Malawi DHS Final Report (2010)

Publication date: 2011

Malawi 2010Demographic and Health Survey M alaw i 2010 D em ographic and H ealth Survey Malawi Demographic and Health Survey 2010 National Statistical Office Zomba, Malawi ICF Macro Calverton, Maryland, USA September 2011 The 2010 Malawi Demographic and Health Survey (2010 MDHS) was implemented by the National Statistical Office (NSO) and the Community Health Sciences Unit (CHSU) from June through November 2010. The funding for the MDHS was provided by the government of Malawi, National AIDS Commission (NAC), the United Nations Population Fund (UNFPA), the United Nations Children’s Fund (UNICEF), the United Kingdom Department for International Development (DFID), the Centers for Disease Control and Prevention (CDC), and the United States Agency for International Development (USAID). ICF Macro provided technical assistance as well as funding to the project through the MEASURE DHS programme, a USAID-funded project providing support and technical assistance in the implementation of population and health surveys in countries worldwide. Additional information about the 2010 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, 265-1-524-111; Fax: 265-1-525-130; Email: enquiries@statistics.gov.mw; Internet: www.nso.malawi.net. Information about the MEASURE DHS programme may be obtained from ICF Macro, 11785 Beltsville Drive, Suite 300, Calverton, MD 20705, USA; Telephone: 301-572-0200, Fax: 301-572-0999, E-mail: reports@measuredhs.com, Internet: http://www.measuredhs.com. Recommended citation: National Statistical Office (NSO) and ICF Macro. 2011. Malawi Demographic and Health Survey 2010. Zomba, Malawi, and Calverton, Maryland, USA: NSO and ICF Macro. Contents | iii CONTENTS Page TABLES AND FIGURES . ix FOREWORD . xxi MILLENNIUM DEVELOPMENT GOAL INDICATORS . xxiii MAP OF MALAWI . xxiv CHAPTER 1 INTRODUCTION 1.1 Geography, History, and the Economy . 1 1.1.1 Geography . 1 1.1.2 History. 1 1.1.3 Economy . 1 1.2 Population . 2 1.3 Objective of the Survey . 2 1.4 Organisation of the Survey . 3 1.5 Sample Design . 3 1.6 Questionnaires . 4 1.7 HIV and Anaemia Testing . 5 1.8 Pretest . 6 1.9 Training of Field Staff . 6 1.10 Fieldwork . 6 1.11 Data Processing . 6 1.12 Response Rates . 7 CHAPTER 2 HOUSEHOLD POPULATION AND HOUSING CHARACTERISTICS 2.1 Household Population by Age, Sex, and Residence . 9 2.2 Household Composition . 10 2.3 Education of Household Population . 11 2.3.1 Educational Attainment . 11 2.3.2 School Attendance Rates . 14 2.3.3 Grade Repetition and Dropout Rates . 16 2.4 Household Environment . 17 2.4.1 Improved Drinking Water . 18 2.4.2 Household Sanitation Facilities . 19 2.4.3 Housing Characteristics . 20 2.5 Household Possessions . 21 2.6 Wealth Index . 22 iv | Contents CHAPTER 3 RESPONDENTS’ CHARACTERISTICS 3.1 Characteristics of Survey Respondents . 25 3.2 Educational Attainment by Background Characteristics . 27 3.3 Literacy. 28 3.4 Access to Mass Media . 30 3.5 Employment . 32 3.6 Occupation . 34 3.7 Earnings, Employers, and Continuity of Employment . 36 3.8 Knowledge and Attitudes Regarding Tuberculosis . 37 3.9 Tobacco Use . 39 CHAPTER 4 FERTILITY 4.1 Introduction . 43 4.2 Current Fertility . 43 4.3 Fertility Trends . 45 4.4 Children Ever Born and Living . 46 4.5 Birth Intervals . 47 4.6 Age at First Birth . 49 4.7 Median Age at First Birth . 49 4.8 Teenage Pregnancy and Motherhood . 50 CHAPTER 5 FAMILY PLANNING 5.1 Knowledge of Contraceptive Methods . 53 5.2 Ever Use of Contraception . 55 5.3 Current Use of Contraceptive Methods . 57 5.4 Differentials in Contraceptive Use by Background Characteristics . 59 5.5 Trends in Contraceptive Use . 60 5.6 Number of Children at First Use of Contraception . 61 5.7 Brands of Pills and Condoms Used . 61 5.8 Knowledge of the Fertile Period . 63 5.9 Timing of Sterilisation . 64 5.10 Source of Contraception . 64 5.11 Informed Choice . 65 5.12 Future Use of Contraception . 66 5.13 Exposure to Family Planning Messages in the Media . 67 5.13.1 Exposure of Females to Specific Family Planning Messages . 68 5.13.2 Exposure of Males to Specific Family Planning Messages . 69 5.14 Contact of Non-Users with Family Planning Providers . 70 5.15 Husband’s/Partner’s Knowledge of Women’s Contraceptive Use . 71 CHAPTER 6 OTHER PROXIMATE DETERMINANTS OF FERTILITY 6.1 Current Marital Status . 73 6.2 Polygyny . 74 6.3 Age at First Marriage . 75 6.4 Median Age at First Marriage . 76 6.5 Age at First Sexual Intercourse . 78 Contents | v 6.6 Median Age at First Sexual Intercourse . 79 6.7 Recent Sexual Activity . 80 6.8 Postpartum Amenorrhoea, Abstinence, and Insusceptibility . 82 6.9 Menopause . 84 CHAPTER 7 FERTILITY PREFERENCES 7.1 Desire for More Children . 85 7.2 Desire to Limit Childbearing . 86 7.3 Need for Family Planning Services . 88 7.4 Ideal Family Size . 91 7.5 Fertility Planning . 92 7.6 Wanted Fertility Rates . 93 CHAPTER 8 INFANT AND CHILD MORTALITY 8.1 Background and Assessment of Data Quality . 95 8.2 Infant and Child Mortality Levels and Trends . 96 8.3 Socioeconomic Differentials in Infant and Child Mortality . 97 8.4 Demographic Differentials in Childhood Mortality . 98 8.5 Perinatal Mortality . 100 8.6 High-risk Fertility Behaviour . 101 CHAPTER 9 MATERNAL HEALTH 9.1 Antenatal Care . 103 9.2 Number of ANC Visits and Timing of First Visit . 105 9.3 Components of Antenatal Care . 106 9.4 Tetanus Toxoid Vaccine Doses . 107 9.5 Place of Delivery . 109 9.6 Assistance during Delivery . 110 9.7 Postnatal Care . 111 9.9 Perceived Problems in Accessing Health Care . 113 CHAPTER 10 CHILD HEALTH 10.1 Child’s Weight at Birth . 117 10.2 Vaccination of Children . 118 10.2.1 Trends in Vaccination Coverage . 120 10.3 Acute Respiratory Infection . 121 10.4 Fever . 122 10.5 Prevalence of Diarrhoea . 124 10.6 Diarrhoea Treatment . 126 10.7 Feeding Practices . 127 10.8 Knowledge of ORS Packets . 128 vi | Contents CHAPTER 11 NUTRITION OF CHILDREN AND ADULTS 11.1 Nutritional Status of Children . 129 11.1.1 Measurement of Nutritional Status among Young Children . 129 11.1.2 Results of Data Collection . 130 11.1.3 Trends in Malnutrition . 133 11.2 Initiation Of Breastfeeding . 134 11.3 Breastfeeding Status by Age . 136 11.4 Duration of Breastfeeding . 139 11.5 Types of Complementary Foods . 139 11.6 Infant and Young Child Feeding (IYCF) Practices . 140 11.7 Prevalence of Anaemia in Children . 143 11.8 Micronutrient Intake among Children . 144 11.9 Presence of Iodised Salt in Households . 147 11.10 Nutritional Status of Women . 147 11.11 Prevalence of Anaemia among Women . 149 11.12 Micronutrient Intake among Mothers . 150 CHAPTER 12 MALARIA 12.1 Introduction . 153 12.2 Mosquito Nets . 154 12.2.1 Ownership of Mosquito Nets . 154 12.2.2 Use of Mosquito Nets by Persons in the Household . 155 12.2.3 Use of Mosquito Nets by Children Under Five Years . 155 12.2.4 Use of Mosquito Nets by Pregnant Women . 156 12.3 Indoor Residual Spraying . 157 12.4 Use of Intermittent Preventive Treatment of Malaria in Pregnancy . 159 12.5 Prevalence and Prompt Treatment of Fever . 160 12.6 Prevalence of Anaemia in Children . 163 CHAPTER 13 HIV- AND AIDS-RELATED KNOWLEDGE, ATTITUDES, AND BEHAVIOUR 13.1 Introduction . 165 13.2 HIV and AIDS Knowledge, Transmission and Prevention Methods . 166 13.2.1 Awareness of AIDS . 166 13.2.2 Knowledge of HIV Prevention . 166 13.2.3 Comprehensive Knowledge and Misconceptions about HIV/AIDS . 168 13.3 Knowledge about Mother-to-Child Transmission . 170 13.4 Attitudes Towards People Living with HIV and AIDS . 172 13.5 Attitudes Towards Negotiating Safer Sexual Relations with Husbands . 174 13.6 Attitudes Towards Condom Education for Youth . 175 13.7 Multiple Sexual Partners . 176 13.8 Concurrent Sexual Partners . 178 13.9 Payment for Sex . 181 13.10 Male Circumcision . 182 13.11 Self-reporting of Sexually Transmitted Infections . 183 13.12 Prevalence of Medical Injections . 184 Contents | vii 13.13 HIV and AIDS-related Knowledge and Behaviour among Youth . 185 13.13.1 Knowledge about HIV and AIDS and Sources for Condoms . 185 13.13.2 Age at First Sexual Intercourse . 187 13.13.3 Premarital Sex . 188 13.13.4 Multiple Sexual Partners among Youth . 190 13.13.5 Age-mixing in Sexual Relationships . 191 CHAPTER 14 HIV PREVALENCE 14.1 Coverage Rates for HIV Testing . 193 14.2 HIV Prevalence . 196 14.2.1 HIV Prevalence by Age and Sex . 196 14.2.2 Trends in HIV Prevalence . 197 14.2.3 HIV Prevalence by Socioeconomic Characteristics . 197 14.2.4 HIV Prevalence by Demographic Characteristics . 199 14.2.5 HIV Prevalence by Sexual Risk Behaviour . 200 14.3 HIV Prevalence Among Youth . 202 14.3.1 HIV Prevalence by Sexual Behaviour among Youth . 204 14.4 HIV Prevalence by Other Characteristics . 205 14.4.1 HIV Prevalence and STIs . 205 14.4.2 HIV Prevalence by Male Circumcision . 205 14.5 HIV Prevalence Among Cohabiting Couples . 208 CHAPTER 15 SELF-REPORTED PRIOR HIV TESTING AND TREATMENT 15.1 Coverage of HIV Testing Services . 209 15.2 HIV Testing among Youth . 211 15.3 Self-reported HIV Status and HIV Status According to the 2010 MDHS . 212 15.4 Self-Reported Use of Antiretroviral Medications (ARVs) . 214 15.5 HIV Testing during Pregnancy . 217 15.6 Self-reported Use of Prevention of Mother-to-Child Transmission (PMTCT) Services . 218 CHAPTER 16 ADULT AND MATERNAL MORTALITY 16.1 Data . 219 16.2 Estimates of Adult Mortality . 220 16.3 Estimates of Maternal Mortality . 221 CHAPTER 17 WOMEN’S STATUS AND DEMOGRAPHIC AND HEALTH OUTCOMES 17.1 Women’s and Men’s Employment . 223 17.1.1 Employment Status . 223 17.2 Women’s Control Over Their Own Earnings and Relative Magnitude of Women’s Earnings . 224 17.3 Women’s Participation in Decision-making . 227 17.4 Attitudes Towards Wife Beating . 231 17.5 Women’s Empowerment Indicators . 234 viii | Contents 17.6 Current Use of Contraception by Woman’s Empowerment Status . 234 17.7 Ideal Family Size and Unmet Need by Women’s Status . 235 17.8 Women’s Status and Reproductive Health Care . 236 CHAPTER 18 DOMESTIC VIOLENCE 18.1 Introduction . 239 18.2 Women Experiencing Physical Violence . 240 18.3 Perpetrators of Physical Violence . 242 18.4 Force at Sexual Initiation . 242 18.5 Experience of Sexual Violence . 243 18.6 Age at First Experience of Sexual Violence . 244 18.7 Perpetrators of Sexual Violence . 245 18.8 Experience of Different Forms of Violence . 246 18.9 Violence during Pregnancy . 246 18.10 Marital Control by Husband. 247 18.11 Forms of Spousal Violence . 249 18.12 Spousal Violence by Background Characteristics . 251 18.13 Violence by Spousal Characteristics and Women’s Empowerment Indicators . 253 18.14 Frequency of Spousal Violence . 254 18.15 Onset of Spousal Violence . 256 18.16 Physical Consequences of Spousal Violence . 257 18.17 Violence by Women Against their Husbands . 257 18.18 Help-Seeking Behaviour by Women Who Experience Violence . 259 CHAPTER 19 ORPHANS AND VULNERABLE CHILDREN 19.1 Orphaned and Vulnerable Children . 261 19.1.1 Children’s Living Arrangements and Orphanhood . 261 19.1.2 Orphaned and Vulnerable Children . 262 19.2 Social and Economic Situation of Orphaned and Vulnerable Children . 264 19.2.1 School Attendance . 264 19.2.2 Basic Material Needs . 265 19.2.3 Nutritional Status . 265 19.2.4 Sex before Age 15 . 266 19.3 Care and Support for OVCs . 267 19.3.1 Property Dispossession and Legal Assistance . 267 19.3.2 External Support for Households with OVCs . 268 REFERENCES . 271 APPENDIX A DISTRICT TABLES . 273 APPENDIX B SAMPLE DESIGN AND IMPLEMENTATION . 409 APPENDIX C ESTIMATES OF SAMPLING ERRORS . 421 APPENDIX D DATA QUALITY TABLES . 431 APPENDIX E NUTRITIONAL STATUS OF CHILDREN: 2010 MDHS DATA ACCORDING TO THE NCHS/CDC/WHO INTERNATIONAL REFERENCE POPULATION . 437 APPENDIX F SURVEY PERSONNEL . 439 APPENDIX G QUESTIONNAIRES . 447 Tables and Figures | ix TABLES AND FIGURES Page CHAPTER 1 INTRODUCTION Table 1.1 Demographic indicators . 2 Table 1.2 Results of the household and individual interviews . 7 CHAPTER 2 HOUSEHOLD POPULATION AND HOUSING CHARACTERISTICS Table 2.1 Household population by age, sex, and residence . 9 Table 2.2 Household composition . 11 Table 2.3.1 Educational attainment of the female household population . 13 Table 2.3.2 Educational attainment of the male household population . 13 Table 2.4 School attendance ratios . 15 Table 2.5 Grade repetition and dropout rates . 16 Table 2.6 Household drinking water . 18 Table 2.7 Household sanitation facilities . 19 Table 2.8 Household characteristics . 21 Table 2.9 Household durable goods . 22 Table 2.10 Wealth quintiles . 23 Figure 2.1 Population Pyramid . 10 Figure 2.2 Distribution of Household Population with No Education by Sex . 14 Figure 2.3 Age-specific Attendance Rates . 17 CHAPTER 3 RESPONDENTS’ CHARACTERISTICS Table 3.1 Background characteristics of respondents . 26 Table 3.2.1 Educational attainment: Women . 27 Table 3.2.2 Educational attainment: Men . 28 Table 3.3.1 Literacy: Women . 29 Table 3.3.2 Literacy: Men . 30 Table 3.4.1 Exposure to mass media: Women . 31 Table 3.4.2 Exposure to mass media: Men . 31 Table 3.5.1 Employment status: Women . 32 Table 3.5.2 Employment status: Men . 33 Table 3.6.1 Occupation: Women . 34 Table 3.6.2 Occupation: Men . 35 Table 3.7.1 Type of employment: Women . 36 Table 3.7.2 Type of employment: Men . 37 Table 3.8.1 Knowledge and attitude concerning tuberculosis: Women . 38 Table 3.8.2 Knowledge and attitude concerning tuberculosis: Men . 39 Table 3.9.1 Use of tobacco: Women . 40 Table 3.9.2 Use of tobacco: Men . 41 x | Tables and Figures CHAPTER 4 FERTILITY Table 4.1 Current fertility . 43 Table 4.2 Fertility by background characteristics . 44 Table 4.3.1 Trends in age-specific fertility rates . 45 Table 4.3.2 Trends in age-specific and total fertility rates . 46 Table 4.4 Children ever born and living . 47 Table 4.5 Birth intervals . 48 Table 4.6 Age at first birth . 49 Table 4.7 Median age at first birth . 50 Table 4.8 Teenage pregnancy and motherhood . 51 Figure 4.1 Trends in Age-specific Fertility Rates, Various Sources, 1992-2010 . 46 CHAPTER 5 FAMILY PLANNING Table 5.1 Knowledge of contraceptive methods . 54 Table 5.2 Knowledge of contraceptive methods by background characteristics . 55 Table 5.3.1 Ever use of contraception: Women . 56 Table 5.3.2 Ever use of contraception: Men . 57 Table 5.4.1 Current use of contraception by age: Women . 58 Table 5.4.2 Current use of contraception by age: Men . 59 Table 5.5 Current use of contraception by background characteristics: Women . 60 Table 5.6 Trends in current use of contraception . 60 Table 5.7 Number of children at first use of contraception . 61 Table 5.8.1 Use of social marketing brand pills and condoms . 62 Table 5.8.2 Use of social marketing brand of condoms: Men . 62 Table 5.9.1 Knowledge of fertile period: Women . 63 Table 5.9.2 Knowledge of fertile period: Men . 63 Table 5.10 Timing of sterilisation . 64 Table 5.11 Source of modern contraception methods . 65 Table 5.12 Informed choice . 66 Table 5.13 Future use of contraception . 67 Table 5.14 Exposure to family planning messages . 68 Table 5.15.1 Exposure of respondents to specific family planning or health programmes on the radio: Women . 69 Table 5.15.2 Exposure of respondents to specific family planning or health programmes on the radio: Men . 70 Table 5.16 Contact of non-users with family planning providers . 71 Table 5.17 Husband/partner’s knowledge of women’s use of contraception . 72 CHAPTER 6 OTHER PROXIMATE DETERMINANTS OF FERTILITY Table 6.1 Current marital status . 73 Table 6.2.1 Number of women’s cowives . 74 Table 6.2.2 Number of men’s wives . 75 Table 6.3 Age at first marriage . 76 Table 6.4.1 Median age at first marriage: Women . 77 Table 6.4.2 Median age at first marriage: Men . 77 Table 6.5 Age at first sexual intercourse . 78 Table 6.6.1 Median age at first intercourse: Women . 79 Tables and Figures | xi Table 6.6.2 Median age at first intercourse: Men . 80 Table 6.7.1 Recent sexual activity: Women . 81 Table 6.7.2 Recent sexual activity: Men . 82 Table 6.8 Postpartum amenorrhoea, abstinence, and insusceptibility . 83 Table 6.9 Median duration of amenorrhoea, postpartum abstinence and postpartum insusceptibility . 84 Table 6.10 Menopause . 84 CHAPTER 7 FERTILITY PREFERENCES Table 7.1 Fertility preferences by number of living children . 85 Table 7.2.1 Desire to limit childbearing: Women . 87 Table 7.2.2 Desire to limit childbearing: Men . 88 Table 7.3.1 Need and demand for family planning among currently married women . 89 Table 7.3.2 Need and demand for family planning for all women and for women who are not currently married . 90 Table 7.4 Ideal number of children . 91 Table 7.5 Mean ideal number of children. 92 Table 7.6 Fertility planning status . 92 Table 7.7 Wanted fertility rates . 93 Figure 7.1 Percentage of Currently Married Women and Men Who Want No More Children, by Number of Living Children . 86 CHAPTER 8 INFANT AND CHILD MORTALITY Table 8.1 Early childhood mortality rates . 96 Table 8.2 Trends in early childhood mortality . 97 Table 8.3 Early childhood mortality rates by socioeconomic characteristics . 98 Table 8.4 Early childhood mortality rates by demographic characteristics . 99 Table 8.5 Perinatal mortality . 100 Table 8.6 High-risk fertility behaviour . 101 Figure 8.1 Trends in Childhood Mortality, 1992-2010 . 97 CHAPTER 9 MATERNAL HEALTH Table 9.1 Antenatal care . 104 Table 9.2 Number of antenatal care visits and timing of first visit . 105 Table 9.3 Components of antenatal care . 106 Table 9.4 Tetanus toxoid vaccine (TTV) . 108 Table 9.5 Place of delivery . 109 Table 9.6 Assistance during delivery . 111 Table 9.7 Timing of first postnatal checkup. 112 Table 9.8 Type of provider of first postnatal checkup . 113 Table 9.9 Problems in accessing health care . 114 Figure 9.1 Problems in Accessing Health Care . 115 xii | Tables and Figures CHAPTER 10 CHILD HEALTH Table 10.1 Child’s weight and size at birth . 118 Table 10.2 Vaccinations by source of information . 119 Table 10.3 Vaccinations by background characteristics . 120 Table 10.4 Trends in vaccination coverage . 120 Table 10.5 Vaccinations in first year of life. 121 Table 10.6 Prevalence and treatment of symptoms of ARI . 122 Table 10.7 Prevalence and treatment of fever . 123 Table 10.8 Antimalarial drugs taken by children . 124 Table 10.9 Prevalence of diarrhoea . 125 Table 10.10 Diarrhoea treatment . 126 Table 10.11 Feeding practices during diarrhoea . 127 Table 10.12 Knowledge of ORS packets or pre-packaged liquids . 128 CHAPTER 11 NUTRITION OF CHILDREN AND ADULTS Table 11.1 Nutritional status of children . 131 Table 11.2 Initial breastfeeding . 135 Table 11.3 Breastfeeding status by age . 136 Table 11.4 Median duration of breastfeeding . 139 Table 11.5 Foods and liquids consumed by children in the day or night preceding the interview . 140 Table 11.6 Infant and young child feeding (IYCF) practices . 142 Table 11.7 Prevalence of anaemia in children . 144 Table 11.8 Micronutrient intake among children . 146 Table 11.9 Presence of iodized salt in households . 147 Table 11.10 Nutritional status of women . 148 Table 11.11.1 Prevalence of anaemia in nonpregnant women . 149 Table 11.11.2 Prevalence of anaemia in pregnant women . 150 Table 11.12 Micronutrient intake among mothers . 151 Figure 11.1 Nutritional Status of Children by Age . 133 Figure 11.2 Trends in Nutritional Status of Children Under Five, 2004 MDHS and 2010 MDHS . 134 Figure 11.3 Infant Feeding Practices by Age . 137 Figure 11.4 Trends in Infant Feeding Practices for Children 0-5 Months and 6-9 Months, 2004 MDHS and 2010 MDHS . 138 Figure 11.5 Indicators on Breastfeeding Status, Malawi 2010 . 139 Figure 11.6 IYCF Feeding Practices . 143 CHAPTER 12 MALARIA Table 12.1 Household possession of mosquito nets . 154 Table 12.2 Use of mosquito nets by persons in the household . 155 Table 12.3 Use of mosquito nets by children . 156 Table 12.4 Use of mosquito nets by pregnant women . 157 Table 12.5 Indoor residual spraying against mosquitoes . 158 Table 12.6 Use of mosquito nets or sleeping in a house which received IRS . 159 Table 12.7 Prophylactic use of antimalarial drugs and use of Intermittent Preventive Treatment (IPTp) by women during pregnancy . 160 Tables and Figures | xiii Table 12.8 Prevalence and prompt treatment of fever . 161 Table 12.9 Type and timing of antimalarial drugs taken by children with fever . 162 Table 12.10 Percentage of children with haemoglobin <8.0 g/dl in children . 163 CHAPTER 13 HIV- AND AIDS-RELATED KNOWLEDGE, ATTITUDES, AND BEHAVIOUR Table 13.1 Knowledge of AIDS. 166 Table 13.2 Knowledge of HIV prevention methods . 167 Table 13.3.1 Comprehensive knowledge about AIDS: Women . 169 Table 13.3.2 Comprehensive knowledge about AIDS: Men . 170 Table 13.4 Knowledge of prevention of mother-to-child transmission of HIV . 171 Table 13.5.1 Accepting attitudes toward those living with HIV/AIDS: Women . 172 Table 13.5.2 Accepting attitudes toward those living with HIV/AIDS: Men . 173 Table 13.6 Attitudes toward negotiating safer sexual relations with husband . 174 Table 13.7 Adult support of education about condom use to prevent AIDS . 175 Table 13.8.1 Multiple sexual partners in the past 12 months: Women . 176 Table 13.8.2 Multiple sexual partners in the past 12 months: Men . 177 Table 13.9.1 Point prevalence and cumulative prevalence of concurrent sexual partnerships: Women . 179 Table 13.9.2 Point prevalence and cumulative prevalence of concurrent sexual partnerships: Men . 180 Table 13.10 Payment for sexual intercourse and condom use at last paid sexual intercourse: Men . 181 Table 13.11 Male circumcision . 182 Table 13.12 Self-reported prevalence of sexually-transmitted infections (STIs) and STIs symptoms . 183 Table 13.13 Prevalence of medical injections . 185 Table 13.14 Comprehensive knowledge about AIDS and of a source of condoms among youth . 186 Table 13.15 Age at first sexual intercourse among youth . 187 Table 13.16 Premarital sexual intercourse and condom use during premarital sexual intercourse among youth . 189 Table 13.17.1 Multiple sexual partners in the past 12 months among youth: Women . 190 Table 13.17.2 Multiple sexual partners in the past 12 months among youth: Men . 191 Table 13.18 Age-mixing in sexual relationships among women age 15-19 . 192 Figure 13.1 Women and Men Seeking Treatment for STIs . 184 Figure 13.2 Trend in Age at First Sexual Intercourse . 188 CHAPTER 14 HIV PREVALENCE Table 14.1 Coverage of HIV testing by residence and region . 194 Table 14.2 Coverage of HIV testing by selected background characteristics . 195 Table 14.3 HIV prevalence by age . 196 Table 14.4 Trends in HIV prevalence by age . 197 Table 14.5 HIV prevalence by socioeconomic characteristics . 198 Table 14.6 HIV prevalence by demographic characteristics . 200 Table 14.7 HIV prevalence by sexual behaviour . 201 Table 14.8 HIV prevalence among young people by background characteristics . 203 Table 14.9 HIV prevalence among young people by sexual behaviour . 204 Table 14.10 HIV prevalence by sexually transmitted infections . 205 xiv | Tables and Figures Table 14.11 HIV prevalence by male circumcision . 207 Table 14.12 HIV prevalence among cohabiting couples . 208 Figure 14.1 HIV Prevalence by Sex and Age . 196 Figure 14.2 HIV Prevalence by Sex and Age MDHS 2004 and 2010 . 197 CHAPTER 15 SELF-REPORTED PRIOR HIV TESTING AND TREATMENT Table 15.1.1 Coverage of prior HIV testing: Women . 209 Table 15.1.2 Coverage of prior HIV testing: Men . 210 Table 15.2 HIV testing among youth . 211 Table 15.3 HIV prevalence by self-reported prior HIV testing . 213 Table 15.4 Self-reported prior HIV testing by current HIV status . 214 Table 15.5 Self-reported HIV status and ARV use . 215 Table 15.6 Pregnant women counselled and tested for HIV. 217 Table 15.7 PMTCT services . 218 Figure 15.1 Self-reported ARV Use and HIV Status among HIV-positive Women Age 15-49 . 216 Figure 15.2 Self-reported ARV Use and HIV Status among HIV-positive Men Age 15-49 . 216 CHAPTER 16 ADULT AND MATERNAL MORTALITY Table 16.1 Data on siblings . 220 Table 16.2 Adult mortality rates . 221 Table 16.3 Maternal mortality . 222 CHAPTER 17 WOMEN’S STATUS AND DEMOGRAPHIC AND HEALTH OUTCOMES Table 17.1 Employment and cash earnings of currently married women and men . 224 Table 17.2.1 Control over women’s cash earnings and relative magnitude of women’s earnings: Women . 225 Table 17.2.2 Control over men’s cash earnings . 226 Table 17.3 Women’s control over her own earnings and over those of her husband . 227 Table 17.4.1 Women’s participation in decision-making . 228 Table 17.4.2 Women’s participation in decision-making according to men . 228 Table 17.5.1 Women’s participation in decision-making by background characteristics . 229 Table 17.5.2 Men’s attitude toward wives’ participation in decision-making . 231 Table 17.6.1 Attitude toward wife beating: Women . 232 Table 17.6.2 Attitude toward wife beating: Men . 233 Table 17.7 Indicators of women’s empowerment . 234 Table 17.8 Current use of contraception by women’s status . 235 Table 17.9 Women’s empowerment and ideal number of children and unmet need for family planning . 236 Table 17.10 Reproductive health care by women’s empowerment . 237 Figure 17.1 Number of Decisions in which Women Participate . 230 Tables and Figures | xv CHAPTER 18 DOMESTIC VIOLENCE Table 18.1 Experience of physical violence . 241 Table 18.2 Persons committing physical violence . 242 Table 18.3 Force at sexual initiation . 243 Table 18.4 Experience of sexual violence . 244 Table 18.5 Age at first experience of sexual violence . 245 Table 18.6 Persons committing sexual violence . 245 Table 18.7 Experience of different forms of violence . 246 Table 18.8 Violence during pregnancy . 247 Table 18.9 Degree of marital control exercised by husbands . 248 Table 18.10 Forms of spousal violence . 250 Table 18.11 Spousal violence by background characteristics. 252 Table 18.12 Spousal violence by husband’s characteristics and empowerment indicators . 254 Table 18.13 Frequency of spousal violence among those who report violence . 255 Table 18.14 Onset of marital violence . 256 Table 18.15 Injuries to women due to spousal violence . 257 Table 18.16 Violence by women against their spouse . 258 Table 18.17 Help seeking to stop violence . 260 Figure 18.1 Percentage of Ever-married Women Who have Experienced Specific Forms of Physical and Sexual Violence Committed by their Husband/Partner, Ever and During the Past 12 Months . 251 CHAPTER 19 ORPHANS AND VULNERABLE CHILDREN Table 19.1 Children’s living arrangements and orphanhood . 262 Table 19.2 Orphans and vulnerable children (OVC) . 263 Table 19.3 School attendance by survivorship of parents and by OVC status . 264 Table 19.4 Possession of basic material needs by orphans and vulnerable children . 265 Table 19.5 Underweight orphans and vulnerable children . 266 Table 19.6 Sexual intercourse before age 15 of orphans and vulnerable children . 266 Table 19.7 Widows dispossessed of property . 267 Table 19.8 External support for very sick persons . 268 Table 19.9 External support for orphans and vulnerable children. 269 APPENDIX A DISTRICT TABLES Table A-2.3.1 Educational attainment of the female household population . 273 Table A-2.3.2 Educational attainment of the male household population . 274 Table A-2.4 School attendance ratios . 275 Table A-2.6.1 Household drinking water: Regions . 277 Table A-2.6.2 Household drinking water: Districts . 277 Table A-2.7.1 Household sanitation facilities: Regions . 278 Table A-2.7.2 Household sanitation facilities: Districts . 279 Table A-2.8.1 Household access to electricity: Regions . 280 Table A-2.8.2 Household access to electricity: Districts . 281 Table A-3.1 Background characteristics of respondents: Districts . 283 Table A-3.2.1 Educational attainment: Women by district . 284 Table A-3.2.2 Educational attainment: Men by district . 285 Table A-3.3.1 Literacy: Women by district . 286 xvi | Tables and Figures Table A-3.3.2 Literacy: Men by district . 287 Table A-3.4.1 Exposure to mass media: Women by district . 288 Table A-3.4.2 Exposure to mass media: Men by district . 289 Table A-3.5.1 Employment status: Women by district . 290 Table A-3.5.2 Employment status: Men by district . 291 Table A-3.6.1 Occupation: Women by district . 292 Table A-3.6.2 Occupation: Men by district . 293 Table A-3.7.1 Type of earnings: Women by district . 294 Table A-3.7.2 Type of earnings: Men by district . 295 Table A-3.7.3 Type of employer: Women by district . 296 Table A-3.7.4 Type of employer: Men by district . 297 Table A-3.7.5 Continuity of employment: Women by district . 298 Table A-3.7.6 Continuity of employment: Men by district . 299 Table A-3.9.1 Knowledge and attitude concerning tuberculosis: Women by district . 300 Table A-3.9.2 Knowledge and attitude concerning tuberculosis: Men by district . 301 Table A-3.10.1 Use of tobacco: Women by district . 302 Table A-3.10.2 Use of tobacco: Men by district . 303 Table A-4.5 Birth intervals . 305 Table A-4.7 Median age at first birth . 306 Table A-4.8 Teenage pregnancy and motherhood . 307 Table A-5.2 Knowledge of contraceptive methods by district of residence . 308 Table A-5.3.1 Ever use of contraception: Women by district . 309 Table A-5.3.2 Ever use of contraception: Men by district . 310 Table A-5.5.1 Current use of contraception by background characteristics: Women by district . 311 Table A-5.5.2 Current use of contraception by background characteristics: Men by district . 312 Table A-5.7 Number of children at first use of contraception: Districts . 313 Table A-5.14 Exposure to family planning messages: Districts . 314 Table A-5.18.1 Exposure of respondents to specific family planning or health programs on the radio: Women by district . 315 Table A-5.18.2 Exposure of respondents to specific family planning or health programs on the radio: Men by district . 316 Table A-5.19 Contact of nonusers with family planning providers: Districts . 317 Table A-5.20 Husband/partner’s knowledge of women’s use of contraception: Districts . 318 Table A-6.2.2 Number of men’s wives: Districts . 320 Table A-6.6.1 Median age at first intercourse: Women . 321 Table A-6.6.2 Median age at first intercourse: Men by districts . 322 Table A-6.7.1 Recent sexual activity: Women by districts . 323 Table A-6.7.2 Recent sexual activity: Men by districts . 324 Table A-7.3.1 Need and demand for family planning among currently married women: Districts . 326 Table A-7.5 Mean ideal number of children: Districts . 327 Table A-8.3 Early childhood mortality rates by socioeconomic characteristics . 329 Table A-9.1 Antenatal care: Districts . 330 Table A-9.3 Components of antenatal care: Districts . 331 Table A-9.4 Tetanus toxoid vaccine (TTV): Districts . 332 Table A-9.5 Place of delivery: Districts . 333 Table A-9.6 Assistance during delivery: Districts . 334 Table A-9.7 Timing of first postnatal checkup: Districts . 335 Table A-9.8 Type of provider of first postnatal checkup: Districts . 336 Tables and Figures | xvii Table A-9.9 Problems in accessing health care: Districts . 337 Table A-10.1 Child’s weight and size at birth: Districts . 338 Table A-10.3 Vaccinations by background characteristics: Districts . 339 Table A-10.6 Prevalence and treatment of symptoms of ARI: Districts . 340 Table A-10.7 Prevalence and treatment of fever: Districts . 341 Table A-10.8 Antimalarial drugs taken by children: Districts . 342 Table A-10.9 Prevalence of diarrhoea: Districts . 343 Table A-10.10 Diarrhoea treatment: Districts . 344 Table A-10.11 Feeding practices during diarrhoea: Districts . 345 Table A-10.12 Knowledge of ORS packets or pre-packaged liquids: Districts . 346 Table A-11.1 Nutritional status of children: Districts . 347 Table A-11.2 Initial breastfeeding: Districts . 348 Table A-11.4 Median duration of breastfeeding: Districts . 349 Table A-11.6 Infant and young child feeding (IYCF) practices: Districts . 350 Table A-11.7 Prevalence of anaemia in children: Districts . 351 Table A-11.8 Micronutrient intake among children: Districts. 352 Table A-11.9 Presence of iodised salt in households: Districts . 353 Table A-11.10 Nutritional status of women: Districts . 354 Table A-11.11.1 Prevalence of anaemia in nonpregnant women: Districts . 355 Table A-11.12 Micronutrient intake among mothers: Districts . 356 Table A-12.1 Household possession of mosquito nets: Districts . 357 Table A-12.2 Use of mosquito nets by persons in the household: Districts . 358 Table A-12.3 Use of mosquito nets by children: Districts . 359 Table A-12.4 Use of mosquito nets by pregnant women: Districts . 360 Table A-12.5 Indoor residual spraying against mosquitoes: Districts . 361 Table A-12.6 Use of mosquito nets or sleeping in a house which received IRS . 362 Table A-12.7 Prophylactic use of antimalarial drugs and use of Intermittent Preventive Treatment (IPTp) by women during pregnancy: Districts . 363 Table A-12.8 Prevalence and prompt treatment of fever: Districts . 364 Table A-12.9 Type and timing of antimalarial drugs taken by children with fever: Districts 365 Table A-12.10 Percentage of children with haemoglobin <8.0 g/dl in children: Districts . 366 Table A-13.1 Knowledge of AIDS: Districts . 367 Table A-13.2 Knowledge of HIV prevention methods: Districts . 368 Table A-13.3.1 Comprehensive knowledge about AIDS: Women by districts . 369 Table A-13.3.2 Comprehensive knowledge about AIDS: Men by districts . 370 Table A-13.4 Knowledge of prevention of mother to child transmission of HIV: Districts . 371 Table A-13.5.1 Accepting attitudes toward those living with HIV/AIDS: Women by districts . 372 Table A-13.5.2 Accepting attitudes toward those living with HIV/AIDS: Men by districts . 373 Table A-13.6 Attitudes toward negotiating safer sexual relations with husband: Districts . 374 Table A-13.7 Adult support of education about condom use to prevent AIDS: Districts . 375 Table A-13.8.1 Multiple sexual partners in the past 12 months: Women by districts . 376 Table A-13.8.2 Multiple sexual partners in the past 12 months: Men by districts . 377 Table A-13.10 Payment for sexual intercourse and condom use at last paid sexual intercourse: Men by districts . 378 Table A-13.11 Male circumcision: Districts . 379 Table A-13.12 Self-reported prevalence of sexually-transmitted infections (STIs) and STI symptoms: Districts . 380 Table A-13.13 Prevalence of medical injections: Districts . 381 Table A-13.14 Comprehensive knowledge about AIDS and of a source of condoms among youth: Districts . 382 xviii | Tables and Figures Table A-13.15 Age at first sexual intercourse among youth: Districts . 383 Table A-13.16 Premarital sexual intercourse and condom use during premarital sexual intercourse among youth . 384 Table A-13.17.1 Multiple sexual partners in the past 12 months among youth: Women by districts . 385 Table A-13.17.2 Multiple sexual partners in the past 12 months among youth: Men by districts . 386 Table A-13.18 Age-mixing in sexual relationships among women age 15-19: Districts . 387 Table A-17.2.1 Control over women’s cash earnings and relative magnitude of women’s earnings: Women by districts . 389 Table A-17.2.2 Control over men’s cash earnings: Districts . 390 Table A-17.5.1 Women’s participation in decision making by background characteristics: Districts . 391 Table A-17.5.2 Men’s attitude toward wives’ participation in decision making: Districts . 392 Table A-17.6.1 Attitude toward wife beating: Women by district . 393 Table A-17.6.2 Attitude toward wife beating: Men by districts . 394 Table A-18.1 Experience of physical violence: Districts . 395 Table A-18.4 Experience of sexual violence: Districts . 396 Table A-18.8 Violence during pregnancy: Districts . 397 Table A-18.9 Degree of marital control exercised by husbands: Districts . 398 Table A-18.11 Spousal violence by district . 399 Table A-18.13 Frequency of spousal violence among those who report violence: Districts . 400 Table A-18.17 Help seeking to stop violence: Districts . 401 Table A-19.1 Children’s living arrangements and orphanhood: Districts . 402 Table A-19.2 Orphans and vulnerable children (OVC): Districts . 403 Table A-19.3 School attendance by OVC status: Districts . 404 Table A-19.4 Possession of basic material needs by orphans and vulnerable children: Districts . 405 Table A-19.7 Widows dispossessed of property: Districts . 406 Table A-19.8 External support for very sick persons: Districts . 407 Table A-19.9 External support for orphans and vulnerable children: Districts . 408 APPENDIX B SAMPLE DESIGN AND IMPLEMENTATION Table B.1 Sample allocation of clusters and households . 410 Table B.2 Sample implementation . 414 Table B.3 Sample implementation . 415 Table B.4 Coverage of HIV testing among interviewed women by social and demographic characteristics . 416 Table B.5 Coverage of HIV testing among interviewed men by social and demographic characteristics . 417 Table B.6 Coverage of HIV testing among interviewed women by sexual behaviour characteristics . 418 Table B.7 Coverage of HIV testing among interviewed men by sexual behaviour characteristics . 419 APPENDIX C ESTIMATES OF SAMPLING ERRORS Table C.1 List of selected variables for sampling errors, Malawi DHS 2010 . 423 Table C.2 Sampling errors for national sample, Malawi 2010 . 424 Table C.3 Sampling errors for urban sample, Malawi 2010 . 425 Tables and Figures | xix Table C.4 Sampling errors for rural sample, Malawi 2010 . 426 Table C.5 Sampling errors for Northern Region sample, Malawi 2010 . 427 Table C.6 Sampling errors for Central Region sample, Malawi 2010 . 428 Table C.7 Sampling errors for Southern Region sample, Malawi 2010 . 429 APPENDIX D DATA QUALITY TABLES Table D.1 Household age distribution . 431 Table D.2.1 Age distribution of eligible and interviewed women . 432 Table D.2.2 Age distribution of eligible and interviewed men . 432 Table D.3 Completeness of reporting . 433 Table D.4 Births by calendar years . 433 Table D.5 Reporting of age at death in days . 434 Table D.6 Reporting of age at death in months . 435 Table D.7 Data on siblings . 435 Table D.8 Sibship size and sex ratio of siblings . 436 APPENDIX E NUTRITIONAL STATUS OF CHILDREN: 2010 MDHS DATA ACCORDING TO THE NCHS/CDC/WHO INTERNATIONAL REFERENCE POPULATION Table E.1 Nutritional status of children . 437 Foreword | xxi FOREWORD The 2010 Malawi Demographic and Health Survey (2010 MDHS) presents the major findings of a large, nationally representative sample survey conducted by the National Statistical Office (NSO) in partnership with the Ministry of Health Community Sciences Unit (CHSU). It is the fourth survey of its kind to be conducted in Malawi, encompassing a total of 27,000 households and involving 24,000 female and 7,000 male respondents. The survey, which has expanded in sample size over the years, updates the 1992, 2000, and 2004 survey findings. The 2010 report is the second in the series to include results of HIV testing. In addition to presenting national estimates, the report provides estimates of key indicators for rural and urban areas in Malawi, the three regions, and for the first time, the 27 districts. The primary objective of the 2010 MDHS is to provide up-to-date information for policymakers, planners, researchers, and programme managers. Topics include fertility levels, nuptiality, fertility preferences, knowledge and use of family planning methods, breastfeeding practices, nutritional status of mothers and children, childhood illnesses and mortality, use of maternal and child health services, maternal mortality, and domestic violence. The survey also reports on the anaemia status of women age 15-49 and children age 6-59 months. Chapters on infectious processes cover malaria, HIV and AIDS-related knowledge and behaviour, and HIV prevalence. The 2010 MDHS results demonstrate a decline in current fertility, an increase in use of modern methods of contraception, an improvement in child vaccination rates, and expanded coverage of prior HIV testing. The NSO would like to acknowledge the efforts of a number of organizations that made the success of the 2010 survey possible. First, we would like to acknowledge the financial assistance of the government of Malawi, the United States Agency for International Development (USAID/Malawi), the President’s Emergency Plan for AIDS Relief (PEPFAR), the Centers for Disease Control and Prevention (CDC), the United Kingdom Department for International Development (DFID), the United Nations Children’s Fund (UNICEF/Malawi), and the United National Population Fund (UNFPA). We gratefully acknowledge the dedication of the core 2010 MDHS staff at NSO for managing all technical, administrative, and logistical phases of the survey. Similarly, we wish to acknowledge the technical support provided by CHSU, and we especially commend the laboratory team for their work throughout training, data collection, and HIV testing. We would also like to acknowledge ICF Macro for its technical assistance at all stages of the survey. Special mention is given to the Ministry of Health and Population, Ministry of Development Planning and Cooperation, and all members of the steering committee and various technical working groups. Finally, we wish to acknowledge the dedication and professionalism of all team members and others who worked tirelessly to produce this report. Our gratitude also goes to the survey respondents who generously gave of their time to provide the required information. Charles Machinjili Commissioner of Statistics Millennium Development Goal Indicators | xxiii MILLENNIUM DEVELOPMENT GOAL INDICATORS Goals and Indicators Value Female Male Total 1. Eradicate extreme poverty and hunger 1.8 Prevalence of underweight children under five years of age1 11.7 14.0 12.8 2. Achieve universal primary education 2.1 Net enrollment ratio in primary education2 91.5 89.9 90.7 2.3 Literacy rate of 15-24 year olds3 77.4 81.8 79.6 3. Promote gender equality and empower women 3.1a Ratio of girls to boys in primary education4 na na 1.02 3.1b Ratio of girls to boys in secondary education4 na na 1.08 3.1c Ratio of girls to boys in tertiary education4 na na 0.74 4. Reduce child mortality 4.1 Under-five mortality rate (per 1000 live births)5 99 125 112 4.2 Infant mortality rate (per 1000 live births)5 56 76 66 4.3 Proportion of 1 year-old children immunized against measles 94.3 91.7 93.0 5. Improve maternal health 5.1 Maternal mortality ratio6 675 na na 5.2 Proportion of births attended by skilled health personnel6 na na 71.4 5.3 Contraceptive prevalence rate7 46.1 32.8 na 5.4 Adolescent birth rate8 152 na na 5.5a Antenatal care coverage: at least 1 visit by skilled health professional 97.6 na na 5.5b Antenatal care coverage: at least 4 visits by any provider 45.5 na na 5.6 Unmet need for family planning 26.1 na na 6. Combat HIV/AIDS, malaria and other diseases 6.1 HIV prevalence among population aged 15-24 5.2 1.9 3.6 6.2 Condom use at last high-risk sex: youth 15-24 years9 na 40.5 49.7 6.3 Percentage of population 15-24 years with comprehensive knowledge of HIV/AIDS10 41.8 47.7 42.2 6.4 Ratio of school attendance of orphans to school attendance of non- orphans aged 10-14 years11 0.97 0.95 0.96 6.7 Percentage of children under five sleeping under ITN 40.2 38.6 39.4 6.8 Percentage of children under five with fever who are appropriately treated with anti-malarial drugs11 43.5 43.3 43.4 Value Urban Rural Total 7. Ensure environmental sustainability 7.8 Percentage of population using an improved drinking water source12 91.9 76.9 79.3 7.9 Percentage of population with access to improved sanitation13 21.9 6.5 8.8 na = Not applicable 1 Proportion of children age 0-59 months who are below -2 standard deviations (SD) from the median of the WHO Child Growth Standards in weight-for-age. 2 Based on reported attendance, not enrollment. 3 Refers to respondents who attended secondary school or higher or who could read a whole sentence or part of a sentence. The total estimate is an average of the female and male literacy rate for 15-24 year olds. 4 Based on reported net attendance not gross enrollment 5 Among births in the 5-year period before the survey 6 Based on the 5-year period before survey 7 Use of any contraceptive method among women/men married or in-union aged 15 to 49 8 Age-specific fertility rates for women age 15-19 years corresponding to the 3-year period before the survey 9 Higher-risk sex refers to sexual intercourse with two or more partners in the 12 months preceding the survey 10 A person is considered to have comprehensive knowledge about HIV/AIDS when s/he knows that consistent use of a condom during sexual intercourse and having just one HIV-negative and faithful partner can reduce the chances of getting HIV, knows that a health-looking person can have HIV, and rejects the two most common misconceptions about HIV, i.e., that HIV can be transmitted by mosquito bites and that a person can get HIV by eating from the same plate as someone who has HIV. 11 Malaria treatment is measured as the percentage of children age 0-59 months who were ill with a fever in the two weeks preceding the interview and received anti-malarial drug. 12 Percentage of de-jure population whose main source of drinking water is a household connection (piped), public standpipe, borehole, protected dug well or spring, or rainwater collection. 13 Percentage of de-jure population with access to flush toilet, ventilated improved pit latrine, traditional pit latrine with a slab, or composting toilet. xxiv | Map of Malawi Introduction | 1 INTRODUCTION 1 1.1 GEOGRAPHY, HISTORY, AND THE ECONOMY 1.1.1 Geography Malawi is a sub-Saharan African country located south of the equator. It is bordered to the north and northeast by the United Republic of Tanzania; to the east, south, and southwest by the People’s Republic of Mozambique; and to the west and northwest by the Republic of Zambia. The country is 901 kilometres long and 80 to 161 kilometres wide. The total area is approximately 118,484 square kilometres of which 94,276 square kilometres is land. The remaining area is mostly composed of Lake Malawi, which is about 475 kilometres long and delineates Malawi’s eastern boundary with Mozambique. Malawi’s most striking topographic feature is the Rift Valley, which runs the entire length of the country, passing through Lake Malawi in the Northern and Central Regions to the Shire Valley in the south. The Shire River drains the water from Lake Malawi into the Zambezi River in Mozambique. To the west and south of Lake Malawi lay fertile plains and mountain ranges whose peaks range from 1,700 to 3,000 metres above sea level. The country is divided into three regions: the Northern, Central, and Southern Regions. There are 28 districts in the country. Six districts are in the Northern Region, nine are in the Central Region, and 13 are in the Southern Region. Administratively, the districts are subdivided into traditional authorities (TAs), presided over by chiefs. Each TA is composed of villages, which are the smallest administrative units, and the villages are presided over by village headmen. Malawi has a tropical continental climate with maritime influences. Rainfall and temperature vary depending on altitude and proximity to the lake. From May to August, the weather is cool and dry. From September to November, the weather becomes hot. The rainy season begins in October or November and continues until April. 1.1.2 History Malawi was ruled by Britain and known as the Nyasaland protectorate from 1891 until July 1964. In 1953, the Federation of Rhodesia and Nyasaland was created, which was composed of three countries, Southern Rhodesia (now Zimbabwe), Northern Rhodesia (now Zambia), and Nyasaland (now Malawi). In July 1964, Nyasaland became the independent state of Malawi, which gained republic status in 1966. 1.1.3 Economy The economy of Malawi is based primarily on agriculture, which accounts for 30 percent of the gross domestic product (GDP). The country’s major exports are tobacco, tea, and sugar. They account for approximately 85 percent of Malawi’s domestic exports. In 2009, the agricultural sector achieved growth of 13.9 percent. Tobacco production was high following favourable prices that were offered at auction in the 2008 marketing season. In 2010, estimated growth slowed to 1.3 percent because of dry spells and heavy rains. Malawi experienced a food surplus during the 2008-2009 growing season due to favourable weather and the benefits of the government’s Farm Input Subsidy Programme (FISP). These events led to the financial growth that occurred during the 2009-2010 fiscal year. 2 | Introduction 1.2 POPULATION The major source of historical demographic data comes from the population census, which took place approximately every ten years from 1891 to 1931. After World War II, the population censuses were conducted in 1945, 1966, 1977, 1987, 1998, and 2008. Other sources of population data include nationwide surveys, such as the 1992 Malawi Demographic and Health Survey (MDHS); the 1996 Malawi Knowledge, Attitudes, and Practices in Health survey (MKAPH); the 2000 MDHS, and the 2004 MDHS. Table 1.1 shows data for demographic indicators for Malawi between 1966 and 2008. Table 1.1 Demographic indicators Selected demographic indicators, Malawi Population and Housing Census, 1966-2008 Indicators Census 1966 Census 1977 Census 1987 Census 1998 Census 2008 Population (millions) 4,039,583 5,547,460 7,988,507 9,933,868 13,077,160 Intercensal growth rate 3.3 2.9 3.7 2.0 2.8 Density (pop/sq.km) 43 59 85 105 139 Percentage of urban population 5.0 8.5 10.7 14.0 15.3 Women of childbearing age as a percentage of female population 47.6 45.1 44.2 47.2 44.4 Sex ratio 90.0 93.0 94.0 96.0 94.7 Crude birth rate na 48.3 41.2 37.9 39.5 Crude death rate na 25.0 14.1 21.1 10.4 Male na 39.2 41.4 40.0 48.3 Female na 42.4 44.6 44.0 51.4 na = Not available The population of Malawi grew from 8.0 million in 1987 to 9.9 million in 1998. The 2008 Population and Housing Census found the population to be 13.1 million, representing an increase of 32 percent, or an intercensal population growth rate of 2.8 percent per year. Population density increased from 105 persons per square kilometre in 1998 to 139 persons per square kilometre in 2008. Malawi adopted in 1994 a National Population Policy, which was designed to reduce population growth to a level compatible with Malawi’s social and economic goals (OPC, 1994). The policy’s objectives are to improve family planning and health care programmes, to increase school enrolment (with emphasis on raising the proportion of female students to half of total enrolment), and to increase employment opportunities, particularly in the private sector. Also in 1994, Malawi adopted a multiparty system and a strategy to eradicate poverty. The Malawi Growth and Development Strategy (MGDS) is a five-year strategy launched in July 2007 to reduce poverty. The MGDS is the overarching development strategy for the country. 1.3 OBJECTIVE OF THE SURVEY The 2010 Malawi Demographic and Health Survey (2010 MDHS) was implemented by the National Statistical Office (NSO) from June through November 2010, with a nationally representative sample of more than 27,000 households. All eligible women age 15-49 in these households and all eligible men age 15-54 in a subsample of one-third of the households were individually interviewed. The survey is a follow-up to the 1992, 2000, and 2004 MDHS surveys, although it expands the content and provides updated estimates of basic demographic and health indicators covered in these earlier surveys. Similar to the 2004 MDHS survey, the 2010 MDHS includes information on violence against women and HIV testing among women age 15-49 and men age 15-54. Although previous surveys collected data at the national, regional, and selected district levels, the 2010 MDHS is the first MDHS survey to collect data on basic demographic and health indicators at the district level. Introduction | 3 The primary objectives of the 2010 MDHS project are to provide up-to-date information on fertility levels; nuptiality; sexual activity; fertility preferences; awareness and use of family planning methods; breastfeeding practices; nutritional status of mothers and young children; early childhood mortality; maternal mortality; maternal and child health; malaria; awareness and behaviour regarding HIV/AIDS and other sexually transmitted infections; and HIV prevalence. 1.4 ORGANISATION OF THE SURVEY The 2010 MDHS survey was a comprehensive survey that involved several agencies. The survey was implemented by the National Statistical Office (NSO) and the Community Health Sciences Unit (CHSU). The funding for the MDHS was provided by the Government of the Republic of Malawi, the National AIDS Commission (NAC), the United Nations Population Fund (UNFPA), the United Nations Children’s Fund (UNICEF), the United Kingdom’s Department for International Development (DFID), the Centers for Disease Control and Prevention (CDC), and the United States Agency for International Development (USAID). Technical assistance was provided by ICF Macro through the MEASURE DHS programme, a USAID-funded project. 1.5 SAMPLE DESIGN The sample for the 2010 MDHS was designed to provide population and health indicator estimates at the national, regional, and district levels. The sample design allowed for specific indicators, such as contraceptive use, to be calculated for each of the country’s 3 regions and 27 districts (Nkhata Bay and Likoma are combined). The sampling frame used for the 2010 MDHS was the 2008 Malawi Population and Housing Census (PHC), which was provided by the National Statistical Office. Administratively, Malawi is divided into 28 districts. Each district is subdivided into smaller administrative units. During the 2008 PHC, which was designed and carried out by the National Statistical Office, each of the districts was subdivided into enumeration areas (EAs), also referred to as clusters, where each EA as a whole was classified as urban or rural. The 2010 MDHS sample was selected using a stratified, two-stage cluster design, with EAs being the sampling units for the first stage. The 2010 MDHS sample included 849 clusters: 158 in urban areas and 691 in rural areas.1 The 849 clusters were not allocated among the districts in proportion to their contribution to the national population because this would have left smaller districts and regions with too few clusters to represent them. For example, districts in the Northern Region were oversampled to take into account its smaller population size. In most districts in Malawi, more than 90 percent of the population resides in rural areas, so urban areas were also oversampled. A complete listing of households was done in each of the MDHS clusters from May to June 2009. The list of households served as a sampling frame for selection of households. Households comprised the second stage of sampling. A minimum sample size of 950 households was required per district to provide an acceptable level of precision for the indicators measured in the survey. A representative sample of 27,345 households was selected for the 2010 MDHS survey. A subsample of one-third of the households was selected to conduct HIV testing for eligible women age 15-49 and eligible men age 15-54. In the same subsample of households, anaemia testing was conducted for eligible children age 6-59 months and eligible women age 15-49 years, and anthropometric measures were taken for eligible children age 0-5 years and eligible women age 15- 1 The final survey sample included all of the selected 849 clusters. However, during fieldwork some of these clusters were found to be dramatically smaller than they were at the time of listing. The sample size did not reach the expected number of households for eight clusters, despite selecting every household in these clusters, resulting in a net decrease of 38 households between the sample design and fieldwork. 4 | Introduction 49. Additionally, domestic violence questions were asked of one eligible woman per household in the same subsample of households. 1.6 QUESTIONNAIRES Three questionnaires were used for the 2010 MDHS: the Household Questionnaire, the Woman’s Questionnaire, and the Man’s Questionnaire. These questionnaires were adapted to reflect the population and health issues relevant to Malawi. Issues were identified at a series of meetings with various stakeholders from government ministries and agencies, nongovernmental organisations, and development partners. In addition to English, the questionnaires were translated into two major languages, Chichewa and Tumbuka. The Household Questionnaire was used to list all the usual members and visitors of selected households. Basic information was collected on the characteristics of each person listed, including his or her age, sex, education, and relationship to the head of the household. For children under age 18, survival status of the parents was determined. If a child in the household had a parent who was sick for more than three consecutive months in the 12 months preceding the survey or had a parent who had died during the 12 months preceding the survey, additional questions relating to support for orphans and vulnerable children were asked. Further, if an adult in the household was sick for more than three consecutive months in the 12 months preceding the survey or an adult in the household had died in the past 12 months, questions were asked relating to support for sick people or those who have died. The data on the age and sex of household members obtained in the Household Questionnaire was used to identify women and men who were eligible for the individual interview. Additionally, the Household Questionnaire collected information on characteristics of the household’s dwelling unit, such as the source of water, type of toilet facilities, materials used for the floor of the house, ownership of various durable goods, and ownership and use of mosquito nets (to assess the coverage of malaria prevention programmes). The Household Questionnaire was also used to record height and weight measurements for eligible children age 0-59 months and eligible women age 15-49 years. The Woman’s Questionnaire was used to collect information from all eligible women age 15- 49. These women were asked questions on the following main topics: • Background characteristics (education, residential history, media exposure, etc.) • Birth history and childhood mortality • Knowledge and use of family planning methods • Fertility preferences • Antenatal, delivery, and postnatal care • Breastfeeding and infant feeding practices • Women’s and children’s nutritional status • Vaccinations and childhood illnesses • Marriage and sexual activity • Women’s work and husband’s background characteristics • Malaria prevention and treatment • Awareness and behaviour regarding AIDS and other sexually transmitted infections (STIs) • Adult mortality, including maternal mortality • Domestic violence The Man’s Questionnaire was administered to all eligible men age 15-54 in every third household in the 2010 MDHS sample. This questionnaire collected much of the same information found in the Woman’s Questionnaire but was shorter because it did not contain a detailed reproductive history or questions on maternal and child health or nutrition. Introduction | 5 1.7 HIV AND ANAEMIA TESTING In a subsample of one-third of all households, blood specimens were collected for anaemia testing from children age 6-59 months and women age 15-49 years who voluntarily consented to the testing. Additionally, in every third household, blood specimens were collected for HIV testing from all women age 15-49 and men age 15-54 who consented to the test. The protocol for the blood specimen collection and the testing for HIV was reviewed and approved by the Malawi Health Sciences Research Committee, the Institutional Review Board of ICF Macro, and the Centres for Disease Control and Prevention (CDC) in Atlanta. Women and men who were interviewed in the 2010 MDHS were asked to voluntarily provide five drops of blood for HIV testing. The protocol for the blood specimen collection and analysis was based on the anonymous linked protocol developed for MEASURE DHS. This protocol allows for the merging of the HIV test results with the sociodemographic data collected in the individual questionnaires, provided that information that could potentially identify an individual is destroyed before data linking takes place. Interviewers explained the procedure, the confidentiality of the data, and the fact that the test results would not be made available to the respondent. They also explained the option of dried blood spot (DBS) storage for use in additional testing. If a respondent consented to the HIV testing, five blood spots from the finger prick were collected on a filter paper card to which a bar code label unique to the respondent was affixed. If the respondent did not consent to additional testing using their sample, it was indicated on the questionnaire that the respondent refused additional tests using their specimen, and the words ‘no further testing’ were written on the filter paper card. Each household, whether individuals consented to HIV testing or not, was given an information brochure on HIV/AIDS and a list of fixed sites providing voluntary counselling and testing (VCT) services in surrounding districts within the region. Each DBS sample was given a bar code label, with a duplicate label attached to the Individual Questionnaire. A third copy of the same bar code was affixed to the Blood Sample Transmittal Form to track the blood samples from the field to the laboratory. DBS samples were dried overnight and packaged for storage the following morning. Samples were periodically collected in the field, along with the corresponding completed questionnaires for each completed cluster, and transported to the NSO in Zomba to be logged in, checked, and then transported to the Community Health Sciences Unit (CHSU) in Lilongwe. Upon arrival at CHSU, each DBS sample was logged into the CSPro HIV Test Tracking System (CHTTS) database, given a laboratory number, and stored at -20˚C until tested. According to the HIV testing protocol, testing on all samples could only be conducted after all of the questionnaire data entry was completed, verified, and cleaned, and all unique identifiers were removed from the questionnaire file except the barcode number. HIV testing began in February 2011. The testing protocol was to test all samples on the first assay test, an ELISA, Vironostika® HIV Uni-Form II Plus O, Biomerieux. A negative result was considered negative. All samples with positive results were subjected to a second ELISA test by Enzygnost® Anti-HIV 1/2 Plus, Dade Behring. Positive samples on the second test were considered positive. If the first and second tests were discordant, the sample was retested with tests 1 and 2. If on repetition of tests 1 and 2, both results were negative, the sample was rendered negative. If both results were positive, the sample was rendered positive. If there was still a discrepancy in the results after repeating tests 1 and 2, a third confirmatory test, Western Blot 2.2, Abbott Labs, was administered. The final result was rendered positive if the Western Blot (WB) confirmed the result to be positive and rendered negative if the WB confirmed it to be negative. If the Western Blot results were indeterminate, the sample was rendered indeterminate. Upon finalising HIV testing, the HIV test results for the 2010 MDHS were entered into a spreadsheet with a barcode as the unique identifier to the result. Data from the HIV results and linked demographic and health data are included in this 2010 MDHS Final Report. 6 | Introduction 1.8 PRETEST The training for the pretest took place from January through February 2010. Twelve interviewers (six females and six males) and five supervisors were trained to administer the questionnaires. Two laboratory scientists from CHSU and a biomarker specialist from ICF Macro trained interviewers to take anthropometric measurements and collect blood for anaemia and HIV testing. The pretest training for the interviewers and supervisors focused on survey objectives, techniques of interviewing, field procedures, and all sections of the household and individual questionnaires. Blood specimen collection procedures were demonstrated and practiced, and two days of field practice were held. The trainers/resource persons included professionals from NSO and ICF Macro. The pretest fieldwork was conducted in the Northern, Central, and Southern Regions of Malawi by three teams. The teams were divided according to languages spoken by team members. There was one Tumbuka team in the North and two Chichewa teams, one each in the Central and the Southern Regions. The supervisors and editors were drawn from the NSO core technical team. The teams covered 12 enumeration areas, half in urban areas and half in rural areas. At the end of the fieldwork, a debriefing session was held at NSO among all staff involved in the pretest, and the questionnaires were amended based on the pretest findings. 1.9 TRAINING OF FIELD STAFF NSO recruited and trained 318 people for the fieldwork to serve as supervisors, field editors, female and male interviewers, reserve interviewers, and quality control interviewers. Training of field staff for the main survey was conducted during a four-week period in May through June 2010. Specialists in various areas such as HIV/AIDS, malaria, and family planning were invited as guest lecturers. The training course consisted of instruction regarding interviewing techniques and field procedures, a detailed review of items on the questionnaires, instruction and practice in weighing and measuring children, mock interviews between participants in the classroom, and practice interviews with real respondents in areas outside the 2010 MDHS sample points. During this period, field editors, team supervisors, and quality control interviewers were provided with additional training in methods of field editing, data quality control procedures, and fieldwork coordination. Thirty-seven supervisors, 37 editors, 148 female interviewers, and 74 male interviewers were selected to make up 37 data collection teams for the 2010 MDHS. Six people were selected to be quality control interviewers. 1.10 FIELDWORK Thirty-seven interviewing teams carried out data collection for the 2010 MDHS. Each team consisted of one supervisor (team leader), one field editor, four female interviewers, two male interviewers, and one driver. Six senior staff members from NSO, one ICF Macro resident advisor, and one ICF Macro consultant coordinated and supervised fieldwork activities. Data collection took place over a six-month period, from June through November 2010. 1.11 DATA PROCESSING All questionnaires for the 2010 MDHS were returned to the NSO headquarters office in Zomba for data processing, which consisted of office editing, coding of open-ended questions, data entry, and editing computer-identified errors. The data were processed by a team of 38 data entry operators, 6 office editors, and 3 data entry supervisors. Data entry and editing were accomplished using the CSPro software. The processing of data began in June 2010 and was completed in December 2010. Introduction | 7 1.12 RESPONSE RATES The household and individual response rates for the 2010 MDHS are shown in Table 1.2. For the sample, a total of 27,307 households were selected, and of these, 25,311 were occupied. Of the 25,311 households found, 24,825 were successfully interviewed, yielding a response rate of 98 percent. In the interviewed households, a total of 23,748 women were identified to be eligible for the individual interview, of which 97 percent were successfully interviewed. Among men, 7,783 were identified as eligible, and 92 percent were successfully interviewed. Table 1.2 Results of the household and individual interviews Number of households, number of interviews, and response rates, according to residence (unweighted), Malawi 2010 Result Residence Total Urban Rural Household interviews Households selected 3,157 24,150 27,307 Households occupied 2,965 22,346 25,311 Households interviewed 2,909 21,916 24,825 Household response rate1 98.1 98.1 98.1 Interviews with women age 15-49 Number of eligible women 3,179 20,569 23,748 Number of eligible women interviewed 3,068 19,952 23,020 Eligible women response rate2 96.5 97.0 96.9 Interviews with men age 15-54 Number of eligible men 1,130 6,653 7,783 Number of eligible men interviewed 1,014 6,161 7,175 Eligible men response rate2 89.7 92.6 92.2 1 Households interviewed/households occupied 2 Respondents interviewed/eligible respondents Household Population and Housing Characteristics | 9 HOUSEHOLD POPULATION AND HOUSING CHARACTERISTICS 2 This chapter summarises demographic and socioeconomic characteristics of the population in households sampled during the 2010 MDHS. Information on housing characteristics is also provided. For the 2010 MDHS, a household was defined as a person or a group of persons, related or unrelated, who live together and share common cooking and eating arrangements. The Household Questionnaire included a schedule for collecting basic demographic and socioeconomic information (e.g., age, sex, educational attainment, and current school attendance) for all usual residents and visitors who slept in the household the night preceding the interview. This method of data collection allowed for analysis of the results for either the de jure population (usual residents) or the de facto population (persons in the household at the time of the survey). The Household Questionnaire also was used to obtain information on housing facilities, including dwelling characteristics, source of water supply, sanitation facilities, and household assets. The information in this chapter is intended to facilitate interpretation of key demographic, socioeconomic, and health indices presented later in the report. It will also assist in the assessment of the representativeness of the survey sample.1 2.1 HOUSEHOLD POPULATION BY AGE, SEX, AND RESIDENCE Age and sex, which are important demographic variables, are the primary basis for demographic classification. They are also important variables in the study of mortality, fertility, and nuptiality. The distribution by five-year age groups of the de facto household population in the 2010 MDHS is shown in Table 2.1, according to sex and residence. The 24,825 households successfully interviewed in the 2010 MDHS consisted of 113,574 persons; 58,414 were women representing 51 percent of the population, and 55,159 were men, representing 49 percent of the population. The distribution shows that the younger age groups make up the higher proportion of the household population in both urban and rural areas. Sixty-seven percent of the total population is under age 25, while 4 percent of the population is age 65 or older. Table 2.1 Household population by age, sex, and residence Percent distribution of the de facto household population by five-year age groups, according to sex and residence, Malawi 2010 Age Urban Rural Total Male Female Total Male Female Total Male Female Total <5 14.5 15.0 14.8 17.8 17.4 17.6 17.3 17.0 17.2 5-9 14.4 15.2 14.8 18.0 17.1 17.5 17.4 16.8 17.1 10-14 11.9 12.9 12.4 15.7 14.5 15.1 15.1 14.3 14.7 15-19 12.3 11.2 11.7 10.3 8.6 9.4 10.6 9.0 9.8 20-24 10.8 10.9 10.9 6.9 7.6 7.3 7.6 8.1 7.8 25-29 10.7 11.0 10.8 6.1 7.2 6.6 6.8 7.7 7.3 30-34 8.3 7.3 7.8 5.2 5.5 5.4 5.7 5.8 5.8 35-39 5.7 4.4 5.1 4.7 4.4 4.5 4.8 4.4 4.6 40-44 3.2 3.0 3.1 3.1 3.1 3.1 3.1 3.1 3.1 45-49 2.4 2.7 2.6 2.7 2.7 2.7 2.6 2.7 2.7 50-54 1.9 2.2 2.1 2.2 2.8 2.5 2.2 2.7 2.5 55-59 1.4 1.2 1.3 1.9 2.2 2.1 1.8 2.1 1.9 60-64 1.2 1.1 1.1 1.8 2.0 1.9 1.7 1.9 1.8 65-69 0.5 0.8 0.7 1.2 1.5 1.3 1.1 1.4 1.2 70-74 0.4 0.4 0.4 0.9 1.2 1.1 0.8 1.1 1.0 75-79 0.3 0.2 0.2 0.7 1.0 0.9 0.6 0.9 0.8 80+ 0.2 0.3 0.3 0.7 1.2 0.9 0.6 1.0 0.8 Don’t know/ missing 0.0 0.0 0.0 0.0 0.1 0.0 0.0 0.0 0.0 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Number 9,079 8,817 17,896 46,080 49,597 95,677 55,159 58,414 113,574 1 The survey results in this chapter are presented for the country as a whole, by urban-rural residence, and by region. District-level results are available in Appendix A. 10 | Household Population and Housing Characteristics Figure 2.1 illustrates the age structure of the Malawi household population in a population pyramid. A feature of population pyramids is their strength in illustrating whether a population is young or old. The broad base of the pyramid indicates that Malawi’s population is young. This scenario is typical of countries with high fertility rates. Figure 2.1 Population Pyramid MDHS 2010 80+ 75-79 70-74 65-69 60-64 55-59 50-54 45-49 40-44 35-39 30-34 25-29 20-24 15-19 10-14 5-9 <5 Ag e g r ou p 0246810 0 2 4 6 8 10 Percent MaleFemale 2.2 HOUSEHOLD COMPOSITION Information on key aspects of household composition, including sex of the household head and size of the household, is presented in Table 2.2. These characteristics are important because they are associated with household welfare. Female-headed households are, for example, typically poorer than male-headed households. Economic resources are often more limited in larger households. Moreover, where the size of the household is large, crowding also can lead to health problems. Table 2.2 shows that households in Malawi are predominantly headed by men (72 percent). This figure has remained relatively constant through all of the DHS surveys in Malawi: it was 75 percent in 1992, 73 percent in 2000, and 75 percent in 2004. Households headed by women are more common in rural areas (30 percent) than in urban areas (21 percent). The 2010 MDHS results indicate that the average household size is 4.6 persons, with rural households (4.7 persons) having slightly more members than urban households (4.4 persons). This shows that a modest increase in household size has occurred in the five years since the 2004 MDHS when households averaged 4.4 household members. Table 2.2 further provides information on the proportion of households with foster children (that is, children who live in households with neither biological parent present), double orphans (children with both parents dead), and single orphans (children with one parent dead). Overall, 33 percent of households contain foster children or orphans. The proportion of households with foster children (28 percent) is higher than the proportion with double orphans (4 percent) or the proportion with single orphans (15 percent). There are no differences across urban and rural areas in the proportion of households with foster children and orphans. Household Population and Housing Characteristics | 11 Table 2.2 Household composition Percent distribution of households by sex of head of household and by household size; mean size of household, and percentage of households with orphans and foster children under 18, according to residence, Malawi 2010 Characteristic Residence Total Urban Rural Household headship Male 79.3 70.5 71.9 Female 20.7 29.5 28.1 Total 100.0 100.0 100.0 Number of usual members 0 0.1 0.1 0.1 1 8.8 6.4 6.8 2 11.3 9.6 9.9 3 17.7 15.7 16.1 4 17.5 18.3 18.2 5 16.6 16.7 16.7 6 11.1 13.8 13.4 7 7.0 9.2 8.9 8 5.3 5.1 5.1 9+ 4.5 5.0 5.0 Total 100.0 100.0 100.0 Mean size of households 4.4 4.7 4.6 Percentage of households with orphans and foster children under 18 Foster children1 27.8 27.9 27.9 Double orphans 5.1 4.3 4.4 Single orphans2 14.5 14.7 14.7 Foster and/or orphan children 32.6 33.3 33.2 Number of households 4,116 20,709 24,825 Note: Table is based on de jure household members, i.e., usual residents. 1 Foster children are those under age 18 living in households where neither their mother nor their father is a de jure resident. 2 Includes children with one dead parent and an unknown survival status of the other parent. 2.3 EDUCATION OF HOUSEHOLD POPULATION Education is a key determinant of the lifestyle and societal status an individual enjoys. Studies have consistently shown that educational attainment is strongly associated with health-related behaviours and attitudes. In the 2010 MDHS, information on education, including school attendance and educational attainment, was collected for every household member. In Malawi, official primary school age is age 6-13; students enter primary school at age 6. They stay in primary school for eight years, and at the end they sit for a Primary School Leaving Certificate (PSLCE). Students who receive the certificate qualify to start secondary education; the official age for the secondary school level is age 14-17. Secondary school lasts four years and is divided into two sets of two-year courses. At the end of the first two years, students sit for the Junior Certificate of Education (JCE). At the end of the second set of courses, they sit for the Malawi School Certificate of Education (MSCE) and the General School Certificate of Education (GCSE). Tertiary education consists of public and private universities and technical colleges. 2.3.1 Educational Attainment Tables 2.3.1 and 2.3.2 present data on educational attainment for female and male household members age 6 and older. Results from both tables indicate that, overall, more females than males have never attended school (19 percent compared with 11 percent). Figure 2.2 shows the percentage of males and females who have never attended school by age group. The proportion that has never attended school is higher for females than for males across all age groups except for those under age 14. The proportion of respondents with some primary education is about the same among men (65 percent) and women (64 percent), as is the proportion of men and women completing the primary 12 | Household Population and Housing Characteristics level of education (7 percent each). However, more men than women have attended or completed secondary education (17 percent compared to 11 percent). There are some urban-rural differences in educational attainment. More than 20 percent of the women in rural areas (21 percent) have no education at all; in comparison, 9 percent of women in urban areas lack education. The trend is the same for men; 13 percent in rural areas have no education, which compares with 5 percent in urban areas. With the exception of the youngest age group, some of whom will begin to attend school in the future, the proportion with no education increases steadily with age for both men and women. For example, the proportion of women who have never attended any formal schooling increases from 11 percent among those age 25-29 to 60 percent among those age 65 and older. For men, the proportion increases from 7 percent for those age 25-29 to 31 percent for those age 65 and older. The proportion of the population that has attained education varies greatly by region. The Southern and Central Regions have higher proportions of women without education, 21 percent and 20 percent respectively, compared with 9 percent in the Northern Region. Among men, 12 and 13 percent in the Southern and Central Regions, respectively, have never attended school while 5 percent in the Northern Region have no education. As expected, the proportion with no education consistently declines as wealth quintile level increases. The median number of years of schooling completed is 2.5 years for women and 3.5 years for men. This number is much higher in urban areas than in rural areas: 5.3 years compared with 2.1 for women, and 6.9 years compared with 3.0 for men. Median years of schooling completed increases steadily with increasing wealth quintile index for both men and women. Median years completed also varies across the regions of Malawi, with the Northern Region having the highest figures (4.3 for women and 4.9 for men), followed by the Southern Region (2.3 for women and 3.3 for men), and finally the Central Region (2.2 for women and 3.2 for men). Overall there has been progress in educational attainment since the 2004 MDHS: the proportion with no education has decreased, and the proportion with primary education has increased. In the 2004 MDHS, 30 percent of women and 20 percent of men had no education at all; these proportions have decreased to 19 percent and 11 percent. The median number of school years completed has increased from 3.1 to 3.5 for men and from 1.8 to 2.5 for women. Household Population and Housing Characteristics | 13 Table 2.3.1 Educational attainment of the female household population Percent distribution of the de facto female household populations age six and over by highest level of schooling attended or completed and median years completed, according to background characteristics, Malawi 2010 Background characteristic No education Some primary Completed primary1 Some secondary Completed secondary2 More than secondary Don’t know/ missing Total Number Median years completed Age 6-9 18.6 80.7 0.1 0.0 0.0 0.0 0.6 100.0 7,790 0.4 10-14 2.7 88.0 7.7 1.2 0.0 0.0 0.3 100.0 8,343 2.8 15-19 3.5 59.6 14.0 19.2 3.1 0.5 0.2 100.0 5,267 5.7 20-24 7.8 54.7 10.0 15.8 8.7 2.6 0.4 100.0 4,724 5.7 25-29 10.7 55.9 8.9 13.4 8.3 2.5 0.1 100.0 4,518 5.5 30-34 18.1 55.1 7.7 9.5 7.9 1.6 0.1 100.0 3,371 3.9 35-39 30.6 53.3 6.2 4.8 3.3 1.8 0.1 100.0 2,567 2.4 40-44 34.5 50.8 6.3 4.5 1.5 2.2 0.2 100.0 1,791 2.2 45-49 37.7 52.0 5.9 2.1 1.3 0.8 0.2 100.0 1,599 1.5 50-54 44.7 46.7 3.8 2.2 1.0 0.8 0.8 100.0 1,605 0.5 55-59 49.2 43.9 3.1 1.5 0.2 1.2 1.0 100.0 1,207 0.0 60-64 52.6 42.0 2.7 0.7 0.0 0.9 1.1 100.0 1,092 0.0 65+ 59.6 36.8 1.0 0.3 0.1 0.1 2.2 100.0 2,565 0.0 Residence Urban 8.5 54.2 7.1 15.6 9.6 4.9 0.2 100.0 7,155 5.3 Rural 20.7 65.3 6.5 5.0 1.7 0.3 0.5 100.0 39,310 2.1 Region Northern 9.1 69.0 9.1 8.8 3.1 0.5 0.4 100.0 5,491 4.3 Central 19.8 64.0 6.4 6.0 2.6 0.8 0.4 100.0 20,060 2.2 Southern 20.5 61.7 6.0 6.7 3.2 1.3 0.5 100.0 20,913 2.3 Wealth quintile Lowest 29.8 63.4 4.6 1.5 0.2 0.0 0.5 100.0 9,692 1.0 Second 24.6 65.4 6.3 2.8 0.4 0.0 0.5 100.0 9,217 1.6 Middle 18.7 67.8 7.6 4.5 0.9 0.0 0.5 100.0 9,063 2.3 Fourth 14.8 67.4 7.4 7.6 2.2 0.2 0.5 100.0 9,176 3.0 Highest 5.9 54.1 7.0 17.0 11.0 4.7 0.3 100.0 9,317 5.9 Total 18.9 63.6 6.5 6.7 2.9 1.0 0.5 100.0 46,465 2.5 Note: Total includes 28 unweighted cases with information missing on educational attainment. 1 Completed 8th grade at the primary level 2 Completed 4th grade at the secondary level Table 2.3.2 Educational attainment of the male household population Percent distribution of the de facto male household populations age six and over by highest level of schooling attended or completed and median years completed, according to background characteristics, Malawi 2010 Background characteristic No education Some primary Completed primary1 Some secondary Completed secondary2 More than secondary Don’t know/ missing Total Number Median years completed Age 6-9 20.5 78.8 0.1 0.0 0.0 0.0 0.6 100.0 7,652 0.4 10-14 4.1 88.8 6.3 0.4 0.0 0.0 0.3 100.0 8,331 2.6 15-19 4.4 62.3 13.4 17.4 2.0 0.2 0.2 100.0 5,842 5.4 20-24 5.3 45.5 6.9 23.7 14.8 3.5 0.3 100.0 4,170 7.2 25-29 7.4 46.5 8.2 16.8 16.3 4.7 0.1 100.0 3,773 6.9 30-34 9.3 46.8 6.4 15.6 18.0 3.7 0.2 100.0 3,161 6.9 35-39 12.3 52.8 7.1 10.6 13.1 3.9 0.2 100.0 2,673 5.8 40-44 13.5 57.3 7.0 8.9 8.2 4.9 0.2 100.0 1,709 5.9 45-49 15.1 61.8 6.9 7.3 4.9 3.8 0.3 100.0 1,460 4.9 50-54 17.2 59.2 8.0 6.9 5.2 3.0 0.5 100.0 1,189 5.0 55-59 21.2 56.6 7.4 6.0 5.3 3.0 0.6 100.0 997 4.0 60-64 29.2 52.4 6.4 5.9 4.0 1.3 0.9 100.0 955 2.8 65+ 30.9 55.9 6.0 4.0 1.2 0.8 1.2 100.0 1,736 1.8 Residence Urban 4.7 49.4 5.7 17.1 16.3 6.5 0.2 100.0 7,459 6.9 Rural 12.8 67.8 6.7 7.5 4.0 0.8 0.4 100.0 36,209 3.0 Region Northern 5.2 68.2 8.0 11.3 5.8 1.2 0.3 100.0 5,230 4.9 Central 12.5 65.1 6.8 8.3 5.6 1.4 0.3 100.0 19,158 3.2 Southern 12.0 63.3 5.8 9.4 6.6 2.3 0.5 100.0 19,279 3.3 Wealth quintile Lowest 20.2 69.6 5.5 3.5 0.8 0.0 0.4 100.0 7,742 1.8 Second 16.5 70.0 6.6 5.0 1.4 0.0 0.5 100.0 8,486 2.4 Middle 10.7 71.0 7.5 7.5 3.0 0.1 0.4 100.0 8,653 3.1 Fourth 8.6 66.2 7.2 11.1 6.0 0.5 0.5 100.0 9,153 4.0 Highest 3.2 48.9 5.9 16.9 17.3 7.5 0.2 100.0 9,634 7.1 Total 11.4 64.7 6.5 9.1 6.1 1.8 0.4 100.0 43,668 3.5 Note: Total includes 21 unweighted cases with information missing on educational attainment. 1 Completed 8th grade at the primary level 2 Completed 4th grade at the secondary level 14 | Household Population and Housing Characteristics Figure 2.2 Distribution of Household Population with No Education by Sex MDHS 2010 6-9 10-14 15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59 60-64 65+ Age 0 20 40 60 80 Percent Female Male 2.3.2 School Attendance Rates The 2010 MDHS collected information that allows the calculation of net attendance ratios (NARs) and gross attendance ratios (GARs). The NAR for primary school is the percentage of the primary-school-age population (age 6-13) that is attending primary school. The NAR for secondary school is the percentage of the secondary-school-age population (age 14-17) that is attending secondary school. By definition, the NAR cannot exceed 100 percent. The GAR for primary school is the total number of primary school students, of any age, expressed as a percentage of the official primary-school-age population. The GAR for secondary school is the total number of secondary school students, of any age, expressed as a percentage of the official secondary-school-age population. If there are significant numbers of overage and underage students at a given level of schooling, the GAR can exceed 100 percent. Youth are considered to be attending school currently if they attended formal academic school at any point during the given school year. The gender parity index (GPI) assesses sex-related differences in school attendance rates and is calculated by dividing the GAR for females by the GAR for males. A GPI that is less than one indicates a gender disparity in favor of males (i.e., a higher proportion of males than females attends that level of schooling). A GPI that exceeds one indicates a gender disparity in favor of females. A GPI of one indicates parity or equality between the rates of participation for males and females. Table 2.4 shows the NARs and GARs for the de facto household population by sex, level of schooling, and GPI, according to background characteristics. Results show that the overall NAR for primary schools is 91 percent, while the GAR is 152 percent. This is an improvement from the 2004 MDHS figures, which indicated an overall primary NAR of 82 percent and a GAR of 106 percent. The primary NAR is slightly higher for female children (92 percent) than for male children (90 percent), and the GAR is higher for males than for females. This might indicate that there are more underage or overage male students attending primary school as compared with females. The primary gender parity index for GAR of 0.95 indicates that there are more male students than female students attending primary school. The same trend was observed in the 2004 MDHS where the GPI was 0.94. There are variations in primary NAR, GAR, and GPI between urban and rural households. Overall, the NAR is higher for urban populations (95 percent) than for rural populations (90 percent). Household Population and Housing Characteristics | 15 The GAR is also slightly higher in urban areas than in rural areas (154 and 152 percent, respectively). Across the regions, the primary school NAR is higher in the Northern Region (97 percent) and lower in the Central and Southern Regions (90 percent in both). Similarly, the primary school GAR is higher in the Northern Region (165 percent) than in the Southern and Central Regions (150 percent in both). There is a consistent increase in the primary NAR and GAR as the wealth quintile index increases. Results for the 2010 MDHS show that the secondary school NAR has increased from 11 percent in the 2004 MDHS to 12 percent, while the GAR has decreased from 30 percent in the 2004 MDHS to 20 percent. The secondary NAR is slightly higher for females than males (13 and 12 percent, respectively), while there is a more pronounced difference between males and females for secondary GAR (22 and 17 percent, respectively). The overall secondary school GPI for GAR of 0.77 indicates that there are more males than females attending secondary school. Table 2.4 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 2010 Background characteristic Net attendance ratio1 Gross attendance ratio2 Male Female Total Gender Parity Index3 Male Female Total Gender Parity Index PRIMARY SCHOOL Residence Urban 96.3 94.6 95.4 0.98 160.8 146.7 153.6 0.91 Rural 88.9 91.0 90.0 1.02 155.4 147.9 151.7 0.95 Region Northern 96.6 96.8 96.7 1.00 170.8 158.3 164.7 0.93 Central 88.8 90.6 89.7 1.02 154.1 146.3 150.1 0.95 Southern 89.1 91.0 90.0 1.02 154.0 146.3 150.1 0.95 Wealth quintile Lowest 82.4 84.0 83.2 1.02 138.6 131.8 135.2 0.95 Second 87.1 89.7 88.5 1.03 153.3 143.6 148.3 0.94 Middle 90.8 92.3 91.6 1.02 159.0 149.6 154.4 0.94 Fourth 92.4 95.0 93.7 1.03 165.3 155.4 160.3 0.94 Highest 97.4 97.7 97.5 1.00 166.0 160.7 163.4 0.97 Total 89.9 91.5 90.7 1.02 156.1 147.8 151.9 0.95 SECONDARY SCHOOL Residence Urban 28.1 30.3 29.2 1.08 47.5 40.8 44.2 0.86 Rural 8.6 9.1 8.8 1.06 17.3 12.4 14.9 0.72 Region Northern 13.3 16.6 15.0 1.25 25.4 20.9 23.2 0.82 Central 8.8 10.4 9.6 1.18 18.5 14.3 16.4 0.77 Southern 14.2 13.8 14.0 0.97 25.0 19.0 22.1 0.76 Wealth quintile Lowest 3.4 3.0 3.2 0.88 7.6 4.0 5.9 0.52 Second 3.7 5.1 4.4 1.37 9.2 6.8 8.0 0.75 Middle 6.6 7.2 6.9 1.10 14.1 9.5 12.0 0.67 Fourth 12.5 12.2 12.3 0.98 23.8 16.8 20.5 0.71 Highest 29.0 30.5 29.8 1.05 50.4 41.5 45.9 0.82 Total 11.8 12.7 12.2 1.08 22.2 17.2 19.8 0.77 1 The NAR for primary school is the percentage of the primary-school age (6-13 years) population that is attending primary school. The NAR for secondary school is the percentage of the secondary-school age (14-17 years) population that is attending secondary school. By definition the NAR cannot exceed 100 percent. 2 The GAR for primary school is the total number of primary school students, expressed as a percentage of the official primary-school-age population. The GAR for secondary school is the total number of secondary school students, expressed as a percentage of the official secondary-school-age population. If there are significant numbers of overage and underage students at a given level of schooling, the GAR can exceed 100 percent. 3 The Gender Parity Index for primary school is the ratio of the primary school NAR (GAR) for females to the NAR (GAR) for males. The Gender Parity Index for secondary school is the ratio of the secondary school NAR (GAR) for females to the NAR (GAR) for males. 16 | Household Population and Housing Characteristics There are differentials between urban and rural populations regarding secondary NAR. A much higher proportion of urban students of appropriate ages are attending secondary school (29 percent) than are rural students (9 percent). The GAR similarly indicates that the urban population is more likely to attend secondary school than their rural counterparts (44 percent and 15 percent, respectively). There are considerable differences in secondary NAR across the regions, with the Central Region having the lowest NAR at 10 percent and the Northern and Southern Regions having NARs of 15 and 14 percent, respectively. The GAR is also lowest in the Central Region (16 percent) while the Southern and Northern Regions stand at 22 and 23 percent, respectively. Secondary NAR and secondary GAR vary consistently across the wealth quintile index, with populations living in higher wealth quintile households more likely to attend secondary school than their counterparts in lower wealth quintile households. 2.3.3 Grade Repetition and Dropout Rates Repetition rates and dropout rates shown in Table 2.5 describe the flow of pupils at the primary level through the educational system in Malawi. The repetition rates and dropout rates were computed from information about the grade or standard that children were attending during the previous school year. The table shows that repetition rates are high in Standard 1 (45 percent); no improvement has occurred since the same figure was reported in the 2004 MDHS. After Standard 1, there is a decline in repetition rates until Standard 8, where they increase sharply. This is a trend similar to that reported in the 2004 MDHS. There are no consistent differences in repetition rates between the sexes and across the grades, although at Standard 8 the rate is slightly higher for females than for males (26 and 24 percent, respectively). Repetition rates according to place of residence show no consistent pattern; however, for Standard 8, rural students are more likely to repeat the year than their urban counterparts. The second panel of Table 2.5 shows the expected pattern of increasing dropout rates with increasing years in school. Three percent of children drop out of school after attending Standard 1, but 17 percent drop out at Standard 8, up from 10 percent in the 2004 MDHS. There are no substantial differences in dropout rates between males and females. Rural children are more likely than urban children to drop out at all grades. Table 2.5 Grade repetition and dropout rates Repetition and dropout rates for the de facto household population age 5-24 who attended primary school in the previous school year by school grade, according to background characteristics, Malawi 2010 Background characteristic School grade 1 2 3 4 5 6 7 8 REPETITION RATE1 Sex Male 45.1 22.0 25.2 18.5 16.3 19.3 14.0 23.8 Female 45.0 21.6 22.9 19.2 16.7 14.5 11.7 26.0 Residence Urban 39.2 14.8 24.0 15.0 19.9 20.3 12.4 11.2 Rural 45.8 22.7 24.1 19.5 15.9 16.1 13.0 28.9 Region Northern 37.4 18.8 22.3 18.3 14.0 17.7 19.1 42.5 Central 45.4 20.6 24.1 19.3 17.2 16.6 8.2 20.8 Southern 46.5 23.8 24.5 18.6 16.8 16.9 14.8 19.9 Wealth quintile Lowest 47.8 24.1 26.1 23.3 17.1 18.2 13.3 34.3 Second 49.7 25.3 27.1 19.5 15.8 15.7 15.1 31.2 Middle 43.0 22.6 23.6 20.1 18.1 16.7 12.3 24.4 Fourth 44.6 19.4 26.0 18.6 15.3 16.8 10.2 23.9 Highest 37.0 16.4 17.3 14.7 16.4 17.2 14.3 20.8 Total 45.1 21.8 24.0 18.8 16.5 16.9 12.9 24.7 Continued… Household Population and Housing Characteristics | 17 Table 2.5—Continued Background characteristic School grade 1 2 3 4 5 6 7 8 DROPOUT RATE2 Sex Male 2.4 2.1 3.0 4.7 4.0 6.2 8.4 16.6 Female 2.8 1.7 3.1 4.0 5.7 6.9 12.0 17.0 Residence Urban 1.3 0.9 2.9 3.9 2.7 2.5 7.2 11.6 Rural 2.7 2.0 3.1 4.4 5.3 7.6 11.0 18.3 Region Northern 0.4 0.4 1.3 2.2 2.0 7.2 5.3 13.2 Central 2.8 2.1 4.6 5.6 7.1 6.4 12.7 21.0 Southern 2.9 2.0 2.2 3.9 3.8 6.5 9.7 14.7 Wealth quintile Lowest 4.1 3.3 5.6 8.2 6.9 11.5 16.9 21.2 Second 3.0 3.2 2.9 4.4 7.4 6.2 17.1 25.4 Middle 2.2 1.6 2.6 4.9 6.0 7.8 9.7 21.2 Fourth 2.1 0.9 2.4 4.0 3.3 8.9 12.3 15.8 Highest 0.9 0.1 2.0 1.6 2.6 2.1 3.1 11.5 Total 2.6 1.9 3.1 4.4 4.8 6.6 10.1 16.7 1 The repetition rate is the percentage of students in a given grade in the previous school year who are repeating that grade in the current school year. 2 The dropout rate is the percentage of students in a given grade in the previous school year who are not attending school. Figure 2.3 shows the age-specific attendance rates for the male and female de facto population age 5-24. There are no marked differences in attendance rates between males and females age 5 to 15; however, attendance rates for males older than age 15 are much higher than rates for females. Figure 2.3 Age-specific Attendance Rates MDHS 2010 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 Age (years) 0 20 40 60 80 100 Percent Female Male 2.4 HOUSEHOLD ENVIRONMENT The 2010 MDHS provides indicators of physical characteristics of household dwelling units and of access to drinking water and sanitation facilities. These indicators are important for socioeconomic planning and monitoring of programmes aimed at the improvement of health status of individuals. Respondents were asked a number of questions about their housing environment, 18 | Household Population and Housing Characteristics including their source of drinking water; type of sanitation facility; type of dwelling construction materials; number of rooms in the dwelling; access to electricity; usage of solid fuels; and possession of durable goods. The results are presented both for households and for the de jure population. 2.4.1 Improved Drinking Water One of the Millennium Development Goals (MDGs) that Malawi and other countries have adopted is to increase the percentage of the population with sustainable access to an improved water source in both urban and rural areas. Improved water sources refer to a household connection (piped), public standpipe, tube well or borehole, protected dug well, and protected spring or rainwater. However, water that must be fetched from an improved source that is not immediately accessible to the household may be contaminated during transport or storage. Long distances to an improved source of water and a disproportionate burden on female members of the household to collect water may limit the quantity of suitable drinking water available to a household. Home water treatment can improve the quality of household drinking water. Table 2.6 includes a number of indicators that are useful in monitoring household access to improved drinking water. Table 2.6 Household drinking water Percent distribution of households and de jure population by source, time to collect, and person who usually collects drinking water; and percentage of households and the de jure population by treatment of drinking water, according to residence, Malawi 2010 Characteristic Households Population Urban Rural Total Urban Rural Total Source of drinking water Improved source 92.6 77.1 79.7 91.9 76.9 79.3 Piped water into dwelling/yard/plot 31.0 1.8 6.6 32.2 1.8 6.6 Public tap/standpipe 45.3 10.1 15.9 43.7 9.8 15.1 Tube well or borehole 12.8 58.8 51.2 12.8 59.1 51.8 Protected dug well 3.4 6.0 5.5 3.1 5.9 5.5 Protected spring 0.1 0.4 0.4 0.1 0.4 0.4 Rainwater 0.0 0.0 0.0 0.0 0.0 0.0 Non-improved source 7.4 22.6 20.1 8.0 22.8 20.5 Unprotected dug well 6.2 17.1 15.3 6.4 17.1 15.5 Unprotected spring 0.8 2.3 2.0 1.0 2.3 2.1 Tanker truck/cart with small tank 0.1 0.1 0.1 0.2 0.1 0.1 Surface water 0.3 3.1 2.7 0.4 3.2 2.8 Other sources 0.0 0.3 0.3 0.0 0.3 0.2 Total 100.0 100.0 100.0 100.0 100.0 100.0 Percentage using any improved source of drinking water 92.6 77.1 79.7 91.9 76.9 79.3 Time to obtain drinking water (round trip) Water on premises 34.4 5.7 10.5 36.1 5.8 10.6 Less than 30 minutes 41.0 48.0 46.9 39.9 47.8 46.5 30 minutes or longer 24.3 45.6 42.1 23.8 45.7 42.3 Don’t know/missing 0.2 0.7 0.6 0.2 0.7 0.6 Total 100.0 100.0 100.0 100.0 100.0 100.0 Person who usually collects drinking water Adult female 15+ 50.8 80.0 75.1 52.2 81.4 76.8 Adult male 15+ 7.7 4.3 4.9 3.6 1.9 2.2 Female child under age 15 5.9 8.6 8.1 6.8 9.4 9.0 Male child under age 15 1.0 1.0 1.0 1.1 1.1 1.1 Other 0.1 0.2 0.2 0.1 0.1 0.1 Water on premises 34.4 5.7 10.5 36.1 5.8 10.6 Missing 0.2 0.2 0.2 0.1 0.2 0.2 Total 100.0 100.0 100.0 100.0 100.0 100.0 Water treatment prior to drinking1 Boiled 6.8 11.3 10.5 6.1 11.4 10.6 Bleach/chlorine 26.1 24.4 24.7 26.1 25.0 25.2 Strained through cloth 1.1 1.7 1.6 1.2 1.8 1.7 Ceramic, sand or other filter 0.2 0.1 0.1 0.2 0.1 0.1 Solar disinfection 0.0 0.0 0.0 0.0 0.0 0.0 Other 3.4 4.1 4.0 3.5 4.3 4.2 No treatment 66.5 64.7 65.0 66.8 64.2 64.6 Percentage using an appropriate treatment method2 31.2 32.5 32.3 30.8 33.0 32.6 Number 4,116 20,709 24,825 18,165 96,935 115,100 1 Respondents may report multiple treatment methods so the sum of treatment may exceed 100 percent. 2 Appropriate water treatment methods include boiling, bleaching, straining, filtering, and solar disinfecting. Household Population and Housing Characteristics | 19 The table shows that 80 percent of the households and 79 percent of the population have access to improved sources of water. In urban areas, 93 percent of the households have access to improved sources of water compared with 77 percent of households in rural areas. Piped water (to the dwelling or to a public tap) is the main source of drinking water for households in urban areas (76 percent), whereas in rural areas the main source of drinking water is a tube well or borehole (59 percent). Overall, 51 percent of households draw water from a borehole. The most commonly used non-improved source of water is an unprotected dug well (15 percent). Eleven percent of households have a source of drinking water on the premises. The availability of a source of drinking water on the premises is higher in urban areas (34 percent) than in rural areas (6 percent). Forty-two percent of the households take 30 or more minutes to obtain water, including 24 percent of households in urban areas and 46 percent of households in rural areas. Adult females collect drinking water more often than female children (75 percent and 8 percent, respectively). Five percent of adult males and one percent of male children collect water. While most households (65 percent) do not treat their water, about 32 percent of households use an appropriate treatment method. Bleach or chlorine is most commonly used by households for water treatment (25 percent). Eleven percent of households boil their water. 2.4.2 Household Sanitation Facilities Increasing the percentage of the population with access to improved sanitation in both urban and rural areas is another indicator of the MDGs. For MDG monitoring, improved sanitation technologies are defined as follows: connection to a public sewer, connection to a septic system, pour- flush latrine, simple pit latrine with a slab, or ventilated, improved pit latrine. According to the WHO/UNICEF Joint Monitoring Programme for Water Supply and Sanitation of 2004, a household is classified as having an improved toilet if the toilet is used only by members of one household (i.e., it is not shared with other households) and if the facility used by the household separates the waste from human contact. Table 2.7 shows that 8 percent of households use an improved latrine facility, and 92 percent use a non-improved facility. Use of improved and not shared facilities is slightly higher among households in urban areas (19 percent) as compared with 6 percent in rural areas. A pit latrine with slab is the toilet facility most commonly used (5 percent) among households using an improved and not shared facility. Eight percent of households in urban areas and 4 percent of households in rural areas use this type of facility. Only 2 percent of households use a facility that flushes to a piped sewer system and is not shared. This proportion is higher among urban households (9 percent) compared with less than 1 percent in rural households. Table 2.7 Household sanitation facilities Percent distribution of households and de jure population by type of toilet/latrine facilities, according to residence, Malawi 2010 Type of toilet/latrine facility Households Population Urban Rural Total Urban Rural Total Improved, not shared facility Flush/pour flush to piped sewer system 9.4 0.4 1.9 10.1 0.4 1.9 Ventilated improved pit (VIP) latrine 1.5 1.6 1.6 2.0 1.7 1.7 Pit latrine with slab 8.3 4.0 4.7 9.8 4.4 5.2 Non-improved facility Any facility shared with other households 16.2 3.3 5.5 13.9 3.2 4.9 Pit latrine without slab/open pit 61.9 77.5 74.9 61.4 78.5 75.8 No facility/bush/field 2.4 12.5 10.8 2.5 11.3 9.9 Other 0.1 0.6 0.5 0.0 0.5 0.5 Missing 0.3 0.0 0.1 0.3 0.0 0.1 Total 100.0 100.0 100.0 100.0 100.0 100.0 Number 4,116 20,709 24,825 18,165 96,935 115,100 20 | Household Population and Housing Characteristics Sharing of a toilet facility is more common in urban areas, where 16 percent of households do so, than in rural areas (3 percent). The majority of the Malawian population uses a pit latrine without a slab (75 percent), which is not an improved sanitation facility. Eleven percent have no facility and use the bush. Usage of the bush as a toilet is more common among households in rural areas (13 percent) than in urban areas (2 percent). 2.4.3 Housing Characteristics Table 2.8 presents information on a number of household dwelling characteristics and the proportion of households using various types of fuel for cooking. These characteristics reflect the household’s socioeconomic situation. They also may influence environmental conditions that have a direct bearing on household members’ health and welfare. For example, the use of biomass fuels for cooking increases exposure to indoor air pollution. In Malawi, 9 percent of households have electricity. The proportion is higher among households in urban areas (35 percent) than in rural areas (4 percent). Earth or sand is the most common material used for flooring (74 percent). Rural households are more likely to have floors made of earth or sand (83 percent) than urban households (32 percent). On the other hand, use of cement floors is more common among households in urban areas than in rural areas (66 percent compared with 14 percent). Overall, 23 percent of the households have floors made of cement. About 42 percent of the dwelling units have two rooms for sleeping, while 36 percent have a single room. There is little difference in the number of rooms used for sleeping in urban and rural areas. Nine percent of the households cook inside the house, while 32 percent cook outdoors and 59 percent cook in a separate building. The percentage of households that cook within the dwelling is higher among households in urban areas (25 percent) than in rural areas (6 percent). Additionally, 48 percent of urban households cook outdoors compared with 28 percent of rural households. The proportion of households cooking in a separate building is higher in rural areas (66 percent) than in urban areas (27 percent). Wood is the fuel most commonly used for cooking, reported by 85 percent of households. Use of wood is more common in rural areas (94 percent) than in urban areas (37 percent). Twelve percent of all households interviewed use charcoal for cooking, including 53 percent in urban areas and 4 percent in rural areas. Among all households interviewed, 98 percent use solid fuel for cooking. Almost all households in rural areas and 90 percent in urban areas use solid fuel. Ninety-eight percent of households using solid fuel for cooking reported usage of an open fire or stove without a chimney. Household Population and Housing Characteristics | 21 Table 2.8 Household characteristics Percent distribution of households and de jure population by housing characteristics and percentage using solid fuel for cooking; and among those using solid fuels, percent distribution by type of fire/stove, according to residence, Malawi 2010 Housing characteristic Households Population Urban Rural Total Urban Rural Total Electricity Yes 34.7 3.5 8.7 36.8 3.8 9.1 No 65.3 96.4 91.2 63.1 96.0 90.8 Missing 0.0 0.1 0.1 0.0 0.1 0.1 Total 100.0 100.0 100.0 100.0 100.0 100.0 Flooring material Earth, sand 32.2 82.5 74.1 30.6 82.0 73.9 Dung 0.6 3.0 2.6 0.5 2.9 2.5 Parquet or polished wood 0.0 0.2 0.1 0.0 0.2 0.2 Ceramic tiles 0.4 0.0 0.1 0.4 0.0 0.1 Cement 65.9 14.1 22.7 67.6 14.6 23.0 Carpet 0.5 0.0 0.1 0.5 0.0 0.1 Other 0.1 0.0 0.0 0.1 0.0 0.0 Missing 0.1 0.0 0.0 0.1 0.0 0.0 Total 99.8 99.9 99.9 99.7 99.9 99.9 Rooms used for sleeping One 33.6 36.2 35.7 21.2 25.1 24.5 Two 40.9 42.2 41.9 42.3 44.8 44.4 Three or more 25.4 21.3 22.0 36.4 29.9 30.9 Missing 0.2 0.4 0.3 0.2 0.3 0.3 Total 100.0 100.0 100.0 100.0 100.0 100.0 Place for cooking In the house 24.5 6.0 9.1 22.5 4.5 7.4 In a separate building 27.0 65.5 59.1 30.7 69.0 63.0 Outdoors 48.2 28.3 31.6 46.6 26.4 29.6 Other 0.1 0.1 0.1 0.1 0.0 0.0 Missing 0.2 0.1 0.1 0.1 0.0 0.0 Total 100.0 100.0 100.0 100.0 100.0 100.0 Cooking fuel Electricity 9.2 0.2 1.7 8.9 0.2 1.6 Kerosene 0.2 0.0 0.0 0.1 0.0 0.0 Coal/lignite 0.2 0.0 0.0 0.1 0.0 0.0 Charcoal 52.8 3.7 11.8 49.4 3.0 10.4 Wood 36.7 94.1 84.6 40.7 95.0 86.4 Straw/shrubs/grass 0.7 1.9 1.7 0.5 1.7 1.5 No food cooked in household 0.2 0.1 0.1 0.1 0.0 0.0 Other 0.1 0.0 0.0 0.1 0.0 0.0 Total 100.0 100.0 100.0 100.0 100.0 100.0 Percentage using solid fuel for cooking1 90.3 99.6 98.1 90.9 99.8 98.3 Number of households 4,116 20,709 24,825 18,165 96,935 115,100 Type of fire/stove among households using solid fuel Closed stove with chimney 0.2 0.2 0.2 0.2 0.1 0.1 Open fire/stove with chimney 0.6 1.0 0.9 0.5 0.9 0.8 Open fire/stove with hood 1.2 0.2 0.4 1.2 0.2 0.4 Open fire/stove without chimney or hood 98.0 98.5 98.4 98.0 98.7 98.6 Missing 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 Number of households/ population using solid fuel 3,716 20,632 24,348 16,503 96,696 113,199 1 Includes coal/lignite, charcoal, wood/straw/shrubs/grass, and agricultural crops. 2.5 HOUSEHOLD POSSESSIONS The availability of durable consumer goods is a good indicator of a household’s socioeconomic status. Moreover, particular goods have specific benefits. For instance, having access to a radio or a television exposes household members to innovative ideas; a refrigerator prolongs food storage; and a means of transport allows greater access to many services away from the local area. 22 | Household Population and Housing Characteristics Table 2.9 shows the presence of selected consumer goods by residence; 53 percent of households own a radio. In urban areas, 70 percent own a radio as compared with half of the households (50 percent) in rural areas. A mobile telephone is owned by 39 percent of households (73 percent in urban areas and 32 percent in rural areas). Eleven percent of the households have a television: 34 percent in urban areas and 6 percent in rural areas. Four percent have a refrigerator, and the proportion is higher among households in urban areas (16 percent) than in rural areas (1 percent). Table 2.9 also shows the proportion of households owning various means of transport. Forty- four percent of the households own a bicycle (30 percent in urban areas and 47 percent in rural areas), while 2 percent own a car or truck and a similar percentage own an animal-drawn cart. Among the means of transport listed, the bicycle and animal drawn cart are more common in rural areas while ownership of a car or truck is more common in urban areas. Agricultural land is owned by 79 percent of households (87 percent in rural areas and 39 percent in urban areas), whereas farm animals are owned by 60 percent of households (66 percent in rural areas and 27 percent in urban areas). Table 2.9 Household durable goods Percentage of households and de jure population possessing various household effects, means of transportation, agricultural land and livestock/farm animals by residence, Malawi 2010 Possession Households Population Urban Rural Total Urban Rural Total Household effects Radio 70.3 49.8 53.2 73.3 52.4 55.7 Television 34.2 6.1 10.8 38.4 6.8 11.8 Mobile telephone 72.7 32.3 39.0 75.6 35.0 41.4 Non-mobile telephone 6.8 1.0 2.0 8.6 1.2 2.3 Refrigerator 15.7 1.3 3.7 18.5 1.6 4.3 Means of transport Bicycle 29.9 46.5 43.8 34.5 50.7 48.1 Animal drawn cart 0.9 2.5 2.2 1.2 3.1 2.8 Motorcycle/scooter 1.2 1.2 1.2 1.5 1.4 1.4 Car/truck 6.5 0.7 1.7 8.0 1.0 2.1 Ownership of agricultural land 38.6 87.4 79.3 40.5 88.4 80.8 Ownership of farm animals1 26.5 66.4 59.8 30.8 70.6 64.3 Number 4,116 20,709 24,825 18,165 96,935 115,100 1 Cattle, cows, bulls, horses, donkeys, goats, sheep or chickens 2.6 WEALTH INDEX The wealth index is used throughout the report as a background characteristic. It serves as a proxy for measuring the long-term standard of living. It is based on data from the household’s ownership of consumer goods; dwelling characteristics; type of drinking water source; toilet facilities; and other characteristics that are related to a household’s socioeconomic status. To construct the index, each of these assets was assigned a weight (factor score) generated through principal component analysis, and the resulting asset scores were standardised in relation to a standard normal distribution with a mean of zero and standard deviation of one (Gwatkin et al., 2000). Each household was then assigned a score for each asset, and the scores were summed for each household. Individuals were ranked according to the total score of the household in which they resided. The sample was then divided into quintiles from one (lowest) to five (highest). A single asset index was developed on the basis of data from the entire country sample, and this index is used in all the tabulations presented. Table 2.10 shows the percent distribution of the de jure household population by wealth quintile, according to residence and region. The distributions indicate the degree to which wealth is evenly (or unevenly) distributed geographically. The table shows that urban areas have a higher proportion of people in the highest quintile (66 percent) compared with rural areas (11 percent). On the other hand, rural areas have a higher proportion of the population in the lowest, second, and third quintiles than urban areas. The fourth quintile contains an equal percentage of households for both urban and rural areas (20 percent). Household Population and Housing Characteristics | 23 The Northern Region has the highest proportion of persons in the fourth and highest quintiles while the Central Region has the lowest proportion of the population in these quintiles. The proportion of households in the lowest and second quintiles is highest in the Central Region followed by the Southern Region, while the Northern Region contributes the lowest proportion of households. Table 2.10 Wealth quintiles Percent distribution of the de jure population by wealth quintiles and the Gini Coefficient, according to residence and region, Malawi 2010 Residence/region Wealth quintile Total Number of population Gini coefficient Lowest Second Middle Fourth Highest Residence Urban 2.9 3.4 7.5 19.9 66.3 100.0 18,165 27.7 Rural 23.2 23.1 22.3 20.0 11.3 100.0 96,935 35.1 Region Northern 12.2 14.5 22.3 26.6 24.5 100.0 13,564 33.1 Central 23.8 21.3 20.0 17.6 17.2 100.0 49,988 42.0 Southern 18.3 20.1 19.4 20.6 21.5 100.0 51,548 42.9 Total 20.0 20.0 20.0 20.0 20.0 100.0 115,100 41.8 Respondents’ Characteristics | 25 RESPONDENTS’ CHARACTERISTICS 3 The purpose of this chapter is to create a demographic and socioeconomic profile of individual female and male respondents. This information helps in interpretation of findings presented later in the report and provides an indication of the representativeness of the survey. The chapter begins by describing basic background characteristics, including age, marital status, residence, education, religion, ethnicity, and economic status of respondents’ households. The chapter then covers more detailed information on education, media exposure, employment, and indicators of women’s status. Information on knowledge and attitudes concerning tuberculosis is presented, and findings on tobacco use are provided as a lifestyle measure.1 3.1 CHARACTERISTICS OF SURVEY RESPONDENTS Table 3.1 shows the distribution of women and men age 15-49 by background characteristics. The table shows declining proportions of women and men with advancing age indicating that Malawi’s age structure is broad based, i.e., a young age structure. This is a trend similar to that observed in the 2004 MDHS. Women who are in union (i.e., currently married or living with a man) constitute two-thirds of all interviewed women (67 percent). In comparison, more than half of men are currently in union (57 percent). The proportion of men who have never been married is almost double that of women who have never been married, 39 percent compared with 20 percent. Table 3.1 also shows that the majority of women (81 percent) and men (79 percent) live in rural areas. By region, the majority of women and men live in the Central and Southern Regions, while 12 percent of women and 11 percent of men live in the Northern Region. Although the majority of respondents have had some education, the level of educational attainment varies by sex: 85 percent of women and 94 percent of men ever attended school. Among all the levels of educational attainment, the majority of women and men have attained some primary level education; however, a higher proportion of men (31 percent) have attended secondary school or higher compared with 20 percent of women. The distribution of respondents by religion shows that a majority of the respondents are Christians (86 percent of women and 84 percent of men), while 13 percent of women and 12 percent of men are Muslims. Less than 1 percent of women and 3 percent of men reported no religious affiliation. Regarding ethnic self-identification, Chewa is the largest ethnic group, making up one- third of female and male respondents, followed by the Lomwe, who constitute 16 percent of women and 18 percent of men. The Yao and Ngoni both constitute 13 percent of the respondents for both women and men. 1 The survey results in this chapter are presented for the country as a whole, by urban-rural residence, and by region. District-level results are available in Appendix A. 26 | Respondents’ Characteristics Table 3.1 Background characteristics of respondents Percent distribution of women and men age 15-49 by selected background characteristics, Malawi 2010 Background characteristic Women Men Weighted percent Weighted Unweighted Weighted percent Weighted Unweighted Age 15-19 21.7 5,005 5,040 25.6 1,748 1,757 20-24 19.8 4,555 4,392 18.2 1,239 1,217 25-29 19.1 4,400 4,313 16.1 1,099 1,064 30-34 14.1 3,250 3,290 13.9 948 942 35-39 11.0 2,522 2,575 11.7 798 777 40-44 7.5 1,730 1,777 7.8 529 552 45-49 6.8 1,558 1,633 6.7 458 496 Marital status Never married 19.7 4,538 4,526 39.4 2,689 2,703 Married 58.7 13,520 13,493 47.8 3,257 3,293 Living together 8.7 2,008 1,952 9.4 638 580 Divorced/separated 9.3 2,135 2,189 3.0 206 204 Widowed 3.6 819 860 0.4 28 25 Residence Urban 18.7 4,302 3,068 21.1 1,440 973 Rural 81.3 18,718 19,952 78.9 5,379 5,832 Region Northern 11.6 2,677 4,189 10.9 744 1,215 Central 42.8 9,857 7,862 45.1 3,074 2,464 Southern 45.5 10,485 10,969 44.0 3,001 3,126 Education No education 15.2 3,505 3,390 6.2 422 398 Primary 64.8 14,916 15,339 62.6 4,270 4,359 Secondary 18.1 4,177 3,970 27.9 1,904 1,854 More than secondary 1.8 422 321 3.3 223 194 Wealth quintile Lowest 18.5 4,268 4,539 14.6 997 1,092 Second 18.8 4,332 4,506 19.2 1,309 1,380 Middle 19.6 4,517 4,721 20.0 1,367 1,401 Fourth 19.6 4,515 4,699 20.2 1,376 1,452 Highest 23.4 5,388 4,555 26.0 1,770 1,480 Religion Anglican 2.3 541 718 2.5 168 221 Catholic 20.6 4,754 4,670 22.3 1,519 1,466 CCAP1 16.6 3,823 3,684 16.8 1,143 1,112 Muslim 13.0 2,993 2,530 12.2 833 695 Seventh Day Advent/Baptist 6.7 1,541 1,653 7.1 482 500 Other Christian 39.5 9,087 9,559 35.2 2,400 2,565 No religion 0.8 173 137 2.6 177 174 Missing 0.1 15 14 0.0 1 1 Ethnicity Chewa 34.1 7,855 6,780 33.3 2,274 1,994 Lambya 0.4 84 170 0.4 26 56 Lomwe 16.3 3,743 3,731 17.8 1,211 1,197 Mang’anja 3.0 701 698 2.8 191 186 Ndali 0.4 89 188 0.3 23 54 Ngoni 12.9 2,969 3,145 12.9 877 889 Nkhonde 1.0 238 377 0.9 65 110 Nyanja 1.3 307 312 1.6 109 87 Sena 4.6 1,061 1,288 4.4 300 384 Tonga 1.9 434 751 1.8 123 234 Tumbuka 9.2 2,109 2,497 8.7 590 690 Yao 13.1 3,005 2,424 13.2 897 714 Other 1.8 418 650 1.9 133 209 Missing 0.0 7 9 0.0 1 1 Total 15-49 100.0 23,020 23,020 100.0 6,818 6,805 50-54 na na na na 357 370 Total men 15-54 na na na na 7,175 7,175 Note: Education categories refer to the highest level of education attended, whether or not that level was completed. na = Not applicable 1Church of Central Africa, Presbyterian Respondents’ Characteristics | 27 3.2 EDUCATIONAL ATTAINMENT BY BACKGROUND CHARACTERISTICS Table 3.2.1 provides an overview of the relationship between women’s level of education and various background characteristics. In Malawi, 15 percent of women have never attended school, 56 percent have some primary education, and 9 percent have completed primary school. At the secondary level, 13 percent have some secondary education, while 6 percent have completed secondary school. Two percent of women have more than a secondary education. The results show that older women are less likely than younger women to have some education. Thirty-eight percent of women age 45-49 reported that they have no education compared with 5 percent of women age 15-24. Place of residence is also associated with women’s level of education because women in rural areas are far less likely to have ever attended school than their urban counterparts: 17 percent of rural women have never attended school compared with 7 percent of urban women. Women in the Central and Southern Regions (17 percent each) are four times as likely as women in the Northern Region (4 percent) to have no schooling. Wealth is highly associated with having ever been to school, as more than a quarter of women in the lowest wealth quintile (26 percent) have never been to school compared with only 4 percent of women in the highest quintile. Nationally, women have completed a median number of 4.9 years of school. The median number of years of school completed for rural women is 4.3 years compared with 7.5 years for women from urban areas. Similarly, differences in the level of education attained are observed among the regions. The median number of years of school completed is highest for women from the Northern Region at 6.8 years, followed by 4.7 years in the Southern Region, and 4.3 years in the Central Region. Educational attainment increases as household wealth increases. One-quarter of women in the highest wealth quintile have completed secondary or higher education compared with less than 1 percent of women in the lowest wealth quintile. Table 3.2.1 Educational attainment: Women Percent distribution of women age 15-49 by highest level of schooling attended or completed, and median grade completed, according to background characteristics, Malawi 2010 Background characteristic Highest level of schooling Total Median years completed Number of women No education Some primary Completed primary1 Some secondary Completed secondary2 More than secondary Age 15-24 5.3 56.9 12.0 18.2 6.0 1.6 100.0 5.9 9,559 15-19 2.9 59.6 13.7 19.7 3.4 0.7 100.0 5.9 5,005 20-24 7.9 53.8 10.1 16.6 8.9 2.7 100.0 5.8 4,555 25-29 10.0 56.6 9.0 13.8 7.8 2.8 100.0 5.5 4,400 30-34 18.2 55.1 7.8 9.6 7.6 1.8 100.0 4.0 3,250 35-39 30.8 53.2 6.3 4.6 3.4 1.8 100.0 2.4 2,522 40-44 34.3 52.5 5.4 4.5 1.3 1.9 100.0 2.1 1,730 45-49 38.3 51.8 6.1 2.0 1.2 0.7 100.0 1.4 1,558 Residence Urban 7.0 40.1 7.2 23.5 14.8 7.3 100.0 7.5 4,302 Rural 17.1 59.0 9.8 10.0 3.5 0.6 100.0 4.3 18,718 Region Northern 3.9 60.9 11.0 16.8 6.5 1.0 100.0 6.8 2,677 Central 16.7 56.1 9.5 11.2 5.0 1.5 100.0 4.3 9,857 Southern 16.7 53.6 8.7 12.7 5.9 2.4 100.0 4.7 10,485 Wealth quintile Lowest 26.3 61.6 8.1 3.5 0.5 0.0 100.0 2.5 4,268 Second 21.2 61.7 10.7 5.4 0.9 0.0 100.0 3.4 4,332 Middle 16.1 60.9 12.3 8.8 1.9 0.0 100.0 4.5 4,517 Fourth 11.8 60.0 9.2 14.5 4.1 0.4 100.0 5.4 4,515 Highest 3.8 37.3 6.7 26.9 17.8 7.4 100.0 8.2 5,388 Total 15.2 55.5 9.3 12.5 5.6 1.8 100.0 4.9 23,020 1 Completed 8 years at the primary level 2 Completed 4 years at the secondary level 28 | Respondents’ Characteristics Table 3.2.2 shows the relationship between men’s level of education and other background characteristics. Nationally, 6 percent of men age 15-49 have no education compared with more than twice as many women of the same age (15 percent). Men from urban areas have higher levels of educational attainment than their rural counterparts. Two percent of urban males compared with 7 percent of their rural counterparts have no formal education. While 31 percent of urban males have completed secondary or higher education, 9 percent of their rural counterparts have done so. Overall, the median years of school completed for men age 15-49 is 6.1 years. For men, the level of educational attainment varies by region, but similar to the trend among women, men in the Northern Region attend school longer compared with men from the Central and Southern Regions. Two percent of men in the Northern Region had no education compared with 7 percent of men with no education in both the Central and Southern Regions. For men, as for women, educational attainment increases as household wealth increases. The median years of education completed increases with each wealth quintile, from 3.8 years among men in the lowest quintile to 7.6 years among men in the highest quintile. Table 3.2.2 Educational attainment: Men Percent distribution of men age 15-49 by highest level of schooling attended or completed, and median grade completed, according to background characteristics, Malawi 2010 Background characteristic Highest level of schooling Total Median years completed Number of men No education Some primary Completed primary1 Some secondary Completed secondary2 More than secondary Age 15-24 2.6 55.2 10.9 21.6 7.5 2.1 100.0 6.1 2,987 15-19 1.9 62.1 13.1 20.0 2.4 0.5 100.0 5.7 1,748 20-24 3.7 45.6 7.8 23.8 14.7 4.4 100.0 6.6 1,239 25-29 5.1 45.5 10.7 18.3 15.8 4.6 100.0 6.6 1,099 30-34 7.0 46.0 7.0 18.0 18.0 4.0 100.0 6.6 948 35-39 12.2 55.4 7.7 9.5 13.0 2.0 100.0 5.3 798 40-44 11.3 60.1 6.6 8.1 7.3 6.5 100.0 5.6 529 45-49 13.8 63.4 5.7 8.8 3.8 4.4 100.0 4.7 458 Residence Urban 1.7 31.8 6.8 28.4 22.1 9.2 100.0 7.5 1,440 Rural 7.4 59.1 9.9 14.2 7.6 1.7 100.0 5.6 5,379 Region Northern 1.7 50.7 10.2 22.7 11.8 3.0 100.0 7.0 744 Central 6.5 56.3 9.1 14.6 10.7 2.7 100.0 5.8 3,074 Southern 7.0 51.0 9.2 18.5 10.4 3.9 100.0 6.0 3,001 Wealth quintile Lowest 14.7 67.5 9.3 7.2 1.3 0.0 100.0 3.8 997 Second 8.8 64.5 11.4 12.2 3.1 0.0 100.0 4.8 1,309 Middle 6.9 62.3 11.0 13.2 6.4 0.2 100.0 5.5 1,367 Fourth 3.6 52.9 9.7 20.2 12.1 1.6 100.0 6.5 1,376 Highest 1.0 30.6 6.1 27.4 23.8 11.2 100.0 7.6 1,770 Total 15-49 6.2 53.3 9.3 17.2 10.7 3.3 100.0 6.1 6,818 50-54 15.4 65.5 6.6 6.4 3.9 2.2 100.0 4.7 357 Total men 15-54 6.6 53.9 9.2 16.7 10.4 3.2 100.0 6.1 7,175 1 Completed 8 years at the primary level 2 Completed 4 years at the secondary level 3.3 LITERACY The ability to read is crucial for exploring social and economic opportunities during a person’s lifetime. Program planners use literacy statistics to determine the best ways to get health and other messages to women and men in different subgroups. The literacy status of respondents in the 2010 MDHS was determined by assessing their ability to read all or part of a simple sentence in any of the four languages; English, Chichewa, Yao, or Tumbuka. The literacy test was administered only to respondents who had less than a secondary school education because those with a secondary education or higher were assumed to be literate. Tables 3.3.1 and 3.3.2 present literacy data for women and men age 15-49. Respondents’ Characteristics | 29 Table 3.3.1 shows the percent distribution of women by the level of schooling attended, level of literacy, and percentage literate, according to background characteristics. More than three in five (68 percent) women are literate. The level of literacy is much higher for women age 15-19, compared with women age 45-49 (81 and 45 percent, respectively). Eighty-three percent of women in urban areas are literate compared with 64 percent of their rural counterparts. Literacy varies by region, ranging from a high of 80 percent in the Northern Region to a low of 65 percent in the Central Region. Women in the highest wealth quintile are nearly twice as likely to be literate as women in the lowest wealth quintile (89 and 48 percent, respectively). 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 2010 Background characteristic Secondary school or higher No schooling or primary school Total Percentage literate1 Number Can read a whole sentence Can read part of a sentence Cannot read at all No card with required language Blind/ visually impaired Missing Age 15-19 23.8 48.5 8.6 18.9 0.0 0.0 0.2 100.0 80.9 5,005 20-24 28.1 37.5 7.8 26.2 0.0 0.1 0.1 100.0 73.5 4,555 25-29 24.4 40.1 8.1 27.2 0.1 0.0 0.1 100.0 72.7 4,400 30-34 18.9 37.9 7.8 35.0 0.0 0.2 0.1 100.0 64.6 3,250 35-39 9.7 32.5 8.4 49.2 0.0 0.1 0.1 100.0 50.6 2,522 40-44 7.8 34.2 9.6 47.5 0.0 0.6 0.3 100.0 51.5 1,730 45-49 3.9 33.0 8.4 53.6 0.0 0.9 0.2 100.0 45.3 1,558 Residence Urban 45.7 32.7 4.5 16.6 0.0 0.2 0.2 100.0 82.9 4,302 Rural 14.1 40.9 9.1 35.6 0.0 0.2 0.1 100.0 64.1 18,718 Region Northern 24.3 44.0 11.4 20.0 0.1 0.1 0.1 100.0 79.7 2,677 Central 17.7 38.9 7.8 35.2 0.0 0.2 0.1 100.0 64.5 9,857 Southern 21.0 38.6 7.9 32.1 0.0 0.2 0.2 100.0 67.5 10,485 Wealth quintile Lowest 4.0 34.3 9.3 52.1 0.0 0.1 0.1 100.0 47.7 4,268 Second 6.3 40.9 9.3 43.2 0.1 0.2 0.1 100.0 56.5 4,332 Middle 10.7 45.5 9.6 33.8 0.0 0.3 0.1 100.0 65.8 4,517 Fourth 19.0 45.6 8.5 26.6 0.0 0.1 0.2 100.0 73.1 4,515 Highest 52.2 31.8 5.3 10.3 0.0 0.2 0.3 100.0 89.3 5,388 Total 20.0 39.4 8.3 32.0 0.0 0.2 0.2 100.0 67.6 23,020 1 Refers to women who attended secondary school or higher and women who can read a whole sentence or part of a sentence. Table 3.3.2 shows that 81 percent of men are literate. The patterns of men’s literacy are similar to those among women. However, there are marked differences between the sexes in the literacy levels across the age groups. Eighty percent of men age 45-49 are literate compared with 45 percent of women in the same age group. Similarly, marked disparities are observed between women and men across the wealth quintiles, as 64 percent of men in the poorest households are literate compared with 48 percent of women in the same wealth quintile. 30 | Respondents’ Characteristics 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 2010 Background characteristic Secondary school or higher No schooling or primary school Total Percentage literate1 Number Can read a whole sentence Can read part of a sentence Cannot read at all No card with required language Blind/ visually impaired Missing Age 15-19 22.9 49.0 10.2 17.4 0.0 0.0 0.5 100.0 82.2 1,748 20-24 42.9 31.1 7.3 18.4 0.1 0.0 0.2 100.0 81.3 1,239 25-29 38.7 38.4 6.3 16.2 0.0 0.2 0.2 100.0 83.4 1,099 30-34 40.0 36.5 7.4 16.1 0.0 0.0 0.0 100.0 83.9 948 35-39 24.6 43.4 7.8 24.0 0.0 0.2 0.0 100.0 75.8 798 40-44 21.9 46.7 10.0 21.4 0.0 0.0 0.0 100.0 78.6 529 45-49 17.1 53.6 8.9 20.2 0.3 0.0 0.0 100.0 79.6 458 Residence Urban 59.7 27.8 4.6 7.7 0.0 0.0 0.2 100.0 92.1 1,440 Rural 23.6 45.5 9.3 21.4 0.0 0.1 0.2 100.0 78.4 5,379 Region Northern 37.5 35.9 8.9 17.6 0.0 0.0 0.0 100.0 82.3 744 Central 28.1 42.8 10.0 18.6 0.0 0.1 0.3 100.0 80.9 3,074 Southern 32.8 42.2 6.3 18.5 0.0 0.0 0.1 100.0 81.3 3,001 Wealth quintile Lowest 8.5 46.6 9.3 35.5 0.0 0.0 0.1 100.0 64.4 997 Second 15.3 49.6 9.7 25.1 0.1 0.1 0.1 100.0 74.6 1,309 Middle 19.8 47.5 11.2 21.2 0.1 0.0 0.2 100.0 78.5 1,367 Fourth 33.9 44.7 8.0 13.1 0.0 0.2 0.2 100.0 86.5 1,376 Highest 62.4 26.7 4.7 6.0 0.0 0.0 0.2 100.0 93.8 1,770 Total 15-49 31.2 41.8 8.3 18.5 0.0 0.1 0.2 100.0 81.3 6,818 50-54 12.6 56.1 7.6 23.4 0.0 0.3 0.0 100.0 76.3 357 Total men 15-54 30.3 42.5 8.3 18.7 0.0 0.1 0.2 100.0 81.0 7,175 1 Refers to men who attended secondary school or higher and men who can read a whole sentence or part of a sentence. 3.4 ACCESS TO MASS MEDIA The 2010 MDHS collected information on the respondents’ exposure to common print and electronic media. Respondents were asked how often they read a newspaper, listened to the radio, or watched television. This information is important because it indicates the extent to which Malawians are regularly exposed to mass media, often used to convey messages on family planning and other health topics. Data on exposure to mass media for both women and men age 15-49 are presented in Tables 3.4.1 and 3.4.2. There are disparities in the exposure to mass media between the sexes. Twelve percent of women read the newspaper at least once a week compared with 26 percent of men. More than twice as many men (34 percent) watch the television at least once a week compared with women (16 percent). Although more than half of female respondents (57 percent) listen to the radio at least once a week, more than three-quarters of men (76 percent) do so. The percentage of men who are exposed to all three forms of media (newspaper, television, and radio) is about three times that of women (14 percent compared with 5 percent). Similarly, wealth status is positively related to exposure to mass media. For instance, 66 percent of women in the lowest quintile have no weekly exposure to any media source; while 15 percent of those in the highest quintile have no exposure. For men, 31 percent in the lowest wealth quintile have no weekly exposure to any media source compared with 6 percent of men in the highest wealth quintiles. Respondents’ Characteristics | 31 Table 3.4.1 Exposure to mass media: Women Percentage of women age 15-49 who are exposed to specific media on a weekly basis, by background characteristics, Malawi 2010 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 All three media at least once a week No media at least once a week Number Age 15-19 17.0 20.5 58.4 6.5 34.7 5,005 20-24 14.1 15.6 60.0 5.4 35.8 4,555 25-29 11.1 16.0 56.8 4.8 38.9 4,400 30-34 9.7 15.9 57.5 4.1 38.6 3,250 35-39 7.7 13.1 55.1 3.0 41.2 2,522 40-44 7.5 12.3 53.1 2.4 43.1 1,730 45-49 6.1 10.4 55.0 2.7 43.2 1,558 Residence Urban 22.9 41.3 65.7 13.3 24.2 4,302 Rural 9.2 10.1 55.3 2.7 41.4 18,718 Region Northern 15.7 19.0 64.9 5.0 29.8 2,677 Central 10.4 13.1 54.5 4.1 41.6 9,857 Southern 12.1 17.8 57.9 5.2 37.2 10,485 Education No education 0.3 4.3 43.2 0.0 55.3 3,505 Primary 7.8 10.9 56.0 1.6 40.5 14,916 Secondary 30.1 38.0 71.7 15.7 19.0 4,177 More than secondary 66.4 70.5 75.4 42.4 3.5 422 Wealth quintile Lowest 5.1 3.3 30.9 0.5 65.8 4,268 Second 5.7 4.1 47.4 0.8 49.9 4,332 Middle 7.7 6.2 60.4 1.0 36.7 4,517 Fourth 9.5 10.2 66.6 1.8 30.6 4,515 Highest 27.3 48.3 75.7 16.5 14.5 5,388 Total 11.8 15.9 57.3 4.7 38.2 23,020 Table 3.4.2 Exposure to mass media: Men Percentage of men age 15-49 who are exposed to specific media on a weekly basis, by background characteristics, Malawi 2010 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 All three media at least once a week No media at least once a week Number Age 15-19 24.4 41.1 73.1 13.7 17.9 1,748 20-24 30.2 39.0 76.2 17.7 16.4 1,239 25-29 26.3 33.7 78.4 13.6 15.0 1,099 30-34 23.7 29.8 76.1 13.5 19.9 948 35-39 24.3 27.7 76.4 11.9 17.4 798 40-44 25.9 28.0 84.3 12.4 11.6 529 45-49 21.7 24.8 76.3 11.5 18.6 458 Residence Urban 44.9 55.3 75.6 27.3 11.3 1,440 Rural 20.4 28.6 76.6 10.3 18.5 5,379 Region Northern 27.1 40.2 78.9 16.1 15.7 744 Central 22.4 31.5 76.8 11.7 17.3 3,074 Southern 28.5 35.7 75.4 15.7 16.9 3,001 Education No education 0.7 17.9 68.9 0.2 28.0 422 Primary 15.8 28.1 74.7 7.6 19.8 4,270 Secondary 46.3 46.4 80.9 25.5 9.7 1,904 More than secondary 83.8 78.9 84.8 63.0 3.2 223 Wealth quintile Lowest 11.6 20.6 64.0 4.7 30.7 997 Second 14.9 20.6 71.1 5.2 23.9 1,309 Middle 18.0 27.1 76.4 8.4 17.6 1,367 Fourth 24.6 30.1 81.4 11.9 14.2 1,376 Highest 48.0 60.8 83.5 31.4 5.7 1,770 Total 15-49 25.6 34.3 76.4 13.9 16.9 6,818 50-54 20.7 17.7 79.6 6.2 17.7 357 Total men 15-54 25.3 33.4 76.6 13.5 17.0 7,175 32 | Respondents’ Characteristics 3.5 EMPLOYMENT Employment is one source of empowerment for women, given that they exercise control over their own income. It is, however, difficult to measure employment status because even though some women work, it is on family farms, in family businesses, or in the informal sector, and such work is often not perceived as employment by the women and men themselves. As a result, it is difficult to capture this type of activity, which is rarely reported as work. The 2010 MDHS asked women and men detailed questions about their employment status in order to ensure complete coverage of employment in any sector, formal or informal. Women and men who reported that they were currently working and those who reported that they worked at some time during the 12 months preceding the survey are considered to have been employed. Additional information was collected on the type of work women and men were doing, whether they worked continuously throughout the year or not, for whom they worked, and the form in which they received their earnings. Tables 3.5.1 and 3.5.2 show the percent distribution of women and men age 15-49 by employment status, according to background characteristics. Fifty-six percent of women are currently employed. Seventeen percent of women reported that they worked at some point during the past Table 3.5.1 Employment status: Women Percent distribution of women age 15-49 by employment status, according to background characteristics, Malawi 2010 Background characteristic Employed in the 12 months preceding the survey Not employed in the 12 months preceding the survey Missing/ don’t know Total Number of women Currently employed1 Not currently employed Age 15-19 36.5 19.0 44.4 0.1 100.0 5,005 20-24 51.0 18.5 30.5 0.0 100.0 4,555 25-29 59.7 17.5 22.8 0.1 100.0 4,400 30-34 63.8 17.3 18.8 0.0 100.0 3,250 35-39 67.3 16.0 16.7 0.1 100.0 2,522 40-44 66.6 15.9 17.6 0.0 100.0 1,730 45-49 68.8 13.5 17.7 0.0 100.0 1,558 Marital status Never married 37.4 16.8 45.7 0.1 100.0 4,538 Married or living together 58.1 18.1 23.7 0.0 100.0 15,528 Divorced/separated/widowed 69.4 15.0 15.7 0.0 100.0 2,954 Number of living children 0 39.3 17.3 43.3 0.0 100.0 5,344 1-2 55.7 17.8 26.5 0.1 100.0 7,079 3-4 62.2 18.1 19.6 0.1 100.0 6,006 5+ 65.2 16.1 18.7 0.0 100.0 4,592 Residence Urban 49.5 12.3 38.2 0.0 100.0 4,302 Rural 56.9 18.6 24.4 0.1 100.0 18,718 Region Northern 52.7 19.4 27.8 0.1 100.0 2,677 Central 56.6 20.1 23.2 0.0 100.0 9,857 Southern 55.1 14.4 30.4 0.0 100.0 10,485 Education No education 56.2 17.8 25.9 0.1 100.0 3,505 Primary 56.4 18.4 25.2 0.0 100.0 14,916 Secondary 50.3 14.9 34.8 0.0 100.0 4,177 More than secondary 69.8 7.0 23.2 0.0 100.0 422 Wealth quintile Lowest 56.9 20.4 22.7 0.0 100.0 4,268 Second 56.3 18.9 24.6 0.1 100.0 4,332 Middle 56.7 18.4 24.7 0.1 100.0 4,517 Fourth 55.7 17.4 26.9 0.0 100.0 4,515 Highest 52.5 13.1 34.4 0.0 100.0 5,388 Total 55.5 17.4 27.0 0.0 100.0 23,020 1 ‘Currently employed’ is defined as having done work in the past seven days. Includes persons who did not work in the past seven days but who are regularly employed and were absent from work for leave, illness, vacation, or any other such reason. Respondents’ Characteristics | 33 12 months, but were not working at the time of the survey; while 27 percent of women reported not having worked at all in the 12 months preceding the survey. Older women are more likely to be currently employed when compared with their younger counterparts. While 37 percent of women age 15-19 are currently employed, 69 percent of women age 45-49 are employed. More rural women are currently employed than their urban counterparts (57 and 50 percent, respectively). Women who are divorced, separated, or widowed (69 percent), those with five or more children (65 percent), and women with more than a secondary education (70 percent) are more likely to be currently employed than their counterparts. Women in the highest wealth quintile were the least likely to be currently employed and the most likely to have been unemployed during the 12 months preceding the survey (53 and 34 percent, respectively). A similar pattern is observed in men’s employment status. Overall, 82 percent of men age 15- 49 are currently employed, 7 percent worked in the 12 months prior to the survey but are not currently working, and 11 percent have not been employed for the 12 months preceding the survey. Men age Table 3.5.2 Employment status: Men Percent distribution of men age 15-49 by employment status, according to background characteristics, Malawi 2010 Background characteristic Employed in the 12 months preceding the survey Not employed in the 12 months preceding the survey Missing/ don’t know Total Number of men Currently employed1 Not currently employed Age 15-19 60.3 10.8 28.9 0.0 100.0 1,748 20-24 79.4 7.5 13.1 0.0 100.0 1,239 25-29 91.1 4.9 4.1 0.0 100.0 1,099 30-34 93.9 3.6 2.4 0.1 100.0 948 35-39 92.8 5.8 1.4 0.0 100.0 798 40-44 95.0 3.8 1.1 0.1 100.0 529 45-49 91.9 6.0 2.1 0.0 100.0 458 Marital status Never married 64.9 9.9 25.2 0.0 100.0 2,689 Married or living together 93.3 4.7 1.9 0.0 100.0 3,895 Divorced/separated/widowed 90.7 5.4 3.9 0.0 100.0 234 Number of living children 0 66.9 9.6 23.6 0.0 100.0 2,918 1-2 93.3 4.2 2.4 0.0 100.0 1,485 3-4 92.6 5.5 1.8 0.1 100.0 1,269 5+ 94.2 4.4 1.4 0.0 100.0 1,146 Residence Urban 76.3 5.2 18.6 0.0 100.0 1,440 Rural 83.6 7.2 9.2 0.0 100.0 5,379 Region Northern 78.3 4.9 16.8 0.0 100.0 744 Central 85.3 6.4 8.2 0.0 100.0 3,074 Southern 79.6 7.6 12.8 0.0 100.0 3,001 Education No education 85.5 9.4 5.0 0.1 100.0 422 Primary 83.7 6.9 9.3 0.0 100.0 4,270 Secondary 77.5 6.0 16.4 0.0 100.0 1,904 More than secondary 82.3 4.6 13.2 0.0 100.0 223 Wealth quintile Lowest 82.2 10.6 7.2 0.1 100.0 997 Second 84.3 6.9 8.7 0.1 100.0 1,309 Middle 86.4 5.3 8.3 0.0 100.0 1,367 Fourth 83.3 7.3 9.4 0.0 100.0 1,376 Highest 75.9 5.2 18.8 0.0 100.0 1,770 Total 15-49 82.0 6.8 11.2 0.0 100.0 6,818 50-54 90.2 5.5 4.2 0.0 100.0 357 Total men 15-54 82.4 6.7 10.8 0.0 100.0 7,175 1 ‘Currently employed’ is defined as having done work in the past seven days. Includes persons who did not work in the past seven days but who are regularly employed and were absent from work for leave, illness, vacation, or any other such reason. 34 | Respondents’ Characteristics 40-44 are more likely to be currently employed (95 percent) than men in other age groups. Men who are divorced, separated, or widowed (91 percent) are more likely to be currently employed than those who have never married (65 percent). Similar to the pattern seen among women, employment status is associated with the number of living children that the man has. Sixty-seven percent of men with no living children were currently working compared with 93 percent of men with one to two children. As observed with women, men in rural areas are more likely to be currently employed than men in urban areas (84 and 76 percent, respectively). Likewise, women and men in the Central Region are more likely to be currently employed than their counterparts in other regions: 57 percent for women and 85 percent for men. 3.6 OCCUPATION Respondents who reported that they are currently employed or that they worked in the 12 months preceding the survey were asked what type of work they normally do. Tables 3.6.1 and 3.6.2 show the distribution of women and men by occupation, according to background characteristics. Table 3.6.1 Occupation: Women Percent distribution of women age 15-49 employed in the 12 months preceding the survey by occupation, according to background characteristics, Malawi 2010 Background characteristic Professional/ technical/ managerial Clerical Sales and services Skilled manual Unskilled manual1 Domestic service Agriculture Total Number of women Age 15-19 0.3 0.2 16.3 5.4 7.9 2.1 67.8 100.0 2,780 20-24 1.7 0.8 26.0 5.5 6.1 1.7 58.2 100.0 3,168 25-29 2.1 1.1 29.4 6.7 6.4 1.7 52.6 100.0 3,396 30-34 2.6 1.4 28.0 6.8 6.1 1.5 53.6 100.0 2,637 35-39 3.5 0.7 25.2 7.2 5.5 1.5 56.4 100.0 2,101 40-44 3.7 1.3 23.0 7.4 5.9 1.0 57.7 100.0 1,426 45-49 1.3 0.6 21.1 8.3 7.6 1.0 60.0 100.0 1,283 Marital status Never married 2.1 1.6 19.3 5.5 8.8 3.0 59.7 100.0 2,460 Married or living together 2.0 0.6 25.1 6.4 5.5 0.9 59.4 100.0 11,838 Divorced/separated/widowed 2.1 1.5 28.0 7.9 8.6 3.6 48.4 100.0 2,491 Number of living children 0 2.1 1.4 20.2 5.5 7.5 2.9 60.4 100.0 3,028 1-2 2.9 1.4 27.7 6.1 6.0 1.9 54.0 100.0 5,202 3-4 1.8 0.6 26.1 7.0 6.3 1.0 57.2 100.0 4,826 5+ 1.2 0.1 22.1 7.3 6.6 0.9 61.8 100.0 3,734 Residence Urban 6.1 3.9 53.1 7.5 6.7 6.6 16.1 100.0 2,657 Rural 1.3 0.3 19.3 6.3 6.4 0.6 65.6 100.0 14,133 Region Northern 2.2 0.3 29.6 7.3 4.0 0.5 56.1 100.0 1,930 Central 1.6 0.7 22.4 6.7 8.2 1.3 59.0 100.0 7,565 Southern 2.4 1.3 25.7 6.1 5.3 2.2 57.0 100.0 7,294 Education No education 0.0 0.1 16.4 6.6 7.2 0.9 68.8 100.0 2,596 Primary 0.4 0.1 22.4 6.6 6.5 1.7 62.2 100.0 11,149 Secondary 6.1 2.9 41.4 6.3 5.7 2.0 35.6 100.0 2,722 More than secondary 42.0 16.4 27.3 3.7 6.1 1.1 3.5 100.0 324 Wealth quintile Lowest 0.3 0.1 14.2 5.0 8.9 0.5 71.0 100.0 3,299 Second 0.2 0.0 16.7 6.0 7.6 0.5 68.9 100.0 3,260 Middle 0.7 0.0 19.2 7.4 5.9 0.8 66.0 100.0 3,396 Fourth 0.9 0.5 26.7 6.4 5.6 2.0 57.9 100.0 3,299 Highest 7.7 3.7 45.1 7.8 4.6 4.0 27.2 100.0 3,536 Total 2.0 0.9 24.7 6.5 6.5 1.6 57.8 100.0 16,790 1 Unskilled manual labour includes cases for occupations for unskilled labour and cases for which occupation information was missing for respondents who worked in the past 12 months, but did not provide information on their occupation. Respondents’ Characteristics | 35 Among women, more than half of women are employed in the agricultural sector, and a quarter of women are employed in sales and services (58 and 25 percent, respectively). Seven percent of women are engaged in both skilled and unskilled manual jobs. Forty-two percent of women with more than secondary school education are in professional, technical, or managerial occupations representing the majority in that educational group. On the other hand, 69 percent of women with no education and 62 percent of women with a primary school education are employed in the agricultural sector. Findings for men are similar to those for women: Table 3.6.2 shows that the highest proportion of men age 15-49 work in agriculture (49 percent). Eighteen percent of men work as skilled labourers, followed by 16 percent of men in sales and services. The trends in occupation type by the level of education are very similar to those for women. The majority of men with more than a secondary education (45 percent) are in the professional, technical, or managerial occupations, while 65 percent of men with no education have agricultural occupations. Table 3.6.2 Occupation: Men Percent distribution of men age 15-49 employed in the 12 months preceding the survey by occupation, according to background characteristics, Malawi 2010 Background characteristic Professional/ technical/ managerial Clerical Sales and services Skilled manual Unskilled manual1 Domestic service Agriculture Total Number of men Age 15-19 0.5 0.2 9.8 10.6 13.2 2.0 63.8 100.0 1,243 20-24 3.0 1.1 14.6 21.8 10.5 1.5 47.5 100.0 1,076 25-29 3.4 1.7 18.5 22.9 13.0 1.3 39.2 100.0 1,054 30-34 5.0 2.4 19.7 20.1 7.8 1.0 44.0 100.0 924 35-39 4.5 1.7 18.6 19.2 7.8 0.8 47.4 100.0 787 40-44 9.1 2.9 14.7 19.7 5.3 2.0 46.4 100.0 522 45-49 5.2 1.1 14.7 14.4 8.0 0.4 56.2 100.0 448 Marital status Never married 2.7 0.9 11.7 14.9 12.6 1.9 55.2 100.0 2,011 Married or living together 4.4 1.7 17.8 19.8 8.5 1.1 46.7 100.0 3,818 Divorced/separated/widowed 2.3 1.1 12.8 24.5 15.0 1.4 43.0 100.0 225 Number of living children 0 3.0 0.8 12.1 15.3 12.4 1.9 54.5 100.0 2,230 1-2 4.5 1.9 17.5 20.6 11.1 1.4 43.0 100.0 1,449 3-4 3.8 2.3 20.4 19.8 8.0 0.9 45.0 100.0 1,245 5+ 4.4 1.2 14.9 19.9 6.7 0.7 52.3 100.0 1,130 Residence Urban 9.7 4.0 28.5 31.1 12.1 4.0 10.6 100.0 1,172 Rural 2.3 0.8 12.5 15.3 9.6 0.7 58.7 100.0 4,882 Region Northern 3.7 1.1 11.4 15.2 13.9 0.5 54.2 100.0 619 Central 3.4 1.2 14.3 17.0 8.9 1.2 54.0 100.0 2,821 Southern 4.1 1.8 18.0 20.6 10.5 1.7 43.3 100.0 2,615 Education No education 0.0 0.4 11.0 16.6 7.3 0.2 64.5 100.0 400 Primary 0.4 0.7 14.0 17.1 10.5 1.1 56.2 100.0 3,870 Secondary 7.8 3.0 21.1 21.6 10.3 2.4 33.9 100.0 1,591 More than secondary 45.0 5.8 11.0 20.6 7.0 0.1 10.5 100.0 193 Wealth quintile Lowest 0.4 0.0 8.3 12.7 10.4 0.3 68.0 100.0 925 Second 0.2 0.3 12.0 14.3 11.0 0.4 61.8 100.0 1,194 Middle 0.9 0.6 12.7 17.0 12.4 0.6 55.7 100.0 1,253 Fourth 2.2 1.7 16.0 19.8 9.2 1.8 49.3 100.0 1,246 Highest 12.7 3.8 25.4 25.2 8.0 3.2 21.7 100.0 1,436 Total 15-49 3.7 1.4 15.6 18.3 10.1 1.4 49.4 100.0 6,054 50-54 5.5 0.5 15.8 15.3 7.2 0.3 55.5 100.0 342 Total men 15-54 3.8 1.4 15.6 18.2 10.0 1.3 49.7 100.0 6,396 1 Unskilled manual labour includes cases for occupations for unskilled labour and cases for which occupation information was missing for respondents who worked in the past 12 months, but did not provide information on their occupation. 36 | Respondents’ Characteristics 3.7 EARNINGS, EMPLOYERS, AND CONTINUITY OF EMPLOYMENT Tables 3.7.1 and 3.7.2 show the distribution of women and men by type of earnings, type of employer, and continuity of employment. Table 3.7.1 separately presents information on women engaged in agricultural or nonagricultural work. The two sectors influence the type of earnings women receive, the type of employer they work for, and the continuity of their employment. Over half of women (58 percent) employed in agricultural work are not paid; this compares with one in five women (21 percent) who are employed in nonagricultural work and are not paid. More than two- thirds of the women employed in the agricultural sector are self-employed and work seasonally (67 and 70 percent, respectively). About a quarter of women in agricultural work are employed by a family member (26 percent) compared with 11 percent of women employed in nonagricultural work. Among women employed in the nonagricultural sector, 72 percent earn cash only, 67 percent are self- employed, and 47 percent work all year. Table 3.7.1 Type of employment: Women Percent distribution of women age 15-49 employed in the 12 months preceding the survey by type of earnings, type of employer, and continuity of employment, according to type of employment (agricultural or nonagricultural), Malawi 2010 Employment characteristic Agricultural work Nonagricultural work Missing Total Type of earnings Cash only 25.9 71.8 2.3 45.1 Cash and in-kind 11.2 6.0 4.3 9.0 In-kind only 5.0 1.2 0.0 3.4 Not paid 57.7 20.7 91.2 42.3 Missing 0.2 0.3 2.1 0.3 Total 100.0 100.0 100.0 100.0 Type of employer Employed by family member 25.9 10.7 2.7 19.5 Employed by nonfamily member 6.6 22.3 0.0 13.2 Self-employed 67.3 66.7 95.1 67.1 Missing 0.1 0.3 2.1 0.2 Total 100.0 100.0 100.0 100.0 Continuity of employment All year 23.8 47.4 78.7 33.8 Seasonal 69.8 29.6 13.0 52.8 Occasional 6.2 22.6 6.2 13.1 Missing 0.2 0.3 2.1 0.3 Total 100.0 100.0 100.0 100.0 Number of women employed during the last 12 months 9,705 7,040 45 16,790 Note: Total includes women with missing information on type of employment who are not shown separately. Table 3.7.2 shows that half of the men (50 percent) employed in agricultural work are not paid. Fifty-six percent of men in agricultural work are self-employed, and 61 percent work seasonally. Among men employed in the nonagricultural sector, 82 percent are paid in cash only, 46 percent are self-employed, and 59 percent work all year. Respondents’ Characteristics | 37 Table 3.7.2 Type of employment: Men Percent distribution of men age 15-49 employed in the 12 months preceding the survey by type of earnings, type of employer, and continuity of employment, according to type of employment (agricultural or nonagricultural), Malawi 2010 Employment characteristic Agricultural work Nonagricultural work Missing Total Type of earnings Cash only 35.0 81.7 59.5 56.4 Cash and in-kind 11.2 4.3 2.2 7.5 In-kind only 3.4 0.6 0.3 2.0 Not paid 50.4 13.4 37.8 34.1 Total 100.0 100.0 100.0 100.0 Type of employer Employed by family member 33.4 9.2 16.7 21.9 Employed by nonfamily member 10.9 45.0 44.4 28.1 Self-employed 55.7 45.7 38.7 49.9 Total 100.0 100.0 100.0 100.0 Continuity of employment All year 35.1 58.8 22.9 43.5 Seasonal 61.4 27.6 42.3 45.8 Occasional 3.2 13.5 34.6 10.5 Total 100.0 100.0 100.0 100.0 Number of men employed during the last 12 months 2,990 2,452 612 6,054 Note: Total includes men with missing information on type of employment who are not shown separately. 3.8 KNOWLEDGE AND ATTITUDES REGARDING TUBERCULOSIS The 2010 MDHS collected information on knowledge and attitudes towards tuberculosis (TB), a major public health concern worldwide. Respondents were asked if they had ever heard of TB and how it is spread, whether the disease is curable and through what methods, and several other TB- related questions. Additionally, respondents were asked whether or not they would want other people to know if a family member had TB. Tables 3.8.1 and 3.8.2 present information on knowledge and attitudes concerning TB for women and men age 15-49, by background characteristics. Almost all women and men are knowledgeable about TB: 98 percent of women and 99 percent of men. Among all respondents who report having heard of TB, 78 percent of women and 86 percent of men reported that TB is spread through the air by coughing. The greatest differentials regarding knowledge of the spread of TB and attitudes on whether it can be cured are observed by respondents’ educational levels. Eighty-nine percent of women and 92 percent of men with at least a secondary school education correctly reported that TB is spread through the air by coughing compared with 74 percent of women and 80 percent of men with no education. Ninety-two percent of women with at least a secondary school education believe that TB can be cured compared with 73 percent of women with no education. For men, 96 percent with at least a secondary school education believe TB can be cured compared with 75 percent with no education. 38 | Respondents’ Characteristics Table 3.8.1 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 percentages who know that TB is spread through the air by coughing, the percentage who believe that TB can be cured, and the percentage who would want to keep secret that a family member has TB, by background characteristics, Malawi 2010 Background characteristic Among all respondents Among respondents who have heard of TB Percentage who have heard of TB Number Percentage who report that TB is spread through the air by coughing Percentage who believe that TB can be cured Percentage who would want a family member’s TB kept secret Number Age 15-19 96.0 5,005 73.1 67.7 52.5 4,803 20-24 97.6 4,555 76.2 79.1 51.1 4,446 25-29 98.5 4,400 80.8 83.3 50.5 4,335 30-34 98.7 3,250 82.7 85.1 51.3 3,209 35-39 97.7 2,522 78.9 81.9 49.1 2,463 40-44 98.1 1,730 81.7 82.0 49.0 1,697 45-49 98.5 1,558 80.9 80.9 47.8 1,534 Residence Urban 99.5 4,302 87.1 90.5 48.3 4,280 Rural 97.3 18,718 76.3 76.3 51.3 18,208 Region Northern 98.3 2,677 65.6 70.8 53.5 2,633 Central 97.2 9,857 77.5 73.3 45.2 9,581 Southern 98.0 10,485 82.5 86.4 55.1 10,273 Education No education 95.6 3,505 73.7 72.7 54.0 3,350 Primary 97.6 14,916 75.8 76.2 51.6 14,552 Secondary 99.7 4,177 89.3 91.8 46.9 4,164 More than secondary 100.0 422 97.8 99.3 30.4 422 Wealth quintile Lowest 95.6 4,268 71.8 69.9 49.2 4,081 Second 96.4 4,332 73.8 72.8 53.3 4,176 Middle 97.6 4,517 76.9 76.3 51.9 4,411 Fourth 98.6 4,515 79.7 81.6 52.1 4,454 Highest 99.6 5,388 87.0 90.8 47.7 5,366 Total 97.7 23,020 78.4 79.0 50.7 22,487 Women in the highest wealth quintile are more likely to believe that TB can be cured (91 percent) compared with those from the lowest quintile (70 percent). A similar pattern is observed among men (94 percent and 81 percent, respectively). Overall, women are more likely than men to want to conceal the fact that a family member has TB (51 and 34 percent, respectively). Data on both sexes show that attitudes on whether they would want others to know that their family member had TB are associated with the level of education. Fifty-four percent of females and 44 percent of males with no education would want knowledge of their family member’s TB kept a secret compared with 30 percent of women and 17 percent of men with more than a secondary school education. Respondents’ Characteristics | 39 Table 3.8.2 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 percentages who know that TB is spread through the air by coughing, the percentage who believe that TB can be cured, and the percentage who would want to keep secret that a family member has TB, by background characteristics, Malawi 2010 Background characteristic Among all respondents Among respondents who have heard of TB Percentage who have heard of TB Number Percentage who report that TB is spread through the air by coughing Percentage who believe that TB can be cured Percentage who would want a family member’s TB kept secret Number Age 15-19 96.3 1,748 82.5 78.4 38.2 1,683 20-24 98.7 1,239 85.0 88.4 35.4 1,223 25-29 99.3 1,099 85.3 90.9 32.0 1,091 30-34 99.8 948 88.3 93.5 33.5 947 35-39 99.6 798 87.5 90.9 31.3 795 40-44 99.5 529 90.4 92.3 27.5 527 45-49 99.1 458 86.8 92.0 26.4 453 Residence Urban 99.2 1,440 88.2 94.5 28.9 1,428 Rural 98.3 5,379 85.1 86.1 34.8 5,289 Region Northern 98.5 744 80.4 82.5 45.0 733 Central 98.7 3,074 89.0 85.5 29.3 3,035 Southern 98.3 3,001 83.7 91.6 35.2 2,950 Education No education 95.0 422 80.4 75.4 43.8 401 Primary 98.2 4,270 83.0 84.7 35.8 4,195 Secondary 99.9 1,904 92.0 96.3 28.4 1,902 More than secondary 99.2 223 93.8 98.9 16.9 221 Wealth quintile Lowest 97.0 997 81.7 80.9 35.7 967 Second 98.4 1,309 83.5 84.6 35.1 1,288 Middle 98.4 1,367 86.2 87.5 35.3 1,345 Fourth 98.5 1,376 86.0 88.3 36.3 1,354 Highest 99.6 1,770 89.1 94.1 27.8 1,762 Total 15-49 98.5 6,818 85.7 87.9 33.6 6,718 50-54 99.4 357 88.0 91.2 24.0 354 Total men 15-54 98.6 7,175 85.9 88.0 33.1 7,072 3.9 TOBACCO USE Tobacco is used in various ways. It is dried and rolled into cigarettes and cigars for smoking, shredded and inserted into pipes (also for smoking), and finely pulverised for inhalation as snuff. Smoking has been shown to have significant adverse health effects, including increased risk of respiratory and cardiovascular illnesses both for the individual smoker and for other people exposed to second-hand or environmental tobacco smoke (WHO, 2002). Information on women’s and men’s tobacco use was collected during the 2010 MDHS. Tables 3.9.1 and 3.9.2 show the percentages of women and men age 15-49 who smoke cigarettes or a pipe or use other forms of tobacco. Additionally, both tables show the percent distribution of cigarette smokers age 15-49 by the number of cigarettes smoked in the past 24 hours, according to background characteristics. The majority of women (99 percent) and men (83 percent) reported that they do not use tobacco. Only one percent of women reported using tobacco. Two percent of women in the Northern Region reported using tobacco, compared with one percent each for women in the Central and Southern Regions. Women with no education are more likely to use tobacco products (4 percent) than their counterparts who have been to school. Among men age 15-49, 17 percent reported they use tobacco products, of which almost all smoke cigarettes. Men in rural areas are more likely to smoke cigarettes (19 percent) compared with their urban counterparts (10 percent). Cigarette smoking among 40 | Respondents’ Characteristics men is also highest among men with no education and among those in the lowest wealth quintile (34 percent and 29 percent, respectively). Men from the Central Region are most likely to smoke cigarettes (20 percent) compared with men from the Northern Region and the Southern Region (both 14 percent). By age, tobacco use is highest among men age 45-49 (32 percent). Among men who use tobacco, 63 percent report smoking one to five cigarettes in the last 24 hours. Sixteen percent of men report smoking 6-9 cigarettes in the last 24 hours and 14 percent reported smoking 10 or more cigarettes in the last 24 hours. Half of women that report using tobacco smoked one to five cigarettes in the last 24 hours. Table 3.9.1 Use of tobacco: Women Percentage of women age 15-49 who smoke cigarettes or a pipe or use other tobacco products and the percent distribution of cigarette smokers by number of cigarettes smoked in preceding 24 hours, according to background characteristics and maternity status, Malawi 2010 Background characteristic Cigarettes Pipe Other tobacco Does not use tobacco Number of women Number of cigarettes in the last 24 hours Total Number of cigarette smokers 1-2 3-5 6-9 10+ Don’t know/ missing Age 15-19 0.1 0.0 0.0 99.8 5,005 * * * * * 100.0 4 20-24 0.2 0.0 0.1 99.7 4,555 * * * * * 100.0 10 25-29 0.3 0.0 0.4 99.4 4,400 * * * * * 100.0 14 30-34 0.6 0.1 0.3 99.2 3,250 * * * * * 100.0 19 35-39 0.4 0.0 1.3 98.4 2,522 * * * * * 100.0 9 40-44 1.1 0.0 3.4 95.9 1,730 * * * * * 100.0 19 45-49 1.0 0.0 4.5 94.8 1,558 * * * * * 100.0 15 Residence Urban 0.5 0.1 0.2 99.4 4,302 * * * * * 100.0 21 Rural 0.4 0.0 1.0 98.7 18,718 14.0 34.5 4.6 4.3 42.7 100.0 70 Region Northern 0.3 0.0 1.5 98.3 2,677 * * * * * 100.0 7 Central 0.3 0.0 0.8 98.9 9,857 * * * * * 100.0 34 Southern 0.5 0.0 0.7 98.9 10,485 26.7 24.0 5.9 6.0 37.4 100.0 50 Education No education 1.0 0.0 2.5 96.8 3,505 (22.8) (53.2) (8.1) (8.9) (7.0) 100.0 33 Primary 0.3 0.0 0.7 99.1 14,916 (17.9) (16.4) (1.1) (4.8) (59.9) 100.0 45 Secondary 0.3 0.0 0.2 99.7 4,177 * * * * * 100.0 11 More than secondary 0.3 0.0 0.0 99.7 422 * * * * * 100.0 1 Maternity status Pregnant 0.2 0.0 0.4 99.4 2,072 * * * * * 100.0 3 Breastfeeding (not pregnant) 0.3 0.0 0.5 99.2 7,403 (5.1) (14.4) (0.0) (3.7) (76.8) 100.0 23 Neither 0.5 0.0 1.1 98.5 13,544 26.4 33.1 5.0 6.7 28.8 100.0 64 Wealth quintile Lowest 0.5 0.0 1.2 98.4 4,268 * * * * * 100.0 20 Second 0.5 0.0 1.3 98.3 4,332 * * * * * 100.0 23 Middle 0.3 0.0 1.0 98.8 4,517 * * * * * 100.0 11 Fourth 0.5 0.0 0.6 98.9 4,515 (4.8) (43.9) (4.8) (9.0) (37.5) 100.0 23 Highest 0.3 0.0 0.2 99.6 5,388 * * * * * 14 Total 0.4 0.0 0.8 98.8 23,020 20.0 30.3 3.5 5.7 40.6 100.0 91 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. Respondents’ Characteristics | 41 Table 3.9.2 Use of tobacco: Men Percentage of men age 15-49 who smoke cigarettes or a pipe or use other tobacco products and the percent distribution of cigarette smokers by number of cigarettes smoked in preceding 24 hours, according to background characteristics, Malawi 2010 Background characteristic Cigarettes Pipe Other tobacco Does not use tobacco Number of men Number of cigarettes in the last 24 hours Total Number of cigarette smokers 0 1-2 3-5 6-9 10+ Don’t know/ missing Age 15-19 2.5 0.0 0.4 97.2 1,748 (9.9) (30.7) (29.2) (3.1) (12.6) 14.5 100.0 44 20-24 12.8 0.0 1.0 87.0 1,239 4.1 33.4 38.5 9.9 12.5 1.6 100.0 159 25-29 21.2 0.1 1.3 78.5 1,099 5.4 32.5 32.3 21.1 8.0 0.7 100.0 233 30-34 22.8 0.1 1.3 77.0 948 6.5 20.2 44.7 11.2 15.4 2.0 100.0 216 35-39 27.4 0.5 1.7 71.9 798 1.8 24.8 33.4 22.1 14.5 3.3 100.0 219 40-44 25.5 0.0 1.2 74.2 529 6.1 21.4 41.6 14.4 15.0 1.6 100.0 135 45-49 31.6 0.0 3.2 66.4 458 2.3 17.6 40.6 19.4 19.5 0.7 100.0 144 Residence Urban 10.0 0.0 0.5 89.9 1,440 10.2 23.4 42.3 7.9 15.5 0.7 100.0 144 Rural 18.7 0.1 1.4 80.8 5,379 3.8 25.9 37.0 17.4 13.4 2.4 100.0 1,006 Region Northern 14.2 0.1 1.1 85.1 744 3.0 25.3 35.6 16.4 16.1 3.6 100.0 105 Central 20.0 0.2 1.3 79.6 3,074 4.3 24.4 41.2 17.5 11.7 0.8 100.0 615 Southern 14.3 0.0 1.1 85.3 3,001 5.4 27.4 33.2 14.3 15.9 3.8 100.0 429 Education No education 33.5 0.7 3.3 65.8 422 2.9 27.2 29.3 20.3 18.2 2.0 100.0 141 Primary 19.2 0.1 1.4 80.3 4,270 3.7 25.5 38.7 16.5 13.9 1.8 100.0 819 Secondary 9.7 0.1 0.3 90.3 1,904 10.3 25.0 40.5 12.1 8.3 3.8 100.0 184 More than secondary 2.5 0.0 0.0 97.5 223 * * * * * * 100.0 6 Wealth quintile Lowest 29.2 0.4 2.5 69.9 997 4.8 25.2 37.6 15.5 16.3 0.6 100.0 291 Second 21.4 0.1 2.0 77.9 1,309 2.5 23.5 35.4 21.7 14.1 2.8 100.0 281 Middle 18.4 0.1 0.9 81.3 1,367 4.2 30.6 33.0 17.5 12.2 2.5 100.0 252 Fourth 13.9 0.0 1.0 85.7 1,376 5.0 26.1 42.8 12.2 11.4 2.3 100.0 191 Highest 7.6 0.0 0.2 92.3 1,770 8.9 20.8 44.2 9.4 13.2 3.5 100.0 134 Total 15-49 16.9 0.1 1.2 82.7 6,818 4.6 25.6 37.7 16.2 13.7 2.2 100.0 1,150 50-54 31.4 0.2 1.7 67.4 357 6.7 14.2 50.4 9.3 17.9 1.4 100.0 112 Total men 15-54 17.6 0.1 1.2 82.0 7,175 4.8 24.6 38.8 15.6 14.1 2.1 100.0 1,262 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. Fertility | 43 FERTILITY 4 4.1 INTRODUCTION This chapter focuses on a number of fertility indicators including levels, patterns, and trends in both current and cumulative fertility; the length of birth intervals; and the age at which women begin childbearing. Information on current and cumulative fertility is essential for monitoring population growth. Birth intervals are important because short intervals are associated with high childhood mortality. The age at which childbearing begins can also have a major impact on the health and wellbeing of both the mother and the child. To generate data on fertility, a birth history was collected from each woman interviewed in the 2010 MDHS. Women were asked to report the total number of sons and daughters to whom they had given birth in their lifetime. To ensure all information was reported, women were asked separately about children still living at home, those living elsewhere, and those who had died. Sex, date of birth, and survival status of each child was obtained, and age at death for dead children was recorded.1 4.2 CURRENT FERTILITY The level of current fertility is one of the most important topics in this report because of its direct relevance to population policies and programmes. Measures of current fertility presented in this chapter include age-specific fertility rates (ASFR), the total fertility rate (TFR), the general fertility rate (GFR), and the crude birth rate (CBR). The rates are presented for the period 1 to 36 months preceding the survey, which was determined from the date of interview and a child’s birth date. A three-year period is chosen for calculating these rates to provide the most current information, to reduce sampling error, and to avoid problems from the displacement of births. Age-specific fertility rates show the age pattern of fertility. Numerators for the ASFRs are calculated by identifying live births that occurred in the three-year period preceding the survey and classifying them by the age of the mother (in five-year age groups) at the time of the child’s birth. The denominators of the rates represent the number of woman-years lived by the survey respondents in each of the five-year age groups during the specified period. The TFR refers to the number of live births a woman would have if she were subject to the current age-specific fertility rates throughout her reproductive years (15-49 years). The GFR represents the number of live births per 1,000 women of reproductive age. The CBR is the number of live births per 1,000 population. The latter two measures are based on birth history data for the three-year period before the survey and the age-sex distribution of the household population. 1 The survey results in this chapter are presented for the country as a whole, by urban-rural residence, and by region. District-level results are available in Appendix A. Table 4.1 Current fertility Age-specific and total fertility rates, the general fertility rate, and the crude birth rate for the three years preceding the survey, by residence, Malawi 2010 Age group Residence Total Urban Rural 15-19 109 162 152 20-24 206 285 269 25-29 200 248 238 30-34 133 222 206 35-39 125 169 162 40-44 32 91 82 45-49 3 38 33 TFR (15-49) 4.0 6.1 5.7 GFR 154 213 202 CBR 36.0 39.8 39.2 Notes: Age-specific fertility rates are per 1,000 women. Rates for age group 45-49 may be slightly biased due to truncation. Rates are for the period 1-36 months prior to interview. TFR: Total fertility rate expressed per woman GFR: General fertility rate expressed per 1,000 women CBR: Crude birth rate, expressed per 1,000 population 44 | Fertility Table 4.1 shows age-specific fertility rates for women by five-year age groups; it also shows the current fertility for the three-year period preceding the 2010 MDHS. Age-specific and total fertility rates were calculated directly from the birth history data. The sum of age-specific fertility rates (known as the total fertility rate, or TFR) is a summary measure of the level of fertility. If fertility were to remain constant at current levels, a Malawian woman would bear an average of 5.7 children in her lifetime. The phenomenon of rural-urban variation in fertility also holds true, as the table indicates that rural women will give birth to two more children during their reproductive years than urban women (6.1 and 4.0, respectively). This rural-urban difference in the TFR is similar to that observed in the 2004 MDHS. The TFR measured in the 2010 MDHS (5.7) is slightly lower than the TFR measured in the 2004 MDHS (6.0). Examination of the age pattern of fertility rates show that the peak of childbearing in Malawi is during age 20-24. The same age pattern was observed in the 2004 MDHS. Table 4.1 further shows a general fertility rate of 202 live births per 1,000 women age 15-44 years and a crude birth rate of 39.2 births per 1,000 population. This section examines associations between a woman’s background characteristics and her fertility. Table 4.2 shows fertility differentials by residence, region, education, and wealth quintile. The analysis of the fertility differentials in this report is conducted by presenting the TFR, percentage of currently pregnant women, and completed fertility in terms of the mean number of births to women age 40-49 by these characteristics. Table 4.2 Fertility by background characteristics Total fertility rate for the three years preceding the survey, percentage of women age 15-49 currently pregnant, and mean number of children ever born to women age 40-49 years, by background characteristics, Malawi 2010 Background characteristic Total fertility rate Percentage women age 15-49 currently pregnant Mean number of children ever born to women age 40-49 Residence Urban 4.0 5.8 5.8 Rural 6.1 9.7 6.7 Region Northern 5.7 9.4 6.5 Central 5.8 8.6 7.0 Southern 5.6 9.3 6.1 Education No education 6.9 8.7 7.1 Primary 5.9 9.8 6.5 Secondary 3.8 6.8 4.2 More than secondary 2.1 6.0 3.6 Wealth quintile Lowest 6.8 9.7 7.0 Second 6.8 11.0 7.2 Middle 6.3 10.5 6.8 Fourth 5.3 8.1 6.4 Highest 3.7 6.3 5.5 Total 5.7 9.0 6.6 Note: Total fertility rates are for the period 1-36 months prior to interview. Table 4.2 shows that the TFR in the Northern Region is 5.7 births per woman, while in the Central and Southern Regions it is 5.8 and 5.6 births per woman, respectively. Education consistently appears as an important variable in the analysis of fertility-related behaviour. Generally, the TFR declines as educational level increases. Women with more than a secondary education have a TFR of 2.1, compared with women with no education who have a TFR of 6.9. A similar relationship is reflected in the association between fertility rates and the wealth index, which shows that women have Fertility | 45 fewer children as wealth increases. Women in the highest wealth quintile have an average of three children fewer than women in the lowest quintile (3.7 and 6.8 births per woman, respectively). Nine percent of interviewed women reported that they were pregnant at the time of the survey. The percentage of women who are currently pregnant provides another measure of current fertility, although it is recognised that the survey may not capture all pregnancies because some women may not know that they are pregnant or may be reluctant to report early-stage pregnancies. The last column in Table 4.2 shows the mean number of children ever born (CEB) to women age 40-49. This is an indicator of cumulative fertility; it reflects the fertility performance of older women who are nearing the end of their reproductive period and thus represents completed fertility. The findings show that the mean number of children ever born to women age 40-49 (6.6 children per woman) is slightly higher than the TFR for the 3 years preceding the survey (5.7 children per woman), suggesting a slight recent reduction in fertility. 4.3 FERTILITY TRENDS Table 4.3.1 uses information from the retrospective birth histories obtained from the 2010 MDHS respondents to examine trends in age-specific fertility rates for successive five-year periods before the survey. To calculate these rates, births are classified according to the period of time in which the birth occurred and the mother’s age at the time of the birth. Because birth histories were not collected for women age 50 and older, the rates for older age groups become progressively more truncated for periods more distant from the survey date. For example, rates cannot be calculated for women age 45-49 for the period five to nine years or more preceding the survey because women in that age group would have been 50 years or older at the time of the survey. The results in Table 4.3.1 show age-specific fertility rates decreased between the two five- year periods prior to the survey for all age groups. A constant decrease is also observed for the last three periods before the survey for the 20-24, 25-29, 30-34, and 35-39 age groups. Table 4.3.1 Trends in age-specific fertility rates Age-specific fertility rates for five-year periods preceding the survey, by mother’s age at the time of the birth, Malawi 2010 Mother’s age at birth Number of years preceding survey 0-4 5-9 10-14 15-19 15-19 157 180 171 166 20-24 270 297 316 303 25-29 241 281 288 289 30-34 208 240 253 [297] 35-39 159 172 [207] - 40-44 82 [119] - - 45-49 [35] - - - Note: Age-specific fertility rates are per 1,000 women. Estimates in brackets are truncated. Rates exclude the month of interview. Another way to examine fertility trends is to compare current estimates with earlier surveys and censuses. The results shown in Table 4.3.2 and Figure 4.1 confirm the earlier conclusion that fertility has declined in Malawi in the past two decades and continues to decline. The TFR has substantially declined from 6.7 children per woman in the 1992 MDHS to 6.3 children per woman in the 2000 MDHS, to 6.0 children per woman in the 2004 MDHS, and to 5.7 children per woman in the 2010 MDHS. 46 | Fertility Table 4.3.2 Trends in age-specific and total fertility rates Age-specific and total fertility rates (TFR), Malawi DHS 1992- 2010 Mother’s age at birth 1992 MDHS1 2000 MDHS2 2004 MDHS3 2010 MDHS 15-19 161 172 162 152 20-24 287 305 293 269 25-29 269 272 254 238 30-34 254 219 222 206 35-39 197 167 163 162 40-44 120 94 80 82 45-49 58 41 35 33 TFR 15-49 6.7 6.3 6.0 5.7 Note: Age-specific fertility rates are per 1,000 women. 1 NSO and Macro International, 1994 2 NSO and ORC Macro, 2001 3 NSO and ORC Macro, 2005 Figure 4.1 Trends in Age-specific Fertility Rates, Various Sources, 1992-2010 MDHS 2010 # # # # # # # & & & & & & & , , , , , , , ) ) ) ) ) ) ) 15-19 20-24 25-29 30-34 35-39 40-44 45-49 Age group 0 50 100 150 200 250 300 350 Bi rt h s pe r 1 , 0 00 w om en MDHS 1992 MDHS 2000 MDHS 2004 MDHS 2010) , & # 4.4 CHILDREN EVER BORN AND LIVING Table 4.4 shows the distribution of all women and currently married women by the number of children ever born, according to five-year age groups. The table also shows the mean number of children ever born and the mean number of living children. Information on the number of children ever born reflects the accumulation of births over a woman’s entire reproductive period (parity) and therefore has limited reference to current fertility levels, particularly when the country has experienced a decline in fertility. However, as an indicator, the number of children ever born to all women is useful for observing how average family size varies across age groups, and for observing the level of primary infertility. Comparison of the mean number of children ever born to all women and the mean number of living children shows the cumulative effects of mortality during the childbearing period. Four-fifths of all women age 15-19 (80 percent) have never given birth. However, this proportion declines to 2 percent or less for women age 30 and older; indicating that childbearing among Malawian women is nearly universal. The percentage of women who are childless at the end Fertility | 47 of the reproductive period is an indirect measure of primary infertility (the proportion of women who are unable to bear children at all). Voluntary childlessness is rare in Malawi; therefore, it is likely that married women with no births are unable to have children. The data show that less than two percent of married women remain childless by their 40s. The same pattern is seen for currently married women, except that the mean number of children ever born is higher (3.8 children) among currently married women compared with all women (3.1 children). The difference in the mean number of children ever born to all women and to currently married women can be attributed to a substantial proportion of young and unmarried women in the former category who exhibit lower fertility. In addition to giving a description of average family size, information on children ever born and number of living children also gives some indication of the extent of childhood mortality. The 2010 MDHS results indicate that on average, all women have more than 2.6 surviving children, and currently married women have 3.2 children who survive. The difference between the mean number of children ever born and mean number of children still living for the two groups of women increases with a woman’s age. Table 4.4 Children ever born and living Percent distribution of all women and currently married women by number of children ever born, mean number of children ever born, and mean number of living children, according to age group, Malawi 2010 Age Number of children ever born Total Number of women Mean number of children ever born Mean number of living children 0 1 2 3 4 5 6 7 8 9 10+ ALL WOMEN 15-19 79.9 17.6 2.3 0.2 0.0 0.0 0.0 0.0 0.0 0.0 0.0 100.00 5,005 0.23 0.21 20-24 15.4 31.7 34.1 14.5 3.6 0.6 0.1 0.0 0.0 0.0 0.0 100.00 4,555 1.61 1.44 25-29 3.8 8.8 22.6 30.5 23.2 8.0 2.6 0.4 0.1 0.0 0.0 100.00 4,400 2.98 2.64 30-34 1.9 4.3 8.4 18.0 22.7 22.7 13.2 6.1 1.9 0.4 0.3 100.00 3,250 4.23 3.59 35-39 2.1 2.3 4.3 7.4 13.3 20.3 19.8 15.6 8.5 4.2 2.3 100.00 2,522 5.45 4.50 40-44 1.3 2.4 4.0 6.1 9.1 12.8 13.9 21.6 12.1 8.3 8.4 100.00 1,730 6.26 5.04 45-49 1.6 2.9 3.6 4.7 6.6 9.2 12.4 13.6 13.8 14.0 17.5 100.00 1,558 6.91 5.29 Total 21.8 13.0 13.8 12.9 10.9 8.7 6.4 5.2 3.1 2.1 2.1 100.00 23,020 3.07 2.57 CURRENTLY MARRIED WOMEN 15-19 37.0 53.6 8.6 0.7 0.0 0.0 0.0 0.0 0.0 0.0 0.0 100.00 1,171 0.73 0.65 20-24 4.9 33.6 39.9 16.8 4.2 0.6 0.1 0.0 0.0 0.0 0.0 100.00 3,469 1.84 1.65 25-29 2.0 7.5 22.5 31.8 24.1 8.7 2.8 0.5 0.1 0.0 0.0 100.00 3,718 3.09 2.74 30-34 1.2 3.5 7.6 17.4 22.5 24.1 13.9 6.8 2.2 0.5 0.3 100.00 2,636 4.37 3.74 35-39 1.5 1.5 3.5 5.5 11.9 20.8 21.3 16.8 9.9 4.5 2.8 100.00 2,040 5.70 4.73 40-44 1.2 2.1 3.6 4.6 7.8 12.0 14.3 22.8 12.4 9.2 9.8 100.00 1,339 6.48 5.21 45-49 1.3 2.2 2.8 4.0 5.2 7.8 12.5 13.5 14.1 16.3 20.2 100.00 1,155 7.26 5.62 Total 5.0 14.5 17.2 15.8 13.2 10.6 8.0 6.4 3.8 2.7 2.8 100.00 15,528 3.80 3.20 4.5 BIRTH INTERVALS A birth interval is defined as the period of time between two successive live births. Information about birth intervals is important in understanding the health status of young children. Research has shown that short birth intervals (<24 months) are associated with poor health outcomes, especially during infancy. Children born too soon after a previous birth, especially if the interval between the births is less than two years, have an increased risk of sickness and death at an early age. Longer birth intervals (more than two years), on the other hand, contribute to improved health status for both the mother and child. Table 4.5 presents the percent distribution of non-first births in the five years preceding the survey by number of months since preceding birth, according to selected demographic and socioeconomic variables. The median length of birth interval in Malawi is 36 months, which is the same as the median birth interval in the 2004 MDHS. The table further shows that 5 percent of non- first births are born after an interval of less than 18 months, and 10 percent are born after an interval of 18 to 23 months. One in three births (35 percent) are born 24 to 35 months after the previous birth, and 25 percent are born 36 to 47 months after the previous birth. 48 | Fertility The median number of months since the preceding birth increases markedly with age, from 26 months among mothers age 15-19 to 41 months among mothers age 40-49. The median birth interval does not vary much by birth order or sex of the preceding birth. However, there are notable variations in the median birth interval according to survival of the preceding birth, residence, and educational level. The median birth interval is higher (36.7 months) if the preceding birth’s survival status is living rather than dead (28.4 months). Variation by residence shows that the median birth interval for urban mothers is higher (39.8 months) than for rural mothers (35.7 mothers). By level of education, the median birth interval ranges from 35.9 months among women with no education to 55.3 months among women with more than secondary education. Table 4.5 Birth intervals Percent distribution of non-first births in the five years preceding the survey by number of months since preceding birth, and median number of months since preceding birth, according to background characteristics, Malawi 2010 Background characteristic Months since preceding birth Total Number of non-first births Median number of months since preceding birth 7-17 18-23 24-35 36-47 48-59 60+ Age 15-19 15.3 18.2 44.6 16.6 2.5 2.8 100.0 125 26.1 20-29 5.4 10.9 39.4 25.8 11.1 7.4 100.0 8,165 34.2 30-39 3.8 9.3 30.2 25.0 14.4 17.4 100.0 5,871 38.4 40-49 6.0 7.6 27.2 20.2 13.0 26.0 100.0 1,466 41.2 Birth order 2-3 5.0 10.2 36.2 25.1 12.0 11.4 100.0 7,160 35.6 4-6 4.2 9.4 33.7 25.0 13.3 14.4 100.0 6,173 36.8 7+ 6.5 11.3 33.5 23.6 11.7 13.3 100.0 2,294 35.4 Sex of preceding birth Male 5.0 9.4 34.6 23.8 13.3 13.9 100.0 7,853 36.3 Female 4.8 10.7 35.1 26.0 11.6 11.8 100.0 7,773 35.8 Survival of preceding birth Living 2.8 9.3 35.6 26.1 13.0 13.2 100.0 13,855 36.7 Dead 21.0 16.1 28.9 15.5 8.1 10.4 100.0 1,772 28.4 Residence Urban 5.2 8.1 29.5 23.5 15.2 18.4 100.0 2,064 39.8 Rural 4.8 10.4 35.6 25.1 12.0 12.0 100.0 13,562 35.7 Region Northern 4.2 7.7 38.1 27.1 12.0 10.9 100.0 1,805 36.0 Central 5.4 10.3 35.0 24.3 12.6 12.4 100.0 6,659 35.7 Southern 4.6 10.4 33.9 24.9 12.4 13.8 100.0 7,163 36.4 Education No education 5.3 11.2 33.8 23.4 12.4 13.9 100.0 3,170 35.9 Primary 4.8 10.2 36.1 25.5 11.9 11.5 100.0 10,616 35.6 Secondary 5.0 7.3 29.8 24.1 15.4 18.4 100.0 1,759 39.6 More than secondary 2.2 9.1 14.6 13.4 22.2 38.5 100.0 81 55.3 Wealth quintile Lowest 5.4 11.7 35.3 25.8 10.8 10.9 100.0 3,483 35.1 Second 5.8 10.7 36.9 24.3 11.6 10.7 100.0 3,472 35.1 Middle 4.6 9.9 36.7 26.0 11.3 11.5 100.0 3,396 35.6 Fourth 4.1 9.8 34.8 24.4 13.9 12.9 100.0 2,912 36.5 Highest 4.1 7.4 28.3 23.3 16.0 20.8 100.0 2,363 41.4 Total 4.9 10.1 34.8 24.9 12.5 12.9 100.0 15,627 36.1 Note: First-order births are excluded. The interval for multiple births is the number of months since the preceding pregnancy that ended in a live birth. Fertility | 49 4.6 AGE AT FIRST BIRTH The age at which childbearing commences is an important determinant of overall fertility as well as the health and welfare of the mother and child. In some societies, the delay of first births as a result of an increase in the age at marriage has contributed to a decrease in fertility. However, in Malawi, it is not uncommon for women to have children before getting married. Table 4.6 shows the percentage of women who have given birth by specific ages, according to their age at the time of the survey. Overall, the median age at first birth for women age 20-49 in Malawi is 18.9 years. The median age at first birth varies little by age group. In Malawi, 7 percent of women age 25-49 have given birth by age 15, and 65 percent have become mothers by age 20. Comparing the proportions of women who have given birth by age 15 across age groups provides another way to view trends in age at first birth over time. The results indicate a decrease in early childbearing over time. The percentage of women who gave birth by exact age 15 is 7 percent or higher among women age 35-49, around 5 percent among women age 20-34, and less than two percent among women age 15-19.This reduction in the percentage of women giving birth early supports the findings that age at first childbirth has been increasing slowly. Table 4.6 Age at first birth Percentage of women age 15-49 who gave birth by exact ages, percentage who have never given birth, and median age at first birth, according to current age, Malawi 2010 Current age Percentage who gave birth by exact age Percentage who have never given birth Number of women Median age at first birth 15 18 20 22 25 15-19 1.3 na na na na 79.9 5,005 a 20-24 4.8 34.7 66.7 na na 15.4 4,555 18.9 25-29 5.1 35.2 66.3 84.8 94.0 3.8 4,400 18.9 30-34 5.4 34.4 65.1 83.8 94.4 1.9 3,250 19.0 35-39 6.9 34.2 60.6 79.0 92.6 2.1 2,522 19.2 40-44 10.8 40.9 65.4 82.2 91.5 1.3 1,730 18.7 45-49 7.1 38.3 63.8 80.6 90.0 1.6 1,558 18.9 20-49 6.1 35.6 65.1 na na 5.7 18,015 18.9 25-49 6.5 35.9 64.5 82.6 93.0 2.4 13,461 18.9 na = Not applicable due to censoring a = Omitted because less than 50 percent of women had a birth before reaching the beginning of the age group 4.7 MEDIAN AGE AT FIRST BIRTH Age at first birth varies by the demographic and socioeconomic characteristics of the woman. Table 4.7 shows the median age at first birth across age cohorts for key sub-groups of women. The measures are presented for women age 25-49 to ensure that half of the women have already had a birth by the start of the age group. Urban women age 25-49 have a higher median age at first birth (19.4 years) than their rural counterparts (18.8 years). A comparison across regions shows that the median age at first birth for women age 25-49 ranges from 19.2 years in the Central Region to 18.7 years in the Southern Region. The median age at first birth increases with level of education. Women with no education have their first birth at a median age of 18.4 years, while women who have attended more than secondary education have a median age at first birth of 24.4 years, a difference of six years. On the other hand, there is no correlation between age at first birth and wealth quintile. 50 | Fertility Table 4.7 Median age at first birth Median age at first birth among women age 20-49 (25-49) years, according to background characteristics, Malawi 2010 Background characteristic Age Women age 20-49 Women age 25-49 20-24 25-29 30-34 35-39 40-44 45-49 Residence Urban 19.8 19.7 19.6 19.5 18.7 18.4 19.5 19.4 Rural 18.8 18.7 18.9 19.1 18.7 19.0 18.8 18.8 Region Northern 19.1 18.7 19.3 19.0 19.2 18.7 19.0 18.9 Central 19.2 19.4 19.2 19.3 18.8 19.2 19.2 19.2 Southern 18.5 18.6 18.7 19.0 18.4 18.6 18.6 18.7 Education No education 18.3 17.8 18.2 18.8 18.1 19.2 18.4 18.4 Primary 18.4 18.5 18.8 19.0 18.7 18.7 18.6 18.7 Secondary a 20.5 21.2 21.2 20.4 20.1 a 20.8 More than secondary a a 26.4 23.7 23.2 22.5 a 24.4 Wealth quintile Lowest 18.5 18.6 18.7 19.5 18.9 19.4 18.8 18.9 Second 18.5 18.6 18.9 18.8 18.6 18.7 18.7 18.7 Middle 18.7 18.7 18.7 19.2 18.1 18.6 18.7 18.7 Fourth 18.8 18.6 19.0 18.7 18.4 18.7 18.7 18.7 Highest a 19.8 19.9 19.8 19.3 19.1 19.9 19.7 Total 18.9 18.9 19.0 19.2 18.7 18.9 18.9 18.9 a = Omitted because less than 50 percent of the women had a birth before reaching the beginning of the age group 4.8 TEENAGE PREGNANCY AND MOTHERHOOD Teenage pregnancy is a major health concern because of its association with higher morbidity and mortality for both the mother and child. In addition, childbearing during the teenage years frequently has adverse social consequences, particularly regarding educational attainment, because women who become mothers in their teens are more likely to curtail their education. Table 4.8 shows the percentage of women age 15-19 who have either had a live birth or who are pregnant with their first child. Overall, one in every four teenagers (26 percent) age 15-19 has begun childbearing; 20 percent have had a live birth and 6 percent are pregnant with their first child. A higher proportion of teenagers in rural areas (27 percent) has begun childbearing compared with teenagers in urban areas (21 percent). At the regional level, the proportion of teenagers who have started childbearing is highest in the Southern Region (29 percent) and the Northern Region (28 percent) compared with the Central Region (22 percent). The percentage of teenagers who have started childbearing decreases with increasing level of education. Forty-five percent of teenagers with no education have already begun childbearing as compared with only 4 percent of those with more than secondary education. Teenagers in the lowest wealth quintile are more than twice as likely to have started childbearing as those in the highest wealth quintile (31 and 16 percent, respectively). Fertility | 51 Table 4.8 Teenage pregnancy and motherhood Percentage of women age 15-19 who have had a live birth or who are pregnant with their first child, and percentage who have begun childbearing, by background characteristics, Malawi 2010 Background characteristic Percentage who: Percentage who have begun childbearing Number of women Have had a live birth Are pregnant with first child Age 15 1.6 2.0 3.5 1,234 16 7.5 5.1 12.6 1,152 17 15.0 6.7 21.7 927 18 34.4 9.0 43.4 907 19 57.2 6.3 63.5 784 Residence Urban 16.0 4.5 20.5 947 Rural 21.0 5.8 26.8 4,058 Region Northern 20.7 7.5 28.1 618 Central 16.6 5.1 21.7 2,179 Southern 23.3 5.4 28.7 2,208 Education No education 32.9 11.6 44.6 146 Primary 22.0 6.1 28.1 3,669 Secondary 13.0 2.9 15.9 1,156 More than secondary 0.0 4.0 4.0 34 Wealth quintile Lowest 24.7 6.4 31.1 891 Second 24.9 6.2 31.1 890 Middle 23.2 7.0 30.2 985 Fourth 18.1 5.7 23.8 985 Highest 12.5 3.2 15.6 1,254 Total 20.1 5.5 25.6 5,005 Family Planning | 53 FAMILY PLANNING 5 Family planning refers to a conscious effort by a couple to limit or space the number of children they want to have through the use of contraceptive methods. This chapter presents results from the 2010 MDHS on a number of aspects of contraception: knowledge of specific contraceptive methods, attitudes and behaviour towards contraceptive use, ever use and current use, sources of contraceptive methods, and costs of methods. The focus of this chapter is on sexually active women, as these women have the greatest risk of exposure to pregnancy and the greatest need to regulate their fertility. The results of interviews with men are presented alongside those with women, as men play an equally important role in the realisation of reproductive health and family planning decisions and behaviour. Comparisons are also made, where feasible, with findings from previous surveys to evaluate changes in contraceptive measures over time in Malawi.1 5.1 KNOWLEDGE OF CONTRACEPTIVE METHODS Information on knowledge and use of family planning methods was obtained from female and male respondents by asking them to mention ways or methods by which a couple can delay or avoid pregnancy. If the respondent failed to mention a particular method spontaneously, the interviewer described the method and asked whether the respondent had heard of it. For each method known, respondents were asked if they had ever used the method. Respondents who reported they used the method were asked whether they or their partners were using a method at the time of the survey. Contraceptive methods are classified as modern or traditional methods. Modern methods include female sterilisation, male sterilisation, the pill, the intrauterine device (IUD), injectables, implants, the male condom, the female condom, and emergency contraception. Methods such as rhythm (periodic abstinence) and withdrawal are grouped as traditional methods. Provision was also made in the questionnaire to record any other methods mentioned by the respondent, including folk methods. Table 5.1 shows that knowledge of any contraceptive method is universal in Malawi, with 98 percent of all women and 99 percent of all men knowing at least one method of contraception. Modern methods are more widely known than traditional methods; 98 percent of all women know of a modern method while 74 percent know of a traditional method. Among modern methods for women, injectables and male condoms are the most commonly known methods (95 percent each), and emergency contraception is the least known modern method (35 percent). Knowledge of a modern method of family planning among currently married women (100 percent) and sexually active unmarried women (99 percent) is universal. Among traditional methods, withdrawal and the rhythm method are the most commonly known among all women (60 and 53 percent, respectively). Overall, women know a mean number of 8.5 contraceptive methods while men know 7.8 methods. 1 The survey results in this chapter are presented for the country as a whole, by urban-rural residence, and by region. District-level results are available in Appendix A. 54 | Family Planning Table 5.1 Knowledge of contraceptive methods Percentage of all respondents, currently married respondents and sexually active unmarried respondents age 15-49 who know any contraceptive method, by specific method, Malawi 2010 Method Women Men All women Currently married women Sexually active unmarried woman1 All men Currently married men Sexually active unmarried men1 Any method 97.9 99.7 99.2 98.6 99.7 98.9 Any modern method 97.9 99.7 99.2 98.5 99.7 98.5 Female sterilisation 88.6 93.0 88.4 83.9 91.9 83.3 Male sterilisation 67.7 73.3 67.0 69.9 78.9 62.3 Pill 91.1 96.6 89.2 82.9 92.3 79.4 IUD 73.8 81.7 71.9 62.1 73.9 48.4 Injectables 95.3 99.0 95.2 90.0 97.5 88.5 Implants 77.6 85.9 75.4 53.5 66.9 38.8 Male condom 94.7 96.8 97.5 97.6 98.9 98.4 Female condom 86.0 89.6 89.0 84.8 89.4 85.0 Emergency contraception 35.1 38.8 35.8 34.2 40.6 38.7 Any traditional method 74.4 82.3 75.5 70.3 81.4 73.8 Rhythm 53.4 57.7 58.2 53.0 61.7 53.9 Withdrawal 59.6 67.8 63.6 57.4 68.1 62.1 Folk method 22.5 26.6 19.0 9.9 14.4 7.7 Mean number of methods known by respondents 15-49 8.5 9.1 8.5 7.8 8.7 7.5 Number of respondents 23,020 15,528 523 6,818 3,895 469 Mean number of methods known by respondents 15-54 na na na 7.8 8.7 7.5 Number of respondents na na na 7,175 4,218 474 na = Not applicable 1 Had last sexual intercourse within 30 days preceding the survey Table 5.2 shows knowledge of contraceptive methods among women and men by background characteristics. There is no variation in contraceptive knowledge by background characteristics between women and men. In general, all currently married women and men have heard of at least one contraceptive method and at least one modern contraceptive method. Family Planning | 55 Table 5.2 Knowledge of contraceptive methods by background characteristics Percentage of currently married women and currently married men age 15-49 who have heard of at least one contraceptive method and who have heard of at least one modern method by background characteristics, Malawi 2010 Background characteristic Women Men Heard of any method Heard of any modern method1 Number Heard of any method Heard of any modern method1 Number Age 15-19 98.0 98.0 1,171 (100.0) (100.0) 40 20-24 99.9 99.9 3,469 99.2 99.2 466 25-29 99.9 99.9 3,718 99.8 99.8 868 30-34 99.9 99.8 2,636 99.8 99.7 862 35-39 99.7 99.7 2,040 100.0 100.0 737 40-44 99.6 99.6 1,339 99.8 99.8 495 45-49 99.6 99.6 1,155 99.5 99.5 428 Residence Urban 100.0 100.0 2,686 99.3 99.3 686 Rural 99.6 99.6 12,841 99.8 99.8 3,209 Region Northern 99.6 99.6 1,871 100.0 100.0 428 Central 99.7 99.7 6,678 99.9 99.9 1,792 Southern 99.7 99.7 6,979 99.4 99.4 1,676 Education No education 99.5 99.4 2,826 98.5 98.5 333 Primary 99.7 99.7 10,231 99.8 99.8 2,460 Secondary 100.0 100.0 2,275 100.0 100.0 980 More than secondary 100.0 100.0 195 99.0 99.0 122 Wealth quintile Lowest 99.2 99.2 2,639 99.5 99.5 603 Second 99.9 99.8 3,120 99.9 99.9 826 Middle 99.5 99.5 3,303 99.9 99.9 850 Fourth 99.8 99.8 3,197 99.8 99.8 783 Highest 99.9 99.9 3,268 99.4 99.4 833 Total 15-49 99.7 99.7 15,528 99.7 99.7 3,895 50-54 na na na 99.8 99.5 323 Total men 15-54 na na na 99.7 99.7 4,218 Note: Figures in parentheses are based on 25-49 unweighted cases. na = Not applicable 1 Female sterilisation, male sterilisation, pill, IUD, injectables, implants, male condom, female condom, and emergency contraception 5.2 EVER USE OF CONTRACEPTION Ever use of contraception provides a measure of the cumulative experience of a population with family planning. Ever use of family planning methods in the 2010 MDHS thus refers to use of a method at any time, with no distinction between past and current use. The 2010 MDHS collected data on the level of ever use of family planning methods from respondents. All women interviewed in the 2010 MDHS who said that they had heard of a method of family planning were asked whether they had ever used that method. Men were only asked about ever use of male sterilisation, the male condom, the female condom, the rhythm method, and withdrawal. Table 5.3.1 shows the percentage of all women, currently married women, and sexually active unmarried women who have ever used specific methods of family planning, by age. Table 5.3.2 presents comparable information for men. Overall, 65 percent of all women reported ever using a method of contraception at some time; 62 percent used a modern method and 18 percent used any traditional method. Among currently married women, 79 percent have used any method in the past and 75 percent have ever used a modern method. The most widely used modern methods among currently married women are: injectables (61 percent), male condoms (20 percent), the pill (15 percent), and female sterilisation (10 percent). 56 | Family Planning Seventy-two percent of sexually active unmarried women have ever used a family planning method at some time. Half (50 percent) have used a male condom; 43 percent have used injectables; 14 percent have used pills; 4 percent have used female s

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