0 11.1 b) Prevalence of overweight among children under 5 years of age 5.4 5.5 5.5 11.0 3. Good health and well-being 3.1.1 Maternal mortality ratio1 3.1.2 Proportion of births attended by skilled health personnel na na 56.7 9.6 3.2.1 Under-five mortality rate2 46 36 41 8.2 3.2.2 Neonatal mortality rate2 24 13 19 8.2 3.7.1 Proportion of women of reproductive age (aged 15-49 years) who have their need for family planning satisfied with modern methods na 46.6 na 7.12.2 3.7.2 Adolescent birth rates per 1,000 women b) Women aged 15-19 years3 na 42 na 5.1 3.a.1 Age-standardized prevalence of current tobacco use among persons aged 15 years and older4 52.7 4.1 28.4a 3.9.1 and 3.9.2 3.b.1 Proportion of the target population covered by all vaccines included in their national program5 43.1 47.4 45.2 10.3 5. Gender equality 5.2.1 Proportion of ever-partnered women and girls aged 15 years and older subjected to physical, sexual or psychological violence by a current or former intimate partner in the previous 12 months6,7,8 na 36.8 na 16.9 a) Physical violence na 33.1 na 16.9 b) Sexual violence na 4.8 na 16.9 c) Psychological violence8 na 8.9 na 16.9 5.3.1 Proportion of women aged 20-24 years who were married or in a union before age 15 and before age 18 a) before age 15 na 2.6 na 4.3 b) before age 18 na 14.9 na 4.3 5.6.1 Proportion of women aged 15-49 years who make their own informed decisions regarding sexual relations, contraceptive use and reproductive health care9 na 35.9 na na 5.b.1 Proportion of individuals who own a mobile telephone10 77.3 65.6 71.4a 15.5.1, 15.5.2 Residence Urban Rural 6. Clean water and sanitation 6.1.1 Proportion of the population using safely managed drinking water services11 92.1 75.1 79.8 2.1 6.2.1 Proportion of population using safely managed sanitation services, including a handwashing facility with soap and water12 76.0 45.4 53.8 2.3 7. Affordable clean energy 7.1.1 Proportion of population with access to electricity 98.4 68.3 76.5 2.4 7.1.2 Proportion of population with primary reliance on clean fuels and technology13 21.8 4.1 9.0 2.4 Sex Male Female 8. Decent work and economic growth 8.7.2 Proportion of adults (15 years and older) with an account at a bank or other financial institution or with a mobile-money-service provider10 15.6 11.1 13.4a 15.5.1, 15.5.2 16. Peace, justice, and strong institutions 16.9.1 Proportion of children under 5 years of age whose births have been registered with a civil authority 59.8 61.0 60.4 2.11 17. Partnerships for the goals 17.8.1 Proportion of individuals using the Internet14 31.1 22.4 26.8a 3.5.1, 3.5.2 na = Not applicable 1 Expressed in terms of maternal deaths per 100,000 live births in the 7-year period preceding the survey 2 Expressed in terms of deaths per 1,000 live births for the 5-year period preceding the survey 3 Equivalent to the age-specific fertility rate for women age 15-19 for the 3-year period preceding the survey, expressed in terms of births per 1,000 women age 15-19 4 Data are not age-standardized and are available for women and men age 15-49 only. 5 Data are presented for children age 12-23 months receiving all vaccines included in their national program appropriate for their age: BCG, three doses of DPT-HepB-HiB (Pentavalent), four doses of oral polio vaccine, and one dose of Measles Rubella. 6 Data are available for women age 15-49 who have ever been in union only. 7 In the DHS, psychological violence is termed emotional violence. 8 Data are available for current or most recent partner. 9 Data are available for currently married women who are not pregnant only. 10 Data are available for women and men age 15-49 only. 11 Measured as the percentage of population using an improved water source: the percentage of de jure population whose main source of drinking water is a household connection (piped), public tap or standpipe, tube well or borehole, protected dug well, protected spring, or rainwater collection. Households using bottled water for drinking are classified as using an improved or unimproved source according to their water source for cooking and handwashing. 12 Measured as the percentage of population using an improved sanitation facility: the percentage of de jure population whose household has a flush or pour flush toilet to a piped water system, septic tank or pit latrine; ventilated improved pit latrine; pit latrine with a slab; or composting toilet and does not share this facility with other households. 13 Measured as the percentage of the population using clean fuel for cooking. 14 Data are available for women and men age 15-49 who have used the internet in the past 12 months. a The total is calculated as the simple arithmetic mean of the percentages in the columns for males and females xxx • Map of Timor-Leste Introduction and Survey Methodology • 1 INTRODUCTION AND SURVEY METHODOLOGY 1 he 2016 Timor-Leste Demographic and Health Survey (TLDHS) was implemented by the General Directorate of Statistics (GDS) of the Ministry of Planning and Finance in collaboration with the Ministry of Health (MOH). Data collection took place from 16 September to 22 December, 2016. ICF provided technical assistance through The DHS Program , which is funded by the United States Agency for International Development (USAID) and offers financial support and technical assistance for population and health surveys in countries worldwide. Other agencies and organizations that facilitated the successful implementation of the survey through technical or financial support were the Government of Timor -Leste , the USAID /Timor -Leste , the United Nations Population Fund (UNFPA ), the United Nations Children’s Fund (UNICEF), the World Health Organization (WHO), the European Union, and the World Bank. 1.1 SURVEY OBJECTIVES The primary objective of the 2016 TLDHS project is to provide up-to-date estimates of basic demographic and health indicators. The TLDHS provides a comprehensive overview of population, maternal, and child health issues in Timor-Leste. More specifically, the 2016 TLDHS:  Collected data at the national level, which allows the calculation of key demographic indicators, particularly fertility, and child, adult, and maternal mortality rates  Provided data to explore the direct and indirect factors that determine the levels and trends of fertility and child mortality  Measured the levels of contraceptive knowledge and practice  Obtained data on key aspects of maternal and child health, including immunization coverage, prevalence and treatment of diarrhea and other diseases among children under age 5, and maternity care, including antenatal visits and assistance at delivery  Obtained data on child feeding practices, including breastfeeding, and collected anthropometric measures to assess nutritional status in children, women, and men  Tested for anemia in children, women, and men  Collected data on the knowledge and attitudes of women and men about sexually-transmitted diseases and HIV/AIDS, potential exposure to the risk of HIV infection (risk behaviors and condom use), and coverage of HIV testing and counseling  Measured key education indicators, including school attendance ratios, level of educational attainment, and literacy levels  Collected information on the extent of disability  Collected information on non-communicable diseases  Collected information on early childhood development  Collected information on domestic violence T 2 • Introduction and Survey Methodology  The information collected through the 2016 TLDHS is intended to assist policy makers and program managers in evaluating and designing programs and strategies for improving the health of the country’s population. 1.2 SAMPLE DESIGN The sampling frame used for the 2016 TLDHS is the 2015 Timor-Leste Population and Housing Census (2015 TLPHC) provided by the Timor-Leste GDS. The sampling frame is a complete list of enumeration areas (EAs) created for the 2015 population census. In the 2015 TLPHC, there are an average of 89 households per EA. The sampling frame contains information about the administrative unit, the type of residence, the number of residential households, and the male and female population in each of the EAs. There are five geographic regions in Timor-Leste, and these are subdivided into 12 municipalities and special administrative region (SAR) of Oecussi. The 2016 TLDHS sample was designed to produce reliable estimates of indicators for the country as a whole, for urban and rural areas, and for each of the 13 municipalities. A representative probability sample of approximately 12,000 households was drawn; the sample was stratified and selected in two stages. In the first stage, 455 EAs were selected with probability proportional to EA size from the 2015 TLPHC: 129 EAs in urban areas and 326 EAs in rural areas. In the second stage, 26 households were randomly selected within each of the 455 EAs; the sampling frame for this household selection was the 2015 TLPHC household listing available from the census database. It was decided not to conduct a standard DHS household listing operation because the 2015 TLPHC listing was less than a year old and there were constraints on the survey’s funding and timeline. In the list of households provided by the 2015 TLPHC, each dwelling was identified by a unique number, its GIS coordinates, and a computerized map indicating the dwelling’s position. At the time of fieldwork, GDS also provided the names of the household heads for the selected households. These data were uploaded to the tablet computers used for data collection to assist survey teams in locating the selected households. Interviewers only contacted pre-selected households. The sample design and sample size calculations took into consideration anticipated rates of non-response at the household and individual levels. No replacements or changes of the pre-selected households were allowed in order to prevent bias. Because of the non- proportional sample allocation to the sampling strata and the fixed sample size per cluster, the survey is not self-weighting. The resulting data have, therefore, been weighted to be representative at the national, urban/rural, and municipality levels. All selected households were eligible for an interview with the Household Questionnaire. All women age 15-49 and children age 0-59 months who were either permanent residents of the selected households or visitors who stayed in the household the night before the survey were eligible for anthropometric measurements, and the women were eligible for individual interview. In one-third of the sampled households, all men age 15-59, including both usual residents and visitors who stayed in the household the night before the interview, were eligible for individual interview. In the subsample of households selected for the men’s interview, women age 15-49, men age 15-49, and children age 0-59 months were eligible for anthropometric measurements. Also in the subsample of households selected for the men’s interview, anemia testing was performed among consenting women age 15-49 and consenting men age 15-59, and among children age 6-59 months whose parents or guardians consented. In addition, a subsample consisting of one eligible woman in two-thirds of households (those households not selected for the men’s interviews) was randomly selected to be asked questions about domestic violence. 1.3 QUESTIONNAIRES Four questionnaires were used for the 2016 TLDHS: the Household Questionnaire, the Woman’s Questionnaire, the Man’s Questionnaire, and the Biomarker Questionnaire. These questionnaires, based on The DHS Program’s standard Demographic and Health Survey questionnaires, were adapted to reflect the population and health issues relevant to Timor-Leste. Feedback was solicited from various stakeholders Introduction and Survey Methodology • 3 representing government ministries and agencies, non-governmental organizations, and development partners. After the preparation of the questionnaires in English, the questionnaires were translated into Tetum. Each questionnaire was programmed into the tablet computers to facilitate computer-assisted personal interviewing (CAPI). The questionnaires and survey protocol was reviewed and approved by the ICF Institutional Review Board. The Household Questionnaire listed all members of and visitors to the selected households. Basic demographic information was collected on the characteristics of each person, including age, sex, marital status, education, and relationship to the head of the household. Parents’ survival status was collected for children under age 18. Data on age and sex of household members obtained in the Household Questionnaire were used to identify women and men who were eligible for individual interviews and to identify women, men, and children eligible for anthropometry measurement and anemia testing. The Household Questionnaire also collected information on characteristics of the household dwelling, including source of water, type of toilet facilities, materials used to construct the house, ownership of various consumer goods, use of iodized salt, and types and use of mosquito nets. Finally, the Household Questionnaire included a set of questions on disability, based on the module developed by the Washington Group, asked for all household members age 5 and above. The Woman’s Questionnaire collected information from all eligible women age 15-49. Women were asked questions on:  Background characteristics (age, education, literacy, religion, etc.)  Reproductive history  Knowledge and use of contraceptive methods  Antenatal, delivery, and postnatal care  Breastfeeding and infant feeding practices  Immunization, child health, and nutrition  Marriage and recent sexual activity  Fertility preferences  Husband’s background and respondent’s work  Knowledge about HIV/AIDS and other sexually transmitted diseases  Other health issues, for example, recent injections, smoking habits, and alcohol use  Adult and maternal mortality  Domestic violence (one woman per household)  Early childhood development  Questions specific to youth  Non-communicable diseases The Man’s Questionnaire was administered to all men age 15-59 in the subsample of households selected for the men’s interview. The Man’s Questionnaire collected much of the same information elicited with the Woman’s Questionnaire, although it was shorter and did not contain a detailed reproductive history or questions on maternal and child health. The Biomarker Questionnaire recorded the anthropometry measurements, and hemoglobin measurements for anemia testing. The organization of the questionnaire content in the 1/3 sub-sample selected for male interview and the 2/3 not selected for male interview is shown in Figure 1.1. 4 • Introduction and Survey Methodology Figure 1.1 Questionnaire Content and Sampling Interviewers used tablet computers to record responses during the interviews. The tablet computers had Bluetooth® technology to enable remote electronic transfer of files, such as assignments from the team supervisor to the interviewers, individual questionnaires among survey team members, and completed questionnaires from interviewers to team supervisors. The CAPI data collection system was developed by The DHS Program with the mobile version of CSPro. The CSPro software was developed jointly by the U.S. Census Bureau, Serpro S.A., and The DHS Program. 1.4 ANTHROPOMETRY AND ANEMIA TESTING The 2016 TLDHS conducted anthropometry measurement and anemia testing. Women age 15-49 years and children age 0-59 months were eligible for anthropometry measurement in all households. In one-third of the sampled households, men age 15-59 were also eligible for anthropometry measurement. In this subsample, anemia testing was performed among consenting women age 15-49 and men age 15-59 years and among children age 6-59 months whose parents or guardians consented. Anthropometry. Height and weight measurements were recorded for children age 0-59 months, women age 15-49, and men age 15-59. Anemia testing. Blood specimens for anemia testing were collected from eligible women and men who voluntarily consented to be tested and from all children age 6-59 months for whom consent was obtained from their parents or the adult responsible for the children. Blood samples were obtained from a drop of blood taken from a finger prick (or a heel prick for children age 6-11 months). A drop of blood from the prick site was drawn into a microcuvette, and hemoglobin analysis was carried out on-site with a battery- operated portable HemoCue analyzer. Results were provided verbally and in writing. Parents of children with a hemoglobin level below 7 g/dl were instructed to take the child to a health facility for follow-up care. Likewise, nonpregnant women, pregnant women, and men were referred for follow-up care if their Households In 2/3 of HHs Survey among all Men age 15-59 + NCD age 30+ + additional questions for Youth age 15-24 In 1/3 of HHs Anthropometry among Children, Women, Men + Anemia testing among Children, Women, Men Survey among all Women age 15-49 + HIV knowledge/behavior + NCD age 30+ + Adult and Maternal Mortality Survey among all Women age 15-49 (no HIV knowledge/behavior) + Domestic Violence + Adult and Maternal Mortality + additional questions for Youth age 15-24 + Early Childhood Development Anthropometry among Children, Women, Men (no Anemia testing) no Men’s survey Introduction and Survey Methodology • 5 hemoglobin levels were below 9 g/dl, 7 g/dl, and 9 g/dl, respectively. All households in which anemia testing was conducted were given a brochure that explained the causes and prevention of anemia. 1.5 PRETEST Pretest training took place from 13 June to 6 July, 2016, at the GDS offices in Dili, Timor-Leste. The TLDHS technical team and The DHS Program staff trained 24 participants to administer the Household, Woman’s, Man’s, and Biomarker questionnaires with tablet computers, to take anthropometric measurements, and to collect blood samples for anemia testing. Participants were staff from GDS and the MOH. Classroom training addressed all aspects of the questionnaire content and interviewing procedures and included practice in taking anthropometric measurements and testing blood for anemia. Pretest fieldwork took place from July 7 through July 12 in eight clusters comprising a mixture of rural and urban settings near Dili (these clusters were not included in the 2016 TLDHS survey sample). After the fieldwork, on 13 July, a debriefing workshop was held to look at the issues emanating from the pretest. Feedback from the debriefing was used to finalize the questionnaires and to improve field logistics before the main training and the actual survey. 1.6 TRAINING OF TRAINERS Following the pretest, The DHS Program staff conducted a two-day training of trainers on 15-16 July 2016 with the participants of the pretest. Sessions highlighted adult learning principles and guidelines on conducting effective training. The participants worked in groups to develop lesson plans on questionnaire topics using various training techniques, for example, a slide presentation, flip charts, an interactive question- and-answer session, a case study, and role play. They were encouraged to develop participatory methods for the training. These participants were trained to be involved during the pretest, lead specific sessions during the main training, and also monitor the fieldwork of the survey. 1.7 TRAINING OF FIELD STAFF The TLDHS Main Training took place from 10 August to 13 September, 2016, at two government facilities in Dili, Timor-Leste, and was attended by 120 trainees, consisting of 80 women and 40 men. Questionnaire- related training included instruction on interviewing techniques and field procedures, questionnaire content, administering questionnaires via CAPI on tablet computers, and mock interviews between participants in the classroom. Biomarker-related training topics included lectures, demonstrations of measurement and testing procedures, and standardization of height and weight measurements. The training was led by the TLDHS technical team and DHS Program staff; guest speakers from the MOH, including the Head of Immunization, Malaria, Family Planning, and Nutrition among others, and from the GDS Geographic Information Systems (GIS) team supplemented the training. Three days of field practice were organized to provide trainees with additional hands-on practice before the actual fieldwork. Participants were evaluated through classwork, in-class exercises, quizzes, and observations conducted during field practice. The selection of supervisors and field editors was based on experience in leading survey teams and performance during the pretest and main training. Supervisors and field editors received additional instruction and practice on performing supervisory activities with the CAPI system. These activities included assigning households and receiving completed interviews from interviewers, recognizing and dealing with error messages, receiving a system update and distributing updates to interviewers, resolving duplicated cases, closing clusters, and transferring interviews to the central office via a secure Internet file streaming system (IFSS). In addition to training on the CAPI material, supervisors and field editors received instruction on their roles and responsibilities. 1.8 FIELDWORK Data collection was conducted by 20 field teams, each consisting of one supervisor, one editor, three female interviewers, one male interviewer, and one driver. Supervisors were responsible for the team, contacting local officials, locating and assigning the selected households, maintaining the pace of work, conducting 6 • Introduction and Survey Methodology household interviews as needed, and assisting with and providing oversight to anthropometry measurement. Editors were responsible for transferring questionnaires to interviewers, collecting completed questionnaires, resolving inconsistencies in questionnaires, completing the cluster data file, transferring data to the central office, and observing interviews. Interviewers were responsible for conducting household and individual interviews with eligible respondents, anthropometry measurement, and anemia testing. Electronic data files were collected from each interviewer’s tablet computer every day. Data were transferred to the central data processing office via IFSS. Staff from GDS, MOH, USAID, UNFPA, and The DHS Program coordinated and supervised fieldwork activities. Data collection took place over a 3-month period, from 16 September to 22 December, 2016. 1.9 DATA PROCESSING All electronic data files for the 2016 TLDHS were transferred via IFSS to the GDS central office in Dili, where they were stored on a password-protected computer. The data processing operation included registering and checking for inconsistencies, incompleteness, and outliers. Data editing and cleaning included structure and consistency checks to ensure completeness of work in the field. The central office also conducted secondary editing, which required resolution of computer-identified inconsistencies and coding of open-ended questions. The data were processed by two staff who took part in the main fieldwork training. Data editing was accomplished with CSPro software. Secondary editing and data processing were initiated in October 2016 and completed in February 2017. 1.10 RESPONSE RATES Table 1.1 shows response rates for the 2016 TLDHS. A total of 11,829 households were selected for the sample, of which 11,660 were occupied. Of the occupied households, 11,502 were successfully interviewed, which yielded a response rate of 99 percent. In the interviewed households, 12,998 eligible women were identified for individual interviews. Interviews were completed with 12,607 women, yielding a response rate of 97 percent. In the subsample of households selected for the men’s interviews, 4,878 eligible men were identified and 4,622 were successfully interviewed, yielding a response rate of 95 percent. Response rates were higher in rural than in urban areas, with the difference being more pronounced among men (97 percent versus 90 percent, respectively) than among women (98 percent versus 94 percent, respectively). The lower response rates for men were likely due to their more frequent and longer absences from the household. Table 1.1 Results of the household and individual interviews Number of households, number of interviews, and response rates, according to residence (unweighted), Timor-Leste DHS 2016 Residence Total Result Urban Rural Household interviews Households selected 3,355 8,474 11,829 Households occupied 3,288 8,372 11,660 Households interviewed 3,215 8,287 11,502 Household response rate1 97.8 99.0 98.6 Interviews with women age 15-49 Number of eligible women 4,592 8,406 12,998 Number of eligible women interviewed 4,337 8,270 12,607 Eligible women response rate2 94.4 98.4 97.0 Interviews with men age 15-59 Number of eligible men 1,666 3,212 4,878 Number of eligible men interviewed 1,497 3,125 4,622 Eligible men response rate2 89.9 97.3 94.8 1 Households interviewed/households occupied 2 Respondents interviewed/eligible respondents Housing Characteristics and Household Population • 7 HOUSING CHARACTERISTICS AND HOUSEHOLD POPULATION 2 Key Findings  Drinking water: 79% of households have access to an improved source of drinking water, including 92% of urban households and 74% of rural households.  Sanitation: 50% of households have access to an improved sanitation facility, including 75% of urban households and 43% of rural households.  Electricity: 73% of households have electricity, including 98% of urban households and 66% of rural households.  Household population: 41% of the household population is below the age of 15, and 26% are adolescents (age 10-19).  Orphanhood: 6% of children under age 18 are orphans (one or both parents dead).  School attendance: Among primary school age children, 86% of girls and boys are attending primary school. Among secondary school age children, 57% of boys and 66% of girls are attending secondary school. nformation on the socioeconomic characteristics of the household population in the 2016 TLDHS provides context to interpret demographic and health indicators and can furnish an approximate indication of the representativeness of the survey. In addition, this information sheds light on the living conditions of the population. This chapter presents information on source of drinking water, sanitation, exposure to smoke inside the home, wealth, hand washing, household population composition, family living arrangements, birth registration, educational attainment, and school attendance. 2.1 DRINKING WATER SOURCES AND TREATMENT Improved sources of drinking water Include piped water, public taps, standpipes, tube wells, boreholes, protected dug wells and springs, and rainwater. Households that use bottled water for drinking are classified as using an improved source only if their water source for cooking and handwashing comes from an improved source. Sample: Households Access to safe drinking water prevents diarrheal diseases and promotes public health. The 2016 TLDHS included questions to classify drinking water sources according to the framework developed by the WHO/UNICEF Joint Monitoring Programme for Water Supply, Sanitation and Hygiene (JMP), and to report on the Sustainable Development Goals in water and sanitation. Seventy-nine percent of households and 80% of the population have access to an improved source of drinking water (Table 2.1). Thirty-six percent of I 8 • Housing Characteristics and Household Population households have water piped into their dwelling, into their yard or plot, or a neighbor’s yard, 24% obtain water from a public tap or standpipe, 4% from a tube well or borehole, and 11% from a protected well or spring (Figure 2.1). Five percent of households use bottled water for drinking and use water from one of the improved sources listed above for other purposes such as cooking and handwashing. Twenty-one percent of households uses an unimproved source for drinking water, including 13% who obtain water from an unprotected spring, 4% from a surface water source such as a river or lake, and 3% from an unprotected well. Access to an improved source of drinking water is greater in urban than in rural areas (92% vs. 74%). The source of drinking water is on the premises for 66% of households; 18% of households obtain drinking water from a source less than 30 minutes away, and 14% of households obtain drinking water from a source that is at least 30 minutes away. Seventy-eight percent of households treat drinking water with an appropriate treatment method prior to drinking, usually by boiling it (Table 2.1). Trends: Access to an improved source of drinking water has increased from 63% in the 2009-10 TLDHS to 79% in the 2016 TLDHS. 2.2 SANITATION Improved toilet facilities Include any non-shared toilet of the following types: flush/pour flush toilets to piped sewer systems, septic tanks, and pit latrines; ventilated improved pit (VIP) latrines; pit latrines with slabs; and composting toilets Sample: Households As shown in Figure 2.2, 50% of households in Timor- Leste have access to an improved source of sanitation, 9% share a sanitation facility with other households, 14% use an unimproved sanitation facility, and 27% have no sanitation facility at all. Access to an improved sanitation facility is higher in urban than rural areas (75% compared with 42%). A toilet that flushes to a pit latrine is the most common type of improved sanitation facility (used by 19% of households), followed by a toilet that flushes to a septic tank (16%), and pit latrine with a slab (13%) (Table 2.3). Figure 2.1 Household drinking water by residence Figure 2.2 Household toilet facilities by residence 36 47 32 24 10 28 4 8 3 11 9 12 5 18 <1 21 8 26 Total Urban Rural Percent distribution of households by source of drinking water Unimproved source Bottled water (improved source for cooking/ handwashing) Protected well or spring Tube well or borehole Public tap/ standpipe Piped water into dwelling/ yard/plot/neighbor’s yard 50 75 42 9 13 7 14 10 16 27 3 35 Total Urban Rural No facility/ bush/field Unimproved facility Shared facility Improved facility Percent distribution of households by type of toilet facilities Housing Characteristics and Household Population • 9 Trends: The percentage of households with access to an improved sanitation facility has increased from 41% in the 2009-10 TLDHS to 50% in the 2016 TLDHS. The percentage of households resorting to open defecation has declined from 37% to 27% and has declined in both urban and rural areas. 2.3 EXPOSURE TO SMOKE INSIDE THE HOME Exposure to smoke inside the home, either from cooking with solid fuels or from smoking tobacco, has potentially harmful health effects. Eighty-seven percent of households use solid fuels, consisting mostly of firewood, for cooking. Use of solid fuels for cooking is more common in rural areas (95%) than in urban areas (58%) (Table 2.4). Exposure to cooking smoke is greater when cooking takes place inside the house. In Timor-Leste, 62% of households cook outdoors under a cover, 14% cook outdoors, and 12% each cook in a separate building and inside the house. Exposure to tobacco smoke is high in Timor-Leste. In 51% of households, someone smokes inside the house on a daily basis. Someone smokes in the house at least once a week in 15% of households, and at least once a month and less than once a month in 2% of households each. In 31% of households, no one ever smokes inside the house. Other Housing Characteristics Overall, 73% of households in Timor-Leste have electricity, including 98% of urban households and 66% of rural households (Table 2.4). The most common flooring material is earth or sand (51%), followed by cement (36%). 2.4 HOUSEHOLD WEALTH Household Durable Goods The 2016 TLDHS collected information about household effects, means of transportation, and ownership of agricultural land and farm animals. As shown in Table 2.5, 84% of households own a mobile phone, 40% own a television, 25% own a radio, and 20% own a refrigerator. The most common means of transport is a motorcycle or scooter, owned by 32% of households; 15% of households own a bicycle. Overall, 65% of households own agricultural land, including 21% of urban households and 79% of rural households. Most households own farm animals regardless of residence (60% of urban households and 90% of rural households). Wealth Index Wealth index Households are given scores based on the number and kinds of consumer goods they own, ranging from a television to a bicycle or car, and housing characteristics such as source of drinking water, toilet facilities, and flooring materials. These scores are derived using principal component analysis. National wealth quintiles are compiled by assigning the household score to each usual (de jure) household member, ranking each person in the household population by their score, and then dividing the distribution into five equal categories, each with 20% of the population. Sample: Households Table 2.6 presents the distribution of the de jure household population by wealth quintile according to residence and municipality. Also included is the Gini coefficient, a measure of the equity of wealth distribution. The Gini coefficient ranges from 0 to 1 with higher values reflecting a less equitable distribution of wealth. 10 • Housing Characteristics and Household Population Patterns by background characteristics  Urban households are more likely than rural households to fall into the higher wealth quintiles, while rural households are more likely to fall into the lower wealth quintiles. Eighty-six percent of urban households are included in the highest two wealth quintiles, whereas 53% of rural households are included in the lowest two (Figure 2.3).  The municipality with the greatest percentage of households in the highest wealth quintile is Dili (60%). By contrast, 46% of households in SAR of Oecussi are in the lowest wealth quintile. 2.5 HANDWASHING Handwashing is an important step in improving hygiene and preventing the spread of disease. Rather than asking direct questions on the practice of handwashing, which can be subject to over-reporting, interviewers in the 2016 TLDHS asked to see the place where members of the household most often washed their hands. A place for washing hands was observed in 90% of households (Table 2.7). Interviewers observed the presence of soap and water in 28% of the households where a place for handwashing was observed. Five percent of these handwashing locations had water but no soap, 31% had soap but no water, and 36% had neither soap nor water. 2.6 HOUSEHOLD POPULATION AND COMPOSITION Household A person or group of related or unrelated persons who live together in the same dwelling unit(s), who acknowledge one adult male or female as the head of the household, who share the same housekeeping arrangements, and who are considered a single unit. De facto population All persons who stayed in the selected households the night before the interview (whether usual residents or visitors). De jure population All persons who are usual residents of the selected households, whether or not they stayed in the household the night before the interview. How data are calculated All tables are based on the de facto population, unless specified otherwise. A total of 59,960 individuals stayed overnight in the 11,502 households interviewed in the 2016 TLDHS, among whom 50% were male and 50% were female (Table 2.8). The population pyramid in Figure 2.4 illustrates the distribution of the population by 5-year age groups and by sex. The broad base of the pyramid is typical of a young population characterized by high fertility. Children under the age of 15 comprise 41% of the population, and adolescents age 10-19 make up just over one-quarter (26%). The large bar at age 10- 14 years indicates that there may have been some displacement of eligible household members age 15 and above into the 10-14 group and out of the age range eligible for interview. Figure 2.3 Household wealth by residence 2 273 26 9 24 30 16 56 6 Urban Rural* Percent distribution of de jure population by wealth quintiles Wealthiest Fourth Middle Second Poorest * Does not add to 100% due to rounding. Housing Characteristics and Household Population • 11 Eighteen percent of households are headed by women (Table 2.9), and the average household consists of 5.3 usual members. Urban households are on average one person larger than rural households (6.0 vs. 5.0 persons per household). Trends: The percentage of the population below age 15 has been decreasing gradually over time, from 51% in the 2003 DHS, to 45% in the 2009-10 TLDHS, to 41% in the current survey. 2.7 CHILDREN’S LIVING ARRANGEMENTS AND PARENTAL SURVIVAL Orphan A child with one or both parents who are dead. Sample: Children under age 18 Over three-quarters (77%) of children under the age of 18 live with both biological parents (Table 2.10). Ten percent of children under the age of 18 does not live with a biological parent. For most of these fostered children, both of their biological parents are alive. An additional 9% of children live with their mother but not their father. For 6% of children, at least one biological parent has died. The percentage of children who do not live with a biological parent, or with one or both parents dead, increases with age. Fostering is highest in Baucau, while orphanhood is most common in Ainaro. Fostering increases with wealth quintile; by contrast, orphanhood is inversely associated with wealth. Trends: Fostering and orphanhood among children under age 18 are similar in the 2009-10 and 2016 TLDHS. Nine percent of children under age 18 did not live with a biological parent in the 2009-10 survey, compared with 10% of children in the 2016 survey. At least one biological parent was dead for 7% of children under age 18 in the 2009-10 survey, compared with 6 percent in the 2016 survey. 2.8 BIRTH REGISTRATION Registered birth Child has a birth certificate or child does not have a birth certificate, but his/her birth is registered with the civil authorities. Sample: De jure children under age 5 Table 2.11 includes information on the percentage of children under age 5 who have a birth certificate, and who do not have a birth certificate but whose birth has been registered with the civil authorities. Overall, 60% of children under age 5 had their births registered with the civil authority; this includes 34% with a birth certificate, and 27% whose birth was registered but who do not have a birth certificate. Trends: Birth registration has increased slightly from 55% in the 2009-10 TLDHS to 60% in the present survey. However, the percentage of children with a birth certificate has decreased from 41% in 2009-10 to 34% in 2016. Figure 2.4 Population pyramid 10 6 2 2 6 10 <5 5-9 10-14 15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59 60-64 65-69 70-74 75-79 80+ Age Percent distribution of the household population Male Female 261210 12 • Housing Characteristics and Household Population Patterns by background characteristics  Birth registration is higher among children age 2-4 than among children under age 2, suggesting that births are often registered when the child is a few years old rather than at the time of birth.  Children in urban areas are more likely than those in rural areas to have their births registered (66% vs. 58%).  Birth registration ranges from 38% in Liquiçá to 75% in Ermera. Birth registration increases from 55% in the lowest wealth quintile to 69% in the highest wealth quintile (Figure 2.5). 2.9 EDUCATION 2.9.1 Educational Attainment Median educational attainment Half of the population has completed less than the median number of years of schooling, and half of the population has completed more than the median number of years of schooling. Sample: De facto household population age 6 and older Tables 2.12.1 and 2.12.2 present information on educational attainment of the household population age 6 and over for women and men, respectively. Overall 30% of women and girls age 6 and over have never been to school, 28% percent attended some primary school, 5% completed primary but advanced no further, 21% attended some secondary school, 11% completed secondary school but advanced no further, and 6% attained some education after secondary school. The median years of schooling completed for women and girls age 6 and over is 3.5. Educational attainment of men is similar to that of women. Twenty-three percent of men and boys age 6 and over have never attended school, 34% attended some primary school, 5% completed primary school, 20% attended some secondary school, 12% completed secondary school, and 7% attained some education after secondary school. The median years of schooling completed for men and boys age 6 and over is 3.9. Trends: The percentage of women age 6 and over who have never attended school has decreased from 37% in the 2009-10 TLDHS to 30% in the 2016 TLDHS, and the median number of years of schooling has increased from 1.8 to 3.5. Among men age 6 and over, the percentage who have never attended school has decreased from 30% to 23%, and the median years of schooling has increased from 2.7 to 3.9. Patterns by background characteristics  Twenty-four percent of girls age 6-9 years have never attended school. This percentage drops to 4% among girls age 10-14 and then steadily increases to 95% among women age 65 or over. A similar pattern is observed among men.  The median years of schooling completed is greatest among women age 20-24 (11.0 years) and 25-29 (10.0 years), and among men age 20-34, at around 11 years. Figure 2.5 Birth registration by household wealth 55 57 58 64 69 Lowest Second Middle Fourth Highest Percentage of de jure children under age 5 whose births are registered with the civil authorities Poorest Wealthiest Housing Characteristics and Household Population • 13  Educational attainment ranges widely across municipalities. The median years of schooling is highest among women and men in Dili (8.3 years each), and lowest in Ermera—0.2 years among women and 1.8 years among men.  The percentage of women and men who have attended more than secondary school increases by wealth from the first to the fourth quintile. There is a big jump in the percentage who have attended more than secondary school between women in the fourth quintile (6%) and those in the highest quintile (20%) among women. A similar pattern exists among men. Pre-primary school attendance Tables 2.13.1 and 2.13.2 present information on pre-primary school attendance among boys and girls age 3- 5 years. Eighteen percent of girls and 16% of boys age 3-5 have ever attended pre-primary school. Pre- primary school attendance is higher in urban than in rural areas—23% versus 16% among girls and 21% versus 14% among boys. By municipality, pre-primary school attendance ranges from 8% in Baucau to 34% in Viqueque among girls, and from 7% in Ermera to 27% in Viqueque among boys. Pre-primary school attendance also increases with wealth quintile. 2.9.2 School Attendance Net attendance ratios (NAR) Percentage of the school-age population that attends primary or secondary school. Sample: Children age 6-11 for primary school NAR and children age 12-17 for secondary school NAR Gross attendance ratios (GAR) The total number of children attending primary school divided by the official primary school age population and the total number of children attending secondary school divided by the official secondary school age population. Sample: Children age 6-11 for primary school GAR and children age 12-17 for secondary school GAR School attendance ratios are shown in Table 2.14. Eighty-six percent of girls and boys of primary school age are currently attending primary school. The GAR for primary school is 119 for boys and 114 for girls. Among girls and boys of secondary school age, 57% of boys are attending secondary school compared with 66% of girls. Overall, 61% of children of secondary school age are attending secondary school. The GAR for secondary school is 76 for boys, 82 for girls, and 79 overall. Gender Parity Indices (GPI) The ratio of female to male students attending primary school and the ratio of female to male students attending secondary school. The index reflects the magnitude of the gender gap. Sample: Primary school students and secondary school students The GPI for the GAR for primary school is 0.96, indicating that in primary school, there are slightly more male students than female students. However, for secondary school, the GPI for the GAR is greater than 1.0 (1.08), indicating that in secondary school, females outnumber males. Patterns by background characteristics  The NAR for primary school is slightly higher in urban than in rural areas (89% vs. 85%), increases with wealth and ranges from 75% in Ermera to 91% in Viqueque. 14 • Housing Characteristics and Household Population  The NAR for secondary school is higher in urban areas than rural areas. By municipality, the NAR for secondary school increases from 44% in SAR of Oecussi to 77% in Dili. The secondary school NAR increases according to wealth quintile from 41% to 87% for girls and from 36% to 82% for boys (Figure 2.6).  By municipality, the GPI for the GAR for primary school ranges from 0.90 in Liquiçá to 1.05 in SAR of Oecussi. The GPI for secondary school is less than 1.0 only in Ermera (0.99), and is highest in Manatuto (1.19). LIST OF TABLES For more information on household population and housing characteristics, see the following tables:  Table 2.1 Household drinking water  Table 2.2 Availability of water  Table 2.3 Household sanitation facilities  Table 2.4 Household characteristics  Table 2.5 Household possessions  Table 2.6 Wealth quintiles  Table 2.7 Handwashing  Table 2.8 Household population by age, sex, and residence  Table 2.9 Household composition  Table 2.10 Children’s living arrangements and orphanhood  Table 2.11 Birth registration of children under age 5  Table 2.12.1 Educational attainment of the female household population  Table 2.12.2 Educational attainment of the male household population  Table 2.13.1 Pre-primary school attendance: Females  Table 2.13.2 Pre-primary school attendance: Males  Table 2.14 School attendance ratios Figure 2.6 Secondary school net attendance ratio by household wealth 41 52 65 76 87 36 47 50 64 82 Lowest Second Middle Fourth Highest Girls Boys WealthiestPoorest Net attendance ratio for secondary school among children age 12-17 Housing Characteristics and Household Population • 15 Table 2.1 Household drinking water Percent distribution of households and de jure population by source of drinking water, time to obtain drinking water, and treatment of drinking water, according to residence, Timor-Leste DHS 2016 Characteristic Households Population Urban Rural Total Urban Rural Total Source of drinking water Improved source 91.9 74.4 78.6 92.1 75.1 79.8 Piped into dwelling/yard plot 43.5 29.0 32.5 43.3 30.3 33.9 Piped to neighbor 3.4 3.1 3.2 3.1 3.1 3.1 Public tap/standpipe 10.0 27.8 23.6 9.3 27.3 22.4 Tube well or borehole 7.9 2.5 3.8 8.9 2.5 4.2 Protected dug well 8.5 5.1 5.9 7.8 5.3 6.0 Protected spring 0.7 6.5 5.2 0.7 6.2 4.7 Rain water 0.1 0.1 0.1 0.1 0.1 0.1 Bottled water, improved source for cooking/handwashing1 17.8 0.3 4.5 18.8 0.4 5.4 Unimproved source 6.1 25.5 20.9 5.7 24.8 19.6 Unprotected dug well 2.2 3.8 3.4 1.8 4.1 3.4 Unprotected spring 0.9 16.2 12.5 0.8 15.5 11.5 Tanker truck/cart with small tank 2.0 0.6 0.9 1.9 0.6 0.9 Surface water 0.4 4.7 3.7 0.4 4.5 3.4 Bottled water, unimproved source for cooking/handwashing1 0.7 0.2 0.3 0.9 0.2 0.4 Bottled water, unknown source for cooking/handwashing 1.9 0.1 0.5 2.2 0.0 0.6 Total 100.0 100.0 100.0 100.0 100.0 100.0 Time to obtain drinking water (round trip) Water on premises2 89.1 58.6 65.9 90.1 60.6 68.7 Less than 30 minutes 5.9 21.1 17.5 5.5 19.5 15.7 30 minutes or longer 4.4 17.3 14.2 3.7 17.0 13.3 Don’t know/missing 0.7 3.0 2.5 0.8 2.9 2.3 Total 100.0 100.0 100.0 100.0 100.0 100.0 Person who usually collects drinking water Adult male 15+ 3.3 11.2 9.3 2.6 10.1 8.1 Adult female 15+ 5.9 25.6 20.9 5.6 24.5 19.3 Male child under age 15 0.4 1.8 1.5 0.3 1.9 1.4 Female child under age 15 0.8 2.6 2.2 0.9 2.8 2.3 Other 0.6 0.1 0.2 0.6 0.1 0.2 Water on premises2 89.1 58.6 65.9 90.1 60.6 68.7 Total 100.0 100.0 100.0 100.0 100.0 100.0 Water treatment prior to drinking3 Boiled 67.6 80.1 77.1 66.5 80.9 76.9 Bleach/chlorine added 2.4 0.7 1.1 2.5 0.7 1.2 Strained through cloth 42.0 38.5 39.3 41.7 38.8 39.6 Ceramic, sand or other filter 1.5 0.3 0.6 1.5 0.3 0.6 Solar disinfection 0.2 0.4 0.4 0.2 0.4 0.3 Let it stand and settle 4.9 11.5 10.0 5.0 11.2 9.5 Other 3.2 0.2 0.9 2.8 0.2 0.9 No treatment 20.6 11.6 13.7 21.8 10.9 13.9 Percentage using an appropriate treatment method4 70.3 80.5 78.1 69.2 81.3 78.0 Number 2,744 8,758 11,502 16,539 44,030 60,569 1 Because the quality of bottled water is not known, households using bottled water for drinking are classified as using an improved or unimproved source according to their water source for cooking and washing. 2 Includes water piped to a neighbor 3 Respondents may report multiple treatment methods so the sum of treatment may exceed 100 percent. 4 Appropriate water treatment methods include boiling, bleaching, filtering, and solar disinfecting. 16 • Housing Characteristics and Household Population Table 2.2 Availability of water Among households and de jure population using piped water or water from a tube well or borehole, percentage with lack of availability of water in the last 2 weeks, according to residence, Timor-Leste DHS 2016 Availability of water in last 2 weeks Households Population Urban Rural Total Urban Rural Total Not available for at least one day 43.4 35.8 38.0 41.8 37.5 38.9 Available with no interruption of at least one day 53.0 62.9 60.0 54.0 61.3 58.9 Don’t know/missing 3.6 1.3 2.0 4.2 1.3 2.2 Total 100.0 100.0 100.0 100.0 100.0 100.0 Number using piped water or water from a tube well1 2,249 5,489 7,737 13,674 27,971 41,645 1 Includes households reporting piped water or water from a tube well or borehole as their main source of drinking water and households reporting bottled water as their main source of drinking water if their main source of water for cooking and handwashing is piped water or water from a tube well or borehole. Table 2.3 Household sanitation facilities Percent distribution of households and de jure population by type of toilet/latrine facilities and percent distribution of households and de jure population with a toilet/latrine facility by location of the facility, according to residence, Timor-Leste DHS 2016 Type and location of toilet/latrine facility Households Population Urban Rural Total Urban Rural Total Improved sanitation 74.5 42.4 50.1 76.0 45.4 53.8 Flush/pour flush to septic tank 32.3 10.7 15.8 32.0 11.6 17.2 Flush/pour flush to pit latrine 25.8 16.3 18.5 28.3 17.9 20.8 Ventilated improved pit (VIP) latrine 4.5 1.3 2.0 4.5 1.4 2.2 Pit latrine with slab 11.9 13.2 12.9 11.2 13.4 12.8 Composting toilet 0.1 1.0 0.8 0.1 1.0 0.8 Unimproved sanitation 25.5 57.6 49.9 24.0 54.6 46.2 Shared facility1 13.0 7.2 8.5 12.0 7.1 8.4 Flush/pour flush to septic tank 3.9 1.7 2.2 3.6 1.7 2.2 Flush/pour flush to pit latrine 5.6 3.0 3.6 5.4 3.1 3.7 Ventilated improved pit (VIP) latrine 1.1 0.5 0.6 1.1 0.4 0.6 Pit latrine with slab 2.4 1.9 2.0 1.9 1.8 1.8 Composting toilet 0.0 0.1 0.1 0.0 0.0 0.0 Unimproved facility 9.9 15.6 14.2 9.6 15.6 13.9 Flush/pour flush not to sewer/septic tank/pit latrine 8.0 5.7 6.2 7.9 5.9 6.4 Pit latrine without slab/open pit 0.5 1.7 1.4 0.4 1.9 1.5 Bucket 0.6 0.9 0.9 0.7 0.9 0.9 Hanging toilet/hanging latrine 0.8 7.3 5.7 0.6 6.9 5.2 Open defecation (no facility/bush/ field) 2.6 34.8 27.1 2.3 31.9 23.9 Total 100.0 100.0 100.0 100.0 100.0 100.0 Number of households/population 2,744 8,758 11,502 16,539 44,030 60,569 Location of the facility In own dwelling 73.1 48.1 56.1 73.8 48.3 57.3 In own yard/plot 22.8 36.5 32.1 22.8 37.4 32.3 Elsewhere 4.0 15.3 11.7 3.4 14.3 10.5 Total 100.0 100.0 100.0 100.0 100.0 100.0 Number of households/population with a toilet/latrine facility 2,673 5,708 8,382 16,153 29,971 46,123 1 Facilities that would be considered improved if they were not shared by two or more households. Housing Characteristics and Household Population • 17 Table 2.4 Household characteristics Percent distribution of households and de jure population by housing characteristics, percentage using solid fuel for cooking, percentage using clean fuel for cooking, and percent distribution by frequency of smoking in the home, according to residence, Timor-Leste DHS 2016 Housing characteristic Households Population Urban Rural Total Urban Rural Total Electricity Yes 98.1 65.5 73.3 98.4 68.3 76.5 No 1.9 34.5 26.7 1.6 31.7 23.5 Total 100.0 100.0 100.0 100.0 100.0 100.0 Flooring material Earth, sand 15.7 62.3 51.2 14.2 61.0 48.2 Dung 0.5 0.7 0.7 0.5 0.6 0.6 Wood/planks 0.2 2.0 1.6 0.2 1.3 1.0 Palm/bamboo 0.1 1.0 0.8 0.2 0.9 0.7 Parquet or polished wood 0.0 0.1 0.1 0.0 0.1 0.1 Vinyl or asphalt strips 0.0 0.1 0.1 0.1 0.1 0.1 Ceramic tiles 28.6 3.8 9.7 31.0 4.2 11.5 Cement 54.4 29.9 35.8 53.5 31.8 37.7 Carpet 0.5 0.1 0.2 0.3 0.1 0.1 Total 100.0 100.0 100.0 100.0 100.0 100.0 Rooms used for sleeping One 8.1 15.0 13.4 5.3 10.7 9.2 Two 25.2 30.2 29.0 21.2 27.4 25.7 Three or more 66.7 54.8 57.6 73.5 61.9 65.1 Total 100.0 100.0 100.0 100.0 100.0 100.0 Place for cooking In the house 23.4 8.1 11.8 21.6 6.4 10.5 In a separate building 19.8 9.9 12.3 19.8 9.7 12.5 Outdoors 13.3 14.2 14.0 13.3 14.0 13.8 Outdoors under cover 43.5 67.8 62.0 45.4 69.9 63.2 Total 100.0 100.0 100.0 100.0 100.0 100.0 Cooking fuel Electricity 21.3 4.1 8.2 18.7 4.0 8.0 LPG/natural gas/biogas 3.3 0.1 0.9 3.1 0.1 0.9 Kerosene 17.1 0.5 4.4 16.3 0.4 4.8 Charcoal 0.1 0.0 0.0 0.1 0.0 0.1 Wood 58.1 95.3 86.4 61.5 95.4 86.1 Straw/shrubs/grass 0.0 0.0 0.0 0.0 0.0 0.0 Agricultural crop 0.1 0.0 0.0 0.2 0.0 0.0 Total 100.0 100.0 100.0 100.0 100.0 100.0 Percentage using solid fuel for cooking1 58.3 95.3 86.5 61.8 95.5 86.3 Percentage using clean fuel for cooking2 24.6 4.2 9.1 21.8 4.1 9.0 Frequency of smoking in the home Daily 47.5 52.3 51.2 49.9 56.6 54.8 Weekly 11.2 14.6 13.8 11.4 14.9 13.9 Monthly 1.7 1.9 1.8 1.7 1.8 1.7 Less than once a month 2.4 2.1 2.1 3.0 1.9 2.2 Never 37.2 29.2 31.1 34.0 24.9 27.4 Total 100.0 100.0 100.0 100.0 100.0 100.0 Number of households/population 2,744 8,758 11,502 16,539 44,030 60,569 LPG = Liquefied petroleum gas 1 Includes charcoal, wood, straw/shrubs/grass, agricultural crops, and animal dung 2 Includes electricity and LPG/natural gas/biogas 18 • Housing Characteristics and Household Population Table 2.5 Household possessions Percentage of households possessing various household effects, means of transportation, agricultural land and livestock/farm animals by residence, Timor-Leste DHS 2016 Possession Residence Total Urban Rural Household effects Radio 33.6 21.6 24.5 Television 79.9 27.8 40.2 Mobile phone 96.1 80.5 84.3 Non-mobile telephone 13.7 8.3 9.6 Computer 32.8 4.0 10.9 Refrigerator 52.8 9.2 19.6 Means of transport Bicycle 32.6 8.9 14.6 Animal drawn cart 2.4 0.3 0.8 Motorcycle/scooter 60.7 22.7 31.8 Car/truck 14.2 2.0 4.9 Boat with a motor 1.0 0.5 0.6 Ownership of agricultural land 21.3 78.9 65.2 Ownership of farm animals1 60.4 89.9 82.9 Number 2,744 8,758 11,502 1 Buffalo, cows, bulls, horses, donkeys, mules, goats, sheep, pigs, chickens, ducks, or other poultry Table 2.6 Wealth quintiles Percent distribution of the de jure population by wealth quintiles, and the Gini Coefficient, according to residence and municipality, Timor-Leste DHS 2016 Residence/region Wealth quintile Total Number of persons Gini coefficient Lowest Second Middle Fourth Highest Residence Urban 1.5 3.4 8.8 30.0 56.2 100.0 16,539 0.11 Rural 26.9 26.2 24.2 16.3 6.4 100.0 44,030 0.25 Municipality Aileu 16.6 33.3 27.2 17.1 5.9 100.0 2,357 0.21 Ainaro 35.0 27.1 20.8 13.5 3.7 100.0 3,076 0.15 Baucau 20.0 22.4 22.5 22.6 12.6 100.0 6,994 0.23 Bobonaro 15.6 22.0 29.8 22.5 10.0 100.0 4,797 0.23 Covalima 24.4 18.9 24.8 20.8 11.1 100.0 3,569 0.15 Dili 2.9 4.4 6.8 26.0 59.8 100.0 12,625 0.18 Ermera 30.0 32.8 21.9 11.2 4.1 100.0 5,818 0.27 Lautem 15.1 20.9 25.4 26.5 12.2 100.0 3,374 0.21 Liquiçá 17.0 28.3 24.1 18.8 11.9 100.0 3,966 0.28 Manatuto 18.7 19.3 25.5 21.7 14.9 100.0 2,795 0.26 Manufahi 24.2 22.7 20.2 21.6 11.3 100.0 3,201 0.27 SAR of Oecussi 45.7 18.7 16.8 10.6 8.2 100.0 3,985 0.25 Viqueque 30.3 22.0 24.3 15.0 8.3 100.0 4,012 0.27 Total 20.0 20.0 20.0 20.0 20.0 100.0 60,569 0.16 Housing Characteristics and Household Population • 19 Table 2.7 Handwashing Percentage of households in which the place most often used for washing hands was observed by whether the location was fixed or mobile and total percentage of households in which the place for handwashing was observed; and among households in which the place for handwashing was observed, percent distribution by availability of water, soap and other cleansing agents, according to background characteristics, Timor-Leste DHS 2016 Background characteristic Percentage of households in which place for washing hands was observed: Number of house- holds Among households in which place for handwashing was observed, percentage with: Number of house- holds in which a place for hand- washing was observed And place for hand- washing was a fixed place And place for hand- washing was mobile Total Soap and water1 Water and cleansing agent other than soap only2 Water only Soap but no water3 Cleansing agent other than soap only2 No water, no soap, no other cleansing agent Total Residence Urban 44.1 49.9 93.9 2,744 43.2 0.0 5.0 28.4 0.0 23.4 100.0 2,578 Rural 22.5 66.2 88.7 8,758 22.9 0.1 4.6 32.1 0.1 40.2 100.0 7,767 Municipality Aileu 40.6 50.9 91.5 414 26.2 0.1 10.3 34.6 0.1 28.7 100.0 379 Ainaro 17.1 64.7 81.7 617 10.7 0.0 1.3 42.3 0.2 45.5 100.0 504 Baucau 30.3 58.0 88.3 1,383 33.8 0.0 3.4 29.8 0.0 33.0 100.0 1,222 Bobonaro 25.4 62.9 88.3 953 29.6 0.0 1.8 37.9 0.0 30.8 100.0 841 Covalima 27.7 49.5 77.3 787 34.9 0.0 1.6 39.6 0.4 23.5 100.0 608 Dili 43.2 51.3 94.5 2,016 38.6 0.0 5.6 27.6 0.0 28.2 100.0 1,905 Ermera 36.7 63.1 99.7 1,175 35.5 0.0 4.4 26.0 0.0 34.1 100.0 1,172 Lautem 21.5 70.5 92.0 695 23.0 0.4 7.8 23.3 0.9 44.5 100.0 639 Liquiçá 19.6 73.6 93.2 721 23.1 0.0 5.1 31.5 0.0 40.4 100.0 672 Manatuto 10.9 88.2 99.1 505 10.1 0.0 1.2 44.9 0.0 43.7 100.0 501 Manufahi 24.6 50.5 75.1 556 23.9 0.0 5.1 26.8 0.0 44.2 100.0 417 SAR of Oecussi 18.0 67.6 85.5 883 25.3 0.8 8.4 35.0 0.2 30.2 100.0 755 Viqueque 10.9 80.4 91.3 798 9.7 0.0 5.4 22.4 0.0 62.5 100.0 729 Time to obtain drinking water (round trip) Water on premises4 32.3 59.9 92.2 7,576 32.3 0.0 4.6 30.7 0.1 32.2 100.0 6,984 Less than 30 minutes 20.9 65.0 86.0 2,008 21.3 0.2 6.9 31.6 0.0 39.9 100.0 1,726 30 minutes or longer 14.9 68.8 83.7 1,636 16.4 0.2 2.7 31.4 0.2 49.1 100.0 1,369 Don’t know/missing 25.6 68.4 94.0 282 16.2 0.1 2.9 38.6 0.0 42.2 100.0 265 Wealth quintile Lowest 13.5 69.4 82.8 2,802 12.3 0.2 5.1 26.7 0.2 55.4 100.0 2,320 Second 20.7 68.3 89.0 2,417 19.8 0.1 6.1 31.0 0.1 42.8 100.0 2,152 Middle 27.0 64.5 91.5 2,288 26.1 0.1 4.4 34.7 0.1 34.6 100.0 2,094 Fourth 30.8 62.8 93.6 2,079 31.5 0.1 3.9 37.5 0.0 27.0 100.0 1,946 Highest 54.7 41.0 95.7 1,916 55.7 0.0 3.7 26.2 0.0 14.5 100.0 1,833 Total 27.7 62.3 89.9 11,502 28.0 0.1 4.7 31.2 0.1 36.0 100.0 10,345 1 Soap includes soap or detergent in bar, liquid, powder or paste form. This column includes households with soap and water only as well as those that had soap and water and another cleansing agent. 2 Cleansing agents other than soap include locally available materials such as ash, mud or sand 3 Includes households with soap only as well as those with soap and another cleansing agent 4 Includes water piped to a neighbor 20 • Housing Characteristics and Household Population Table 2.8 Household population by age, sex, and residence Percent distribution of the de facto household population by five-year age groups, according to sex and residence, Timor-Leste DHS 2016 Age Urban Rural Total Total Male Female Total Male Female Total Male Female <5 13.5 12.0 12.8 13.0 12.3 12.7 13.1 12.2 12.7 5-9 12.2 11.9 12.0 14.3 13.4 13.9 13.7 13.0 13.4 10-14 13.3 12.4 12.9 16.2 15.4 15.8 15.4 14.6 15.0 15-19 12.6 12.6 12.6 10.3 9.2 9.7 10.9 10.1 10.5 20-24 9.8 11.5 10.6 6.0 6.0 6.0 7.1 7.5 7.3 25-29 7.7 9.0 8.3 5.0 6.1 5.6 5.7 6.9 6.3 30-34 7.4 7.8 7.6 5.3 5.5 5.4 5.9 6.1 6.0 35-39 4.4 4.6 4.5 3.4 3.7 3.5 3.7 3.9 3.8 40-44 5.0 4.5 4.7 4.9 5.0 4.9 4.9 4.9 4.9 45-49 4.0 3.5 3.8 4.5 3.8 4.2 4.4 3.7 4.0 50-54 3.1 3.3 3.2 3.8 4.9 4.3 3.6 4.5 4.0 55-59 2.0 1.7 1.9 2.6 3.1 2.9 2.5 2.7 2.6 60-64 2.1 1.7 1.9 3.6 3.4 3.5 3.2 2.9 3.1 65-69 0.9 1.1 1.0 3.2 3.6 3.4 2.6 2.9 2.7 70-74 0.6 0.9 0.7 2.1 2.2 2.1 1.7 1.8 1.7 75-79 0.4 0.4 0.4 1.1 1.1 1.1 0.9 0.9 0.9 80 + 0.2 0.4 0.3 0.7 1.1 0.9 0.6 0.9 0.7 Don’t know/missing 0.7 0.8 0.8 0.1 0.2 0.2 0.3 0.4 0.3 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Dependency age groups 0-14 39.0 36.3 37.7 43.4 41.2 42.3 42.2 39.9 41.0 15-64 58.2 60.2 59.2 49.3 50.8 50.0 51.8 53.3 52.5 65+ 2.1 2.7 2.4 7.1 7.9 7.5 5.7 6.5 6.1 Don’t know/missing 0.7 0.8 0.8 0.1 0.2 0.2 0.3 0.4 0.3 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Child and adult populations 0-17 46.8 44.2 45.5 50.4 47.4 48.9 49.4 46.5 48.0 18+ 52.4 55.0 53.7 49.5 52.4 51.0 50.3 53.1 51.7 Don’t know/missing 0.7 0.8 0.8 0.1 0.2 0.2 0.3 0.4 0.3 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Adolescents 10-19 25.9 25.0 25.5 26.4 24.6 25.5 26.3 24.7 25.5 Number of persons 8,260 8,014 16,274 21,763 21,924 43,687 30,022 29,938 59,960 Housing Characteristics and Household Population • 21 Table 2.9 Household composition Percent distribution of households by sex of head of household and by household size; mean size of household, and percentage of households with orphans and foster children under 18 years of age, according to residence, Timor-Leste DHS 2016 Characteristic Residence Total Urban Rural Household headship Male 84.8 81.8 82.5 Female 15.2 18.2 17.5 Total 100.0 100.0 100.0 Number of usual members 0 0.0 0.0 0.0 1 3.9 7.2 6.4 2 5.8 10.0 9.0 3 10.0 12.2 11.6 4 13.0 14.5 14.1 5 14.4 15.8 15.5 6 15.5 14.3 14.6 7 11.8 10.6 10.9 8 9.3 7.2 7.7 9+ 16.3 8.3 10.2 Total 100.0 100.0 100.0 Mean size of households 6.0 5.0 5.3 Percentage of households with orphans and foster children under 18 years of age Double orphans 0.8 0.7 0.7 Single orphans1 7.7 8.3 8.2 Foster children2 20.9 16.0 17.2 Foster and/or orphan children 24.4 21.1 21.9 Number of households 2,744 8,758 11,502 Note: Table is based on de jure household members, i.e., usual residents. 1 Includes children with one dead parent and an unknown survival status of the other parent. 2 Foster children are those under age 18 living in households with neither their mother nor their father present, and the mother and/or the father are alive. 22 • Housing Characteristics and Household Population Table 2.10 Children’s living arrangements and orphanhood Percent distribution of de jure children under age 18 by living arrangements and survival status of parents, the percentage of children not living with a biological parent, and the percentage of children with one or both parents dead, according to background characteristics, Timor-Leste DHS 2016 Background characteristic Living with both parents Living with mother but not with father Living with father but not with mother Not living with either parent Total Percent- age not living with a biolo- gical parent Percent- age with one or both parents dead1 Number of children Father alive Father dead Mother alive Mother dead Both alive Only father alive Only mother alive Both dead Missing inform- ation on father/ mother Age 0-4 80.4 10.8 1.3 1.3 0.4 5.0 0.2 0.3 0.1 0.1 100.0 5.7 2.3 7,628 <2 80.6 13.6 1.1 1.1 0.1 2.9 0.3 0.1 0.0 0.1 100.0 3.4 1.6 3,033 2-4 80.3 9.0 1.4 1.4 0.6 6.4 0.2 0.5 0.2 0.1 100.0 7.2 2.8 4,595 5-9 79.5 6.0 2.3 2.0 1.2 7.8 0.5 0.4 0.3 0.0 100.0 9.0 4.7 8,023 10-14 75.7 4.1 4.0 2.4 2.2 9.1 1.0 1.0 0.5 0.1 100.0 11.6 8.6 8,997 15-17 66.6 3.3 5.9 2.2 2.4 15.5 1.8 1.5 0.7 0.1 100.0 19.6 12.3 4,161 Sex Male 77.3 6.4 3.0 2.1 1.5 8.0 0.7 0.7 0.3 0.0 100.0 9.7 6.3 14,882 Female 76.1 6.2 3.1 1.8 1.5 9.2 0.8 0.8 0.4 0.1 100.0 11.3 6.6 13,926 Residence Urban 76.5 7.2 2.6 1.4 1.0 9.3 0.7 0.9 0.4 0.1 100.0 11.3 5.6 7,444 Rural 76.8 6.0 3.2 2.1 1.6 8.3 0.8 0.7 0.3 0.0 100.0 10.2 6.7 21,364 Municipality Aileu 81.8 5.6 1.6 2.0 1.9 6.0 0.4 0.5 0.3 0.0 100.0 7.1 4.6 1,098 Ainaro 80.2 4.1 4.3 2.3 2.1 5.4 0.5 0.7 0.3 0.1 100.0 6.9 8.0 1,568 Baucau 67.4 9.0 2.8 3.0 2.5 13.3 0.7 1.1 0.1 0.1 100.0 15.2 7.2 3,356 Bobonaro 73.9 7.8 3.9 0.9 0.7 10.5 0.6 1.1 0.5 0.1 100.0 12.7 6.8 2,357 Covalima 81.7 3.7 4.1 1.0 0.9 6.5 1.1 0.6 0.2 0.2 100.0 8.4 6.9 1,592 Dili 77.3 7.5 3.2 1.0 1.2 7.7 0.9 0.9 0.2 0.1 100.0 9.7 6.5 5,435 Ermera 82.0 4.2 3.2 3.2 1.3 4.7 0.8 0.4 0.2 0.0 100.0 6.2 5.9 2,904 Lautem 75.9 9.1 2.8 3.1 1.3 7.1 0.3 0.2 0.1 0.0 100.0 7.8 4.8 1,755 Liquiçá 73.8 7.3 2.4 3.5 1.2 10.8 0.5 0.3 0.2 0.0 100.0 11.8 4.5 1,898 Manatuto 78.2 6.7 1.7 1.0 1.1 9.6 0.6 0.6 0.3 0.1 100.0 11.2 4.4 1,332 Manufahi 77.6 5.0 2.5 1.4 2.1 9.0 0.7 0.7 0.8 0.1 100.0 11.3 6.9 1,558 SAR of Oecussi 79.2 3.1 3.0 1.4 1.3 8.9 1.3 1.0 0.8 0.0 100.0 12.0 7.3 1,970 Viqueque 75.8 4.8 3.2 1.7 1.8 9.8 0.9 0.8 1.1 0.1 100.0 12.5 7.7 1,988 Wealth quintile Lowest 77.7 5.6 4.2 2.8 1.7 6.3 0.6 0.6 0.4 0.1 100.0 8.0 7.6 5,821 Second 78.1 5.1 3.1 2.2 2.0 7.8 0.7 0.6 0.3 0.1 100.0 9.4 6.7 5,900 Middle 77.1 5.6 3.7 1.8 1.4 8.8 0.6 0.6 0.4 0.0 100.0 10.4 6.7 5,825 Fourth 74.7 8.1 2.4 1.5 1.1 9.9 0.9 1.0 0.3 0.0 100.0 12.1 5.7 5,841 Highest 75.8 7.3 1.8 1.4 1.1 10.2 0.9 1.0 0.4 0.1 100.0 12.5 5.2 5,421 Total <15 78.4 6.8 2.6 1.9 1.3 7.4 0.6 0.6 0.3 0.1 100.0 8.9 5.4 24,648 Total <18 76.7 6.3 3.1 1.9 1.5 8.6 0.8 0.8 0.4 0.1 100.0 10.4 6.4 28,808 Note: Table is based on de jure members, i.e., usual residents. 1 Includes children with father dead, mother dead, both dead and one parent dead but missing information on survival status of the other parent. Housing Characteristics and Household Population • 23 Table 2.11 Birth registration of children under age 5 Percentage of de jure children under age 5 whose births are registered with the civil authorities, according to background characteristics, Timor-Leste DHS 2016 Background characteristic Percentage of children whose births are registered and who: Number of children Had a birth certificate Did not have birth certificate Total percentage of children whose births are registered Age <2 21.8 25.5 47.3 3,033 2-4 41.6 27.4 69.0 4,595 Sex Male 34.6 25.2 59.8 3,953 Female 32.8 28.2 61.0 3,675 Residence Urban 44.3 21.5 65.8 2,101 Rural 29.7 28.6 58.3 5,527 Municipality Aileu 39.4 34.0 73.4 294 Ainaro 25.3 23.8 49.1 395 Baucau 30.9 40.1 71.0 819 Bobonaro 41.2 25.6 66.8 654 Covalima 32.4 17.5 49.9 435 Dili 45.7 22.8 68.5 1,609 Ermera 28.7 46.4 75.2 734 Lautem 35.1 13.3 48.5 437 Liquiçá 15.7 21.7 37.5 526 Manatuto 33.2 22.0 55.2 354 Manufahi 31.4 15.1 46.5 394 SAR of Oecussi 32.5 31.6 64.1 492 Viqueque 22.6 19.6 42.3 483 Wealth quintile Lowest 26.0 28.5 54.5 1,571 Second 28.3 28.4 56.7 1,573 Middle 27.7 30.7 58.4 1,501 Fourth 39.0 24.6 63.6 1,489 Highest 48.4 20.9 69.3 1,494 Total 33.7 26.7 60.4 7,628 24 • Housing Characteristics and Household Population Table 2.12.1 Educational attainment of the female household population Percent distribution of the de facto female household population age 6 and over by highest level of schooling attended or completed and median years completed, according to background characteristics, Timor-Leste DHS 2016 Background characteristic No education Some primary Completed primary1 Some secondary Completed secondary2 More than secondary Don’t know/ missing Total Number Median years completed Age 6-9 23.8 76.0 0.1 0.1 0.0 0.0 0.0 100.0 3,241 0.4 10-14 4.4 65.3 5.6 24.6 0.1 0.0 0.0 100.0 4,376 4.0 15-19 5.4 8.9 3.5 74.0 5.8 2.4 0.0 100.0 3,031 7.8 20-24 11.7 7.2 3.5 27.2 29.1 21.2 0.1 100.0 2,248 11.0 25-29 16.8 9.8 7.0 19.3 28.4 18.7 0.0 100.0 2,063 10.0 30-34 22.3 11.4 7.1 18.7 26.8 13.6 0.0 100.0 1,826 8.3 35-39 29.0 13.3 10.9 15.1 22.1 9.5 0.0 100.0 1,178 5.7 40-44 34.0 12.1 14.0 16.6 17.1 6.2 0.0 100.0 1,461 5.3 45-49 49.7 12.9 7.3 14.0 12.1 4.0 0.0 100.0 1,118 0.0 50-54 65.2 15.6 5.8 5.4 5.4 2.6 0.0 100.0 1,336 0.0 55-59 76.1 12.1 3.0 4.0 2.3 2.4 0.1 100.0 813 0.0 60-64 88.6 6.5 2.0 0.7 1.1 1.1 0.1 100.0 882 0.0 65+ 94.6 4.0 0.4 0.4 0.5 0.1 0.0 100.0 1,941 0.0 Don’t know/ missing 41.7 14.4 0.0 15.8 13.0 11.9 3.2 100.0 110 2.9 Residence Urban 12.8 21.8 4.3 25.4 18.2 17.3 0.1 100.0 6,859 8.1 Rural 36.3 29.9 5.1 19.4 7.6 1.7 0.0 100.0 18,763 2.1 Municipality Aileu 32.1 28.6 5.7 21.4 9.2 3.0 0.0 100.0 993 3.2 Ainaro 38.2 29.4 4.0 18.6 7.4 2.1 0.3 100.0 1,303 2.0 Baucau 30.4 28.2 3.6 24.4 9.9 3.5 0.0 100.0 3,092 3.2 Bobonaro 38.4 30.9 5.1 16.5 7.1 2.1 0.0 100.0 2,037 1.8 Covalima 32.6 25.3 7.4 22.5 10.2 2.0 0.0 100.0 1,541 3.3 Dili 12.2 21.5 4.5 22.7 18.7 20.3 0.1 100.0 5,113 8.3 Ermera 46.7 26.9 2.6 17.5 5.3 1.0 0.0 100.0 2,452 0.2 Lautem 29.5 30.8 6.5 21.6 9.7 2.0 0.0 100.0 1,494 3.2 Liquiçá 34.8 30.6 4.2 19.5 8.8 2.2 0.0 100.0 1,668 2.5 Manatuto 30.6 29.1 5.0 22.1 10.4 2.8 0.0 100.0 1,173 3.0 Manufahi 26.6 28.1 4.0 27.2 11.2 2.8 0.1 100.0 1,377 4.3 SAR of Oecussi 35.2 35.6 7.1 14.9 5.2 2.0 0.0 100.0 1,674 1.6 Viqueque 32.0 28.5 6.7 21.9 8.5 2.4 0.0 100.0 1,706 3.1 Wealth quintile Lowest 49.8 29.9 4.4 12.6 3.0 0.3 0.1 100.0 5,151 0.0 Second 39.2 30.6 5.0 18.9 5.3 1.0 0.0 100.0 5,113 1.6 Middle 32.9 29.2 5.2 21.9 9.0 1.8 0.0 100.0 5,108 2.9 Fourth 18.7 27.5 5.5 27.4 14.8 6.0 0.1 100.0 5,128 5.5 Highest 9.3 21.3 4.3 24.4 20.3 20.4 0.0 100.0 5,122 8.7 Total 30.0 27.7 4.9 21.0 10.5 5.9 0.0 100.0 25,622 3.5 1 Completed grade 6 at the primary level 2 Completed grade 12 at the secondary level Housing Characteristics and Household Population • 25 Table 2.12.2 Educational attainment of the male household population Percent distribution of the de facto male household population age 6 and over by highest level of schooling attended or completed and median years completed, according to background characteristics, Timor-Leste DHS 2016 Background characteristic No education Some primary Completed primary1 Some secondary Completed secondary2 More than secondary Don’t know/ missing Total Number Median years completed Age 6-9 23.0 76.6 0.1 0.2 0.0 0.1 0.0 100.0 3,406 0.3 10-14 5.1 71.5 5.1 18.2 0.0 0.0 0.0 100.0 4,615 3.5 15-19 6.5 14.5 4.8 68.4 4.5 1.3 0.0 100.0 3,279 7.2 20-24 10.4 10.4 4.0 28.1 31.6 15.4 0.0 100.0 2,121 10.7 25-29 12.7 13.6 4.6 14.9 28.9 25.2 0.1 100.0 1,720 11.1 30-34 16.3 12.0 7.2 14.6 28.6 21.3 0.0 100.0 1,763 10.9 35-39 20.7 15.3 8.0 12.1 27.4 16.5 0.0 100.0 1,102 8.2 40-44 24.4 16.9 10.4 15.7 20.4 11.9 0.2 100.0 1,474 5.8 45-49 29.7 14.2 8.6 15.6 21.7 10.1 0.1 100.0 1,308 5.6 50-54 38.7 22.4 7.6 9.1 14.9 7.3 0.1 100.0 1,073 2.5 55-59 47.0 28.3 5.4 5.2 7.3 6.7 0.0 100.0 742 0.5 60-64 65.1 22.5 3.6 3.1 3.3 2.2 0.2 100.0 955 0.0 65+ 81.1 14.4 1.4 0.8 1.6 0.6 0.2 100.0 1,726 0.0 Don’t know/missing 29.7 11.1 4.0 15.0 13.5 22.5 4.2 100.0 87 8.0 Residence Urban 8.7 26.7 4.7 23.2 18.6 18.0 0.1 100.0 6,940 8.0 Rural 27.9 36.5 4.9 18.2 9.2 3.2 0.0 100.0 18,431 2.8 Municipality Aileu 26.7 34.2 5.6 19.3 9.8 4.3 0.0 100.0 1,009 3.3 Ainaro 31.4 32.5 6.1 17.6 8.3 3.9 0.2 100.0 1,303 2.7 Baucau 22.0 37.3 3.4 21.8 10.6 4.8 0.0 100.0 2,947 3.5 Bobonaro 30.0 36.2 5.1 17.0 8.9 2.8 0.1 100.0 1,977 2.5 Covalima 25.8 31.2 6.2 18.6 13.7 4.5 0.1 100.0 1,485 3.7 Dili 7.9 26.4 4.9 21.0 19.4 20.3 0.1 100.0 5,365 8.3 Ermera 36.6 32.0 3.7 17.4 7.7 2.5 0.0 100.0 2,420 1.8 Lautem 21.7 39.7 4.9 20.5 9.9 3.1 0.1 100.0 1,345 3.3 Liquiçá 24.3 40.1 4.6 18.7 8.8 3.4 0.0 100.0 1,689 3.1 Manatuto 23.3 36.2 5.0 18.9 12.2 4.4 0.0 100.0 1,183 3.6 Manufahi 23.3 32.0 4.4 24.5 11.9 4.0 0.1 100.0 1,345 4.0 SAR of Oecussi 30.2 40.5 4.7 13.9 7.0 3.6 0.0 100.0 1,610 2.0 Viqueque 21.1 36.4 6.2 21.8 9.9 4.6 0.0 100.0 1,693 3.8 Wealth quintile Lowest 41.5 37.3 4.2 12.4 3.9 0.8 0.0 100.0 4,981 0.8 Second 28.6 38.9 4.5 18.1 8.1 1.6 0.0 100.0 5,062 2.5 Middle 24.2 35.0 5.6 20.5 11.2 3.4 0.1 100.0 5,141 3.5 Fourth 14.0 33.1 5.9 23.0 15.6 8.3 0.0 100.0 5,125 5.3 Highest 5.3 24.7 3.8 23.8 20.0 22.3 0.1 100.0 5,061 8.8 Total 22.7 33.8 4.8 19.6 11.8 7.3 0.1 100.0 25,371 3.9 1 Completed grade 6 at the primary level 2 Completed grade 12 at the secondary level 26 • Housing Characteristics and Household Population Table 2.13.1 Pre-primary school attendance: Females Percentage of the de facto female household population age 3-5 years who have attended pre- primary school, according to background characteristics, Timor-Leste DHS 2016 Background characteristic Has attended pre-primary school Number Residence Urban 22.6 571 Rural 15.7 1,537 Municipality Aileu 25.0 76 Ainaro 14.0 104 Baucau 8.3 223 Bobonaro 18.2 180 Covalima 12.1 131 Dili 21.9 420 Ermera 10.1 237 Lautem 29.9 123 Liquiçá 16.0 129 Manatuto 18.3 96 Manufahi 16.7 98 SAR of Oecussi 9.0 146 Viqueque 33.8 145 Wealth quintile Lowest 9.0 439 Second 11.6 421 Middle 18.2 426 Fourth 19.6 443 Highest 30.9 379 Total 17.6 2,108 Table 2.13.2 Pre-primary school attendance: Males Percentage of the de facto male household population age 3-5 years who have attended pre-primary school, according to background characteristics, Timor-Leste DHS 2016 Background characteristic Has attended pre-primary school Number Residence Urban 20.8 655 Rural 13.7 1,657 Municipality Aileu 25.3 80 Ainaro 8.3 111 Baucau 12.1 218 Bobonaro 20.2 194 Covalima 9.3 115 Dili 19.2 507 Ermera 7.0 251 Lautem 15.3 138 Liquiçá 11.2 137 Manatuto 12.8 120 Manufahi 23.6 125 SAR of Oecussi 13.2 171 Viqueque 26.7 144 Wealth quintile Lowest 8.3 488 Second 10.7 482 Middle 16.2 445 Fourth 18.1 433 Highest 25.9 464 Total 15.7 2,313 Housing Characteristics and Household Population • 27 Table 2.14 School attendance ratios Net attendance ratios (NAR) and gross attendance ratios (GAR) for the de facto household population by sex and level of schooling; and the Gender Parity Index (GPI), according to background characteristics, Timor-Leste DHS 2016 Background characteristic Net attendance ratio1 Gross attendance ratio2 Male Female Total Gender Parity Index3 Male Female Total Gender Parity Index3 PRIMARY SCHOOL Residence Urban 89.1 89.5 89.3 1.00 114.1 108.4 111.4 0.95 Rural 85.1 85.4 85.3 1.00 120.8 116.0 118.5 0.96 Municipality Aileu 85.9 88.8 87.4 1.03 130.3 123.3 126.8 0.95 Ainaro 81.1 80.7 80.9 1.00 109.4 108.7 109.1 0.99 Baucau 84.5 82.8 83.7 0.98 112.9 103.9 108.5 0.92 Bobonaro 89.8 88.8 89.3 0.99 123.8 120.8 122.4 0.98 Covalima 88.3 90.6 89.4 1.03 127.5 120.9 124.4 0.95 Dili 88.8 90.2 89.4 1.02 116.1 108.2 112.4 0.93 Ermera 73.9 75.9 74.9 1.03 104.2 104.2 104.2 1.00 Lautem 92.1 92.2 92.1 1.00 132.1 128.4 130.3 0.97 Liquiçá 86.9 84.0 85.5 0.97 126.1 113.7 120.2 0.90 Manatuto 89.8 89.8 89.8 1.00 134.4 125.0 129.9 0.93 Manufahi 84.0 86.3 85.2 1.03 112.9 111.7 112.3 0.99 SAR of Oecussi 84.8 88.5 86.5 1.04 121.2 126.7 123.8 1.05 Viqueque 92.3 89.9 91.1 0.97 124.9 119.1 122.2 0.95 Wealth quintile Lowest 79.0 79.9 79.4 1.01 115.7 112.7 114.2 0.97 Second 84.8 84.0 84.4 0.99 117.6 118.0 117.8 1.00 Middle 88.6 89.6 89.1 1.01 127.5 119.3 123.5 0.94 Fourth 89.5 89.2 89.4 1.00 121.0 112.8 117.1 0.93 Highest 89.5 90.0 89.7 1.00 113.8 107.7 110.8 0.95 Total 86.1 86.3 86.2 1.00 119.2 114.3 116.8 0.96 SECONDARY SCHOOL Residence Urban 74.3 82.7 78.4 1.11 100.6 104.9 102.7 1.04 Rural 49.6 58.9 54.1 1.19 66.4 73.1 69.6 1.10 Municipality Aileu 49.8 57.7 53.6 1.16 71.7 81.2 76.3 1.13 Ainaro 54.4 63.3 58.9 1.16 75.3 75.6 75.5 1.00 Baucau 60.0 74.3 67.2 1.24 78.6 88.1 83.3 1.12 Bobonaro 48.0 57.6 52.6 1.20 66.5 72.2 69.2 1.08 Covalima 54.8 69.1 62.1 1.26 71.0 83.8 77.5 1.18 Dili 72.2 82.5 77.0 1.14 97.7 101.6 99.5 1.04 Ermera 49.9 51.5 50.7 1.03 68.9 68.4 68.6 0.99 Lautem 50.4 57.5 54.0 1.14 70.1 77.3 73.7 1.10 Liquiçá 45.9 55.5 50.4 1.21 61.5 70.4 65.7 1.14 Manatuto 44.8 62.2 53.2 1.39 62.9 74.6 68.5 1.19 Manufahi 60.9 72.5 66.8 1.19 79.8 90.6 85.3 1.14 SAR of Oecussi 43.5 44.3 43.9 1.02 57.2 58.3 57.7 1.02 Viqueque 61.0 65.8 63.3 1.08 76.6 83.8 80.0 1.09 Wealth quintile Lowest 35.7 41.1 38.3 1.15 47.4 49.8 48.6 1.05 Second 47.2 52.1 49.6 1.10 65.2 65.5 65.4 1.00 Middle 49.8 64.9 56.9 1.30 68.7 82.9 75.3 1.21 Fourth 63.9 75.8 69.7 1.19 86.2 95.8 90.9 1.11 Highest 81.8 87.3 84.5 1.07 106.8 107.6 107.2 1.01 Total 56.5 65.6 60.9 1.16 75.9 82.0 78.9 1.08 1 The NAR for primary school is the percentage of the primary-school age (6-11 years) population that is attending primary school. The NAR for secondary school is the percentage of pre-secondary and the secondary-school age (12-17 years) population that is attending pre-secondary and secondary school. By definition the NAR cannot exceed 100.0 percent. 2 The GAR for primary school is the total number of primary school students, expressed as a percentage of the official primary-school- age population. The GAR for secondary school is the total number of pre-secondary and secondary school students, expressed as a percentage of the official secondary-school-age population. If there are significant numbers of overage and underage students at a given level of schooling, the GAR can exceed 100 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 secondary school is the ratio of the secondary school NAR (GAR) for females to the NAR (GAR) for males. Characteristics of Respondents • 29 CHARACTERISTICS OF RESPONDENTS 3 Key Findings  Education: 22% of women and 19% of men age 15-49 have no education. 11% of women and 12% of men have attended schooling beyond secondary school.  Literacy: 75% percent of women and 82% of men age 15-49 are literate.  Exposure to mass media: 57% of women and 53% of men age 15-49 accesses neither newspaper, radio, nor television on a weekly basis.  Employment: 34% of women and 70% of men are currently employed.  Smoking and alcohol: 4% percent of women and 52% of men smoke cigarettes. 8% of women have ever consumed alcohol and 45% of men have ever consumed alcohol. his chapter presents information on the demographic and socioeconomic characteristics of the survey respondents such as age, education, place of residence, marital status, employment, and wealth status. This information is useful for understanding the factors that affect use of reproductive health services, contraceptive use, and other health behaviors. 3.1 BASIC CHARACTERISTICS OF SURVEY RESPONDENTS The 2016 TLDHS interviewed 12,607 women age 15-49 and 4,622 men age 15-59 (Table 3.1). Among the 15-49 year-old respondents, 41% of women and 42% of men are age 15-24. Thirty percent of women and 27% of men are age 25-34, and 29% of women and 32% of men are age 35-49. While men were interviewed up to age 59, the body of tables in this report will present the male data for ages 15-49 to be comparable with the data for women, as well as comparable with the 2009-10 TLDHS, and present a row of data for the 50- 59 year-old and 15-59 year-old men. The vast majority of the population is Roman Catholic; 98% of both female and male respondents are Roman Catholic, and the remaining 2% are Protestant, Muslim, or Hindu. Among respondents age 15-49, women are more likely than men to be married (54% vs. 45%), living together (7% vs. 5%), divorced/separated (1% vs. 0.4%), and widowed (1% vs. 0.3%). Thirty-seven percent of women and 50% of men have never been married. Thirty-three percent of women and 34% of men are urban residents and 67% of women and 66% of men are rural residents. Twenty-five percent of women and 27% of men live in Dili. The next most populated municipality is Bacau, with 10% of respondents residing there. Each of the other 11 municipalities is home to less than 10% of the population age 15-49. T 30 • Characteristics of Respondents 3.2 EDUCATION AND LITERACY Twenty-two percent of women 23% of men have no education (Tables 3.2.1 and 3.2.2). Twenty percent of women 22% of men have completed secondary school (without going on for higher education). Eleven percent of women and 12% of men have attended schooling beyond secondary school (Figure 3.1). Trends: Twenty-two percent of women and 23% of men with no education is an improvement for women and status quo at the national level among men; the 2009-10 TLDHS found that 29% of women and 19% of men had no education. There has been an increase among women and men who have continued beyond secondary school since the previous TLDHS, which found 3% of women and 6% of men had gone beyond a secondary education. Since 2009-10, the median number of years of schooling completed by women and men age 15-49 has increased. The median number of years of schooling completed in 2009-10 was 6 years among women and 7 years among men, compared with 8 years among both women and men in 2016. Literacy Respondents who have attended higher than secondary school are assumed to be literate. All other respondents, shown a typed sentence to read aloud, are considered literate if they could read all or part of the sentence. Sample: Women and men age 15-49 Note that only those who attended higher than secondary school are assumed to be literate. All other respondents were shown a card and asked to read a sentence. The previous TLDHS had a looser definition of literacy, assuming that everyone who attended pre-secondary or higher was literate. But even with a more stringent definition of literacy than was used in the previous DHS, national literacy levels have increased. Seventy-five percent of women and 82% of men age 15-49 are literate (Tables 3.3.1 and 3.3.2). Patterns by background characteristics  Completion of each level of education is similar between women and men.  While those with no education has been declining significantly and steadily over time, there are still some youth who have never been to school (9% of women and 10% of men age 15-24).  There is great variability across municipalities in the percent of women and men with no education from a low of 7% of women in Dili to as high as 48% in Ermera, and a low of 5% of men in Dili to a high of 39% in Ermera.  Literacy rises steadily with decreasing age, reaching a high of 91% among female teens age 15-19, both female and male. Figure 3.1 Education of survey respondents Characteristics of Respondents • 31  The percentage of the population age 15-49 with no education rises steadily by approximately 1 in 10 persons with each step down the wealth quintile (Figure 3.2).  Literacy varies significantly by wealth, rising steadily from a low of 50% to a high of 95% of women in the lowest to highest wealth quintiles (Figure 3.3). Figure 3.2 No education by household wealth Figure 3.3 Literacy by household wealth 3.3 MASS MEDIA EXPOSURE Exposure to mass media Respondents were asked how often they read a newspaper, listened to the radio, or watched television. Those who responded at least once a week are considered regularly exposed to that form of media. Sample: Women and men age 15-49 Information on the exposure of women and men to mass media is especially important to the development of educational programs and the dissemination of all types of information, including important health topics. Men are more likely than women to be regularly exposed to newspapers (15% vs. 7%), television (41% vs. 38%), and radio (25% vs. 14%), as well as all 3 forms of media (11% vs. 3%) (Tables 3.4.1 and 3.4.2). Fifty-seven percent of women and 53% of men age 15-49 access none of the 3 forms of media on a regular basis (Figure 3.4). Television is the most common form of media exposure for both women and men across all subgroups shown, with the one exception of the lowest wealth quintile. The Internet is also a critical tool through which information is shared. Internet use includes accessing web pages, email, and social media. Twenty-two percent of women and 31% of men have accessed the Internet in the past 12 months (Tables 3.5.1 and 3.5.2). Though among those that have used the Internet in the past 12 months, women and men are equally likely to have accessed it on a daily basis (46% of women and 45% of men). Trends: At the national level, exposure to newspapers and radio has decreased among women and men since 2009-10. Exposure to television has remained the same. Thus, the percentage of women who do not access any of the media types at least once a week increased from 48% in 2009-10 to 57% in 2016 and increased from 40% to 53% among men age 15-49 (due to decreases in accessing newspapers and radio). 45 34 26 10 4 44 24 20 11 3 Lowest Second Middle Fourth Highest Women Men WealthiestPoorest Percentage of women and men age 15-49 with no education 50 62 71 86 95 59 74 82 89 97 Lowest Second Middle Fourth Highest Women Men WealthiestPoorest Percentage of women and men age 15-49 who are literate Figure 3.4 Exposure to mass media 7 38 14 3 57 15 41 25 11 53 Reads news- paper Watches tele- vision Listens to radio All three media None of these media Percentage of women and men age 15-49 who are exposed to media on a weekly basis Women Men 32 • Characteristics of Respondents Patterns by background characteristics  Seventy percent of rural women report having no regular exposure to a newspaper, television or radio, compared with 32% of urban women. Similarly among men, 66% of rural men report having no regular exposure to a newspaper, television or radio, compared with 27% of urban men (Tables 3.4.1 and 3.4.2).  Women in Ermera and men in Viqueque are the most likely to report no regular exposure to any of the three mass media (81% and 84%, respectively).  Twenty-eight percent of women and 23% of men with more than a secondary education lack regular exposure to any mass media compared with 84% of women and 80% of men with no education.  Internet usage is more common in urban than rural areas (Tables 3.5.1 and 3.5.2). In urban areas, 46% of women and 60% of men have used the Internet in the past 12 months compared with 11% of women and 17% of men in the rural areas.  Internet use rises sharply with increasing education and wealth. Only 1% of women with no education have used the Internet in the past 12 months while 76% of women with more than secondary education have done so. Similarly, only 3% of women in the lowest wealth quintile have used the Internet in the past 12 months compared with 53% in the highest wealth quintile. 3.4 EMPLOYMENT Currently employed Respondents who were employed in the 7 days before the survey Sample: Women and men age 15-49 Men are more likely to be employed than women; 34% of women age 15-49 are currently employed compared with 70% of men age 15-49 (Tables 3.6.1 and 3.6.2). An additional 3% of women and men reported working in the past 12 months although they were not currently employed. Trends: Since 2009-10, current employment levels have declined by 15 percentage points, from 85% to 70% among men, and by 5 percentage points, from 39% to 34% among women. Patterns by background characteristics  Employment status varies more by marital status than it does by education or wealth quintile (Figure 3.5).  Current employment status varies considerably across municipalities, from a low of 10% among women in Viqueque to a high of 57% in SAR of Oecussi and from a low of 41% among men in Viqueque to a high of 91% in Ermera.  Women and men in the highest wealth quintiles are less likely to be currently employed than those in the lower wealth quintiles and the decline is steady among men, from 77% of men in the lowest wealth quintile being employed, down to 64% among men in the highest wealth quintile. Figure 3.5 Employment by marital status 22 40 5851 89 63 Never married Married or living together Divorced/ separated/ widowed Percentage of women and men age 15-49 who are currently employed Women Men Characteristics of Respondents • 33 3.5 OCCUPATION Occupation Categorized as professional/technical/managerial, clerical, sales and services, skilled manual, unskilled manual, domestic service, agriculture, and other Sample: Women and men age 15-49 who were currently employed or had worked in the 12 months before the survey Among those who are employed, 32% of women are in agriculture; domestic service, and sales and service are other dominant occupational fields for women (Table 3.7.1 and Figure 3.6). Among men who are employed, 47% are in agriculture, and skilled manual occupations are the next most dominant field (22%) (Table 3.7.2 and Figure 3.6). Women and men are equally likely to be employed in professional, technical, or managerial occupations (11% and 12% respectively). Ninety percent of women who are employed are either self-employed or employed by a family member (Table 3.8). Seventy-four percent of women who work in agriculture are unpaid and 51% work on a seasonal basis. Trends: The percentage of women employed in agriculture has fallen from 61% to 32%, while the percentage employed in domestic service has increased from 4% to 18% since 2009-10. The percentage of men in agriculture has declined from 67% to 45% while the percentage in skilled manual has increased from 2% to 22% since 2009-10. Patterns by background characteristics  The highest percentages of professional/technical/managerial occupations are among women interviewed in Covalima (22%), and men interviewed in Dili (20%). The highest percentages of agricultural occupations are among women interviewed in Ermera (66%) and Aileu (67%), and men interviewed in Ermera (74%) and Aileu (70%).  Among the employed, the percentage employed in agriculture falls dramatically with each increase in the wealth quintile, from a high of 66% of women and 76% of men in the lowest wealth quintile to a low of 3% of women and 6% of men in the highest wealth quintile. 3.6 TOBACCO USE Tobacco use is not common among women, 4% of women age 15-49 report that they currently smoke cigarettes (Table 3.9.1). Fifty-two percent of men age 15-49 smoke cigarettes, and 41% of men smoke tobacco on a daily basis (Table 3.9.2). Among men who smoke cigarettes daily, 36% smoke 1-4 cigarettes each day, 11% smoke 5-14 each day, and 13% smoke 15 or more cigarettes a day (Table 3.10). Note that the data on the number of cigarettes smoked daily is not clear, since the data are only based on 60% of men who reported smoking cigarettes. Twenty-one percent of men use smokeless tobacco products (Table 3.11), while use of smokeless tobacco is rare among women (0.2%). Figure 3.6 Occupation 11 6 28 5 18 32 11 6 10 23 2 3 45 Professional/ technical/ managerial Clerical Sales and services Skilled manual Unskilled manual Domestic service Agriculture Percentage of women and men age 15-49 employed in the 12 months before the survey by occupation Women Men 34 • Characteristics of Respondents Trends: The percentage of men age 15-49 who do not use (either smoke or chew) any tobacco product has increased from 31% in 2009-10 to 43% in 2016. The percentage remains at 95% among women. Patterns by background characteristics  Over half of men are smoking by age 24, 56% of men age 20-24 smoke cigarettes.  The prevalence of smoking cigarettes varies more by municipality than it does by education or wealth quintile. Men who smoke cigarettes varies from a low of 27% in Viqueque to a high of 74% in SAR of Oecussi, with variability across the municipalities.  Among men, the prevalence of smoking cigarettes varies from 45% to 61% across education levels and from 48% to 57% across wealth quintiles. 3.7 ALCOHOL CONSUMPTION Eight percent of women and 46% of men age 15-49 have ever drunk alcohol (Tables 3.12.1 and 3.12.2). The median age at having drunk alcohol is 20 for women and 18 for men. Among those who have ever had alcohol, 21% of women and 48% of men drink at least once a week. Among those who have ever drunk alcohol, the majority of women and men who report ever having been drunk also report having been drunk at least once in the past 3 months (31% and 25% of women, and 50% and 41% of men). Patterns by background characteristics  Overall, very few women consume alcohol, but it is the women in the highest education level and highest wealth quintile that are more likely to have ever had alcohol (15% and 12%).  While there is variability across education and wealth quintiles among men, there is no strong pattern.  Whether someone has ever had alcohol varies considerably across municipalities. LIST OF TABLES For more information on the characteristics of survey respondents, see the following tables:  Table 3.1 Background characteristics of respondents  Table 3.2.1 Educational attainment: Women  Table 3.2.2 Educational attainment: Men  Table 3.3.1 Literacy: Women  Table 3.3.2 Literacy: Men  Table 3.4.1 Exposure to mass media: Women  Table 3.4.2 Exposure to mass media: Men  Table 3.5.1 Internet usage: Women  Table 3.5.2 Internet usage: Men  Table 3.6.1 Employment status: Women  Table 3.6.2 Employment status: Men  Table 3.7.1 Occupation: Women  Table 3.7.2 Occupation: Men  Table 3.8 Type of employment: Women  Table 3.9.1 Tobacco smoking: Women  Table 3.9.2 Tobacco smoking: Men  Table 3.10 Average number of cigarettes smoked daily: Men  Table 3.11 Smokeless tobacco use and any tobacco use  Table 3.12.1 Alcohol consumption: Women  Table 3.12.2 Alcohol consumption: Men Characteristics of Respondents • 35 Table 3.1 Background characteristics of respondents Percent distribution of women and men age 15-49 by selected background characteristics, Timor-Leste DHS 2016 Background characteristic Women Men Weighted percent Weighted number Unweighted number Weighted percent Weighted number Unweighted number Age 15-19 23.7 2,985 3,126 24.6 1,001 1,053 20-24 17.2 2,165 2,047 16.9 689 676 25-29 15.9 2,011 1,925 13.2 539 505 30-34 14.1 1,772 1,789 13.7 557 533 35-39 9.0 1,141 1,175 8.9 361 357 40-44 11.4 1,438 1,440 11.7 478 476 45-49 8.7 1,096 1,105 11.0 450 459 Religion Roman Catholic 98.3 12,396 12,385 98.4 4,009 3,989 Muslim 0.3 43 46 0.4 17 16 Protestant 1.3 166 173 1.1 46 52 Hindu 0.0 2 2 0.1 3 2 Other 0.0 0 1 0.0 0 0 Marital status Never married 36.6 4,615 4,689 50.1 2,043 2,038 Married 53.9 6,799 6,751 44.6 1,817 1,781 Living together 7.1 898 877 4.6 186 213 Divorced/separated 1.3 161 151 0.4 17 14 Widowed 1.1 133 139 0.3 12 13 Residence Urban 33.2 4,182 4,337 33.7 1,374 1,355 Rural 66.8 8,425 8,270 66.3 2,701 2,704 Municipality Aileu 4.2 524 1,047 4.3 174 354 Ainaro 4.1 515 768 4.5 184 273 Baucau 10.2 1,288 896 9.5 388 267 Bobonaro 7.5 946 915 7.5 305 318 Covalima 5.9 750 852 5.8 234 264 Dili 25.4 3,206 1,661 26.9 1,098 536 Ermera 9.3 1,178 943 8.6 350 281 Lautem 5.1 645 867 4.6 188 251 Liquiçá 6.0 757 944 6.3 255 307 Manatuto 4.4 555 933 4.3 177 282 Manufahi 5.4 676 1,087 5.5 225 385 SAR of Oecussi 6.2 778 773 5.2 212 207 Viqueque 6.3 791 921 7.0 285 334 Education No education 21.7 2,741 2,692 19.0 772 783 Primary 15.2 1,922 1,946 18.1 736 709 Secondary 52.0 6,561 6,823 50.6 2,063 2,128 More than secondary 11.0 1,383 1,146 12.4 504 439 Wealth quintile Lowest 16.5 2,085 2,059 15.9 648 653 Second 18.1 2,287 2,319 20.2 823 836 Middle 19.2 2,423 2,538 19.9 809 842 Fourth 22.0 2,771 3,005 20.7 844 926 Highest 24.1 3,041 2,686 23.3 950 802 Total 15-49 100.0 12,607 12,607 100.0 4,075 4,059 50-59 na na na na 547 563 Total 15-59 na na na na 4,622 4,622 Note: Education categories refer to the highest level of education attended, whether or not that level was completed. na = Not applicable 36 • Characteristics of Respondents Table 3.2.1 Educational attainment: Women Percent distribution of women age 15-49 by highest level of schooling attended or completed, and median years completed, according to background characteristics, Timor-Leste DHS 2016 Background characteristic Highest level of schooling Total Median years completed Number of women No education Some primary Completed primary1 Some secondary Completed secondary2 More than secondary Age 15-24 8.6 6.9 3.4 54.0 16.9 10.2 100.0 8.7 5,149 15-19 5.7 7.4 3.4 74.4 7.0 2.0 100.0 7.9 2,985 20-24 12.5 6.2 3.4 25.9 30.5 21.5 100.0 11.1 2,165 25-29 18.3 8.7 6.6 20.4 27.2 18.9 100.0 9.5 2,011 30-34 24.8 10.9 6.5 17.9 26.6 13.3 100.0 8.2 1,772 35-39 31.7 11.4 10.5 15.6 21.3 9.5 100.0 5.6 1,141 40-44 37.2 9.8 14.0 16.7 16.3 6.1 100.0 5.2 1,438 45-49 54.3 9.9 7.0 12.3 12.3 4.2 100.0 - 1,096 Residence Urban 7.1 4.2 3.4 31.7 27.4 26.2 100.0 11.1 4,182 Rural 29.0 11.0 8.0 32.4 16.1 3.4 100.0 6.1 8,425 Municipality Aileu 24.4 11.2 7.7 33.7 17.5 5.6 100.0 7.0 524 Ainaro 31.0 11.7 5.5 30.9 16.8 4.1 100.0 6.1 515 Baucau 16.2 9.4 4.9 40.1 22.0 7.4 100.0 8.3 1,288 Bobonaro 35.9 11.7 7.7 25.8 14.8 4.0 100.0 5.3 946 Covalima 18.0 9.0 11.8 36.9 20.6 3.6 100.0 7.7 750 Dili 6.6 4.7 3.6 28.6 26.7 30.0 100.0 11.2 3,206 Ermera 47.9 7.0 4.8 28.3 10.2 1.8 100.0 2.5 1,178 Lautem 20.1 7.3 10.4 36.2 21.8 4.3 100.0 7.8 645 Liquiçá 24.6 14.6 6.0 31.8 18.4 4.7 100.0 6.7 757 Manatuto 20.7 9.9 6.3 36.8 21.1 5.1 100.0 7.6 555 Manufahi 18.7 7.9 6.1 41.2 20.9 5.2 100.0 8.1 676 SAR of Oecussi 30.2 15.6 13.1 25.0 12.3 3.8 100.0 5.3 778 Viqueque 25.8 8.3 8.3 36.2 17.2 4.2 100.0 7.1 791 Wealth quintile Lowest 44.5 14.9 8.0 24.8 7.1 0.7 100.0 2.8 2,085 Second 34.1 12.3 8.2 31.9 11.4 2.2 100.0 5.4 2,287 Middle 26.0 9.4 8.3 34.8 18.1 3.5 100.0 6.9 2,423 Fourth 10.3 7.5 6.7 39.1 26.0 10.3 100.0 8.9 2,771 Highest 3.9 2.6 2.6 29.1 30.7 31.2 100.0 11.4 3,041 Total 21.7 8.8 6.5 32.2 19.8 11.0 100.0 8.0 12,607 1 Completed grade 6 at the primary level 2 Completed grade 12 at the secondary level Characteristics of Respondents • 37 Table 3.2.2 Educational attainment: Men Percent distribution of men age 15-49 by highest level of schooling attended or completed, and median years completed, according to background characteristics, Timor-Leste DHS 2016 Background characteristic Highest level of schooling Total Median years completed Number of men No education Some primary Completed primary1 Some secondary Completed secondary2 More than secondary Age 15-24 10.4 8.4 5.4 50.7 18.6 6.5 100.0 8.2 1,690 15-19 8.4 7.4 5.8 69.7 7.2 1.5 100.0 7.7 1,001 20-24 13.3 9.8 4.9 23.1 35.2 13.6 100.0 10.9 689 25-29 19.9 11.4 5.3 11.5 27.2 24.8 100.0 11.1 539 30-34 18.1 12.1 8.2 16.2 26.2 19.2 100.0 8.9 557 35-39 25.1 13.1 10.0 11.0 25.4 15.5 100.0 7.0 361 40-44 31.4 13.4 9.3 13.7 20.1 12.1 100.0 5.5 478 45-49 33.0 16.8 7.0 12.2 22.1 8.9 100.0 5.0 450 Residence Urban 5.7 8.0 3.6 27.5 29.6 25.6 100.0 11.2 1,374 Rural 25.7 12.9 8.5 29.3 18.0 5.6 100.0 6.3 2,701 Municipality Aileu 26.3 12.2 6.8 27.6 20.4 6.6 100.0 6.7 174 Ainaro 32.0 12.6 11.9 23.9 14.2 5.5 100.0 5.4 184 Baucau 16.5 12.7 5.6 38.0 17.1 10.1 100.0 7.2 388 Bobonaro 26.7 13.9 9.2 27.1 18.7 4.3 100.0 6.0 305 Covalima 23.9 6.4 11.0 27.0 23.9 7.9 100.0 7.8 234 Dili 5.1 9.0 3.9 24.3 29.7 28.0 100.0 11.3 1,098 Ermera 38.8 9.2 6.4 22.6 18.8 4.1 100.0 5.3 350 Lautem 25.7 8.4 6.6 34.0 20.0 5.3 100.0 7.9 188 Liquiçá 15.9 20.0 6.5 31.7 19.0 7.0 100.0 7.0 255 Manatuto 14.2 17.3 5.7 29.9 24.0 9.0 100.0 7.9 177 Manufahi 13.9 9.0 7.5 39.4 24.4 5.8 100.0 8.3 225 SAR of Oecussi 31.2 17.2 9.6 23.8 12.8 5.3 100.0 5.1 212 Viqueque 22.2 7.5 9.5 35.6 17.4 7.7 100.0 7.6 285 Wealth quintile Lowest 43.5 16.6 9.0 21.5 8.2 1.2 100.0 2.9 648 Second 24.3 16.3 9.3 30.0 16.8 3.3 100.0 5.9 823 Middle 20.3 12.9 8.3 30.1 21.2 7.3 100.0 7.4 809 Fourth 11.2 10.2 6.8 33.0 26.2 12.5 100.0 9.1 844 Highest 3.3 2.7 1.9 27.5 32.6 32.0 100.0 11.4 950 Total 15-49 19.0 11.2 6.8 28.7 21.9 12.4 100.0 8.1 4,075 50-59 50.9 19.8 6.1 6.1 11.5 5.5 100.0 - 547 Total 15-59 22.7 12.2 6.7 26.0 20.7 11.6 100.0 7.5 4,622 1 Completed grade 6 at the primary level 2 Completed grade 12 at the secondary level 38 • Characteristics of Respondents Table 3.3.1 Literacy: Women Percent distribution of women age 15-49 by level of schooling attended and level of literacy, and percentage literate, according to background characteristics, Timor-Leste DHS 2016 Background characteristic Higher than secondary schooling No schooling, primary or secondary school Total Percentage literate1 Number of women Can read a whole sentence Can read part of a sentence Cannot read at all Blind/ visually impaired Age 15-24 10.2 67.5 10.8 11.3 0.2 100.0 88.5 5,149 15-19 2.0 78.8 10.3 8.8 0.1 100.0 91.1 2,985 20-24 21.5 52.1 11.4 14.7 0.3 100.0 85.0 2,165 25-29 18.9 44.0 14.9 21.9 0.4 100.0 77.7 2,011 30-34 13.3 44.2 14.4 27.6 0.6 100.0 71.9 1,772 35-39 9.5 36.5 18.5 34.8 0.7 100.0 64.5 1,141 40-44 6.1 32.2 17.8 43.3 0.6 100.0 56.1 1,438 45-49 4.2 23.8 14.4 55.8 1.8 100.0 42.4 1,096 Residence Urban 26.2 56.7 7.2 9.8 0.1 100.0 90.1 4,182 Rural 3.4 46.5 17.0 32.4 0.7 100.0 66.9 8,425 Municipality Aileu 5.6 47.3 21.2 25.9 0.1 100.0 74.0 524 Ainaro 4.1 46.1 14.6 35.2 0.0 100.0 64.8 515 Baucau 7.4 52.0 17.5 21.2 1.9 100.0 76.9 1,288 Bobonaro 4.0 42.4 13.9 39.4 0.3 100.0 60.3 946 Covalima 3.6 49.2 17.1 29.9 0.2 100.0 69.9 750 Dili 30.0 53.9 7.2 8.9 0.0 100.0 91.1 3,206 Ermera 1.8 38.3 13.8 46.1 0.0 100.0 53.9 1,178 Lautem 4.3 54.9 15.3 22.5 3.0 100.0 74.5 645 Liquiçá 4.7 40.9 26.6 27.9 0.0 100.0 72.1 757 Manatuto 5.1 54.0 14.0 26.3 0.5 100.0 73.2 555 Manufahi 5.2 61.7 11.0 22.1 0.0 100.0 77.9 676 SAR of Oecussi 3.8 50.2 10.2 35.5 0.3 100.0 64.2 778 Viqueque 4.2 52.2 17.1 24.9 1.6 100.0 73.5 791 Wealth quintile Lowest 0.7 33.1 15.7 49.6 0.9 100.0 49.5 2,085 Second 2.2 39.8 19.5 37.7 0.8 100.0 61.5 2,287 Middle 3.5 48.7 18.4 28.6 0.7 100.0 70.6 2,423 Fourth 10.3 62.6 12.7 14.1 0.3 100.0 85.6 2,771 Highest 31.2 58.2 5.3 5.2 0.1 100.0 94.6 3,041 Total 11.0 49.9 13.7 24.9 0.5 100.0 74.6 12,607 1 Refers to women who attended schooling higher than the secondary level and women who can read a whole sentence or part of a sentence Characteristics of Respondents • 39 Table 3.3.2 Literacy: Men Percent distribution of men age 15-49 by level of schooling attended and level of literacy, and percentage literate, according to background characteristics, Timor-Leste DHS 2016 Background characteristic Higher than secondary schooling No schooling, primary or secondary school Total Percentage literate1 Number of men Can read a whole sentence Can read part of a sentence Cannot read at all Blind/ visually impaired Age 15-24 6.5 70.0 13.0 10.6 0.0 100.0 89.4 1,690 15-19 1.5 76.2 13.2 9.1 0.0 100.0 90.9 1,001 20-24 13.6 61.0 12.8 12.6 0.0 100.0 87.4 689 25-29 24.8 44.7 11.7 18.8 0.1 100.0 81.1 539 30-34 19.2 49.1 14.5 17.1 0.0 100.0 82.9 557 35-39 15.5 43.5 17.0 23.8 0.1 100.0 76.1 361 40-44 12.1 38.5 21.7 27.6 0.0 100.0 72.4 478 45-49 8.9 39.2 17.0 34.8 0.0 100.0 65.2 450 Residence Urban 25.6 60.7 7.1 6.5 0.0 100.0 93.5 1,374 Rural 5.6 51.1 18.8 24.5 0.0 100.0 75.5 2,701 Municipality Aileu 6.6 45.0 24.8 23.5 0.0 100.0 76.5 174 Ainaro 5.5 27.6 27.4 39.6 0.0 100.0 60.4 184 Baucau 10.1 66.4 11.2 12.4 0.0 100.0 87.6 388 Bobonaro 4.3 52.5 16.4 26.7 0.0 100.0 73.3 305 Covalima 7.9 62.1 10.4 19.6 0.0 100.0 80.4 234 Dili 28.0 60.3 5.0 6.7 0.0 100.0 93.3 1,098 Ermera 4.1 45.1 23.0 27.8 0.0 100.0 72.2 350 Lautem 5.3 43.5 26.6 24.6 0.0 100.0 75.4 188 Liquiçá 7.0 64.3 8.1 20.5 0.2 100.0 79.3 255 Manatuto 9.0 59.8 12.0 18.9 0.3 100.0 80.8 177 Manufahi 5.8 59.6 28.6 6.0 0.0 100.0 94.0 225 SAR of Oecussi 5.3 46.3 20.2 28.1 0.0 100.0 71.9 212 Viqueque 7.7 41.7 21.0 29.5 0.0 100.0 70.5 285 Wealth quintile Lowest 1.2 36.0 22.0 40.8 0.0 100.0 59.2 648 Second 3.3 49.7 20.4 26.5 0.0 100.0 73.5 823 Middle 7.3 56.1 18.8 17.6 0.1 100.0 82.3 809 Fourth 12.5 64.0 12.2 11.3 0.0 100.0 88.7 844 Highest 32.0 60.7 4.2 3.0 0.0 100.0 97.0 950 Total 15-49 12.4 54.3 14.9 18.4 0.0 100.0 81.6 4,075 50-59 5.5 30.1 16.7 47.1 0.6 100.0 52.3 547 Total 15-59 11.6 51.5 15.1 21.8 0.1 100.0 78.1 4,622 1 Refers to men who attended schooling higher than the secondary level and men who can read a whole sentence or part of a sentence 40 • Characteristics of Respondents Table 3.4.1 Exposure to mass media: Women Percentage of women age 15-49 who are exposed to specific media on a weekly basis, by background characteristics, Timor-Leste DHS 2016 Background characteristic Reads a newspaper at least once a week Watches television at least once a week Listens to the radio at least once a week Accesses all three media at least once a week Accesses none of the three media at least once a week Number of women Age 15-19 7.7 43.1 14.6 3.8 52.2 2,985 20-24 8.9 40.8 15.7 4.6 53.1 2,165 25-29 7.3 36.9 12.8 3.1 58.1 2,011 30-34 7.5 40.7 12.8 3.0 54.1 1,772 35-39 6.2 30.7 14.1 3.2 64.4 1,141 40-44 6.0 32.3 11.3 2.7 63.0 1,438 45-49 4.3 26.9 11.0 1.8 69.1 1,096 Residence Urban 12.5 63.7 19.3 5.9 31.5 4,182 Rural 4.5 24.7 10.6 2.1 70.2 8,425 Municipality Aileu 5.2 21.2 12.4 2.5 73.8 524 Ainaro 1.8 15.1 10.7 0.4 78.8 515 Baucau 4.4 37.5 10.2 1.7 57.6 1,288 Bobonaro 5.4 38.4 17.2 3.8 56.7 946 Covalima 4.4 19.8 9.1 0.9 74.0 750 Dili 11.9 65.9 16.3 4.8 30.4 3,206 Ermera 5.1 12.9 8.1 1.5 80.9 1,178 Lautem 4.6 33.0 12.0 2.6 61.6 645 Liquiçá 10.4 27.0 20.7 8.6 66.3 757 Manatuto 6.3 43.9 14.0 3.9 52.3 555 Manufahi 5.8 37.3 23.7 4.4 55.7 676 SAR of Oecussi 5.4 20.2 7.5 2.9 77.0 778 Viqueque 8.0 28.9 9.1 2.0 64.9 791 Education No education 0.3 12.7 6.0 0.3 84.2 2,741 Primary 3.2 23.6 9.4 1.1 71.4 1,922 Secondary 8.3 46.4 16.1 3.9 48.2 6,561 More than secondary 21.0 65.1 21.9 10.0 28.2 1,383 Wealth quintile Lowest 1.9 5.4 5.3 0.9 91.2 2,085 Second 3.2 11.6 9.2 0.9 81.7 2,287 Middle 5.0 27.1 12.1 2.2 67.2 2,423 Fourth 7.5 54.0 17.0 3.9 40.6 2,771 Highest 15.2 72.8 20.3 7.3 23.4 3,041 Total 7.2 37.6 13.5 3.4 57.4 12,607 Characteristics of Respondents • 41 Table 3.4.2 Exposure to mass media: Men Percentage of men age 15-49 who are exposed to specific media on a weekly basis, by background characteristics, Timor-Leste DHS 2016 Background characteristic Reads a newspaper at least once a week Watches television at least once a week Listens to the radio at least once a week Accesses all three media at least once a week Accesses none of the three media at least once a week Number of men Age 15-19 14.6 43.9 23.8 10.4 51.3 1,001 20-24 15.8 44.3 26.5 10.9 49.9 689 25-29 13.8 35.5 21.9 10.8 59.3 539 30-34 14.9 42.9 28.4 10.4 48.9 557 35-39 18.1 41.9 26.2 12.5 51.5 361 40-44 15.5 38.0 22.1 9.8 55.8 478 45-49 14.2 39.3 23.5 9.6 55.7 450 Residence Urban 25.0 65.9 35.2 16.5 27.3 1,374 Rural 10.1 28.9 19.2 7.6 65.8 2,701 Municipality Aileu 12.6 38.3 30.1 11.2 57.1 174 Ainaro 7.4 30.4 28.1 6.1 58.5 184 Baucau 3.3 44.4 11.4 1.3 50.9 388 Bobonaro 7.2 35.4 20.9 5.8 58.2 305 Covalima 18.2 19.6 16.4 14.2 76.3 234 Dili 25.1 65.1 36.2 14.0 25.0 1,098 Ermera 9.5 19.7 10.0 5.2 78.0 350 Lautem 3.3 24.2 7.2 2.5 74.2 188 Liquiçá 7.0 32.9 28.4 4.4 56.2 255 Manatuto 35.8 72.7 53.2 33.9 26.7 177 Manufahi 20.0 32.2 28.8 18.8 65.8 225 SAR of Oecussi 21.2 35.8 24.2 18.0 60.7 212 Viqueque 6.0 16.4 8.5 5.7 83.6 285 Education No education 1.9 17.3 9.0 1.6 79.9 772 Primary 7.1 30.1 21.5 5.4 62.3 736 Secondary 17.5 47.5 28.4 12.3 46.5 2,063 More than secondary 37.1 69.5 37.7 24.8 23.4 504 Wealth quintile Lowest 6.4 10.2 12.5 5.2 84.4 648 Second 8.3 20.6 17.5 5.9 72.9 823 Middle 11.5 36.4 22.4 8.6 56.5 809 Fourth 17.5 56.5 31.6 13.2 38.6 844 Highest 27.9 71.2 34.7 17.6 23.5 950 Total 15-49 15.1 41.4 24.6 10.6 52.8 4,075 50-59 9.0 28.2 19.8 7.5 66.1 547 Total 15-59 14.4 39.8 24.0 10.2 54.4 4,622 42 • Characteristics of Respondents Table 3.5.1 Internet usage: Women Percentage of women age 15-49 who have ever used the internet, and percentage who have used the internet in the past 12 months; and among women who have used the internet in the past 12 months, percent distribution by frequency of internet use in the past month, according to background characteristics, Timor-Leste DHS 2016 Background characteristic Ever used the internet Used the internet in the past 12 months Number Among respondents who have used the internet in the past 12 months, percentage who, in the past month, used internet: Almost every day At least once a week Less than once a week Not at all Total Number Age 15-19 31.3 26.8 2,985 45.0 40.2 14.2 0.7 100.0 799 20-24 42.0 37.1 2,165 46.2 41.0 12.7 0.1 100.0 802 25-29 31.1 28.5 2,011 51.2 32.0 16.2 0.6 100.0 572 30-34 22.2 20.4 1,772 44.6 36.2 18.6 0.5 100.0 361 35-39 14.9 12.2 1,141 38.4 40.8 20.9 0.0 100.0 140 40-44 8.5 7.4 1,438 45.9 33.3 20.8 0.0 100.0 106 45-49 5.0 4.0 1,096 (43.9) (41.0) (15.1) (0.0) (100.0) 44 Residence Urban 51.0 45.5 4,182 50.8 34.4 14.6 0.2 100.0 1,904 Rural 12.8 10.9 8,425 36.8 45.5 16.9 0.9 100.0 920 Municipality Aileu 13.8 11.0 524 35.5 48.5 14.9 1.1 100.0 57 Ainaro 10.3 9.5 515 44.2 49.4 5.6 0.7 100.0 49 Baucau 27.3 24.2 1,288 28.8 54.3 15.9 1.0 100.0 311 Bobonaro 16.0 13.4 946 39.5 44.8 15.3 0.4 100.0 126 Covalima 12.6 11.0 750 40.5 37.8 20.0 1.8 100.0 82 Dili 54.3 47.3 3,206 52.1 32.6 15.2 0.2 100.0 1,517 Ermera 6.0 5.6 1,178 49.6 39.9 10.5 0.0 100.0 66 Lautem 24.3 23.9 645 53.4 34.8 11.3 0.5 100.0 154 Liquiçá 14.2 13.1 757 42.6 37.5 19.9 0.0 100.0 99 Manatuto 17.7 15.4 555 45.7 43.7 9.5 1.0 100.0 85 Manufahi 24.8 23.0 676 44.7 38.9 16.1 0.3 100.0 155 SAR of Oecussi 7.2 5.8 778 35.6 33.7 30.7 0.0 100.0 45 Viqueque 11.9 9.7 791 23.7 53.9 20.8 1.6 100.0 77 Education No education 1.4 1.0 2,741 * * * * * 26 Primary 4.3 3.0 1,922 22.9 55.4 20.9 0.7 100.0 58 Secondary 30.4 25.8 6,561 42.1 39.3 18.0 0.5 100.0 1,691 More than secondary 79.5 75.9 1,383 54.7 35.1 10.0 0.2 100.0 1,049 Wealth quintile Lowest 3.9 3.3 2,085 25.6 50.0 22.9 1.6 100.0 68 Second 7.2 5.9 2,287 38.8 45.0 15.7 0.5 100.0 135 Middle 14.8 12.5 2,423 34.0 45.5 19.4 1.1 100.0 304 Fourth 29.9 25.0 2,771 37.9 41.5 20.1 0.5 100.0 694 Highest 58.4 53.4 3,041 53.6 34.1 12.2 0.2 100.0 1,623 Total 25.5 22.4 12,607 46.2 38.0 15.3 0.4 100.0 2,824 Notes: Figures in parentheses are based on 25-49 unweighted cases. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. Characteristics of Respondents • 43 Table 3.5.2 Internet usage: Men Percentage of men age 15-49 who have ever used the internet ever, and percentage who have used the internet in the past 12 months; and among men who have used the internet in the past 12 months, percent distribution by frequency of internet use in the past month, according to background characteristics, Timor-Leste DHS 2016 Background characteristic Ever used the internet Used the internet in the past 12 months Number Among respondents who have used the internet in the past 12 months, percentage who, in the past month, used internet: Almost every day At least once a week Less than once a week Not at all Total Number Age 15-19 34.2 28.4 1,001 38.5 54.8 6.3 0.5 100.0 284 20-24 49.9 46.2 689 49.5 41.0 9.4 0.0 100.0 319 25-29 44.7 41.9 539 44.5 41.7 12.6 1.3 100.0 226 30-34 37.6 34.9 557 49.3 44.2 5.1 1.5 100.0 194 35-39 31.9 29.9 361 38.9 49.8 10.8 0.5 100.0 108 40-44 19.1 16.7 478 43.4 37.6 17.8 1.3 100.0 80 45-49 14.0 12.7 450 (42.7) (54.9) (2.4) (0.0) (100.0) 57 Residence Urban 63.6 59.3 1,374 49.4 45.0 5.5 0.1 100.0 814 Rural 19.7 16.8 2,701 35.8 47.4 15.2 1.7 100.0 453 Municipality Aileu 25.3 22.5 174 20.3 52.5 27.2 0.0 100.0 39 Ainaro 21.8 18.0 184 22.5 74.2 3.3 0.0 100.0 33 Baucau 36.8 33.8 388 59.8 24.0 13.7 2.4 100.0 131 Bobonaro 22.4 18.4 305 31.1 62.7 6.2 0.0 100.0 56 Covalima 13.3 11.8 234 (25.5) (64.4) (10.1) (0.0) (100.0) 28 Dili 67.4 62.6 1,098 52.2 43.7 4.1 0.0 100.0 687 Ermera 9.0 7.7 350 (25.8) (55.3) (18.9) (0.0) (100.0) 27 Lautem 21.5 20.8 188 35.4 25.8 36.2 2.6 100.0 39 Liquiçá 24.8 24.2 255 39.1 52.3 7.9 0.8 100.0 62 Manatuto 28.1 20.7 177 52.5 31.7 15.0 0.8 100.0 37 Manufahi 37.1 31.3 225 1.4 81.9 16.7 0.0 100.0 71 SAR of Oecussi 19.6 16.4 212 (30.6) (42.6) (16.2) (10.6) (100.0) 35 Viqueque 10.5 8.3 285 (49.5) (40.6) (9.9) (0.0) (100.0) 24 Education No education 3.3 2.4 772 * * * * * 19 Primary 13.0 10.6 736 34.7 48.2 13.5 3.7 100.0 78 Secondary 41.7 36.7 2,063 37.8 51.6 10.0 0.5 100.0 757 More than secondary 84.4 82.0 504 59.8 34.1 5.7 0.4 100.0 413 Wealth quintile Lowest 6.7 5.9 648 (18.7) (58.8) (16.0) (6.5) (100.0) 38 Second 17.6 15.1 823 31.1 47.2 19.1 2.5 100.0 124 Middle 22.8 19.6 809 41.4 41.0 17.6 0.0 100.0 159 Fourth 41.2 35.8 844 36.9 53.5 8.9 0.7 100.0 302 Highest 72.2 67.8 950 53.0 42.4 4.5 0.1 100.0 644 Total 15-49 34.5 31.1 4,075 44.5 45.9 8.9 0.7 100.0 1,267 50-59 6.7 5.5 547 (28.9) (51.2) (19.9) (0.0) (100.0) 30 Total 15-59 31.2 28.1 4,622 44.2 46.0 9.2 0.7 100.0 1,297 Notes: Figures in parentheses are based on 25-49 unweighted cases. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 44 • Characteristics of Respondents Table 3.6.1 Employment status: Women Percent distribution of women age 15-49 by employment status, according to background characteristics, Timor-Leste DHS 2016 Background characteristic Employed in the 12 months preceding the survey Not employed in the 12 months preceding the survey Total Number of women Currently employed1 Not currently employed Age 15-19 15.3 2.8 81.9 100.0 2,985 20-24 24.7 4.0 71.3 100.0 2,165 25-29 34.6 4.1 61.2 100.0 2,011 30-34 41.7 3.6 54.7 100.0 1,772 35-39 48.6 2.6 48.8 100.0 1,141 40-44 49.6 1.7 48.7 100.0 1,438 45-49 51.1 2.0 46.9 100.0 1,096 Marital status Never married 21.9 3.9 74.2 100.0 4,615 Married or living together 39.9 2.6 57.4 100.0 7,697 Divorced/separated/ widowed 57.8 4.8 37.5 100.0 294 Number of living children 0 23.2 3.8 73.0 100.0 5,132 1-2 35.6 3.6 60.8 100.0 2,704 3-4 45.3 2.6 52.1 100.0 2,469 5+ 42.5 1.9 55.6 100.0 2,302 Residence Urban 32.0 4.9 63.1 100.0 4,182 Rural 34.6 2.3 63.1 100.0 8,425 Municipality Aileu 55.6 6.4 38.0 100.0 524 Ainaro 34.1 2.7 63.2 100.0 515 Baucau 24.8 3.6 71.6 100.0 1,288 Bobonaro 38.6 2.5 58.9 100.0 946 Covalima 20.4 1.2 78.4 100.0 750 Dili 29.6 5.7 64.7 100.0 3,206 Ermera 42.4 2.3 55.3 100.0 1,178 Lautem 25.3 1.5 73.3 100.0 645 Liquiçá 42.8 1.3 55.9 100.0 757 Manatuto 27.4 1.7 70.9 100.0 555 Manufahi 50.3 0.8 48.8 100.0 676 SAR of Oecussi 56.6 1.9 41.5 100.0 778 Viqueque 10.0 1.4 88.6 100.0 791 Education No education 41.6 2.0 56.4 100.0 2,741 Primary 36.7 3.2 60.1 100.0 1,922 Secondary 28.1 3.0 68.9 100.0 6,561 More than secondary 40.8 6.0 53.2 100.0 1,383 Wealth quintile Lowest 37.0 2.9 60.0 100.0 2,085 Second 35.2 2.2 62.5 100.0 2,287 Middle 32.3 2.5 65.1 100.0 2,423 Fourth 31.2 2.9 65.8 100.0 2,771 Highest 33.7 4.7 61.6 100.0 3,041 Total 33.7 3.1 63.1 100.0 12,607 1 "Currently employed" is defined as having done work in the past seven days. Includes persons who did not work in the past seven days but who are regularly employed and were absent from work for leave, illness, vacation, or any other such reason. Characteristics of Respondents • 45 Table 3.6.2 Employment status: Men Percent distribution of men age 15-49 by employment status, according to background characteristics, Timor- Leste DHS 2016 Background characteristic Employed in the 12 months preceding the survey Not employed in the 12 months preceding the survey Total Number of men Currently employed1 Not currently employed Age 15-19 37.8 3.1 59.1 100.0 1,001 20-24 59.8 3.1 37.1 100.0 689 25-29 75.4 4.2 20.4 100.0 539 30-34 87.2 2.1 10.7 100.0 557 35-39 89.7 1.4 8.9 100.0 361 40-44 89.6 1.7 8.7 100.0 478 45-49 88.6 1.6 9.8 100.0 450 Marital status Never married 50.8 3.1 46.1 100.0 2,043 Married or living together 88.8 2.0 9.2 100.0 2,003 Divorced/separated/ widowed (62.9) (12.6) (24.6) 100.0 29 Number of living children 0 52.0 3.3 44.6 100.0 2,209 1-2 89.5 2.0 8.5 100.0 664 3-4 90.2 2.2 7.6 100.0 634 5+ 91.2 1.0 7.8 100.0 568 Residence Urban 63.1 4.0 32.9 100.0 1,374 Rural 72.8 1.9 25.3 100.0 2,701 Municipality Aileu 89.7 1.8 8.6 100.0 174 Ainaro 89.7 3.0 7.3 100.0 184 Baucau 56.9 3.0 40.1 100.0 388 Bobonaro 65.3 1.4 33.3 100.0 305 Covalima 87.0 1.9 11.1 100.0 234 Dili 64.2 4.0 31.8 100.0 1,098 Ermera 91.1 2.8 6.1 100.0 350 Lautem 67.2 3.3 29.5 100.0 188 Liquiçá 64.6 1.5 33.8 100.0 255 Manatuto 69.1 1.4 29.5 100.0 177 Manufahi 66.2 1.9 31.9 100.0 225 SAR of Oecussi 88.4 2.1 9.5 100.0 212 Viqueque 40.5 1.0 58.5 100.0 285 Education No education 82.8 2.0 15.2 100.0 772 Primary 78.8 2.1 19.1 100.0 736 Secondary 60.1 3.0 36.9 100.0 2,063 More than secondary 74.1 2.8 23.1 100.0 504 Wealth quintile Lowest 77.2 2.6 20.2 100.0 648 Second 73.8 1.5 24.7 100.0 823 Middle 71.0 2.5 26.5 100.0 809 Fourth 64.3 3.0 32.7 100.0 844 Highest 64.0 3.3 32.7 100.0 950 Total 15-49 69.5 2.6 27.9 100.0 4,075 50-59 87.7 0.8 11.5 100.0 547 Total 15-59 71.7 2.4 25.9 100.0 4,622 Notes: Figures in parentheses are based on 25-49 unweighted cases. 1 "Currently employed" is defined as having done work in the past seven days. Includes persons who did not work in the past seven days but who are regularly employed and were absent from work for leave, illness, vacation, or any other such reason. 46 • Characteristics of Respondents Table 3.7.1 Occupation: Women Percent distribution of women age 15-49 employed in the 12 months preceding the survey by occupation, according to background characteristics, Timor-Leste DHS 2016 Background characteristic Professional/ technical/ managerial Clerical Sales and services Skilled manual Domestic service Agriculture Missing Total Number of women Age 15-19 1.1 1.0 18.3 1.9 38.5 39.2 0.1 100.0 541 20-24 4.7 6.5 25.7 4.4 28.5 30.1 0.1 100.0 621 25-29 13.0 8.2 30.4 6.0 18.3 23.5 0.7 100.0 780 30-34 16.2 8.9 28.7 5.4 12.9 27.1 0.7 100.0 802 35-39 15.7 6.6 29.5 4.5 11.4 32.3 0.1 100.0 584 40-44 11.7 4.2 32.4 6.6 11.0 33.6 0.6 100.0 738 45-49 9.8 3.5 29.6 5.7 7.5 43.3 0.6 100.0 582 Marital status Never married 8.2 6.3 19.0 3.6 27.6 34.7 0.6 100.0 1,189 Married or living together 11.9 5.7 31.0 5.6 14.6 30.8 0.4 100.0 3,276 Divorced/separated/ widowed 7.7 3.7 36.5 5.7 9.0 37.4 0.0 100.0 184 Number of living children 0 8.8 6.3 21.1 3.6 26.6 32.8 0.8 100.0 1,385 1-2 13.5 8.2 28.6 4.2 18.9 25.9 0.7 100.0 1,059 3-4 11.0 5.7 34.4 6.5 12.3 29.9 0.3 100.0 1,182 5+ 10.5 2.8 30.0 6.3 10.5 39.8 0.1 100.0 1,022 Residence Urban 16.5 13.8 36.3 4.9 22.1 5.6 0.9 100.0 1,541 Rural 8.0 1.8 24.1 5.1 15.5 45.2 0.3 100.0 3,108 Municipality Aileu 5.7 1.4 8.6 1.8 15.1 67.4 0.0 100.0 325 Ainaro 11.4 2.6 23.3 7.2 4.7 50.7 0.0 100.0 189 Baucau 14.5 5.3 36.1 7.3 2.1 34.8 0.0 100.0 366 Bobonaro 7.1 1.7 35.1 4.1 23.7 27.8 0.5 100.0 389 Covalima 21.8 5.7 32.6 6.1 13.6 20.2 0.0 100.0 162 Dili 15.4 16.5 38.7 5.3 20.6 2.5 1.0 100.0 1,133 Ermera 5.1 0.1 15.6 0.5 12.1 65.8 0.7 100.0 526 Lautem 11.7 5.0 22.3 15.7 21.7 23.6 0.0 100.0 172 Liquiçá 5.6 2.1 18.1 2.6 44.2 26.4 0.9 100.0 334 Manatuto 16.4 7.7 27.0 8.0 20.4 20.0 0.6 100.0 162 Manufahi 10.0 1.2 22.7 2.0 25.6 38.5 0.0 100.0 346 SAR of Oecussi 6.5 0.6 30.8 7.9 7.3 46.9 0.0 100.0 456 Viqueque 16.9 2.4 37.3 9.9 6.6 27.0 0.0 100.0 90 Education No education 0.2 0.1 26.3 5.4 11.0 57.0 0.0 100.0 1,194 Primary 0.9 1.3 31.9 5.4 17.6 42.5 0.5 100.0 766 Secondary 10.7 5.9 32.3 5.1 22.9 22.9 0.1 100.0 2,042 More than secondary 42.4 21.4 14.0 3.9 13.7 2.4 2.2 100.0 647 Wealth quintile Lowest 2.1 0.5 14.7 6.0 10.4 66.3 0.0 100.0 833 Second 3.6 0.6 21.5 4.6 15.6 54.1 0.0 100.0 857 Middle 7.4 1.6 29.1 4.1 21.2 36.1 0.5 100.0 844 Fourth 11.8 5.0 40.2 6.0 22.8 13.7 0.5 100.0 946 Highest 24.0 17.1 32.2 4.7 17.7 3.2 1.1 100.0 1,168 Total 10.8 5.8 28.2 5.1 17.7 32.0 0.5 100.0 4,649 Characteristics of Respondents • 47 Table 3.7.2 Occupation: Men Percent distribution of men age 15-49 employed in the 12 months preceding the survey by occupation, according to background characteristics, Timor- Leste DHS 2016 Background characteristic Professional/ technical/ managerial Clerical Sales and services Skilled manual Unskilled manual Domestic service Agriculture Missing Total Number of men Age 15-19 0.8 0.2 11.1 14.5 3.6 12.1 57.4 0.2 100.0 409 20-24 3.0 2.9 13.4 29.7 3.9 6.6 39.9 0.5 100.0 434 25-29 9.4 9.7 11.5 28.3 2.3 2.2 36.5 0.2 100.0 429 30-34 16.3 8.2 6.4 29.4 2.8 0.6 35.5 0.8 100.0 497 35-39 16.3 6.7 10.6 23.0 0.5 1.1 40.8 1.0 100.0 329 40-44 16.3 6.9 7.7 16.1 0.6 0.2 51.7 0.3 100.0 437 45-49 16.2 6.1 7.0 15.7 0.9 0.2 53.4 0.4 100.0 405 Marital status Never married 4.7 4.1 11.4 21.4 3.7 8.0 46.3 0.4 100.0 1,100 Married or living together 15.2 6.8 8.3 23.3 1.2 0.5 44.1 0.6 100.0 1,818 Divorced/separated/ widowed * * * * * * * * 100.0 22 Number of living children 0 5.0 4.4 11.7 22.5 3.6 7.2 45.2 0.4 100.0 1,224 1-2 16.5 8.0 9.2 26.7 2.0 0.6 36.4 0.7 100.0 607 3-4 14.2 7.4 8.5 23.4 0.7 0.7 44.3 0.8 100.0 586 5+ 16.0 5.0 6.4 17.5 0.6 0.1 54.3 0.2 100.0 523 Residence Urban 20.5 13.1 20.1 31.3 2.5 4.4 7.1 1.1 100.0 922 Rural 6.9 2.6 4.8 18.7 2.0 2.8 62.1 0.2 100.0 2,018 Municipality Aileu 9.5 2.1 4.9 10.9 1.7 1.4 69.5 0.0 100.0 159 Ainaro 7.8 2.1 7.2 15.6 3.2 4.3 59.2 0.4 100.0 170 Baucau 10.2 6.2 7.8 15.3 6.0 1.1 53.3 0.0 100.0 232 Bobonaro 8.9 2.6 6.0 27.5 1.7 1.8 50.8 0.6 100.0 203 Covalima 8.2 1.2 2.9 31.8 3.9 5.3 45.9 0.8 100.0 208 Dili 20.4 13.8 22.3 31.3 2.7 2.8 6.0 0.7 100.0 748 Ermera 5.2 1.0 3.8 11.2 1.0 4.1 73.6 0.0 100.0 328 Lautem 12.3 1.2 3.4 21.8 0.0 0.5 60.9 0.0 100.0 133 Liquiçá 8.4 4.6 7.0 16.5 1.6 1.6 59.7 0.5 100.0 169 Manatuto 8.0 6.3 3.1 29.6 1.0 1.0 50.0 0.9 100.0 124 Manufahi 6.3 2.4 7.4 21.5 0.0 5.1 57.3 0.0 100.0 153 SAR of Oecussi 7.0 3.5 4.8 23.0 0.9 8.1 50.9 1.7 100.0 192 Viqueque 6.4 8.1 3.8 18.7 0.0 5.9 57.1 0.0 100.0 118 Education No education 1.2 0.0 4.9 20.5 1.5 0.5 71.3 0.1 100.0 655 Primary 3.5 1.0 9.8 25.8 2.3 2.1 55.2 0.4 100.0 595 Secondary 12.1 5.5 11.7 23.9 2.4 5.6 38.2 0.6 100.0 1,302 More than secondary 36.8 24.6 9.9 17.2 2.1 1.9 6.6 0.9 100.0 388 Wealth quintile Lowest 1.7 0.4 1.7 15.1 0.4 4.3 76.2 0.1 100.0 518 Second 2.9 1.1 4.6 18.6 1.8 2.6 68.1 0.3 100.0 620 Middle 9.3 2.8 6.4 22.1 4.4 3.4 51.1 0.5 100.0 595 Fourth 12.7 6.8 16.7 31.5 1.9 2.6 27.6 0.3 100.0 568 Highest 27.2 16.9 17.5 25.3 2.1 3.5 6.4 1.1 100.0 639 Total 15-49 11.2 5.9 9.6 22.6 2.2 3.3 44.8 0.5 100.0 2,940 50-59 14.4 3.4 4.4 14.3 0.0 1.0 61.7 0.8 100.0 484 Total 15-59 11.6 5.5 8.8 21.5 1.8 3.0 47.2 0.5 100.0 3,424 Note: An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 48 • Characteristics of Respondents Table 3.8 Type of employment: Women Percent distribution of women age 15-49 employed in the 12 months preceding the survey by type of earnings, type of employer, and continuity of employment, according to type of employment (agricultural or nonagricultural), Timor-Leste DHS 2016 Employment characteristic Agricultural work Nonagricultural work Total Type of earnings Cash only 15.1 60.6 46.0 Cash and in-kind 7.6 4.4 5.5 In-kind only 2.8 0.2 1.1 Not paid 74.4 34.8 47.4 Total 100.0 100.0 100.0 Type of employer Employed by family member 80.9 71.7 74.6 Employed by nonfamily member 1.3 10.3 7.5 Self-employed 17.8 18.0 17.9 Total 100.0 100.0 100.0 Continuity of employment All year 42.6 70.1 61.3 Seasonal 50.7 27.4 34.9 Occasional 6.7 2.5 3.8 Total 100.0 100.0 100.0 Number of women employed during the last 12 months 1,489 3,138 4,649 Note: Total includes women with missing information on type of employment who are not shown separately. Characteristics of Respondents • 49 Table 3.9.1 Tobacco smoking: Women Percentage of women age 15-49 who smoke various tobacco products, according to background characteristics and maternity status, Timor-Leste DHS 2016 Background characteristic Percentage who smoke:1 Number of women Cigarettes2 Other type of tobacco3 Any type of tobacco Age 15-19 1.4 0.1 1.4 2,985 20-24 2.2 0.3 2.2 2,165 25-29 3.4 0.2 3.4 2,011 30-34 4.9 0.3 4.9 1,772 35-39 4.4 0.7 4.4 1,141 40-44 7.5 0.2 7.5 1,438 45-49 10.3 0.1 10.4 1,096 Residence Urban 4.4 0.2 4.4 4,182 Rural 4.0 0.2 4.0 8,425 Municipality Aileu 5.1 0.4 5.1 524 Ainaro 5.8 0.2 5.8 515 Baucau 2.3 0.1 2.3 1,288 Bobonaro 2.2 0.0 2.2 946 Covalima 1.2 0.1 1.2 750 Dili 4.8 0.2 4.8 3,206 Ermera 2.8 0.2 2.8 1,178 Lautem 6.7 1.2 6.9 645 Liquiçá 5.6 0.1 5.6 757 Manatuto 7.7 0.2 7.7 555 Manufahi 4.9 0.1 4.9 676 SAR of Oecussi 4.9 0.5 4.9 778 Viqueque 1.9 0.0 1.9 791 Education No education 6.5 0.2 6.5 2,741 Primary 4.9 0.3 4.9 1,922 Secondary 3.1 0.2 3.1 6,561 More than secondary 2.8 0.5 2.8 1,383 Wealth quintile Lowest 4.6 0.2 4.6 2,085 Second 4.7 0.5 4.7 2,287 Middle 3.9 0.2 4.0 2,423 Fourth 4.1 0.2 4.1 2,771 Highest 3.5 0.1 3.5 3,041 Total 4.1 0.2 4.1 12,607 1 Includes daily and occasional (less than daily) use 2 Cigarettes include kreteks 3 Includes pipes full of tobacco, cigars, cheroots and cigarillos 50 • Characteristics of Respondents Table 3.9.2 Tobacco smoking: Men Percentage of men age 15-49 who smoke various tobacco products, and percent distribution of men by smoking frequency, according to background characteristics, Timor-Leste DHS 2016 Background characteristic Percentage who smoke:1 Smoking frequency Total Number of men Cigarettes2 Other type of tobacco3 Any type of tobacco Daily smoker Occasional smoker4 Non- smoker Age 15-19 25.2 1.8 25.4 13.3 14.2 72.5 100.0 1,001 20-24 56.1 5.7 56.3 38.2 21.9 39.9 100.0 689 25-29 69.3 8.4 69.7 53.3 19.1 27.6 100.0 539 30-34 64.4 5.9 65.0 54.4 14.1 31.5 100.0 557 35-39 61.6 7.2 62.6 51.6 13.9 34.5 100.0 361 40-44 56.3 8.2 57.1 47.0 12.9 40.1 100.0 478 45-49 59.3 7.3 59.6 47.6 16.2 36.2 100.0 450 Residence Urban 52.8 5.7 53.2 40.2 14.9 45.0 100.0 1,374 Rural 52.0 5.7 52.4 39.2 16.9 43.9 100.0 2,701 Municipality Aileu 61.5 7.5 61.5 43.0 20.8 36.1 100.0 174 Ainaro 68.8 6.5 68.8 57.8 13.8 28.4 100.0 184 Baucau 48.7 2.1 48.7 39.0 10.2 50.9 100.0 388 Bobonaro 45.6 3.3 45.6 23.7 22.0 54.2 100.0 305 Covalima 37.7 10.9 40.1 35.0 20.8 44.2 100.0 234 Dili 58.1 4.6 58.3 46.3 13.5 40.2 100.0 1,098 Ermera 66.4 10.6 67.9 34.2 36.0 29.8 100.0 350 Lautem 43.0 3.0 43.0 32.8 10.4 56.8 100.0 188 Liquiçá 61.0 2.1 61.0 41.9 19.7 38.4 100.0 255 Manatuto 33.5 6.8 34.2 35.2 19.1 45.7 100.0 177 Manufahi 35.7 7.6 35.7 28.2 10.9 60.9 100.0 225 SAR of Oecussi 73.9 16.4 75.0 63.5 12.7 23.8 100.0 212 Viqueque 27.1 0.8 27.1 23.7 4.6 71.7 100.0 285 Education No education 61.1 9.5 62.3 49.1 16.1 34.7 100.0 772 Primary 60.5 4.8 60.7 47.0 17.0 35.9 100.0 736 Secondary 45.0 4.7 45.3 32.4 16.1 51.5 100.0 2,063 More than secondary 56.4 5.5 56.4 43.3 15.3 41.4 100.0 504 Wealth quintile Lowest 57.3 9.2 57.6 45.7 15.1 39.2 100.0 648 Second 55.7 5.8 56.4 41.9 17.2 40.9 100.0 823 Middle 52.7 5.7 53.3 38.3 18.7 43.0 100.0 809 Fourth 48.3 4.0 48.8 35.8 16.8 47.5 100.0 844 Highest 49.0 4.8 49.0 37.7 13.3 49.0 100.0 950 Total 15-49 52.3 5.7 52.7 39.5 16.2 44.3 100.0 4,075 50-59 61.1 7.6 61.2 47.5 16.5 35.9 100.0 547 Total 15-59 53.3 5.9 53.7 40.5 16.2 43.3 100.0 4,622 1 Includes daily and occasional (less than daily) use 2 Includes manufactured cigarettes, hand-rolled cigarettes, and kreteks 3 Includes pipes full of tobacco, cigars, cheroots and cigarillos 4 Occasional refers to less often than daily use Characteristics of Respondents • 51 Table 3.10 Average number of cigarettes smoked daily: Men Among men age 15-49 who smoke cigarettes daily, percent distribution by average number of cigarettes smoked per day, according to background characteristics, Timor-Leste DHS 2016 Background characteristic Average number of cigarettes smoked per day1 Total Number of respondents who smoke cigarettes daily1 <5 5-9 10-14 15-24 ≥25 Don't know/ missing Age 15-19 42.9 4.5 2.4 7.0 0.0 43.2 100.0 122 20-24 30.8 9.5 1.5 10.8 3.3 44.1 100.0 245 25-29 41.1 6.2 6.8 8.9 4.6 32.4 100.0 276 30-34 35.7 5.5 4.3 9.1 5.4 40.0 100.0 287 35-39 35.7 9.7 2.4 6.8 2.2 43.1 100.0 175 40-44 38.0 6.8 2.2 7.8 5.6 39.5 100.0 220 45-49 26.9 14.4 3.0 7.9 6.2 41.6 100.0 199 Residence Urban 38.7 12.2 2.8 7.3 2.5 36.5 100.0 530 Rural 34.0 5.8 3.8 9.2 5.2 42.0 100.0 995 Municipality Aileu 25.3 0.0 8.1 29.4 9.1 28.1 100.0 74 Ainaro 4.3 4.7 3.8 20.4 8.5 58.2 100.0 101 Baucau 72.6 4.4 5.9 8.7 2.2 6.2 100.0 149 Bobonaro 46.6 21.6 0.0 0.0 0.0 31.9 100.0 72 Covalima 0.6 1.3 0.0 4.5 0.7 92.9 100.0 52 Dili 39.2 12.7 1.9 5.6 2.1 38.6 100.0 489 Ermera 78.0 0.0 3.1 0.8 3.3 14.8 100.0 118 Lautem 5.2 0.0 0.4 9.1 32.9 52.4 100.0 62 Liquiçá 19.0 14.4 0.0 0.0 0.0 66.6 100.0 105 Manatuto 19.3 7.7 0.0 7.9 3.1 62.1 100.0 43 Manufahi 3.2 5.8 0.0 8.7 12.3 70.0 100.0 60 SAR of Oecussi 40.7 7.1 9.7 5.9 1.2 35.4 100.0 134 Viqueque 10.5 1.9 12.0 34.6 1.7 39.3 100.0 65 Education No education 31.9 7.8 6.3 9.5 4.5 40.0 100.0 364 Primary 30.3 7.2 2.5 9.9 3.6 46.4 100.0 332 Secondary 37.4 8.0 2.5 7.9 4.7 39.6 100.0 620 More than secondary 45.5 10.0 3.0 6.9 3.3 31.5 100.0 208 Wealth quintile Lowest 25.7 7.6 6.7 9.0 3.9 47.1 100.0 283 Second 35.4 6.3 2.7 10.5 4.0 41.2 100.0 334 Middle 37.3 4.3 3.7 8.6 6.0 39.9 100.0 285 Fourth 35.8 9.3 3.1 10.5 4.7 36.6 100.0 278 Highest 42.5 12.2 1.5 4.7 3.0 36.0 100.0 345 Total 15-49 35.7 8.0 3.4 8.6 4.2 40.0 100.0 1,524 50-59 36.2 8.5 5.4 9.3 4.3 36.3 100.0 254 Total 15-59 35.7 8.1 3.7 8.7 4.3 39.5 100.0 1,778 1 Includes manufactured cigarettes, hand-rolled cigarettes, and kreteks 52 • Characteristics of Respondents Table 3.11 Smokeless tobacco use and any tobacco use Percentage of women and men age 15-49 who currently use smokeless tobacco, according to type of tobacco product, and percentage who use any type of tobacco, Timor-Leste DHS 2016 Tobacco product Women Men Chewing tobacco 0.2 3.5 Betel quid with tobacco 0.1 19.8 Other type of smokeless tobacco 0.0 1.8 Any type of smokeless tobacco1 0.2 20.9 Any type of tobacco2 4.7 56.6 Number 12,607 4,075 Note: Table includes women and men who use smokeless tobacco daily or occasionally (less than daily). 1 Includes chewing tobacco, betel quid with tobacco, and any other type of smokeless tobacco. 2 Includes all types of smokeless tobacco shown in this table plus cigarettes, kreteks, pipes, cigars, cheroots, cigarillos, and beetle quid with tobacco. Characteristics of Respondents • 53 Table 3.12.1 Alcohol consumption: Women Percentage of women who have ever drunk alcohol; among women who ever drank alcohol, median age at first consumption, percentage who consumed alcohol at least once a week within the past three months, percentage who have ever been drunk from consuming alcohol, and percentage who have been drunk at least once within the past three months, according to background characteristics, Timor-Leste DHS 2016 Background characteristic Percentage of women who ever drank alcohol Among women who ever drank alcohol Percentage who ever drank alcohol Number of women Median age at first consumption Percentage who, in the last three months, consumed alcohol at least once a week Percentage who have ever been drunk from consuming alcohol Percentage who, in the last three months, have been drunk at least once Number of women Age 15-19 4.3 2,985 15.6 12.1 34.8 22.4 127 20-24 8.2 2,165 19.4 13.4 48.1 36.7 177 25-29 7.8 2,011 20.1 23.0 36.7 30.5 158 30-34 9.0 1,772 23.0 18.0 24.0 20.8 159 35-39 9.6 1,141 22.9 20.9 16.4 13.6 109 40-44 9.7 1,438 20.7 33.5 21.8 19.5 140 45-49 13.5 1,096 20.9 28.4 26.6 23.0 147 Marital status Never married 6.5 4,615 18.5 14.5 33.9 24.5 301 Married or living together 8.7 7,697 20.6 24.2 28.8 23.8 670 Divorced/separated/ widowed 15.8 294 (20.6) (20.3) (39.5) (36.6) 47 Residence Urban 11.2 4,182 20.0 13.0 39.1 29.4 468 Rural 6.5 8,425 20.3 28.2 23.7 20.6 549 Municipality Aileu 5.8 524 15.6 32.4 32.0 29.9 30 Ainaro 4.3 515 (21.0) (39.8) (11.7) (7.4) 22 Baucau 7.4 1,288 20.3 48.7 7.3 5.8 96 Bobonaro 5.0 946 21.9 18.2 42.7 28.3 47 Covalima 2.0 750 * * * * 15 Dili 13.4 3,206 20.2 10.1 40.3 30.8 431 Ermera 5.8 1,178 19.7 24.8 23.1 23.1 68 Lautem 3.1 645 (13.7) (30.9) (49.8) (43.5) 20 Liquiçá 5.9 757 19.1 55.8 32.1 29.6 45 Manatuto 2.7 555 (15.3) (48.5) (22.5) (16.8) 15 Manufahi 5.8 676 17.1 11.2 9.5 7.6 39 SAR of Oecussi 21.6 778 23.4 11.6 30.1 25.5 168 Viqueque 2.7 791 (3.0) (57.3) (9.4) (9.4) 21 Education No education 8.2 2,741 20.4 35.5 28.4 26.1 226 Primary 8.6 1,922 20.8 21.7 24.7 20.6 165 Secondary 6.4 6,561 19.0 16.5 32.6 24.3 421 More than secondary 14.8 1,383 20.5 14.7 34.6 26.8 205 Wealth quintile Lowest 7.9 2,085 20.5 23.2 23.8 19.9 164 Second 5.6 2,287 18.9 29.2 24.0 21.9 128 Middle 6.4 2,423 20.4 29.4 25.6 19.9 154 Fourth 8.0 2,771 19.9 18.8 31.7 25.3 223 Highest 11.5 3,041 20.4 15.2 38.3 29.5 349 Total 8.1 12,607 20.2 21.2 30.8 24.6 1,017 Notes: Figures in parentheses are based on 25-49 unweighted cases. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 54 • Characteristics of Respondents Table 3.12.2 Alcohol consumption: Men Percentage of men who have ever drunk alcohol; among men who ever drank alcohol, median age at first consumption, percentage who consumed alcohol at least once a week within the past three months, percentage who have ever been drunk from consuming alcohol, and percentage who have been drunk at least once within the past three months, according to background characteristics, Timor-Leste DHS 2016 Background characteristic Percentage of men who ever drank alcohol Among men who ever drank alcohol Percentage who ever drank alcohol Number of men Median age at first consumption Percentage who, in the last three months, consumed alcohol at least once a week Percentage who have ever been drunk from consuming alcohol Percentage who, in the last three months, have been drunk at least once Number of men Age 15-19 22.7 1,001 16.2 36.6 30.0 27.4 227 20-24 49.8 689 18.0 39.8 51.9 44.0 343 25-29 54.5 539 18.3 51.1 51.4 41.3 294 30-34 58.4 557 18.6 54.1 60.3 50.3 325 35-39 52.3 361 20.1 51.1 49.8 39.8 189 40-44 50.0 478 20.2 54.3 48.9 36.3 239 45-49 54.6 450 20.2 47.1 48.1 40.0 245 Marital status Never married 36.7 2,043 17.5 43.0 46.4 40.2 751 Married or living together 54.5 2,003 19.3 50.7 51.6 40.9 1,091 Divorced/separated/ widowed (72.0) 29 * * * * 21 Residence Urban 58.6 1,374 18.1 48.2 48.4 40.6 804 Rural 39.2 2,701 18.5 47.2 50.4 40.8 1,058 Municipality Aileu 46.3 174 16.3 52.5 73.7 69.1 80 Ainaro 52.4 184 17.7 48.5 64.7 51.3 96 Baucau 47.8 388 18.6 60.5 65.6 62.1 185 Bobonaro 52.0 305 17.4 51.0 54.6 37.2 159 Covalima 9.1 234 * * * * 21 Dili 65.9 1,098 18.3 50.7 46.1 38.9 723 Ermera 23.3 350 19.7 48.7 41.2 34.5 82 Lautem 31.7 188 18.0 70.2 34.7 34.7 60 Liquiçá 59.1 255 20.3 18.2 42.7 26.9 151 Manatuto 42.2 177 1.8 43.8 23.1 16.0 75 Manufahi 22.1 225 18.2 41.8 62.6 36.3 50 SAR of Oecussi 69.6 212 19.3 22.7 42.7 36.0 148 Viqueque 11.7 285 (16.7) (90.7) (38.5) (35.3) 33 Education No education 44.0 772 18.4 48.8 50.8 44.2 340 Primary 53.2 736 19.3 50.0 53.5 45.9 391 Secondary 40.4 2,063 17.6 47.3 47.9 38.5 834 More than secondary 59.0 504 19.0 44.2 47.6 36.1 298 Wealth quintile Lowest 40.2 648 18.2 46.5 48.3 38.2 261 Second 40.8 823 17.8 52.3 49.0 43.5 336 Middle 38.7 809 18.6 44.4 52.8 42.2 313 Fourth 49.1 844 18.2 44.4 51.1 42.2 414 Highest 56.7 950 18.4 49.6 47.3 38.1 539 Total 15-49 45.7 4,075 18.3 47.6 49.5 40.7 1,863 50-59 43.3 547 20.5 49.7 44.0 32.2 237 Total 15-59 45.4 4,622 18.5 47.9 48.9 39.7 2,100 Notes: Figures in parentheses are based on 25-49 unweighted cases. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. Marriage and Sexual Activity • 55 MARRIAGE AND SEXUAL ACTIVITY 4 Key Findings  Age at first marriage: Women marry on average 5 years earlier than men in Timor-Leste.  Polygyny: Across municipalities, the percentage of married women who reported that their husband has more than 1 wife ranges from 1% to 11%.  Sexual initiation: The median age at first sexual intercourse is 1.2 years earlier than the median age at first marriage among women and 4 years prior to marriage among men. arriage and sexual activity help determine the extent to which women are exposed to the risk of pregnancy. Thus, they are important determinants of fertility levels. However, the timing and circumstances of marriage and sexual activity also have profound consequences for women’s and men’s lives. 4.1 MARITAL STATUS Currently married Women and men who report being married or living together with a partner as though married at the time of the survey Sample: Women and men age 15-49 Sixty-one percent of women and 49% of men age 15-49 are currently married (also referred to as currently in a union), that is, they are either married or living together. (Table 4.1). Thirty-seven percent of women and 50% of men age 15-49 have never married (Figure 4.1). Very few women (2%) and men (1%) are widowed, divorced, or separated. While many young people are not yet married, most people do marry; only 6% of women and men in their forties have never married. Trends: The percentage of women age 15-49 who are currently in a union has remained the same since the previous TLDHS of 2009-10; the percentage of men who are currently in union has declined slightly from 53% to 49%. M Figure 4.1 Marital status Never married 37% Married or living together 61% Widowed/ divorced/ separated 2% Women Never married 50% Married or living together 49% Widowed/ divorced/ separated 1% Men Percent distribution of women and men age 15-49 56 • Marriage and Sexual Activity 4.2 POLYGYNY Polygyny Women who report that their husband or partner has other wives are considered to be in a polygynous marriage. Sample: Currently married women age 15-49 Four percent of women reported that their husband or partner has other wives (Table 4.2.1). One percent of men report having multiple wives (Table 4.2.2). Trends: In 2009-10, 2% of women reported that their husband or partner had other wives and 1% of men reported having multiple wives. Patterns by background characteristics  The percentage of married women who have co-wives does not vary greatly by age or urban/rural residence (Table 4.2.1).  At 11%, women in Bobonaro municipality are the most likely to have co-wives. Five percent or more of women living in Baucau, Dili, and SAR of Oecussi also report having co-wives, compared with 1% of women in Manufahi (Figure 4.2). Figure 4.2 Polygyny by municipality Percent of currently married women age 15-49 in a polygynous union  Polygyny spans all education levels and wealth quintiles; married women in the middle quintile are the most likely to have co-wives (6%). 4.3 AGE AT FIRST MARRIAGE Median age at first marriage Age by which half of respondents have been married. Sample: Women age 20-49 and 25-49, and men age 20-49, 25-49, 20-59, 25- 59, and 30-59 Women marry on average 5 years earlier than men in Timor-Leste. The median age at first marriage is 21.7 years among women age 25-49 and 26.8 years among men age 30-59 (Table 4.4). Thirty-five percent of women age 20-49 marry in their teen years, while only 9% of men marry before age 20 (Table 4.3). Marriage and Sexual Activity • 57 Trends: The median age at first marriage among women age 25-49 has increased slightly, from 20.9 years in 2009-10 to 21.7 years in 2016. During the same time period, the percentage of women age 20-49 who married in their teens declined from 41% to 35%. Among men, the median age at first marriage has increased by about 1 year of age, from age 25.3 among 30-49 year-olds in 2009-10, up to age 26.8 among 30-59 year-olds in 2016. Patterns by background characteristics  Urban women tend to marry later than rural women. Among women age 25-49, the median age at first marriage among urban women is 22.6 and 21.3 among rural women (Table 4.4). Median age at marriage is also about 1 year older among urban men, compared with rural men.  The lowest median age at marriage among women is in SAR of Oecussi, at 20.3 years of age. At nearly 23 years of age (22.7), it is the women of Dili who have the highest median age at marriage.  The median age at marriage rises by 2-3 years with increasing education and increasing wealth (Figure 4.3). 4.4 AGE AT FIRST SEXUAL INTERCOURSE Median age at first sexual intercourse Age by which half of respondents have had sexual intercourse. Sample: Women age 20-49 and 25-49 and men age 20-49, 25-49, 20-59, and 25-59 The median age at first sexual intercourse is 20.5 years among women age 25-49 (Table 4.5). Twenty- six percent of women age 25-49 had first sex before age 18, and 60% by age 22. By age 25, 75% of women have had sexual intercourse. On average, men initiate sexual intercourse later than women do. The median age at first intercourse among men age 25-49 is 22.9 years, more than 2 years later than women. Fifteen percent of men age 25-49 had first sex before age 18, and 44% by age 22. By age 25, 61% of men have had sexual intercourse. A comparison of the median age at first intercourse with the median age at first marriage can be used as a measure of whether people are engaging in sex before marriage. The median age at first intercourse among women age 25-49 is 1 year younger than the median age at first marriage (20.5 years versus 21.7 years) (Figure 4.4). The median age at first intercourse among men age 30-59 is 26.8 years, about 4 years older than the median age at marriage of 22.9 among men age 24-49. Trends: The median age at first sex between 2009-10 and 2016 has dipped slightly lower among women (from 20.9 to 20.5) and remained at age 23 among men. Figure 4.3 Women’s median age at marriage by wealth Figure 4.4 Median age at first sex and first marriage 20.9 21.1 21.2 21.5 23.2 Lowest Second Middle Fourth Highest Median age at first marriage among women age 25-49 Poorest Wealthiest 20.5 21.722.9 26.8* Median age at first sex Median age at first marriage Median age in years Women age 25-49 Men age 25-49 * Men age 30-59 58 • Marriage and Sexual Activity Patterns by background characteristics  Rural women age 25-49 begin having sex about a bit younger than urban women. The median age at first sex is 20.2 among rural women compared with 21.8 among urban women age 25-49 (Table 4.6).  The median age at first sex among women age 25-49 is lowest in Covalima (18.9 years), the highest median age at first sex is seen among the women of Dili (22.0 years).  There is no particular pattern in the median age at first sex by education or wealth quintile, either for women or men. 4.5 RECENT SEXUAL ACTIVITY The survey collected data on recent sexual activity. Forty-two percent of women and 45% of men age 15-49 reported having sexual intercourse within the 4 weeks prior to the survey. Thirty-five percent of women and 31% of men report never having had sexual intercourse, nearly identical to the percentages reported in the 2009-10 TLDHS. For information on recent sexual activity by background characteristics, see Tables 4.7.1 and 4.7.2. LIST OF TABLES For more information on marriage and sexual activity, see the following tables:  Table 4.1 Current marital status  Table 4.2.1 Number of women’s co-wives  Table 4.2.2 Number of men’s wives  Table 4.3 Age at first marriage  Table 4.4 Median age at first marriage according to background characteristics  Table 4.5 Age at first sexual intercourse  Table 4.6 Median age at first sexual intercourse according to background characteristics  Table 4.7.1 Recent sexual activity: Women  Table 4.7.2 Recent sexual activity: Men Marriage and Sexual Activity • 59 Table 4.1 Current marital status Percent distribution of women and men age 15-49 by current marital status, according to age, Timor-Leste DHS 2016 Age Marital status Total Percentage of respondents currently in union Number of respondents Never married Married Living together Divorced Separated Widowed WOMEN 15-19 91.7 5.2 3.0 0.1 0.1 0.0 100.0 8.2 2,985 20-24 51.2 35.6 12.0 0.6 0.4 0.2 100.0 47.6 2,165 25-29 19.5 66.2 12.1 1.0 0.7 0.5 100.0 78.3 2,011 30-34 8.2 80.3 8.5 1.9 0.4 0.7 100.0 88.8 1,772 35-39 7.6 84.1 4.1 1.9 0.3 2.0 100.0 88.2 1,141 40-44 5.9 85.5 4.9 0.7 0.2 2.7 100.0 90.5 1,438 45-49 5.7 84.7 3.4 1.5 0.7 4.1 100.0 88.0 1,096 Total 15-49 36.6 53.9 7.1 0.9 0.3 1.1 100.0 61.1 12,607 MEN 15-19 98.7 0.2 0.5 0.1 0.4 0.0 100.0 0.7 1,001 20-24 83.1 12.7 3.3 0.0 0.9 0.1 100.0 16.0 689 25-29 47.8 41.2 10.7 0.0 0.2 0.1 100.0 51.9 539 30-34 21.9 71.2 6.5 0.2 0.1 0.1 100.0 77.8 557 35-39 14.1 79.5 6.4 0.1 0.0 0.0 100.0 85.8 361 40-44 6.9 87.2 5.3 0.2 0.0 0.4 100.0 92.4 478 45-49 4.3 90.1 3.4 0.0 0.3 1.9 100.0 93.6 450 Total 15-49 50.1 44.6 4.6 0.1 0.3 0.3 100.0 49.1 4,075 50-59 6.6 85.9 4.4 0.2 0.0 2.8 100.0 90.4 547 Total 15-59 45.0 49.5 4.5 0.1 0.3 0.6 100.0 54.0 4,622 60 • Marriage and Sexual Activity Table 4.2.1 Number of women’s co-wives Percent distribution of currently married women age 15-49 by number of co-wives, and percentage of currently married women with one or more co-wives, according to background characteristics,

View the publication

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