Malawi - Demographic and Health Survey - 2017

Publication date: 2017

Malawi Demographic and Health Survey 2015-16Dem ographic and H ealth S urvey M alaw i 2015-16 Malawi Demographic and Health Survey 2015-16 National Statistical Office Zomba, Malawi The DHS Program ICF Rockville, Maryland, USA February 2017 THE WORLD BANK The 2015-16 Malawi Demographic and Health Survey (2015-16 MDHS) was implemented by the National Statistical Office from 19 October 2015 to 17 February 2016. The funding for the 2015-16 MDHS was provided by the government of Malawi, the United States Agency for International Development (USAID), the United Nations Children’s Fund (UNICEF), the Malawi National AIDS Commission (NAC), the United Nations Population Fund (UNFPA), UN WOMEN, Irish Aid, and the World Bank. ICF provided technical assistance through The DHS Program, a USAID-funded project providing support and technical assistance in the implementation of population and health surveys in countries worldwide. Additional information about the 2015-16 MDHS may be obtained from the Demography and Social Statistics Division, National Statistical Office, Chimbiya Road, P.O. Box 333, Zomba, Malawi; Telephone +265-1-524-377; E-mail: enquiries@statistics.gov.mw; Internet: www.nsomalawi.mw. Information about The DHS Program may be obtained from ICF, 530 Gaither Road, Suite 500, Rockville, MD 20850, USA; Telephone: +1-301-407-6500; Fax: +1-301-407-6501; E-mail: info@DHSprogram.com; Internet: www.DHSprogram.com. Cover art “Lake Scenery” ©2016 Steve Bakali. Used with permission. Recommended citation: National Statistical Office (NSO) [Malawi] and ICF. 2017. Malawi Demographic and Health Survey 2015-16. Zomba, Malawi, and Rockville, Maryland, USA. NSO and ICF. Contents • iii CONTENTS TABLES AND FIGURES . ix FOREWORD . xxi ACRONYMS AND ABBREVIATIONS . xxiii READING AND UNDERSTANDING THE 2015-16 MALAWI DEMOGRAPHIC AND HEALTH SURVEY (MDHS) . xxv MAP OF MALAWI . xxxii 1 INTRODUCTION AND SURVEY METHODOLOGY . 1 1.1 Survey Objectives . 1 1.2 Sample Design . 2 1.3 Questionnaires . 2 1.4 Anthropometry, Anaemia Testing, and HIV Testing . 3 1.5 Pretest . 6 1.6 Training of Field Staff . 6 1.7 Fieldwork . 6 1.8 Data Processing . 7 1.9 Response Rates . 7 2 HOUSING CHARACTERISTICS AND HOUSEHOLD POPULATION . 9 2.1 Drinking Water Sources and Treatment . 9 2.2 Sanitation . 10 2.3 Exposure to Smoke inside the Home and Other Housing Characteristics . 11 2.3.1 Exposure to Smoke Inside the Home . 11 2.3.2 Other Housing Characteristics . 11 2.4 Household Wealth and Durable Goods . 11 2.5 Hand Washing . 12 2.6 Household Population and Composition . 12 2.7 Birth Registration . 13 2.8 Children’s Living Arrangements and Parental Survival . 14 2.9 Education . 14 2.9.1 Educational Attainment . 14 2.9.2 School Attendance . 15 2.9.3 Other Measures of School Attendance . 16 2.10 Child Functioning and Disability. 17 3 CHARACTERISTICS OF RESPONDENTS . 31 3.1 Basic Characteristics of Survey Respondents . 31 3.2 Education and Literacy . 32 3.3 Mass Media Exposure and Internet Usage . 33 3.4 Employment . 34 3.5 Occupation . 34 3.6 Health Insurance Coverage . 35 3.7 Tobacco Use . 35 3.8 Knowledge and Attitudes regarding Tuberculosis . 36 4 MARRIAGE AND SEXUAL ACTIVITY . 55 4.1 Marital Status . 55 4.2 Polygyny . 56 iv • Contents 4.3 Age at First Marriage . 57 4.4 Age at First Sexual Intercourse . 57 4.5 Recent Sexual Activity . 58 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 . 71 5.5 Age at First Birth . 73 5.6 Teenage Childbearing and Sexual and Reproductive Behaviours before Age 15 . 73 5.6.1 Teenage Childbearing . 73 5.6.2 Sexual and Reproductive Behaviours before Age 15 . 74 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 . 95 7.3 Informed Choice . 96 7.4 Discontinuation of Contraceptives . 97 7.4.1 Knowledge of the Fertile Period . 97 7.5 Demand for Family Planning . 97 7.5.1 Decision-making about Family Planning . 99 7.5.2 Future Use of Contraception . 99 7.5.3 Exposure to Family Planning Messages in the Media . 99 7.6 Contact of Nonusers with Family Planning Providers . 99 8 INFANT AND CHILD MORTALITY . 111 8.1 Infant and Child Mortality . 112 8.2 Biodemographic Risk Factors . 113 8.3 Perinatal Mortality . 113 9 MATERNAL HEALTH CARE . 119 9.1 Antenatal Care Coverage and Content . 120 9.1.1 Skilled Providers . 120 9.1.2 Timing and Number of ANC Visits . 120 9.2 Components of ANC Visits . 121 9.3 Protection against Neonatal Tetanus . 121 9.4 Delivery Services . 122 9.4.1 Institutional Deliveries . 122 9.4.2 Skilled Assistance during Delivery . 123 9.4.3 Delivery by Caesarean . 123 9.5 Postnatal Care . 124 9.5.1 Postnatal Health Check for Mothers . 124 9.5.2 Postnatal Health Checks for Newborns . 125 9.6 Obstetric Fistula . 125 9.7 Problems in Accessing Health Care . 126 Contents • v 10 CHILD HEALTH . 141 10.1 Birth Weight . 141 10.2 Vaccination of Children . 142 10.2.1 Vaccination Coverage . 142 10.2.2 Uptake of the Newly Introduced Vaccines . 143 10.2.3 Vaccination Card Ownership and Availability . 144 10.3 Symptoms of Acute Respiratory Infection . 144 10.4 Fever . 144 10.5 Diarrhoeal Disease . 145 10.5.1 Prevalence of Diarrhoea and Treatment Seeking Behaviour . 145 10.5.2 Feeding Practices during Diarrhoea . 145 10.5.3 Oral Rehydration Therapy and other Treatments for Diarrhoea . 146 10.5.4 Knowledge of ORS Packets . 146 10.5.5 Treatment of Childhood Illness . 147 10.6 Disposal of Children’s Stools . 147 11 NUTRITION OF CHILDREN AND WOMEN . 159 11.1 Nutritional Status of Children . 159 11.1.1 Measurement of Nutritional Status among Young Children . 159 11.1.2 Data Collection . 161 11.1.3 Levels of Child Malnutrition . 161 11.2 Infant and Young Child Feeding Practices . 162 11.2.1 Breastfeeding . 162 11.2.2 Complementary Feeding . 163 11.2.3 Minimum Acceptable Diet . 164 11.3 Anaemia Prevalence in Children . 166 11.4 Presence of Iodised Salt in Households . 166 11.5 Micronutrient Intake and Supplementation among Children . 167 11.6 Women’s Nutritional Status . 167 11.7 Anaemia Prevalence in Women. 168 11.8 Micronutrient Intake among Mothers . 169 12 MALARIA . 183 12.1 Ownership of Insecticide-Treated Nets . 183 12.2 Indoor Residual Spraying . 185 12.3 Household Access and Use of ITNs . 186 12.4 Use of ITNs by Children and Pregnant Women . 187 12.5 Malaria in Pregnancy . 187 12.6 Case Management of Malaria in Children . 188 12.7 Prevalence of Low Haemoglobin in Children . 189 13 HIV/AIDS-RELATED KNOWLEDGE, ATTITUDES, AND BEHAVIOUR . 201 13.1 HIV/AIDS Knowledge, Transmission, and Prevention Methods . 202 13.2 Knowledge about Mother-to-Child Transmission . 203 13.3 Attitudes toward People Living with HIV . 204 13.4 Multiple Sexual Partners . 204 13.5 Paid Sex . 205 13.6 Coverage of HIV Testing Services . 206 13.6.1 Awareness of HIV Testing Services and Experience with HIV Testing . 206 13.6.2 HIV Testing of Pregnant Women . 207 13.7 Male Circumcision . 207 13.8 Self-reporting of Sexually Transmitted Infections . 208 13.9 HIV/AIDS-related Knowledge and Behaviour among Young People . 209 vi • Contents 13.9.1 Knowledge . 209 13.9.2 First Sex . 210 13.9.3 Premarital Sex . 211 13.9.4 Multiple Sexual Partners . 211 13.9.5 Coverage of HIV Testing Services . 212 14 HIV PREVALENCE . 229 14.1 Coverage Rates for HIV Testing . 229 14.2 HIV Prevalence . 230 14.2.1 HIV Prevalence by Age and Sex . 230 14.2.2 HIV Prevalence by Sexual Risk Behaviour . 232 14.2.3 HIV Prevalence among Young People . 232 14.2.4 HIV Prevalence by Other Characteristics Related to HIV Risk . 233 14.2.5 HIV Prevalence among Couples . 233 15 ADULT AND MATERNAL MORTALITY . 245 15.1 Data . 245 15.2 Direct Estimates of Adult Mortality . 246 15.3 Direct Estimates of Maternal Mortality . 247 15.4 Trends in Pregnancy-Related Mortality . 248 16 WOMEN’S EMPOWERMENT . 251 16.1 Married Women’s and Men’s Employment . 252 16.2 Control over Women’s Earnings . 252 16.3 Control over Men’s Earnings . 253 16.4 Women’s Control Over Their Own Earnings and over Those of Their Husbands . 254 16.5 Women’s and Men’s Ownership of Assets . 254 16.6 Ownership of Title or Deed for House and Land . 255 16.7 Ownership of Bank Accounts and Mobile Phones . 255 16.8 Participation in Decision Making . 256 16.9 Attitudes toward Wife Beating . 257 16.10 Attitudes toward Negotiating Safer Sexual Relations with Husband . 258 16.11 Ability to Negotiate Sexual Relations with Husband . 259 16.12 Women’s Empowerment Indicators . 260 16.13 Current Use of Contraception by Woman’s Empowerment Status . 260 16.14 Women’s Empowerment and Ideal Number of Children and Unmet Need for the Family . 260 16.15 Reproductive Health Care by Women’s Empowerment . 261 16.16 Early Childhood Mortality Rates by Women’s Status . 261 17 DOMESTIC VIOLENCE . 279 17.1 Measurement of Violence . 280 17.2 Women’s Experience of Physical Violence . 281 17.2.1 Perpetrators of Physical Violence . 282 17.3 Experience of Sexual Violence . 282 17.3.1 Prevalence of Sexual Violence . 282 17.3.2 Perpetrators of Sexual Violence . 283 17.4 Experience of Different Forms of Violence . 283 17.5 Marital Control by Husband . 283 17.6 Forms of Spousal Violence . 284 17.6.1 Prevalence of Spousal Violence . 284 17.7 Injuries to Women due to Spousal Violence . 287 17.8 Violence Initiated by Women against Husbands . 287 Contents • vii 17.9 Help-Seeking among Women Who Have Experienced Violence . 288 17.9.1 Sources for Help . 288 REFERENCES . 305 APPENDIX A DISTRICT TABLES . 307 APPENDIX B SAMPLE DESIGN . 441 B.1 Introduction . 441 B.2 Sample Frame . 441 B.3 Sample Design and Implementation . 442 B.4 Sample Probabilities and Sampling Weights . 442 APPENDIX C ESTIMATES OF SAMPLING ERRORS . 455 APPENDIX D DATA QUALITY TABLES . 493 APPENDIX E SURVEY PERSONNEL . 501 APPENDIX F QUESTIONNAIRES . 507 Tables and Figures • ix TABLES AND FIGURES 1 INTRODUCTION AND SURVEY METHODOLOGY . 1 Table 1.1 Results of the household and individual interviews . 7 Figure 1.1 HIV testing algorithm . 5 2 HOUSING CHARACTERISTICS AND HOUSEHOLD POPULATION . 9 Table 2.1 Household drinking water . 18 Table 2.2 Availability of water . 18 Table 2.3 Household sanitation facilities . 19 Table 2.4 Household characteristics . 20 Table 2.5 Wealth quintiles . 21 Table 2.6 Household possessions . 21 Table 2.7 Hand washing . 22 Table 2.8 Household population by age, sex, and residence . 22 Table 2.9 Household composition . 23 Table 2.10.1 Birth registration of children under age 5 . 24 Table 2.10.2 Place of birth registration of children under age 5 . 24 Table 2.11 Children’s living arrangements and orphanhood . 25 Table 2.12.1 Educational attainment of the female household population . 26 Table 2.12.2 Educational attainment of the male household population . 27 Table 2.13 School attendance ratios . 28 Table 2.14.1 Child functioning and disability: Children age 2-9 . 29 Table 2.14.2 Child functioning and disability: Children age 10-17 . 30 Figure 2.1 Household drinking water by residence . 10 Figure 2.2 Household toilet facilities by residence . 11 Figure 2.3 Household wealth by residence. 12 Figure 2.4 Population pyramid . 13 Figure 2.5 Secondary school attendance by household wealth . 15 Figure 2.6 Age-specific attendance rates . 16 3 CHARACTERISTICS OF RESPONDENTS . 31 Table 3.1 Background characteristics of respondents . 37 Table 3.2.1 Educational attainment: Women . 38 Table 3.2.2 Educational attainment: Men . 38 Table 3.3.1 Literacy: Women . 39 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 . 40 Table 3.5.1 Internet usage: Women . 41 Table 3.5.2 Internet usage: Men . 42 Table 3.6.1 Employment status: Women . 43 Table 3.6.2 Employment status: Men . 44 Table 3.7.1 Occupation: Women . 45 Table 3.7.2 Occupation: Men . 46 Table 3.8 Type of employment: Women . 47 Table 3.9.1 Health insurance coverage: Women . 48 x • Tables and Figures Table 3.9.2 Health insurance coverage: Men . 48 Table 3.10.1 Tobacco smoking: Women . 49 Table 3.10.2 Tobacco smoking: Men . 50 Table 3.11 Average number of cigarettes smoked daily: Men . 51 Table 3.12 Smokeless tobacco use . 51 Table 3.13.1 Knowledge and attitude concerning tuberculosis: Women . 52 Table 3.13.2 Knowledge and attitude concerning tuberculosis: Men . 53 Figure 3.1 Education of survey respondents . 32 Figure 3.2 Secondary education by household wealth . 32 Figure 3.3 Exposure to mass media . 33 Figure 3.4 Employment status by residence . 34 Figure 3.5 Occupation . 35 4 MARRIAGE AND SEXUAL ACTIVITY . 55 Table 4.1 Current marital status . 60 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 . 56 Figure 4.2 Polygyny by region . 56 Figure 4.3 Women’s median age at marriage by education . 57 Figure 4.4 Median age at first sex and first marriage . 58 5 FERTILITY . 69 Table 5.1 Current fertility . 76 Table 5.2 Fertility by background characteristics . 76 Table 5.3.1 Trends in age-specific fertility rates . 77 Table 5.3.2 Trends in age-specific and total fertility rates . 77 Table 5.4 Children ever born and living . 77 Table 5.5 Birth intervals . 78 Table 5.6 Postpartum amenorrhea, abstinence, and insusceptibility . 79 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 . 81 Figure 5.1 Trends in fertility by residence . 70 Figure 5.2 Trends in age-specific fertility . 70 Figure 5.3 Fertility by household wealth . 70 Figure 5.4 Birth intervals . 71 Figure 5.5 Median age at birth by education . 73 Figure 5.6 Teenage pregnancy and motherhood by region . 74 Figure 5.7 Teenage pregnancy and motherhood by household wealth . 74 Figure 5.8 Sexual and reproductive health behaviours before age 15 . 74 Tables and Figures • xi 6 FERTILITY PREFERENCES . 83 Table 6.1 Fertility preferences by number of living children . 88 Table 6.2.1 Desire to limit childbearing: Women . 89 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 according to background characteristics . 91 Table 6.5 Fertility planning status . 92 Table 6.6 Wanted fertility rates . 92 Figure 6.1 Trends in desire to limit childbearing by number of living children . 84 Figure 6.2 Ideal family size . 84 Figure 6.3 Ideal family size by number of living children . 85 Figure 6.4 Fertility planning status . 85 Figure 6.5 Trends in fertility planning status . 86 Figure 6.6 Trends in wanted and actual fertility . 86 7 FAMILY PLANNING . 93 Table 7.1 Knowledge of contraceptive methods . 101 Table 7.2 Current use of contraception according to age . 101 Table 7.3 Current use of contraception by background characteristics . 102 Table 7.4 Timing of sterilisation . 102 Table 7.5 Source of modern contraception methods . 103 Table 7.6 Use of social marketing brand pills and condoms . 103 Table 7.7 Informed choice . 104 Table 7.8 Twelve-month contraceptive discontinuation rates . 104 Table 7.9 Reasons for discontinuation . 105 Table 7.10 Knowledge of fertile period . 105 Table 7.11 Knowledge of fertile period by age . 105 Table 7.12.1 Need and demand for family planning among currently married women . 106 Table 7.12.2 Need and demand for family planning for all women and for women who are not currently married . 107 Table 7.13 Decision-making about family planning . 108 Table 7.14 Future use of contraception . 108 Table 7.15 Exposure to family planning messages . 109 Table 7.16 Contact of nonusers with family planning providers . 110 Figure 7.1 Contraceptive use . 94 Figure 7.2 Trends in contraceptive use . 94 Figure 7.3 Modern contraceptive use by region . 95 Figure 7.4 Use of modern methods by household wealth . 95 Figure 7.5 Source of modern contraceptive methods . 96 Figure 7.6 Contraceptive discontinuation rates . 97 Figure 7.7 Demand for family planning . 98 Figure 7.8 Trends in demand for family planning . 98 Figure 7.9 Unmet need by region . 98 Figure 7.10 Unmet need by wealth quintile . 99 8 INFANT AND CHILD MORTALITY . 111 Table 8.1 Early childhood mortality rates . 115 Table 8.2 Early childhood mortality rates according to socioeconomic characteristics . 115 Table 8.3 Early childhood mortality rates according to demographic characteristics . 116 Table 8.4 Perinatal mortality . 117 Table 8.5 High-risk fertility behaviour . 118 xii • Tables and Figures Figure 8.1 Trends in early childhood mortality rates . 112 Figure 8.2 Under-5 mortality by household wealth . 113 Figure 8.3 Childhood mortality by previous birth interval . 113 9 MATERNAL HEALTH CARE . 119 Table 9.1 Antenatal care . 127 Table 9.2 Number of antenatal care visits and timing of first visit . 127 Table 9.3 Components of antenatal care . 128 Table 9.4 Tetanus toxoid injections . 129 Table 9.5 Place of delivery . 130 Table 9.6 Assistance during delivery . 131 Table 9.7 Caesarean section . 132 Table 9.8 Duration of stay in health facility after birth . 132 Table 9.9 Timing of first postnatal check for the mother . 133 Table 9.10 Type of provider of first postnatal check for the mother . 134 Table 9.11 Timing of first postnatal check for the newborn . 135 Table 9.12 Type of provider of first postnatal check for the newborn . 136 Table 9.13 Content of postnatal care for newborns . 137 Table 9.14 Pregnancy outcomes . 138 Table 9.15 Prevalence of obstetric fistula . 139 Table 9.16 Problems in accessing health care . 140 Figure 9.1 Trends in antenatal care coverage . 120 Figure 9.2 Components of antenatal care . 121 Figure 9.3 Trends in place of birth . 122 Figure 9.4 Health facility births by education . 122 Figure 9.5 Assistance during delivery . 123 Figure 9.6 Skilled assistance at delivery by education . 123 Figure 9.7 Postnatal care by place of delivery . 124 10 CHILD HEALTH . 141 Table 10.1 Child’s size and weight at birth. 148 Table 10.2 Vaccinations by source of information . 149 Table 10.3 Vaccinations by background characteristics . 150 Table 10.4 Possession and observation of vaccination cards, according to background characteristics . 151 Table 10.5 Prevalence and treatment of symptoms of ARI . 152 Table 10.6 Prevalence and treatment of fever . 153 Table 10.7 Prevalence and treatment of diarrhoea . 154 Table 10.8 Feeding practices during diarrhoea . 155 Table 10.9 Oral rehydration therapy, zinc, and other treatments for diarrhoea . 156 Table 10.10 Knowledge of ORS packets . 157 Table 10.11 Disposal of children’s stools . 158 Figure 10.1 Childhood vaccinations . 142 Figure 10.2 Trends in childhood vaccinations . 143 Figure 10.3 Vaccination coverage by mother’s education . 144 Figure 10.4 Diarrhoea prevalence by age . 145 Figure 10.5 Feeding practices during diarrhoea . 145 Figure 10.6 Treatment of diarrhoea . 146 Figure 10.7 Prevalence and treatment of childhood illness . 147 Tables and Figures • xiii 11 NUTRITION OF CHILDREN AND WOMEN . 159 Table 11.1 Nutritional status of children . 170 Table 11.2 Initial breastfeeding . 171 Table 11.3 Breastfeeding status according to age . 172 Table 11.4 Median duration of breastfeeding . 173 Table 11.5 Foods and liquids consumed by children in the day or night before the interview . 174 Table 11.6 Minimum acceptable diet . 175 Table 11.7 Prevalence of anaemia in children . 176 Table 11.8 Presence of iodised salt in household . 177 Table 11.9 Micronutrient intake among children . 178 Table 11.10 Therapeutic and supplemental foods . 179 Table 11.11 Nutritional status of women . 180 Table 11.12 Prevalence of anaemia in women . 181 Table 11.13 Micronutrient intake among mothers . 182 Figure 11.1 Trends in nutritional status of children . 161 Figure 11.2 Stunting in children by household wealth . 161 Figure 11.3 Breastfeeding practices by age . 163 Figure 11.4 IYCF indicators on minimum acceptable diet (MAD). 165 Figure 11.5 Trends in childhood anaemia . 166 Figure 11.6 Nutritional status of women . 168 Figure 11.7 Trends in women’s nutritional status . 168 Figure 11.8 Trends in anaemia status among women . 169 12 MALARIA . 183 Table 12.1 Household possession of mosquito nets . 191 Table 12.2 Source of mosquito nets . 191 Table 12.3 Indoor residual spraying against mosquitoes . 192 Table 12.4 Access to an insecticide-treated net (ITN) . 192 Table 12.5 Access to an ITN . 193 Table 12.6 Use of mosquito nets by persons in the household . 193 Table 12.7 Use of existing ITNs . 194 Table 12.8 Use of mosquito nets by children . 194 Table 12.9 Use of mosquito nets by pregnant women . 195 Table 12.10 Use of Intermittent Preventive Treatment (IPTp) by women during pregnancy . 195 Table 12.11 Prevalence, diagnosis, and treatment of children with fever . 196 Table 12.12 Source of advice or treatment for children with fever . 197 Table 12.13 Type of antimalarial drugs used . 198 Table 12.14 Haemoglobin <8.0 g/dl in children . 199 Figure 12.1 Source of ITNs . 184 Figure 12.2 Household ownership of ITNs . 184 Figure 12.3 Trends in household ownership of ITNs . 185 Figure 12.4 ITN ownership by household wealth . 185 Figure 12.5 Access to and use of ITNs . 186 Figure 12.6 Trends in ITN access and use . 186 Figure 12.7 Trends in use of ITNs by children and pregnant women . 187 Figure 12.8 Trends in IPTp use by pregnant women . 188 Figure 12.9 Low haemoglobin in children by household wealth . 190 xiv • Tables and Figures 13 HIV/AIDS-RELATED KNOWLEDGE, ATTITUDES, AND BEHAVIOUR . 201 Table 13.1 Knowledge of HIV prevention methods . 213 Table 13.2 Comprehensive knowledge about HIV . 214 Table 13.3 Knowledge of prevention of mother-to-child transmission of HIV . 214 Table 13.4 Discriminatory attitudes towards people living with HIV . 215 Table 13.5.1 Multiple sexual partners and higher-risk sexual intercourse in the past 12 months: Women . 216 Table 13.5.2 Multiple sexual partners and higher-risk sexual intercourse in the past 12 months: Men . 217 Table 13.6 Payment for sexual intercourse and condom use at last paid sexual intercourse . 218 Table 13.7.1 Coverage of prior HIV testing: Women . 219 Table 13.7.2 Coverage of prior HIV testing: Men . 220 Table 13.8 Pregnant women counselled and tested for HIV . 221 Table 13.9 Male circumcision . 222 Table 13.10 Self-reported prevalence of sexually transmitted infections (STIs) and STIs symptoms . 223 Table 13.11 Comprehensive knowledge about HIV among young people . 224 Table 13.12 Age at first sexual intercourse among young people . 224 Table 13.13 Premarital sexual intercourse among young people . 225 Table 13.14.1 Multiple sexual partners and higher-risk sexual intercourse in the past 12 months among young people: Women . 226 Table 13.14.2 Multiple sexual partners and higher-risk sexual behaviour in the past 12 months among young people: Men . 227 Table 13.15 Recent HIV tests among young people . 228 Figure 13.1 Trends in knowledge of HIV prevention methods . 202 Figure 13.2 Knowledge of mother-to-child transmission (MTCT) of HIV . 203 Figure 13.3 Discriminatory attitudes towards people living with HIV by education . 204 Figure 13.4 Sex and condom use with non-regular partner . 205 Figure 13.5 Trends in recent HIV testing . 206 Figure 13.6 Recent HIV testing by region. 207 Figure 13.7 Recent HIV testing by education . 207 Figure 13.8 Male circumcision by age . 208 Figure 13.9 Women and men seeking treatment for STIs . 209 Figure 13.10 Trends in age at first sexual intercourse among young people . 210 Figure 13.11 Premarital sex by region . 211 14 HIV PREVALENCE . 229 Table 14.1 Coverage of HIV testing according to residence and region . 235 Table 14.2 Coverage of HIV testing according to selected background characteristics . 236 Table 14.3 HIV prevalence according to age . 237 Table 14.4 HIV prevalence according to socioeconomic characteristics . 238 Table 14.5 HIV prevalence according to sociodemographic characteristics . 239 Table 14.6 HIV prevalence according to sexual behaviour . 240 Table 14.9 HIV prevalence according to other characteristics . 242 Table 14.10 Prior HIV testing by current HIV status . 242 Table 14.11 HIV prevalence by male circumcision . 243 Table 14.12 HIV prevalence among couples . 244 Tables and Figures • xv Figure 14.1 HIV prevalence by age . 230 Figure 14.2 Trends in HIV prevalence . 231 Figure 14.3 HIV prevalence by residence and sex . 231 Figure 14.4 HIV prevalence by region . 232 Figure 14.5 HIV prevalence by number of lifetime partners . 232 Figure 14.6 HIV prevalence in couples . 233 15 ADULT AND MATERNAL MORTALITY . 245 Table 15.1 Completeness of information on siblings . 249 Table 15.2 Adult mortality rates . 249 Table 15.3 Adult mortality probabilities . 249 Table 15.4 Maternal mortality . 250 Figure 15.1 Adult mortality rates by age . 246 Figure 15.2 Trends in pregnancy-related mortality ratio (PRMR) with confidence intervals . 248 16 WOMEN’S EMPOWERMENT . 251 Table 16.1 Employment and cash earnings of currently married women and men . 262 Table 16.2.1 Control over women’s cash earnings and relative magnitude of women’s cash earnings . 263 Table 16.2.2 Control over men’s cash earnings . 264 Table 16.3 Women’s control over their own earnings and over those of their husbands . 264 Table 16.4.1 Ownership of assets: Women . 265 Table 16.4.2 Ownership of assets: Men . 265 Table 16.5.1 Ownership of title or deed for house: Women . 266 Table 16.5.2 Ownership of title or deed for house: Men . 267 Table 16.6.1 Ownership of title or deed for land: Women . 268 Table 16.6.2 Ownership of title or deed for land: Men . 268 Table 16.7.1 Ownership and use of bank accounts and mobile phones: Women . 269 Table 16.7.2 Ownership and use of bank accounts and mobile phones: Men . 269 Table 16.8 Participation in decision making . 270 Table 16.9.1 Women’s participation in decision making by background characteristics . 270 Table 16.9.2 Men’s participation in decision making by background characteristics . 271 Table 16.10.1 Attitude toward wife beating: Women . 272 Table 16.10.2 Attitude toward wife beating: Men . 273 Table 16.11 Attitudes toward negotiating safer sexual relations with husband . 274 Table 16.12 Ability to negotiate sexual relations with husband . 275 Table 16.13 Indicators of women’s empowerment . 275 Table 16.14 Current use of contraception by women’s empowerment . 276 Table 16.15 Ideal number of children and unmet need for family planning by women’s empowerment . 276 Table 16.16 Reproductive health care by women’s empowerment . 277 Table 16.17 Early childhood mortality rates by indicators of women’s empowerment . 277 Figure 16.1 Employment by age . 252 Figure 16.2 Control over woman’s earnings . 253 Figure 16.3 Ownership of assets . 254 Figure 16.4 Women’s participation in decision making. 256 Figure 16.5 Men’s participation in decision making . 257 Figure 16.6 Attitudes towards wife beating . 258 xvi • Tables and Figures 17 DOMESTIC VIOLENCE . 279 Table 17.1 Experience of physical violence . 290 Table 17.2 Experience of violence during pregnancy . 291 Table 17.3 Persons committing physical violence . 292 Table 17.4 Experience of sexual violence. 293 Table 17.5 Age at first experience of sexual violence . 294 Table 17.6 Persons committing sexual violence . 294 Table 17.7 Experience of different forms of violence . 294 Table 17.8 Marital control exercised by husbands . 295 Table 17.9 Forms of spousal violence . 296 Table 17.10 Spousal violence according to background characteristics . 297 Table 17.11 Spousal violence according to husband’s characteristics and empowerment indicators . 298 Table 17.12 Physical or sexual violence in the past 12 months by any husband/partner . 299 Table 17.13 Experience of spousal violence by duration of marriage . 300 Table 17.14 Injuries to women due to spousal violence . 300 Table 17.15 Violence by women against their husband according to women’s background characteristics . 301 Table 17.16 Violence by women against their husband according to husband’s characteristics and empowerment indicators . 302 Table 17.17 Help seeking to stop violence . 303 Table 17.18 Sources for help to stop the violence . 304 Figure 17.1 Violence during pregnancy by residence . 281 Figure 17.2 Woman’s experience of violence by marital status . 281 Figure 17.3 Types of spousal violence . 285 Figure 17.4 Spousal violence by region . 285 Figure 17.5 Spousal violence by husband’s alcohol consumption . 286 Figure 17.6 Help seeking by type of violence experienced . 288 APPENDIX A DISTRICT TABLES . 307 Table A-2.1 Household drinking water: Districts . 307 Table A-2.3 Household sanitation facilities: Districts . 308 Table A-2.4 Household access to electricity: Districts . 309 Table A-2.7 Hand washing: Districts . 310 Table A-2.10.1 Birth registration of children under age five: Districts . 311 Table A-2.11 Children’s living arrangements and orphanhood: Districts . 312 Table A-2.12.1 Educational attainment of the female household population: Districts . 313 Table A-2.12.2 Educational attainment of the male household population: Districts . 314 Table A-3.1 Distribution of survey respondents: Districts . 315 Table A-3.2.1 Educational attainment: Women by districts . 316 Table A-3.2.2 Educational attainment: Men by districts . 317 Table A-3.3.1 Literacy: Women by districts . 318 Table A-3.3.2 Literacy: Men by districts . 319 Table A-3.4.1 Exposure to mass media: Women by districts . 320 Table A-3.4.2 Exposure to mass media: Men by districts . 321 Table A-3.5.1 Internet usage: Women by districts . 322 Table A-3.5.2 Internet usage: Men by districts . 323 Table A-3.6.1 Employment status: Women by districts . 324 Table A-3.6.2 Employment status: Men by districts . 325 Table A-3.7.1 Occupation: Women by districts . 326 Table A-3.7.2 Occupation: Men by districts . 327 Tables and Figures • xvii Table A-3.8.1 Type of earnings: Women by districts . 328 Table A-3.8.2 Type of employer: Women by districts . 329 Table A-3.8.3 Continuity of employment: Women by districts . 330 Table A-3.10.2 Tobacco smoking: Men by districts . 331 Table A-3.13.1 Knowledge and attitude concerning tuberculosis: Women by districts . 332 Table A-3.13.2 Knowledge and attitude concerning tuberculosis: Men by districts. 333 Table A-4.2.1 Number of women’s co-wives: Districts . 334 Table A-4.2.2 Number of men’s wives: Districts . 335 Table A-4.4 Median age at first marriage: Districts . 336 Table A-4.6 Median age at first sexual intercourse: Districts . 337 Table A-4.7.1 Recent sexual activity: Women by district. 338 Table A-4.7.2 Recent sexual activity: Men by district . 339 Table A-5.2 Fertility: district . 340 Table A-5.5 Birth intervals: Districts . 341 Table A-5.10 Median age at first birth: Districts . 342 Table A-5.11 Teenage pregnancy and motherhood: Districts . 343 Table A-6.4 Mean ideal number of children: Districts . 344 Table A-6.6 Wanted fertility rates: Districts . 345 Table A-7.3 Current use of contraception: Districts . 346 Table A-7.12.1 Need and demand for family planning among currently married women: Districts . 347 Table A-7.13 Decision-making about family planning: Districts . 348 Table A-7.15 Exposure to family planning messages: Districts . 349 Table A-7.16 Contact of nonusers with family planning providers: Districts . 350 Table A-8.2 Early childhood mortality rates: Districts . 351 Table A-9.1 Antenatal care: Districts . 352 Table A-9.3 Components of antenatal care: Districts . 353 Table A-9.4 Tetanus toxoid injections: Districts . 354 Table A-9.5 Place of delivery: Districts . 355 Table A-9.6 Assistance during delivery: Districts . 356 Table A-9.7 Caesarean section: Districts . 357 Table A-9.9 Timing of first postnatal check for the mother: Districts . 358 Table A-9.10 Type of provider of first postnatal check for the mother: Districts . 359 Table A-9.11 Timing of first postnatal check for the newborn: Districts . 360 Table A-9.12 Type of provider of first postnatal check for the newborn: Districts . 361 Table A-9.13 Content of postnatal care for newborns: Districts . 362 Table A-9.14 Pregnancy outcomes: Districts . 363 Table A-9.15 Prevalence of obstetric fistula: Districts . 364 Table A-9.16 Problems in accessing health care: Districts . 365 Table A-10.1 Child’s size and weight at birth: Districts . 366 Table A-10.3 Vaccinations: Districts . 367 Table A-10.4 Possession and observation of vaccination cards: Districts . 368 Table A-10.5 Prevalence of ARI: Districts . 369 Table A-10.6 Prevalence and treatment of fever: Districts . 370 Table A-10.7 Prevalence and treatment of diarrhoea: Districts . 371 Table A-10.8 Feeding practices during diarrhoea: Districts . 372 Table A-10.9 Oral rehydration therapy, zinc and other treatments for diarrhoea: Districts . 373 Table A-10.10 Knowledge of ORS packets: Districts . 374 Table A-10.11 Disposal of children’s stools: Districts . 375 Table A-11.1 Nutritional status of children: Districts . 376 Table A-11.2 Initial breastfeeding: Districts . 378 Table A-11.6 Minimum acceptable diet: Districts . 379 xviii • Tables and Figures Table A-11.7 Prevalence of anaemia in children: Districts . 380 Table A-11.8 Presence of iodized salt in household: Districts . 381 Table A-11.9 Micronutrient intake among children: Districts . 382 Table A-11.10 Therapeutic and supplemental foods: Districts . 383 Table A-11.11 Nutritional status of women: Districts: Districts . 384 Table A-11.12 Prevalence of anaemia in women: Districts . 385 Table A-11.13 Micronutrient intake among mothers: Districts . 386 Table A-12.1 Household possession of mosquito nets: Districts . 387 Table A-12.2 Source of mosquito nets: Districts . 388 Table A-12.3 Indoor residual spraying against mosquitoes: Districts . 389 Table A-12.6 Use of mosquito nets by persons in the household: Districts . 390 Table A-12.7 Use of existing ITNs: Districts. 391 Table A-12.8 Use of mosquito nets by children: Districts . 392 Table A-12.9 Use of mosquito nets by pregnant women: Districts . 393 Table A-12.10 Use of Intermittent Preventive Treatment (IPTp) by women during pregnancy: Districts . 394 Table A-12.11 Prevalence, diagnosis, and prompt treatment of children with fever: Districts . 395 Table A-12.14 Haemoglobin <8.0 g/dl in children: Districts . 396 Table A-13.1 Knowledge of HIV prevention methods: Districts . 397 Table A-13.4 Discriminatory attitudes towards people living with HIV: Districts . 398 Table A-13.5.1 Multiple sexual partners and higher-risk sexual intercourse in the past 12 months: Women - Districts . 399 Table A-13.5.2 Multiple sexual partners and higher-risk sexual intercourse in the past 12 months: Men - Districts . 400 Table A-13.6 Payment for sexual intercourse and condom use at last paid sexual intercourse: Districts . 401 Table A-13.7.1 Coverage of prior HIV testing: Women - Districts . 402 Table A-13.7.2 Coverage of prior HIV testing: Men - Districts . 403 Table A-13.8 Pregnant women counselled and tested for HIV: Districts . 404 Table A-13.9 Male circumcision: Districts . 405 Table A-13.10 Self-reported prevalence of sexually-transmitted infections (STIs) and STIs symptoms: Districts . 406 Table A-13.11 Comprehensive knowledge about HIV among young people: Districts . 407 Table A-13.12 Age at first sexual intercourse among young people: Districts . 408 Table A-13.13 Premarital sexual intercourse among young people: Districts . 409 Table A-13.14.1 Multiple sexual partners in the past 12 months among young people: Women - Districts . 410 Table A-13.14.2 Multiple sexual partners in the past 12 months among young people: Men - Districts . 411 Table A-14.1 Coverage of HIV testing: Districts . 412 Table A-14.3 HIV prevalence: Districts . 414 Table A-16.2.1 Control over women’s cash earnings and relative magnitude of women’s cash earnings: Districts . 416 Table A-16.2.2 Control over men’s cash earnings: Districts . 417 Table A-16.4.1 Ownership of assets: Women by district . 418 Table A-16.4.2 Ownership of assets; Men by district . 419 Table A-16.5.1 Ownership of title or deed for house: Women by district . 420 Table A-16.5.2 Ownership of title or deed for house: Men by district . 421 Table A-16.6.1 Ownership of title or deed for land: Women by district . 422 Table A-16.6.2 Ownership of title or deed for land: Men by districts . 423 Table A-16.7.1 Ownership and use of bank accounts and mobile phones: Women by district . 424 Table A-16.7.2 Ownership and use of bank accounts and mobile phones: Men . 425 Tables and Figures • xix Table A-16.9.1 Women’s participation in decision making: Districts . 426 Table A-16.9.2 Men’s participation in decision making: Districts . 427 Table A-16.10.1 Attitude toward wife beating: Women by district . 428 Table A-16.10.2 Attitude toward wife beating: Men by district . 429 Table A-16.11 Attitudes toward negotiating safer sexual relations with husband: Districts . 430 Table A-16.12 Ability to negotiate sexual relations with husband: Districts . 431 Table A-17.1 Experience of physical violence: Districts . 432 Table A-17.2 Experience of violence during pregnancy: Districts . 433 Table A-17.4 Experience of sexual violence: Districts . 434 Table A-17.8 Marital control exercised by husbands: Districts . 435 Table A-17.10 Spousal violence: Districts . 436 Table A-17.12 Physical or sexual violence in the past 12 months by any husband/partner: Districts . 437 Table A-17.15 Violence by women against their husband: Districts . 438 Table A-17.17 Help seeking to stop violence: Districts . 439 APPENDIX B SAMPLE DESIGN . 441 Table B.1 Distribution of residential households . 445 Table B.2 Enumeration areas and households . 446 Table B.3 Sample allocation of clusters and households . 446 Table B.4 Sample allocation of completed interviews with women and men . 447 Table B.5 Sample implementation: Women . 448 Table B.6 Sample implementation: Men . 449 Table B.7 Coverage of HIV testing by social and demographic characteristics: Women . 450 Table B.8 Coverage of HIV testing by social and demographic characteristics: Men . 451 Table B.9 Coverage of HIV testing by sexual behaviour characteristics: Women . 452 Table B.10 Coverage of HIV testing by sexual behaviour characteristics: Men . 453 APPENDIX C ESTIMATES OF SAMPLING ERRORS . 455 Table C.1 List of indicators for sampling errors, Malawi DHS 2015-16 . 457 Table C.2 Sampling errors: Total sample, Malawi DHS 2015-16 . 458 Table C.3 Sampling errors: Urban sample, Malawi DHS 2015-16 . 459 Table C.4 Sampling errors: Rural sample, Malawi DHS 2015-16 . 460 Table C.5 Sampling errors: Northern region sample, Malawi DHS 2015-16 . 461 Table C.6 Sampling errors: Central region sample, Malawi DHS 2015-16 . 462 Table C.7 Sampling errors: Southern region sample, Malawi DHS 2015-16 . 463 Table C.8 Sampling errors: Chitipa sample, Malawi DHS 2015-16 . 464 Table C.9 Sampling errors: Karonga sample, Malawi DHS 2015-16 . 465 Table C.10 Sampling errors: Nkhatabay sample, Malawi DHS 2015-16 . 466 Table C.11 Sampling errors: Rumphi sample, Malawi DHS 2015-16 . 467 Table C.12 Sampling errors: Mzimba sample, Malawi DHS 2015-16 . 468 Table C.13 Sampling errors: Likoma sample, Malawi DHS 2015-16 . 469 Table C.14 Sampling errors: Kasungu sample, Malawi DHS 2015-16 . 470 Table C.15 Sampling errors: Nkhota kota sample, Malawi DHS 2015-16 . 471 Table C.16 Sampling errors: Ntchisi sample, Malawi DHS 2015-16 . 472 Table C.17 Sampling errors: Dowa sample, Malawi DHS 2015-16 . 473 Table C.18 Sampling errors: Salima sample, Malawi DHS 2015-16 . 474 Table C.19 Sampling errors: Lilongwe sample, Malawi DHS 2015-16 . 475 Table C.20 Sampling errors: Mchinji sample, Malawi DHS 2015-16 . 476 Table C.21 Sampling errors: Dedza sample, Malawi DHS 2015-16 . 477 Table C.22 Sampling errors: Ntcheu sample, Malawi DHS 2015-16 . 478 Table C.23 Sampling errors: Mangochi sample, Malawi DHS 2015-16 . 479 Table C.24 Sampling errors: Machinga sample, Malawi DHS 2015-16 . 480 xx • Tables and Figures Table C.25 Sampling errors: Zomba sample, Malawi DHS 2015-16 . 481 Table C.26 Sampling errors: Chiradzulu sample, Malawi DHS 2015-16 . 482 Table C.27 Sampling errors: Blantyre sample, Malawi DHS 2015-16 . 483 Table C.28 Sampling errors: Mwanza sample, Malawi DHS 2015-16 . 484 Table C.29 Sampling errors: Thyolo sample, Malawi DHS 2015-16 . 485 Table C.30 Sampling errors: Mulanje sample, Malawi DHS 2015-16 . 486 Table C.31 Sampling errors: Phalombe sample, Malawi DHS 2015-16 . 487 Table C.32 Sampling errors: Chikwawa sample, Malawi DHS 2015-16 . 488 Table C.33 Sampling errors: Nsanje sample, Malawi DHS 2015-16 . 489 Table C.34 Sampling errors: Balaka sample, Malawi DHS 2015-16 . 490 Table C.35 Sampling errors: Neno sample, Malawi DHS 2015-16. 491 Table C.36 Sampling errors for adult and maternal mortality rates, Malawi DHS 2015-16 . 492 APPENDIX D DATA QUALITY TABLES . 493 Table D.1 Household age distribution . 493 Table D.2.1 Age distribution of eligible and interviewed women . 494 Table D.2.2 Age distribution of eligible and interviewed men . 494 Table D.3 Completeness of reporting . 495 Table D.4 Births by calendar years . 495 Table D.5 Reporting of age at death in days . 496 Table D.6 Reporting of age at death in months . 497 Table D.7 Nutritional status of children based on the NCHS/CDC/WHO International Reference Population . 498 Table D.8 Sibship size and sex ratio of siblings . 499 Table D.9 Pregnancy-related mortality . 499 Table D.10 Pregnancy-related mortality . 499 Foreword • xxi FOREWORD he 2016-16 Malawi Demographic and Health Survey (2015-16 MDHS) was conducted between October 2015 and February 2016 by the National Statistical Office (NSO) of Malawi in joint collaboration with the Ministry of Health (MoH) and the Community Health Services Unit (CHSU). Malawi conducted its first DHS in 1992 and again in 2000, 2004, and 2010. The 2015-16 MDHS is the fifth in the series. The survey is based on a nationally representative sample that provides estimates at the national and regional levels and for urban and rural areas with key indicator estimates at the district level. The survey included 26,361 households, 24,562 female respondents, and 7,478 male respondents. The 2015-16 MDHS includes household and respondent characteristics, fertility and family planning, infant and child health and mortality, maternal health and maternal and adult mortality, child and adult nutrition, malaria, HIV/AIDS, domestic violence, orphans, and vulnerable children. As in the 2004 and 2010 MDHS, the 2015-16 MDHS included HIV testing that provides data on HIV prevalence in the country. The 2015-16 MDHS was conducted jointly with the Micronutrient Survey (MNS), which was implemented by the NSO in partnership with the Department of Nutrition, HIV, and AIDS (DNHA). The MDHS provides data that are needed to monitor and evaluate population, health, and nutrition programmes on a regular basis. The increasing emphasis by planners and policy makers on the utilisation of objective indicators for policy formulation, planning, and measurement of progress has increased reliance on regular household survey data. This was necessary because of the inadequate availability of appropriate, reliable information from administrative statistics and other routine data-collection systems. The MDHS is a crucial response to this paradigm shift. The 2015-16 MDHS provides an update on the status of health, maternal and child health, and family planning issues in Malawi. Most importantly, the 2015-16 MDHS provides baseline and critical information needed for monitoring Sustainable Development Goals (SDGs), the Malawi Growth and Development Strategy II (MGDS II), and other national and international development programmes. We would like to thank the Malawi Government, the U.S. Agency for International Development (USAID), National AIDs Commission (NAC), the United Nations Children’s Fund (UNICEF), the United Nations Population Fund (UNFPA), and UN Women, who funded the 2015-16 MDHS. ICF International provided technical assistance through the DHS Program, a USAID-funded project that provides support and technical assistance for the implementation of population and health surveys in countries across the world. The NSO also gratefully acknowledges the World Bank and Irish Aid, who funded the Micronutrient Survey. We would also like to thank staff members from the NSO, MoH, CHSU, and the University of Malawi, Chancellor College for efficiently coordinating the survey. Special mention is given to the Steering Committee and the Technical Working Group, which were chaired by the Department of Economic Planning and Development (DEPD). These groups were instrumental in guiding the resource mobilisation process, implementation, and technical aspects of the survey. We are very grateful to our field staff, who worked tirelessly and diligently to collect the data needed for this report. Finally, we extend our appreciation to the respondents, who generously provided data, without which it would have been impossible to produce this report. Mercy Kanyuka Commissioner of Statistics T Acronyms and Abbreviations • xxiii ACRONYMS AND ABBREVIATIONS ACT artemisinin-based combination therapy AIDS acquired immunodeficiency syndrome ANC antenatal care ARI acute respiratory infection ART antiretroviral therapy ASAQ artesunate-amodiaquine ASAR age-specific attendance rate BBSS Biological Behavioural Surveillance Survey BCG Bacille Calmette-Guérin BLM Banja la Mtsogolo BMI body mass index CAPI computer-assisted personal interviewing CBR crude birth rate CCAP Church of Central Africa Presbyterian CDC Centers for Diseases Control and Prevention CHAM Christian Health Association of Malawi CHSU Community Health Sciences Unit CPR contraceptive prevalence rate CSPro Census and Survey Processing System DBS dried blood spots DEFT design effect DHS Demographic and Health Surveys DPT Diphtheria-pertussis-tetanus EA enumeration area ELISA enzyme-linked immunosorbent assay EPI Expanded Programme on Immunisation GAR gross attendance ratio GFR general fertility rate GPI gender parity index HepB Hepatitis B Hib Haemophilus influenzae type B HIV human immunodeficiency virus HSSP health sector strategic plan HTC HIV testing and counselling HTS HIV testing services IFSS Internet file streaming system IPTp Intermittent preventive treatment during pregnancy IRS indoor residual spraying ITN insecticide-treated net IUD intrauterine devices IYCF infant and young child feeding xxiv • Acronyms and Abbreviations LA lumefantrine-artemether LAM lactational amenorrhoea method LLIN long-lasting insecticidal net LPG liquid petroleum gas MAD minimum acceptable diet MDHS Malawi Demographic and Health Surveys MICS Multiple Indicator Cluster Surveys PPHC Malawi population and housing census MMR maternal mortality ratio MTCT mother-to-child transmission NAC National Aids Commission NAR net attendance ratio NMCP National Malaria Control Programme NSO National Statistical Office NSP National HIV and AIDS Strategic Plan ORS oral rehydration salts ORT oral rehydration therapy PCV pneumococcal conjugate vaccine PHIA Population-based HIV Impact Assessment PMTCT prevention of mother-to-child transmission PRMR pregnancy-related mortality ratio PSU primary sampling unit RHF recommended home fluids RUFT ready-to-use therapeutic food RV rotavirus vaccine SD standard deviation SDM standard days method SE standard error SEA standard enumeration area SP Sulfadoxine/pyrimethamin STD sexually-transmitted disease STI sexually transmitted infection TB tuberculosis TFR total fertility rate UNAIDS United Nations Programme on HIV and AIDS 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 VMMC voluntary medical male circumcision WHO World Health Organization Reading and Understanding the 2015-16 MDHS • xxv READING AND UNDERSTANDING THE 2015-16 MALAWI DEMOGRAPHIC AND HEALTH SURVEY (MDHS) he 2015-16 Malawi Demographic and Health Survey (MDHS) report is very similar in content to the 2010 MDHS but is presented in a new format. The new style features more figures to highlight trends, subnational patterns, and background characteristics. The text has been simplified to highlight key points in bullets and to clearly identify indicator definitions in boxes. The tables in this report are located at the end of each chapter instead of being imbedded in the chapter text. 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, data users should be comfortable reading and interpreting tables. The following pages provide an introduction to the organization of MDHS tables, the presentation of background characteristics, and a brief summary of sampling and understanding denominators. In addition, this section provides some exercises for users as they practice their new skills in interpreting MDHS tables. T xxvi • Reading and Understanding the 2015-16 MDHS Example 1: 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, according to background characteristics, Malawi DHS 2015-16 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 9.8 11.5 26.4 2.1 64.7 5,263 20-24 8.9 11.5 31.2 2.2 61.1 5,159 25-29 9.5 14.2 33.0 2.4 57.8 3,953 30-34 7.7 11.1 32.7 2.4 61.5 3,668 35-39 7.0 10.6 29.1 2.4 65.0 2,924 40-44 6.1 9.8 28.5 1.8 66.6 2,029 45-49 4.5 9.5 28.0 1.8 68.7 1,567 Residence Urban 17.1 39.2 42.3 7.2 37.6 4,496 Rural 6.3 5.3 27.2 1.1 68.5 20,066 Region Northern 10.0 16.5 33.2 3.5 58.1 2,838 Central 8.5 10.4 31.7 1.8 60.2 10,529 Southern 7.6 11.3 27.6 2.2 66.4 11,194 Education No education 0.3 2.4 17.4 0.0 81.1 2,977 Primary 5.5 5.5 27.1 0.6 68.1 15,245 Secondary 15.3 26.0 42.2 5.5 44.7 5,598 More than secondary 43.2 61.9 48.0 19.5 17.3 742 Wealth quintile Lowest 3.4 1.0 12.5 0.1 85.0 4,745 Second 4.2 1.7 22.8 0.1 74.1 4,692 Middle 6.0 2.7 26.9 0.4 69.0 4,635 Fourth 7.1 4.4 34.4 0.7 60.5 4,680 Highest 18.2 40.7 49.0 8.2 32.6 5,810 Total 8.3 11.5 30.0 2.2 62.8 24,562 1 3 2 4 5 Reading and Understanding the 2015-16 MDHS • xxvii 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 age 15-49 and their exposure to different types of media. All eligible female respondents age 15-49 were asked these questions. Step 2: Scan the column headings—highlighted in green in Example 1.They describe how the information is 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 media, while the fifth column is women who do not access any of the three types of 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 highlighted in blue in Example 1. These show the different ways the data are divided into categories based on population characteristics. In this case, the table presents women’s exposure to media by age, urban-rural residence, region, educational level, and wealth quintile. Most of the tables in the MDHS report will be divided into these same categories. Step 4: Look at the row at the bottom of the table highlighted in red. These percentages represent the totals of all women age 15-49 and their access to different types of media. In this case, 8.3%* of women age 15- 49 read a newspaper at least once a week, 11.5% watch television weekly, and 30.0% 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 19.5% of women age 15-49 with more than secondary education access all three types of media weekly. Step 6: By looking at patterns by background characteristics, we can see how exposure to mass media varies across Malawi. Mass media are often used to communicate health messages. Knowing how mass media exposure varies among different groups can help programme planners and policy makers determine how to most effectively reach their target populations. *For the purpose of this document data are presented exactly as they appear in the table including decimal places. However, the text in the remainder of this report rounds data to the nearest whole percentage point. Practice: Use the table in Example 1 to answer the following questions: a) What percentage of women in Malawi do not access any of the three media at least once a week? b) What age group of women are most likely to watch television weekly? c) Compare women in urban areas to women in rural areas—which group is more likely to read the newspaper weekly? d) What are the lowest and highest percentages (range) of women who do not access any of the three media at least once a week by region? 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) 62.8% b) Women age 25-29: 14.2% of women in this age group watch television weekly c) Women in urban areas, 17.1% read a newspaper weekly, compared to 6.3% of women in rural areas d) 58.1% of women in the Northern region do not access any of the three media at least once a week, compared to 66.4% of women in the Southern region. e) Exposure to television on a weekly basis increases as a woman’s level of education increases; 2.4% of women with no education watch television weekly, compared to 61.9% of women with more than secondary education. f) Exposure to radio on a weekly basis increases as household wealth increases; 12.5% of women in the lowest wealth quintile listen to the radio on a weekly basis, compared to 49.0% of women in the highest wealth. xxviii • Reading and Understanding the 2015-16 MDHS 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, Malawi DHS 2015-16 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 4.6 1,674 70.2 40.7 77 6-11 6.5 1,692 79.8 48.5 110 12-23 6.2 3,230 81.4 56.7 201 24-35 6.1 3,261 78.0 53.7 197 36-47 4.7 3,391 72.0 43.1 158 48-59 4.5 3,300 79.8 54.7 150 Sex Male 5.7 8,242 76.5 50.5 467 Female 5.1 8,307 78.7 51.3 426 Mother’s smoking status Smokes cigarettes/tobacco 4.5 88 * * 4 Does not smoke 5.4 16,461 77.5 50.9 890 Cooking fuel Electricity or gas 0.7 249 * * 2 Coal/lignite * 7 * * 0 Charcoal 4.9 2,427 78.1 55.7 119 Wood/straw3 5.6 13,865 77.6 50.2 773 Residence Urban 3.6 2,212 83.5 55.2 80 Rural 5.7 14,336 77.0 50.5 814 Region Northern 5.8 1,900 77.9 52.0 109 Central 5.9 7,003 79.2 53.4 414 Southern 4.8 7,645 75.6 47.8 370 Mother’s education No education 4.6 2,224 76.2 39.8 102 Primary 5.7 10,962 78.1 51.7 625 Secondary 5.3 3,070 76.5 55.0 163 More than secondary 1.2 293 * * 3 Wealth quintile Lowest 5.9 4,074 77.8 50.3 240 Second 4.9 3,707 76.7 47.3 183 Middle 6.2 3,203 77.1 53.8 197 Fourth 5.8 2,901 79.1 47.9 167 Highest 4.0 2,663 76.8 57.6 107 Total 5.4 16,548 77.6 50.9 894 Note: 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 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 five (a) and children under age five who had symptoms of acute respiratory infection (ARI) in the two weeks before the survey (b). Step 2: Identify the two panels. First, identify the columns that refer to all children under age five (a), and then isolate the columns that refer only to those children under age five 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 five had symptoms of ARI in the two weeks before the survey? It’s 5.4%. Now look at the second panel. How many children under age five 1 a b 2 3 3 4 Reading and Understanding the 2015-16 MDHS • xxix are there who had symptoms of ARI in the two weeks before the survey? It’s 894 children or 5.4% of the 16,548 children under age five (with rounding). The second panel is a subset of the first panel. Step 4: Only 5.4% of children under age five had symptoms of ARI in the two weeks before the survey. Once these children are further divided into the background characteristic categories, there may be too few cases for the percentages to be reliable.  What percentage of children under age five whose mothers have more than secondary education who had symptoms of ARI in the two weeks before the survey sought advice or treatment? There is no number in this cell—only an asterisk. This is because fewer than 25 children under age five whose mothers have more than secondary education had symptoms of ARI in the two weeks before the survey and sought treatment or advice. Results for this group are not reported. The subgroup is too small, and therefore the data are not reliable.  Although not shown in the table above, you may find tables with percentages in parentheses. The percentage is in parentheses because there are between 25 and 49 cases (unweighted) in the category. Readers should use this number with caution—it may not be reliable. (For more information on weighted and unweighted numbers, see Example 3.) Note: When parentheses or asterisks are used in a table, the explanation will be noted under the table. If there are no parentheses or asterisks in a table, you can proceed with confidence that enough cases were included in all categories that the data are reliable. xxx • Reading and Understanding the 2015-16 MDHS Example 3: Understanding Sampling Weights in MDHS Tables A sample is a group of people who have been selected for a survey. In the MDHS, 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 regional areas. However, doing so requires a minimum sample size per area. For the 2015-16 MDHS, the survey sample is representative at the national and regional levels, for urban and rural areas, and for some, but not all indicators, estimates at the district level. To generate statistics that are representative of the country as a whole and the three regions, the number of women surveyed in each region should contribute to the size of the total (national) sample in proportion to size of the region. However, if some regions have small populations, then a sample allocated in proportion to each region’s population may not include sufficient women from each region for analysis. To solve this problem, regions with small populations are oversampled. For example, let’s say that you have enough money to interview 24,562 women and want to produce results that are representative of Malawi as a whole and its regions (as in Table 3.1). However, the total population of Malawi is not evenly distributed among the regions: some regions, such as Southern, are heavily populated while others, such as Northern are not. Thus, Northern must be oversampled. A sampling statistician determines how many women should be interviewed in each region in order to get reliable statistics. The blue column (1) in the table at the right shows the actual number of women interviewed in each region. Within the regions, the number of women interviewed ranges from 4,803 in Northern to 11,342 in Southern. The number of interviews is sufficient to get reliable results in each region. With this distribution of interviews, some regions are overrepresented and some regions are underrepresented. For example, the population in Southern is about 46% of the population in Malawi, while Northern’s population contributes only 12% of the population in Malawi. But as the blue column shows, the number of women interviewed in Northern accounts for about 20% of the total sample of women interviewed (4,803/24,562) and the number of women interviewed in Southern accounts for almost the same percentage of the total sample of women interviewed (46%, or 11,342/24,562). This unweighted distribution of women does not accurately represent the population. In order to get statistics that are representative of Malawi, the distribution of the women in the sample needs to be weighted (or mathematically adjusted) such that it resembles the true distribution in the country. Women from a small region, Northern, should only contribute a small amount to the national total. Women from a large region, like Southern, should contribute much more. Therefore, DHS statisticians mathematically calculate a “weight” which is used to adjust the number of women from each region so that each region’s contribution to the total is proportional to the actual population of the region. The numbers in the purple column (2) represent the “weighted” values. The weighted values can be smaller or larger than the unweighted values at regional level. The total national sample size of 24,562 women has not changed after weighting, but the distribution of the women in the regions has been changed to represent their contribution to the total population size. 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 red column (3) to the actual population distribution of Malawi, you would see that women in each region are contributing to the total sample with the same weight that they contribute to the population of the country. The weighted number of women in the survey now accurately represents the proportion of women who live in Southern region and the proportion of women who live in Northern region. Table 3.1 Background characteristics of respondents Percent distribution of women and men age 15-49 by selected background characteristics, Malawi DHS 2015-16 Background characteristic Women Weighted percent Weighted number Unweighted number Region Northern 11.6 2,838 4,803 Central 42.9 10,529 8,417 Southern 45.6 11,194 11,342 Total 15-49 100.0 24,562 24,562 3 2 1 Reading and Understanding the 2015-16 MDHS • xxxi With sampling and weighting, it is possible to interview enough women to provide reliable statistics at national and regional levels. In general, only the weighted numbers are shown in each of the MDHS tables, so don’t be surprised if these numbers seem low: they may actually represent a larger number of women interviewed. xxxii • Map of Malawi Introduction and Survey Methodology • 1 INTRODUCTION AND SURVEY METHODOLOGY 1 he 2015-16 Malawi Demographic and Health Survey (MDHS) was implemented by the National Statistical Office (NSO) in joint collaboration with the Ministry of Health. Data collection took place from 19 October 2015 to 17 February 2016. ICF provided technical assistance through The DHS Program, which is funded by the United States Agency for International Development (USAID) and provides financial support and technical assistance for population and health surveys in countries worldwide. Other agencies and organisations that facilitated the successful implementation of the survey through technical or financial support include the National Aids Commission (NAC), United Nations Children’s Fund (UNICEF), United Nations Population Fund (UNFPA) and UN Women. Irish Aid and the World Bank provided assistance to the micronutrient component of the 2015-16 MDHS. 1.1 SURVEY OBJECTIVES The primary objective of the 2015-16 MDHS is to provide current estimates of basic demographic and health indicators. The MDHS provides a comprehensive overview of population, maternal, and child health issues in Malawi. More specifically, the 2015-16 MDHS:  collected data that allow the calculation of key demographic indicators, particularly fertility and under- 5 and adult 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 family health, such as immunisation coverage among children, prevalence and treatment of diarrhoea and other diseases among children under age 5, and maternity care indicators that include antenatal visits and assistance at delivery  obtained data on child feeding practices including breastfeeding  collected anthropometric measures that assess nutritional status, and conducted anaemia testing for all eligible children under age 5 and women age 15-49  collected data on knowledge and attitudes of women and men about sexually-transmitted diseases (STDs) and HIV/AIDS, potential exposure to the risk of HIV infection (risk behaviours and condom use) and coverage of HIV Testing and Counselling (HTC) and other key HIV programmes  collected dried blood spot (DBS) specimens for HIV testing from women age 15-49 and men age 15- 54 to provide information on the prevalence of HIV among the adult population in the prime reproductive ages. The micronutrient component of the 2015-16 MDHS was designed to: (1) determine the prevalence of micronutrient deficiencies (vitamin A, B, iron, iodine, zinc) and anaemia among pre-school and school-age children, women, and men of child-bearing age; (2) estimate micronutrient supplementation and fortification coverage; and (3) assess the knowledge and practices in maternal and child nutrition. Information on the design and implementation of the micronutrient component and its findings will be presented in a separate report. T 2 • Introduction and Survey Methodology The information collected in the 2015-16 MDHS will assist policy makers and programme managers in evaluating and designing programmes and strategies that can improve the health of the country’s population. 1.2 SAMPLE DESIGN The sampling frame used for the 2015-16 MDHS is the frame of the Malawi Population and Housing Census (MPHC), conducted in Malawi in 2008, and provided by the Malawi National Statistical Office (NSO). The census frame is a complete list of all census standard enumeration areas (SEAs) created for the 2008 MPHC. A SEA is a geographic area that covers an average of 235 households. The sampling frame contains information about the SEA location, type of residence (urban or rural), and the estimated number of residential households. Administratively, Malawi is divided into 28 districts. The sample for the 2015-16 MDHS was designed to provide estimates of key indicators for the country as a whole, for urban and rural areas separately, and for each of the 28 districts. Indicators will also be shown for the Northern, Central, and Southern regions of the country. The 2015-16 MDHS sample was stratified and selected in two stages. Each district was stratified into urban and rural areas; this yielded 56 sampling strata. Samples of SEAs were selected independently in each stratum in two stages. Implicit stratification and proportional allocation were achieved at each of the lower administrative levels by sorting the sampling frame within each sampling stratum before sample selection, according to administrative units in different levels, and by using a probability proportional to size selection at the first stage of sampling. In the first stage, 850 SEAs, including 173 SEAs in urban areas and 677 in rural areas, were selected with probability proportional to the SEA size and with independent selection in each sampling stratum. The SEA size is the number of residential households in the SEA as defined in the 2008 MPHC. A household listing operation was implemented in all the selected SEAs during August-October 2016. The resulting lists of households served as a sampling frame for the selection of households in the second stage. Some of the selected SEAs were large. To minimise the task of household listing, each large SEA (more than 250 households) selected for the 2015-16 MDHS was segmented. One segment was selected for the survey with probability proportional to the segment size. A household listing was conducted only in the selected segment. Thus, in the 2015-16 MDHS, a cluster is either an SEA or a segment of an SEA. In the second stage of selection, a fixed number of 30 households per urban cluster and 33 per rural cluster were selected with an equal probability systematic selection from the newly created household listing. All women age 15-49 who were either permanent residents of the selected households or visitors who stayed in the household the night before the survey were eligible to be interviewed. In one-third of all sampled households, all men age 15-54, including both usual residents and other persons who stayed in the household the night before the interview, were eligible for individual interview. In the subsample of households selected for the male survey, anaemia testing was performed among eligible women who consented to being tested. With the parent’s or guardian’s consent, children age 6-59 months were also tested for anaemia. In the same subsample, blood samples were collected for laboratory testing of HIV from eligible women and men who consented. Height and weight information was also collected from eligible women and from children age 0-59 months. 1.3 QUESTIONNAIRES Four questionnaires were used in the 2015-16 MDHS: 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 Malawi. Input was solicited from stakeholders who represented government ministries and agencies, nongovernmental organisations, and international donors. After the Introduction and Survey Methodology • 3 preparation of the definitive questionnaires in English, the questionnaires were then translated into Chichewa and Tumbuka languages. All four questionnaires were programmed into tablet computers to facilitate computer-assisted personal interviewing (CAPI) for data collection, and to offer the option to choose either English, Chichewa or Tumbuka for each questionnaire. The Household Questionnaire listed all members of and visitors to the selected households. Basic demographic information was collected on the characteristics of each person listed such as age, sex, marital status, education, and relationship to the head of the household. Parents’ survival status was determined for children under age 18. The 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. The Household Questionnaire collected information on characteristics of the household’s dwelling unit such as source of water, type of toilet facilities, materials used for the floor of the dwelling unit, and ownership of various durable goods. The Household Questionnaire also collected information on the ownership and use of mosquito nets. An additional module developed by UNICEF to estimate the prevalence of disabilities among children age 5-17 was also included in the Household Questionnaire. The Woman’s Questionnaire collected information from all eligible women age 15-49 who were asked questions on:  Background characteristics: age, education, media exposure  Reproduction: children ever born, birth history, current pregnancy  Family planning: knowledge and use of contraception, sources of contraceptive methods, information on family planning  Maternal and child health, breastfeeding, and nutrition: prenatal care, delivery, postnatal care, breastfeeding and complementary feeding practices, vaccination coverage, prevalence and treatment of diarrhoea, acute respiratory infection (ARI), fever, knowledge and use of oral rehydration therapy (ORT), breastfeeding, and feeding practices  Marriage and sexual activity: marital status, age at first marriage, number of unions, age at first sexual intercourse, recent sexual activity, number and type of sexual partners, use of condoms  Fertility preferences: desire for more children, ideal number of children, gender preferences, intention to use family planning  Husband’s background and woman’s work: husband’s age, level of education, and occupation, and woman’s occupation and sources of earnings  STDs and HIV: knowledge of STDs and HIV, methods of transmission, sources of information, behaviours to avoid STDs and HIV, and stigma  Knowledge, attitudes, and behaviours related to other health issues such as injections, smoking, fistula, tuberculosis  Adult and maternal mortality  Domestic violence 1.4 ANTHROPOMETRY, ANAEMIA TESTING, AND HIV TESTING In the subsample of households selected for the male survey, the 2015-16 MDHS incorporated the biomarkers for anthropometry, anaemia testing, and HIV testing. In contrast to the data collection procedure for the household and individual interviews, data related to the biomarkers were initially 4 • Introduction and Survey Methodology recorded on the Biomarker Questionnaire and subsequently entered into interviewers’ tablet computers. The survey protocol, including biomarker collection, was reviewed and approved by the National Health Sciences Research Committee in Malawi and the ICF Institutional Review Board. Anthropometry: Height and weight measurements were recorded for children age 0-59 months and women age 15-49. Anaemia testing: Blood specimens for anaemia testing were collected from women age 15-49 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 drawn from a drop of blood taken from a finger prick (or a heel prick from children age 6-11 months) and collected in a microcuvette. Haemoglobin analysis was conducted on-site with a battery-operated portable HemoCue analyser. Test results were provided verbally and in writing. Parents of children with a haemoglobin level below 7 g/dl were instructed to take the child to a health facility for follow-up care. Non-pregnant women and pregnant women were referred for follow-up care if their haemoglobin levels were below 7 g/dl and 9 g/dl, respectively. All households in which anaemia testing was conducted were given a brochure that explained the causes and prevention of anaemia. HIV testing: Interviewers collected finger-prick blood specimens from women age 15-49 and men age 15- 54 who consented to laboratory HIV testing. The protocol for blood specimen collection and analysis was based on the anonymous linked protocol developed for The DHS Program. This protocol allows for the merger of HIV test results with the sociodemographic data collected in the individual questionnaires after removal of all information that could potentially identify an individual. Interviewers explained the procedure, the confidentiality of the data, and the fact that the test results would not be made available to respondents. If a respondent consented to HIV testing, five blood spots from the finger prick were collected on a filter paper card to which a barcode label unique to the respondent was affixed. A duplicate label was attached to the Biomarker Questionnaire. A third copy of the same barcode was affixed to the dried blood spot transmittal sheet to track the blood samples from the field to the laboratory. Respondents were asked whether they would consent to allow the laboratory to store their blood sample for future unspecified testing. If respondents did not consent to additional testing, it was indicated on the Biomarker Questionnaire that they refused additional tests on their specimen, and the words “no additional testing” were written on the filter paper card. Each respondent, whether they provided consent or not, was given an informational brochure on HIV and a list of nearby sites that provide HIV testing services (HTS). Blood samples were dried overnight and packaged for storage the following morning. Samples were collected periodically from the field and transported to the laboratory at the Community Health Sciences Unit (CHSU) in Lilongwe. Upon arrival at CHSU, each blood sample was logged into the CSPro HIV Test Tracking System database, given a laboratory number, and stored at -20˚C until tested. The HIV testing protocol (Figure 1.1) stipulated that blood could be tested only after the questionnaire data collection had been completed, the data had been verified and cleaned, and all unique identifiers other than the anonymous barcode number had been removed from the data file. The testing algorithm calls for testing all samples with the first assay, the Enzygnost Integral II (Siemens) enzyme-linked immunoassay (ELISA I). All samples that tested positive on the ELISA I are subjected to a second ELISA (ELISA II), the Murex HIV Ag/Ab combination (DiaSorin). Similar to samples that tested positive on ELISA I, 5% of the samples that tested negative on the ELISA I are also subjected on the ELISA II while the other 95% are recorded as negative. Concordant negative results on the ELISA I and ELISA II are recorded as negative. If the results on ELISA I and ELISA II are discordant, the two ELISAs are repeated in parallel. If the results remain Introduction and Survey Methodology • 5 discordant, a third confirmatory assay is used, the InnoLia HIV I/II Score (Fujirebio) line immunoassay. Concordant positive results on the ELISA I and ELISA II are also subjected to the third confirmatory assay. When both ELISA I and ELISA II are positive, the sample is rendered positive if InnoLia is positive, and inconclusive if InnoLia is negative or indeterminate. When ELISA I and ELISA II are discordant, the specimen is rendered inconclusive if InnoLia is positive, negative if InnoLia is negative, and indeterminate if InnoLia is indeterminate. To monitor the quality of HIV testing and assess the validity of test results, two levels of quality control steps were employed. During HIV testing at CHSU, an internal quality control process was established through the use of control materials and retesting of a randomly selected proportion of negative samples. To assess the validity of results obtained by CHSU, a selected number of specimens that tested positive at CHSU were sent to the Global Clinical and Viral Laboratory (GCVL) in Durban, South Africa for retesting. For the purpose of internal quality control: 1) positive and negative serum controls supplied by the manufacturer with the test kits were included on each microtiter plate of samples, and 2) known HIV- negative, low-positive, and high-positive DBS controls obtained from CDC, Atlanta, USA were tested in parallel with the kit controls on every microtiter plate of samples. As a part of the external quality control, 23% of all specimens confirmed HIV positives at CHSU were randomly selected and sent to the GCVL for retesting. The external quality control testing yielded a 99% agreement with the CHSU results. Figure 1.1 HIV testing algorithm After HIV testing had been completed, the test results for the 2015-16 MDHS were entered into a spreadsheet with a barcode as the unique identifier. The barcode linked the HIV test results with the individual interview data. 95% 5% Positive ELISA 1 & ELISA NEGATIVE ELISA 1 & ELISA 2 Indeterminate/ Missing Negative Inconclusive Inconclusive/ Missing Inconclusive Negative Positive Nagative Repeat Positive Negative Inno-Lia HIV I/II line immunoassay Inno-Lia HIV I/II line immunoassay Indeterminate/Missing Negative Positive Indeterminate/Missing Negative Negative Negative Positive Internal Quality Control ELISA 2 ELISA 1 & ELISA POSITIVE ELISA 1 NEGATIVE & ELISA 2 POSITIVE ELISA 1 POSITIVE & ELISA 2 NEGATIVE ELISA 1 Enzygnost Integral II ELISA 2 Murex HIV Ag/Ab Combination Murex HIV Ag/Ab Combination Positive 6 • Introduction and Survey Methodology 1.5 PRETEST The pretest for the 2015-16 MDHS was conducted from 28 July 2015 to 21 August 2015 in Malosa at the Chilema Training Centre. The pretest included in-class training, a visit to a health clinic to practice collecting biomarker data on children, and field practice days. The field practice was conducted in clusters that surround the Chilema Training Centre and were not included in the 2015-16 MDHS sample. A total of 38 trainees attended the pretest. All trainees had some experience with household surveys, either involvement in previous Malawi DHS surveys or in other similar surveys. After field practice, a debriefing session was held with the pretest field staff. Modifications to the questionnaires were made based on lessons from the training exercise. 1.6 TRAINING OF FIELD STAFF The NSO recruited and trained 268 individuals to serve as team leaders, field editors, interviewers, secondary editors, and reserve interviewers for the main fieldwork. The training took place from 21 September 2015 to 10 October 2015 at St. Luke’s Nursing School in Malosa. The training course included instruction on interviewing techniques and field procedures, a detailed review of questionnaire content, instruction on administering the paper and electronic questionnaires, mock interviews between participants in the classroom, and practice interviews with real respondents in areas beyond the survey sample. A total of 90 individuals were recruited and trained on collecting biomarker data that included taking height and weight measurements, testing for anaemia by measuring haemoglobin level, and preparing dried blood spots (DBS) for subsequent HIV testing. The biomarker training was held from 28 September 2015 to 10 October 2015 in Malosa at the Chilema Training Centre. The training included lectures, demonstrations of biomarker measurement or testing procedures, field practice with children at a health clinic, and standardisation exercises for the height and weight measurements. To put the importance of the 2015-16 MDHS into context for the trainees, the training also included presentations by the Ministry of Health staff on Malawi-specific policies and programmes on malaria, HIV/AIDS, child immunisations, child nutrition, and childhood diseases. A four-day field practice from 12 October 2015 to 16 October 2015 provided trainees with additional hands-on practice before the actual fieldwork. A total of 39 teams were formed for field practice. Each team included a team leader, field editor, three female interviewers, one male interviewer, and two biomarker technicians. Training participants were evaluated through homework, in-class exercises, quizzes, and observations during field practice. A total of 148 participants were selected to serve as interviewers, 74 as biomarker technicians, 37 as field editors, and 37 as team leaders. The selection of team leaders and field editors was based on their experience in leading survey teams and their performance during the pretest and primary training. Team leaders and field editors received additional instructions and practice with the CAPI system to perform supervisory activities. These activities included assigning households and receiving completed interviews from interviewers, recognising and resolving with error messages, receiving a system update, distributing updates to interviewers, completing biomarker questionnaires and DBS transmittal sheets, preparing a micronutrient questionnaire for eligible households, resolving duplicated cases, closing clusters, and transferring interviews to the central office via a secure Internet file streaming system (IFSS). In addition to the CAPI material, team leaders and field editors received additional training on strategies to locate and contact households selected for the survey, procedures for data quality control, and fieldwork supervision. 1.7 FIELDWORK Data collection was completed by 37 field teams, with each including one team leader, one field editor, three female interviewers, one male interviewer, two biomarker technicians, and one driver. Electronic Introduction and Survey Methodology • 7 data files were transferred to the NSO central office in Zomba every day via the secured IFSS. Senior staff from the NSO; University of Malawi-Chancellor College; the Ministry of Health; the Ministry of Finance, Economic Planning and Development; and a survey technical specialist from The DHS Program coordinated and supervised fieldwork activities. Data collection took place over a 4-month period, from 19 October 2015 through 17 February 2016. 1.8 DATA PROCESSING All electronic data collected in the 2015-16 MDHS were received via IFSS at the NSO central office in Zomba, where the data were stored on a password-protected computer. The data processing operation included secondary editing, which required resolution of computer-identified inconsistencies and coding of open-ended questions. The data were processed by four individuals who took part in the fieldwork training, and were supervised by two senior staff from NSO. Data editing was accomplished with CSPro software. Secondary editing and data processing were initiated in October 2015 and completed in March 2016. 1.9 RESPONSE RATES Table 1.1 shows response rates for the 2015-16 MDHS. A total of 27,516 households were selected for the sample, of which 26,564 were occupied. Of the occupied households, 26,361 were successfully interviewed, for a response rate of 99%. In the interviewed households, 25,146 eligible women were identified for individual interviews. Interviews were completed with 24,562 women, for a response rate of 98%. In the subsample of households selected for the male survey, 7,903 eligible men were identified and 7,478 were successfully interviewed, for a response rate of 95%. There is little variation in response rates according to residence. Table 1.1 Results of the household and individual interviews Number of households, number of interviews, and response rates, according to residence (unweighted), Malawi DHS 2015-16 Residence Total Result Urban Rural Household interviews Households selected 5,181 22,335 27,516 Households occupied 5,029 21,535 26,564 Households interviewed 4,991 21,370 26,361 Household response rate1 99.2 99.2 99.2 Interviews with women age 15-49 Number of eligible women 5,363 19,783 25,146 Number of eligible women interviewed 5,247 19,315 24,562 Eligible women response rate2 97.8 97.6 97.7 Interviews with men age 15-54 Number of eligible men 1,774 6,129 7,903 Number of eligible men interviewed 1,661 5,817 7,478 Eligible men response rate2 93.6 94.9 94.6 1 Households interviewed/households occupied. 2 Respondents interviewed/eligible respondents. Housing Characteristics and Household Population • 9 HOUSING CHARACTERISTICS AND HOUSEHOLD POPULATION 2 Key Findings  Drinking water: Eighty-seven percent of households use an improved source of drinking water. By residence, 85% of rural households use water from an improved source compared with 98% of urban households.  Sanitation: Fifty-two percent of households use an improved facility and 31% use a facility that would be considered improved if it were not shared. Six percent of households have no facility.  Electricity: Only 4% of rural households have access to electricity compared with 49% in urban areas.  Household population and composition: Almost half (48%) of the population of Malawi is under age 15.  Orphans: Among children under age 18, 12% are orphans (one or both parents are dead) and one in five is not living with either biological parent.  School attendance: The net attendance ratio falls from 94% in primary school to 17% in secondary school. Girls and boys of the primary and secondary school age are about equally likely to attend primary and secondary schools (94% and 93% respectively for primary, 18% and 17% respectively for secondary school). nformation on the socioeconomic characteristics of the household population in the 2015-16 MDHS provides a context for interpreting demographic and health indicators and an approximate indication of the representativeness of the survey. In addition, this information describes the living conditions of the population. This chapter presents information on the sources of drinking water, sanitation, exposure to smoke inside the home, wealth, hand washing, composition of the household population, educational attainment, school attendance, birth registration, children’s living arrangements, and parental survivorship. 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. Because the quality of bottled water is unknown, households that use bottled water for drinking are classified as using an improved source only if their water source for cooking and hand washing comes from an improved source. Sample: Households I 10 • Housing Characteristics and Household Population In Malawi, almost all urban households (98%) have access to an improved source of drinking water compared with only 85% of rural households (Table 2.1). Improved sources of water protect against outside contamination so that the water is more likely to be safe to drink. Urban and rural households rely on different sources of drinking water. The main sources of drinking water for urban households are piped water in their dwelling or yard (41%) and public tap or standpipe (33%). In contrast, rural households rely on tube well or borehole (72%), followed by unimproved sources (15%) (Figure 2.1). In rural areas, only 2% of households have piped water on their premises and 47% of households travel 30 minutes or longer round trip to fetch drinking water. Clean water is a basic need for human life. However, seven in ten households (69%) report that they do no treat their water prior to drinking. Treatment is less common in urban areas than rural areas; 78% of urban households do not treat water compared with 67% in rural areas. Adding bleach or chlorine to drinking water before drinking is the most common water treatment (20%). A total of 26% of households in Malawi are using an appropriate treatment method with 20% in urban areas and 27% in rural areas. Table 2.2 presents information on the percentage of households using piped water or water from a tube well or borehole that reported availability of water in the last 2 weeks. Seventy-five percent of households in Malawi reported having water with no interruption of at least a single day in the last 2 weeks. Urban households are more likely to report no availability of water for at least 1 day compared with rural households (55% versus 18%). Trends: There was little variation in the percentage of households using water from an improved water source between 1992 and 2004. However, the percentage has been increasing steadily from 65% in 2004 to 80% in 2010 and 87% in 2015-16. 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 Figure 2.1 Household drinking water by residence 8 41 2 3 12 1 10 33 6 62 10 72 4 2 4 13 2 15 Total Urban Rural Unimproved source Protected dug well Tubewell or borehole Public tap/standpipe Piped to neighbor Piped water into dwelling/yard/plot Percent distribution of households by source of drinking water Housing Characteristics and Household Population • 11 About half of Malawian households (52%) use improved toilet facilities, which are non-shared facilities that prevent people from coming into contact with human waste and can reduce the transmission of cholera, typhoid, and other diseases. Shared toilet facilities of an otherwise acceptable type are also common, especially in urban areas; 51% of urban households use shared facility compared with 28% of rural households (Figure 2.2). Seventeen percent of households in Malawi use unimproved toilet facilities, with 6% of households not using any toilet facility (Table 2.3). 2.3 EXPOSURE TO SMOKE INSIDE THE HOME AND OTHER HOUSING CHARACTERISTICS 2.3.1 Exposure to Smoke Inside the Home Exposure to smoke inside the home, either from cooking with solid fuels or smoking tobacco, has potentially harmful health effects. Ninety-eight percent of households in Malawi use some type of solid fuel for cooking, with virtually all being wood (Table 2.4); this figure has remained unchanged since 2010 (98%). Exposure to cooking smoke is greater when cooking takes place inside the house rather than in a separate building or outdoors. In Malawi, cooking is done in a separate building in 60% of households, a figure that is nearly identical to the 2010 MDHS (59%). In 12% of households, someone smokes inside the house on daily basis. 2.3.2 Other Housing Characteristics The survey collected data on access to electricity, flooring materials, and the number of rooms used for sleeping. Forty-nine percent of urban households and 4% of rural households have access to electricity. Overall, 11% of households in Malawi have electricity. The materials used for flooring include earth or sand (74% of households) and cement (25%). There exist, however, considerable differences in flooring material according to place of residence. The most common flooring material in rural areas is earth or sand (83%), while the most common flooring material in urban areas is cement (71%). 2.4 HOUSEHOLD WEALTH AND DURABLE GOODS 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 with 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 Figure 2.2 Household toilet facilities by residence 52 45 53 31 51 28 11 4 12 6 1 7 Total Urban Rural Open defecation (no facility/bush/field) Unimproved facility Shared facility Improved sanitation Percent distribution of households by type of toilet facilities 12 • Housing Characteristics and Household Population Table 2.5 presents wealth quintiles according to urban-rural residence and region. Included in the table is the Gini coefficient, which indicates the level of concentration of wealth, with 0 an equal distribution and 1 a totally unequal distribution. In Malawi, the wealthiest households are concentrated in urban areas. Ninety-one percent of the urban population belongs to the two highest wealth quintiles. By contrast, almost half of the rural population (46%) falls in the two lowest wealth quintiles (Figure 2.3). The survey also collected information on household effects, means of transportation, agricultural land, and farm animals (Table 2.6). Urban households are more likely than rural households to own a radio (65% versus 36%), television (45% versus 6%), or mobile telephone (86% versus 48%). In contrast, rural households are more likely than urban households to own agricultural land (83% versus 37%) or farm animals (53% versus 23%). 2.5 HAND WASHING To obtain hand washing information, interviewers asked to see the place where members of the household most often wash their hands. A place for washing hands was observed in 83% of households. Soap and water were observed in 11% of the hand washing locations, while 26% had water only (Table 2.7). Water, soap, or other cleaning agents were not observed in 58% of hand washing locations. 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. Figure 2.3 Household wealth by residence 2 23 2 23 5 23 16 21 75 11 Urban Rural Percent distribution of de jure population by wealth quintiles Highest Fourth Middle Second Lowest Housing Characteristics and Household Population • 13 A total of 117,177 individuals stayed overnight in the 26,361 sample households in the 2015-16 MDHS. Fifty-two percent (60,819) were female, and 48% (56,358) were male (Table 2.8). The population pyramid in Figure 2.4 illustrates the distribution by 5-year age groups and sex. The broad base of the pyramid shows that Malawi’s population is young, which is typical of developing countries with low life expectancy. Children under age 15 represent 48% of the household population, while individuals age 65 and older represent only 4%. Table 2.9 shows that females head 3 in 10 households in Malawi. Urban and rural households are, on average, of the similar size (4.3 and 4.5 persons, respectively). Overall, 33% of households in Malawi are caring for foster or orphaned children. Trends: Similar to the current distribution of the household population, children under age 15 were 49% of the population in 2010, with individuals age 65 and older at 4%. Average household size remained essentially the same between 2010 and 2015-16 (4.6 versus 4.5 persons, respectively), while the percentage of female-headed households has increased slightly from 28% in 2010 to 31% in 2015-16. 2.7 BIRTH REGISTRATION Registered birth Child has a birth certificate or his/her birth is registered with the civil authority. Sample: De jure children under age 5 In 2009, the Malawian Parliament passed the National Registration Act of 2009. The law states that a parent must register a child’s birth within 6 weeks. In the parents’ absence, others must take responsibility for registering the birth of a child; this includes the head of the household in which the child was born, anyone who was present at the child’s birth, or anyone in charge of the child. Those registering a birth after 6 weeks incur a fine. To register a birth, a parent or other representative must complete a birth report and deliver a copy to the district registrar. A mother can acquire a birth report from a health facility after giving birth, during her postnatal check-ups, or at the time of the baby’s first immunisations. Upon receiving a birth report, the district registrar enters the birth in the birth register and offers a birth certificate. Tables 2.10.1 presents information on birth registration of children under age 5. At the time of the survey, 67% of children under age 5 had births registered with the civil authority; this includes 17% of children with birth certificates. The percentage of children whose birth has been registered is higher among children under age 2 (71%) than those between age 2 and 4. Children in urban areas are more likely than children in rural areas to have their birth registered. Birth registration is higher in the Northern region (75%) than in Central and Southern regions (66% each). For the majority of children whose birth were registered, the process was not completed as required by the National Registration Act of 2009. For 9 in 10 children (91%) whose births were registered, the birth was 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 14 • Housing Characteristics and Household Population registered at a health facility (Table 2.10.2); this means that they received a birth report but did obtain a birth certificate from a district officer. 2.8 CHILDREN’S LIVING ARRANGEMENTS AND PARENTAL SURVIVAL Orphan A child with one or both parents who are dead. Sample: Children under age 18 One in five (20%) children under age 18 are not living with a biological parent (Table 2.11). Twelve percent of children under age 18 are orphans with one or both parents who have died. The percentage of children who are orphans rises rapidly with age, from 3% among children under age 5 to 10% among children age 5-9 and 24% among children age 15-17. The Southern region has the highest percentage of children who are orphans (14%). Trends: The percentage of children under age 18 who do not live with a biological parent has remained essentially the same between 2010 and 2015-16 (18% and 20%, respectively). Similarly, the percentage of children under age 18 who are orphans has not changed since 2010; 13% children were orphans in 2010 compared with 12% in 2015-16. 2.9 EDUCATION 2.9.1 Educational Attainment Median educational attainment Half the population has completed less than the median number of years of schooling and half the population has completed more than the median number of years of schooling. Sample: De facto household population age 6 and older Overall, 86% of females and 92% of males age 6 and over have ever attended school. For the majority of women, the primary education is the highest level of schooling attended or completed; 67% of women have some primary education and 5% have completed primary education. Similarly, among men, 65% have some primary education and 6% have completed the primary education. Only 5% of females and 9% of males have completed secondary school or gone beyond secondary school. Fourteen percent of females and 8% of males have never attended school. Median educational attainment is slightly higher for males (3.9 years) than for females (3.1 years) (Tables 2.12.1 and 2.12.2). Trends: Educational attainment at the household level has increased since 1992. Among women, the median number of years of schooling has increased from 0 years in 1992 to 2.5 years in 2010 and 3.1 years in 2015-16. Similar to women, the median number of years of schooling completed by men has increased from 1.9 years in 1992 to 3.5 years in 2010 and 3.9 years in 2015-16. Over the same period, the percentage of women and men with no education has decreased from 47% of women and 28% of men in 1992 to 19% of women and 11% of men in 2010 to 14% of women and 8% of men in 2015-16. Housing Characteristics and Household Population • 15 Patterns by background characteristics  Among both women and men, the median number of years of schooling is higher in urban areas than in rural areas with 6.7 years versus 2.7 years among women and 7.6 versus 3.4 years among men.  Educational attainment increases with household wealth. Women in the lowest wealth quintile have completed a median of 1.6 years of schooling compared with a median of 6.5 years for women in the highest wealth quintile. The median number of years of schooling increases from 2.1 years among men in the lowest wealth quintile to 7.3 among those in the highest quintile.  The median number of years of schooling is highest in the Northern region (4.6 years for women and 7.6 years for men). Differences in the median number of years of schooling are minor between the Central region (3.0 years for women and 3.8 years for men) and the Southern region (2.9 years for women and 3.7 years for men).  The percentage of household populations with no education is higher in rural areas than urban areas (16% versus 5% for females and 3% versus 9% for males). 2.9.2 School Attendance Net attendance ratio (NAR) Percentage of the school-age population that attends primary or secondary school. Sample: Children age 6-13 for primary school NAR and children age 14-17 for secondary school NAR Ninety-four percent of girls age 6-13 attend primary school compared with 93% of boys (Table 2.13). The net attendance ratio (NAR) drops in secondary school: only 18% of girls and 17% of boys age 14-17 attend secondary school. Patterns by background characteristics  At the primary school level, there is little difference in NAR between urban and rural (95% and 94%, respectively). However, at the secondary school level, the NAR is much higher in urban areas than in rural areas (41% versus 13%).  Among regions, the Northern region has the highest NAR both at the primary school level (96%) and the secondary school level (21%).  The NARs increase with household wealth, especially at the secondary school level. Attendance in the lowest wealth quintile is 5% of girls and 4% of boys compared with 42% of girls and 40% of boys in the highest wealth quintile (Figure 2.5). Figure 2.5 Secondary school attendance by household wealth 5 5 10 20 42 4 6 11 18 40 Lowest Second Middle Fourth Highest Girls Boys WealthiestPoorest Net attendance ratio for secondary school among children age 14-17 16 • Housing Characteristics and Household Population 2.9.3 Other Measures of School Attendance Gross attendance ratio (GAR) The total number of primary and secondary school students expressed as a percentage of the official primary and secondary school-age population. Sample: Children age 6-13 for primary school GAR and children age 14-17 for secondary school GAR Gender Parity Index (GPI) The ratio of female to male attendance rates at the primary and secondary levels that indicates the magnitude of the gender gap. Sample: Primary and secondary school students The gross attendance ratio (GAR) is 127% at the primary school level and 37% at the secondary school level. These figures indicate that a number of children outside the official school age population for that level are attending primary school, and not all those who should be are attending secondary school (Table 2.13). A gender parity index (GPI) of 1 indicates parity or equality between the school participation ratios for males and females. A GPI lower than 1 indicates a gender disparity in favour of males, with a higher proportion of males than females attending that level of schooling. A GPI higher than 1 indicates a gender disparity in favour of females. The GPI for the NAR is 1.01 at the primary school level and 1.03 at the secondary school level. This indicates that there is relatively little difference in overall school attendance by school-age girls and boys at either the primary or secondary school level. Conversely, the GPI for the GAR is less than 1, which indicates that male children outside of the official school age population are more likely to attend school than their female counterparts; the GPIs for the GAR are 0.93 at the primary school level and 0.84 at the secondary school level. Age-specific attendance rate (ASAR) Children attending school, irrespective of whether they are attending the appropriate grade for their age. Sample: De facto household population age 5-24 attending school Age-specific attendance rates (ASARs) for the population age 5 to 24 are presented in Figure 2.6 by age and sex. The ASAR indicates participation in schooling at any level, from primary to higher levels of education. The trends are generally the same for males and females. Approximately 80% of children attend school by age 6. In the age group 6-13, the ASARs are slightly higher for females than for males. Between ages 7 and 13, more than 90% of children attend Figure 2.6 Age-specific attendance rates 0 10 20 30 40 50 60 70 80 90 100 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 Age in years Female Male Percentage of the de facto household population age 5-24 years attending school Housing Characteristics and Household Population • 17 school. The attendance rate declines rapidly from age 14 to 24, and in this age group, the ASARs are higher for males than females. 2.10 CHILD FUNCTIONING AND DISABILITY The 2015-16 MDHS household questionnaire included questions on the functioning and disability among the usual resident children age 2-17. The questions were adapted from a module developed as a part of Multiple Indicator Cluster Surveys (MICS), a UNICEF-supported household survey programme (http://mics.unicef.org/surveys). The respondents to the household questionnaire were asked questions about the specific functioning problems or disability of children. The questions included speech and language, hearing, vision, learning (cognition and intellectual development), mobility and motor skills, emotions, and behaviours. Results displayed in Table 2.14.1 indicate that 29% of children age 2-9 have at least one reported functioning problem or disability. One in five (21%) children age 2 cannot name at least one object such as an animal, toy, cup, or spoon, while 5% of children age 3-9 were reported to have speech that was different from normal. Table 2.14.2 presents the percentage of children 10-17 with reported specific functioning problems or disability. Difficulty either hearing (5%) or remembering or concentrating (6%) among children age 10-17 were the two most commonly reported problems. 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 Wealth quintiles  Table 2.6 Household possessions  Table 2.7 Hand washing  Table 2.8 Household population by age, sex, and residence  Table 2.9 Household composition  Table 2.10.1 Birth registration of children under age 5  Table 2.10.2 Place of birth registration of children under age 5  Table 2.11 Children’s living arrangements and orphanhood  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 School attendance ratios  Table 2.14.1 Child functioning and disability: Children age 2-9  Table 2.14.2 Child functioning and disability: Children age 10-17 18 • Housing Characteristics and Household Population Table 2.1 Household drinking water Percent distribution of households and de jure population by source of drinking water, time to obtain drinking water, and treatment of drinking water, according to residence, Malawi DHS 2015-16 Households Population Characteristic Urban Rural Total Urban Rural Total Source of drinking water Improved source 98.0 85.2 87.2 98.2 85.1 87.0 Piped into dwelling/yard plot 41.3 2.3 8.3 42.6 2.3 8.2 Piped to neighbour 11.7 1.0 2.7 11.1 0.9 2.4 Public tap/standpipe 32.7 5.9 10.0 32.1 5.9 9.7 Tube well or borehole 9.6 71.6 62.1 9.6 71.7 62.7 Protected dug well 2.3 4.1 3.8 2.6 4.1 3.9 Protected spring 0.1 0.2 0.2 0.2 0.3 0.2 Bottled water, improved source for cooking/washing1 0.1 0.0 0.0 0.1 0.0 0.0 Unimproved source 2.0 14.6 12.7 1.7 14.7 12.8 Unprotected dug well 1.6 9.2 8.0 1.3 9.3 8.2 Unprotected spring 0.1 1.1 0.9 0.0 1.1 1.0 Surface water 0.4 4.3 3.7 0.4 4.2 3.7 Other source 0.0 0.2 0.2 0.1 0.1 0.1 Total 100.0 100.0 100.0 100.0 100.0 100.0 Time to obtain drinking water (round trip) Water on premises2 55.8 8.1 15.4 56.3 8.1 15.1 Less than 30 minutes 25.6 43.5 40.7 25.2 43.1 40.5 30 minutes or longer 18.6 47.2 42.9 18.4 47.7 43.5 Don’t know 0.0 1.2 1.0 0.0 1.1 1.0 Total 100.0 100.0 100.0 100.0 100.0 100.0 Water treatment prior to drinking3 Boil 6.7 8.6 8.3 6.6 9.1 8.7 Bleach/chlorine added 14.5 20.4 19.5 14.6 20.5 19.6 Strain through cloth 1.0 2.1 1.9 1.1 2.2 2.1 Ceramic, sand or other filter 0.2 0.5 0.5 0.3 0.6 0.6 Let it stand and settle 1.6 5.7 5.1 1.6 5.9 5.3 Other 0.2 1.0 0.8 0.1 1.0 0.9 No treatment 78.4 67.0 68.7 78.4 66.3 68.0 Percentage using an appropriate treatment method4 19.9 27.3 26.2 19.8 27.8 26.6 Number 4,042 22,319 26,361 17,230 101,536 118,766 1 Because the quality of bottled water is unknown, households using bottled water for drinking are classified as using an improved or unimproved source according to their water source for cooking and hand washing . 2 Includes water piped to a neighbour. 3 Since respondents may report multiple treatment methods, the sum of treatment may exceed 100%. 4 Appropriate water treatment methods include boiling, bleaching, filtering, and solar disinfecting. 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, Malawi DHS 2015-16 Availability of water in last 2 weeks Households Population Urban Rural Total Urban Rural Total Not available for at least one day 54.8 17.8 24.3 55.1 18.1 24.3 Available with no interruption of at least one day 44.4 82.1 75.4 44.5 81.8 75.6 Don’t know/missing 0.8 0.1 0.2 0.5 0.1 0.2 Total 100.0 100.0 100.0 100.0 100.0 100.0 Number using piped water or water from a tube well 3,860 18,036 21,896 16,445 82,024 98,469 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 hand washing is piped water or water from a tube well or borehole. Housing Characteristics and Household Population • 19 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, Malawi DHS 2015-16 Type and location of toilet/latrine facility Households Population Urban Rural Total Urban Rural Total Improved sanitation 44.7 53.0 51.8 49.1 56.1 55.1 Flush/pour flush to piped sewer system 2.7 0.1 0.5 2.8 0.1 0.5 Flush/pour flush to septic tank 10.8 0.3 1.9 11.2 0.3 1.9 Flush/pour flush to pit latrine 1.0 0.1 0.3 1.2 0.2 0.3 Ventilated improved pit (VIP) latrine 0.4 0.7 0.6 0.5 0.7 0.7 Pit latrine with slab 29.7 51.6 48.3 33.5 54.6 51.6 Composting toilet 0.0 0.2 0.2 0.0 0.2 0.2 Unimproved sanitation 55.3 47.0 48.2 50.9 43.9 44.9 Shared facility1 51.1 27.6 31.2 46.9 25.4 28.6 Flush/pour flush to piped sewer system 0.1 0.0 0.0 0.0 0.1 0.0 Flush/pour flush to septic tank 0.3 0.1 0.1 0.2 0.1 0.1 Flush/pour flush to pit latrine 0.2 0.1 0.1 0.2 0.1 0.1 Ventilated improved pit (VIP) latrine 0.3 0.2 0.2 0.2 0.2 0.2 Pit latrine with slab 50.2 27.0 30.6 46.2 24.9 28.0 Composting toilet 0.1 0.1 0.1 0.1 0.1 0.1 Unimproved facility 3.6 12.2 10.8 3.6 12.3 11.0 Pit latrine without slab/open pit 3.5 12.0 10.7 3.5 12.1 10.8 Bucket 0.0 0.1 0.1 0.0 0.1 0.1 Open defecation (no facility/bush/ field) 0.6 7.3 6.2 0.5 6.2 5.4 Total 100.0 100.0 100.0 100.0 100.0 100.0 Number of households/population 4,042 22,319 26,361 17,230 101,536 118,766 Location of the facility In own dwelling 14.8 2.8 4.7 15.5 2.8 4.7 In own yard/plot 80.8 85.5 84.8 80.6 86.9 85.9 Elsewhere 4.4 11.7 10.5 4.0 10.3 9.3 Total 100.0 100.0 100.0 100.0 100.0 100.0 Number of households/population with a toilet/latrine facility 4,016 20,704 24,721 17,143 95,282 112,425 1 Facilities that would be considered improved if they were not shared by two or more households. 20 • Housing Characteristics and Household Population Table 2.4 Household characteristics Percent distribution of households and de jure population by housing characteristics, percentage using solid fuel for cooking, and percent distribution by frequency of smoking in the home, according to residence, Malawi DHS 2015-16 Households Population Housing characteristic Urban Rural Total Urban Rural Total Electricity Yes 48.7 3.9 10.8 50.1 4.1 10.7 No 51.3 96.1 89.2 49.9 95.9 89.3 Total 100.0 100.0 100.0 100.0 100.0 100.0 Flooring material Earth, sand 24.7 82.6 73.7 23.7 81.9 73.5 Dung 0.3 0.6 0.6 0.4 0.6 0.6 Ceramic tiles 3.4 0.1 0.6 3.8 0.1 0.6 Cement 71.1 16.6 24.9 71.8 17.2 25.1 Carpet 0.5 0.0 0.1 0.3 0.1 0.1 Total 100.0 100.0 100.0 100.0 100.0 100.0 Rooms used for sleeping One 28.3 37.5 36.1 18.0 28.1 26.6 Two 38.4 38.5 38.5 39.0 40.3 40.1 Three or more 33.3 24.0 25.4 43.1 31.6 33.3 Total 100.0 100.0 100.0 100.0 100.0 100.0 Place for cooking In the house 27.8 4.8 8.3 25.9 4.0 7.2 In a separate building 22.7 67.3 60.4 26.0 70.6 64.1 Outdoors 49.4 27.7 31.0 48.1 25.3 28.6 No food cooked in household 0.2 0.2 0.2 0.0 0.1 0.1 Total 100.0 100.0 100.0 100.0 100.0 100.0 Cooking fuel Electricity 11.9 0.3 2.1 11.3 0.3 1.9 LPG/natural gas/biogas 0.2 0.0 0.1 0.2 0.0 0.1 Coal/lignite 0.1 0.0 0.0 0.1 0.0 0.0 Charcoal 64.4 6.9 15.7 62.5 6.0 14.2 Wood 23.0 91.4 80.9 25.6 92.6 82.8 Straw/shrubs/grass 0.0 1.1 0.9 0.0 0.9 0.8 Agricultural crop 0.1 0.1 0.1 0.1 0.1 0.1 No food cooked in household 0.2 0.2 0.2 0.0 0.1 0.1 Total 100.0 100.0 100.0 100.0 100.0 100.0 Percentage using solid fuel for cooking1 87.7 99.4 97.6 88.4 99.6 98.0 Frequency of smoking in the home Daily 8.0 12.8 12.1 7.9 13.4 12.6 Weekly 3.0 3.8 3.7 3.2 4.0 3.8 Monthly 0.3 0.6 0.5 0.3 0.6 0.5 Less than once a month 0.6 0.5 0.5 0.7 0.5 0.5 Never 88.1 82.3 83.2 87.9 81.6 82.5 Total 100.0 100.0 100.0 100.0 100.0 100.0 Number of households/population 4,042 22,319 26,361 17,230 101,536 118,766 LPG = Liquefied petroleum gas. 1 Includes coal/lignite, charcoal, wood, straw/shrubs/grass, agricultural crops, and animal dung. Housing Characteristics and Household Population • 21 Table 2.5 Wealth quintiles Percent distribution of the de jure population by wealth quintiles, and the Gini coefficient, according to residence and region, Malawi DHS 2015-16 Residence/ region Wealth quintile Total Number of persons Gini coefficient Lowest Second Middle Fourth Highest Residence Urban 2.0 2.0 4.8 16.1 75.0 100.0 17,230 0.22 Rural 23.1 23.0 22.6 20.7 10.7 100.0 101,536 0.37 Region Northern 11.7 15.1 18.5 26.3 28.3 100.0 14,564 0.41 Central 23.0 22.1 18.8 17.4 18.7 100.0 49,389 0.43 Southern 19.5 19.4 21.5 20.7 19.0 100.0 54,813 0.39 Total 20.0 20.0 20.0 20.0 20.0 100.0 118,766 0.39 Table 2.6 Household possessions Percentage of households possessing various household effects, means of transportation, agricultural land, and livestock/farm animals by residence, Malawi DHS 2015-16 Residence Total Possession Urban Rural Household effects Radio 65.1 36.1 40.6 Television 45.3 5.6 11.7 Mobile phone 86.2 47.8 53.7 Non-mobile telephone 5.6 1.4 2.1 Computer 15.5 1.3 3.5 Refrigerator 26.7 2.3 6.0 Means of transport Bicycle 29.6 42.3 40.4 Animal drawn cart 1.2 2.3 2.1 Motorcycle/scooter 2.9 2.4 2.5 Car/truck 13.0 1.6 3.3 Boat with a motor 0.7 0.7 0.7 Ownership of agricultural land 36.6 83.3 76.2 Ownership of farm animals1 23.1 52.9 48.3 Number of households 4,042 22,319 26,361 1 Cows, bulls, other cattle, horses, donkeys, goats, sheep, chickens, pigs, or other poultry. 22 • Housing Characteristics and Household Population Table 2.7 Hand washing 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 hand washing was observed; and among households in which the place for hand washing was observed, percent distribution by availability of water, soap and other cleansing agents, according to background characteristics, Malawi DHS 2015-16 Percentage of households in which place for washing hands was observed: Number of households Among households where place for hand washing was observed, percentage with: Number of households in which place for hand washing was observed Background characteristic And place for hand washing was in fixed place And place for hand washing was mobile Total Soap and water1 Water and cleansing agent2 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 29.1 63.4 92.5 4,042 16.9 0.9 24.3 2.0 0.7 55.2 100.0 3,739 Rural 17.8 63.9 81.7 22,319 9.2 1.9 26.8 2.9 1.1 58.2 100.0 18,237 Region Northern 24.7 65.5 90.2 2,960 14.6 0.4 30.5 3.8 0.3 50.5 100.0 2,670 Central 16.6 65.1 81.7 10,952 10.1 1.6 27.3 2.5 1.0 57.4 100.0 8,949 Southern 20.8 62.4 83.2 12,449 9.7 2.1 24.6 2.6 1.1 59.8 100.0 10,358 Wealth quintile Lowest 12.6 64.0 76.6 5,676 4.5 1.8 26.7 1.9 1.4 63.8 100.0 4,347 Second 16.4 65.2 81.6 5,446 7.0 2.3 28.2 2.2 1.1 59.2 100.0 4,446 Middle 17.2 65.4 82.7 5,141 7.8 1.8 25.9 2.4 1.4 60.7 100.0 4,250 Fourth 18.9 65.9 84.9 4,978 11.0 1.8 25.1 3.5 0.7 57.9 100.0 4,225 Highest 33.3 58.7 92.0 5,120 21.4 0.8 26.1 3.5 0.4 47.8 100.0 4,708 Total 19.5 63.9 83.4 26,361 10.5 1.7 26.4 2.7 1.0 57.7 100.0 21,977 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. Table 2.8 Household population by age, sex, and residence Percent distributions of the de facto household population by various age groups and percentage of the de facto household population age 10-19, according to sex and residence, Malawi DHS 2015-16 Urban Rural Total Total Age Male Female Total Male Female Total Male Female <5 13.5 13.2 13.3 15.8 15.0 15.4 15.5 14.7 15.1 5-9 13.9 13.5 13.7 17.8 17.0 17.4 17.2 16.5 16.8 10-14 12.6 13.3 12.9 17.0 16.2 16.6 16.3 15.8 16.0 15-19 11.6 10.8 11.2 11.3 8.7 9.9 11.3 9.0 10.1 20-24 10.6 11.7 11.1 7.6 8.4 8.0 8.0 8.9 8.5 25-29 8.9 10.2 9.6 5.4 6.2 5.8 5.9 6.8 6.4 30-34 7.5 8.7 8.1 4.8 5.7 5.3 5.2 6.1 5.7 35-39 7.2 5.6 6.4 4.7 4.9 4.8 5.0 5.0 5.0 40-44 4.1 3.9 4.0 3.6 3.3 3.4 3.7 3.4 3.5 45-49 2.9 2.2 2.5 2.5 2.4 2.5 2.6 2.4 2.5 50-54 2.2 2.6 2.4 2.1 3.1 2.6 2.1 3.0 2.6 55-59 1.8 1.5 1.6 1.8 2.2 2.0 1.8 2.1 2.0 60-64 1.3 1.0 1.2 1.6 1.9 1.8 1.6 1.8 1.7 65-69 0.9 0.9 0.9 1.5 1.7 1.6 1.4 1.6 1.5 70-74 0.3 0.4 0.4 0.9 1.1 1.0 0.8 1.0 0.9 75-79 0.4 0.3 0.3 0.7 1.0 0.8 0.6 0.9 0.8 80 + 0.3 0.3 0.3 0.9 1.2 1.0 0.8 1.1 0.9 Don’t know/missing 0.1 0.0 0.0 0.1 0.1 0.1 0.1 0.1 0.1 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Dependency age groups 0-14 40.0 40.0 40.0 50.6 48.1 49.3 49.0 47.0 48.0 15-64 58.1 58.2 58.1 45.4 46.7 46.1 47.3 48.4 47.9 65+ 1.8 1.9 1.8 3.9 5.0 4.5 3.6 4.6 4.1 Don’t know/missing 0.1 0.0 0.0 0.1 0.1 0.1 0.1 0.1 0.1 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Child and adult populations 0-17 47.5 46.3 46.9 57.9 53.3 55.5 56.4 52.3 54.3 18+ 52.4 53.7 53.1 41.9 46.6 44.4 43.5 47.6 45.6 Don’t know/missing 0.1 0.0 0.0 0.1 0.1 0.1 0.1 0.1 0.1 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Adolescents 10-19 24.2 24.1 24.1 28.2 24.9 26.5 27.6 24.8 26.1 Number of persons 8,431 8,697 17,128 47,927 52,122 100,049 56,358 60,819 117,177 Housing Characteristics and Household Population • 23 Table 2.9 Household composition Percent distribution of households by sex of head of household and by household size; mean size of households; and percentage of households with orphans and foster children under age 18, according to residence, Malawi DHS 2015-16 Residence Total Characteristic Urban Rural Household headship Male 75.8 68.2 69.4 Female 24.2 31.8 30.6 Total 100.0 100.0 100.0 Number of usual members 0 0.1 0.1 0.1 1 8.7 6.0 6.4 2 10.6 10.8 10.8 3 18.4 17.1 17.3 4 19.7 17.9 18.2 5 17.1 17.4 17.3 6 12.2 13.5 13.3 7 7.3 8.6 8.4 8 3.2 4.7 4.4 9+ 2.8 3.9 3.7 Total 100.0 100.0 100.0 Mean size of households 4.3 4.5 4.5 Percentage of households with orphans and foster children under 18 years of age Double orphans 3.2 3.3 3.3 Single orphans1 12.1 13.5 13.3 Foster children2 25.4 28.4 28.0 Foster and/or orphan children 30.0 33.3 32.8 Number of households 4,042 22,319 26,361 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. 24 • Housing Characteristics and Household Population Table 2.10.1 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, Malawi DHS 2015-16 Percentage of children whose births are registered and who: Total percentage of children whose births are registered Number of children Background characteristic Had a birth certificate Did not have birth certificate Age <2 21.4 49.7 71.2 6,741 2-4 13.6 51.2 64.8 11,042 Sex Male 16.7 50.5 67.2 8,795 Female 16.4 50.8 67.2 8,988 Residence Urban 20.7 54.6 75.3 2,282 Rural 15.9 50.1 66.0 15,502 Region Northern 23.4 51.1 74.5 2,057 Central 17.5 48.9 66.4 7,424 Southern 14.0 52.1 66.1 8,302 Wealth quintile Lowest 14.8 49.9 64.7 4,378 Second 16.0 49.7 65.7 3,949 Middle 15.0 50.4 65.3 3,521 Fourth 18.0 50.4 68.4 3,146 Highest 20.5 53.9 74.4 2,789 Total 16.6 50.7 67.2 17,783 Table 2.10.2 Place of birth registration of children under age 5 Percentage distribution of de jure children under age 5 whose births are registered with the civil authorities by place of registration, and according to residence, Malawi DHS 2015-16 Residence Total Place of registration Urban Rural District commissioner 0.8 0.5 0.6 Hospital 95.7 89.7 90.5 Registrar general 0.2 0.4 0.4 Traditional village chief 2.8 9.3 8.4 Other 0.4 0.1 0.2 Total 100.0 100.0 100.0 Number of children 1,718 10,235 11,953 Housing Characteristics and Household Population • 25 Table 2.11 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, Malawi DHS 2015-16 Living with both parents Living with mother but not with father Living with father but not with mother Not living with either parent Missing informa- tion on father/ mother Total Percent- age not living with a biological parent Percent- age with one or both parents dead1 Number of children Background characteristic Father alive Father dead Mother alive Mother dead Both alive Only father alive Only mother alive Both dead Age 0-4 64.9 24.9 1.9 0.8 0.1 5.9 0.5 0.4 0.2 0.2 100.0 7.1 3.3 17,783 <2 69.6 26.6 1.5 0.5 0.1 1.2 0.3 0.1 0.1 0.1 100.0 1.6 1.9 6,741 2-4 62.1 23.9 2.2 1.0 0.1 8.7 0.7 0.7 0.4 0.3 100.0 10.4 4.1 11,042 5-9 53.4 19.9 4.1 2.5 0.4 14.2 1.6 2.1 1.5 0.4 100.0 19.3 9.7 19,804 10-14 45.6 17.1 6.7 2.8 0.8 17.4 2.6 3.6 2.9 0.4 100.0 26.6 16.7 18,892 15-17 38.6 14.8 8.4 3.3 1.3 19.4 3.4 5.0 5.1 0.6 100.0 32.9 23.5 7,499 Sex Male 53.0 20.1 5.0 2.5 0.7 12.2 1.7 2.4 2.0 0.4 100.0 18.4 11.9 32,013 Female 52.2 19.7 4.6 1.9 0.4 14.6 1.9 2.4 2.0 0.3 100.0 20.9 11.3 31,966 Residence Urban 54.3 17.6 4.3 4.0 0.5 12.1 1.5 2.6 2.4 0.4 100.0 18.7 11.5 8,016 Rural 52.3 20.2 4.9 2.0 0.5 13.6 1.9 2.4 1.9 0.3 100.0 19.8 11.6 55,963 Region Northern 54.5 12.6 4.0 3.6 0.8 18.0 1.2 2.9 1.8 0.6 100.0 23.8 10.8 7,868 Central 57.4 18.6 4.0 2.4 0.6 11.8 1.8 1.9 1.3 0.3 100.0 16.8 9.6 25,817 Southern 48.0 22.9 5.6 1.7 0.5 13.6 2.0 2.8 2.6 0.4 100.0 21.0 13.6 30,294 Wealth quintile Lowest 43.1 29.9 7.2 1.5 0.4 11.4 1.9 2.0 2.4 0.2 100.0 17.8 13.9 13,701 Second 54.1 20.4 5.4 1.7 0.4 11.9 2.0 2.3 1.5 0.4 100.0 17.6 11.6 13,068 Middle 54.5 18.2 4.3 1.9 0.7 14.1 1.8 2.3 1.9 0.3 100.0 20.1 11.1 13,096 Fourth 56.4 15.8 3.8 2.4 0.6 14.3 1.7 2.7 1.9 0.4 100.0 20.6 10.8 12,756 Highest 55.8 13.8 2.8 3.9 0.7 15.8 1.7 2.9 2.2 0.5 100.0 22.6 10.3 11,359 Total <15 54.4 20.6 4.3 2.1 0.4 12.6 1.6 2.1 1.6 0.3 100.0 17.9 10.0 56,480 Total <18 52.6 19.9 4.8 2.2 0.5 13.4 1.8 2.4 2.0 0.4 100.0 19.6 11.6 63,979 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. 26 • 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, Malawi DHS 2015-16 Background characteristic No education Some primary Completed primary1 Some secondary Completed secondary2 More than secondary Don’t know Total Number Median years completed Age 6-9 10.0 90.0 0.0 0.0 0.0 0.0 0.0 100.0 8,159 0.3 10-14 1.5 96.3 0.4 1.7 0.0 0.0 0.0 100.0 9,597 3.0 15-19 2.7 65.4 5.7 23.0 2.6 0.4 0.1 100.0 5,457 5.9 20-24 5.6 49.3 9.8 21.4 9.8 3.9 0.2 100.0 5,391 6.6 25-29 8.5 51.3 9.7 16.5 8.9 5.0 0.1 100.0 4,142 6.0 30-34 10.3 54.8 9.5 13.6 7.9 3.5 0.2 100.0 3,707 5.5 35-39 19.2 54.1 8.6 9.4 5.8 2.8 0.0 100.0 3,040 4.0 40-44 26.3 54.0 6.7 5.8 3.2 3.7 0.3 100.0 2,039 2.5 45-49 33.3 47.5 8.8 5.4 2.2 2.7 0.2 100.0 1,458 2.1 50-54 36.5 48.7 7.9 3.1 1.5 2.3 0.0 100.0 1,838 1.7 55-59 41.0 47.2 6.0 3.2 0.7 1.4 0.5 100.0 1,256 0.7 60-64 43.5 47.4 4.2 2.3 0.7 1.6 0.2 100.0 1,095 0.4 65+ 54.3 40.9 2.0 1.1 0.5 0.6 0.7 100.0 2,772 0.0 Residence Urban 4.6 47.5 7.6 19.2 12.0 8.9 0.2 100.0 7,342 6.7 Rural 15.5 70.5 4.5 7.0 1.8 0.5 0.1 100.0 42,663 2.7 Region Northern 7.0 67.3 9.1 11.1 3.7 1.7 0.2 100.0 6,089 4.6 Central 13.2 68.0 4.4 8.5 3.4 2.4 0.1 100.0 20,667 3.0 Southern 16.3 66.4 4.4 8.5 3.2 1.1 0.1 100.0 23,249 2.9 Wealth quintile Lowest 22.4 71.1 2.9 3.1 0.3 0.0 0.2 100.0 10,000 1.6 Second 17.3 73.2 4.1 4.5 0.8 0.0 0.1 100.0 9,749 2.3 Middle 14.9 72.9 4.6 6.2 1.3 0.1 0.1 100.0 10,015 2.7 Fourth 10.7 69.7 6.2 10.3 2.6 0.4 0.1 100.0 10,032 3.6 Highest 4.4 49.4 7.0 19.5 11.4 8.0 0.2 100.0 10,209 6.5 Total 13.9 67.1 5.0 8.8 3.3 1.7 0.1 100.0 50,005 3.1 Note: Total includes 54 weighted cases with information missing on age. 1 Completed 8th grade at the primary level. 2 Completed 4th grade at the secondary level. Housing Characteristics and Household Population • 27 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, Malawi DHS 2015-16 Background characteristic No education Some primary Completed primary1 Some secondary Completed secondary2 More than secondary Don’t know Total Number Median years completed Age 6-9 11.3 88.6 0.0 0.1 0.0 0.0 0.0 100.0 7,888 0.1 10-14 2.2 96.1 0.2 1.5 0.0 0.0 0.0 100.0 9,185 2.7 15-19 2.3 69.5 3.8 22.1 2.0 0.2 0.1 100.0 6,384 5.6 20-24 4.3 40.5 9.0 26.4 15.1 4.3 0.3 100.0 4,522 7.4 25-29 7.0 38.6 9.1 18.3 19.0 7.6 0.3 100.0 3,330 7.4 30-34 6.8 41.8 10.3 17.9 15.3 7.2 0.6 100.0 2,952 7.1 35-39 8.1 41.2 10.7 17.7 15.3 6.1 0.9 100.0 2,839 7.0 40-44 12.7 45.4 10.5 11.2 12.9 6.9 0.5 100.0 2,059 6.0 45-49 15.0 44.9 16.2 9.7 8.4 4.9 0.8 100.0 1,453 6.1 50-54 15.5 47.3 16.1 8.8 6.4 4.3 1.6 100.0 1,196 5.4 55-59 16.9 45.4 18.5 6.4 6.3 5.5 1.1 100.0 1,035 5.3 60-64 18.8 47.6 15.5 5.5 6.3 4.8 1.5 100.0 897 4.5 65+ 25.9 52.4 9.3 5.4 2.4 2.3 2.2 100.0 2,003 2.5 Residence Urban 3.0 41.9 6.5 19.9 17.0 11.1 0.6 100.0 7,059 7.6 Rural 8.8 69.5 5.9 9.5 4.6 1.2 0.4 100.0 38,749 3.4 Region Northern 3.7 62.7 7.9 14.8 7.5 3.2 0.2 100.0 5,804 5.3 Central 7.9 65.7 5.9 10.2 6.7 3.2 0.4 100.0 19,018 3.8 Southern 9.2 65.6 5.6 10.9 6.0 2.2 0.4 100.0 20,986 3.7 Wealth quintile Lowest 13.8 74.9 4.7 4.7 1.5 0.0 0.3 100.0 8,160 2.1 Second 10.1 72.6 6.2 7.8 2.8 0.1 0.4 100.0 8,779 3.0 Middle 8.1 72.1 6.0 9.7 3.6 0.2 0.4 100.0 9,206 3.4 Fourth 6.2 65.7 6.9 13.1 6.7 1.0 0.4 100.0 9,617 4.4 Highest 2.8 44.4 6.1 18.7 16.2 11.3 0.5 100.0 10,045 7.3 Total 7.9 65.3 6.0 11.1 6.5 2.8 0.4 100.0 45,807 3.9 Note: Total includes 65 weighted cases with information missing on age. 1 Completed 8th grade at the primary level. 2 Completed 4th grade at the secondary level. 28 • Housing Characteristics and Household Population Table 2.13 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, Malawi DHS 2015-16 Net attendance ratio1 Gross attendance ratio2 Background characteristic Male Female Total Gender Parity Index3 Male Female Total Gender Parity Index3 PRIMARY SCHOOL Residence Urban 95.0 94.4 94.7 0.99 129.9 121.0 125.3 0.93 Rural 93.2 94.3 93.8 1.01 131.7 122.7 127.1 0.93 Region Northern 96.4 96.1 96.3 1.00 135.5 122.6 128.8 0.90 Central 93.1 94.7 93.9 1.02 134.5 125.2 129.7 0.93 Southern 92.9 93.6 93.2 1.01 128.1 120.3 124.2 0.94 Wealth quintile Lowest 89.2 91.0 90.1 1.02 120.1 115.7 117.9 0.96 Second 92.6 93.9 93.2 1.01 134.4 123.3 128.7 0.92 Middle 94.7 95.1 94.9 1.00 134.2 125.0 129.5 0.93 Fourth 95.4 96.9 96.2 1.02 135.4 126.3 130.7 0.93 Highest 95.4 94.6 95.0 0.99 134.1 122.1 127.8 0.91 Total 93.4 94.3 93.9 1.01 131.5 122.5 126.9 0.93 SECONDARY SCHOOL Residence Urban 41.3 40.5 40.9 0.98 87.5 79.4 83.7 0.91 Rural 13.1 13.5 13.3 1.03 31.6 25.0 28.7 0.79 Region Northern 20.4 21.6 20.9 1.06 52.5 38.9 46.5 0.74 Central 14.0 15.0 14.5 1.07 32.9 28.7 31.0 0.87 Southern 19.1 19.2 19.1 1.01 42.3 36.3 39.6 0.86 Wealth quintile Lowest 3.7 5.3 4.4 1.44 12.5 10.7 11.7 0.86 Second 6.1 5.3 5.7 0.88 21.6 10.5 16.5 0.48 Middle 10.8 10.4 10.6 0.96 30.4 18.7 25.1 0.62 Fourth 18.0 19.7 18.7 1.10 40.5 36.8 38.9 0.91 Highest 40.3 41.9 41.0 1.04 80.8 79.3 80.1 0.98 Total 17.1 17.7 17.4 1.03 39.7 33.4 36.9 0.84 1 The NAR for primary school is the percentage of the primary-school age (age 6-13) population that is attending primary school. The NAR for secondary school is the percentage of the secondary-school age (age 14-17) population that is attending secondary school. By definition, the NAR cannot exceed 100%. 2 The GAR for primary school is the total number of primary school students, expressed as a percentage of the official primary- school-age population. The GAR for secondary school is the total number of secondary school students, expressed as a percentage of the official secondary-school-age population. If there are significant numbers of overage and underage students at a given level of schooling, the GAR can exceed 100%. 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. Housing Characteristics and Household Population • 29 Table 2.14.1 Child functioning and disability: Children age 2-9 Percentage of children age 2-9 with reported specific functioning problems or disability, according to selected background characteristics, Malawi DHS 2015-16 Percentage of children age 2-9 with reported functioning problems or disability: Percentage of children age 2-9 with at least one reported functioning problem or disability Number of children age 2-9 Children age 3-9 Children age 2 Background characteristic Delay in sitting, standing or walking Difficulty seeing, either in the daytime or at night Appear to have difficulty hearing Not understand ing of instructions Difficulty walking moving arms, weakness or stiffness Have fits, become rigid, lose consciousn ess Not learning to do things like other children their age Not speaking/ cannot be understood in words Appear mentally backward, dull or slow Percentage with speech different from normal Number of children age 3-9 Percentage who cannot name at least one object Number of children age 2 Age 2-4 4.5 2.3 3.1 7.9 2.2 4.2 5.1 6.2 6.5 26.7 11,042 6.5 7,638 20.6 3,404 5-6 4.2 3.1 5.8 8.6 2.5 4.0 5.3 4.3 7.0 28.1 7,879 5.3 7,879 na na 7-9 4.7 3.2 7.5 9.7 3.3 3.8 5.2 3.9 9.5 30.9 11,925 4.6 11,925 na na Sex Male 4.8 2.9 5.4 8.6 2.9 4.1 5.4 5.2 8.4 29.1 15,163 6.1 13,519 21.1 1,644 Female 4.3 2.8 5.6 8.9 2.6 3.9 4.9 4.5 7.3 28.3 15,683 4.6 13,923 20.1 1,760 Residence Urban 2.7 3.0 3.5 5.1 1.7 1.7 3.0 3.5 4.4 20.1 3,725 4.4 3,284 16.2 441 Rural 4.8 2.8 5.8 9.3 2.8 4.3 5.5 5.0 8.3 29.9 27,121 5.5 24,158 21.2 2,963 Region Northern 3.4 2.8 3.8 5.7 1.7 3.0 3.6 4.1 3.2 21.3 3,842 4.2 3,443 26.3 399 Central 4.5 3.2 5.5 9.8 2.6 5.5 5.9 5.0 8.5 30.5 12,389 4.7 11,020 18.8 1,370 Southern 4.9 2.6 5.9 8.7 3.1 3.1 5.0 4.9 8.4 29.1 14,614 6.2 12,979 20.7 1,635 Wealth quintile Lowest 5.9 3.6 6.5 10.0 3.5 5.7 6.5 5.3 9.6 33.2 6,914 6.8 6,101 22.0 813 Second 5.5 2.6 5.8 9.5 2.9 4.8 5.7 4.8 8.4 30.9 6,590 5.7 5,811 20.7 779 Middle 4.2 2.4 5.8 9.2 3.0 4.2 5.4 5.3 8.8 29.5 6,264 4.6 5,603 21.1 661 Fourth 3.8 2.6 5.7 8.0 2.1 3.1 4.4 4.6 6.7 26.8 5,953 5.0 5,335 21.0 618 Highest 2.6 3.0 3.0 6.6 1.7 1.7 3.3 4.0 4.7 20.9 5,125 4.2 4,592 17.1 533 Total 4.5 2.9 5.5 8.8 2.7 4.0 5.2 4.8 7.8 28.7 30,846 5.3 27,442 20.6 3,404 Note: Table is based on de jure members, i.e., usual residents. na: Not applicable. 30 • Housing Characteristics and Household Population Table 2.14.2 Child functioning and disability: Children age 10-17 Percentage of children age 10-17 with reported specific functioning problems or disability, according to selected background characteristics, Malawi DHS 2015-16 Percentage with difficulty seeing Percentage with difficulty hearing Percentage with difficulty communicating using usual language Percentage with difficulty remembering/ concentrating Percentage with difficulty walking/ climbing steps Percentage with difficulty washing all over/dressing Number of children age 10-17 Background characteristic Some difficulty A lot of difficulty/ can’t see at all Some difficulty A lot of difficulty/ can’t hear at all Some difficulty A lot of difficulty/ can’t communica te at all Some difficulty A lot of difficulty/ can’t remember/ concentrat e at all Some difficulty A lot of difficulty/ can’t walk/ climb steps at all Some difficulty A lot of difficulty/ can’t wash/ dress at all Age 10-12 1.6 0.6 3.2 1.2 1.5 0.6 4.1 1.2 0.8 0.3 1.7 0.4 12,334 13-15 2.4 0.7 3.6 1.3 1.7 0.7 3.8 1.7 0.8 0.6 1.1 0.4 6,559 16-17 2.0 0.6 3.9 0.9 1.4 0.6 4.7 1.5 1.0 0.3 0.6 0.5 7,499 Sex Male 1.7 0.6 3.4 1.3 1.6 0.7 3.9 1.5 0.8 0.3 1.4 0.5 13,457 Female 2.1 0.6 3.7 1.0 1.4 0.5 4.4 1.4 1.0 0.4 1.0 0.4 12,935 Residence Urban 2.6 0.8 3.0 1.0 1.1 0.4 4.2 1.0 0.3 0.3 0.5 0.2 3,384 Rural 1.8 0.6 3.6 1.1 1.6 0.6 4.2 1.5 1.0 0.4 1.3 0.5 23,008 Region Northern 2.0 0.6 3.1 0.9 1.2 0.5 2.3 0.9 1.0 0.5 1.4 0.6 3,245 Central 1.9 0.5 3.5 0.9 1.5 0.6 4.7 1.4 1.0 0.3 1.0 0.3 10,558 Southern 1.9 0.7 3.7 1.4 1.6 0.7 4.3 1.6 0.8 0.4 1.4 0.5 12,589 Wealth quintile Lowest 1.6 0.6 3.6 1.3 1.8 0.8 3.6 1.4 1.0 0.5 1.3 0.5 5,046 Second 1.9 0.4 4.0 1.6 2.1 0.7 4.4 1.5 1.2 0.3 1.7 0.6 4,941 Middle 1.8 0.6 3.5 1.0 1.2 0.5 4.4 1.7 0.8 0.5 1.4 0.4 5,515 Fourth 2.0 0.5 3.4 1.2 1.5 0.7 4.3 1.3 0.9 0.3 1.1 0.4 5,687 Highest 2.3 0.8 3.2 0.6 1.1 0.4 4.1 1.1 0.5 0.2 0.8 0.3 5,203 Total 1.9 0.6 3.5 1.1 1.5 0.6 4.2 1.4 0.9 0.4 1.2 0.4 26,392 Note: Table is based on de jure members, i.e., usual residents. Characteristics of Respondents • 31 CHARACTERISTICS OF RESPONDENTS 3 Key Findings  Education: About 1 in 4 women (26%) and 36% of men have at least some secondary education. Only 3% of women and 5% of men have more than secondary education.  Literacy: Seventy-two percent of women and 83% of men are literate.  Exposure to mass media: Sixty-three percent of women and 43% of men do not read a newspaper, listen to the radio, or watch television at least once a week.  Internet usage: In the past 12 months, 6% of women and 18% of men used the Internet. Among those who used the Internet in past 12 months, 58% of women and 48% of men used it nearly every day.  Employment: Men are more likely to be employed than women; 63% of women are currently employed, as compared with 81% of men.  Tobacco use: Fewer than 1% of women and 12% of men age 15-49 use tobacco products. 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 the use of reproductive health services and contraception, and other health behaviours. 3.1 BASIC CHARACTERISTICS OF SURVEY RESPONDENTS A total of 24,562 women age 15-49 and 7,478 men age 15-54 were interviewed in the 2015-16 MDHS. Forty-two percent of women and 45% of men are in the 15-24 age group, while 31% of women and 27% of men are in the 25-34 age group (Table 3.1). Among respondents age 15-49, women are more likely than men to be married (62% versus 53%), divorced/separated (10% versus 3%), or widowed (3% versus <1%). There were no differences in the percentage of women and men who were living together (4% each). The distribution of respondents by religion shows that a majority of the respondents are Christians, while 13% of women and 11% of men are Muslims. Fewer than 1% of women and 3% of men reported no religious affiliation. Eight in ten women (82%) and men (81%) live in rural areas. By region, the majority of women and men live in the Central and Southern regions, while 12% of women and 13% of men live in the Northern region. T 32 • Characteristics of Respondents 3.2 EDUCATION AND LITERACY Literacy Respondents who have attended higher than secondary school are assumed to be literate. All other respondents were given a sentence to read, and were considered literate if they could read all or part of the sentence. Sample: Women and men age 15-49 About one in four (26%) women and one in three men (36%) age 15-49 have at least some secondary education (Tables 3.2.1 and 3.2.2). Twelve percent of women and 5% of men have no education. Advanced education is relatively rare; only 3% of women and 5% of men have more than secondary education (Figure 3.1). Seventy-two percent of women and 83% of men are literate (Tables 3.3.1 and 3.3.2). Trends: Since 1992, the median number of years of schooling completed by women and men age 15-49 has increased substantially, and the gap between them has narrowed. The median number of years of schooling completed in 1992 was 0.4 years for women and 4.3 years for men compared with 5.6 years for women and 6.6 years for men in 2015-16. Patterns by background characteristics  Younger respondents are more likely to have attended school and to have reached higher levels of education than the older respondents. Only 3% of women age 15-19 and 6% of women age 20-24 have no education while 30% of women age 40-44 and 36% of women age 45-49 have no education (Table 3.2.1).  Urban women are more educated than their rural counterparts. Fourteen percent of rural women have never attended school compared with 3% of urban women. In rural areas, only 1% of women have attended more than secondary school compared with 12% in urban areas.  The Northern region has the lowest percentage of women and men with no education; 4% of women and 1% of men in the Northern region have no education compared with 12% of women and 6% of men who live in the Central region and 14% of women and 6% of men in the Southern region.  The percentage of women and men who have completed secondary school or higher increases by wealth quintile; less than 1% of women and 3% of men in the lowest wealth quintile completed secondary school or higher compared with 31% of women and 41% of men in the highest wealth quintile (Figure 3.2). Figure 3.1 Education of survey respondents Figure 3.2 Secondary education by household wealth 12 5 54 50 8 9 16 20 7 12 3 5 Women Men Percent distribution of women and men age 15-49 by highest level of schooling attended or completed More than secondary Completed secondary Some secondary Primary complete Primary incomplete No education 1 2 3 6 31 3 5 7 16 41 Lowest Second Middle Fourth Highest Women Men WealthiestPoorest Percentage of women and men age 15-49 with secondary education complete or higher Characteristics of Respondents • 33  Women and men living in urban areas are more likely to be literate than those living in rural areas. Ninety percent of urban women and 96% of urban men are literate compared with 68% of rural women and 80% of rural men.  The literacy rate increases with wealth, and rises from 53% of women in the lowest wealth quintile to 91% in the highest, and from 66% of men in the lowest wealth quintile to 95% in the highest. 3.3 MASS MEDIA EXPOSURE AND INTERNET USAGE 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 to be 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 programmes and the dissemination of all types of information, particularly information about family planning, HIV/AIDS awareness, and other important health topics. Men are more likely than women to be exposed to any and all forms of media, including newspapers, television, and radio (Figure 3.3). Radio is the most common form of media exposure for both women and men across nearly all subgroups. Large proportions of women and men do not access to any of the three media on a weekly basis (63% of women and 43% of men) (Tables 3.4.1 and 3.4.2). The Internet is also a critical tool through which information is shared. Internet use includes accessing web pages, email, and social media. Overall, 6% of women and 18% of men age 15-49 have used the Internet in the past 12 months (Tables 3.5.1 and 3.5.2). Among those who have used the Internet in the past 12 months, women are more likely than men to have used it on a daily basis; 58% of women report that they have used it nearly every day in the past month, compared with 48% of men. Trends: Exposure to the three mass media for both women and men has decreased between 2000 and 2015-16. The percentage of women who did not access any of the media types at least once a week decreased from 46% in 2000 to 31% in 2004 before going up from 38% in 2010 to 63% in 2015-16. In 2000, 26% of men did not access any of the media types at least once a week, compared with 43% in 2015- 16. Patterns by background characteristics  Rural women are more likely to have no regular exposure to any form of mass media than their urban counterparts (69% versus 38%). The same pattern holds true for men (47% versus 26%) (Tables 3.4.1 and 3.4.2).  Women and men in the Southern region are the most likely to report no regular exposure to any of the three mass media (66% and 49%, respectively). Figure 3.3 Exposure to mass media 8 12 30 2 63 15 18 49 6 43 Reads newspaper Watches television Listens to radio All three media None of these media Percentage of women and men age 15-49 who are exposed to media on a weekly basis Women Men 34 • Characteristics of Respondents  Only 17% of women and 13% of men with more than a secondary education lack regular exposure to any mass media compared with 81% of women and 61% 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, 21% of women and 45% of men have used the Internet in the past 12 months compared with 2% of women and 11% of men in the rural areas.  Internet use rises sharply with increasing education and wealth. The use of the Internet in the past 12 months was non-existent among of women with no education while 76% of women with more than secondary education have used the Internet in the past 12 months. Similarly, less than 1% of women in the lowest wealth quintile have used the Internet in the past 12 months compared with 21% 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; 63% of women age 15-49 are currently employed compared with 81% of men age 15-49 (Tables 3.6.1 and 3.6.2). An additional 5% of women and 5% of men reported working in the past 12 months although they were not currently employed. Trends: Since 2010, current employment levels have remained stable or slightly increased. Fifty-six percent of women were currently employed in 2010 compared with 63% in 2015-16. Among men, the percentage of currently employed remained essentially unchanged (82% in 2010 and 81% in 2015-16). Patterns by background characteristics  Currently married or divorced, separated, or widowed women and men are more likely to be employed compared with those who have never married.  A greater percentage of rural women and men are currently employed than their urban counterparts (Figure 3.4).  Women and men in the highest wealth quintiles are less likely to be currently employed than those in the lower wealth quintiles. 3.5 OCCUPATION Occupation Categorised 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 Figure 3.4 Employment status by residence 63 54 65 81 73 83 Total Urban Rural Percentage of women and men age 15-49 who are currently employed Women Men Characteristics of Respondents • 35 Women and men are most commonly employed in agriculture (59% and 44%, respectively), followed by unskilled manual labour (20% and 25%, respectively) (Tables 3.7.1 and 3.7.2, Figure 3.5). Women are much less likely to be employed in skilled manual labour than men (2% versus 14%), but are equally likely to be employed in professional, technical, or managerial occupations (7% each). Women who did agriculture work in past year were less likely to receive any payment for their work than those who did non-agriculture work (73% versus 36%). More than 6 in 10 women (64%) who worked in past year were self-employed (Table 3.8). Patterns by background characteristics  Urban women are most likely to be employed in sales and services (26%) and in the professional, technical or managerial sector (26%), while urban men are most likely to be employed in skilled manual sector (31%). In rural areas, however, the majority of women and men work in agriculture (68% and 52%, respectively).  Women and men with more than secondary education are equally likely to work in professional, technical, and managerial occupations (67% each). Women and men with no primary or secondary education most often work in agriculture. 3.6 HEALTH INSURANCE COVERAGE Ninety-nine percent of women and 98% of men age 15-49 do not have health insurance coverage (Tables 3.9.1 and 3.9.2). Coverage is extremely low across all background characteristics except those with more than secondary education; 25% of women and 28% of men with more than secondary school have some form of insurance. 3.7 TOBACCO USE Tobacco use is rare among women age 15-49 with fewer than 1% reporting that they currently smoke cigarettes (Table 3.10.1). Among men age 15-49, 12% currently smoke tobacco including 8% of men who smoke on a daily basis (Table 3.10.2). Among men who smoke cigarettes daily, three-quarters (74%) smoke between 1 and 9 cigarettes each day; and 5% of daily cigarette smokers who smoke 25 or more cigarettes each day (Table 3.11). Fewer than 1% of women and men use smokeless tobacco products (Table 3.12). Trends: The percentage of men age 15-49 who do not smoke tobacco has increased from 77% in 2000 to 87% in 2015-16. Patterns by background characteristics  Tobacco smoking rises sharply with age among men, from a low of 2% among those age 15-19 to a high of 25% among those age 40-44.  Tobacco use declines markedly by education level; only 6% of men with more than secondary education smoke compared with 28% of men with no education. Figure 3.5 Occupation 7 2 6 14 25 2 44 7 2 8 2 20 3 59 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 Men Women 36 • Characteristics of Respondents  Only 8% of men from the highest wealth quintile are smokers compared with 20% from the lowest. 3.8 KNOWLEDGE AND ATTITUDES REGARDING TUBERCULOSIS Tables 3.13.1 and 3.13.2 present information on knowledge and attitudes about tuberculosis (TB) among women and men age 15-49. Ninety-four percent of women and 97% of men have heard of TB. Among women and men who report having heard of TB:  68% of women and 77% of men reported that TB is spread through the air by coughing or sneezing  75% of women and 81% of men believe that TB can be cured  34% of women and 27% of men would want a family member’s TB status kept secret Patterns by background characteristics  Women and men in rural areas (66% and 75%, respectively) are less likely to have correctly reported that TB is spread through the air by coughing or sneezing than women and men in urban areas (80% and 88%, respectively).  The percentage of women and men who correctly reported that TB is spread through the air by coughing or sneezing increases with education; from 61% of women and 67% of men with no education to 97% of women and 98% of men with more than secondary education.  The percentage of women and men who correctly reported that TB is spread through the air by coughing or sneezing increases with the level of wealth quintile; from 60% of women and 68% of men in the lowest wealth quintile to 80% of women and 85% of men in the highest wealth quintile. 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 Health insurance coverage: Women  Table 3.9.2 Health insurance coverage: Men  Table 3.10.1 Tobacco smoking: Women  Table 3.10.2 Tobacco smoking: Men  Table 3.11 Average number of cigarettes smoked daily: Men  Table 3.12 Smokeless tobacco use  Table 3.13.1 Knowledge and attitude concerning tuberculosis: Women  Table 3.13.2 Knowledge and attitude concerning tuberculosis: Men Characteristics of Respondents • 37 Table 3.1 Background characteristics of respondents Percent distribution of women and men age 15-49 by selected background characteristics, Malawi DHS 2015-16 Background characteristic Women Men Weighted percent Weighted number Unweighted number Weighted percent Weighted number Unweighted number Age 15-19 21.4 5,263 5,273 25.5 1,818 1,846 20-24 21.0 5,159 5,094 19.8 1,408 1,380 25-29 16.1 3,953 3,976 14.3 1,022 1,030 30-34 14.9 3,668 3,648 13.0 925 945 35-39 11.9 2,924 2,988 12.4 882 866 40-44 8.3 2,029 2,022 8.7 624 619 45-49 6.4 1,567 1,561 6.3 450 452 Religion Anglican 2.6 639 1,258 2.5 179 373 Catholic 18.1 4,442 4,320 19.4 1,384 1,321 CCAP1 17.4 4,268 3,878 18.9 1,345 1,205 Muslim 12.5 3,069 2,726 10.7 766 685 Seventh Day Adventist/ Baptist 6.9 1,704 1,839 6.8 488 520 Other Christian 41.9 10,281 10,390 38.6 2,751 2,853 No religion 0.5 123 113 2.9 208 171 Other 0.1 36 38 0.1 7 10 Ethnic group Chewa 34.7 8,529 7,317 36.3 2,585 2,223 Lomwe 19.1 4,692 4,453 18.3 1,302 1,257 Mang’anja 2.5 621 569 2.5 175 174 Ngoni 11.8 2,895 3,085 12.9 920 918 Nkhonde 0.8 207 335 1.1 77 118 Nyanja 1.1 264 547 0.7 51 125 Sena 3.6 889 1,153 3.3 233 305 Tonga 1.8 446 942 1.6 115 273 Tombuka 9.4 2,298 2,612 9.4 668 783 Yao 13.4 3,289 2,782 12.2 870 732 Other 1.8 433 767 1.8 132 230 Marital status Never married 21.0 5,170 5,326 40.2 2,863 2,929 Married 61.7 15,149 14,912 52.5 3,742 3,734 Living together 4.0 981 1,040 4.0 288 238 Divorced/separated 10.4 2,558 2,542 2.9 206 210 Widowed 2.9 704 742 0.4 29 27 Residence Urban 18.3 4,496 5,247 18.8 1,340 1,602 Rural 81.7 20,066 19,315 81.2 5,788 5,536 Region Northern 11.6 2,838 4,803 12.9 922 1,508 Central 42.9 10,529 8,417 44.6 3,176 2,548 Southern 45.6 11,194 11,342 42.5 3,030 3,082 Education No education 12.1 2,977 2,779 5.3 375 339 Primary 62.1 15,245 15,028 58.3 4,153 4,034 Secondary 22.8 5,598 6,061 31.5 2,249 2,432 More than secondary 3.0 742 694 4.9 351 333 Wealth quintile Lowest 19.3 4,745 4,279 15.9 1,134 992 Second 19.1 4,692 4,429 18.6 1,325 1,266 Middle 18.9 4,635 4,508 19.8 1,409 1,373 Fourth 19.1 4,680 4,897 20.5 1,462 1,494 Highest 23.7 5,810 6,449 25.2 1,798 2,013 Total 15-49 100.0 24,562 24,562 100.0 7,128 7,138 50-54 na na na na 350 340 Total 15-54 na na na na 7,478 7,478 Note: Education categories refer to the highest level of education attended, whether or not that level was completed. na = Not applicable. 1 Church of Central Africa Presbyterian. 38 • 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, Malawi DHS 2015-16 Highest level of schooling Total Median years completed Number of women Background characteristic No education Some primary Completed primary1 Some secondary Completed secondary2 More than secondary Age 15-24 4.4 56.9 7.7 22.2 6.5 2.2 100.0 6.2 10,422 15-19 2.6 64.1 6.3 23.5 3.1 0.4 100.0 6.0 5,263 20-24 6.2 49.6 9.3 20.9 10.0 4.1 100.0 6.5 5,159 25-29 8.9 49.6 9.7 17.4 9.4 5.0 100.0 6.2 3,953 30-34 11.4 54.3 9.2 14.3 7.6 3.3 100.0 5.5 3,668 35-39 20.2 53.1 8.3 9.7 5.8 2.8 100.0 4.0 2,924 40-44 29.5 51.7 6.5 5.5 3.4 3.4 100.0 2.5 2,029 45-49 35.9 46.5 8.1 5.2 1.9 2.5 100.0 1.8 1,567 Residence Urban 3.4 27.4 9.8 28.3 18.9 12.3 100.0 9.1 4,496 Rural 14.1 59.7 7.9 13.6 3.7 0.9 100.0 5.0 20,066 Region Northern 4.0 49.5 15.0 20.8 7.3 3.4 100.0 6.8 2,838 Central 12.2 54.8 7.1 15.2 6.4 4.2 100.0 5.3 10,529 Southern 14.1 53.9 7.6 16.2 6.3 1.8 100.0 5.4 11,194 Wealth quintile Lowest 21.6 66.3 5.4 6.2 0.5 0.0 100.0 3.4 4,745 Second 15.6 66.2 7.8 8.7 1.6 0.1 100.0 4.3 4,692 Middle 12.5 63.6 8.4 12.7 2.6 0.2 100.0 5.0 4,635 Fourth 9.7 52.7 10.7 20.5 5.6 0.8 100.0 6.1 4,680 Highest 3.3 26.6 8.9 30.2 19.0 12.0 100.0 9.1 5,810 Total 12.1 53.8 8.3 16.3 6.5 3.0 100.0 5.6 24,562 1 Completed 8th grade at the primary level. 2 Completed 4th grade at the secondary level. 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, Malawi DHS 2015-16 Highest level of schooling Total Median years completed Number of men Background characteristic No education Some primary Completed primary1 Some secondary Completed secondary2 More than secondary Age 15-24 2.2 57.2 5.5 23.8 9.2 2.1 100.0 6.4 3,226 15-19 1.3 69.5 3.8 22.2 2.9 0.3 100.0 5.8 1,818 20-24 3.3 41.3 7.7 26.0 17.4 4.4 100.0 7.5 1,408 25-29 6.3 39.8 8.8 18.4 18.0 8.6 100.0 7.4 1,022 30-34 5.0 44.4 11.4 17.7 12.7 8.8 100.0 7.1 925 35-39 6.4 40.2 11.7 21.1 15.1 5.5 100.0 7.3 882 40-44 13.4 47.9 8.2 13.6 9.8 7.1 100.0 5.7 624 45-49 12.0 49.1 20.0 7.5 6.6 4.8 100.0 6.1 450 Residence Urban 2.1 21.2 6.8 29.5 22.9 17.6 100.0 9.9 1,340 Rural 6.0 56.2 9.1 17.8 8.9 2.0 100.0 6.1 5,788 Region Northern 0.9 44.4 11.2 26.6 12.4 4.6 100.0 7.3 922 Central 5.5 51.4 7.5 17.2 12.1 6.3 100.0 6.3 3,176 Southern 6.4 49.3 9.1 20.9 10.7 3.6 100.0 6.5 3,030 Wealth quintile Lowest 11.2 68.0 9.1 8.4 3.3 0.0 100.0 4.4 1,134 Second 7.0 62.4 9.6 16.1 4.7 0.2 100.0 5.4 1,325 Middle 5.0 60.4 10.2 17.5 6.7 0.2 100.0 6.1 1,409 Fourth 4.0 46.4 10.5 23.2 13.9 2.0 100.0 7.0 1,462 Highest 1.5 22.7 4.9 29.5 23.7 17.7 100.0 9.9 1,798 Total 15-49 5.3 49.6 8.7 20.0 11.5 4.9 100.0 6.6 7,128 50-54 20.9 48.7 14.2 6.6 3.5 6.1 100.0 4.5 350 Total 15-54 6.0 49.6 8.9 19.4 11.2 5.0 100.0 6.5 7,478 1 Completed 8th grade at the primary level. 2 Completed 4th grade at the secondary level. Characteristics of Respondents • 39 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, Malawi DHS 2015-16 Higher than secondary schooling No schooling, primary or secondary school Total Percentage literate1 Number of women Background characteristic Can read a whole sentence Can read part of a sentence Cannot read at all No card with required language Blind/ visually impaired Age 15-24 2.2 70.2 8.6 18.9 0.0 0.0 100.0 81.1 10,422 15-19 0.4 74.5 9.5 15.5 0.0 0.0 100.0 84.4 5,263 20-24 4.1 65.8 7.8 22.3 0.0 0.0 100.0 77.7 5,159 25-29 5.0 62.2 8.8 23.9 0.0 0.1 100.0 76.0 3,953 30-34 3.3 60.7 8.5 27.4 0.0 0.1 100.0 72.5 3,668 35-39 2.8 52.3 7.6 37.3 0.0 0.0 100.0 62.7 2,924 40-44 3.4 39.2 9.5 47.8 0.1 0.1 100.0 52.0 2,029 45-49 2.5 35.2 7.1 54.7 0.0 0.6 100.0 44.8 1,567 Residence Urban 12.3 72.3 5.8 9.6 0.0 0.1 100.0 90.4 4,496 Rural 0.9 57.9 9.1 31.9 0.0 0.1 100.0 68.0 20,066 Region Northern 3.4 68.5 8.9 18.9 0.1 0.1 100.0 80.8 2,838 Central 4.2 59.2 7.3 29.2 0.0 0.1 100.0 70.8 10,529 Southern 1.8 59.8 9.5 28.8 0.0 0.1 100.0 71.1 11,194 Wealth quintile Lowest 0.0 44.1 9.3 46.5 0.0 0.1 100.0 53.4 4,745 Second 0.1 52.3 10.0 37.5 0.0 0.0 100.0 62.4 4,692 Middle 0.2 60.4 9.7 29.6 0.0 0.1 100.0 70.3 4,635 Fourth 0.8 68.5 9.2 21.4 0.1 0.1 100.0 78.4 4,680 Highest 12.0 74.3 5.1 8.5 0.0 0.1 100.0 91.4 5,810 Total 3.0 60.6 8.5 27.8 0.0 0.1 100.0 72.1 24,562 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 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, Malawi DHS 2015-16 Higher than secondary schooling No schooling, primary or secondary school Total Percentage literate1 Number of men Background characteristic Can read a whole sentence Can read part of a sentence Cannot read at all No card with required language Blind/ visually impaired Age 15-24 2.1 69.6 12.8 15.3 0.0 0.2 100.0 84.6 3,226 15-19 0.3 69.0 14.7 16.1 0.0 0.0 100.0 83.9 1,818 20-24 4.4 70.5 10.4 14.3 0.0 0.3 100.0 85.4 1,408 25-29 8.6 64.6 10.3 16.4 0.1 0.1 100.0 83.4 1,022 30-34 8.8 61.7 11.9 16.8 0.1 0.6 100.0 82.5 925 35-39 5.5 69.4 10.1 15.0 0.0 0.0 100.0 85.0 882 40-44 7.1 58.2 10.9 23.7 0.0 0.0 100.0 76.3 624 45-49 4.8 57.7 14.0 23.1 0.0 0.4 100.0 76.5 450 Residence Urban 17.6 72.9 5.6 3.9 0.0 0.0 100.0 96.1 1,340 Rural 2.0 64.5 13.4 19.8 0.0 0.2 100.0 79.9 5,788 Region Northern 4.6 71.3 12.1 11.3 0.0 0.6 100.0 88.0 922 Central 6.3 63.0 11.2 19.3 0.0 0.2 100.0 80.6 3,176 Southern 3.6 67.7 12.6 16.0 0.1 0.1 100.0 83.9 3,030 Wealth quintile Lowest 0.0 53.6 12.6 33.3 0.0 0.5 100.0 66.2 1,134 Second 0.2 61.5 15.9 22.4 0.0 0.0 100.0 77.5 1,325 Middle 0.2 66.8 14.3 18.3 0.0 0.4 100.0 81.4 1,409 Fourth 2.0 72.4 13.4 12.1 0.0 0.1 100.0 87.8 1,462 Highest 17.7 71.7 5.4 5.1 0.1 0.0 100.0 94.8 1,798 Total 15-49 4.9 66.1 11.9 16.8 0.0 0.2 100.0 82.9 7,128 50-54 6.1 55.7 10.1 27.5 0.1 0.6 100.0 71.9 350 Total 15-54 5.0 65.6 11.8 17.3 0.0 0.2 100.0 82.4 7,478 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, according to background characteristics, Malawi DHS 2015-16 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 9.8 11.5 26.4 2.1 64.7 5,263 20-24 8.9 11.5 31.2 2.2 61.1 5,159 25-29 9.5 14.2 33.0 2.4 57.8 3,953 30-34 7.7 11.1 32.7 2.4 61.5 3,668 35-39 7.0 10.6 29.1 2.4 65.0 2,924 40-44 6.1 9.8 28.5 1.8 66.6 2,029 45-49 4.5 9.5 28.0 1.8 68.7 1,567 Residence Urban 17.1 39.2 42.3 7.2 37.6 4,496 Rural 6.3 5.3 27.2 1.1 68.5 20,066 Region Northern 10.0 16.5 33.2 3.5 58.1 2,838 Central 8.5 10.4 31.7 1.8 60.2 10,529 Southern 7.6 11.3 27.6 2.2 66.4 11,194 Education No education 0.3 2.4 17.4 0.0 81.1 2,977 Primary 5.5 5.5 27.1 0.6 68.1 15,245 Secondary 15.3 26.0 42.2 5.5 44.7 5,598 More than secondary 43.2 61.9 48.0 19.5 17.3 742 Wealth quintile Lowest 3.4 1.0 12.5 0.1 85.0 4,745 Second 4.2 1.7 22.8 0.1 74.1 4,692 Middle 6.0 2.7 26.9 0.4 69.0 4,635 Fourth 7.1 4.4 34.4 0.7 60.5 4,680 Highest 18.2 40.7 49.0 8.2 32.6 5,810 Total 8.3 11.5 30.0 2.2 62.8 24,562 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, according to background characteristics, Malawi DHS 2015-16 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 11.1 17.2 40.2 2.7 50.2 1,818 20-24 17.1 19.6 52.4 6.1 39.3 1,408 25-29 15.7 16.5 52.3 5.3 41.7 1,022 30-34 16.9 18.2 52.0 8.0 42.7 925 35-39 18.1 22.2 56.4 8.9 36.8 882 40-44 12.9 14.7 49.8 5.8 45.1 624 45-49 14.7 14.9 48.9 4.5 43.2 450 Residence Urban 29.6 46.7 57.9 16.7 26.3 1,340 Rural 11.6 11.3 47.3 3.0 47.2 5,788 Region Northern 13.6 22.7 47.7 4.9 43.0 922 Central 17.7 18.2 55.3 6.6 37.8 3,176 Southern 12.5 16.3 43.4 4.8 49.2 3,030 Education No education 0.7 6.7 36.2 0.1 60.8 375 Primary 8.5 10.6 43.7 1.6 50.4 4,153 Secondary 22.5 26.9 58.9 9.7 32.0 2,249 More than secondary 58.0 59.5 67.6 31.9 12.7 351 Wealth quintile Lowest 6.3 5.0 28.9 0.6 66.8 1,134 Second 9.6 5.8 44.4 1.4 51.1 1,325 Middle 9.9 8.9 46.4 1.5 47.4 1,409 Fourth 14.6 12.0 54.4 4.2 39.4 1,462 Highest 28.6 47.0 63.8 16.1 22.8 1,798 Total 15-49 15.0 18.0 49.3 5.6 43.3 7,128 50-54 11.1 12.6 43.9 5.3 51.6 350 Total 15-54 14.8 17.7 49.0 5.6 43.7 7,478 Characteristics of Respondents • 41 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, Malawi DHS 2015-16 Ever used the internet Used the Internet in the past 12 months Number of women Among women who have used the Internet in the past 12 months, percentage who, in the past month, used the Internet: Background characteristic Almost every day At least once a week Less than once a week Not at all Missing Total Number of women Age 15-19 4.7 4.1 5,263 46.5 32.9 16.2 4.4 0.0 100.0 216 20-24 10.1 8.6 5,159 56.9 25.8 9.7 7.6 0.0 100.0 445 25-29 8.3 7.5 3,953 65.7 17.6 10.4 6.4 0.0 100.0 295 30-34 6.1 5.3 3,668 57.3 29.0 10.8 2.8 0.0 100.0 194 35-39 4.1 3.6 2,924 65.3 26.2 7.6 0.8 0.0 100.0 106 40-44 3.6 3.1 2,029 55.5 18.0 22.8 3.6 0.0 100.0 63 45-49 2.4 2.1 1,567 (66.6) (22.5) (9.8) (1.1) (0.0) (100.0) 33 Residence Urban 23.3 21.2 4,496 61.8 23.2 10.4 4.7 0.0 100.0 953 Rural 2.5 2.0 20,066 49.2 30.0 14.1 6.6 0.0 100.0 399 Region Northern 7.5 6.4 2,838 57.7 25.6 12.0 4.8 0.0 100.0 181 Central 7.4 6.7 10,529 61.0 22.4 12.0 4.6 0.0 100.0 707 Southern 5.0 4.1 11,194 53.8 29.2 10.5 6.4 0.0 100.0 464 Education No education 0.0 0.0 2,977 * * * * * * 1 Primary 0.7 0.4 15,245 27.6 17.4 40.1 14.9 0.0 100.0 56 Secondary 15.3 13.0 5,598 47.5 32.1 13.3 7.1 0.0 100.0 729 More than secondary 79.5 76.2 742 74.8 17.0 6.3 1.9 0.0 100.0 565 Wealth quintile Lowest 0.3 0.2 4,745 * * * * * * 10 Second 0.4 0.3 4,692 * * * * * * 12 Middle 0.8 0.5 4,635 (39.0) (25.6) (31.0) (4.4) (0.0) (100.0) 24 Fourth 2.5 1.8 4,680 37.2 33.8 18.7 10.3 0.0 100.0 84 Highest 23.4 21.0 5,810 60.4 24.3 10.5 4.8 0.0 100.0 1,222 Total 6.3 5.5 24,562 58.1 25.2 11.5 5.3 0.0 100.0 1,352 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. 42 • Characteristics of Respondents Table 3.5.2 Internet usage: Men Percentage of men age 15-49 who have ever used the Internet, 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, Malawi DHS 2015-16 Ever used the internet Used the Internet in the past 12 months Number of men Among men who have used the Internet in the past 12 months, percentage who, in the past month, used the Internet: Background characteristic Almost every day At least once a week Less than once a week Not at all Missing Total Number of men Age 15-19 15.6 14.2 1,818 42.5 31.6 16.9 9.0 0.0 100.0 258 20-24 28.6 25.2 1,408 44.4 28.6 17.0 10.0 0.0 100.0 355 25-29 24.2 21.8 1,022 47.6 28.6 9.4 14.4 0.0 100.0 222 30-34 19.5 18.1 925 55.1 19.3 14.5 11.1 0.0 100.0 168 35-39 16.8 14.8 882 54.2 25.5 9.0 11.3 0.0 100.0 130 40-44 13.3 11.9 624 54.7 27.4 9.9 8.0 0.0 100.0 74 45-49 9.3 8.3 450 (56.1) (23.8) (2.1) (18.0) (0.0) (100.0) 37 Residence Urban 48.4 45.2 1,340 59.0 21.9 10.3 8.8 0.0 100.0 606 Rural 12.7 11.0 5,788 37.6 32.7 16.6 13.1 0.0 100.0 639 Region Northern 25.2 23.0 922 45.1 37.1 9.8 8.0 0.0 100.0 212 Central 18.9 17.0 3,176 53.1 21.4 13.1 12.4 0.0 100.0 541 Southern 18.2 16.2 3,030 43.8 29.9 15.8 10.6 0.0 100.0 492 Education No education 0.9 0.6 375 * * * * * * 2 Primary 5.3 4.1 4,153 34.0 31.3 15.3 19.5 0.0 100.0 171 Secondary 38.2 34.4 2,249 39.6 32.0 16.0 12.4 0.0 100.0 774 More than secondary 87.1 84.6 351 78.4 12.9 6.3 2.5 0.0 100.0 297 Wealth quintile Lowest 2.7 1.9 1,134 * * * * * * 22 Second 4.9 3.8 1,325 16.3 36.8 23.2 23.7 0.0 100.0 51 Middle 10.0 8.5 1,409 35.8 35.3 14.0 14.9 0.0 100.0 120 Fourth 17.5 14.2 1,462 27.7 35.7 22.2 14.5 0.0 100.0 207 Highest 49.7 47.0 1,798 57.6 23.7 10.5 8.2 0.0 100.0 846 Total 15-49 19.5 17.5 7,128 48.0 27.4 13.6 11.0 0.0 100.0 1,245 50-54 6.9 5.4 350 * * * * * * 19 Total 15-54 18.9 16.9 7,478 48.3 27.2 13.5 11.0 0.0 100.0 1,264 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. Characteristics of Respondents • 43 Table 3.6.1 Employment status: Women Percent distribution of women age 15-49 by employment status, according to background characteristics, Malawi DHS 2015-16 Employed in the 12 months preceding the survey Not employed in the 12 months preceding the survey Total Number of women Background characteristic Currently employed1 Not currently employed Age 15-19 40.0 4.5 55.5 100.0 5,263 20-24 58.9 5.2 35.8 100.0 5,159 25-29 66.9 5.2 27.9 100.0 3,953 30-34 72.3 4.3 23.4 100.0 3,668 35-39 75.6 4.2 20.2 100.0 2,924 40-44 75.5 4.2 20.3 100.0 2,029 45-49 76.2 2.0 21.9 100.0 1,567 Marital status Never married 38.7 4.2 57.1 100.0 5,170 Married or living together 67.3 4.7 28.0 100.0 16,130 Divorced/separated/ widowed 77.2 4.3 18.5 100.0 3,262 Number of living children 0 42.2 4.9 53.0 100.0 5,739 1-2 63.8 4.9 31.4 100.0 7,834 3-4 71.2 4.5 24.3 100.0 6,344 5+ 74.1 3.4 22.4 100.0 4,644 Residence Urban 53.5 5.4 41.2 100.0 4,496 Rural 64.6 4.3 31.0 100.0 20,066 Region Northern 52.7 4.4 42.9 100.0 2,838 Central 71.8 5.0 23.2 100.0 10,529 Southern 56.5 4.1 39.4 100.0 11,194 Education No education 68.6 4.1 27.3 100.0 2,977 Primary 63.5 4.4 32.1 100.0 15,245 Secondary 55.2 5.1 39.7 100.0 5,598 More than secondary 76.1 4.7 19.2 100.0 742 Wealth quintile Lowest 67.9 4.3 27.8 100.0 4,745 Second 66.2 4.4 29.4 100.0 4,692 Middle 65.2 4.4 30.4 100.0 4,635 Fourth 60.5 4.6 34.9 100.0 4,680 Highest 55.0 4.8 40.3 100.0 5,810 Total 62.6 4.5 32.9 100.0 24,562 1 “Currently employed” is defined as having done work in the past 7 days. Includes persons who did not work in the past 7 days but who are regularly employed and were absent from work for leave, illness, vacation, or any other such reason. 44 • Characteristics of Respondents Table 3.6.2 Employment status: Men Percent distribution of men age 15-49 by employment status, according to background characteristics, Malawi DHS 2015- 16 Employed in the 12 months preceding the survey Not employed in the 12 months preceding the survey Total Number of men Background characteristic Currently employed1 Not currently employed Age 15-19 55.9 6.7 37.4 100.0 1,818 20-24 79.8 5.3 14.9 100.0 1,408 25-29 92.6 3.7 3.7 100.0 1,022 30-34 94.3 3.0 2.7 100.0 925 35-39 94.5 3.5 2.0 100.0 882 40-44 92.8 5.0 2.1 100.0 624 45-49 92.1 5.8 2.1 100.0 450 Marital status Never married 61.7 6.6 31.7 100.0 2,863 Married or living together 94.3 3.7 2.0 100.0 4,030 Divorced/separated/ widowed 91.9 5.0 3.0 100.0 235 Number of living children 0 64.7 6.1 29.2 100.0 3,107 1-2 93.7 3.9 2.4 100.0 1,567 3-4 94.1 3.3 2.6 100.0 1,325 5+ 93.6 5.0 1.5 100.0 1,129 Residence Urban 72.8 4.5 22.8 100.0 1,340 Rural 83.1 5.0 11.9 100.0 5,788 Region Northern 77.5 4.2 18.3 100.0 922 Central 84.2 6.5 9.4 100.0 3,176 Southern 79.1 3.5 17.4 100.0 3,030 Education No education 90.5 5.4 4.1 100.0 375 Primary 81.0 5.5 13.4 100.0 4,153 Secondary 78.6 4.1 17.4 100.0 2,249 More than secondary 88.8 2.3 9.0 100.0 351 Wealth quintile Lowest 85.9 5.5 8.6 100.0 1,134 Second 84.9 5.3 9.8 100.0 1,325 Middle 82.4 5.5 12.1 100.0 1,409 Fourth 81.5 4.6 13.9 100.0 1,462 Highest 74.1 4.0 21.9 100.0 1,798 Total 15-49 81.1 4.9 14.0 100.0 7,128 50-54 93.9 3.6 2.5 100.0 350 Total 15-54 81.7 4.8 13.4 100.0 7,478 1 “Currently employed” is defined as having done work in the past 7 days. Includes persons who did not work in the past 7 days but who are regularly employed and were absent from work for leave, illness, vacation, or any other such reason. Characteristics of Respondents • 45 Table 3.7.1 Occupation: Women Percent distribution of women age 15-49 employed in the 12 months before the survey by occupation, according to background characteristics, Malawi DHS 2015- 16 Background characteristic Professional/ technical/ managerial Clerical Sales and services Skilled manual Unskilled manual Domestic service Agriculture Total Number of women Age 15-19 2.2 0.8 4.0 1.7 17.9 2.6 70.9 100.0 2,343 20-24 6.0 1.5 9.4 1.5 17.5 3.2 60.9 100.0 3,310 25-29 9.3 2.1 10.7 2.5 20.1 2.2 53.0 100.0 2,850 30-34 9.8 1.9 8.0 2.3 21.0 2.9 54.0 100.0 2,809 35-39 9.2 1.6 8.0 2.3 19.8 2.9 56.2 100.0 2,332 40-44 8.5 1.3 5.6 2.3 20.2 2.6 59.4 100.0 1,617 45-49 6.9 1.4 7.9 2.0 22.7 1.0 58.1 100.0 1,224 Marital status Never married 8.5 2.1 8.0 2.2 16.9 4.4 57.8 100.0 2,218 Married or living together 7.4 1.4 7.8 2.0 19.2 1.6 60.5 100.0 11,608 Divorced/separated/ widowed 6.6 1.8 8.4 2.4 23.4 5.5 51.8 100.0 2,658 Number of living children 0 7.6 1.8 7.2 2.4 16.2 3.4 61.3 100.0 2,700 1-2 9.6 2.0 9.8 2.2 19.7 3.0 53.7 100.0 5,378 3-4 7.7 1.7 8.0 2.1 20.2 2.1 58.2 100.0 4,804 5+ 3.8 0.5 5.6 1.7 21.1 2.1 65.1 100.0 3,603 Residence Urban 26.3 5.9 25.7 3.7 20.8 8.7 8.9 100.0 2,646 Rural 3.8 0.7 4.5 1.8 19.4 1.4 68.3 100.0 13,839 Region Northern 11.2 1.5 12.3 2.9 11.2 1.4 59.5 100.0 1,620 Central 5.0 1.5 9.4 1.7 19.9 2.6 59.8 100.0 8,083 Southern 9.4 1.7 5.1 2.3 21.2 2.9 57.4 100.0 6,783 Education No education 2.2 0.5 3.3 1.2 19.7 2.1 71.0 100.0 2,165 Primary 2.9 0.8 6.0 1.9 20.5 2.7 65.3 100.0 10,347 Secondary 14.4 3.3 16.6 3.1 18.9 3.0 40.7 100.0 3,374 More than secondary 66.5 9.4 9.7 2.7 8.1 0.7 2.9 100.0 599 Wealth quintile Lowest 1.2 0.4 2.7 1.4 19.6 2.2 72.5 100.0 3,426 Second 1.4 0.5 3.5 1.9 19.1 1.0 72.6 100.0 3,312 Middle 2.3 0.6 4.8 1.8 18.9 1.4 70.1 100.0 3,228 Fourth 6.4 1.2 9.4 1.9 20.1 2.2 58.8 100.0 3,048 Highest 25.1 4.9 19.0 3.4 20.2 6.1 21.3 100.0 3,471 Total 7.4 1.6 7.9 2.1 19.6 2.6 58.8 100.0 16,485 46 • Characteristics of Respondents Table 3.7.2 Occupation: Men Percent distribution of men age 15-49 employed in the 12 months before the survey by occupation, according to background characteristics, Malawi DHS 2015-16 Background characteristic Professional/ technical/ managerial Clerical Sales and services Skilled manual Unskilled manual Domestic service Agriculture Total Number of men Age 15-19 0.9 1.0 3.6 6.7 27.2 2.3 58.3 100.0 1,137 20-24 4.5 2.1 5.3 13.0 27.7 2.8 44.5 100.0 1,198 25-29 9.5 2.5 9.5 16.6 23.8 1.4 36.8 100.0 984 30-34 11.5 2.2 5.4 17.4 23.5 0.6 39.4 100.0 900 35-39 10.5 3.2 6.9 15.7 26.2 0.7 36.9 100.0 864 40-44 9.9 2.2 4.7 15.0 22.8 1.0 44.3 100.0 610 45-49 9.7 2.9 5.8 12.4 23.4 0.9 44.9 100.0 440 Marital status Never married 4.5 2.1 4.6 10.6 26.1 2.8 49.2 100.0 1,956 Married or living together 9.1 2.2 6.4 14.6 24.8 0.9 42.0 100.0 3,950 Divorced/separated/ widowed 3.5 3.0 8.2 20.8 28.2 2.0 34.2 100.0 228 Number of living children 0 4.8 1.8 5.2 10.7 25.8 2.5 49.1 100.0 2,201 1-2 11.5 2.6 7.6 16.6 25.7 1.2 34.7 100.0 1,529 3-4 8.5 1.8 6.5 14.8 26.8 0.9 40.6 100.0 1,291 5+ 5.7 2.7 4.1 13.7 22.4 0.8 50.7 100.0 1,112 Residence Urban 20.7 5.9 15.0 31.0 17.3 3.5 6.5 100.0 1,035 Rural 4.7 1.4 4.0 10.0 27.0 1.1 51.6 100.0 5,099 Region Northern 6.7 3.1 6.8 11.5 35.2 2.8 33.8 100.0 753 Central 7.3 1.0 5.1 12.5 24.0 1.3 48.7 100.0 2,879 Southern 7.7 3.3 6.5 15.4 23.9 1.4 41.7 100.0 2,501 Education No education 0.6 1.1 4.1 8.9 25.4 1.2 58.7 100.0 360 Primary 2.1 1.5 4.0 11.2 28.0 1.4 51.9 100.0 3,596 Secondary 8.7 3.5 10.0 18.7 24.0 2.2 32.9 100.0 1,858 More than secondary 67.3 3.5 5.5 16.0 3.6 0.2 3.9 100.0 320 Wealth quintile Lowest 0.8 0.8 3.4 9.5 23.3 0.4 61.9 100.0 1,037 Second 1.2 0.4 2.5 10.9 29.3 1.0 54.6 100.0 1,195 Middle 1.5 1.4 4.4 10.1 28.7 1.0 52.9 100.0 1,238 Fourth 6.5 2.6 5.9 13.4 29.3 1.6 40.7 100.0 1,259 Highest 23.6 5.1 11.9 22.1 17.1 3.4 16.9 100.0 1,405 Total 15-49 7.4 2.2 5.9 13.6 25.4 1.6 44.0 100.0 6,134 50-54 7.3 1.4 4.6 13.4 20.8 0.5 52.0 100.0 341 Total 15-54 7.4 2.2 5.8 13.6 25.1 1.5 44.4 100.0 6,475 Characteristics of Respondents • 47 Table 3.8 Type of employment: Women Percent distribution of women age 15-49 employed in the 12 months before the survey by type of earnings, type of employer, and continuity of employment, according to type of employment (agricultural or nonagricultural), Malawi DHS 2015-16 Employment characteristic Agricultural work Nonagricultural work Total Type of earnings Cash only 13.1 57.2 31.3 Cash and in-kind 8.7 5.5 7.4 In-kind only 5.0 1.7 3.6 Not paid 73.2 35.7 57.7 Total 100.0 100.0 100.0 Type of employer Employed by family member 23.0 13.8 19.2 Employed by nonfamily member 7.8 30.7 17.3 Self-employed 69.1 55.5 63.5 Total 100.0 100.0 100.0 Continuity of employment All year 26.1 51.3 36.5 Seasonal 69.7 37.6 56.5 Occasional 4.1 11.1 7.0 Total 100.0 100.0 100.0 Number of women employed during the last 12 months 9,686 6,799 16,485 48 • Characteristics of Respondents Table 3.9.1 Health insurance coverage: Women Percentage of women age 15-49 with specific types of health insurance coverage, according to background characteristics, Malawi DHS 2015-16 Background characteristic Employer based insurance Privately purchased commercial insurance None Number of women Age 15-19 0.7 0.1 99.3 5,263 20-24 0.7 0.3 99.0 5,159 25-29 1.2 0.9 97.9 3,953 30-34 1.5 0.8 97.7 3,668 35-39 1.6 0.1 98.2 2,924 40-44 1.7 0.3 98.0 2,029 45-49 1.4 0.3 98.2 1,567 Residence Urban 4.3 1.9 93.9 4,496 Rural 0.4 0.1 99.5 20,066 Region Northern 1.6 0.3 98.2 2,838 Central 1.2 0.7 98.1 10,529 Southern 0.9 0.2 98.9 11,194 Education No education 0.4 0.0 99.6 2,977 Primary 0.3 0.0 99.7 15,245 Secondary 1.7 0.7 97.5 5,598 More than secondary 17.2 7.7 75.1 742 Wealth quintile Lowest 0.1 0.0 99.9 4,745 Second 0.1 0.0 99.9 4,692 Middle 0.1 0.0 99.9 4,635 Fourth 0.5 0.1 99.5 4,680 Highest 4.2 1.6 94.1 5,810 Total 1.1 0.4 98.5 24,562 Table 3.9.2 Health insurance coverage: Men Percentage of men age 15-49 with specific types of health insurance coverage, according to background characteristics, Malawi DHS 2015-16 Background characteristic Employer based insurance Privately purchased commercial insurance Other None Number of men Age 15-19 0.3 0.8 0.2 98.6 1,818 20-24 1.0 1.3 0.2 97.5 1,408 25-29 1.5 1.4 0.2 97.0 1,022 30-34 2.9 0.8 0.1 96.2 925 35-39 3.0 1.4 0.5 95.5 882 40-44 3.1 0.8 0.0 96.1 624 45-49 2.4 0.4 0.0 97.4 450 Residence Urban 6.5 3.3 0.2 90.2 1,340 Rural 0.5 0.5 0.2 98.8 5,788 Region Northern 1.8 0.4 0.1 97.7 922 Central 2.3 1.6 0.2 96.1 3,176 Southern 1.0 0.6 0.2 98.1 3,030 Education No education 0.0 0.0 0.0 100.0 375 Primary 0.3 0.2 0.1 99.4 4,153 Secondary 1.9 1.4 0.2 96.5 2,249 More than secondary 18.2 9.9 1.4 71.9 351 Wealth quintile Lowest 0.0 0.0 0.3 99.7 1,134 Second 0.1 0.0 0.1 99.8 1,325 Middle 1.0 0.3 0.1 98.6 1,409 Fourth 0.3 0.2 0.1 99.5 1,462 Highest 5.6 3.7 0.4 90.7 1,798 Total 15-49 1.7 1.0 0.2 97.2 7,128 50-54 1.1 1.3 0.0 97.6 350 Total 15-54 1.6 1.0 0.2 97.2 7,478 Characteristics of Respondents • 49 Table 3.10.1 Tobacco smoking: Women Percentage of women age 15-49 who smoke various tobacco products, according to background characteristics, Malawi DHS 2015-16 Percentage who smoke:1 Number of women Background characteristic Cigarettes2 Other type of tobacco2 Any type of tobacco Age 15-19 0.3 0.1 0.3 5,263 20-24 0.5 0.2 0.5 5,159 25-29 0.4 0.1 0.4 3,953 30-34 0.4 0.2 0.4 3,668 35-39 0.2 0.0 0.3 2,924 40-44 0.6 0.2 0.7 2,029 45-49 3.2 0.7 3.2 1,567 Residence Urban 0.1 0.1 0.1 4,496 Rural 0.7 0.2 0.7 20,066 Region Northern 0.8 0.1 0.8 2,838 Central 0.3 0.0 0.3 10,529 Southern 0.8 0.3 0.8 11,194 Education No education 1.8 0.7 1.9 2,977 Primary 0.5 0.1 0.5 15,245 Secondary 0.2 0.0 0.2 5,598 More than secondary 0.0 0.0 0.0 742 Wealth quintile Lowest 0.9 0.2 0.9 4,745 Second 0.7 0.3 0.7 4,692 Middle 0.7 0.2 0.7 4,635 Fourth 0.4 0.1 0.4 4,680 Highest 0.2 0.1 0.2 5,810 Total 0.6 0.2 0.6 24,562 1 Includes daily and occasional (less than daily) use. 2 Includes pipes full of tobacco, cigars, cheroots, cigarillos, and water pipes. 50 • Characteristics of Respondents Table 3.10.2 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, Malawi DHS 2015-16 Percentage who smoke:1 Smoking frequency Total Number of men Background characteristic Cigarettes2 Other type of tobacco3 Any type of tobacco Daily smoker Occasional smoker4 Non- smoker Age 15-19 1.8 0.3 1.9 0.9 1.0 98.1 100.0 1,818 20-24 8.4 0.9 8.5 3.8 5.6 90.6 100.0 1,408 25-29 12.5 0.5 12.6 9.6 4.3 86.1 100.0 1,022 30-34 19.0 2.1 19.0 12.7 7.0 80.3 100.0 925 35-39 17.4 1.1 17.4 12.4 5.6 82.0 100.0 882 40-44 25.0 1.0 25.1 19.2 7.3 73.5 100.0 624 45-49 20.2 0.7 20.3 17.2 4.2 78.6 100.0 450 Residence Urban 11.9 0.6 11.9 7.9 4.7 87.4 100.0 1,340 Rural 12.0 0.9 12.1 8.4 4.4 87.2 100.0 5,788 Region Northern 10.9 0.7 11.1 7.9 4.1 88.0 100.0 922 Central 14.7 1.3 14.9 10.3 5.3 84.4 100.0 3,176 Southern 9.4 0.4 9.4 6.4 3.7 89.9 100.0 3,030 Education No education 27.3 1.9 27.7 22.3 6.7 71.1 100.0 375 Primary 13.0 1.0 13.1 9.3 4.4 86.3 100.0 4,153 Secondary 8.6 0.5 8.6 4.7 4.7 90.6 100.0 2,249 More than secondary 5.5 0.1 5.5 4.3 1.5 94.2 100.0 351 Wealth quintile Lowest 20.1 1.7 20.4 13.7 7.6 78.7 100.0 1,134 Second 14.5 1.7 14.5 10.4 4.8 84.8 100.0 1,325 Middle 9.8 0.5 9.8 7.3 3.6 89.1 100.0 1,409 Fourth 11.1 0.3 11.2 7.8 4.2 88.0 100.0 1,462 Highest 7.4 0.4 7.5 4.6 3.1 92.3 100.0 1,798 Total 15-49 12.0 0.8 12.1 8.3 4.5 87.2 100.0 7,128 50-54 23.9 1.1 24.2 18.6 6.8 74.6 100.0 350 Total 15-54 12.5 0.9 12.6 8.8 4.6 86.6 100.0 7,478 1 Includes daily and occasional (less than daily) use. 2 Includes manufactured cigarettes and hand-rolled cigarettes. 3 Includes pipes, cigars, cheroots, cigarillos, and water pipes. 4 Occasional refers to less often than daily use. Characteristics of Respondents • 51 Table 3.11 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, Malawi DHS 2015-16 Average number of cigarettes smoked per day1 Total Number of men who smoke cigarettes daily1 Background characteristic <5 5-9 10-14 15-24 ≥25 Don’t know/ missing Age 15-19 * * * * * * * 16 20-24 (38.5) (33.9) (19.0) (0.0) (8.6) (0.0) (100.0) 52 25-29 41.3 32.1 19.0 4.7 2.8 0.0 100.0 97 30-34 36.5 48.0 12.6 0.0 0.4 2.6 100.0 115 35-39 29.5 46.1 13.5 9.7 1.1 0.0 100.0 109 40-44 26.6 41.6 5.7 15.4 10.7 0.0 100.0 117 45-49 26.6 39.0 15.4 11.2 6.6 1.4 100.0 74 Residence Urban 41.0 31.6 19.5 7.9 0.0 0.0 100.0 105 Rural 31.4 42.6 11.7 7.7 5.7 0.8 100.0 476 Region Northern 46.1 26.4 10.7 8.1 8.7 0.0 100.0 70 Central 31.8 43.0 8.6 9.9 5.5 1.2 100.0 321 Southern 30.8 41.8 21.4 4.0 1.9 0.0 100.0 191 Education No education 36.9 36.1 10.3 5.5 11.2 0.0 100.0 81 Primary 32.9 41.5 13.6 7.6 3.3 1.0 100.0 381 Secondary 29.8 43.8 13.4 7.8 5.3 0.0 100.0 104 More than secondary * * * * * * * 15 Wealth quintile Lowest 32.9 42.8 13.8 4.0 6.4 0.0 100.0 152 Second 30.0 42.1 10.5 9.4 5.0 2.9 100.0 137 Middle 42.1 37.0 8.1 8.9 3.9 0.0 100.0 101 Fourth 24.4 47.7 14.2 8.5 5.2 0.0 100.0 110 Highest 39.8 28.8 20.5 9.5 1.4 0.0 100.0 82 Total 15-49 33.2 40.6 13.1 7.8 4.7 0.7 100.0 581 50-54 35.1 33.9 15.3 10.8 4.9 0.0 100.0 64 Total 15-54 33.4 39.9 13.3 8.1 4.7 0.6 100.0 645 Note: Figures in parentheses are based on 25-49 unweighted cases. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 1 Includes manufactured and hand-rolled cigarettes. Table 3.12 Smokeless tobacco use Percentage of women and men age 15-49 who currently use smokeless tobacco, according to type of tobacco product, Malawi DHS 2015-16 Tobacco product Women Men Snuff, by mouth 0.1 0.1 Snuff, by nose 0.1 0.3 Chewing tobacco 0.0 0.0 Other type of smokeless tobacco 0.0 0.1 Any type of smokeless tobacco1 0.3 0.4 Any type of tobacco2 0.7 12.9 Number 24,562 7,128 Note: Table includes women and men who use smokeless tobacco daily or occasionally (less than daily). 1 Includes snuff by mouth, snuff by nose, and chewing tobacco. 2 Includes all types of smokeless tobacco shown in this table plus cigarettes, pipes, cigars, cheroots, cigarillos, and water pipes. 52 • Characteristics of Respondents Table 3.13.1 Knowledge and attitude concerning tuberculosis: Women Percentage of women age 15-49 who have heard of tuberculosis (TB), and among women who have heard of TB, the percentage who know that TB is spread through the air by coughing or sneezing, the percentage who believe that TB can be cured, and the percentage who would want to keep secret that a family member has TB, according to background characteristics, Malawi DHS 2015-16 Percentage who heard of TB Number of women Among women who heard of TB: Background characteristic Percentage who report that TB is spread through the air by coughing or sneezing Percentage who believe that TB can be cured Percentage who would want a family member’s TB kept secret Number of women Age 15-19 89.9 5,263 58.8 59.2 41.1 4,732 20-24 94.0 5,159 65.6 73.1 38.7 4,847 25-29 95.4 3,953 71.3 81.2 34.4 3,771 30-34 95.3 3,668 72.9 82.5 31.4 3,495 35-39 95.3 2,924 75.1 83.4 28.6 2,786 40-44 94.8 2,029 72.4 81.6 27.4 1,922 45-49 94.0 1,567 70.6 78.2 26.2 1,472 Residence Urban 99.0 4,496 79.7 87.8 35.2 4,453 Rural 92.6 20,066 65.6 72.3 34.2 18,573 Region Northern 95.1 2,838 61.1 71.1 31.3 2,700 Central 95.8 10,529 65.8 69.4 33.2 10,091 Southern 91.4 11,194 72.7 82.2 36.5 10,236 Education No education 86.3 2,977 60.8 68.9 35.1 2,568 Primary 93.3 15,245 64.1 70.5 36.0 14,225 Secondary 98.2 5,598 78.9 87.9 31.7 5,495 More than secondary 99.5 742 96.9 95.6 20.5 738 Wealth quintile Lowest 90.1 4,745 59.9 63.2 37.8 4,276 Second 91.6 4,692 63.3 69.1 34.4 4,297 Middle 93.1 4,635 66.9 73.9 34.8 4,316 Fourth 95.2 4,680 68.1 78.3 33.5 4,455 Highest 97.8 5,810 79.7 87.6 32.3 5,683 Total 93.7 24,562 68.3 75.3 34.4 23,026 Characteristics of Respondents • 53 Table 3.13.2 Knowledge and attitude concerning tuberculosis: Men Percentage of men age 15-49 who have heard of tuberculosis (TB), and among men who have heard of TB, the percentage who know that TB is spread through the air by coughing or sneezing, the percentage who believe that TB can be cured, and the percentage who would want to keep secret that a family member has TB, according to background characteristics, Malawi DHS 2015-16 Percentage who heard of TB Number of men Among men who heard of TB: Background characteristic Percentage who report that TB is spread through the air by coughing or sneezing Percentage who believe that TB can be cured Percentage who would want a family member’s TB kept secret Number of men Age 15-19 91.2 1,818 68.9 64.2 41.0 1,659 20-24 97.0 1,408 76.8 79.0 29.4 1,366 25-29 99.3 1,022 80.1 86.3 21.1 1,015 30-34 99.0 925 79.4 90.3 24.7 916 35-39 97.7 882 82.9 90.2 19.2 862 40-44 99.7 624 82.0 88.8 19.4 622 45-49 99.7 450 80.6 88.8 16.1 448 Residence Urban 99.1 1,340 88.3 89.1 24.4 1,328 Rural 96.0 5,788 74.5 79.0 28.0 5,559 Region Northern 96.8 922 69.0 76.2 26.3 892 Central 96.6 3,176 75.7 76.6 23.8 3,069 Southern 96.6 3,030 81.3 86.9 31.3 2,926 Education No education 95.6 375 67.1 75.2 26.8 358 Primary 95.0 4,153 71.5 74.1 31.5 3,945 Secondary 99.4 2,249 85.8 91.2 22.4 2,236 More than secondary 99.0 351 97.6 98.1 12.0 348 Wealth quintile Lowest 94.7 1,134 68.1 71.3 30.4 1,074 Second 96.1 1,325 73.2 75.3 29.3 1,273 Middle 96.4 1,409 75.3 79.5 28.8 1,359 Fourth 96.2 1,462 79.6 84.3 25.9 1,405 Highest 98.7 1,798 85.1 89.2 24.0 1,775 Total 15-49 96.6 7,128 77.2 80.9 27.3 6,887 50-54 98.6 350 83.2 85.9 18.3 345 Total 15-54 96.7 7,478 77.5 81.2 26.9 7,232 Marriage and Sexual Activity • 55 MARRIAGE AND SEXUAL ACTIVITY 4 Key Findings  Age at first marriage: Marriage is nearly universal in Malawi, although women marry about 5 years earlier than men, on average. The median age at first marriage is 18.2 years for women and 23.0 years for men age 25-49.  Polygyny: Thirteen percent of currently married women reported that their husband has more than one (multiple) wives.  Sexual initiation: The median age at first sexual intercourse is 1.4 years earlier than the median age at first marriage for women and 4.5 years earlier for men; this indicates that both women and men engage in sex before marriage.  Widowhood: One in ten women in their 40s is widowed. arriage and sexual activity help to determine the extent to which women are exposed to the risk of pregnancy, and 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 Marriage is nearly universal in Malawi. By age 45-49, only 1% of women and 2% of men have never been married (Table 4.1). Sixty-six percent of women and 57% of men age 15-49 are currently married or living together with a partner as though they are married (Figure 4.1). Women are more likely than men to be divorced or separated (10% versus 3%). One in ten of women age 45-49 is widowed, compared with one in fifty men. Trends: The percentage of women married or living together has declined from 72% in 1992 to 68% in 2010 and to 66% in 2015-16. The percentage of men married or living together decreased substantially between 1992 and 2010 (from 74% to 57%) but is unchanged since 2010. M 56 • Marriage and Sexual Activity Figure 4.1 Marital status 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 Thirteen percent of women reported that their husband or partner has other wives (Table 4.2.1). The percentage of men who report multiple wives was about half that of women (7%) (Table 4.2.2). Trends: The percentage of women who reported that they were in polygynous unions has decreased since 1992, from 20% in 1992 to 13% in 2015-16. The percentage of men who reported having multiple wives has changed slightly since 1992, from 9% in 1992 to 7% in 2015-16. Patterns by background characteristics  Older women are much more likely than younger women to have co-wives. The percentage of women with co-wives peaks among women age 40-44 (22%) (Table 4.2.1).  Women living in the rural areas are more likely to report co- wives (14%) compared with their counterparts living in the urban areas (5%).  Women in the Northern region report the highest percentage of co-wives. Eighteen percent of women living in the Northern region report having co-wives, compared with 11% of women in the Southern region (Figure 4.2).  Less educated women are more likely to have co-wives. Twenty- one percent of women with no education report that their husband has multiple wives compared with only 3% of women with more than secondary education. Percent distribution of women and men age 15-49 Never married 21% Married or living together 66% Divorced/ separated 10% Widowed 3% Women Never married 40% Married or living together 57% Divorced/ separated 3% Widowed 0% Men Figure 4.2 Polygyny by region Marriage and Sexual Activity • 57 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, 20-54 and 25-54 Women tend to marry considerably earlier than men in Malawi. The median age at first marriage is 18.2 years among women age 25-49 and 23 years among men age 25-49 (Table 4.4). Although 47% of women marry before their eighteenth birthday, only 8% of men marry at that young age. Trends: The median age at first marriage for women age 25-49 has increased slightly, from 17.8 years in 1992 to 18.2 years in 2015-16. During the same time period, the percentage of women who were married before age 18 declined from 52% to 47%. For men age 25-54, the median age at first marriage remained essentially unchanged between 1992 and 2015-16 (23.5 years and 23.0 years, respectively). Patterns by background characteristics  Urban women marry later than rural women. For women age 25-49, the median age at first marriage is 1.7 years older among urban women than rural women (19.7 years versus 18.0 years) (Table 4.4).  Regional variations indicate that women in the Central region marry at a slightly older age than women in the Southern and Northern regions.  Educated women marry much later. The median age at first marriage for women age 25-49 increases from 17.6 years for women with no education to 24.8 years for women with more than secondary education (Figure 4.3).  Median age at first marriage for women age 25- 49 is higher among women in the highest wealth quintile (19.6 years) than in other quintiles (17.8-18.0 years). 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, 20-54, and 25-54 In Malawi, the median age at first sexual intercourse is 16.8 years for women age 25-49 (Table 4.5). Nineteen percent of women age 25-49 have first sex before age 15, and 64% before age 18. By age 20, 85% of women have had sexual intercourse. On average, men in Malawi initiate sexual intercourse at slightly older ages than women. The median age at first intercourse for men age 25-49 is 18.5 years. Eleven percent of men age 25-49 first have sex before age 15 and 42% do so before age 18. By age 20, 66% of men have experienced sexual intercourse. Age at first marriage is widely considered a proxy indicator for the age at which women begin to be exposed to the risks inherent in sexual activity. A comparison of the median age at first intercourse with the median age at first marriage can be used as a measure of whether respondents engage in sex before Figure 4.3 Women’s median age at marriage by education 17.6 17.7 20.4 24.8 No education Primary Secondary More than secondary Median age at first marriage among women age 25-49 58 • Marriage and Sexual Activity marriage. The median age at first intercourse for women age 25-49 in Malawi is 1.4 years younger than the median age at first marriage of women age 25-49 (16.8 years versus 18.2 years). This indicates that many women engage in sex before marriage (Figure 4.4). Thus, women in Malawi may be exposed to the risk of pregnancy and begin childbearing at an even earlier age than indicated by the median age at first marriage. The median age at first intercourse for men age 25- 49 is 18.5 years. By contrast, the median age at first marriage for men age 25-49 is 23.0. Thus, on average, men in Malawi are initiating sexual intercourse several years (4.5 years) before marriage. Trends: Between 2000 and 2015-16, the median age at first sexual intercourse has not changed among women age 25-49 (16.8 years in 2000 and in 2015-16) or men

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