Malawi - Demographic and Health Survey - 2005

Publication date: 2005

Malawi Demographic and Health Survey M alaw i 2004 D em ographic and H ealth S urvey 2004 Malawi Demographic and Health Survey 2004 National Statistical Office Zomba, Malawi ORC Macro Calverton, Maryland, USA December 2005 This report summarises the findings of the 2004 Malawi Demographic and Health Survey (MDHS), which was carried out by the Malawi National Statistical Office (NSO). Most of the funds for the local costs of the survey were provided by multiple donors through the National AIDS Commission. The Department for International Development (DfID) of the British Government, UNICEF, and UNFPA also provided funds for the survey. The United States Agency for International Development (USAID) provided technical assistance through ORC Macro. Technical assistance for the HIV testing was provided by the Centers for Disease Control and Prevention. The MDHS is part of the worldwide Demographic and Health Surveys (DHS) programme funded by the United States Agency for International Development (USAID). The programme is designed to collect data on fertility, family planning, maternal and child health, nutrition, and HIV/AIDS. The opinions expressed herein are those of the authors and do not necessarily reflect the views of USAID. Additional information about the survey may be obtained from the Demography and Social Statistics Division (DSS), National Statistical Office, Chimbiya Road, P.O. Box 333, Zomba, Malawi (Telephone: 265-1-524-377, 265-1-524-111 (switchboard); Fax: 265-1-525-130, E-mail: demography@statistics.gov.mw; Internet: www.nso.malawi.net). Additional information about the DHS programme may be obtained from MEASURE DHS, ORC Macro, 11785 Beltsville Drive, Suite 300, Calverton, MD 20705, U.S.A. (Telephone: 301.572.0200; Fax: 301.572.0999; E-mail: reports@orcmacro.com; Internet: www.measuredhs.com) Recommended citation: National Statistical Office (NSO) [Malawi], and ORC Macro. 2005. Malawi Demographic and Health Survey 2004. Calverton, Maryland: NSO and ORC Macro. Contents | iii CONTENTS Page TABLES AND FIGURES .ix FOREWORD . xvii SUMMARY OF FINDINGS . xix MAP OF MALAWI . xxviii CHAPTER 1 INTRODUCTION .1 1.1 Geography, History, and the Economy. 1 1.2 Population. 2 1.3 Objective of the Survey . 3 1.4 Organisation of the Survey. 4 CHAPTER 2 CHARACTERISTICS OF HOUSEHOLDS AND HOUSEHOLD MEMBERS .9 2.1 Household Population by Age, Sex, and Residence . 9 2.2 Household Composition . 11 2.3 Fosterhood and Orphanhood . 11 2.4 Educational Level of Household Population . 13 2.5 School Attendance. 16 2.6 Child Labour . 20 2.7 Housing Characteristics. 21 CHAPTER 3 CHARACTERISTICS OF RESPONDENTS AND WOMEN’S STATUS.25 3.1 Characteristics of Survey Respondents . 25 3.2 Educational Attainment. 27 3.3 Literacy. 29 3.4 Access to Mass Media . 31 3.5 Employment Status . 34 3.6 Women’s Occupation . 37 3.7 Type of Employment . 40 3.8 Measures of Women’s Empowerment. 41 CHAPTER 4 FERTILITY .55 4.1 Current Fertility Levels and Trends. 55 4.2 Children Ever Born and Children Surviving . 62 4.3 Birth Intervals . 63 4.4 Age of Mothers at First Birth. 65 4.5 Median Age at First Birth by Background Characteristics . 65 4.6 Adolescent Fertility . 66 iv | Contents CHAPTER 5 FERTILITY REGULATION.69 5.1 Knowledge of Contraceptive Methods . 69 5.2 Ever Use of Contraception . 73 5.3 Current Use of Contraceptive Methods. 74 5.4 Current Use of Contraception By Background Characteristics . 75 5.5 Trends in Contraceptive Use. 77 5.6 Current Use of Contraception By Woman's Status. 78 5.7 Number of Children At First Use of Contraception. 79 5.8 Knowledge of Fertile Period. 79 5.9 Timing of Sterilisation . 80 5.10 Source of Contraception. 81 5.11 Informed Choice . 82 5.12 Contraceptive Discontinuation. 83 5.13 Future Use of Contraception. 85 5.14 Reasons for Not Intending to Use Contraception . 86 5.15 Preferred Method of Contraception for Future Use . 87 5.16 Exposure to Family Planning Messages Through the Media . 87 5.17 Contact of Nonusers with Family Planning Providers. 89 5.18 Discussion of Family Planning with Husband . 91 5.19 Men's Attitude Toward Contraception. 92 CHAPTER 6 OTHER PROXIMATE DETERMINANTS OF FERTILITY .93 6.1 Marital Status. 93 6.2 Polygyny. 94 6.3 Age at First Marriage . 96 6.4 Age at First Sexual Intercourse . 99 6.5 Recent Sexual Activity. 101 6.6 Postpartum Amenorrhoea, Abstinence, and Insusceptibility . 105 6.7 Termination of Exposure to Pregnancy. 107 CHAPTER 7 FERTILITY PREFERENCES AND UNMET NEED FOR FAMILY PLANNING . 109 7.1 Desire For More Children . 109 7.2 Desire To Limit Childbearing by Background Characteristics . 110 7.3 Unmet Need For Family Planning . 112 7.4 Ideal Family Size. 115 7.5 Wanted and Unwanted Fertility. 119 CHAPTER 8 INFANT AND CHILD MORTALITY . 123 8.1 Definitions. 123 8.2 Methodological Considerations. 124 8.3 Assessment of Data Quality. 124 8.4 Levels and Trends of Early Childhood Mortality . 126 8.5 Socioeconomic Differentials in Childhood Mortality . 127 8.6 Biodemographic Differentials in Childhood Mortality. 128 Contents | v 8.7 Childhood Mortality by Women’s Status . 130 8.8 Perinatal Mortality . 131 8.9 High-Risk Fertility Behaviour. 132 CHAPTER 9 MATERNAL AND CHILD HEALTH . 133 9.1 Antenatal Care. 133 9.2 Assistance and Medical Care at Delivery . 140 9.3 Postnatal Care . 145 9.4 Women’s Participation in Decisionmaking. 148 9.5 Childhood Vaccinations. 149 9.6 Acute Respiratory Infection. 153 9.7 Diarrhoeal Disease . 155 9.8 Women’s Perceptions of Problems in Accessing Health Care . 158 CHAPTER 10 INFANT FEEDING AND CHILDREN’S AND WOMEN’S NUTRITIONAL STATUS. 163 10.1 Breastfeeding. 163 10.2 Complementary Feeding. 169 10.3 Micronutrients . 171 10.4 Prevalence of Anaemia in Children. 175 10.5 Nutritional Status . 178 10.6 Nutritional Status of Women . 181 CHAPTER 11 HIV/AIDS AND OTHER SEXUALLY TRANSMITTED INFECTIONS. 185 11.1 Introduction . 185 11.2 Knowledge of AIDS and HIV Transmission. 186 11.3 Accepting Attitudes Towards Those with HIV/AIDS. 193 11.4 Attitudes Towards Condom Education for Youth. 196 11.5 Attitudes Towards Negotiating Safer Sex . 197 11.6 Multiple Sexual Partnerships . 198 11.7 Higher-Risk Sex . 200 11.8 Paid Sex and Condom Use . 201 11.9 Counselling and Testing for HIV. 202 11.10 Self-Reporting of Sexually Transmitted Infections and Symptoms . 207 11.11 Prevalence of Injections . 209 11.12 HIV/AIDS-Related Knowledge and Behaviour among Youth. 210 11.13 Age at First Sex among Youth. 212 11.14 Condom Use at First Sex among Youth . 214 11.15 Premarital Sex . 216 11.16 Higher-Risk Sex and Condom Use among Youth. 217 11.17 HIV Testing among Youth . 221 11.18 Orphanhood and School Attendance. 222 11.19 Male Circumcision. 223 vi | Contents CHAPTER 12 HIV PREVALENCE AND ASSOCIATED FACTORS . 225 12.1 Coverage of HIV Testing . 226 12.2 HIV Prevalence. 230 12.3 Measuring the HIV Burden in Malawi . 241 CHAPTER 13 ADULT AND MATERNAL MORTALITY. 243 13.1 Data . 243 13.2 Direct Estimates of Adult Mortality. 245 13.3 Maternal Mortality . 247 CHAPTER 14 MALARIA . 249 14.1 Mosquito Nets . 250 14.2 Intermittent Preventive Treatment During Pregnancy. 257 14.3 Prevalence and Management of Malaria in Children . 259 CHAPTER 15 DOMESTIC VIOLENCE . 265 15.1 Introduction . 265 15.2 Physical Violence Since Age 15. 266 15.3 Perpetrators of Physical Violence . 267 15.4 Violence During Pregnancy. 268 15.5 Marital Control by Husband. 269 15.6 Forms of Marital Violence. 272 15.7 Frequency of Spousal Violence . 274 15.8 Onset of Spousal Violence . 275 15.9 Physical Consequences of Spousal Violence. 276 15.10 Violence by Spousal Characteristics and Women’s Indicators. 277 15.11 Help Seeking for Women Who Experience Violence . 279 CHAPTER 16 MEN’S PARTICIPATION IN HEALTH CARE. 281 16.1 Advice or Care Received by Mother During Pregnancy, Delivery, and After Delivery . 281 16.2 Main Provider During Pregnancy, Delivery, and After Delivery . 283 16.3 Reasons for Not Getting Care During Pregnancy, Delivery, and After Delivery 283 16.4 Decisionmaking on Child’s Health Care. 284 16.5 Men’s Knowledge of Pregnancy Complications . 286 REFERENCES . 289 APPENDIX A SAMPLE IMPLEMENTATION . 293 APPENDIX B ESTIMATES OF SAMPLING ERRORS . 299 APPENDIX C DATA QUALITY . 321 Contents | vii APPENDIX D PERSONS INVOLVED IN THE 2004 MALAWI DEMOGRAPHIC AND HEALTH SURVEY . 327 APPENDIX E QUESTIONNAIRES . 331 APPENDIX F MILLENNIUM DEVELOPMENT GOAL INDICATORS . 449 APPENDIX G ANALYSIS OF RESPONSE BIAS AND ADJUSTMENT OF HIV PREVALENCE . 451 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 CHARACTERISTICS OF HOUSEHOLDS AND HOUSEHOLD MEMBERS Table 2.1 Household population by age, sex, and residence .10 Table 2.2 Household composition.11 Table 2.3 Children's living arrangements and orphanhood.12 Table 2.4.1 Educational attainment of household population: women .14 Table 2.4.2 Educational attainment of household population: men .15 Table 2.5.1 School attendance ratios: primary school.17 Table 2.5.2 School attendance ratios: secondary school .18 Table 2.6 Grade repetition and dropout rates.19 Table 2.7 Child labour .21 Table 2.8 Household characteristics .22 Table 2.9 Household durable goods.24 Figure 2.1 Population pyramid .10 CHAPTER 3 CHARACTERISTICS OF RESPONDENTS AND WOMEN’S STATUS Table 3.1 Background characteristics of respondents .26 Table 3.2.1 Educational attainment by background characteristics: women.28 Table 3.2.2 Educational attainment by background characteristics: men.29 Table 3.3.1 Literacy: women.30 Table 3.3.2 Literacy: men .31 Table 3.4.1 Exposure to mass media: women.32 Table 3.4.2 Exposure to mass media: men .33 Table 3.5.1 Employment status: women.35 Table 3.5.2 Employment status: men .36 Table 3.6.1 Occupation: women.38 Table 3.6.2 Occupation: men .39 Table 3.7.1 Type of employment: women.40 Table 3.7.2 Type of employment: men .41 Table 3.8 Decision on use of earnings and contribution of earnings to household expenditures.43 Table 3.9 Women's control over earnings .44 Table 3.10 Women's participation in decisionmaking .45 x | Tables and Figures Table 3.11.1 Women's participation in decisionmaking by background characteristics: women .46 Table 3.11.2 Men’s attitudes towards women’s control of decisionmaking by background characteristics .47 Table 3.12.1 Women's attitude towards wife beating.49 Table 3.12.2 Men's attitude towards wife beating .50 Table 3.13.1 Women's attitude towards refusing sex with husband.52 Table 3.13.1 Men's attitude towards refusing sex with husband .53 Figure 3.1 Employment status of women age 15-49 .37 Figure 3.2 Type of earnings of women age 15-49 .41 CHAPTER 4 FERTILITY Table 4.1 Current fertility .56 Table 4.2 Fertility by background characteristics.58 Table 4.3 Trends in age-specific fertility rates .59 Table 4.4 Trends in fertility by background characteristics .61 Table 4.5 Trends in age-specific fertility rates .61 Table 4.6 Children ever born and living.62 Table 4.7 Birth intervals.64 Table 4.8 Age at first birth .65 Table 4.9 Median age at first birth by background characteristics.66 Table 4.10 Adolescent pregnancy and motherhood.67 Figure 4.1 Total fertility rates for selected sub-Saharan countries .57 Figure 4.2 Total fertility rate by background characteristics .59 Figure 4.3 Trends in the total fertility rate .60 Figure 4.4 Trends in age-specific fertility rates .60 CHAPTER 5 FERTILITY REGULATION Table 5.1.1 Knowledge of contraceptive method: women.70 Table 5.1.2 Knowledge of contraceptive method: men .71 Table 5.2 Knowledge of contraceptive methods by background characteristics.72 Table 5.3.1 Ever use of contraception: women.73 Table 5.3.2 Ever use of contraception: men .74 Table 5.4 Current use of contraception .75 Table 5.5 Current use of contraception by background characteristics .76 Table 5.6 Trends in contraceptive use .77 Table 5.7 Current use of contraception by women's status.78 Table 5.8 Number of children at first use of contraception .79 Table 5.9 Knowledge of fertile period.80 Table 5.10 Timing of sterilisation.80 Table 5.11 Source of contraception.81 Table 5.12 Informed choice .83 Table 5.13 First-year contraceptive discontinuation rates.84 Tables and Figures | xi Table 5.14 Reasons for discontinuation .85 Table 5.15 Future use of contraception .85 Table 5.16 Reason for not intending to use contraception .86 Table 5.17 Preferred method of contraception for future use .87 Table 5.18.1 Exposure to family planning messages: women .88 Table 5.18.2 Exposure to family planning messages: men.89 Table 5.19 Contact of nonusers with family planning providers .90 Table 5.20 Discussion of family planning with husband.91 Table 5.21 Men's attitudes towards contraception .92 CHAPTER 6 OTHER PROXIMATE DETERMINANTS OF FERTILITY Table 6.1 Current marital status.93 Table 6.2 Number of cowives and wives .95 Table 6.3 Age at first marriage .97 Table 6.4 Median age at first marriage.98 Table 6.5 Age at first sexual intercourse.99 Table 6.6.1 Median age at first intercourse: women . 100 Table 6.6.2 Median age at first intercourse: men. 101 Table 6.7.1 Recent sexual activity: women. 103 Table 6.7.2 Recent sexual activity: men . 104 Table 6.8 Postpartum amenorrhoea, abstinence, and insusceptibility . 105 Table 6.9 Median duration of postpartum insusceptibility by background characteristics . 106 Table 6.10 Menopause . 107 Figure 6.1 Percentage of currently married men in a polygynous marriage, by background characteristics .96 CHAPTER 7 FERTILITY PREFERENCES AND UNMET NEED FOR FAMILY PLANNING Table 7.1.1 Fertility preferences by number of living children: women . 110 Table 7.1.2 Fertility preferences by number of living children: men. 110 Table 7.2 Desire to limit childbearing. 111 Table 7.3 Need for family planning . 113 Table 7.4 Ideal number of children . 116 Table 7.5.1 Mean ideal number of children by background characteristics: women . 118 Table 7.5.2 Mean ideal number of children by background characteristics: men . 119 Table 7.6 Fertility planning status . 120 Table 7.7 Wanted fertility rates . 121 Figure 7.1 Percentage of currently married women who have two children who want to end childbearing . 112 Figure 7.2 Trend in unmet need for family planning, total demand, and percentage of demand satisfied. 114 xii | Tables and Figures CHAPTER 8 INFANT AND CHILD MORTALITY Table 8.1 Early childhood mortality rates. 126 Table 8.2 Early childhood mortality rates by background characteristics . 128 Table 8.3 Early childhood mortality rates by demographic characteristics . 129 Table 8.4 Early childhood mortality rates by women's status . 130 Table 8.5 Perinatal mortality . 131 Table 8.6 High-risk fertility behaviour. 132 CHAPTER 9 MATERNAL AND CHILD HEALTH Table 9.1 Antenatal care . 134 Table 9.2 Number of antenatal care visits and timing of first visit . 135 Table 9.3 Components of antenatal care . 136 Table 9.4 Tetanus toxoid injections . 137 Table 9.5 Complications during pregnancy. 138 Table 9.6 Treatment for complications during pregnancy . 140 Table 9.7 Place of delivery . 141 Table 9.8 Assistance during delivery . 142 Table 9.9 Delivery characteristics . 144 Table 9.10 Postnatal care . 146 Table 9.11 Complications after delivery. 147 Table 9.12 Reproductive health care by women's status . 148 Table 9.13 Vaccinations by source of information . 150 Table 9.14 Trends in vaccination coverage . 151 Table 9.15 Vaccinations by background characteristics. 152 Table 9.16 Prevalence and treatment of symptoms of ARI and fever. 154 Table 9.17 Prevalence of diarrhoea . 155 Table 9.18 Knowledge of ORS packets . 156 Table 9.19 Diarrhoea treatment . 157 Table 9.20 Feeding practices during diarrhoea . 158 Table 9.21 Problems in accessing health care . 159 Figure 9.1 Complications during pregnancy. 139 Figure 9.2 Assistance at delivery from a health professional, by residence and district . 143 Figure 9.3 Percentage of children age 12-23 months who were vaccinated by 12 months of age. 150 Figure 9.4 Percentage of women who reported they have big problems in accessing health care, by type of problem. 160 Figure 9.5 Percentage of women who reported the cost of transport as a big problem in accessing health care. 161 Tables and Figures | xiii CHAPTER 10 INFANT FEEDING AND CHILDREN’S AND WOMEN’S NUTRITIONAL STATUS Table 10.1 Initial breastfeeding . 164 Table 10.2 Breastfeeding status by age . 166 Table 10.3 Median duration and frequency of breastfeeding. 168 Table 10.4 Foods consumed by children in the day or night preceding the interview . 170 Table 10.5 Frequency of foods consumed by children in the day or night preceding the interview . 171 Table 10.6 Micronutrient intake among children . 172 Table 10.7 Micronutrient intake among mothers . 174 Table 10.8 Prevalence of anaemia in children . 175 Table 10.9 Prevalence of anaemia in women . 177 Table 10.10 Prevalence of anaemia in children by anaemia status of mother. 178 Table 10.11 Nutritional status of children. 180 Table 10.12 Nutritional status of women . 183 Figure 10.1 Distribution of children by breastfeeding status, according to age. 167 Figure 10.2 Percentage of children with low height-for-age, weight-for-height, and weight-for-age, by age of child . 182 Figure 10.3 Prevalence of chronic energy deficiency (percent with BMI <18.5) among women age 15-49, for selected districts. 184 CHAPTER 11 HIV/AIDS AND OTHER SEXUALLY TRANSMITTED INFECTIONS Table 11.1 Knowledge of AIDS. 186 Table 11.2 Knowledge of HIV prevention methods . 187 Table 11.3.1 Beliefs about AIDS: women . 189 Table 11.3.2 Beliefs about AIDS: men. 190 Table 11.4 Knowledge of prevention of mother-to-child transmission of HIV. 192 Table 11.5.1 Accepting attitudes towards people living with HIV: women. 194 Table 11.5.2 Accepting attitudes towards people living with HIV: men. 195 Table 11.6 Adult support of education about condom use to prevent AIDS. 196 Table 11.7 Attitudes toward negotiating safer sex with husband . 197 Table 11.8 Multiple sex partners among women and men. 199 Table 11.9 Higher-risk sex and condom use at last higher-risk sex in the past year. 200 Table 11.10 Paid sex in past year and condom use at last paid sex . 201 Table 11.11 HIV testing status and receipt of test results. 203 Table 11.12 Pregnant women counselled and tested for HIV. 205 Table 11.13 Knowledge of source for test. 206 Table 11.14 Self-reporting of sexually transmitted infection and STI symptoms. 208 Table 11.15 Injections by background characteristics . 210 Table 11.16 Comprehensive knowledge about AIDS and of a source of condoms among youth . 211 Table 11.17 Age at first sex among young women and men . 213 Table 11.18 Condom use at first sex among young women and men . 215 Table 11.19 Premarital sex and condom use during premarital sex. 216 xiv | Tables and Figures Table 11.20 Higher-risk sex and condom use at last higher-risk sex in the past year among young women and men . 218 Table 11.21 Age-mixing in sexual relationships. 220 Table 11.22 Recent HIV tests among youth . 221 Table 11.23 Schooling of children 10-14 by orphanhood and living arrangements . 222 Table 11. 24 Male circumcision . 223 Figure 11.1 Percentage of women and men reporting an STI or symptoms of an STI in the past 12 months who sought care, by source of advice or treatment. 209 Figure 11.2 Percentage of respondents age 15-19 who had sex before age 15 and percentage of respondents age 18-19 who had sex before age 18. 214 Figure 11.3 Scale of risk for young women: abstinence, being faithful, and condom use. 219 Figure 11.4 Scale of risk for young men: abstinence, being faithful, and condom use . 219 CHAPTER 12 HIV PREVALENCE AND ASSOCIATED FACTORS Table 12.1 Coverage of HIV testing by residence and region . 227 Table 12.2.1 Coverage of HIV testing by background characteristics: women. 228 Table 12.2.2 Coverage of HIV testing by background characteristics: men. 229 Table 12.3 HIV prevalence by age. 230 Table 12.4 HIV prevalence by socioeconomic characteristics . 232 Table 12.5 Observed and adjusted HIV prevalence. 233 Table 12.6 HIV prevalence by sociodemographic characteristics . 234 Table 12.7 HIV prevalence by sexual behaviour characteristics . 236 Table 12.8 HIV prevalence by other characteristics . 237 Table 12.9 HIV prevalence among young people . 239 Table 12.10 HIV prevalence among couples . 240 Figure 12.1 Percentage HIV positive among women and men age 15-49 . 231 Figure 12.2 HIV Prevalence by prior testing status . 238 CHAPTER 13 ADULT AND MATERNAL MORTALITY Table 13.1 Data on siblings: completeness of reported data . 244 Table 13.2 Adult mortality rates . 245 Table 13.3 Direct estimates of maternal mortality. 247 Figure 13.1 Trends in age-specific mortality among women age 15-49 . 246 Figure 13.2 Trends in age-specific mortality among men age 15-49. 246 CHAPTER 14 MALARIA Table 14.1 Ownership of mosquito nets. 251 Table 14.2 Colour and shape of mosquito nets. 252 Table 14.3 Use of mosquito nets by children. 254 Table 14.4 Use of mosquito nets by pregnant women . 256 Tables and Figures | xv Table 14.5 Prophylactic use of antimalarial drugs and of Intermittent Preventive Treatment by women during pregnancy. 258 Table 14.6 Initial response to fever. 260 Table 14.7 Prevalence and prompt treatment of fever . 261 Table 14.8 Type and timing of antimalarial drugs taken by children with fever . 263 Figure 14.1 Preferred colour of mosquito nets, by residence . 253 Figure 14.2 Preferred shape of mosquito nets, by residence . 253 Figure 14.3 Percentage of children under age five who slept under a mosquito net the night before the survey . 255 Figure 14.4 Percentage of women age 15-49 who slept under a mosquito net on the night before the survey . 257 Figure 14.5 Percentage of pregnant women who took at least 2 doses of SP for IPT of malaria during pregnancy in the 5 years preceding the survey. 259 CHAPTER 15 DOMESTIC VIOLENCE Table 15.1 Experience of physical violence since age 15 . 267 Table 15.2 Perpetrators of physical violence. 268 Table 15.3 Violence during pregnancy . 269 Table 15.4 Degree of marital control by husband . 270 Table 15.5 Marital violence. 272 Table 15.6 Frequency of spousal violence . 275 Table 15.7 Onset of spousal violence . 276 Table 15.8 Physical consequences of spousal violence . 277 Table 15.9 Spousal violence by spousal characteristics . 278 Table 15.10: Spousal violence by women's status . 279 Table 15.11 Help seeking for women who experience violence . 280 Figure 15.1 Percentage of ever-married women who have experienced violence by their current or last husband . 273 Figure 15.2 Percentage of women who ever experienced sexual, physical, and/or emotional violence . 274 CHAPTER 16 MEN’S PARTICIPATION IN HEALTH CARE Table 16.1 Care received by mother during pregnancy, delivery, and after delivery . 282 Table 16.2 Main provider for payment for maternal care. 283 Table 16.3 Reason for not getting care during pregnancy, delivery, and after delivery. 284 Table 16.4 Decisionmaker in child's health care . 285 Table 16.5 Knowledge of pregnancy complications . 287 APPENDIX A SAMPLE IMPLEMENTATION Table A.1 Sample implementation: women . 295 Table A.2 Sample implementation: men. 296 xvi | Tables and Figures APPENDIX B ESTIMATES OF SAMPLING ERRORS Table B.1 List of selected variables for sampling errors, Malawi 2004. 302 Table B.2 Sampling errors: Total sample . 303 Table B.3 Sampling errors: Urban sample. 304 Table B.4 Sampling errors: Rural sample. 305 Table B.5 Sampling errors: Northern Region. 306 Table B.6 Sampling errors: Central Region. 307 Table B.7 Sampling errors: Southern Region. 308 Table B.8 Sampling errors: Blantyre District . 309 Table B.9 Sampling errors: Kasungu District. 310 Table B.10 Sampling errors: Machinga District. 311 Table B.11 Sampling errors: Mangochi District . 312 Table B.12 Sampling errors: Mzimba District . 313 Table B.13 Sampling errors: Salima District . 314 Table B.14 Sampling errors: Thyolo District . 315 Table B.15 Sampling errors: Zomba District. 316 Table B.16 Sampling errors: Lilongwe District. 317 Table B.17 Sampling errors: Mulanje District . 318 Table B.18 Sampling errors: Other Districts . 319 APPENDIX C DATA QUALITY Table C.1 Household age distribution. 321 Table C.2 Age distribution of eligible and interviewed women. 322 Table C.3 Completeness of reporting . 323 Table C.4 Births by calendar years . 324 Table C.5 Reporting of age at death in days . 325 Table C.6 Reporting of age at death in months . 326 APPENDIX D PERSONS INVOLVED IN THE 2004 MALAWI DEMOGRAPHIC AND HEALTH SURVEY . 327 APPENDIX E QUESTIONNAIRES . 331 APPENDIX F MILLENNIUM DEVELOPMENT GOAL INDICATORS . 449 APPENDIX G ANALYSIS OF RESPONSE BIAS AND ADJUSTMENT OF HIV PREVALENCE Table G.1 Observed and adjusted HIV prevalence among women and men age 15-49 . 453 Table G.2 Observed and adjusted HIV prevalence among women and men age 15-49 by selected background characteristics . 454 Foreword | xvii FOREWORD This final report presents the major findings of the 2004 Malawi Demographic and Health Survey (MDHS). The 2004 MDHS survey is the third survey of its kind to be conducted in Malawi; the first MDHS was in 1992 and the second was in 2000. The 2004 MDHS included, for the first time, testing of blood samples to provide national rates for anaemia and HIV. The fieldwork was carried out by the National Statistical Office (NSO) in collaboration with the Ministry of Health from October 2004 to January 2005. In 1996, a similar survey on Knowledge, Attitudes, and Practices in Health (MKAPH) was conducted. All four surveys were designed to provide information on indicators of maternal and child health in Malawi. The primary objective of the 2004 MDHS was to provide up-to-date information for policymakers, planners, researchers, and programme managers that would allow guidance in the development, monitoring, and evaluation of health programmes in Malawi. Specifically, the 2004 MDHS collected information on 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, malaria, maternal mortality, HIV/AIDS-related knowledge and behaviours. The survey will also provide the national level estimates of HIV prevalence for women age 15-49 and men age 15-54, and anaemia status of women age 15-49 and children age 6-59 months. The 2004 MDHS results present evidence of a decline in maternal mortality rate as compared to the 2000 MDHS; decrease in fertility rates, an increase in the use of family planning methods and a decline in infant and under-five mortality since the 1992 MDHS. However, the disparity between knowledge and use of family planning remains high. Some of these are critical issues and need to be addressed without delay. The NSO would like to acknowledge the efforts of a number of organisations and individuals who contributed immensely to the success of the survey. First, we would like to acknowledge the financial assistance from the National AIDS Commission (NAC), United States Agency for International Development (USAID), the Department for International Development (DFID), United Kingdom, and the United Nations Children’s Fund (UNICEF/Malawi), the Centers for Disease Control and Prevention (CDC), NORAD (Norway), CIDA (Canada), and UNFPA. We would also like to acknowledge ORC Macro for technical backstopping, and the assistance of the staff of the National Statistical Office, the Ministry of Health and Population, Department of Population Services in the Ministry of Economic Planning and Development, all members of the steering committee and various technical working groups. We also appreciate the work done by the Community Health Services Unit (CHSU), and especially commend the laboratory team assigned to work on the blood samples for their tireless efforts in getting the testing done successfully. xviii | Foreword Finally, we are grateful to the survey respondents who generously gave their time to provide the information that forms the basis of this report. Charles Machinjili Commissioner for Statistics Summary of Findings | xix SUMMARY OF FINDINGS The 2004 Malawi Demographic and Health Survey (MDHS) is a nationally representative survey of 11,698 women age 15- 49 and 3,261 men age 15-54. The main purpose of the 2004 MDHS is to provide policymakers and programme managers with detailed information on fertility, family planning, childhood and adult mortality, maternal and child health, as well as knowledge of and attitudes related to HIV/AIDS and other sexually transmitted infections (STIs). The 2004 MDHS is designed to provide data to monitor the population and health situation in Malawi as a followup of the 1992 and 2000 MDHS surveys, and the 1996 Malawi Knowledge, Attitudes, and Practices in Health Survey. New features of the 2004 MDHS include the collection of information on use of mosquito nets, domestic violence, anaemia testing of women and children under 5, and HIV testing of adults. The 2004 MDHS survey was implemented by the National Statistical Office (NSO). The Ministry of Health and Population, the National AIDS Commission (NAC), the National Economic Council, and the Ministry of Gender contributed to the development of the questionnaires for the survey. Most of the funds for the local costs of the survey were provided by multiple donors through the NAC. The United States Agency for International Development (USAID) provided additional funds for the technical assistance through ORC Macro. The Department for International Development (DfID) of the British Government, the United Nations Children’s Fund (UNICEF), and the United Nations Population Fund (UNFPA) also provided funds for the survey. The Centers of Disease Control and Prevention provided technical assistance in HIV testing. The survey used a two-stage sample based on the 1998 Census of Population and Housing and was designed to produce estimates for key indicators for ten large districts in addition to estimates for national, regional, and urban-rural domains. Fieldwork for the 2004 MDHS was carried out by 22 mobile interviewing teams. Data collection commenced on 4 October 2004 and was completed on 31 January 2005. FERTILITY Fertility Levels and Trends. While there has been a significant decline in fertility in the past two decades from 7.6 children in the early 1980s to 6.0 children per woman in the early 2000s, compared with selected countries in Eastern and Southern Africa, such as Zambia, Tanzania, Mozambique, Kenya, and Uganda, the total fertility rate (TFR) in Malawi is high, lower only than Uganda (6.9). Fertility Differentials. Fertility varies substantially across residence. Urban women have, on average, more than two children fewer than rural women (4.2 and 6.4, respectively). While the TFR in the Central Region is 6.4, in the Southern and Northern Regions it is only 5.8 and 5.6 births per woman, respectively. Among the ten oversampled districts, TFR varies from 4.8 births per woman in Blantyre to 7.2 births per woman in Mangochi. As expected, fertility is strongly associated with education and wealth status. The TFR decreases dramatically from 6.9 for women with no education to 3.8 for women with at least some secondary education. The TFR for women in the lowest (poorest) quintile is 7.1 births per woman, compared with 4.1 births for women in the highest (richest) quintile. xx | Summary of Findings Unplanned Fertility. Despite increasing use of contraception, the 2004 MDHS data indicate that unplanned pregnancies are common in Malawi. Twenty percent of births in the five years preceding the survey are not wanted and 21 percent are mistimed (wanted later). The percentage of recent births that are not wanted increased from 14 percent in 1992 to 22 percent in 2000, and declined to 20 percent in 2004. Fertility Preferences. The 2004 MDHS finding indicates that 35 percent of women wanted no more children and therefore want to limit the family size at its current level, and 6 percent had already been sterilised. Thirty- eight percent of men also report wanting no more children. There has been a decline in fertility preferences among currently married women since 2000. The average ideal family size for all women was 5.0 children in 2000 and was 4.1 in 2004. For all men, ideal family size declined from 4.8 children in 2000 to 4.0 in 2004. FAMILY PLANNING Knowledge of Contraception. Know- ledge of family planning is nearly universal, with 97 percent of women age 15-49 and 97 percent of men age 15-54 knowing at least one modern method of family planning. The most widely known modern methods of contraception among all women are injectables (93 percent), the pill and male condom (90 percent each), and female sterilisation (83 percent). The male condom is the most widely known contraceptive method (72 percent) among women with no sexual experience. These findings are similar to those in the 2000 MDHS. Use of Contraception. One in three married women (33 percent) in Malawi is using a method of family planning. Most of these women are using a modern method (28 percent). Injectables, female sterilisation, and the pill are the most commonly used contraceptive methods, used by 18, 6, and 2 percent of married women, respectively. The most commonly used methods for sexually active unmarried women are injectables (11 percent) and male condoms (10 percent). Trends in Contraceptive Use. Contra- ceptive use among married women in Malawi has increased slightly from 31 percent in 2000 to 33 percent in 2004. This is a much slower increase than between 1992 and 2000 (13 and 31 percent, respectively). There is a notable rise in the use of modern methods from 7 percent in 1992 to 28 percent in 2004, mostly because of a sharp increase in the use of injectables and female sterilisation. The use of male condoms remained unchanged at 2 percent. Differentials in Contraceptive Use. Use of a modern contraceptive method is higher among currently married women in urban areas than women in rural areas (35 and 27 percent, respectively). The highest levels of use of modern family planning methods are in Lilongwe and Blantyre (each 34 percent), and the lowest levels are in Mangochi (17 percent) and Salima (20 percent). Use of modern family planning methods is slightly higher in the Central Region (30 percent) and the Northern Region (29 percent) than in the Southern Region (27 percent). The same pattern was seen in the 2000 MDHS. Use of traditional methods is more common in the Northern Region (13 percent) than in the other regions (3 percent or less). In the Northern Region, withdrawal is the traditional method most commonly used (10 percent). Modern contraceptive methods increase with the woman’s education and wealth status. Twenty-two percent of married women in the lowest wealth quintile use a modern family planning method, and the corresponding proportion for those in the highest wealth quintile is 38 percent. Summary of Findings | xxi Source of Modern Methods. In Malawi, 67 percent of current users of modern methods obtain their methods from a public facility. This is about the same proportion captured in the 2000 MDHS (68 percent). Thirteen percent of all current users get their methods from religious (mission) facilities, 4 percent from the private medical sector, and 17 percent from other sources including nongovernmental organizations (NGOs), where Banja La Mtsogolo is the most commonly used source (13 percent). Contraceptive Discontinuation Rates. Thirty-six percent of contraceptive users discontinue use of a method within a year after beginning to use the method. The 12-month discontinuation rate for modern contraceptives is highest for the male condom (62 percent), followed by the pill (52 percent) and injectables (33 percent). Eight percent of the users report that they stopped using a method because of the desire to get pregnant. Twenty percent gave other reasons for discontinuing. Unmet Need for Family Planning. Unmet need for family planning services is defined as the percentage of currently married women who either do not want any more children or want to wait before having their next birth, but are not using any method of family planning. The 2004 MDHS shows that 28 percent of married women have an unmet need for family planning services: 17 percent for spacing births and 10 percent for limiting births. The total demand for family planning among married women increased from 60 percent in 2000 to 62 percent in 2004. MATERNAL HEALTH Antenatal Care. There has been little change in the coverage of antenatal care (ANC) from a medical professional since 2000 (93 percent in 2004 compared with 91 percent in 2000). Most women receive ANC from a nurse or a midwife (82 percent), although 10 percent go to a doctor or a clinical officer. A small proportion (2 percent) receives ANC from a traditional birth attendant, and 5 percent do not receive any ANC. Only 8 percent of women initiated ANC before the fourth month of pregnancy, a marginal increase from 7 percent in the 2000 MDHS. Eighty-five percent of women received at least one tetanus toxoid injection during pregnancy for their most recent birth in the five years preceding the survey. The coverage of tetanus toxoid injection has not changed since 1992 (85-86 percent). Two in three women had two or more doses of tetanus toxoid injections. This figure is lower than that reported in the 1992 MDHS (73 percent). With regard to malaria prevention during pregnancy, the 2004 MDHS data show that 81 percent of pregnant women took an antimalarial drug and 43 percent of women received two or more doses of intermittent preventive treatment (IPT), at least once during an ANC visit. Delivery Care. The majority of births were attended by medical professionals, 50 percent by a nurse or midwife, 6 percent by a doctor/clinical officer, and only 1 percent by a patient attendant. There has been a slight increase in the proportion of births that are attended by a doctor/clinical officer from 4 percent in 2000 to 6 percent in 2004. The role of traditional birth attendants in assisting delivery also increased from 23 percent in 2000 to 26 percent in 2004. Similar to that recorded in the 2000 MDHS, 3 percent of births in the five years preceding the survey were delivered by C–section. Postnatal Care. Postnatal care is recommended to start immediately after the birth of the baby and placenta to 42 days after delivery. The 2004 MDHS shows that seven in ten women did not receive postnatal care. Among those who had postnatal care (31 percent), 21 percent received care within two days of delivery. Few women had a xxii | Summary of Findings checkup 3-6 days after delivery, and 8 percent received care between the first and sixth week after delivery. Adult and Maternal Mortality. Com- parison of data from the 2000 and 2004 MDHS surveys indicates that mortality for both women and men has remained at the same levels since 1997 (11-12 deaths per 1,000). Data on the survival of respondents’ sisters were used to calculate a maternal mortality ratio for the 7-year period before the survey, centered in mid-2001. Using direct estimation procedures, the maternal mortality ratio (MMR) is estimated to be 984 maternal deaths per 100,000 live births. The MMR based on the 2000 MDHS is significantly higher than that calculated from the 1992 MDHS (620 maternal deaths per 100,000 live births), but lower than the rate from the 2000 MDHS survey of 1,120 maternal deaths per 100,000 live births. It is unlikely that maternal mortality has changed so dramatically up and then down again, especially because the reference periods for the estimates overlap each other. MMRs measured in this way are subject to very high sampling errors and cannot adequately indicate short-term trends. CHILD HEALTH Childhood Mortality. Data from the 2004 MDHS show that for the 2000-2004 period, the infant mortality rate is 76 per 1,000 live births, child mortality is 62 per 1,000, and the under-five mortality rate is 133 per 1,000 live births. This means that about one in every eight children born in Malawi dies before reaching their fifth birthday. The estimate of under-five mortality calculated from the 1992 MDHS data (for the period 1988-1992) is 234 and from the 2000 MDHS data (1996-2000) is 189 per 1,000 live births. These figures suggest that the decline between 2000 and 2004 is faster than between 1992 and 2000 (29 and 19 percent, respectively). During the 15-year period preceding the survey, the estimates of neonatal mortality show a decline of 36 percent (from 42 to 27 per 1,000 live births). Childhood Vaccination Coverage. In the 2004 MDHS, mothers were able to show a health card with immunisation data for 74 percent of children age 12-23 months. This is lower than that recorded in 1992 and 2000 (86 and 81 percent, respectively). Sixty-four percent of children 12-23 months are fully vaccinated against six major childhood illnesses (tuberculosis, diphtheria, pertussis, tetanus, polio, and measles). Nine in ten of these children have been vaccinated against tuberculosis, 95 percent received polio 1 and DPT 1. Comparison with estimates of coverage of specific vaccines based on the 1992 and 2000 MDHS data show that the immunisation coverage for children has declined over time. Child Illness and Treatment. Acute respiratory infections (ARI), diarrhoea, and malaria are common causes of child death. In the two weeks before the survey, 19 percent of children under five years of age were ill with a cough and short, rapid breathing, 37 percent of children had fever, and 22 percent of children experienced diarrhoea. Among children with symptoms of ARI and/or fever, 20 percent were taken to a health facility, as were 36 percent of children with diarrhoea. Cough and diarrhoea are highest among children age 6-11 months. More than half (61 percent) of children with diarrhoea were treated with ORS (solution prepared from oral rehydration salts), 70 percent were given either ORS or increased fluids, and 18 percent received no treatment. Among children with fever, 57 percent were given an antimalarial drug, and 46 percent were given the drug on the same day or the following day. One in five children under age five years slept under a mosquito net the night before the survey, and most of them (18 percent) slept under an insecticide-treated net. Summary of Findings | xxiii NUTRITION Breastfeeding Practices. Breastfeeding is nearly universal in Malawi. Ninety- eight percent of children are breastfed for some period of time. The median duration of breastfeeding in Malawi in 2004 is 23.2 months, one month shorter than in 2000. The median duration of exclusive breastfeeding is 2.5 months, whereas the median for predominant breastfeeding is 4.8 months, twice as long as that recorded in 2000. More than half (53 percent) of children under six months are exclusively breastfed compared with 45 percent in the 2000 MDHS. Bottle-feeding is uncommon in Malawi. Use of feeding bottles in children under age six months has remained at the same level as in the 2000 MDHS (3 percent). Intake of Vitamin A. The Ministry of Health’s policy is to supplement children age 6- 59 months with a dose of vitamin A capsules once every six months. The 2004 MDHS shows that 65 percent of children under age three had consumed foods rich in vitamin A in the seven days preceding the survey and 65 percent of children had received a vitamin A capsule in the last six months before the survey. Furthermore, 41 percent of women received a vitamin A supplement during the postnatal period. This is the same level as that recorded in the 2000 MDHS. Nutritional Status of Children. The 2004 MDHS shows that the nutritional status of children under five has not improved since 1992. At the national level, 48 percent of children under five in Malawi are stunted, or too short for their age, 5 percent of children are wasted or too thin, and 22 percent are underweight. For the first time in Malawi, the DHS collected blood samples to be tested for haemoglobin level, a measurement of anaemia. The survey found that 73 percent of children age 6-59 months are anaemic: 26 percent have mild anaemia, 42 percent have moderate anaemia, and 5 percent have severe anaemia. Nutritional Status of Women. The nutritional status of women in Malawi has remained constant since 2000; the mean height of mothers is 156 centimetres. The cut-off point, below which a woman is considered at risk, is between 140 and 150 centimetres. Three percent of women are less than 145 centimetres in height., The 2004 MDHS used the body mass index (BMI)—defined as weight in kilograms divided by height squared in metres, to assess thinness and obesity. A cut off point of 18.5 is used to define chronic energy deficiency. The mean BMI among the weighed and measured women in the 2004 MDHS is 22, with 77 percent of women classified as normal (BMI 18.5-24.9) and 9 percent are considered thin (BMI below 18.5). Fourteen percent of women in Malawi are classified as overweight or obese (BMI 25.0 or higher). The survey also found that 45 percent of women are anaemic: 33 percent have mild anaemia, 11 percent have moderate anaemia, and 2 percent have severe anaemia. HIV/AIDS Awareness of AIDS. Knowledge of AIDS among women and men in Malawi is almost universal. This is true across age group, urban-rural residence, marital status, wealth index, and education. Nearly half of women and six in ten men can identify the two most common misconceptions about the transmission of HIV—HIV can be transmitted by mosquito bites, and HIV can be transmitted by supernatural means—and know that a healthy-looking person can have the AIDS virus. Attitudes Towards Persons with HIV. To gauge stigma associated with AIDS, the 2004 MDHS asked respondents who had heard of HIV/AIDS about their attitudes towards people with HIV. These questions include whether respondents would be willing to take care of orphaned children of family member who died of HIV, whether they would buy fresh vegetables from a shopkeeper who is xxiv | Summary of Findings infected with HIV, and whether they believe an HIV-positive female teacher should be allowed to keep on teaching. Almost all women and men age 15-49 (94 and 97 percent, respectively) say that they are willing to take care of orphaned children of a family member who died of AIDS. About two in three women and 84 percent of men say they would buy fresh vegetables from a shopkeeper who is HIV- positive. Two in three women and 80 percent of men say that an HIV-positive female teacher should be allowed to keep teaching. Sixty- five percent of women and 48 percent of men say that they would not necessarily fear disclosure of a family member’s HIV-positive status. Looking at all of the stigmas attached to persons with AIDS, 31 percent of women age 15-49 and 30 percent of men age 15-49 expressed acceptance of all four measures of stigma. HIV-Related Behavioural Indicators. Three in four women agree that HIV can be transmitted by breastfeeding, while about four in ten said the risk of mother-to-child transmission (MTCT) can be reduced by the mother taking drugs during pregnancy, and 37 percent reported both, that HIV can be transmitted by breastfeeding and the risk of MTCT can be reduced by the mother taking special drugs during pregnancy. Sixty- seven percent of men say that HIV can be transmitted by breastfeeding, 35 percent say that the risk of MTCT can be reduced by the mother taking drugs during pregnancy, and 29 percent report that HIV can be transmitted by breastfeeding and that the risk of MTCT can be reduced by taking special drugs during pregnancy. Delaying the age at which young persons become sexually active is an important strategy for reducing the risk of contracting a sexually transmitted infection (STI). In Malawi, 15 percent of women age 15-24 and 14 percent of men age 15-24 have had sex by age 15. Sexual intercourse with a nonmarital or noncohabiting partner is associated with an increase in the risk of contracting an STI. Eight percent of women and 27 percent of men engaged in higher-risk sexual behaviour in the last 12 months. Higher-risk sexual behaviour is even more common among youth age 15-24. Fourteen percent of young women and 62 percent of young men age 15-24 engaged in higher-risk sexual activity in the 12 months preceding the survey. Only 39 percent of young women and 46 percent of young men reported using a condom at last higher-risk sexual intercourse. HIV Testing. To gauge the coverage of HIV testing, respondents in the 2004 MDHS were asked if they had ever been tested to see if they have the AIDS virus. Those who had been tested were asked when they were last tested, whether they had asked for the test or were required to take it, and whether they received their results. Thirteen percent of women age 15-49 and 15 percent of men age 15-49 have been tested for HIV and received the test results. Additionally, 2 percent of women and 2 percent of men were tested but never received the result. HIV Prevalence. One in three households in the 2004 MDHS sample was selected for individual interviews with male respondents. All men age 15-54 in these households were eligible for individual interview. In the same households, all women age 15-49 and all men age 15-54 were asked to voluntarily provide some drops of blood for HIV testing in the laboratory. Results indicate that 12 percent of adults age 15-49 in Malawi is infected with HIV. HIV prevalence is higher among women than among men (13 and 10 percent, respectively). Prevalence peaks at 19 percent for adults age 30-34, 18 percent for women, and 20 percent for men. Patterns of HIV Prevalence. Prevalence is higher in urban areas than in rural areas. While 18 percent of urban women are HIV Summary of Findings | xxv positive, the corresponding proportion for rural women is 13 percent. For men, the urban-rural difference in HIV prevalence is even greater; urban men are nearly twice as likely to be infected as rural men (16 and 9 percent, respectively). HIV prevalence among women is higher in the Southern Region (20 percent) than in the Northern (10 percent) or Central (7 percent) Regions. The same pattern is observed for men, HIV prevalence is higher in Southern Region (15 percent) than in Central (6 percent) and Northern (5 percent) Regions. In Malawi, circumcised men have a slightly higher HIV infection rate than men who are not circumcised (13 and 10 percent, respectively). Among couples, 83 percent are both HIV negative, and 7 percent are both HIV positive. Ten percent of the couples are discordant, that is, one partner is infected and the other not. GENDER-RELATED VIOLENCE Violence since Age 15. Gender-related violence refers to any act of violence that results in, or is likely to result in, physical, sexual, or psychological harm or suffering to women. Domestic violence has negative health consequences on the victims and on the reproductive health of women. In response to the international and regional instruments on women’s rights, the Malawi government and its stakeholders started to implement various initiatives aimed at creating awareness on the dangers of gender-based violence. In the 2004 MDHS, women were asked if they had experienced any physical violence since age 15. The data show that 28 percent of women experienced physical violence since age 15 and 15 percent experienced it in the 12 months preceding the survey. Marital Violence. Seventy-seven percent of ever-married women who ex- perienced physical violence report their husbands as the perpetrators of the violence. The survey further found that 13 percent of ever-married women report to have ever experienced emotional violence, 20 percent experienced physical violence, and 13 percent experienced sexual violence. About one-third of women (30 percent) experienced at least one of the three forms of violence, and 4 percent experience all three forms of violence. The common form of spousal violence is slapping and arm twisting (16 percent) and forced intercourse or marital rape (13 percent). The 2004 MDHS results show that 39 percent of women were physically or sexually violated once or twice in the 12 months preceding the survey, 21 percent three to five times, and 10 percent more than five times. The factor most strongly related to marital violence is husband’s alcohol and/or drug use. Violence is more than twice as prevalent among women who say their husband gets drunk very often as among those whose husbands do not drink. Help-seeking Behaviour among Wo- men who Experienced Violence. Less than half of women who experienced violence actually sought help (42 percent). Of these women, 44 percent sought help from relatives or friends, one in three sought help from their own family, and 11 percent sought help from their in-laws. MALARIA Mosquito Nets. The use of insecticide- treated mosquito nets (ITNs) is a primary health intervention proven to reduce malaria transmission. The 2004 MDHS found that 42 percent of households in Malawi own at least one mosquito net, 29 percent of households own at least one ever-treated mosquito net, and 12 percent of households own an ITN. In one in five households the interviewer observed the mosquito nets. Among the observed nets, 21 percent are blue, 74 percent are green, and 5 percent are white. Most nets (71 percent) are rectangular. About one in four of the observed nets had at least one hole. Of the households that have no mosquito nets, 38 percent prefer a blue net and 41 percent prefer a green net. Forty-five percent of households with no mosquito net prefer a xxvi | Summary of Findings conical net while 43 percent prefer a rectangular net. One in five children under five years in Malawi slept under a mosquito net the night before the survey. Most of these children (18 percent) slept under an ever-treated net and 15 percent slept under an ITN. There is a small difference in the use of mosquito nets between pregnant women (19 percent) and all women (21 percent). Intermittent Preventive Treatment during Pregnancy. In Malawi, as a protective measure against various adverse outcomes of pregnancy, it is recommended that pregnant women receive at least two doses of sulfadoxine- pyrimethamine (SP), one in the second trimester and one in the third trimester. The 2004 MDHS data show that 81 percent of pregnant women in Malawi take an antimalarial drug for prevention during pregnancy—almost all take SP/Fansidar (79 percent)—and most women receive the drug during an ANC visit. Less than half (47 percent) of the women receive the recommended two or more doses of SP/ Fansidar. Prevalence and Management of Malaria in Children. The survey found that 37 percent of children had fever and/or convulsions in the two weeks preceding the survey. Of the children that had fever, 57 percent were given an antimalaria drug and 46 percent were given the medication the same or the following day. Children with fever were given quinine (45 percent), amodiaquine (39 percent), or SP/Fansidar (23 percent). One in five children were given medication (modern pharmaceutical or traditional) that was obtained at home, 39 percent of the children were given medicine that was bought at a pharmacy or shop (without a prescription), and 31 percent were taken to a health centre. Six percent of children with fever were not treated. MEN’S PARTICIPATION IN HEALTH CARE Reproductive Health Care. The 2004 MDHS collected information on men’s participation in their wives and children’s health care. This information helps family planning and health programme managers in investigating men’s role in taking care of the health of their family. When asked about antenatal care, 96 percent of fathers reported that the mother of their last child born in the five years preceding the survey received care from a health professional. This was almost the same as the response given by women (93 percent). For delivery assistance by a health care provider, 74 percent of men reported this response compared with 57 percent of women. Differences in question wording may account for differences in reporting by men and women. It should also be noted that fathers and mothers may not necessarily be reporting on the same child. Main Provider during Pregnancy, Delivery and after Delivery. The majority of men with a child born in the past five years reported that free services were received for antenatal care for 76 percent of pregnancies, delivery care for 66 percent of births, and postnatal care for 86 percent of births. Fathers reported providing payment for antenatal care for 19 percent of pregnancies, delivery care for 27 percent of births, and postnatal care for 12 percent of births. Decisionmaker on Child’s Health Care. The 2004 MDHS also collected information from fathers on who usually decides about their children’s health care. Questions were specifically asked about the health care for their youngest child under five. In 87 percent of cases, fathers reported that they decide about the health care for their children; mothers do so in 64 percent of cases. Summary of Findings | xxvii Knowledge of Signs of Danger in Pregnancy. The results from the 2004 MDHS show that men’s knowledge of danger signs in pregnancy is limited. Two in three men have no knowledge of any danger signs or symptoms that indicate that a pregnancy may be at an elevated risk. The most often cited sign of pregnancy complication is vaginal bleeding, with 11 percent of men reporting this complication. xxviii | Map of Malawi Introduction | 1 INTRODUCTION 1 Derek Zanera 1.1 GEOGRAPHY, HISTORY, AND THE ECONOMY 1.1.1 Geography Malawi is a landlocked country south of the equator in sub-Saharan Africa. 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 ranges in width from 80 to 161 kilometres. The total area is 118,484 square kilometres of which 94,276 square kilometres is land area. The remaining area is mostly composed of Lake Malawi, which is about 475 kilometres long and runs down 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 lie 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 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 under British rule from 1891 until July 1964 under the name of the Nyasaland Protectorate. 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 and gained republic status in 1966. In 1994 Malawi adopted a multiparty system and a strategy to eradicate poverty. Since then, it has introduced free primary school education, a free market economy, a bill of rights, and a parliament with three main parties. Over the past ten years, the country has experienced a considerable increase of rural-to-urban migration. 2 | Introduction 1.1.3 Economy Malawi has a predominantly agricultural economy. Agricultural produce accounted for 70 percent of Malawi exports in 2004, tobacco, tea, and sugar being the major export commodities. The country is largely self-sufficient with regard to food, but due to the high cost of fertilizer, coupled with erratic rains for the past three years, Malawi is experiencing food insecurity, making it largely dependent on imported maize from South Africa. 1.2 POPULATION The major source of historical demographic data comes from the population census, which was taken every ten years from 1891 to 1931. Since World War II, population censuses were conducted in 1945, 1966, 1977, 1987, and 1998. 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); and the 2000 MDHS. Table 1.1 provides some demographic indicators for Malawi based on various data sources. The population of Malawi grew from 8.0 million in 1987 to 9.9 million in 1998, as enumerated by the 1998 Population and Housing census, representing an increase of 24 percent, or an intercensal population growth rate of 2 percent per year. Population density increased from 85 persons per square kilometre in 1987 to 105 persons per square kilometre in 1998. To address problems associated with rapid population growth, in 1994 the Malawi government adopted the 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 an emphasis on raising the proportion of female students to 50 percent of total enrolment, and to increase employment opportunities, particularly in the private sector. Table 1.1 Demographic indicators Selected demographic indicators, Malawi 1998 national census and population projections 1999-2002 Census Year Projections Indicator 1998 1999 2000 2001 2002 Population (midyear population) 9,933,868 10,152,753 10,475,257 10,816,294 11,174,648 Intercensal growth rate 2.0 3.1 3.2 3.3 3.3 Total area (sq km) 118,484 118,484 118,484 118,484 118,484 Land area (sq km) 94,276 94,276 94,276 94,276 94,276 Density (population per sq km) 105 108 111 115 119 Percentage of urban population 14.0 14.3 14.8 15.2 15.7 Women of childbearing age as a percentage of female population 47.2 48.2 49.8 51.4 53.1 Sex ratio 96.0 96.2 96.3 96.4 96.4 Crude birth rate 37.9 52.3 51.9 51.4 50.8 Total fertility rate 6.2 6.7 6.7 6.6 6.5 Crude death rate 21.1 23.1 21.8 20.5 19.4 Infant mortality rate 121.0 91.4 89.5 87.6 85.7 Life expectancy: Male 40.0 41.1 41.7 42.3 42.8 Female 44.0 43.8 44.3 44.9 45.5 Source: National Statistical Office (NSO). 1998 Population Projections for Malawi 1999 to 2023 based on the Population and Housing Census. Introduction | 3 1.3 OBJECTIVE OF THE SURVEY The principal aim of the 2004 MDHS project was to provide up-to-date information on fertility and childhood mortality levels, nuptiality, fertility preferences, awareness and use of family planning methods, use of maternal and child health services, and knowledge and behaviours related to HIV/AIDS and other sexually transmitted infections. It was designed as a follow-on to the 2000 MDHS survey, a national-level survey of similar scope. The 2004 MDHS survey, unlike the 2000 MDHS, collected blood samples which were later tested for HIV in order to estimate HIV prevalence in Malawi. In broad terms, the 2004 MDHS survey aimed to: • Assess trends in Malawi’s demographic indicators, principally fertility and mortality • Assist in the monitoring and evaluation of Malawi’s health, population, and nutrition programmes • Advance survey methodology in Malawi and contribute to national and international databases • Provide national-level estimates of HIV prevalence for women age 15-49 and men age 15-54. In more specific terms, the 2004 MDHS survey was designed to: • Provide data on the family planning and fertility behaviour of the Malawian population and thereby enable policymakers to evaluate and enhance family planning initiatives in the country • Measure changes in fertility and contraceptive prevalence and analyse the factors that affect these changes, such as marriage patterns, desire for children, availability of contraception, breastfeeding habits, and important social and economic factors • Examine basic indicators of maternal and child health and welfare in Malawi, including nutritional status, use of antenatal and maternity services, treatment of recent episodes of childhood illness, and use of immunisation services. Particular emphasis was placed on malaria programmes, including malaria prevention activities and treatment of episodes of fever. • Provide levels and patterns of knowledge and behaviour related to the prevention of HIV/AIDS and other sexually transmitted infections • Provide national estimates of HIV prevalence • Measure the level of infant and adult mortality including maternal mortality at the national level • Assess the status of women in the country. 4 | Introduction 1.4 ORGANISATION OF THE SURVEY The 2004 MDHS survey was a comprehensive survey that involved several agencies. The National Statistical Office (NSO) had primary responsibility for conducting the survey. The Ministry of Health and Population, the National AIDS Commission (NAC), the National Economic Council, and the Ministry of Gender also contributed to the development of the questionnaires for the survey. Most of the funds for the local costs of the survey were provided by multiple donors through NAC. Financial support for the survey was also provided by the United States Agency for International Development (USAID), the United Kingdom’s Department for International Development (DFID), the United Nations Children’s Fund (UNICEF/Malawi) and United Nations Population Fund (UNFPA). Technical assistance was provided by ORC Macro through the USAID-funded MEASURE DHS project based in Calverton, Maryland, USA. The Centers for Disease Control and Prevention provided technical assistance in HIV testing. 1.4.1 Sample Design The 2004 MDHS survey was designed to provide estimates of health and demographic indicators at the national and regional levels, for rural and urban areas, and for selected large districts that were oversampled. To meet this objective, 522 clusters were drawn from the 1998 census sample frame: 458 in rural areas and 64 in urban areas. The following districts were oversampled in the 2004 MDHS in order to produce reliable district level estimates; Mulanje, Thyolo, Kasungu, Salima, Machinga, Zomba, Mangochi, Mzimba, Blantyre, and Lilongwe. The National Statistical Office staff conducted an exhaustive listing of households in each of the MDHS clusters in August and September 2004. From these lists, a systematic sample of households was drawn for a total of 15,091 households. All women age 15-49 in the selected households were eligible for individual interview. Every third household in the 2004 MDHS sample was selected for the male survey. In these households, all men age 15-54 were eligible for individual interview and HIV testing. In the same households, all women age 15-49 were eligible for HIV testing. During data collection, field staff used global positioning system (GPS) receivers to establish and record geographic coordinates of each of the MDHS clusters. 1.4.2 Questionnaires Three types of questionnaires were used in the 2004 MDHS survey: the Household Questionnaire, the Women’s Questionnaire, and the Men’s Questionnaire. The contents of the questionnaires were based on the MEASURE DHS model questionnaires, which were adapted for use in Malawi in collaboration with a wide range of stakeholders. The MDHS survey instruments were translated into and printed in Chichewa and Tumbuka for pretesting. The Household Questionnaire was used to list all of the usual members and visitors in the selected households. Basic information on each person listed was collected, including age, sex, education, and relationship to the head of the household. Height and weight measurements were taken for all women age 15-49 and all children under the age of five. Respondents to the Household Questionnaire were asked questions on child labour for each child ages 5-14 living in the household or who spent the preceding night in the household. In addition, information was collected about the dwelling itself such as the source of water, type of toilet facilities, materials used to construct the Introduction | 5 house, ownership of various consumer goods, and use of bed nets. The Household Questionnaire was also used to identify persons eligible for individual interview: women age 15-49 and men age 15- 54. One woman in each household was selected for the interview on domestic violence. The Women’s Questionnaire was used to collect information from women age 15-49 and included questions on the following topics: • Background characteristics (age, education, religion, etc.) • Reproductive history (to arrive at fertility and childhood mortality rates) • Knowledge and use of family planning methods • Antenatal, delivery, and postnatal care • Infant feeding practices, including patterns of breastfeeding • Vaccinations • Episodes of childhood illness and responses to illness, with a focus on treatment of fevers in the last two weeks • Marriage and sexual activity • Fertility preferences • Husband’s background and the woman’s work status • Woman’s status and decisionmaking • Mortality of adults, including maternal mortality • AIDS-related knowledge, attitudes, and behaviour • Domestic violence The Men’s Questionnaire was much shorter than the Women’s Questionnaire, but covered many of the same topics, excluding the detailed reproductive history and sections dealing with maternal and child health and adult and maternal mortality. 1.4.3 Pretest Twelve NSO permanent staff were recruited as interviewers for the DHS pretest of the questionnaires, which was conducted in June and July 2004. The 12 interviewers were trained in conducting interviews and taking blood samples for anaemia and HIV testing. The training took place at the NSO offices for a period of two weeks. The interviewers were split into three teams to conduct interviews in the Northern Region, Central Region, and Southern Region, respectively. During the pretest fieldwork, 206 Household Questionnaires, 160 Women’s Questionnaires, and 154 Men’s Questionnaires were completed. Based on the observations in the field and suggestions 6 | Introduction made by the pretest field teams, revisions were made in some skip patterns, wording, and translations of the questionnaires. 1.4.4 Training A total of 180 people were recruited by NSO for the main training. Training was held for five weeks at Magomero College, south of Zomba town. The first week of training was devoted to the collection of blood samples. Sixty persons were trained to collect blood samples, 34 of whom had medical training and 26 with no medical training. These participants were joined in subsequent weeks by 120 persons who were trained as interviewers only. The second phase of training focused on interviewing the respondents and taking height and weight measurements. Initially, training consisted of lectures on the underlying rationale of the questionnaires’ content and how to complete the questionnaires. Guest lecturers were invited to give talks on specific subjects such as family planning and gender issues, in particular domestic violence. Mock interviews were conducted between participants to allow practice in proper interviewing techniques and the use of local language questionnaires. Throughout the training, participants were given tests to evaluate their understanding and skills in the survey procedures. Toward the end of training, participants spent several days practicing interviews near the training centre. 1.4.5 Data Collection and Data Processing Fieldwork for the 2004 MDHS was carried out by 22 mobile teams, each consisting of one supervisor, one field editor, four or five female interviewers, and one male interviewer. Two or three of the interviewers on each team were trained in taking blood samples, and at least one of these was medically trained. Four senior NSO staff and one from Ministry of Health and Population supervised and coordinated fieldwork activities. In addition, three health technicians were assigned to supervise the blood collection for anaemia and HIV testing. Fieldwork commenced on 4 October 2004 and was completed by 31 January 2005. All questionnaires for the MDHS were returned to the NSO central office in Zomba for data processing. The processing operation consisted of office editing, coding of open-ended questions, data entry, double entry verification, and editing inconsistencies found by computer programs developed for the MDHS. The MDHS data entry and editing programs used CSPro, a computer software package specifically designed for processing survey data such as that produced by DHS surveys. Data processing commenced one month after fieldwork and was completed in May 2005. Testing of blood samples started in May 2005 and was completed in June 2005. Table 1.2 shows the results of household and individual interviews for Malawi as a whole and for urban and rural areas. A total of 15,041 households were selected in the MDHS sample, of which 13,965 were occupied. Of the occupied households, 13,664 were interviewed, yielding a household response rate of 98 percent. The household response rate is higher in rural areas. In the 13,664 interviewed households, 12,229 women age 15-49 were identified as eligible for the individual interview, and interviews were completed for 11,698, for a 96 percent response rate. Of the 3,797 men age 15-54 who were identified as eligible for individual interview, 3,261 were interviewed, resulting in an 86 percent response rate. For both women and men, the main reason for nonresponse in the MDHS was failure to find the respondents despite repeated visits to the Introduction | 7 household. Compared with the 2000 MDHS, the response rate for women declined from 98 to 96 percent and the response rate for men declined from 97 to 95 percent. Table 1.2 Results of the household and individual interviews Number of households, number of interviews, and response rates, according to residence, Malawi 2004 Residence Result Urban Rural Total Household interviews Households selected 1,984 13,057 15,041 Households occupied 1,799 12,166 13,965 Households interviewed 1,724 11,940 13,664 Household response rate 95.8 98.1 97.8 Interviews with women Number of eligible women 1,733 10,496 12,229 Number of eligible women inter- viewed 1,640 10,058 11,698 Eligible woman response rate 94.6 95.8 95.7 Interviews with men Number of eligible men 632 3,165 3,797 Number of eligible men inter- viewed 507 2,754 3,261 Eligible man response rate 80.2 87.0 85.9 Characteristics of Households and Household Members | 9 CHARACTERISTICS OF HOUSEHOLDS AND HOUSEHOLD MEMBERS 2 Isaac Dambula and Ephraim N.B. Chibwana This chapter describes the demographic and socioeconomic characteristics of the population in the sampled households. It also examines environmental conditions, such as housing facilities and physical features of dwelling units. This information on the characteristics of the surveyed population is essential for the interpretation of survey findings and can provide an approximate indication of the representativeness of the MDHS survey. For the 2004 MDHS survey, a household was defined as a person or a group of persons, related or unrelated, who live together in the same dwelling unit, who make common provisions for food and regularly take their food from the same pot or share the same grain store (nkhokwe), or who pool their income for the purpose of purchasing food. The Household Questionnaire was used to collect information on all usual residents and visitors who spent the night preceding the survey in the household. This allows the analysis of either de jure (usual residents) or de facto (those who are there at the time of the survey) populations. One of the background characteristics used throughout this report is the wealth index, which is a proxy of socioeconomic status. The index was developed and tested in a large number of countries in relation to inequities in household income, use of health services, and health outcomes (Rutstein et al., 2000). It is an indicator of the level of wealth that is consistent with expenditure and income measures (Rutstein, 1999). The index was constructed by applying principal components analysis to information on household assets. The asset information was collected in the Household Questionnaire of the 2004 MDHS and covers information on household ownership of a number of consumer items ranging from a paraffin lamp to a bicycle, motorcycle, or car, as well as dwelling characteristics, such as source of drinking water, sanitation facilities, and construction material used for flooring. Each asset was assigned a weight (factor score) generated through principal components analysis, and the resulting asset scores were standardized in relation to a normal distribution with a mean of zero and standard deviation of one (Gwatkin et al., 2000). Each household was then assigned a score for each asset, and the scores were summed for each household; individuals were ranked according to the total score of the household in which they resided. The sample was then divided into quintiles—five groups with the same number of individuals in each—from one (lowest) to five (highest). A single asset index was developed for the whole sample; separate indices were not prepared for the urban and rural population separately. 2.1 HOUSEHOLD POPULATION BY AGE, SEX, AND RESIDENCE The distribution of the household population in the 2004 MDHS survey is shown in Table 2.1 by five-year age groups, according to sex and urban-rural residence. The 13,664 households successfully interviewed in the 2004 MDHS were composed of 58,886 persons; 30,163 were women, representing 51 percent of the population, and 28,722 were men, representing 49 percent. The age structure of the population indicates that a larger proportion of the population falls into the younger age groups for each sex in both rural and urban areas as a result of relatively high fertility. 10 | Characteristics of Households and Household Members This pattern mirrors that seen in the 1998 Population and Housing Census, and can be seen in Figure 2.1, which shows that the population structure is much wider at the younger ages than at the older ages. There is no evidence of a tapering at the younger ages, which would be expected in a population with declining fertility rates (see Chapter 4). This indicates that Malawi’s fertility decline is very recent and is not yet evident in the population structure. 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 2004 Urban Rural Total Age Male Female Total Male Female Total Male Female Total <5 13.9 16.7 15.3 19.0 17.9 18.4 18.1 17.7 17.9 5-9 12.9 13.1 13.0 16.5 15.8 16.1 15.9 15.4 15.6 10-14 13.2 15.2 14.1 14.9 14.8 14.9 14.6 14.9 14.8 15-19 10.5 11.0 10.7 9.7 8.1 8.9 9.8 8.5 9.2 20-24 11.8 14.6 13.1 7.7 9.3 8.5 8.4 10.1 9.2 25-29 13.2 9.3 11.3 6.8 7.1 7.0 7.9 7.5 7.7 30-34 7.3 4.6 6.0 5.4 5.1 5.3 5.7 5.0 5.4 35-39 3.9 4.0 4.0 3.8 3.7 3.7 3.8 3.7 3.8 40-44 3.8 2.9 3.4 3.2 3.3 3.2 3.3 3.2 3.2 45-49 2.4 2.2 2.3 2.3 2.5 2.4 2.3 2.5 2.4 50-54 1.9 2.7 2.3 2.3 3.4 2.9 2.3 3.3 2.8 55-59 2.6 1.5 2.1 2.5 2.6 2.5 2.5 2.4 2.5 60-64 0.9 0.7 0.8 2.0 2.0 2.0 1.8 1.8 1.8 65-69 0.6 0.5 0.5 1.4 1.5 1.4 1.2 1.4 1.3 70-74 0.7 0.4 0.6 1.2 1.3 1.2 1.1 1.2 1.1 75-79 0.2 0.3 0.2 0.6 0.8 0.7 0.5 0.7 0.6 80 + 0.3 0.4 0.3 0.7 0.8 0.7 0.6 0.7 0.7 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Number 4,880 4,496 9,376 23,843 25,667 49,510 28,722 30,163 58,886 Figure 2.1 Population Pyramid 80+ 75-79 70-74 65-69 60-64 55-59 50-54 45-49 40-44 35-39 30-34 25-29 20-24 15-19 10-14 5-9 0-4 0246810 0 2 4 6 8 10 Age Male Percent Female Characteristics of Households and Household Members | 11 2.2 HOUSEHOLD COMPOSITION Information about the composition of households by sex of the household head and household size is presented in Table 2.2. The data show that 75 percent of households in Malawi are headed by men. This proportion has not changed since 1992 (75 percent) and 2000 (73 percent). Female-headed households are more common in rural areas (26 percent) than in urban areas (17 percent). The average household size in Malawi remains at 4.4 persons, the same size recorded in 2000. The household size in rural areas is slightly larger than in urban areas (4.4 compared with 4.2 persons, respectively). Table 2.2 Household composition Percent distribution of households by sex of head of household and by household size, according to residence, Malawi 2004 Residence Characteristic Urban Rural Total Sex of head of household Male 83.5 73.7 75.3 Female 16.5 26.3 24.7 Total 100.0 100.0 100.0 Number of usual members 0 0.6 0.2 0.3 1 12.0 7.6 8.4 2 13.1 12.3 12.4 3 16.6 17.7 17.5 4 18.2 18.7 18.6 5 13.2 15.1 14.8 6 11.1 11.4 11.4 7 6.5 8.0 7.8 8 4.0 4.3 4.3 9+ 4.6 4.7 4.7 Total 100.0 100.0 100.0 Number of households 2,262 11,402 13,664 Mean size 4.2 4.4 4.4 Note: Table is based on de jure members, i.e., usual residents. 2.3 FOSTERHOOD AND ORPHANHOOD Information on the living arrangements of children under age 18 is presented in Table 2.3. Of the 31,981 children under age 18 recorded in the 2004 MDHS, only 58 percent currently live with both their biological parents; the remainder live with either their mother only (19 percent) or their father only (3 percent), or live with neither of their natural parents (20 percent). The table also provides data on the extent of orphanhood, that is, the proportion of children who have lost one or both parents. Of children under 18 years, 12 percent have lost their father, 6 percent have lost their mother, and 4 percent have lost both of their natural parents. With the rates of adult illness and mortality related to HIV/AIDS rising in Malawi (see Chapter 12), the percentage of households with orphaned and foster children is expected to rise in the near term. Differentials in fosterhood and orphanhood by background characteristics are not large. As expected, older children are more likely than younger children to be fostered or orphaned. A slightly larger proportion of urban children than rural children have lost one or both parents. 12 | Characteristics of Households and Household Members Table 2.3 indicates that children’s living arrangements have no consistent pattern by household wealth index quintile. Among the oversampled districts, children in Kasungu are the most likely to live with both their parents (69 percent), while children in Mangochi are the least likely to live with both parents (50 percent). Table 2.3 Children's living arrangements and orphanhood Percent distribution of de jure children under age 18 by children's living arrangements and survival status of parents, accord- ing to background characteristics, Malawi 2004 Living with mother but not father Living with father but not mother Not living with either parent Background characteristic Living with both parents Father alive Father dead Mother alive Mother dead Both alive Only father alive Only mother alive Both dead Missing information on father/ mother Total Number of children Age <2 77.3 18.6 2.0 0.1 0.1 1.0 0.2 0.1 0.1 0.5 100.0 4,717 2-4 68.7 15.7 3.5 1.0 0.5 7.7 0.7 0.7 1.0 0.6 100.0 5,947 5-9 56.5 13.1 5.8 2.1 0.7 13.8 2.1 2.6 2.7 0.7 100.0 9,299 10-14 47.5 11.6 8.3 2.4 1.2 14.8 3.1 4.4 6.0 0.8 100.0 8,808 15-17 41.2 9.0 8.6 2.6 1.2 17.2 3.7 5.3 8.8 2.4 100.0 3,211 <15 59.7 14.1 5.5 1.6 0.7 10.7 1.8 2.3 2.9 0.7 100.0 28,770 Sex Male 58.3 13.8 5.8 1.9 0.8 10.3 1.9 2.6 3.6 0.9 100.0 15,902 Female 57.4 13.3 5.7 1.5 0.8 12.4 2.1 2.6 3.4 0.7 100.0 16,079 Residence Urban 58.8 7.7 5.9 3.6 1.4 10.9 2.2 3.8 4.9 0.8 100.0 4,566 Rural 57.7 14.6 5.8 1.4 0.7 11.4 2.0 2.4 3.3 0.8 100.0 27,416 Region Northern 59.1 11.1 5.7 2.3 1.1 11.8 1.5 3.0 3.7 0.6 100.0 4,193 Central 59.4 11.2 5.3 2.2 0.7 12.6 2.2 2.3 3.2 1.0 100.0 13,638 Southern 55.9 16.6 6.3 1.1 0.8 10.0 2.0 2.8 3.8 0.7 100.0 14,150 District Blantyre 61.2 10.7 5.1 2.2 1.2 9.0 2.3 2.9 4.8 0.4 100.0 2,188 Kasungu 68.9 6.0 2.4 1.8 0.8 12.3 2.1 2.7 2.7 0.2 100.0 1,488 Machinga 55.5 17.6 5.8 1.3 0.4 11.2 2.4 2.5 2.3 0.9 100.0 1,230 Mangochi 50.2 21.8 5.6 0.8 0.5 14.4 1.8 2.2 2.1 0.6 100.0 1,800 Mzimba 63.1 10.7 4.2 1.7 1.2 13.0 1.4 2.1 2.0 0.6 100.0 2,064 Salima 57.6 12.1 6.0 0.5 0.6 15.1 2.4 2.4 2.9 0.4 100.0 930 Thyolo 52.8 19.9 5.9 0.8 0.8 10.2 2.1 3.2 3.5 0.8 100.0 1,630 Zomba 51.4 17.1 8.4 0.8 1.0 10.9 2.4 3.5 4.4 0.3 100.0 1,566 Lilongwe 56.4 9.5 5.4 3.1 0.9 14.3 2.3 2.7 3.7 1.7 100.0 4,694 Mulanje 51.6 19.0 8.0 0.8 0.9 7.6 3.5 3.9 3.5 1.1 100.0 1,226 Other districts 58.9 13.7 6.1 1.6 0.6 10.2 1.7 2.4 3.8 0.8 100.0 13,164 Wealth quintile Lowest 41.5 21.8 9.4 0.5 0.4 15.9 2.7 3.2 4.1 0.6 100.0 6,545 Second 60.4 15.4 5.7 1.1 0.6 9.1 1.7 2.0 2.8 1.1 100.0 6,460 Middle 65.5 11.3 5.4 1.6 0.5 9.0 1.7 1.8 2.7 0.5 100.0 6,491 Fourth 63.2 10.0 4.0 1.8 1.0 11.1 1.7 2.8 3.4 1.0 100.0 6,459 Highest 58.9 8.9 4.4 3.7 1.3 11.6 2.2 3.5 4.6 0.8 100.0 6,026 Total 57.8 13.6 5.8 1.7 0.8 11.4 2.0 2.6 3.5 0.8 100.0 31,981 Characteristics of Households and Household Members | 13 2.4 EDUCATIONAL LEVEL OF HOUSEHOLD POPULATION Education is a key determinant of the lifestyle and status an individual enjoys in a society. It affects many aspects of life, including demographic and health behaviour. Studies have consistently shown that educational attainment has strong effects on reproductive behaviour, contraceptive use, fertility, infant and child mortality, morbidity, and attitudes and awareness related to family health and hygiene. In the 2004 MDHS, information on educational attainment was collected for every member of the household. Tables 2.4.1 and 2.4.2 show the percent distribution of the de facto female and male population age six and over by the highest level of education attained, according to background characteristics. There is a strong differential in educational attainment between the sexes, especially as age increases. While 30 percent of female household members in Malawi have never been to school, the proportion among males is 20 percent. The proportion of persons with no education is high at the youngest ages, is lowest between the ages of 10 and 24, and then increases with age. For example, the proportion of women who have never attended any formal schooling increases from 14 percent from age 20-24 to 73 percent among those age 65 and over. For men, the corresponding proportion is 8 percent and 44 percent, respectively. Eight percent of women and 15 percent of men have attended some secondary school. The median number of years of schooling is 1.8 years for women and 3.1 years for men. Overall, educational attainment is higher in urban areas than in rural areas. The proportion with no education in urban areas is about one-third that in rural areas. The proportion of the population age six and over that has attained any education varies across regions and districts. The Northern Region has the highest proportion with some education for both males (90 percent) and females (84 percent). For females, the proportion is lowest in the Southern Region (67 percent); for males, it is lowest in the Central Region (77 percent). Of the oversampled districts, Blantyre has the highest median years of education at 5.6 years for men, while Mzimba has the highest for women (4.0). The lowest educational attainment for both men and women is observed in Mangochi, where the median years of education is 1.1 years for men and 0 years for women. The situation in Mangochi has remained the same since 2000. 14 | Characteristics of Households and Household Members Table 2.4.1 Educational attainment of household population: women Percent distribution of the de facto female household population age six and over by highest level of education attended, according to background characteristics, Malawi 2004 Education Background characteristic No education Primary 1-4 Primary 5-8 Secondary or higher Missing Total Number Median number of years Age 6-9 43.8 55.6 0.3 0.0 0.3 100.0 3,872 0.2 10-14 9.3 68.8 20.6 1.1 0.2 100.0 4,492 2.3 15-19 7.1 24.9 48.9 19.1 0.1 100.0 2,570 5.5 20-24 14.0 26.2 36.0 23.6 0.2 100.0 3,036 5.1 25-29 25.2 27.3 31.0 16.4 0.2 100.0 2,247 3.7 30-34 36.4 26.8 27.9 8.9 0.0 100.0 1,516 2.0 35-39 38.6 22.3 32.0 6.9 0.1 100.0 1,122 2.2 40-44 41.0 24.0 30.1 4.7 0.2 100.0 970 1.5 45-49 51.4 22.5 21.5 4.6 0.0 100.0 743 0.0 50-54 49.6 27.7 15.8 5.5 1.4 100.0 998 0.0 55-59 61.7 27.2 7.5 3.0 0.6 100.0 734 0.0 60-64 67.6 25.8 5.5 0.5 0.6 100.0 536 0.0 65+ 73.3 23.1 2.9 0.5 0.1 100.0 1,189 0.0 Residence Urban 11.8 29.8 31.7 26.7 0.1 100.0 3,651 5.2 Rural 33.4 40.0 21.3 5.0 0.3 100.0 20,388 1.4 Region Northern 16.3 34.9 36.5 12.2 0.1 100.0 3,091 3.8 Central 31.4 39.5 20.6 8.2 0.3 100.0 10,086 1.6 Southern 32.8 38.4 21.1 7.4 0.3 100.0 10,862 1.5 District Blantyre 19.0 33.6 29.4 17.8 0.2 100.0 1,720 3.7 Kasungu 23.8 44.9 23.8 7.5 0.0 100.0 1,011 1.9 Machinga 42.8 37.1 15.8 3.9 0.3 100.0 892 0.6 Mangochi 49.7 32.3 13.7 4.1 0.3 100.0 1,240 0.0 Mzimba 16.6 33.1 37.6 12.6 0.2 100.0 1,550 4.0 Salima 41.7 38.1 14.7 5.4 0.1 100.0 700 0.8 Thyolo 31.9 42.9 19.9 5.2 0.1 100.0 1,234 1.5 Zomba 22.6 42.6 25.3 9.2 0.2 100.0 1,235 2.3 Lilongwe 27.9 36.9 21.8 13.1 0.3 100.0 3,599 2.2 Mulanje 31.2 42.9 20.7 5.2 0.0 100.0 1,029 1.5 Other districts 31.8 39.4 22.3 6.1 0.3 100.0 9,828 1.6 Wealth quintile Lowest 46.3 38.9 12.6 1.9 0.3 100.0 5,220 0.3 Second 38.4 41.1 17.9 2.2 0.3 100.0 4,681 0.9 Middle 31.0 42.1 23.7 2.8 0.4 100.0 4,661 1.5 Fourth 23.7 41.0 27.9 7.3 0.1 100.0 4,719 2.4 Highest 9.7 29.1 33.2 27.8 0.1 100.0 4,758 5.6 Total 30.1 38.4 22.9 8.3 0.2 100.0 24,039 1.8 Characteristics of Households and Household Members | 15 Table 2.4.2 Educational attainment of household population: men Percent distribution of the de facto male household population age six and over by highest level of education at- tended, according to background characteristics, Malawi 2004 Education Background characteristic No education Primary 1-4 Primary 5-8 Secondary or higher Missing Total Number Median number of years Age 6-9 47.9 51.3 0.3 0.0 0.5 100.0 3,868 0.1 10-14 10.3 69.2 19.4 1.0 0.1 100.0 4,204 2.2 15-19 6.4 29.3 45.5 18.6 0.1 100.0 2,826 5.2 20-24 7.7 21.1 35.5 35.5 0.2 100.0 2,408 6.8 25-29 11.1 18.8 34.0 35.9 0.2 100.0 2,271 6.8 30-34 16.4 19.0 36.4 28.1 0.1 100.0 1,651 5.8 35-39 18.8 19.8 39.8 21.2 0.4 100.0 1,101 5.8 40-44 15.9 20.6 41.8 21.3 0.3 100.0 939 5.9 45-49 20.4 18.8 41.8 18.6 0.3 100.0 656 5.1 50-54 21.4 25.8 37.0 15.0 0.8 100.0 649 4.4 55-59 26.1 26.4 32.8 12.1 2.5 100.0 712 3.4 60-64 32.9 34.6 25.8 5.6 1.2 100.0 528 1.9 65+ 43.7 36.4 15.6 3.0 1.4 100.0 996 0.8 Residence Urban 7.8 23.5 30.2 37.9 0.6 100.0 4,100 6.9 Rural 22.9 39.8 26.6 10.4 0.4 100.0 18,719 2.5 Region Northern 10.1 33.7 37.2 18.8 0.2 100.0 2,952 4.8 Central 22.7 36.8 25.3 14.6 0.6 100.0 9,758 2.7 Southern 20.6 37.8 26.2 15.1 0.3 100.0 10,109 2.9 District Blantyre 11.7 27.9 30.3 30.1 0.0 100.0 1,891 5.6 Kasungu 16.2 39.2 32.6 12.0 0.1 100.0 1,034 3.4 Machinga 28.8 38.9 22.3 9.8 0.2 100.0 808 1.9 Mangochi 36.4 38.0 16.6 8.7 0.3 100.0 1,200 1.1 Mzimba 9.4 34.8 37.2 18.5 0.1 100.0 1,471 4.7 Salima 29.8 40.7 20.9 8.1 0.5 100.0 627 1.7 Thyolo 17.6 44.1 25.9 11.8 0.4 100.0 1,103 2.7 Zomba 15.5 39.5 28.3 16.3 0.4 100.0 1,118 3.3 Lilongwe 20.4 30.2 26.3 22.2 0.9 100.0 3,634 3.8 Mulanje 16.4 44.9 27.2 11.2 0.3 100.0 847 2.7 Other districts 21.7 38.9 27.1 12.0 0.4 100.0 9,088 2.7 Wealth quintile Lowest 31.9 43.5 20.0 4.2 0.4 100.0 4,067 1.4 Second 27.9 41.4 24.4 6.0 0.2 100.0 4,484 2.0 Middle 21.5 39.5 30.2 8.3 0.5 100.0 4,497 2.7 Fourth 16.3 36.5 32.5 14.3 0.4 100.0 4,648 3.6 Highest 6.5 25.5 28.1 39.5 0.4 100.0 5,124 7.0 Total 20.2 36.9 27.2 15.3 0.4 100.0 22,819 3.1 Overall, there has been progress in education since 2000, as the proportion of people with no education has decreased, while the proportion with secondary or higher education has increased. In the 2000 MDHS, 6 percent of women and 12 percent of men reported attaining secondary or higher education; these proportions have increased to 8 percent and 15 percent, respectively. The median number of years of schooling for men has increased from 2.7 years in 2000 to 3.1 years in 2004. For women, the median is 1.4 years and 1.8 years, respectively. The improvement is shown by almost all subgroups of the population. 16 | Characteristics of Households and Household Members 2.5 SCHOOL ATTENDANCE The 2004 MDHS collected information that allows the calculation of net attendance ratios (NAR) and gross attendance ratios (GAR). 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. The GAR for primary school is the total number of primary school students of any age, expressed as the percentage of the official primary-school-age population. The GAR for secondary school is the total number of secondary school students up to an age limit of 24 years, expressed as the percentage of the official secondary- school-age population. If there are significant numbers of overage or underage students at a given level of schooling, the GAR can exceed 100 percent. Tables 2.5.1 and 2.5.2 present the NARs and GARs by urban-rural residence, region, and wealth index, by sex, for primary school and secondary school. Findings indicate that among children within the official age range for primary school, slightly more girls (84 percent) are attending school than boys (80 percent), which is a slight improvement over the 2000 MDHS findings. The GAR shows, however, that overall, more boys are attending primary school than girls (109 compared with 103). The NAR at primary school is highest for children in the Northern Region (92 percent), followed by the Central and Southern Regions (both at 81 percent). The NAR for primary school is higher in urban areas (89 percent) than in rural areas (81 percent). Both the NAR and the GAR for primary school increase directly with wealth. Secondary school attendance ratios are much lower and differ substantially by background characteristics. Overall, the net attendance ratio is 11.4, indicating that only 11 percent of secondary-school-age children are attending school at roughly the correct ages. The secondary NAR in urban areas is over four times higher than the NAR in rural areas. The same regional patterns exist for secondary school attendance ratios as for educational attainment: the Northern Region has the highest attendance ratios, with the Central and Southern regions being slightly lower. The gross attendance ratio of 30 percent for secondary school, though slightly higher than in the 2000 MDHS, indicates that a substantial proportion of secondary-school students are outside the official age range for secondary schooling. Characteristics of Households and Household Members | 17 Table 2.5.1 School attendance ratios: primary school Primary school net attendance ratios (NAR) and gross attendance ratios (GAR) for the de jure household population by level of schooling and sex, according to background characteristics, Malawi 2004 Net attendance ratio1 Gross attendance ratio2 Background characteristic Male Female Total Male Female Total Gender Parity Index3 Residence Urban 89.0 89.4 89.2 112.7 104.8 108.7 0.93 Rural 78.7 83.0 80.9 108.3 102.4 105.3 0.95 Region Northern 91.4 93.0 92.2 129.1 117.2 123.2 0.91 Central 77.6 83.4 80.6 105.1 102.3 103.7 0.97 Southern 79.2 81.7 80.5 106.6 99.0 102.8 0.93 District Blantyre 83.7 89.5 86.5 110.7 110.1 110.4 0.99 Kasungu 86.2 88.6 87.5 123.5 107.3 114.9 0.87 Machinga 78.0 79.9 79.0 106.0 94.2 99.9 0.89 Mangochi 66.7 68.7 67.7 84.7 83.0 83.9 0.98 Mzimba 92.4 93.8 93.1 128.7 115.6 122.1 0.90 Salima 77.8 79.6 78.8 100.8 93.5 97.0 0.93 Thyolo 83.9 84.7 84.3 108.6 102.8 105.7 0.95 Zomba 87.8 89.8 88.8 115.3 108.6 111.9 0.94 Lilongwe 79.7 84.0 82.0 103.0 100.1 101.5 0.97 Mulanje 83.5 82.2 82.9 108.8 104.5 106.7 0.96 Other districts 77.8 82.8 80.4 109.9 103.3 106.5 0.94 Wealth quintile Lowest 71.8 75.0 73.5 97.1 89.3 93.1 0.92 Second 73.8 79.5 76.6 101.0 97.5 99.3 0.97 Middle 80.9 84.0 82.5 113.0 104.6 108.7 0.93 Fourth 83.1 88.2 85.7 114.6 110.8 112.6 0.97 Highest 92.2 93.8 93.0 120.5 113.2 116.8 0.94 Total 80.1 83.8 82.0 108.9 102.7 105.8 0.94 1 The NAR for primary school is the percentage of the primary-school-age (6-13 years) population that is attending primary 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. 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 GAR for females to the GAR for males. 18 | Characteristics of Households and Household Members Table 2.5.2 School attendance ratios: secondary school Secondary school net attendance ratios (NAR) and gross attendance ratios (GAR) for the de jure household population by sex, according to background characteristics, Malawi 2004 Net attendance ratio1 Gross attendance ratio2 Background characteristic Male Female Total Male Female Total Gender Parity Index3 Residence Urban 30.3 32.3 31.3 71.9 64.9 68.5 0.90 Rural 6.2 8.7 7.4 25.9 17.0 21.8 0.65 Region Northern 10.2 16.2 13.1 39.9 28.8 34.6 0.72 Central 10.1 10.4 10.3 31.3 21.9 26.9 0.70 Southern 10.3 14.0 12.0 33.6 27.4 30.8 0.81 District Blantyre 15.0 24.6 19.3 46.2 48.3 47.1 1.05 Kasungu 7.1 16.8 11.4 23.2 29.8 26.1 1.29 Machinga 6.5 11.6 8.7 22.0 17.7 20.1 0.80 Mangochi 10.2 5.2 7.9 26.6 14.4 21.2 0.54 Mzimba 10.8 18.7 14.5 41.3 34.1 38.0 0.82 Salima 2.9 9.9 6.0 18.0 17.6 17.8 0.98 Thyolo 10.8 9.6 10.2 36.4 20.3 28.2 0.56 Zomba 16.1 14.7 15.5 41.8 35.4 38.9 0.85 Lilongwe 18.8 14.8 17.0 44.7 29.5 37.8 0.66 Mulanje 7.5 14.1 11.0 27.2 20.4 23.6 0.75 Other districts 6.6 9.8 8.1 29.0 20.2 24.8 0.69 Wealth quintile Lowest 2.6 4.0 3.2 12.4 7.0 10.0 0.57 Second 3.4 3.1 3.3 19.5 7.1 13.7 0.36 Middle 3.5 4.9 4.1 17.9 9.4 14.0 0.53 Fourth 6.8 11.5 9.1 34.6 25.4 30.1 0.74 Highest 30.6 32.9 31.7 74.8 62.7 69.0 0.84 Total 10.2 12.7 11.4 33.5 25.2 29.6 0.75 1 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 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 ex- ceed 100 percent. 3 The Gender Parity Index for secondary school is the ratio of the secondary school GAR for females to the GAR for males. Characteristics of Households and Household Members | 19 Repetition and Dropout By asking about the grade or standard that children were attending during the previous school year, it is possible to calculate dropout rates and repetition rates for primary school. Table 2.6 indicates that repetition rates are high in Standard 1 (45 percent), which may be related to the teachers’ decision to ensure a more uniform preparedness before promoting children to Standard 2. Repetition rates decline at higher standards but increase at Standard 8, due to failed attempts at getting into a secondary school. While the repetition rates at Standard 1 are about the same as those in 2000, the rates at Standard 8 have decreased from 39 to 29 percent. Table 2.6 Grade repetition and dropout rates Repetition and dropout rates for the de jure household population age 5-24 years by school grade, according to back- ground characteristics, Malawi 2004 Standard Background characteristic 1 2 3 4 5 6 7 8 REPETITION RATE Sex Male 45.3 25.4 29.5 23.3 19.8 11.8 13.3 30.8 Female 44.1 27.7 26.2 20.0 18.9 18.6 14.8 25.2 Residence Urban 33.5 23.4 22.7 12.2 19.0 17.0 9.8 13.3 Rural 46.1 27.2 28.7 23.6 19.4 14.4 15.1 34.6 Region Northern 30.3 15.3 16.1 13.4 11.5 8.3 10.0 45.7 Central 47.3 28.9 31.3 24.3 19.6 19.3 15.9 29.5 Southern 45.7 27.7 28.3 22.7 22.5 14.5 14.3 20.3 Wealth quintile Lowest 46.4 30.1 29.2 24.8 19.0 13.7 20.5 30.9 Second 46.3 25.6 33.4 20.8 24.7 16.4 14.4 31.9 Middle 47.5 26.7 26.4 24.5 18.9 13.0 16.3 48.1 Fourth 44.0 28.5 29.0 24.3 18.0 14.8 9.5 32.5 Highest 37.2 21.9 22.4 15.3 18.5 16.0 13.1 16.5 Total 44.7 26.6 27.8 21.7 19.4 15.0 14.0 28.6 DROPOUT RATE Sex Male 2.3 1.8 3.4 3.1 4.9 2.9 4.4 10.7 Female 1.9 2.3 2.4 3.5 5.4 4.3 8.6 8.6 Residence Urban 2.3 1.8 1.5 0.9 1.8 1.1 2.1 3.8 Rural 2.0 2.1 3.1 3.8 6.1 4.3 7.5 12.2 Region Northern 0.3 1.1 1.1 0.9 4.6 1.0 6.4 7.1 Central 1.4 2.0 3.2 3.3 5.9 5.3 8.1 10.9 Southern 3.1 2.4 3.3 4.3 4.6 3.3 4.9 10.2 Wealth quintile Lowest 3.5 3.7 5.5 4.2 7.0 7.3 7.9 21.4 Second 2.5 1.8 3.5 5.7 10.2 5.6 15.7 21.5 Middle 2.0 1.8 4.0 4.3 4.9 4.8 5.1 12.8 Fourth 1.4 2.8 1.9 2.2 4.7 2.6 8.4 11.1 Highest 0.3 0.3 0.8 1.3 2.7 1.3 2.1 2.1 Total 2.1 2.1 2.9 3.3 5.1 3.6 6.3 9.9 Note: 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. The dropout rate is the percentage of students in a given grade in the previous school year who are not attending school in the current school year. 20 | Characteristics of Households and Household Members The second panel of Table 2.6 shows the expected pattern of increasing dropout rates with increasing years in school. Only 2 percent of children drop out of school after attending Standard 1 compared with a dropout rate of 10 percent at Standard 8. It is notable that the dropout rate and the repetition rate at Standard 8 is higher for boys than for girls. Rural children are more likely than urban children to drop out at all grades except Standard 1. Children in the Northern Region are less likely to stop their education than children in the Central or Southern Regions (7 percent compared with 10-11 percent at Standard 8). 2.6 CHILD LABOUR The 2004 MDHS survey collected information on the work activities of children age 5-14 in the week prior to the survey. Working children have less opportunity to attend school and are more susceptible than adults to unfair working environments, including low or no pay, poor working conditions, and physical abuse. Despite policies and laws designed to curtail exploitative child labour, the practice continues in many settings. The 2004 MDHS asked a series of questions about whether children age 5-14 were doing any kind of work for pay, whether children regularly did unpaid family work on the farm or in a family business, and whether and to what extent (number of hours) children helped with household chores. Table 2.7 shows that overall, 37 percent of children age 5-14 are currently engaged in some type of work. Eight percent of children age 5-14 are doing work for nonrelatives, about half of these without pay. Seven in ten children did daily household chores during the past week, most of them working for less than four hours per day. One in three children are engaged in family business or working on the family farm. Older children are much more likely to be working than younger children. Although girls are more likely to be involved in longer hours of domestic work per day than boys, there is little difference in the overall proportions of girls and boys who work (35 and 39 percent, respectively). Urban children (17 percent) are much less likely to be working than rural children (40 percent). Children in the Northern Region are more likely than those in the Central Region and Southern Region to be working without pay for nonrelatives (5 percent compared with 3 percent and 2 percent, respectively). Children in the Northern Region are less likely to be employed on the family farm or in the family business than children in the Southern and Central regions (29 percent compared with 33 percent and 34 percent, respectively). While 41 percent of children in the lowest quintile work, the corresponding proportion among children in the highest quintile is only 22 percent. Among the oversampled districts, almost half of children age 5-14 in Kasungu are working, compared to 30 percent in Blantyre. Characteristics of Households and Household Members | 21 Table 2.7 Child labour Percentage of children age 5-14 years who are currently working, by type of employment and selected background characteristics, Malawi 2004 Domestic work for: Work for nonrelatives Background characteristic Paid Unpaid Currently doing work on family farm or family business Less than 4 hours per day 4 hours or more per day Currently working1 Number of children Age 5-9 2.0 2.3 16.1 56.3 0.8 19.3 9,202 10-14 8.0 3.7 50.5 80.0 3.8 55.9 8,696 Sex Male 5.4 2.3 35.4 62.0 1.6 39.0 8,762 Female 4.5 3.6 30.3 73.4 2.9 35.2 9,137 Residence Urban 1.7 1.6 13.7 71.0 1.9 17.0 2,543 Rural 5.5 3.2 36.0 67.3 2.3 40.4 15,356 Region Northern 3.9 5.4 29.4 74.9 3.3 35.2 2,333 Central 4.7 3.0 33.7 65.9 2.2 37.8 7,711 Southern 5.5 2.3 32.9 67.6 2.1 36.9 7,855 District Blantyre 2.8 3.6 24.4 65.3 2.7 30.4 1,250 Kasungu 6.1 4.0 45.3 68.4 2.5 49.1 807 Machinga 8.4 3.5 38.9 65.1 2.8 43.1 673 Mangochi 6.4 1.5 29.9 58.1 2.2 33.9 1,014 Mzimba 4.6 6.7 39.2 73.7 3.6 44.5 1,146 Salima 5.3 2.7 33.2 68.1 1.9 36.8 541 Thyolo 6.3 3.1 33.2 70.0 2.1 37.7 917 Zomba 5.9 0.9 41.8 76.7 3.4 44.8 849 Lilongwe 2.9 1.8 30.3 65.8 2.4 33.3 2,710 Mulanje 5.9 2.3 30.6 69.2 0.9 34.3 689 Other districts 5.0 3.1 31.7 68.2 1.9 36.3 7,302 Wealth quintile Lowest 7.1 3.0 36.4 65.0 2.0 40.5 3,780 Second 5.8 3.1 38.8 67.6 2.2 43.0 3,544 Middle 5.5 3.3 39.1 67.4 2.2 43.6 3,464 Fourth 4.2 3.2 31.6 67.7 3.0 36.3 3,661 Highest 1.9 2.2 17.7 71.8 2.0 21.5 3,451 Total 4.9 3.0 32.8 67.8 2.3 37.1 17,899 1Working means doing paid or unpaid work or working on a family farm or for a family business. 2.7 HOUSING CHARACTERISTICS 2004 MDHS respondents were asked about their housing environment, including access to electricity, source of drinking water, time to water source, type of toilet facilities, house construction materials, and possession of various durable goods. This information is summarised in Table 2.8. Seven percent of households in Malawi have electricity. Electricity is much more common in urban areas (30 percent) than in rural areas (2 percent). 22 | Characteristics of Households and Household Members Table 2.8 Household characteristics Percent distribution of households by household characteristics, according to residence, Malawi 2004 Residence Household characteristic Urban Rural Total Electricity Yes 30.2 2.2 6.9 No 69.6 97.6 93.0 Missing 0.2 0.1 0.1 Total 100.0 100.0 100.0 Source of drinking water Piped into dwelling 14.1 0.6 2.9 Piped into yard/plot 15.1 1.0 3.4 Public tap 45.2 7.4 13.7 Open well in yard/plot 1.9 2.5 2.4 Open public well 5.4 26.1 22.6 Protected well in yard/plot 2.0 5.5 4.9 Protected public well 14.7 43.4 38.6 Spring 0.1 3.2 2.6 River, stream 1.3 9.4 8.0 Pond, lake 0.0 0.5 0.4 Dam 0.0 0.3 0.2 Tanker truck 0.0 0.1 0.1 Total 100.0 100.0 100.0 Time to water source Percentage <15 minutes 67.4 36.7 41.8 Median time to source 4.9 19.4 19.0 Sanitation facility Flush toilet 16.2 0.8 3.4 Traditional pit toilet 76.1 80.0 79.4 VIP latrine 2.3 0.9 1.1 No facility/bush, field 5.2 18.2 16.1 Missing 0.2 0.0 0.1 Total 100.0 100.0 100.0 Flooring material Earth, sand 35.5 87.1 78.5 Dung 0.6 0.7 0.7 Cement 62.3 12.0 20.3 Carpet 0.9 0.1 0.2 Missing 0.2 0.0 0.1 Total 100.0 100.0 100.0 Cooking fuel Electricity 10.6 0.3 2.0 Kerosene 0.2 0.0 0.1 Charcoal 41.4 2.0 8.5 Firewood, straw 47.1 97.5 89.2 Dung 0.0 0.1 0.1 Total 100.0 100.0 100.0 Number of households 2,262 11,402 13,664 Characteristics of Households and Household Members | 23 A household’s source of drinking water is important because potentially fatal diseases including typhoid, cholera, and dysentery are prevalent in unprotected sources. Piped water, water drawn from protected wells, and deep boreholes are expected to be relatively free of these diseases. Unprotected wells and surface water (rivers, streams, ponds, and lakes), are more likely to carry disease-causing agents. Table 2.8 shows that overall, 64 percent of Malawian households have access to clean water, 20 percent from piped water and 44 percent from protected wells. As expected, a far greater proportion of urban households have access to piped water than rural households (74 compared to 9 percent). In urban areas, 67 percent of the households have access to water within 15 minutes, compared with 37 percent of rural households. Modern sanitation facilities are not yet available to large proportions of Malawian households. The use of traditional pit latrines is still common in both urban and rural areas, accounting for 79 percent of all households. Overall, 16 percent of the households in Malawi have no toilet facilities. This problem is more common in rural areas, where 18 percent of the households have no toilet facilities, compared with 5 percent of households in urban areas. The type of material used for flooring is an indicator of the economic standing of the household as well as an indicator of potential exposure to disease-causing agents. Overall, 79 percent of all households in Malawi live in residences with floors made of earth, sand, or dung, while 21 percent live in houses with finished floors like those made of cement or wooden panels. Earth flooring is almost universal in rural areas (87 percent). The type of cooking fuel used by a household reflects both economic status as well as exposure to varying types of pollutants. Most households (89 percent) use firewood or straw. Charcoal is also a popular fuel in urban areas. Eleven percent of urban households use electricity as their cooking fuel, whereas almost no rural residents do. Respondents were also asked about their household’s ownership of particular durable goods. In addition to providing an indicator of economic status, ownership of these goods provides measures of other aspects of life. Ownership of a radio or television is a measure of access to mass media; ownership of a refrigerator indicates a capacity for more hygienic food storage; and ownership of a bicycle, motorcycle, or car reflects means of transport, which can be important for seeking emergency medical care or taking advantage of employment opportunities. Ownership of a telephone opens up communication with other users. Information on ownership of these items is presented in Table 2.9. Four in ten households own a paraffin lamp. This item is slightly more common in urban households than in rural households. Nationally, 62 percent of households own a radio and only 5 percent of households own a television. Five percent of households in Malawi own a cell phone, and only 2 percent have a landline telephone. More than one in five households own a bed with a mattress (21 percent) or table and chairs (29 percent), while ownership of a sofa set (11 percent) or a refrigerator (3 percent) is uncommon. Bicycles are the most common type of vehicle owned by households; 40 percent of households have a bicycle. Ownership of motorised transport is rare: only 2 percent of households have cars, and fewer households (1 percent) have motorcycles. As expected, urban households are more likely than rural households to own each of the items listed, with the exception of the bicycle. Overall, one in four rural households own none of the listed items, while the same is true for only one in ten urban households. 24 | Characteristics of Households and Household Members Table 2.9 Household durable goods Percentage of households possessing various durable consumer goods, by resi- dence, Malawi 2004 Residence Durable consumer goods Urban Rural Total Household goods Paraffin lamp 47.1 36.5 38.2 Radio 79.2 58.5 61.9 Television 21.1 2.2 5.3 Cell phone 20.8 1.5 4.7 Landline telephone 8.3 0.5 1.8 Bed with mattress 54.5 14.7 21.3 Sofa set 35.5 5.7 10.6 Table and chairs 53.8 24.5 29.3 Refrigerator 14.7 0.7 3.0 Means of transport Bicycle 30.9 41.8 40.0 Motorcycle 1.9 0.8 1.0 Car/truck 8.1 0.8 2.0 None of the above 9.6 25.1 22.5 Number of households 2,262 11,402 13,664 Characteristics of Respondents and Women’s Status | 25 CHARACTERISTICS OF RESPONDENTS AND WOMEN’S STATUS 3 Mylen Mahowe This chapter provides a demographic and socioeconomic profile of the 2004 Malawi DHS sample of individual female and male respondents. It begins by describing basic background characteristics of men and women, including age at the time of the survey, marital status, educational level, and residential characteristics. It also provides detailed information on education, literacy, and exposure to mass media among men and women, data on employment and work status of women, decisionmaking in the household, and attitudes on women’s position in relation to others in the household. 3.1 CHARACTERISTICS OF SURVEY RESPONDENTS Background characteristics of women age 15-49 and men age 15-54 interviewed in the 2004 MDHS survey are presented in Table 3.1. As expected, the percentage of women and men is highest in the younger age groups and the proportion of respondents in each age group declines with age. Sixty-seven percent of women and 63 percent of men are currently married; an additional 4 percent of women and 1 percent of men reported being in an informal marriage or living together. For purposes of the 2004 MDHS survey and in presentation of findings throughout later chapters of this report, informal marriages are grouped together with formalised marriages to form the group “currently married” or “in union.” One in three men had never been married, compared with only 17 percent of women, supporting the fact that men get married later in life than women. Women were more likely than men (12 and 2 percent, respectively) to be divorced, separated, or widowed. As expected, most of the interviewed women and men reside in rural areas (82 percent of women and 80 percent of men). The largest proportion of female and male respondents live in the Southern Region (46 and 45 percent, respectively), while 41 percent of women and 42 percent of men live in the Central Region. Only 13 percent of both women and men live in the Northern Region. Table 3.1 also shows the distribution of men and women by district, including districts that were oversampled in the survey to allow the presentation of estimates of certain indicators at the district level. Notable are the large differences between the weighted and unweighted numbers of men and women in some districts. The unweighted number represents the number of respondents who were actually interviewed in the 2004 MDHS survey, whereas the weighted number represents that district’s proportional representation in the population. For instance, Salima District has only 3 percent of the population of women age 15-49 (as represented by 303 weighted cases), but 703 women were actually interviewed (or 6 percent of the total number of interviewed women). 26 | Characteristics of Respondents and Women’s Status Table 3.1. Background characteristics of respondents Percent distribution of women and men by background characteristics, Malawi 2004 Women Men Background characteristic Weighted percent Weighted number Unweighted number Weighted percent Weighted number Unweighted number Age 15-19 20.4 2,392 2,407 19.9 650 650 20-24 24.5 2,870 2,824 18.0 587 583 25-29 18.4 2,157 2,136 19.4 634 617 30-34 12.6 1,478 1,492 14.9 485 474 35-39 9.5 1,117 1,129 9.0 294 287 40-44 8.0 935 940 8.6 282 293 45-49 6.4 749 770 5.6 182 181 50-54 na 0 0 19.9 650 650 Marital status Never married 16.8 1,970 1,902 33.2 1,084 1,039 Married 66.8 7,810 7,831 62.9 2,050 2,078 Living together 4.3 503 554 0.9 29 36 Divorced/separated 8.4 979 991 2.5 81 93 Widowed 3.7 437 420 0.5 17 15 Residence Urban 17.8 2,076 1,640 20.5 669 507 Rural 82.2 9,621 10,058 79.5 2,593 2,754 Region Northern 13.3 1,552 1,597 13.0 423 456 Central 40.5 4,734 4,199 42.0 1,370 1,261 Southern 46.3 5,412 5,902 45.0 1,468 1,544 District Blantyre 7.8 914 703 9.7 316 208 Kasungu 4.2 497 897 4.8 156 313 Machinga 3.7 427 772 3.5 114 198 Mangochi 5.1 599 774 4.6 150 190 Mzimba 6.7 778 953 6.5 212 274 Salima 2.6 303 703 2.4 78 182 Thyolo 5.3 618 820 5.2 169 211 Zomba 5.4 637 806 4.9 159 209 Lilongwe 14.6 1,705 710 16.6 542 228 Mulanje 4.4 512 777 3.5 114 178 Other districts 40.2 4,708 3,783 38.3 1,250 1,070 Education No education 23.4 2,734 2,823 11.7 383 383 Primary 1-4 25.6 2,998 3,057 24.5 798 830 Primary 5-8 35.5 4,154 4,132 37.4 1,220 1,231 Secondary+ 15.5 1,811 1,685 26.3 859 814 Religion Catholic 23.1 2,698 2,575 21.2 690 683 Church of Central Africa Presbyterian (CCAP) 18.6 2,170 2,065 18.9 616 594 Anglican 2.5 292 252 2.3 76 68 Seventh Day Adventist/Baptist 6.3 731 755 6.5 213 186 Other Christian 36.4 4,257 4,103 36.2 1,179 1,189 Muslim 12.0 1,404 1,816 11.4 372 455 No religion 0.9 100 84 3.0 99 75 Other 0.3 34 35 0.4 13 10 Ethnic group Chewa 33.9 3,967 3,665 32.7 1,068 1,006 Tumbuka 9.7 1,136 1,205 9.6 314 331 Lomwe 16.9 1,976 2,211 17.1 559 638 Tonga 2.2 253 255 2.1 68 71 Yao 12.8 1,496 1,819 13.1 426 469 Sena 4.4 512 383 4.6 151 114 Nkonde 1.1 124 98 1.5 49 42 Ngoni 11.7 1,367 1,155 11.9 388 332 Other 7.3 859 897 7.3 238 258 Total 100.0 11,698 11,698 100.0 3,261 3,261 Note: Education categories refer to the highest level of education attended, whether or not that level was completed. na = Not applicable Characteristics of Respondents and Women’s Status | 27 Table 3.1 further illustrates the distribution of men and women by religion and ethnic group, showing that most of the interviewed women and men are Catholics (23 percent of women and 21 percent of men). Only 1 percent of women and 3 percent of men report having no religion. The Chewa are the largest ethnic group, making up one-third of male and female respondents; the smallest ethnic group is the Nkonde, making up only 1 percent of women and 2 percent of men. 3.2 EDUCATIONAL ATTAINMENT Tables 3.2.1 and 3.2.2 show the percent distribution of respondents by the highest level of schooling attended according to their age, place of residence, region, and district. Young women and men are more likely to have attended school than the older generation. The distribution of respondents who have never attended school rises with increasing age. For example, 6 percent of women and 3 percent of men age 15-19 have no formal education, compared with 50 percent of women and 21 percent of men age 45-49. Similarly, 24 percent of women age 20-24 attended secondary school or higher, compared with only 5 percent of women age 45-49. For male respondents, the corresponding proportions for ages 20-24 and 45-49 are 38 percent and 15 percent, respectively. The 2004 MDHS data indicate that educational opportunities vary among the respondents according to their areas of residence. Urban women and men are more likely to go to school than their rural counterparts. Only 8 percent of urban women and 5 percent of urban men have not attended school, compared with 27 percent and 13 percent in rural areas, respectively. The median number of years of education shows a similar differential, with urban women having a median of 6.9 years of schooling and rural women a median of 3.4 years. Overall, respondents in the Northern Region are better educated than those in other regions. For example, while 9 percent of women in the Northern Region have no formal education, the proportion in the Central Region is 25 percent and in the Southern Region it is 27 percent. While 22 percent of women in the Northern Region have secondary or higher education, the proportions in the Central Region and Southern Region are 16 percent or lower. Tables 3.2.1 and 3.2.2 show that wealth status has a positive relationship with a person’s education. Women and men in higher wealth quintiles are better educated than those with less education. For example, the median years of schooling for women in the highest quintile is 7.6 years compared with 1.7 years for women in the lowest quintile. Tables 3.2.1 and 3.2.2 also show the percent distribution of respondents by highest level of schooling and district. Among the oversampled districts, the proportion of women who have no formal education is lowest in Mzimba (8 percent) and highest in Mangochi (44 percent). Secondary education (or higher) is most common for men and women in Blantyre (43 percent and 28 percent, respectively). Mangochi has the lowest education for both women and men. 28 | Characteristics of Respondents and Women’s Status Table 3.2.1 Educational attainment by background characteristics: women Percent distribution of women by highest level of schooling attended, and median number of years of schooling, according to background characteristics, Malawi, 2004 Education Background characteristic No education Primary 1-4 Primary 5-8 Secondary or higher Total Number of respondents Median years of schooling Age 15-19 5.5 24.2 50.0 20.2 100.0 2,392 5.6 20-24 12.7 26.9 36.5 23.9 100.0 2,870 5.2 25-29 24.3 27.0 31.8 16.9 100.0 2,157 3.9 30-34 36.6 26.5 28.3 8.5 100.0 1,478 2.1 35-39 38.3 22.8 32.5 6.4 100.0 1,117 2.2 40-44 39.4 25.8 30.2 4.6 100.0 935 1.7 45-49 50.0 23.6 21.7 4.7 100.0 749 0.0 Residence Urban 8.2 14.2 37.2 40.2 100.0 2,076 6.9 Rural 26.6 28.1 35.1 10.1 100.0 9,621 3.4 Region Northern 8.7 13.7 55.5 22.1 100.0 1,552 6.3 Central 24.6 27.3 32.3 15.8 100.0 4,734 3.8 Southern 26.5 27.6 32.6 13.3 100.0 5,412 3.5 District Blantyre 12.9 20.5 38.3 28.3 100.0 914 6.0 Kasungu 20.3 29.1 36.7 13.9 100.0 497 4.1 Machinga 38.6 26.8 26.2 8.3 100.0 427 2.1 Mangochi 43.6 24.6 23.7 8.0 100.0 599 1.3 Mzimba 8.2 12.5 56.7 22.6 100.0 778 6.4 Salima 34.0 30.3 24.3 11.3 100.0 303 2.4 Thyolo 28.3 32.4 30.0 9.3 100.0 618 2.8 Zomba 15.3 30.0 37.8 17.0 100.0 637 4.4 Lilongwe 21.5 23.1 31.6 23.7 100.0 1,705 4.8 Mulanje 22.2 35.7 31.7 10.4 100.0 512 3.1 Other districts 24.8 26.5 36.7 12.0 100.0 4,708 3.8 Wealth quintile Lowest 37.5 33.3 24.9 4.4 100.0 2,037 1.7 Second 33.4 32.4 29.6 4.6 100.0 2,277 2.4 Middle 26.6 30.4 38.0 5.1 100.0 2,383 3.3 Fourth 16.9 24.9 44.5 13.7 100.0 2,361 4.8 Highest 6.7 10.3 38.6 44.4 100.0 2,639 7.6 Total 23.4 25.6 35.5 15.5 100.0 11,698 4.1 Characteristics of Respondents and Women’s Status | 29 Table 3.2.2 Educational attainment by background characteristics: men Percent distribution of men by highest level of schooling attended, and median number of years of schooling, accord- ing to background characteristics, Malawi 2004 Education Background characteristic No education Primary 1-4 Primary 5-8 Secondary or higher Total Number of respondents Median years of schooling Age 15-19 3.2 28.4 47.6 20.7 100.0 650 5.5 20-24 7.4 22.9 31.3 38.4 100.0 587 6.4 25-29 10.9 22.5 30.9 35.8 100.0 634 6.3 30-34 14.6 22.5 34.1 28.7 100.0 485 5.7 35-39 20.9 21.2 41.0 17.0 100.0 294 5.3 40-44 16.3 25.1 43.4 15.1 100.0 282 5.3 45-49 21.1 23.3 40.7 14.9 100.0 182 4.5 50-54 22.4 35.0 33.0 9.0 100.0 148 3.3 Residence Urban 5.2 12.2 31.7 50.9 100.0 669 7.3 Rural 13.4 27.6 38.9 20.0 100.0 2,593 5.1 Region Northern 3.1 14.2 53.1 29.6 100.0 423 6.8 Central 13.8 26.4 35.3 24.5 100.0 1,370 5.2 Southern 12.4 25.6 34.8 27.1 100.0 1,468 5.6 District Blantyre 5.0 10.0 41.7 43.2 100.0 316 7.3 Kasungu 10.3 21.6 49.7 18.3 100.0 156 5.3 Machinga 18.0 30.0 29.7 22.4 100.0 114 4.2 Mangochi 20.2 31.3 24.7 23.8 100.0 150 3.9 Mzimba 3.0 15.2 51.7 30.1 100.0 212 6.7 Salima 10.2 38.8 33.1 17.9 100.0 78 4.1 Thyolo 12.5 32.8 31.2 23.0 100.0 169 4.6 Zomba 14.2 25.8 33.8 26.2 100.0 159 4.9 Lilongwe 13.1 23.2 31.1 32.5 100.0 542 5.8 Mulanje 7.3 28.0 42.7 22.0 100.0 114 5.6 Other districts 13.0 26.8 38.4 21.8 100.0 1,250 5.2 Wealth quintile Lowest 18.6 39.2 32.3 10.0 100.0 412 3.3 Second 16.9 35.6 34.0 13.3 100.0 640 3.8 Middle 16.6 26.1 41.1 16.1 100.0 699 4.8 Fourth 7.7 23.0 48.9 20.4 100.0 709 5.9 Highest 3.5 7.9 29.3 59.3 100.0 802 7.6 Total 11.7 24.5 37.4 26.3 100.0 3,261 5.6 3.3 LITERACY The ability to read and write is an important personal asset enabling women and men to have increased opportunities in life. In the 2004 MDHS survey, persons were defined as literate based on the UNICEF definition: persons who are able to read a complete sentence or part of a sentence. Knowing the distribution of the literate population can help programme planners design effective family planning and health messages. Tables 3.3.1 and 3.3.2 show the level of literacy for women and men by background characteristics. There has been a marked increase in the literacy rate over time, especially for women. While 49 percent of women age 15-49 were literate in 2000, this rate has increased to 62 percent in 2004. For men, the increase is less substantial: 72 percent in 2000 compared with 79 percent in 2004. 30 | Characteristics of Respondents and Women’s Status Literacy is much higher among younger women than older women. For instance, only 37 percent of women age 45-49 are literate compared with 78 percent of women age 15-19. The level of literacy is higher among men (79 percent) than women (62 percent). Urban respondents have a higher level of literacy than rural respondents (84 percent and 58 percent for women and 92 percent and 76 percent for men). As indicated in the previous section, respondents in the Northern Region have the highest level of education and thus the highest literacy rate. Literacy rates rise with increasing wealth quintile; variations are more pronounced for females than for males. Table 3.3.1 Literacy: women Percent distribution of women by level of schooling attended and by level of literacy, and percent literate, according to background characteristics, Malawi 2004 No schooling or primary school Background characteristic Secondary school or higher Can read a whole sentence Can read part of a sentence Cannot read at all Missing Total Number of women Percent literate1 Age 15-19 20.2 49.4 8.0 21.9 0.4 100.0 2,392 77.6 20-24 23.9 37.9 9.2 28.8 0.1 100.0 2,870 71.1 25-29 16.9 36.9 9.2 36.8 0.1 100.0 2,157 63.0 30-34 8.5 33.5 7.8 50.2 0.0 100.0 1,478 49.8 35-39 6.4 36.5 8.6 48.5 0.0 100.0 1,117 51.5 40-44 4.6 34.0 9.8 51.4 0.2 100.0 935 48.4 45-49 4.7 25.9 6.4 63.0 0.1 100.0 749 36.9 Residence Urban 40.2 33.6 10.2 15.8 0.0 100.0 2,076 84.0 Rural 10.1 39.3 8.3 42.1 0.2 100.0 9,621 57.7 Region Northern 22.1 45.3 10.8 21.6 0.1 100.0 1,552 78.2 Central 15.8 36.5 8.5 39.0 0.1 100.0 4,734 60.9 Southern 13.3 37.8 8.0 40.6 0.2 100.0 5,412 59.1 Wealth quintile Lowest 4.4 32.0 7.4 56.1 0.1 100.0 2,037 43.8 Second 4.6 34.8 8.8 51.6 0.2 100.0 2,277 48.2 Middle 5.1 41.9 10.3 42.5 0.1 100.0 2,383 57.4 Fourth 13.7 45.6 9.5 30.9 0.2 100.0 2,361 68.9 Highest 44.4 36.3 6.9 12.1 0.2 100.0 2,639 87.6 Total 15.5 38.3 8.6 37.4 0.2 100.0 11,698 62.4 1 Refers to women who attended secondary school or higher and women who can read a whole sentence or part of a sentence. Characteristics of Respondents and Women’s Status | 31 Table 3.3.2 Literacy: men Percent distribution of men by level of schooling attended and by level of literacy, and percent literate, according to background characteristics, Malawi 2004 No schooling or primary school Background characteristic Secondary school or higher Can read a whole sentence Can read part of a sentence Cannot read at all Missing Total Number of men Percent literate1 Age 15-19 20.7 53.0 7.0 18.9 0.3 100.0 650 80.7 20-24 38.4 39.4 5.1 17.1 0.0 100.0 587 82.9 25-29 35.8 39.8 4.2 19.4 0.9 100.0 634 79.8 30-34 28.7 45.1 3.9 22.3 0.0 100.0 485 77.7 35-39 17.0 55.6 4.2 22.6 0.7 100.0 294 76.7 40-44 15.1 59.8 5.9 18.8 0.4 100.0 282 80.8 45-49 14.9 53.4 6.4 25.3 0.0 100.0 182 74.7 50-54 9.0 56.5 4.9 29.7 0.0 100.0 148 70.3 Residence Urban 50.9 37.1 4.1 7.3 0.7 100.0 669 92.1 Rural 20.0 50.6 5.5 23.7 0.2 100.0 2,593 76.0 Region Northern 29.6 46.0 8.6 15.7 0.0 100.0 423 84.3 Central 24.5 50.3 3.3 21.7 0.3 100.0 1,370 78.1 Southern 27.1 46.0 5.9 20.5 0.5 100.0 1,468 79.1 Wealth quintile Lowest 10.0 47.7 7.2 34.9 0.2 100.0 412 64.9 Second 13.3 52.3 4.8 29.4 0.3 100.0 640 70.3 Middle 16.1 50.7 4.9 28.2 0.1 100.0 699 71.7 Fourth 20.4 58.8 7.3 13.0 0.4 100.0 709 86.6 Highest 59.3 32.0 2.8 5.4 0.5 100.0 802 94.1 Total 26.3 47.8 5.2 20.4 0.3 100.0 3,261 79.3 1 Refers to men who attended secondary school or higher and women who can read a whole sentence or part of a sentence. 3.4 ACCESS TO MASS MEDIA The 2004 MDHS survey collected information on the exposure of respondents to common print and electronic media. Respondents were asked how often they read a newspaper, listen to the radio, or watch television. This information helps family planning and health programme planners reach targeted groups. More than half of women and men listen to the radio at least once a week; the proportion who read newspapers or watch television is much smaller. Data in Tables 3.4.1 and 3.4.2 show that 67 percent of women and 85 percent of men listen to the radio at least once a week. Only 9 percent of women and 19 percent of men watch television at least once a week. Twenty-six percent of men and 13 percent of women read a newspaper at least once a week. In general, men are more likely than women to be exposed to mass media; while 12 percent of men have access to all three types of media, only 5 percent of women do. Furthermore, 13 percent of men have no access to any type of mass media compared to 31 percent of women. Urban residents and younger respondents have more access to all three types of media than other respondents. In the Northern Region, where the literacy rate is high, women and men are more likely to read a newspaper weekly than in the Central or Southern regions. Further, exposure to 32 | Characteristics of Respondents and Women’s Status all three media is highest in the Northern Region (6 percent of women and 14 percent of men) and lowest in the Southern Region (4 percent of women and 11 percent of men). Table 3.4.1 Exposure to mass media: women Percentage of women who usually read a newspaper at least once a week, watch television at least once a week, and listen to the radio at least once a week, by background characteristics, Malawi 2004 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 No media Number of women Age 15-19 17.2 11.6 67.0 6.2 29.8 2,392 20-24 15.5 8.3 68.0 5.0 29.0 2,870 25-29 13.0 9.3 68.3 5.5 30.0 2,157 30-34 8.6 6.5 66.3 2.7 32.6 1,478 35-39 9.3 8.6 64.3 3.8 34.7 1,117 40-44 8.6 6.8 64.4 2.9 35.0 935 45-49 7.9 6.8 60.0 3.0 38.3 749 Residence Urban 35.5 31.3 79.3 19.7 16.8 2,076 Rural 8.0 3.9 63.7 1.4 34.6 9,621 Region Northern 18.9 10.3 66.0 6.1 30.7 1,552 Central 13.3 9.1 66.7 4.9 31.2 4,734 Southern 10.8 7.9 66.4 3.9 31.8 5,412 District Blantyre 22.7 19.8 76.0 11.8 21.2 914 Kasungu 11.5 4.9 71.2 1.7 27.3 497 Machinga 7.0 3.8 64.2 0.6 34.4 427 Mangochi 7.7 7.7 61.6 2.0 36.5 599 Mzimba 19.1 11.6 68.1 7.0 29.1 778 Salima 10.3 4.7 63.0 2.3 34.9 303 Thyolo 11.4 5.6 60.0 2.4 38.6 618 Zomba 12.9 10.4 75.9 5.3 21.9 637 Lilongwe 21.8 18.6 66.7 11.3 30.7 1,705 Mulanje 6.7 4.8 60.4 1.4 37.8 512 Other districts 9.1 4.4 65.1 2.2 33.0 4,708 Education No education 0.4 2.1 53.5 0.0 46.0 2,734 Primary 1-4 3.6 2.6 61.5 0.1 37.0 2,998 Primary 5-8 13.6 7.4 70.8 2.6 26.6 4,154 Secondary+ 45.5 32.0 84.2 23.6 11.3 1,811 Wealth quintile Lowest 4.1 1.1 27.4 0.1 70.8 2,037 Second 4.8 1.5 61.9 0.3 36.4 2,277 Middle 5.4 1.3 70.7 0.2 27.8 2,383 Fourth 9.9 3.8 77.7 1.0 19.9 2,361 Highest 36.1 32.1 86.8 19.1 10.3 2,639 Total 12.9 8.7 66.5 4.6 31.4 11,698 Characteristics of Respondents and Women’s Status | 33 Table 3.4.2 Exposure to mass media: men Percentage of men who usually read a newspaper at least once a week, watch television at least once a week, and listen to the radio at least once a week, by background characteristics, Malawi 2004 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 No media Number of men Age 15-19 26.5 23.8 81.5 11.6 16.2 650 20-24 32.6 23.0 85.4 15.3 12.3 587 25-29 26.0 20.4 88.2 13.5 9.8 634 30-34 28.1 22.4 87.9 14.4 10.0 485 35-39 20.8 12.9 85.7 7.6 13.5 294 40-44 21.5 11.4 83.7 6.9 14.8 282 45-49 21.2 14.1 83.4 9.0 15.3 182 50-54 13.0 3.1 81.0 0.7 18.0 148 Residence Urban 51.3 44.5 92.9 35.0 6.0 669 Rural 19.3 12.7 83.1 5.6 14.8 2,593 Region Northern 40.0 21.6 82.2 13.9 13.5 423 Central 21.9 19.8 83.4 11.6 14.9 1,370 Southern 25.6 18.0 87.5 11.1 11.1 1,468 District Blantyre 36.5 20.8 92.7 16.4 7.3 316 Kasungu 26.3 9.0 75.8 4.3 19.5 156 Machinga 47.9 33.0 92.9 25.9 6.6 114 Mangochi 20.2 16.8 84.8 8.2 13.5 150 Mzimba 53.6 25.3 83.3 18.9 10.4 212 Salima 16.2 6.7 88.3 4.5 11.1 78 Thyolo 20.9 8.4 93.3 6.4 6.3 169 Zomba 18.6 23.2 80.9 10.6 16.4 159 Lilongwe 30.4 34.8 87.0 22.7 12.1 542 Mulanje 28.6 13.4 83.5 6.6 14.1 114 Other districts 17.1 13.7 82.5 6.2 15.5 1,250 Education No education 3.6 5.2 77.5 0.0 21.2 383 Primary 1-4 7.2 8.0 78.9 1.7 19.9 798 Primary 5-8 21.5 15.7 84.8 6.6 12.4 1,220 Secondary+ 59.5 41.1 94.8 33.4 3.8 859 Wealth quintile Lowest 9.9 4.7 57.5 1.8 39.1 412 Second 12.9 5.9 82.5 1.2 15.8 640 Middle 16.0 9.7 86.9 3.3 11.2 699 Fourth 23.2 15.7 90.0 6.0 7.6 709 Highest 55.4 48.8 95.5 37.3 3.8 802 Total 25.9 19.2 85.1 11.7 13.0 3,261 Overall, respondents have greater exposure to radio broadcasts than television or print media. Education and household wealth status are strongly associated with mass media exposure: about 24 percent of women and 33 percent of men with secondary or higher education have access to all three types of media, compared with 7 percent or less for respondents in lower education categories. While 19 percent of women in the highest wealth quintile enjoy all three media, the corresponding proportion for women in the lower quintiles is 1 percent or less. 34 | Characteristics of Respondents and Women’s Status At the district level, women in Thyolo, Mulanje, and Mangochi are the most likely not to have access to any type of media (37-39 percent), while those living Lilongwe and Blantyre are more likely to have exposure to all three types of media (11-12 percent). For men, the differences across districts are less striking; exposure to all three media ranges from 4 percent in Kasungu to 26 percent in Machinga. 3.5 EMPLOYMENT STATUS Respondents were asked a number of questions to elicit their employment status at the time of the survey and the continuity of their employment in the 12 months prior to the survey. The measurement of women’s employment is difficult because some of the activities that women do, especially work on family farms, family businesses, or in the informal sector, are often not perceived by women themselves as employment and hence are not reported as such. To avoid underestimating women’s employment, the MDHS survey asked women several questions to ascertain their employment status. First women were asked, “Aside from your own housework, are you currently working?” Women who answered “no” to this question were then asked, “As you know, some women take up jobs for which they are paid in cash or kind. Others sell things, have a small business, or work on the family farm or in the family business. Are your currently doing any of these things or any other work?” Women who answered “no” to this question were asked, “Have you done any work in the last 12 months?” Women are considered currently employed if they answered “yes” to either of the first two questions. Women who answered “yes” to the third question are not currently employed but have worked in the past 12 months. All employed women were asked their occupation; whether they were paid in cash, in kind, or not at all; and for whom they worked. Table 3.5.1 and Table 3.5.2 show the percent distribution of female respondents and male respondents, respectively, by employment status and continuity of employment, according to background characteristics. Fifty-five percent of women reported being currently employed, 3 percent were employed in the 12 months preceding the survey but not working at the time of the survey, and 42 percent were not employed in the 12 months preceding the survey (Figure 3.1). The corresponding proportions for men are 56, 22, and 23 percent, respectively. Employment among women and men increases with age. Women who are formerly married are more likely than other women to be employed at the time of the survey. For men, those who are currently married are most likely to be employed. One in three never-married women and men are currently employed. While rural women are more likely than urban women to be employed, for men the pattern is reversed. Employment among women is highest in Mzimba and Thyolo (79 and 71 percent, respectively), while in Lilongwe the proportion is only 47 percent. For men, employment rates range from 82 percent in Salima to 52 percent in Thyolo. Characteristics of Respondents and Women’s Status | 35 Table 3.5.1 Employment status: women Percent distribution of women by employment status, according to background characteristics, Malawi, 2004 Employed in the 12 months preceding the survey Background characteristic Currently employed Not currently employed Not employed in the 12 months preceding the survey Missing/ don't know Total Number of women Age 15-19 37.1 3.0 59.9 0.0 100.0 2,392 20-24 53.3 3.8 42.9 0.0 100.0 2,870 25-29 57.6 2.9 39.5 0.0 100.0 2,157 30-34 63.6 2.9 33.5 0.0 100.0 1,478 35-39 64.3 2.1 33.6 0.0 100.0 1,117 40-44 67.5 4.2 28.3 0.0 100.0 935 45-49 67.8 2.8 29.3 0.1 100.0 749 Marital status Never married 32.5 2.4 65.1 0.0 100.0 1,970 Married or living together 58.4 3.3 38.3 0.0 100.0 8,312 Divorced/separated/widowed 68.0 3.2 28.8 0.0 100.0 1,416 Number of living children 0 38.9 2.9 58.1 0.0 100.0 2,655 1-2 56.2 3.6 40.2 0.0 100.0 4,092 3-4 60.9 2.7 36.4 0.0 100.0 2,726 5+ 65.8 3.1 31.1 0.1 100.0 2,225 Residence Urban 44.2 1.9 53.9 0.0 100.0 2,076 Rural 57.6 3.4 39.0 0.0 100.0 9,621 Region Northern 62.2 2.3 35.5 0.0 100.0 1,552 Central 48.8 3.5 47.7 0.0 100.0 4,734 Southern 58.8 3.0 38.2 0.0 100.0 5,412 District Blantyre 49.3 2.4 48.4 0.0 100.0 914 Kasungu 47.5 8.0 44.4 0.1 100.0 497 Machinga 54.1 3.8 42.1 0.0 100.0 427 Mangochi 55.3 2.4 42.4 0.0 100.0 599 Mzimba 78.7 3.3 18.0 0.0 100.0 778 Salima 52.4 1.8 45.7 0.1 100.0 303 Thyolo 70.5 2.8 26.7 0.0 100.0 618 Zomba 52.5 0.5 46.9 0.1 100.0 637 Lilongwe 46.6 2.3 51.1 0.0 100.0 1,705 Mulanje 62.0 2.5 35.4 0.0 100.0 512 Other districts 54.3 3.7 42.1 0.0 100.0 4,708 Education No education 63.1 3.0 33.9 0.0 100.0 2,734 Primary 1-4 58.2 3.7 38.1 0.0 100.0 2,998 Primary 5-8 52.5 3.1 44.4 0.0 100.0 4,154 Secondary+ 44.4 2.5 53.1 0.0 100.0 1,811 Wealth quintile Lowest 63.9 3.0 33.1 0.0 100.0 2,037 Second 58.3 3.9 37.8 0.0 100.0 2,277 Middle 56.5 3.6 39.9 0.0 100.0 2,383 Fourth 54.6 3.4 41.9 0.0 100.0 2,361 Highest 45.2 2.0 52.8 0.0 100.0 2,639 Total 55.2 3.1 41.6 0.0 100.0 11,698 36 | Characteristics of Respondents and Women’s Status Table 3.5.2 Employment status: men Percent distribution of men by employment status, according to background characteristics, Malawi 2004 Employed in the 12 months preceding the survey Background characteristic Currently employed Not currently employed Not employed in the 12 months preceding the survey Missing/ don't know Total Number of men Age 15-19 19.6 15.7 64.3 0.5 100.0 650 20-24 52.4 18.5 28.7 0.3 100.0 587 25-29 63.3 28.1 8.6 0.0 100.0 634 30-34 72.4 21.5 6.0 0.0 100.0 485 35-39 71.0 22.6 6.4 0.0 100.0 294 40-44 71.4 22.5 6.1 0.0 100.0 282 45-49 63.3 27.8 8.9 0.0 100.0 182 50-54 69.1 24.1 6.8 0.0 100.0 148 Marital status Never married 31.0 15.1 53.5 0.5 100.0 1,084 Married or living together 68.2 25.3 6.5 0.0 100.0 2,079 Divorced/separated/widowed 62.5 19.8 17.7 0.0 100.0 98 Number of living children 0 34.2 17.7 47.7 0.4 100.0 1,253 1-2 70.8 22.6 6.6 0.0 100.0 794 3-4 68.0 25.4 6.6 0.0 100.0 588 5+ 67.8 25.2 7.0 0.0 100.0 625 Residence Urban 64.9 7.1 28.0 0.0 100.0 669 Rural 53.2 25.5 21.1 0.2 100.0 2,593 Region Northern 55.4 21.1 23.0 0.5 100.0 423 Central 51.6 30.5 17.8 0.1 100.0 1,370 Southern 59.5 13.7 26.7 0.1 100.0 1,468 District Blantyre 61.8 11.4 26.7 0.0 100.0 316 Kasungu 53.2 26.5 20.3 0.0 100.0 156 Machinga 53.7 8.7 37.6 0.0 100.0 114 Mangochi 69.6 17.4 13.0 0.0 100.0 150 Mzimba 60.4 16.2 23.4 0.0 100.0 212 Salima 81.7 8.4 9.9 0.0 100.0 78 Thyolo 51.5 26.0 22.5 0.0 100.0 169 Zomba 61.4 17.0 21.6 0.0 100.0 159 Lilongwe 53.8 26.3 20.0 0.0 100.0 542 Mulanje 62.3 13.8 23.9 0.0 100.0 114 Other districts 50.5 26.0 23.1 0.4 100.0 1,250 Education No education 62.2 29.5 8.4 0.0 100.0 383 Primary 1-4 60.4 23.1 16.5 0.0 100.0 798 Primary 5-8 53.6 23.1 23.1 0.2 100.0 1,220 Secondary+ 51.2 15.2 33.3 0.2 100.0 859 Wealth quintile Lowest 52.1 27.7 19.8 0.5 100.0 412 Second 54.7 24.5 20.8 0.0 100.0 640 Middle 51.0 31.1 17.6 0.3 100.0 699 Fourth 59.0 20.0 20.9 0.1 100.0 709 Highest 59.3 9.8 30.9 0.0 100.0 802 Total 55.6 21.7 22.5 0.2 100.0 3,261 Characteristics of Respondents and Women’s Status | 37 3.6 WOMEN’S OCCUPATION Table 3.6.1 shows the percent distribution of employed women in the 12 months preceding the survey by occupation, according to background characteristics. Information on a woman’s occupation not only allows an evaluation of the woman’s source of income but also has implications for her empowerment. It is expected that occupation and earnings are more likely to empower women if they perceive their earnings as important for meeting the needs of their household. Seven in ten women work in agriculture. Only 3 percent of employed women are in professional, technical, or managerial positions, and 21 percent are employed in sales and services. There are small variations across subgroups of women. However, urban women, women with secondary or higher education, and women living in households in the highest wealth quintile are more likely to hold professional, technical, or managerial jobs. Table 3.6.2 shows that among employed men, 57 percent work in agriculture, 17 percent in sales and services, and 14 percent work as skilled manual laborers. Men show similar variations across subgroups as women. Figure 3.1 Employment Status of Women Age 15-49 Did not work in the 12 months preceding the survey (42%) Not currently employed (3%) Currently employed (55%) MDHS 2004 38 | Characteristics of Respondents and Women’s Status Table 3.6.1 Occupation: women Percent distribution of women employed in the 12 months preceding the survey by occupation, according to background characteristics, Malawi 2004 Background characteristic Professional/ technical/ managerial Clerical Sales and services Skilled manual Unskilled manual Domestic service Agricul- ture Total Number of women Age 15-19 0.2 0.1 15.3 1.8 1.1 3.4 77.8 100.0 958 20-24 1.3 1.8 18.5 2.1 1.2 1.4 73.7 100.0 1,638 25-29 4.3 2.0 22.2 2.1 1.4 1.5 66.4 100.0 1,306 30-34 4.2 1.4 22.2 2.1 1.2 1.3 67.6 100.0 982 35-39 4.7 0.7 24.2 2.7 2.4 0.6 64.7 100.0 741 40-44 2.9 0.5 24.7 4.0 1.1 1.4 65.3 100.0 670 45-49 1.7 0.7 17.8 2.4 0.9 1.1 75.4 100.0 529 Marital status Never married 3.1 5.3 20.5 3.3 2.2 6.5 59.0 100.0 688 Married or living together 2.5 0.7 18.6 2.3 1.0 0.6 74.3 100.0 5,128 Divorced/separated/widowed 3.7 0.9 29.9 1.9 2.3 3.4 57.9 100.0 1,008 Number of living children 0 2.3 3.2 18.3 2.5 1.6 4.2 67.7 100.0 1,112 1-2 3.2 1.4 21.1 2.0 1.3 1.2 69.9 100.0 2,446 3-4 3.4 0.4 20.8 2.1 1.0 0.9 71.4 100.0 1,735 5+ 1.6 0.4 20.7 3.0 1.5 1.0 71.9 100.0 1,531 Residence Urban 8.2 5.7 45.9 4.7 1.9 8.1 25.5 100.0 957 Rural 1.8 0.5 16.3 2.0 1.2 0.5 77.7 100.0 5,867 Region Northern 3.5 0.5 28.4 3.1 1.1 1.5 61.9 100.0 1,001 Central 2.5 1.8 19.7 2.7 1.6 1.7 70.0 100.0 2,477 Southern 2.6 1.0 18.7 1.8 1.2 1.5 73.1 100.0 3,346 District Blantyre 6.5 4.2 35.0 4.3 1.0 4.1 44.8 100.0 472 Kasungu 2.2 0.8 12.7 2.3 2.9 0.8 78.2 100.0 276 Machinga 3.3 0.0 9.1 1.6 1.5 1.0 83.4 100.0 248 Mangochi 2.0 1.4 18.7 1.0 1.4 1.0 74.6 100.0 345 Mzimba 3.0 0.6 13.7 1.6 1.0 1.9 78.2 100.0 638 Salima 2.9 1.7 17.9 3.4 3.8 0.7 69.6 100.0 164 Thyolo 1.7 0.0 15.6 2.7 1.8 0.8 77.5 100.0 453 Zomba 4.0 0.9 17.7 2.2 0.2 3.2 71.8 100.0 337 Lilongwe 2.1 3.7 22.4 2.9 1.0 4.1 63.5 100.0 834 Mulanje 2.3 0.3 17.0 1.2 1.9 1.7 75.6 100.0 330 Other districts 2.3 0.5 22.7 2.3 1.2 0.5 70.5 100.0 2,727 Education No education 0.2 0.0 13.0 2.1 1.4 0.5 82.8 100.0 1,808 Primary 1-4 0.5 0.0 17.3 2.1 1.3 1.3 77.5 100.0 1,855 Primary 5-8 1.1 0.3 25.2 2.2 1.3 2.2 67.6 100.0 2,310 Secondary+ 17.4 8.9 30.2 3.6 1.4 2.7 35.7 100.0 849 Wealth quintile Lowest 0.6 0.1 11.2 1.8 1.7 0.4 84.2 100.0 1,363 Second 0.4 0.0 15.6 1.6 1.4 0.6 80.5 100.0 1,415 Middle 0.4 0.1 17.3 2.2 1.4 0.3 78.1 100.0 1,432 Fourth 1.6 0.7 22.2 2.1 0.9 0.8 71.8 100.0 1,370 Highest 11.6 5.7 37.9 4.2 1.3 6.3 33.1 100.0 1,244 Total 2.7 1.2 20.5 2.3 1.3 1.6 70.3 100.0 6,824 Note: Total includes 2 women with missing information on occupation. Characteristics of Respondents and Women’s Status | 39 Table 3.6.2 Occupation: men Percent distribution of men employed in the 12 months preceding the survey by occupation, according to background characteristics, Malawi 2004 Background characteristic Professional/ technical/ managerial Clerical Sales and services Skilled manual Unskilled manual Domestic service Agricul- ture Total Number of men Age 15-19 0.8 0.2 16.8 7.6 7.3 4.7 62.5 100.0 229 20-24 2.8 2.5 13.7 15.3 6.5 4.3 54.8 100.0 416 25-29 6.1 1.2 19.8 13.1 3.3 1.4 55.1 100.0 579 30-34 8.3 1.8 21.4 16.4 2.4 1.1 48.7 100.0 456 35-39 5.2 3.7 16.0 15.3 4.1 2.0 53.8 100.0 275 40-44 5.4 2.0 14.3 12.9 2.1 0.8 62.6 100.0 265 45-49 2.5 1.2 15.5 13.1 3.8 1.2 62.7 100.0 165 50-54 4.0 0.5 4.9 8.3 1.0 0.8 80.6 100.0 138 Marital status Never married 4.5 2.7 17.6 10.6 7.3 5.7 51.5 100.0 500 Married or living together 4.9 1.6 16.5 14.2 3.2 1.1 58.5 100.0 1,943 Divorced/separated/widowed 7.9 0.0 15.7 16.7 0.6 2.4 56.7 100.0 81 Number of living children 0 4.1 2.1 16.8 11.3 6.3 4.1 55.3 100.0 651 1-2 6.6 1.5 18.1 15.0 3.5 2.2 53.1 100.0 742 3-4 5.8 2.0 15.7 15.0 3.0 0.8 57.7 100.0 550 5+ 3.0 1.4 15.8 12.8 2.5 0.9 63.6 100.0 581 Residence Urban 11.5 5.2 39.7 21.9 4.3 7.1 10.2 100.0 482 Rural 3.4 0.9 11.3 11.6 3.8 0.9 68.2 100.0 2,042 Region Northern 5.1 1.4 9.4 11.3 2.8 1.9 68.2 100.0 324 Central 3.9 1.8 14.3 9.1 3.4 1.9 65.7 100.0 1,126 Southern 6.0 1.8 21.5 18.9 4.8 2.3 44.7 100.0 1,074 District Blantyre 9.5 2.5 34.1 26.1 4.8 3.6 19.4 100.0 232 Kasungu 3.6 0.0 5.2 5.5 8.6 0.0 77.2 100.0 124 Machinga 6.8 2.0 20.2 14.3 2.2 0.7 53.9 100.0 71 Mangochi 3.2 0.0 17.6 12.5 1.4 0.0 65.3 100.0 131 Mzimba 4.6 1.5 5.9 8.3 2.2 2.0 75.4 100.0 163 Salima 2.6 1.0 18.2 9.2 4.9 1.6 62.6 100.0 71 Thyolo 3.7 2.0 17.8 20.6 12.7 1.0 42.2 100.0 131 Zomba 7.0 1.6 22.2 18.4 1.9 3.2 45.7 100.0 125 Lilongwe 5.3 2.5 22.1 8.7 2.6 4.7 54.1 100.0 434 Mulanje 8.2 2.5 17.3 22.3 5.7 1.9 42.2 100.0 87 Other Districts 3.8 1.7 12.0 12.7 3.2 1.2 65.4 100.0 956 Education No education 0.3 0.2 10.5 8.8 4.8 1.7 73.8 100.0 351 Primary 1-4 0.8 0.1 10.6 12.2 4.5 2.6 69.1 100.0 666 Primary 5-8 1.4 1.4 18.2 15.2 3.6 2.1 58.1 100.0 935 Secondary+ 18.3 5.1 25.3 15.3 3.2 1.6 31.1 100.0 571 Wealth quintile Lowest 1.4 0.7 5.4 8.9 2.2 1.6 79.8 100.0 328 Second 0.8 0.4 6.8 14.0 4.3 0.4 73.3 100.0 507 Middle 1.9 1.0 11.7 11.5 3.9 0.8 69.3 100.0 575 Fourth 3.0 0.9 18.0 14.3 4.1 0.5 59.1 100.0 560 Highest 15.9 5.3 36.5 17.1 4.4 6.8 14.0 100.0 554 Total 4.9 1.7 16.7 13.5 3.9 2.1 57.1 100.0 2,523 40 | Characteristics of Respondents and Women’s Status 3.7 TYPE OF EMPLOYMENT Table 3.7.1 shows the percent distribution of women who have worked at any time during the 12 months preceding the survey by type of employment (agricultural or nonagricultural). All employed women were asked whether they were paid in cash, in kind, or not at all. Two in three women receive no payment for their work (Figure 3.2). Women who work in agricultural jobs are much more likely not to be paid than women who work in nonagricultural jobs (80 percent compared with 32 percent). Ten percent of women engaged in agricultural work were paid in cash only, compared with 63 percent of women in nonagricultural jobs. Overall, three in four women who were employed in the 12 months prior to the survey were self-employed. Small differences are found between agriculture and nonagriculture occupations. Two in three women work seasonally. Women in agricultural jobs are more likely to work seasonally (82 percent) than women in nonagricultural jobs (29 percent). Fifteen percent of women who work in agriculture work all year, compared with 53 percent of women in nonagricultural jobs. Table 3.7.1 Type of employment: women Percent distribution of women 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 2004 Employment characteristic Agricultural work Nonagricultural work Total Type of earnings Cash only 10.2 62.6 25.7 Cash and in-kind 6.2 3.6 5.4 In-kind only 3.6 1.4 2.9 Not paid 80.0 32.2 65.8 Missing 0.0 0.3 0.1 Total 100.0 100.0 100.0 Type of employer Employed by family member 17.5 7.1 14.4 Employed by nonfamily member 3.7 23.5 9.6 Self-employed 78.7 69.2 75.9 Missing 0.1 0.3 0.1 Total 100.0 100.0 100.0 Continuity of employment All year 15.2 52.6 26.3 Seasonal 81.9 28.5 66.0 Occasional 2.6 18.8 7.4 Missing 0.4 0.2 0.3 Total 100.0 100.0 100.0 Number of women 4,800 2,022 6,824 Total includes two women with missing information on type of employment. Characteristics of Respondents and Women’s Status | 41 Table 3.7.2 shows the percent distribution of men who were employed in the 12 months preceding the survey by occupation and type of earnings. One in three men are not paid for their work and 54 percent receive cash payment only. Men who work in agriculture are less likely to be paid than men who work in nonagricultural jobs. Among those who are paid for their work, the largest proportion are paid in cash (32 percent), while 10 percent are paid in cash and in-kind and 6 percent are paid in in-kind only. Table 3.7.2 Type of employment: men Percent distribution of men employed in the 12 months preceding the survey by type of earnings, according to type of employment (agricultural or nonagricultural), Malawi 2004 Type of earnings Agricultural work Nonagricultural work Total Cash only 32.4 82.3 53.8 Cash and in-kind 10.4 3.4 7.4 In-kind only 6.1 1.0 3.9 Not paid 49.8 10.1 32.8 Missing 1.3 3.2 2.2 Total 100.0 100.0 100.0 Number of men 1,441 1,083 2,523 3.8 MEASURES OF WOMEN’S EMPOWERMENT In addition to information on women’s education, employment status, and control of earnings, the 2004 MDHS also obtained information on other measures of women’s status and empowerment. In particular, questions were asked on women’s participation in specific household decisions, on their degree of acceptance of wife beating, and on their opinions about when a wife should be able to refuse sex with her husband. These data provide insight into women’s control over their lives and their environment and their attitudes toward traditional gender roles, which are Figure 3.2 Type of Earnings of Women Age 15-49 Not paid (66%) In-kind only (3%) Cash and in-kind (5%) Cash only (26%) MDHS 2004 42 | Characteristics of Respondents and Women’s Status important aspects of women’s empowerment relevant for understanding demographic and health behaviours. These questions are used to define three indicators of women’s empowerment: women’s participation in decision making, women’s degree of acceptance of wife beating, and their degree of acceptance of a wife’s right to refuse sex with her husband. The first measure requires little explanation, since the ability to make decisions about one’s own life is of obvious importance to practical empowerment. The other two measures derive from the notion that gender equity is essential to empowerment. Responses that indicate a view that the beating of wives by husbands is justified reflect a sanction of women’s lower status, both absolutely and relative to men. Although such attitudes do not necessarily signify approval of men beating their wives, they do signify women’s acceptance of norms that give men the right to discipline women with force. Similarly, beliefs about whether and when a woman can refuse sex with her husband reflect issues of gender equity regarding sexual rights and bodily integrity. Besides yielding an important measure of empowerment, the information about women’s attitudes toward sexual rights will be useful for improving and monitoring reproductive health programmes that depend on women’s willingness and ability to control their own sexual lives. Employed women who earn cash for their work were asked who the main decisionmaker is with regard to the use of their earnings. This information allows the assessment of women’s control over their own earnings. In addition, they were asked about the proportion of household expenditures met by their earnings, in order to assess the relative importance of women’s earnings. This information not only allows an evaluation of the relative importance of women’s earnings in the household economy, but has implications for the empowerment of women. It is expected that employment and earnings are more likely to empower women if women perceive their earnings to be important for meeting the needs of their households. Table 3.8 shows how respondents’ degree of control over the use of their earnings and the extent to which earnings of women meet household expenditures varies by background characteristics. The data show that more than half (52 percent) of women decide for themselves on how their earnings are used, 20 percent make the decisions jointly with someone else, and 27 percent reported that someone else decides for them. Respondents’ degree of control over the use of their earnings varies by background characteristics. Older women, more educated women, and women who live in households in the higher wealth quintiles are more likely to have control over their earnings. For example, while 64 percent of women with secondary or higher education decide how their earnings are used, the proportion among women with no education is only 48 percent. Table 3.8 also shows the proportion of household expenditures that are met by the women’s cash earnings. More than half (57 percent) of women reported that their earnings support half or more of their household’s expenditures. Twenty percent of women say their earnings support all of their households’ expenditures, and 37 percent reported that their earnings support half or more of their households’ financial needs. Across subgroups of women, the data show that women who are more likely to meet all of their household’s expenditures are those over age 30, those who are widowed, separated, or divorced; rural women; and those who are less educated. Characteristics of Respondents and Women’s Status | 43 Table 3.8 Decision on use of earnings and contribution of earnings to household expenditures Percent distribution of women employed in the 12 months preceding the survey receiving cash earnings by person who decides how earnings are to be used and by proportion of household expenditures met by earnings, according to background characteristics, Malawi 2004 Person who decides how earnings are used Proportion of household expenditures met by earnings Background characteristic Self only Jointly Someone else only Missing Total Almost none/ none Less than half Half or more All Missing Total Number of women Age 15-19 44.2 13.2 42.6 0.0 100.0 21.3 31.8 33.0 13.9 0.0 100.0 225 20-24 46.0 17.8 35.8 0.4 100.0 12.5 36.6 31.2 19.2 0.5 100.0 467 25-29 52.0 21.4 25.4 1.3 100.0 8.1 33.0 43.6 14.7 0.6 100.0 455 30-34 54.3 22.2 23.6 0.0 100.0 11.6 27.8 31.9 28.3 0.4 100.0 316 35-39 58.5 22.9 18.3 0.2 100.0 5.4 34.2 38.5 21.6 0.2 100.0 273 40-44 56.5 21.6 21.0 0.9 100.0 7.9 32.4 35.3 24.3 0.0 100.0 234 45-49 63.6 19.2 17.3 0.0 100.0 3.7 30.7 44.9 20.6 0.0 100.0 155 Marital status Never married 70.0 4.1 25.8 0.0 100.0 19.6 29.6 31.4 19.4 0.0 100.0 250 Married or living together 37.5 27.9 34.1 0.5 100.0 9.0 35.5 39.4 15.7 0.4 100.0 1,468 Divorced/separated/widowed 95.2 0.7 3.4 0.6 100.0 9.3 25.0 29.4 35.9 0.4 100.0 407 Number of living children 0 55.9 12.3 31.5 0.3 100.0 19.8 34.0 29.0 16.9 0.3 100.0 364 1-2 49.8 21.3 28.0 0.8 100.0 7.7 31.6 40.0 20.2 0.5 100.0 771 3-4 51.4 21.8 26.3 0.5 100.0 9.9 32.9 36.1 20.8 0.4 100.0 531 5+ 55.0 21.4 23.6 0.0 100.0 7.7 33.8 37.2 21.3 0.0 100.0 459 Residence Urban 67.7 22.4 9.1 0.8 100.0 15.8 32.4 34.1 17.7 0.0 100.0 557 Rural 46.9 19.0 33.7 0.4 100.0 8.3 32.9 37.4 20.9 0.4 100.0 1,568 Region Northern 61.2 23.3 14.7 0.8 100.0 7.8 37.2 43.9 10.4 0.8 100.0 385 Central 43.1 13.7 42.9 0.4 100.0 14.9 39.1 31.8 13.8 0.2 100.0 894 Southern 58.2 24.9 16.4 0.5 100.0 6.6 24.1 38.2 30.9 0.2 100.0 847 District Blantyre 63.3 27.6 8.1 1.1 100.0 9.8 25.8 38.8 25.7 0.0 100.0 225 Kasungu 38.9 20.7 40.3 0.0 100.0 8.5 38.2 37.3 16.0 0.0 100.0 65 Machinga (73.5) (10.9) (15.7) (0.0) 100.0 (6.7) (28.3) (35.3) (29.7) (0.0) 100.0 33 Mangochi 68.4 12.2 19.4 0.0 100.0 3.9 19.7 21.8 54.6 0.0 100.0 65 Mzimba 57.7 21.6 20.7 0.0 100.0 11.4 36.1 42.3 10.2 0.0 100.0 121 Salima 34.2 19.3 46.5 0.0 100.0 15.0 56.0 17.4 11.6 0.0 100.0 63 Thyolo 61.4 25.7 11.2 1.8 100.0 8.8 16.4 35.4 37.6 1.8 100.0 106 Zomba 54.4 29.5 16.1 0.0 100.0 3.9 19.6 41.7 34.8 0.0 100.0 109 Lilongwe 54.6 12.4 32.4 0.6 100.0 21.2 35.0 27.1 16.8 0.0 100.0 341 Mulanje 60.1 19.9 20.0 0.0 100.0 2.3 27.1 43.3 27.3 0.0 100.0 119 Other districts 45.9 19.6 34.0 0.5 100.0 8.5 36.8 39.9 14.2 0.6 100.0 877 Education No education 48.2 12.9 38.3 0.6 100.0 9.6 33.3 31.4 24.9 0.9 100.0 411 Primary 1-4 45.8 21.2 33.0 0.0 100.0 11.0 33.3 35.2 20.3 0.2 100.0 487 Primary 5-8 51.8 20.5 27.1 0.5 100.0 11.8 32.6 37.3 18.2 0.1 100.0 755 Secondary+ 63.7 23.7 11.8 0.8 100.0 7.8 32.3 41.2 18.5 0.2 100.0 472 Wealth quintile Lowest 54.7 13.7 31.4 0.2 100.0 9.2 33.1 30.7 27.0 0.0 100.0 329 Second 45.5 18.2 35.3 1.0 100.0 6.2 37.9 31.4 22.9 1.7 100.0 351 Middle 42.1 18.9 39.1 0.0 100.0 11.4 31.5 36.2 20.9 0.0 100.0 367 Fourth 47.0 22.3 30.2 0.6 100.0 11.0 33.0 41.9 14.0 0.0 100.0 392 Highest 63.3 23.0 13.1 0.6 100.0 11.9 30.6 39.1 18.2 0.2 100.0 686 Total 52.4 19.9 27.2 0.5 100.0 10.3 32.8 36.5 20.0 0.3 100.0 2,125 Note: Figures in parentheses are based on 25-49 unweighted cases. 44 | Characteristics of Respondents and Women’s Status Table 3.9 shows working women’s control over their own earnings within marital and non- marital contexts, and how it varies by the extent to which their earnings help to meet household expenditures. Overall, 38 percent of married women have complete control over their earnings, 27 percent share control with their husband or partner, and for 34 percent of married women, their husband/partner controls their earnings. Many married women do not have control over their cash income even if their earnings do not contribute to the household expenditures. For example, husbands decide how their wives’ earnings are used for 43 percent of women whose income does not substantially contribute to household expenditures. Women who are divorced, separated, widowed, or never married are more likely to have control over their earnings than married women (86 percent compared with 38 percent). Table 3.9 Women's control over earnings Percent distribution of women who received cash earnings for work in the past 12 months by person who decides how earnings are used and current marital status, according to the proportion of household expenditures met by earnings, Malawi 2004 Currently married or living together Not married1 Contribution to household expenditures Self only Jointly with husband Jointly with some- one else Hus- band only Someone else only Miss- ing Total Number of women Self only Jointly with some- one else Someone else only Missing Total Number of women Almost none/none 40.8 10.9 3.9 42.9 1.5 0.0 100.0 132 84.6 1.8 13.6 0.0 100.0 87 Less than half 40.2 22.7 1.1 34.8 0.4 0.9 100.0 521 82.3 2.9 14.7 0.0 100.0 176 Half or more 34.5 32.9 0.4 31.9 0.3 0.0 100.0 578 83.6 2.7 13.7 0.0 100.0 198 All 37.7 31.6 0.5 30.0 0.0 0.3 100.0 231 92.0 0.6 7.1 0.3 100.0 195 Total 37.5 27.0 1.0 33.5 0.6 0.5 100.0 1,468 85.6 2.0 12.0 0.4 100.0 657 Note: Total includes women with missing information on contribution to household expenditures. 1Never married, divorced, separated or widowed women The ability of women to take decisions that affect the circumstances of their own lives is an essential aspect of empowerment. In order to assess women’s decisionmaking autonomy, information was collected on women’s participation in five different types of decisions: on the respondent’s own health care, on making large household purchases, on making household purchases for daily needs, on visits to family friends or relatives, and on what food should be cooked each day. Table 3.10 shows the percent distribution of women according to who in the household usually has the final say on each of these decisions. The data show that for 65 percent or more of married women, their husbands make decisions for their wives’ health care, and large and daily household purchases. Decisions to visit family or relatives are more likely to be made together with their husbands (41 percent). The only one of these decisions that a majority of married women make on their own is the type of food to cook daily. The pattern is different for nonmarried women. Nonmarried women are more likely than married women to make four of the five decisions by themselves. However, for about half of women all five of these decisions are made by someone other than the woman herself: someone else decides on visiting family and relatives for 47 percent of nonmarried women and on large household purchases for 56 percent of nonmarried women. Characteristics of Respondents and Women’s Status | 45 Table 3.10 Women's participation in decisionmaking Percent distribution of women by person who has the final say in making specific decisions and current marital status, according to type of decision, Malawi 2004 Currently married or living together Not married1 Decision Self only Jointly with husband Jointly with someone else Hus- band only Some- one else only Decision not made/not applicable Total Number of women Self only Jointly with someone else Some- one else only Decision not made/not applicable Total Num- ber of women Own health care 17.8 9.9 0.1 70.4 1.5 0.3 100.0 8,312 40.7 3.0 51.9 4.4 100.0 3,385 Large household purchases 6.4 11.5 0.1 80.3 1.2 0.5 100.0 8,312 34.2 3.4 55.7 6.7 100.0 3,385 Daily household purchases 18.8 13.8 0.1 65.4 1.5 0.2 100.0 8,312 35.4 3.8 54.8 5.9 100.0 3,385 Visits to family or relatives 18.8 41.3 0.2 38.4 1.1 0.2 100.0 8,312 40.9 6.8 46.5 5.7 100.0 3,385 What food to cook each day 64.3 9.5 0.4 24.2 1.3 0.1 100.0 8,312 38.6 5.9 49.5 5.9 100.0 3,385 1Never married, divorced, separated or widowed women Table 3.11.1 shows the percentage of women who report that they alone or jointly have the final say in specific household decisions, according to background characteristics. Divorced, separated, or widowed women are far more likely than married or never-married women to have the final say in all the specified decisions. Degree of independence in making household decisions increases with age and number of children. Urban women, women who earn cash, and the least educated women are more likely to have a final say in all given decisions. Regardless of background characteristic, ever-married women and those over age 20 have the final say on what food to cook every day. Table 3.11.2 shows similar data from a man’s perspective. Contrary to the women’s report, the majority of men say that in a couple, a wife has an equal or greater say in making decisions on visiting family or friends, control over the money she earns, and how many children she wants to have and when she wants to have them (73 percent, 69 percent, and 64 percent, respectively). Men are less likely to agree on a wife’s role in making decisions on large household purchases and small daily purchases (44 percent and 53 percent, respectively). Twenty-seven percent of men say that a wife has an equal or greater say in all five decisions listed. There are no significant differences by the man’s age, except that men age 15-19 are less likely than older men to agree that a wife has an equal or greater share in making specific decisions. Rural men are much less likely than urban men to agree to the five decisions (23 percent compared with 44 percent). Men in the Northern Region are less likely than men in other regions to agree to the specific decisions (21 percent compared with 27-28 percent). Education and wealth index have a positive relationship with the likelihood that men agree to the role of women in making specific decisions. Better educated men and men in higher wealth quintile are more likely than other men to say that a wife has an equal or greater say in all five decisions. Across oversampled districts, men in Blantyre and Machinga are most likely to say that a wife has an equal or greater say in making specific decisions. On the other hand, men in Salima are the least likely to agree to these decisions. 46 | Characteristics of Respondents and Women’s Status Table 3.11.1 Women's participation in decisionmaking by background characteristics: women Percentage of women who say that they alone or jointly have the final say in specific decisions, by background characteristics, Malawi 2004 Alone or jointly have final say in: Background characteristic Own health care Making large purchases Making daily purchases Visits to family or relatives What food to cook each day All specified decisions None of the specified decisions Number of women Age 15-19 17.8 8.7 13.1 30.3 31.2 6.3 56.4 2,392 20-24 28.2 18.0 30.5 55.5 65.7 13.3 23.6 2,870 25-29 33.8 25.0 39.0 62.2 74.2 19.9 17.9 2,157 30-34 38.5 30.6 43.7 68.1 78.0 24.7 13.6 1,478 35-39 42.4 34.8 44.8 65.3 78.4 27.9 13.6 1,117 40-44 43.4 35.5 49.4 70.9 83.6 28.9 10.8 935 45-49 50.0 43.9 54.7 76.1 85.0 37.8 10.5 749 Marital status Never married 17.1 9.3 10.2 20.6 16.3 7.9 71.3 1,970 Married or living together 27.8 18.0 32.8 60.3 74.3 12.1 16.7 8,312 Divorced/separated/widowed 80.6 76.9 79.5 85.6 83.8 73.2 10.7 1,416 Number of living children 0 19.7 10.9 15.6 30.7 31.3 8.4 56.5 2,655 1-2 33.4 24.8 36.6 61.6 71.8 19.6 18.4 4,092 3-4 37.0 28.9 42.0 65.3 78.0 22.9 14.6 2,726 5+ 40.1 30.4 44.5 67.9 80.4 24.6 13.3 2,225 Residence Urban 34.1 28.2 42.9 53.2 61.2 23.6 31.1 2,076 Rural 32.0 22.7 32.8 57.4 66.6 17.7 23.9 9,621 Region Northern 37.1 25.6 36.6 53.0 70.9 16.2 22.2 1,552 Central 29.3 21.1 32.3 53.4 65.2 16.9 26.5 4,734 Southern 33.7 25.3 36.1 60.5 64.6 21.1 24.8 5,412 District Blantyre 44.3 37.5 48.3 59.7 69.5 31.6 24.9 914 Kasungu 19.3 12.4 20.1 36.9 69.9 8.0 24.7 497 Machinga 27.8 22.5 35.5 57.5 69.7 19.0 26.0 427 Mangochi 26.7 22.8 31.7 43.6 50.9 17.8 39.4 599 Mzimba 41.5 23.6 35.7 57.9 77.7 15.0 15.4 778 Salima 27.8 19.2 31.6 53.4 63.1 15.3 29.8 303 Thyolo 30.3 22.5 33.2 78.8 74.2 19.0 14.1 618 Zomba 26.7 20.6 30.6 57.0 61.7 17.6 27.2 637 Lilongwe 30.7 23.4 36.5 52.8 61.3 19.6 29.4 1,705 Mulanje 29.9 24.5 33.8 61.2 61.4 21.6 29.2 512 Other districts 33.3 23.2 34.0 57.7 65.6 17.9 23.9 4,708 Education No education 36.3 27.9 38.3 63.2 71.8 22.5 18.7 2,734 Primary 1-4 30.3 21.3 32.0 57.8 68.1 17.7 22.8 2,998 Primary 5-8 31.3 21.7 34.3 54.8 64.4 16.6 26.5 4,154 Secondary+ 32.3 25.5 34.2 49.2 55.1 19.8 35.8 1,811 Employment Not employed 25.0 17.2 27.7 46.2 56.3 13.4 35.2 5,235 Employed for cash 44.6 39.6 53.1 68.4 77.7 31.8 15.6 2,033 Employed not for cash 35.5 23.8 34.2 63.6 71.2 19.0 17.7 4,417 Wealth quintile Lowest 42.0 33.5 42.7 63.4 71.4 28.6 19.8 2,037 Second 30.4 20.9 30.4 58.5 67.2 17.0 23.0 2,277 Middle 28.8 19.8 30.4 54.7 65.4 15.0 24.9 2,383 Fourth 28.5 19.5 31.3 56.4 65.4 13.9 25.0 2,361 Highest 33.4 25.6 38.9 51.9 60.5 20.5 31.6 2,639 Total 32.4 23.6 34.6 56.7 65.7 18.8 25.2 11,698 Note: Total includes 13 women with missing information on employment status Characteristics of Respondents and Women’s Status | 47 Table 3.11.2 Men’s attitudes towards women’s control of decisionmaking by background characteristics Percentage of men who say that in a couple the wife should have an equal or greater say than the husband in specific decisions, by background characteristics, Malawi 2004 Wife should have an equal or greater say in: Background characteristic Making large purchases Making daily purchases Visits to family or relatives Control over money she earns How many children to have and when All of the specified decisions Number of men Age 15-19 35.7 46.9 71.7 66.6 58.4 19.5 650 20-24 41.0 51.6 70.9 66.5 63.6 25.1 587 25-29 49.2 55.2 76.1 71.0 69.4 32.6 634 30-34 47.8 57.1 75.4 71.9 68.2 29.3 485 35-39 49.7 56.5 72.6 66.1 61.2 27.8 294 40-44 45.6 53.3 74.3 68.4 61.9 27.6 282 45-49 43.3 51.9 70.1 73.6 64.9 27.7 182 50-54 45.6 52.9 65.2 60.6 54.0 27.7 148 Marital status Never married 41.2 52.6 74.9 69.5 63.4 25.3 1,084 Married or living together 45.7 52.9 71.8 67.7 64.2 27.6 2,079 Divorced/separated/widowed 40.0 55.0 74.4 72.0 54.9 26.5 98 Number of living children 0 40.7 51.7 73.3 69.0 63.4 24.5 1,253 1-2 46.1 53.0 72.6 68.6 65.6 28.7 794 3-4 48.8 53.9 75.1 70.3 64.4 30.1 588 5+ 43.9 54.1 70.3 65.3 60.7 25.8 625 Residence Urban 55.0 68.5 83.8 79.8 79.1 43.6 669 Rural 41.3 48.8 70.1 65.5 59.6 22.5 2,593 Region Northern 35.2 74.8 58.3 70.9 52.0 21.2 423 Central 45.0 45.4 71.2 64.3 62.0 26.8 1,370 Southern 45.8 53.5 78.6 71.6 68.6 28.4 1,468 Education No education 36.4 40.3 66.8 58.5 55.3 20.0 383 Primary 1-4 26.8 40.1 62.0 56.3 50.0 13.6 798 Primary 5-8 41.7 53.5 71.4 67.2 60.7 23.6 1,220 Secondary+ 66.9 69.3 87.8 86.0 84.3 46.6 859 Wealth quintile Lowest 30.3 41.4 61.3 60.3 51.8 15.4 412 Second 35.5 39.9 68.7 59.0 57.3 15.6 640 Middle 41.4 48.9 66.6 65.4 58.2 21.0 699 Fourth 46.3 56.7 75.4 71.3 65.6 29.5 709 Highest 58.3 69.0 85.4 80.3 77.9 44.2 802 District Blantyre 64.9 68.0 89.3 85.3 82.3 47.0 316 Kasungu 29.5 40.7 48.0 51.0 43.1 12.6 156 Machinga 56.4 70.7 74.2 70.6 73.7 48.2 114 Mangochi 30.3 43.4 68.1 59.1 51.6 18.9 150 Mzimba 30.2 71.0 55.8 69.8 51.2 17.1 212 Salima 28.4 28.0 64.7 52.9 47.4 7.7 78 Thyolo 43.3 46.0 70.9 59.1 58.5 21.2 169 Zomba 32.1 46.6 67.2 53.4 50.3 21.4 159 Lilongwe 50.5 53.5 71.0 66.3 66.5 37.3 542 Mulanje 51.2 40.2 79.4 68.3 67.4 28.1 114 Other districts 42.7 51.1 76.9 72.2 65.9 22.0 1,250 Total 44.1 52.8 72.9 68.5 63.6 26.8 3,261 48 | Characteristics of Respondents and Women’s Status To assess women’s degree of acceptance of wife beating, the 2004 MDHS survey asked women, “Sometimes a husband is annoyed or angered by things which his wife does. In your opinion, is a husband justified in hitting or beating his wife in the following situations?” The five situations presented to women for their opinion are: if she burns the food, if she argues with him, if she goes out without telling him, if she neglects the children, and if she refuses to have sex with him. The first five columns in Table 3.12.1 show how acceptance of wife beating varies for each reason. The last column gives the percentages of women who feel that wife beating is justified for at least one of the given reasons. A woman who believes that a husband is justified in hitting or beating his wife for any reason at all may believe herself to be of low status, both absolutely and relative to men. Such a perception could act as a barrier to accessing health care for her and her children, could affect her attitude toward contraceptive use, and could impact her general well being. Twenty-eight percent of women agree with at least one of the selected reasons for wife beating. Neglecting the children was the reason for which women were most likely to find wife beating justified (17 percent). Differentials across respondents’ background characteristics are small, although younger women, married women, rural women, and women with less than secondary education are more likely to accept justifications for wife beating. Women in the Northern Region are much more likely than women in other regions to agree with at least one reason for wife beating (45 percent compared to 32 percent or less). Table 3.12.2 shows men’s perception on justifications for wife beating. Interestingly, men are less likely than women to justify wife beating for any reason (16 percent compared to 28 percent). In general, younger men, never-married men, men with no living children, men in the Northern or Central Regions, and men in the lower wealth quintiles are more likely than other men to agree to wife beating for any reason. The extent of control women have over when and with whom they have sex has important implications for demographic and health outcomes. To measure women’s agreement with the idea that a woman has the right to refuse to have sex with her husband, the 2004 MDHS asked respondents whether a wife is justified in refusing to have sex with her husband under four circumstances: she is tired or not in the mood, she has recently given birth, she knows her husband has had sex with other women, and she knows her husband has a sexually transmitted disease. These four circumstances for which women’s opinions are sought have been chosen because they are effective in combining issues of women’s rights and consequences for women’s health. Table 3.13.1 shows the percentage of women who say that women are justified in refusing to have sex with their husband for specific reasons, by background characteristics. The table also shows how this indicator of women’s empowerment varies with the other two indicators, namely with women’s participation in decisionmaking and women’s attitudes toward wife beating. It is worth noting that, unlike the previous indicator of empowerment, this indicator is positively related to empowerment: the more reasons women agree with, the higher is their empowerment in terms of a belief in women’s sexual rights. Characteristics of Respondents and Women’s Status | 49 Table 3.12.1 Women's attitude towards wife beating Percentage of women who agree that a husband is justified in hitting or beating his wife for specific reasons, by background characteristics, Malawi 2004 Husband is justified in hitting or beating his wife if she: Background characteristic Burns the food Argues with him Goes out without telling him Neglects the children Refuses to have sex with him Agrees with at least one specified reason Number of women Age 15-19 14.2 14.8 15.9 20.9 13.5 31.8 2,392 20-24 12.0 12.8 13.9 18.4 14.4 29.8 2,870 25-29 10.8 10.9 14.9 16.7 14.2 27.6 2,157 30-34 9.1 10.5 11.6 14.7 12.4 24.4 1,478 35-39 10.6 9.7 12.1 14.1 13.1 25.8 1,117 40-44 9.5 10.5 13.5 15.5 14.2 27.4 935 45-49 9.7 8.1 12.4 13.7 12.5 24.7 749 Marital status Never married 11.1 11.5 13.0 17.5 10.8 26.9 1,970 Married or living together 11.7 12.3 14.6 17.6 14.8 29.2 8,312 Divorced/separated/widowed 10.1 9.1 11.0 14.1 11.1 24.5 1,416 Number of living children 0 12.5 13.0 14.4 18.5 12.9 29.7 2,655 1-2 11.7 12.3 13.9 17.5 14.2 28.8 4,092 3-4 10.8 11.0 13.4 16.5 13.7 27.6 2,726 5+ 10.1 10.5 13.9 15.7 13.5 26.3 2,225 Residence Urban 6.3 7.1 10.1 10.5 8.6 18.1 2,076 Rural 12.5 12.8 14.7 18.6 14.7 30.4 9,621 Region Northern 17.7 17.6 24.5 28.2 22.6 45.1 1,552 Central 13.7 14.6 15.3 20.2 17.5 31.8 4,734 Southern 7.5 7.6 9.6 11.4 7.7 20.2 5,412 District Blantyre 4.0 3.9 4.8 6.2 4.0 10.1 914 Kasungu 24.9 25.8 32.6 38.2 27.5 50.4 497 Machinga 5.6 3.1 3.1 4.9 4.6 12.5 427 Mangochi 9.1 12.1 12.4 15.9 11.7 28.0 599 Mzimba 20.2 21.0 28.4 29.5 23.2 47.4 778 Salima 10.0 8.9 8.8 12.3 26.7 35.8 303 Thyolo 11.4 9.5 11.9 14.8 8.7 24.2 618 Zomba 6.7 8.4 8.7 9.6 7.0 18.5 637 Lilongwe 10.8 11.6 11.3 13.9 13.6 20.5 1,705 Mulanje 7.4 7.5 9.3 10.1 9.6 19.9 512 Other districts 12.1 12.6 15.2 19.9 14.7 32.8 4,708 Education No education 11.8 11.4 13.4 16.3 15.1 28.3 2,734 Primary 1-4 13.7 12.8 13.9 17.2 15.0 30.2 2,998 Primary 5-8 11.6 12.5 15.8 19.0 14.3 30.2 4,154 Secondary+ 6.5 9.2 10.2 14.1 7.8 20.3 1,811 Employment Not employed 10.6 10.8 12.5 16.3 13.6 26.5 5,235 Employed for cash 10.1 12.1 15.6 17.3 13.8 29.7 2,033 Employed not for cash 12.9 12.9 14.8 18.2 13.7 29.7 4,417 Number of decisions in which woman has final say1 0 12.5 12.7 14.6 17.9 12.9 27.7 2,945 1-2 12.1 13.4 15.7 19.2 15.1 31.1 4,501 3-4 10.9 10.9 13.1 16.9 14.4 29.9 2,057 5 9.0 8.2 9.9 12.2 11.0 21.6 2,195 Wealth quintile Lowest 13.2 12.8 14.4 17.7 14.7 30.0 2,037 Second 12.5 12.8 14.8 18.2 16.6 31.9 2,277 Middle 13.0 14.3 14.6 20.3 15.8 32.0 2,383 Fourth 11.6 12.2 15.5 18.9 14.3 30.0 2,361 Highest 7.3 7.6 10.7 11.6 7.8 18.8 2,639 Total 11.4 11.8 13.9 17.2 13.7 28.2 11,698 Note: Total includes 13 women with missing information on employment. 1 Either by herself or jointly with others 50 | Characteristics of Respondents and Women’s Status Table 3.12.2 Men's attitude towards wife beating Percentage of men who agree that a husband is justified in hitting or beating his wife for specific reasons, by background character- istics, Malawi 2004 Husband is justified in hitting or beating his wife if she: Background characteristic Burns the food Argues with him Goes out without telling him Neglects the children Refuses to have sex with him Agrees with at least one specified reason Number of men Age 15-19 7.8 14.2 10.6 14.2 11.0 27.9 650 20-24 5.4 11.5 11.6 12.5 9.1 21.9 587 25-29 3.9 5.2 5.3 7.1 4.0 12.0 634 30-34 3.0 4.9 4.5 6.0 6.6 13.1 485 35-39 1.8 3.7 4.8 5.0 4.7 9.5 294 40-44 1.4 2.0 2.5 2.9 2.0 6.5 282 45-49 1.5 4.9 2.5 2.3 2.2 5.4 182 50-54 2.4 4.5 4.4 5.9 6.4 12.9 148 Marital status Never married 7.1 11.9 9.8 12.9 10.2 23.8 1,084 Married or living together 2.7 5.3 5.4 6.2 4.5 12.1 2,079 Divorced/separated/widowed 5.3 8.3 6.4 6.1 10.6 15.1 98 Number of living children 0 6.6 11.8 9.7 12.7 9.9 22.9 1,253 1-2 3.2 5.3 6.6 5.8 4.5 13.3 794 3-4 2.5 5.1 4.9 6.2 4.8 11.7 588 5+ 2.2 4.4 3.6 5.3 4.3 10.0 625 Residence Urban 4.6 5.5 5.7 5.8 6.5 14.1 669 Rural 4.1 8.1 7.2 9.1 6.6 16.6 2,593 Region Northern 6.5 10.9 10.4 14.2 11.7 22.7 423 Central 6.0 10.3 8.7 10.8 8.8 21.1 1,370 Southern 1.9 4.1 4.2 4.5 3.1 9.5 1,468 District Blantyre 2.1 3.1 2.8 3.0 3.9 6.8 316 Kasungu 6.2 12.5 8.1 12.5 8.3 22.5 156 Machinga 1.5 4.6 3.5 1.4 0.7 6.5 114 Mangochi 2.8 5.0 4.0 5.6 3.6 10.0 150 Mzimba 6.7 12.0 7.8 12.9 10.2 21.2 212 Salima 5.8 9.2 8.6 7.5 12.0 17.5 78 Thyolo 3.5 4.7 2.4 6.3 2.0 11.5 169 Zomba 1.6 6.6 5.1 6.3 5.6 13.7 159 Lilongwe 6.0 7.2 8.2 8.5 9.3 19.0 542 Mulanje 2.4 8.6 9.5 10.4 5.3 16.6 114 Other districts 4.2 8.5 8.3 9.9 6.7 17.9 1,250 Education No education 3.1 5.7 3.8 4.8 5.6 12.2 383 Primary 1-4 5.3 9.6 7.4 10.6 9.7 20.3 798 Primary 5-8 5.0 9.6 8.5 9.9 7.0 18.0 1,220 Secondary+ 2.5 3.8 5.5 6.0 3.6 11.3 859 Number of decisions in which a woman should have final say1 0 (0.0) (3.0) (5.1) (5.9) (7.8) (12.9) 35 1-2 5.4 9.1 9.1 9.4 7.8 19.2 911 3-4 3.8 7.1 6.1 8.1 6.1 14.9 2,316 Wealth quintile Lowest 7.0 11.5 7.7 11.0 9.8 19.0 412 Second 4.9 9.1 7.5 11.0 6.8 17.7 640 Middle 3.9 8.0 7.7 8.9 7.2 16.4 699 Fourth 3.4 6.5 5.2 7.1 4.8 15.0 709 Highest 3.2 5.0 6.9 5.9 5.8 14.0 802 Total 4.2 7.6 6.9 8.4 6.6 16.1 3,261 Note: Figures in parentheses are based on 25-49 cases. 1 Either by herself or jointly with others Characteristics of Respondents and Women’s Status | 51 Fifty-two percent of women agree that a woman is justified in refusing sex for all selected reasons and only 13 percent say that a woman is not justified in refusing sex for any of the selected reasons. In general, women are most likely to justify refusing sex if a woman recently gave birth (80 percent), perhaps because it is a cultural taboo in Malawi to have sex right after birth. Hence this finding may not be a sign of empowerment as much as adherence to an important traditional belief. The next most accepted reasons for refusing sex are the knowledge that the husband has a sexually transmitted disease (74 percent), and if the husband has sex with other women (71 percent). Women are the least likely to agree with refusing sex because the woman is tired or not in the mood (64 percent). There is little variation in this index by background characteristics. The percentage of women who say that a woman is justified in refusing sex for all the specified reasons increases with the woman’s education and independence in decisionmaking. Women in the Southern Region are more likely than women in other regions to agree with all of the reasons for refusing sex (59 percent compared with 51 percent in the Northern Region and 45 percent in the Central Region). Table 3.13.2 looks at the same issue from the men’s perspective. Men are more likely than women to think that wives are justified in refusing sex with their husbands for each of the specified reasons. While 74 percent of women say that a wife is justified to refuse sex with her husband if the husband has a sexually transmitted disease, the corresponding proportion for men is 81 percent. Men are least likely to justify a wife refusing sex because she is tired or not in the mood (67 percent), but they are still slightly more likely to find this reason justifiable than women (64 percent). As in the case of women, there are small variations in this index by background characteristics. The differentials among men are similar to those of women. For example, men in the Southern Region are also more likely than men in other regions to agree with all of the reasons for refusing sex (60 percent compared with 51 percent in the Central Region and 42 percent in the Northern Region). 52 | Characteristics of Respondents and Women’s Status Table 3.13.1 Women's attitude towards refusing sex with husband Percentage of women who believe that a wife is justified in refusing to have sex with her husband for specific reasons, by background characteristics, Malawi 2004 Wife is justified in refusing sex with husband if she: Background characteristic Knows husband has a sexually transmitted disease Knows husband has had sex with other women Has recently given birth Is tired or not in the mood Percentage who agree with all of the specified reasons Percentage who agree with none of the specified reasons Number of women Age 15-19 66.0 65.6 69.1 57.7 47.1 22.1 2,392 20-24 74.2 72.8 81.8 67.2 53.4 10.7 2,870 25-29 76.6 72.7 83.4 65.6 53.5 9.5 2,157 30-34 77.3 73.2 83.6 65.7 53.0 9.5 1,478 35-39 76.7 71.2 83.6 68.6 55.4 10.5 1,117 40-44 75.8 72.0 83.7 65.6 54.0 10.0 935 45-49 76.3 72.8 80.5 61.2 51.9 12.1 749 Marital status Never married 65.9 65.2 65.8 56.7 47.9 24.5 1,970 Married or living together 75.3 72.2 83.0 65.9 53.0 10.3 8,312 Divorced/separated/widowed 76.5 72.9 82.1 66.0 53.8 10.2 1,416 Number of living children 0 67.9 67.0 70.0 58.3 48.2 20.9 2,655 1-2 75.6 72.7 82.9 66.6 53.4 10.0 4,092 3-4 75.7 71.7 82.1 65.8 53.4 10.9 2,726 5+ 75.3 72.4 84.0 65.9 53.5 10.0 2,225 Residence Urban 79.8 76.5 83.8 69.7 61.2 11.1 2,076 Rural 72.6 70.0 79.1 63.3 50.3 13.0 9,621 Region Northern 80.1 71.0 85.3 65.3 51.1 6.7 1,552 Central 68.1 67.0 75.0 55.8 44.6 17.4 4,734 Southern 77.1 74.8 82.8 71.7 59.3 10.3 5,412 Education No education 69.5 65.9 78.1 61.5 46.7 13.6 2,734 Primary 1-4 71.0 69.5 78.5 62.5 49.6 14.8 2,998 Primary 5-8 75.5 72.7 80.8 65.2 53.7 11.8 4,154 Secondary or higher 81.4 78.3 83.3 70.0 61.5 9.8 1,811 Employment Not employed 70.7 69.1 76.7 61.6 50.2 16.1 5,235 Employed for cash 78.4 74.8 84.9 67.4 55.6 9.0 2,033 Employed not for cash 75.5 71.8 81.6 66.2 53.0 10.3 4,417 Number of decisions in which woman has final say1 0 67.8 65.4 71.4 60.3 48.4 19.7 2,945 1-2 74.1 73.0 81.4 66.0 52.8 11.2 4,501 3-4 77.8 73.3 85.0 64.5 51.8 8.2 2,057 5 77.6 73.0 83.7 66.5 56.5 10.5 2,195 Number of reasons wife beating is justified 0 73.5 71.3 78.8 65.4 55.3 14.9 8,395 1-2 76.0 68.7 81.6 59.3 42.2 7.3 1,975 3-4 71.6 73.2 83.6 65.5 45.1 6.5 898 5 75.8 74.7 86.6 66.6 53.6 7.2 430 Wealth quintile Lowest 70.0 67.4 77.5 61.8 48.7 14.6 2,037 Second 71.3 69.5 79.2 63.6 50.0 13.5 2,277 Middle 71.9 68.4 78.4 62.4 48.9 13.1 2,383 Fourth 74.9 71.9 81.1 63.5 51.0 11.7 2,361 Highest 79.9 77.2 82.9 69.6 61.1 11.0 2,639 Total 73.9 71.1 80.0 64.4 52.2 12.7 11,698 Note: Total includes 13 women with missing information on employment. 1 Either by herself or jointly with others Characteristics of Respondents and Women’s Status | 53 Table 3.13.2 Men's attitude towards a woman refusing sex with husband Percentage of men who believe that a wife is justified in refusing to have sex with her husband for specific reasons, by background char- acteristics, Malawi 2004 Wife is justified in refusing sex with husband if she: Background characteristic Knows husband has a sexually transmitted disease Knows husband has had sex with other women Has recently given birth Is tired or not in the mood Percentage who agree with all of the specified reasons Percentage who agree with none of the specified reasons Number of men Age 15-19 75.1 66.3 80.8 58.7 46.8 11.3 650 20-24 80.6 74.1 87.3 65.4 52.8 5.1 587 25-29 82.8 75.0 91.3 71.1 58.1 4.9 634 30-34 81.5 73.2 89.9 70.1 55.5 6.9 485 35-39 87.0 79.3 98.3 70.8 59.2 1.3 294 40-44 84.0 76.6 95.2 69.1 55.8 2.1 282 45-49 87.3 77.8 94.1 64.5 54.3 2.2 182 50-54 80.2 72.4 89.1 62.0 49.3 6.9 148 Marital status Never married 76.7 69.3 82.7 61.7 50.9 9.8 1,084 Married or living together 83.6 75.8 92.6 69.4 55.9 3.9 2,079 Divorced/separated/widowed 83.8 68.3 92.2 56.0 42.2 3.8 98 Residence Urban 84.5 78.5 87.5 69.5 62.7 7.9 669 Rural 80.5 72.1 89.8 65.7 51.5 5.4 2,593 Region Northern 77.0 71.0 87.9 52.2 42.3 7.3 423 Central 80.1 72.1 87.9 62.3 50.9 6.5 1,370 Southern 83.7 75.3 91.0 74.5 59.8 4.9 1,468 Education No education 79.7 70.1 91.3 63.0 47.9 5.2 383 Primary 1-4 76.9 67.8 85.0 61.6 46.8 8.6 798 Primary 5-8 81.2 73.3 90.1 63.9 52.1 4.9 1,220 Secondary or higher 86.2 80.3 91.3 76.2 65.4 5.1 859 Wealth quintile Lowest 80.4 69.7 88.6 57.7 45.4 6.7 412 Second 80.8 74.6 91.5 68.0 52.4 4.2 640 Middle 80.5 71.0 89.8 64.1 49.9 4.4 699 Fourth 81.0 72.0 88.0 66.7 54.2 7.2 709 Highest 83.1 77.7 88.7 71.6 62.3 7.0 802 Total 81.3 73.4 89.3 66.5 53.8 5.9 3,261 Fertility | 55 FERTILITY 4 James Kaphuka The 2004 Malawi Demographic and Health Survey (MDHS) collected information on current and past fertility. A set of carefully worded questions to obtain accurate and reliable data on fertility was administered to measure fertility levels, trends, and differentials. The fertility measures presented here are calculated directly from the birth history. All women age 15-49 were asked to report on all live births. Questions were asked about children still living at home, those living elsewhere, and those who had died. The women were then asked the name, month, and year of birth, sex, survival status, current age (if alive), and age at death (if dead). The accuracy of fertility data is affected primarily by underreporting of births (especially children who died in early infancy) and misreporting of the date of birth. Errors in underreporting of births affect the estimates of fertility levels, while misreporting of dates of births can distort estimates of fertility trends. If these errors vary by socioeconomic characteristics of the women, the differentials in fertility will also be affected. 4.1 CURRENT FERTILITY LEVELS AND TRENDS 4.1.1 Fertility Levels The most commonly used measures of current fertility are the total fertility rate (TFR) and its components, age-specific fertility rates. The TFR is a summary measure of fertility and can be interpreted as the average number of births a hypothetical woman would have at the end of her reproductive life if she were subject to the currently prevailing age-specific fertility rates (ASFRs) throughout her reproductive years (15-49). The ASFRs are a valuable measure of the age pattern of childbearing. They are defined as the number of live births to women in a particular age group divided by the number of woman-years in that age group during the specified period. The TFR is the most significant demographic indicator in the analysis of the impact of national population programmes—in particular, family planning programmes—on individual or group reproductive behaviour. To reduce sampling errors and avoid possible problems of displacement of births, a three-year TFR was computed to provide the most recent estimates of current levels of fertility1. Table 4.1 presents the current TFRs and ASFRs for Malawi by urban-rural residence. The results indicate that a woman in Malawi would, on average, bear 6.0 children in her lifetime if fertility were to remain constant at the current age-specific rates measured in the survey (for the 36 months preceding the survey). The table also shows that urban women have lower fertility than their rural counterparts (4.2 children per woman compared with 6.4 children per woman), and lower 1 Numerators of the ASFRs are calculated by summing the number of live births that occurred in the period 1 to 36 months preceding the survey (determined by the date of interview and the date of birth of the child) and classifying them by the age (in five-year groups) of the mother at the time of birth (determined by the mother’s date of birth). The denominators of the rates are the number of woman-years lived in each of the specified five-year groups during the period 1 to 36 months preceding the survey. 56 | Fertility urban fertility is observed across all age groups. The TFR measured from the 2004 MDHS (6.0) is slightly lower than the TFR measured in the 2000 MDHS (6.3). Examination of the age pattern of fertility rates show that the peak of childbearing in Malawi is at ages 20-24. The same age pattern was observed in the 2000 Malawi DHS. Table 4.1 further shows a general fertility rate of 215 live births per 1,000 women age 15-44 years and a crude birth rate of 42 births per 1,000 population. Compared with other eastern and southern African countries that have participated in the DHS programme, Malawi still has one of the highest fertility rates (see Figure 4.1). Table 4.1 Current fertility Age-specific and cumulative fertility rates, the general fertility rate, and the crude birth rate for the three years preceding the survey, by urban-rural residence, Malawi 2004 Residence Age group Urban Rural Total 15-19 109 175 162 20-24 237 308 293 25-29 195 266 254 30-34 159 233 222 35-39 97 174 163 40-44 29 87 80 45-49 22 37 35 TFR 4.2 6.4 6.0 GFR 162 227 215 CBR 37.0 43.4 42.4 Note: Rates for age group 45-49 may be slightly biased due to truncation. TFR: Total fertility rate for ages 15-49, expressed per woman GFR: General fertility rate (births divided by the number of women age 15-44), expressed per 1,000 women CBR: Crude birth rate, expressed per 1,000 population Fertility | 57 4.1.2 Fertility Differentials This section examines associations between a woman’s background characteristics and her fertility. Fertility varies by residence, educational background, and other background characteristics of a woman. Table 4.2 and Figure 4.2 show fertility differentials by urban-rural residence, region, education, wealth index quintile and by the ten oversampled districts. The analysis of the fertility differentials in this report is done using 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. As noted earlier, urban women have fewer children (average of 4.2 children per woman) than their rural counterparts (6.4 children per woman). This rural-urban difference in the TFR is the same as observed in the 2000 MDHS. There is substantial regional variation in the TFR between the Central and the other two regions. The TFR in the Central Region is 6.4 births per woman, while in the Southern and Northern regions it is 5.8 and 5.6 births per woman, respectively. Among the ten oversampled districts, The TFR varies from 4.8 births per woman in Blantyre to 7.2 per woman in Mangochi. In addition to urban-rural, region, and district differentials, there are variations in TFR when measuring a woman’s education and economic status (measured by the wealth index). Education consistently appears as an important variable in the analysis of fertility-related behaviour. Generally, the TFR declines as educational level increases. Women with no education or with primary education 1-4 have a TFR that is higher than that of women with primary education 5-8 and secondary or higher education levels (Table 4.2). A similar relationship is reflected in the association between fertility rates and the wealth index, which shows that women have fewer children as wealth Figure 4.1 Total Fertility Rates for Selected Sub-Saharan Countries 6.9 6.0 5.9 5.7 5.5 5.0 4.0 2.9 0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 Ug an da 20 00 -01 Ma law i 2 00 4 Za mb ia 20 01 -02 Ta nz an ia 20 04 -0 5 Mo za mb iqu e 2 00 3 Ke ny a 2 00 3 Zim ba bw e 1 99 9 So uth Af ric a 1 99 8 B irt hs p er w om an 58 | Fertility increases. The TFR for women in the lowest (poorest) quintile is 7.1 births per woman, compared with 4.1 births for women in the highest (richest) quintile. Table 4.2 also shows that at the time of the survey 12 percent of women were pregnant. The proportion of pregnant women in urban areas, those with secondary and higher education, and women in the highest wealth quintile is lower than those for the other population subgroups. 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 2004 Background characteristic Total fertility rate1 Percentage currently pregnant1 Mean number of children ever born to women age 40-49 Residence Urban 4.2 8.9 5.7 Rural 6.4 12.8 6.7 Region Northern 5.6 11.2 6.6 Central 6.4 12.3 6.9 Southern 5.8 12.1 6.3 District Blantyre 4.8 11.9 5.4 Kasungu 7.0 12.5 7.4 Machinga 7.0 10.6 6.2 Mangochi 7.2 10.0 6.5 Mzimba 5.5 11.7 6.7 Salima 6.8 15.0 6.5 Thyolo 5.7 14.4 6.1 Zomba 5.3 12.1 6.1 Lilongwe 5.7 10.4 6.5 Mulanje 5.6 13.6 6.0 Other districts 6.3 12.5 6.8 Education No education 6.9 11.8 6.7 Primary 1-4 6.6 14.5 6.8 Primary 5-8 5.8 11.8 6.4 Secondary+ 3.8 9.1 4.7 Wealth quintile Lowest 7.1 12.2 6.9 Second 7.0 14.1 6.5 Middle 6.5 14.4 6.8 Fourth 5.8 12.1 6.8 Highest 4.1 8.1 5.7 Total 6.0 12.1 6.5 1 Women age 15-49 years 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. If fertility had remained stable over time, the two fertility measures, TFR and CEB, would be equal or similar. The findings show that the mean number of children ever born to women age 40-49 (6.5 children per woman) is slightly higher than the TFR for the 3 years preceding the survey (6.0 children per woman), suggesting a slight recent reduction in fertility. Fertility | 59 4.1.3 Trends in Fertility The trend in fertility can be assessed by comparing the current TFR with estimates from previous DHS surveys. Tables 4.3 and 4.4 and Figures 4.3 and 4.4 show changes in fertility rates across four surveys that were conducted in Malawi since the early 1980s: the 1984 Family Formation Survey (FFS), the 1992 MDHS, the 2000 MDHS, and the 2004 MDHS. Direct estimates of fertility for the three years preceding the survey have been used in this comparison, because a three-year rate is more robust than rates based on a shorter period of time. The TFR substantially declined from 7.6 children per woman in the 1984 FFS to 6.7 children per woman in 1992 MDHS, to 6.0 children per woman in 2004. This is a 1.5 child drop in fertility over two decades. Table 4.3 shows that since 1984 fertility has fallen primarily in older age groups (30 and above). The pace of fertility decline varied, but was fastest between 1984 and 1992 and between 2000 and 2004. Table 4.3 Trends in age-specific fertility rates Age-specific fertility rates (per 1,000 women) and total fertility rate for the three years preceding the survey, Malawi 1984-2004 Age group 1984 FFS1 1992 MDHS 2000 MDHS 2004 MDHS 15-19 202 161 172 162 20-24 319 287 305 293 25-29 309 269 272 254 30-34 273 254 219 222 35-39 201 197 167 163 40-44 129 120 94 80 45-49 83 58 41 35 TFR 7.6 6.7 6.3 6.0 1 Data from the Family Formation Survey (FFS) are based on the four years preced- ing the survey. Figure 4.2 Total Fertility Rate by Background Characteristics 4.1 5.8 6.5 7.0 7.1 3.8 5.8 6.6 6.9 5.8 6.4 5.6 6.4 4.2 0 1 2 3 4 5 6 7 8 Highest Fourth Middle Second Lowest WEALTH QUINTILE Secondary + Primary 5 - 8 Primary 1 - 4 No education EDUCATION Southern Central Northern REGION Rural Urban RESIDENCE Births per woman MDHS 2004 60 | Fertility Figure 4.3 Trends in the Total Fertility Rate 1984 FFS, 1992 MDHS, 2000 MDHS, and 2004 MDHS7.6 6.7 6.3 6.0 0 1 2 3 4 5 6 7 8 1984 FFS 1992 MDHS 2000 MDHS 2004 MDHS Note: Rates refer to the 3-year period preceding the survey, except for the FFS rate, which is for the 4-year period before the survey. Figure 4.4 Trends in Age-Specific Fertility Rates 1984 FFS, 1992 MDHS, 2000 MDHS, and 2004 MDHS 0 50 100 150 200 250 300 350 15-19 20-24 25-29 30-34 35-39 40-44 45-49 Age Bi rth s pe r 1 ,0 00 w om en 1984 FFS 1992 MDHS 2000 MDHS 2004 MDHS Fertility | 61 Table 4.4 Trends in fertility by background characteristics Total fertility rate for the three years preceding the survey, by back- ground characteristics, Malawi 1992, 2000, and 2004 Background characteristic 1992 MDHS 2000 MDHS 2004 MDHS Residence Urban 5.5 4.5 4.2 Rural 6.9 6.7 6.4 Region Northern 6.7 6.2 5.6 Central 7.4 6.8 6.4 Southern 6.2 6.0 5.8 District Blantyre na 4.3 4.8 Kasungu na 7.0 7.0 Machinga na 7.0 7.0 Mangochi na 7.4 7.2 Mzimba na 6.7 5.5 Salima na 6.7 6.8 Thyolo na 5.3 5.7 Zomba na 6.2 5.3 Lilongwe na 6.5 5.7 Mulanje na 5.5 5.6 Other districts na 6.8 6.3 Education No education 7.2 7.3 6.9 Primar

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