Liberia - Demographic and Health Survey - 2008

Publication date: 2008

Liberia Demographic and Health Survey 2007 Liberia Demographic and Health Survey 2007 Liberia Institute of Statistics and Geo-Information Services (LISGIS) Monrovia, Liberia Ministry of Health and Social Welfare Monrovia, Liberia National AIDS Control Program Monrovia, Liberia Macro International Inc. Calverton, Maryland, USA June 2008 This report summarizes the findings of the 2007 Liberia Demographic and Health Survey (LDHS) carried out by the Liberia Institute of Statistics and Geo-Information Services (LISGIS), the Ministry of Health and Social Welfare (MOH), and the National AIDS Control Program (NACP). The Government of Liberia provided financial assistance in terms of funding and in-kind contribution of government staff time, office space, and logistical support. Additional funding for the survey was contributed by the U.S. Agency for International Development (USAID), the United Nations Population Fund (UNFPA), the United Nations Development Program (UNDP) and the United Nations Children’s Fund (UNICEF). Macro International provided technical assistance and medical supplies and equipment for the survey through the MEASURE DHS program, which is funded by the USAID and is designed to assist developing countries to collect data on fertility, family planning, and maternal and child health. The UNFPA Country Support Team provided some back-stopping support. The opinions expressed in this report are those of the authors and do not necessarily reflect the views of the donor organizations. Additional information about the survey may be obtained from LISGIS, Statistics House, Tubman Boulevard, Sinkor, P.O. Box 629, Monrovia, Liberia (Telephone: 231-(0)6 810-276; Internet: www.lisgis.org). Information about the DHS program may be obtained from MEASURE DHS, Macro International Inc., 11785 Beltsville Drive, Suite 300, Calverton, MD 20705, U.S.A. (Telephone: 1-301-572-0200; Fax: 1-301-572-0999; E-mail: reports@macrointernational.com; Internet: www.measuredhs.com). Suggested citation: Liberia Institute of Statistics and Geo-Information Services (LISGIS) [Liberia], Ministry of Health and Social Welfare [Liberia], National AIDS Control Program [Liberia], and Macro International Inc. 2008. Liberia Demographic and Health Survey 2007. Monrovia, Liberia: Liberia Institute of Statistics and Geo-Information Services (LISGIS) and Macro International Inc. Contents | iii CONTENTS Page TABLES AND FIGURES . ix FOREWORD . xvii ACKNOWLEDGMENTS . xix SUMMARY OF FINDINGS . xxi MAP OF LIBERIA . xxvi CHAPTER 1 INTRODUCTION 1.1 Objectives and Organization of the Survey . 1 1.2 Survey Organization . 1 1.3 Sample Design . 1 1.4 Questionnaires . 2 1.5 HIV Testing . 3 1.6 Training . 4 1.7 Fieldwork . 5 1.8 Data Processing . 5 1.9 Response Rates . 5 CHAPTER 2 HOUSEHOLD POPULATION AND HOUSING CHARACTERISTICS 2.1 Population by Age and Sex. 7 2.2 Household Composition . 9 2.3 Education of the Household Population . 11 2.3.1 Educational Attainment . 11 2.3.2 School Attendance Rates . 13 2.4 Child Labor . 17 2.5 Child Discipline . 18 2.6 Birth Registration . 20 2.7 Household Environment . 20 2.7.1 Drinking Water . 21 2.7.2 Household Sanitation Facilities . 22 2.7.3 Housing Characteristics . 23 2.8 Household Possessions . 25 2.9 Wealth Index . 26 CHAPTER 3 CHARACTERISTICS OF RESPONDENTS 3.1 Characteristics of Survey Respondents . 29 3.2 Educational Attainment by Background Characteristics . 30 3.3 Literacy . 32 3.4 Access to Mass Media . 34 3.5 Employment . 37 3.6 Occupation . 40 iv � Contents 3.7 Earnings and Type of Employment . 41 3.8 Knowledge and Attitudes Concerning Tuberculosis . 42 3.9 Smoking . 44 CHAPTER 4 FERTILITY 4.1 Current Fertility . 47 4.2 Fertility Differentials by Background Characteristics . 48 4.3 Fertility Trends . 49 4.4 Children Ever Born and Living . 50 4.5 Birth Intervals . 52 4.6 Age at First Birth . 53 4.7 Teenage Pregnancy and Motherhood . 54 CHAPTER 5 FAMILY PLANNING 5.1 Knowledge of Contraceptive Methods . 57 5.2 Ever Use of Contraception . 60 5.3 Current Use of Contraceptive Methods . 61 5.4 Differentials in Contraceptive Use by Background Characteristics . 63 5.5 Trends in Contraceptive Use . 64 5.6 Number of Children at First Use of Contraception . 65 5.7 Knowledge of the Fertile Period . 66 5.8 Source of Contraception . 67 5.9 Cost of Contraception . 68 5.10 Informed Choice . 68 5.11 Future Use of Contraception . 69 5.12 Reasons for Not Intending to Use . 70 5.13 Preferred Method for Future Use . 70 5.14 Exposure to Family Planning Messages . 71 5.15 Contact of Nonusers with Family Planning Providers . 72 5.16 Husband/Partner’s Knowledge of Women’s Contraceptive Use . 73 5.17 Men’s Attitudes Towards Contraception . 75 CHAPTER 6 OTHER DETERMINANTS OF FERTILITY 6.1 Current Marital Status . 77 6.2 Polygyny . 78 6.3 Age at First Marriage . 80 6.4 Age at First Sexual Intercourse . 83 6.5 Recent Sexual Activity . 85 6.6 Postpartum Amenorrhea, Abstinence, and Insusceptibility . 88 6.7 Menopause . 89 CHAPTER 7 FERTILITY PREFERENCES 7.1 Desire for More Children . 91 7.2 Desire to Limit Childbearing by Background Characteristics . 93 7.3 Need for Family Planning Services . 95 7.4 Ideal Number of Children . 97 Contents | v 7.5 Mean Ideal Number of Children by Background Characteristics . 98 7.6 Fertility Planning Status . 98 7.7 Wanted Fertility Rates . 99 CHAPTER 8 INFANT AND CHILD MORTALITY 8.1 Levels and Trends in Infant and Child Mortality . 101 8.2 Data Quality . 103 8.3 Socioeconomic Differentials in Infant and Child Mortality . 105 8.4 Demographic Differentials in Infant and Child Mortality . 106 8.5 Perinatal Mortality . 108 8.6 High-Risk Fertility Behavior . 108 CHAPTER 9 MATERNAL HEALTH 9.1 Prenatal Care . 111 9.2 Number and Timing of Prenatal Care Visits . 112 9.3 Components of Prenatal Care . 113 9.4 Tetanus Toxoid Injections . 115 9.5 Place of Delivery . 116 9.6 Assistance during Delivery . 117 9.7 Postnatal Care . 118 9.8 Problems n Accessing Health Care . 121 CHAPTER 10 CHILD HEALTH 10.1 Child’s Size at Birth . 123 10.2 Vaccination Coverage . 124 10.3 Trends in Vaccination Coverage . 127 10.4 Acute Respiratory Infection . 127 10.5 Fever. 128 10.6 Diarrheal Disease . 130 10.7 Knowledge of ORS Packets . 133 10.8 Stool Disposal . 133 CHAPTER 11 NUTRITION OF CHILDREN AND WOMEN 11.1 Nutritional Status of Children . 135 11.1.1 Measurement of Nutritional Status among Young Children . 135 11.1.2 Results of Data Collection . 136 11.1.3 Levels of Malnutrition . 138 11.2 Initiation of Breastfeeding. 139 11.3 Breastfeeding Status by Age . 140 11.4 Duration and Frequency of Breastfeeding . 142 11.5 Types of Complementary Foods . 143 11.6 Infant and Young Child Feeding (IYCF) Practices . 144 11.7 Micronutrient Intake among Children. 146 11.8 Nutritional Status of Women . 148 11.9 Foods Consumed by Mothers . 150 11.10 Micronutrient Intake among Mothers . 151 vi � Contents CHAPTER 12 MALARIA 12.1 Household Ownership of Mosquito Nets . 153 12.2 Intermittent Preventive Treatment of Malaria in Pregnancy . 155 12.3 Malaria Case Management among Children . 156 CHAPTER 13 HIV/AIDS-RELATED KNOWLEDGE, ATTITUDES, AND BEHAVIOR 13.1 HIV/AIDS Knowledge, Transmission, and Prevention Methods . 159 13.1.1 Awareness of HIV/AIDS . 159 13.1.2 Knowledge of HIV Prevention Methods . 160 13.1.3 Rejection of Misconceptions about HIV/AIDS . 162 13.2 Knowledge of Prevention of Mother-to-Child Transmission of HIV . 164 13.3 Attitudes toward People Living with AIDS . 165 13.4 Attitudes toward Negotiating Safer Sex . 167 13.5 Attitudes Toward Condom and Abstinence Education for Youth . 168 13.6 Higher-Risk Sex . 170 13.6.1 Multiple Partners and Condom Use . 170 13.6.2 Transactional Sex . 172 13.7 Coverage of HIV Counseling and Testing . 173 13.8 Male Circumcision . 175 13.9 Self-Reporting of Sexually Transmitted Infections . 176 13.10 Prevalence of Medical Injections . 178 13.11 HIV/AIDS Knowledge and Sexual Behavior among Youth . 180 13.11.1 HIV/AIDS-Related Knowledge among Young Adults . 180 13.11.2 Knowledge of Condom Sources among Young Adults . 180 13.11.3 Trends in Age at First Sex . 181 13.11.4 Condom Use at First Sex . 182 13.11.5 Abstinence and Premarital Sex . 183 13.11.6 Higher-Risk Sex and Condom Use among Young Adults . 184 13.11.7 Cross-generational Sexual Partners . 187 13.11.8 Drunkenness during Sex among Young Adults . 188 13.11.9 Voluntary HIV Counseling and Testing among Young Adults . 189 CHAPTER 14 HIV PREVALENCE AND ASSOCIATED FACTORS 14.1 Background . 191 14.2 Coverage of HIV Testing . 192 14.2.1 Coverage by Sex, Residence, and Region . 192 14.2.2 Coverage by Socio-demographic Characteristics . 193 14.3 HIV Prevalence . 194 14.3.1 HIV Prevalence by Age and Socioeconomic Characteristics . 194 14.3.2 HIV Prevalence by Sociodemographic Characteristics . 196 14.3.3 HIV Prevalence by Sexual Risk Behavior . 197 14.4 HIV Prevalence among Youth. 199 14.5 HIV Prevalence by Other Characteristics . 201 14.6 HIV Prevalence among Couples . 202 14.7 Conclusions . 203 Contents | vii CHAPTER 15 WOMEN’S EMPOWERMENT AND DEMOGRAPHIC AND HEALTH OUTCOMES 15.1 Employment and Form of Earnings . 205 15.2 Control over Women’s and Men’s Earnings . 206 15.3 Women’s Participation in Household Decisionmaking . 209 15.4 Attitudes Toward Wife Beating . 213 15.5 Attitudes Toward Refusing Sex with Husband . 216 15.6 Women’s Empowerment Indicators . 220 15.7 Current Use of Contraception by Women’s Empowerment Status . 221 15.8 Reproductive Health Care and Women’s Empowerment Status . 222 15.9 Differentials in Infant and Child Mortality by Women’s Status . 223 CHAPTER 16 GENDER-BASED VIOLENCE 16.1 Data Collection . 225 16.2 Physical Violence Since Age 15 . 227 16.3 Sexual Violence . 229 16.4 Marital Control . 231 16.5 Marital Violence . 233 16.6 Frequency of Spousal Violence . 238 16.7 Physical Consequences of Spousal Violence . 239 16.8 Violence Initiated by Women Against Husbands . 239 16.9 Female Genital Cutting . 241 CHAPTER 17 ADULT AND MATERNAL MORTALITY 17.1 Data . 245 17.2 Estimates of Adult Mortality . 246 17.3 Estimates of Maternal Mortality . 247 REFERENCES . 249 APPENDIX A SAMPLE DESIGN AND IMPLEMENTATION A.1 Introduction . 253 A.2 Sampling Frame . 253 A.3 Sampling Procedure and Sample Allocation . 255 A.4 Sampling Probabilities . 256 APPENDIX B ESTIMATES OF SAMPLING ERRORS . 261 APPENDIX C DATA QUALITY TABLES . 273 APPENDIX D PERSONS INVOLVED IN THE 2007 LIBERIA DEMOGRAPHIC AND HEALTH SURVEY . 285 APPENDIX E QUESTIONNAIRES . 289 Tables and Figures | ix TABLES AND FIGURES Page CHAPTER 1 INTRODUCTION Table 1.1 Results of the household and individual interviews . 5 CHAPTER 2 HOUSEHOLD POPULATION AND HOUSING CHARACTERISTICS Table 2.1 Household population by age, sex, and residence . 7 Table 2.2 Household composition . 9 Table 2.3 Children's living arrangements and orphanhood . 10 Table 2.4.1 Educational attainment of the female household population . 12 Table 2.4.2 Educational attainment of the male household population . 13 Table 2.5 School attendance ratios . 14 Table 2.6 School absenteeism . 16 Table 2.7 Reasons for school absenteeism . 17 Table 2.8 Child labor . 18 Table 2.9 Child discipline . 19 Table 2.10 Birth registration of children under age five . 20 Table 2.11 Household drinking water . 22 Table 2.12 Household sanitation facilities . 23 Table 2.13 Household characteristics . 24 Table 2.14 Household durable goods . 26 Table 2.15 Wealth quintiles . 27 Figure 2.1 Population Pyramid . 8 Figure 2.2 Distribution of the Household Population by Single Year of Age . 9 Figure 2.3 Age-Specific School Attendance Rates . 15 CHAPTER 3 CHARACTERISTICS OF RESPONDENTS Table 3.1 Background characteristics of respondents . 30 Table 3.2.1 Educational attainment: Women . 31 Table 3.2.2 Educational attainment: Men . 32 Table 3.3.1 Literacy: Women . 33 Table 3.3.2 Literacy: Men . 34 Table 3.4.1 Exposure to mass media: Women . 35 Table 3.4.2 Exposure to mass media: Men . 36 Table 3.5.1 Employment status: Women . 38 Table 3.5.2 Employment status: Men. 39 Table 3.6.1 Occupation: Women . 40 Table 3.6.2 Occupation: Men . 41 Table 3.7 Type of employment: Women . 42 Table 3.8.1 Knowledge and attitudes concerning tuberculosis: Women . 43 Table 3.8.2 Knowledge and attitudes concerning tuberculosis: Men . 44 Table 3.9 Use of tobacco: Men . 45 x | Tables and Figures Figure 3.1 Exposure to Mass Media at Least Once a Week among Women and Men . 36 Figure 3.2 Women’s Employment Status in the Past 12 Months . 37 CHAPTER 4 FERTILITY Table 4.1 Current fertility . 47 Table 4.2 Fertility by background characteristics . 49 Table 4.3 Trends in fertility from various surveys . 49 Table 4.4 Trends in age-specific fertility rates . 50 Table 4.5 Children ever born and living . 51 Table 4.6 Birth intervals . 52 Table 4.7 Age at first birth . 53 Table 4.8 Median age at first birth . 54 Table 4.9 Teenage pregnancy and motherhood . 55 Figure 4.1 Age-Specific Fertility Rates by Urban-Rural Residence . 48 Figure 4.2 Trends in Total Fertility Rates . 50 CHAPTER 5 FAMILY PLANNING Table 5.1 Knowledge of contraceptive methods . 58 Table 5.2 Knowledge of contraceptive methods by background characteristics . 59 Table 5.3.1 Ever use of contraception: Women . 60 Table 5.3.2 Ever use of contraception: Men . 61 Table 5.4 Current use of contraception by age . 62 Table 5.5 Current use of contraception by background characteristics . 63 Table 5.6 Trends in current use of contraceptive methods . 64 Table 5.7 Number of children at first use of contraception . 66 Table 5.8 Knowledge of fertile period . 66 Table 5.9 Source of modern contraceptive methods . 67 Table 5.10 Cost of modern contraceptive methods . 68 Table 5.11 Informed choice . 69 Table 5.12 Future use of contraception . 70 Table 5.13 Reason for not intending to use contraception in the future . 70 Table 5.14 Preferred method of contraception . 71 Table 5.15 Exposure to family planning messages . 72 Table 5.16 Contact of nonusers with family planning providers . 73 Table 5.17 Husband/partner's knowledge of women's use of contraception . 74 Table 5.18 Male attitudes towards contraceptive use . 75 Figure 5.1 Trends in Knowledge of Contraceptive Methods . 59 Figure 5.2 Differentials in Contraceptive Use . 64 Figure 5.3 Trends in Contraceptive Use . 65 CHAPTER 6 OTHER DETERMINANTS OF FERTILITY Table 6.1 Current marital status . 77 Table 6.2.1 Number of women's co-wives . 79 Table 6.2.2 Number of men's wives . 80 Table 6.3 Age at first marriage . 81 Table 6.4.1 Median age at first marriage: Women . 82 Tables and Figures | xi Table 6.4.2 Median age at first marriage: Men . 82 Table 6.5 Age at first sexual intercourse . 83 Table 6.6.1 Median age at first intercourse: Women . 84 Table 6.6.2 Median age at first intercourse: Men . 85 Table 6.7.1 Recent sexual activity: Women . 86 Table 6.7.2 Recent sexual activity: Men . 87 Table 6.8 Postpartum amenorrhea, abstinence, and insusceptibility . 88 Table 6.9 Median duration of postpartum amenorrhea, abstinence, and insusceptibility . 89 Table 6.10 Menopause . 89 Figure 6.1 Current Marital Status of Women and Men . 78 Figure 6.2 Median Age at First Marriage and First Sex . 84 CHAPTER 7 FERTILITY PREFERENCES Table 7.1 Fertility preferences by number of living children . 92 Table 7.2.1 Desire to limit childbearing: Women . 93 Table 7.2.2 Desire to limit childbearing: Men . 94 Table 7.3 Need and demand for family planning . 96 Table 7.4 Ideal number of children . 97 Table 7.5 Mean ideal number of children . 98 Table 7.6 Fertility planning status . 99 Table 7.7 Wanted fertility rates . 100 Figure 7.1 Fertility Preferences among Married Women . 93 CHAPTER 8 INFANT AND CHILD MORTALITY Table 8.1 Early childhood mortality rates . 102 Table 8.2 Early childhood mortality rates by socioeconomic characteristics . 105 Table 8.3 Early childhood mortality rates by demographic characteristics . 107 Table 8.4 Perinatal mortality . 108 Table 8.5 High-risk fertility behavior . 109 Figure 8.1 Infant and Child Mortality Rates, 2002-06 . 102 Figure 8.2 Trends in Under-Five Mortality Rates . 103 Figure 8.3 Under-Five Mortality Rates for Selected Countries . 103 Figure 8.4 Socioeconomic Differentials in Under-Five Mortality Rates . 106 Figure 8.5 Demographic Differentials in Under-Five Mortality Rates . 107 CHAPTER 9 REPRODUCTIVE HEALTH Table 9.1 Prenatal care . 112 Table 9.2 Number of prenatal care visits and timing of first visit . 113 Table 9.3 Components of prenatal care . 114 Table 9.4 Tetanus toxoid injections . 115 Table 9.5 Place of delivery . 116 Table 9.6 Assistance during delivery . 117 Table 9.7 Timing of first postnatal checkup . 119 Table 9.8 Type of provider of first postnatal checkup . 120 xii | Tables and Figures Table 9.9 Problems in accessing health care . 122 Figure 9.1 Assistance by Skilled Provider during Childbirth . 118 CHAPTER 10 CHILD HEALTH Table 10.1 Child's weight and size at birth . 123 Table 10.2 Vaccinations by source of information . 125 Table 10.3 Vaccinations by background characteristics . 126 Table 10.4 Prevalence and treatment of symptoms of ARI . 128 Table 10.5 Prevalence and treatment of fever . 129 Table 10.6 Prevalence of diarrhea . 130 Table 10.7 Diarrhea treatment . 131 Table 10.8 Feeding practices during diarrhea . 132 Table 10.9 Knowledge of ORS . 133 Table 10.10 Disposal of children's stools . 134 Figure 10.1 Percentage of Children Age 12-23 Months with Specific Vaccinations . 125 CHAPTER 11 NUTRITION OF CHILDREN AND WOMEN Table 11.1 Nutritional status of children . 137 Table 11.2 Initial breastfeeding . 140 Table 11.3 Breastfeeding status by age . 141 Table 11.4 Median duration and frequency of breastfeeding . 143 Table 11.5 Foods and liquids consumed by children in the day or night preceding the interview . 144 Table 11.6 Infant and young child feeding (IYCF) practices . 145 Table 11.7 Micronutrient intake among children . 147 Table 11.8 Nutritional status of women . 149 Table 11.9 Foods consumed by mothers in the day or night preceding the interview . 150 Table 11.10 Micronutrient intake among mothers . 151 Figure 11.1 Nutritional Status of Children by Age . 138 Figure 11.2 Infant Feeding Practices by Age . 142 Figure 11.3 Infant and Young Child Feeding Practices . 146 CHAPTER 12 MALARIA Table 12.1 Ownership of mosquito nets . 154 Table 12.3 Prevalence and treatment of fever . 156 Table 12.4 Type of antimalarial drugs . 157 Table 12.5 Availability at home of antimalarial drugs taken by children with fever . 158 Figure 12.1 Ownership of Mosquito Nets . 154 CHAPTER 13 HIV/AIDS-RELATED KNOWLEDGE, ATTITUDES, AND BEHAVIOR Table 13.1 Knowledge of AIDS . 160 Table 13.2 Knowledge of HIV prevention methods . 161 Table 13.3.1 Comprehensive knowledge about AIDS: Women . 162 Tables and Figures | xiii Table 13.3.2 Comprehensive knowledge about AIDS: Men . 163 Table 13.4 Knowledge of prevention of mother-to-child transmission (MTCT) of HIV . 165 Table 13.5.1 Accepting attitudes toward those living with HIV: Women . 166 Table 13.5.2 Accepting attitudes toward those living with HIV: Men . 167 Table 13.6 Attitudes toward negotiating safer sex with husband . 168 Table 13.7 Adult support of education about condom use to prevent AIDS . 169 Table 13.8.1 Multiple sexual partners and higher-risk sexual intercourse in the past 12 months: Women . 171 Table 13.8.2 Multiple sexual partners and higher-risk sexual intercourse in the past 12 months: Men . 172 Table 13.9 Payment for sexual intercourse and condom use at last paid sexual intercourse . 173 Table 13.10.1 Coverage of prior HIV testing: Women . 174 Table 13.10.2 Coverage of prior HIV testing: Men . 175 Table 13.11 Male circumcision . 176 Table 13.12 Self-reported prevalence of sexually-transmitted infections (STIs) and STI symptoms . 177 Table 13.13 Prevalence of medical injections . 179 Table 13.14 Comprehensive knowledge about AIDS and of a source of condoms among youth . 181 Table 13.15 Age at first sexual intercourse among youth . 182 Table 13.16 Condom use at first sexual intercourse among youth . 183 Table 13.17 Premarital sexual intercourse and condom use during premarital sexual intercourse among youth . 184 Table 13.18.1 Higher-risk sexual intercourse among youth and condom use at last higher-risk intercourse in the past 12 months: Women . 185 Table 13.18.2 Higher-risk sexual intercourse among youth and condom use at last higher-risk intercourse in the past 12 months: Men . 186 Table 13.19 Age mixing in sexual relationships among women age 15-19 . 188 Table 13.20 Drunkenness during sexual intercourse among youth . 189 Table 13.21 Recent HIV tests among youth . 190 Figure 13.1 Women and Men Seeking Advice or Treatment for STIs . 178 Figure 13.2 Type of Facility Where Last Medical Injection Was Received . 180 Figure 13.3 Abstinence, Being Faithful, and Condom Use among Young Women and Men . 187 CHAPTER 14 HIV PREVALENCE AND ASSOCIATED FACTORS Table 14.1 Coverage of HIV testing by residence and region . 192 Table 14.2 Coverage of HIV testing by selected background characteristics . 193 Table 14.3 HIV prevalence by age . 194 Table 14.4 HIV prevalence by socioeconomic characteristics . 195 Table 14.5 HIV prevalence by demographic characteristics . 197 Table 14.6 HIV prevalence by sexual behavior . 198 Table 14.7 HIV prevalence among young people by background characteristics . 199 Table 14.8 HIV prevalence among young people by sexual behavior . 200 Table 14.9 HIV prevalence by other characteristics . 201 Table 14.10 Prior HIV testing by current HIV status . 202 Table 14.11 HIV prevalence among couples . 202 xiv | Tables and Figures Figure 14.1 HIV Prevalence by Age and Socioeconomic Characteristics . 195 CHAPTER 15 WOMEN’S EMPOWERMENT AND DEMOGRAPHIC AND HEALTH OUTCOMES Table 15.1 Employment and cash earnings of currently married women . 206 Table 15.2.1 Control over women's cash earnings and relative magnitude of women's earnings . 207 Table 15.2.2 Control over men's cash earnings . 208 Table 15.3 Woman's control over her own earnings and over those of her husband . 209 Table 15.4.1 Women's participation in decisionmaking . 210 Table 15.4.2 Men’s attitudes toward wives’ participation in decisionmaking . 210 Table 15.5.1 Women's participation in decisionmaking by background characteristics . 211 Table 15.5.2 Men's attitudes toward wife’s participation in decisionmaking . 212 Table 15.6.1 Attitude toward wife beating: Women . 214 Table 15.6.2 Attitudes toward wife beating: Men . 215 Table 15.7.1 Attitudes toward refusing sexual intercourse with husband: Women . 217 Table 15.7.2 Attitudes toward refusing sexual intercourse with husband: Men . 218 Table 15.7.3 Men's attitudes toward a husband's rights when his wife refuses to have sexual intercourse . 219 Table 15.8 Indicators of women's empowerment . 220 Table 15.9 Current use of contraception by women's empowerment . 221 Table 15.10 Reproductive health care by women's empowerment . 222 Table 15.11 Early childhood mortality rates by women's empowerment . 223 Figure 15.1 Number of Decisions in Which Women Participate . 213 CHAPTER 16 GENDER-BASED VIOLENCE Table 16.1 Experience of physical violence . 228 Table 16.2 Persons committing physical violence . 229 Table 16.3 Force at sexual initiation . 229 Table 16.4 Experience of sexual violence . 230 Table 16.5 Persons committing sexual violence . 231 Table 16.6 Degree of marital control exercised by husbands . 232 Table 16.7 Forms of spousal violence . 233 Table 16.8 Spousal violence by background characteristics . 235 Table 16.9 Spousal violence by husband's characteristics and empowerment indicators . 237 Table 16.10 Frequency of spousal violence . 238 Table 16.11 Injuries to women due to spousal violence . 239 Table 16.12 Violence by women against their spouse . 240 Table 16.13 Female genital cutting . 242 Figure 16.1 Percentage of Ever-married Women Age 15-49 Who Have Experienced Various Forms of Physical and Sexual Violence by Their Husband/Partner . 234 CHAPTER 17 ADULT AND MATERNAL MORTALITY Table 17.1 Data on siblings . 246 Tables and Figures | xv Table 17.2 Adult mortality rates . 246 Table 17.3 Maternal mortality . 248 Figure 17.1 Age-Specific Mortality Rates by Sex . 247 APPENDIX A SAMPLE DESIGN AND IMPLEMENTATION Table A.1 Number of 1984 census enumeration areas (EAs) by county and by type of residence . 254 Table A.2 Projected population, percent distribution of the population, and percentage urban by county . 254 Table A.3 Projected population, percent distribution of the population, and percentage urban by region . 255 Table A.4 Sample allocation of clusters and households by reporting domain and residence . 256 Table A.5 Sample allocation of clusters by country and residence . 256 Table A.6 Sample implementation: Women . 258 Table A.7 Sample implementation: Men . 259 APPENDIX B ESTIMATES OF SAMPLING ERRORS Table B.1 List of selected variables for sampling errors . 263 Table B.2 Sampling errors for national sample . 264 Table B.3 Sampling errors for urban sample . 265 Table B.4 Sampling errors for rural sample . 266 Table B.5 Sampling errors for Monrovia sample . 267 Table B.6 Sampling errors for North Western sample . 268 Table B.7 Sampling errors for South Central sample . 269 Table B.8 Sampling errors for South Eastern A sample . 270 Table B.9 Sampling errors for South Eastern B sample . 271 Table B.10 Sampling errors for North Central sample . 272 APPENDIX C DATA QUALITY TABLES Table C.1 Household age distribution . 273 Table C.2.1 Age distribution of eligible and interviewed women . 274 Table C.2.2 Age distribution of eligible and interviewed men . 274 Table C.3 Completeness of reporting . 275 Table C.4 Births by calendar years . 275 Table C.5 Reporting of age at death in days . 276 Table C.6 Reporting of age at death in months . 277 Table C.7 Nutritional status of children . 278 Table C.8 Coverage of HIV testing among interviewed women by social and demographic characteristics . 280 Table C.9 Coverage of HIV testing among interviewed men by social and demographic characteristics . 281 Table C.10 Coverage of HIV testing among interviewed women by sexual behavior characteristics . 282 Table C.11 Coverage of HIV testing among interviewed men by sexual behavior characteristics . 283 Foreword | xvii FOREWORD Prior to the civil crisis, the Government of Liberia had conducted three censuses and several demographic surveys. These censuses included the 1962 Population Census and the 1974 and 1984 Population and Housing Censuses, while the surveys included the 1978 National Demographic Survey (NDS) and the 1986 Liberia Demographic and Health Survey (LDHS). With the exception of few hard copies of the 1984 Population and Housing Census Summary results, most census and survey results that were stored on computer tapes and diskettes or printed out in report form, as well as most of the statistical infrastructure of the country, were extensively damaged or looted during the civil crisis. The economic and demographic situation of Liberia was adversely affected by the civil crisis in substantive terms that are yet to be determined. This state of affairs affected policy decision- making and program development since the precise order of magnitude of population structures and processes were unknown. It was difficult to assess the extent of the large-scale displacement of rural and urban populations, the massive loss of lives caused by the civil crisis, and the destruction of social and physical infrastructure except by recourse to secondary analysis of defective data collected by non-statistical professionals during the crisis. Current information on the demographic processes of mortality and fertility and associated aspect of reproductive health and primary health care was based on projections using unreliable data and dubious data manipulation. There was therefore a strong and dire need for accurate socio-demographic statistics that would help in understanding the dynamics of the Liberian population within the context of the recommendations of international conferences such as the Africa Population Conference held in Dakar, Senegal in 1992; the International Conference on Population and Development held in Cairo, Egypt in 1994 and the Fourth World Conference on Women held in Beijing, China in 1995. Within this context, the Government of Liberia, through the Department of Statistics (DOS) of the Ministry of Planning and Economic Affairs, requested its development partners for assistance to conduct a Demographic and Health Survey with the following objectives: • To contribute towards the construction of a population database for socio-economic development planning as well as for monitoring and evaluating population policy; and • To contribute towards institutional capacity building for the future conduct of national statistical activities, especially the Population and Housing Census undertaken in March 2008. The 2007 Liberia Demographic and Health Survey (LDHS) was undertaken in the administration of President Ellen Johnson-Sirleaf of the Unity Party, and constitutes the third LDHS in the Republic of Liberia. The first LDHS was conducted in 1986 as part of the worldwide DHS program; Liberia was the second country in the world and the first in Africa to conduct a DHS under this program. Liberia undertook the second LDHS in 1999/2000 outside the purview of the international DHS program with no assistance from Macro International. The 2007 LDHS covered the entire country. The survey was designed to collect, compile, analyze and disseminate information on household characteristics, housing, education, maternal health, child health, nutrition, family planning, gender, domestic violence, knowledge and behavior related to HIV/AIDS, and the prevalence of HIV infection. xviii | Foreword The planning of the LDHS commenced in 2005 with the signing of a project document by the Government of Liberia and its development partners. Thereafter, a joint management team comprised of personnel from the Liberia Institute of Statistics and Geo-Information Services (LISGIS), Liberia Institute for Biomedical Research (LIBR), National AIDS Control Program (NACP) and Ministry of Planning and Economic Affairs (MPEA) was established. The secretariat of the joint management team was placed in the LISGIS, which also managed the day-to-day affairs of the project. Two committees, the Project Steering Committee (PSC) and the Project Technical Committee (PTC) were established to assist LISGIS manage the project. The PSC, which consisted of representatives from government ministries/agencies, the University of Liberia, UN agencies and bilateral and multilateral donors, monitored the implementation of the project activities. The PTC, which consisted of representatives from government ministries and agencies, the University of Liberia and local non-government organizations, provided technical advice to the project. The PTC assisted LISGIS to prepare interviewers’ and supervisors’ manuals, the sample frame and sampling methodology, etc. The UNFPA Country Support Team and especially Macro International provided technical backstopping during the implementation of the project. The actual activities of the 2007 LDHS commenced in August 2006, with the identification of selected enumeration areas (EAs) and the household listing, which lasted for about four months. The preparation and finalization of the household and individual questionnaires and supervisors’ and interviewers’ manuals were completed with the assistance of Macro. The recruitment and training of field staff were carried out by Macro and LISGIS staff. The field interview exercise was launched in late December 2006 and lasted until April 2007. The data gathered from the field were electronically processed and edited from January to July 2007. It is our hope that this report will be useful for advocacy, research, policy decision-making, program development, policy formulation, service delivery and socio-economic development planning. There is more information available in the dataset which is available from LISGIS. T. Edward Liberty (Ph.D.) Director General/LISGIS Acknowledgments | xix ACKNOWLEDGMENTS The 2007 Liberia Demographic and Health Survey (LDHS) was undertaken by the Liberian Institute of Statistic and Geo-Information Services (LISGIS), the Ministry of Health and Social Welfare, the Liberia Institute for Biomedical Research and the National AIDS Control Program (NACP). Macro International Inc. and the United Nations Population Fund (UNFPA) Country Support Team provided technical support. The survey was conducted because the Government of Liberia was keen to measure the extent of health-related changes in the Liberian society, especially to determine the basic profile of the population by age, sex, and education; fertility and child mortality rates; maternal and child health indicators; knowledge and attitudes of women and men about sexually transmitted diseases and HIV/AIDS; patterns of recent behavior regarding the use of condoms and other contraceptive methods; and the prevalence of HIV infection. The need to conduct a 2007 LDHS derived from two main factors. The first was the inability to conduct a census since 1984. The second derived from the need to update data collected in the 1986 and 1999-2000 LDHS surveys and to monitor progress made on a number of key indicators related to the Millennium Development Goals (MDGs), reproductive health, gender, and violence against women. The LISGIS is responsible for conducting national surveys and censuses for policy decision- making and development planning. Unfortunately, LISGIS could not conduct this survey alone due to the following reasons: • Financial constraints; • The extensive damage and looting of the then Department of Statistics (DOS) of the Ministry of Planning and Economic Affairs (MPEA)—now known as LISGIS— infrastructure including databases, data processing and transport equipment, office facilities, library and other supplies, etc.; and • The loss of DOS professional personnel, mostly due to exodus into refugee camps in neighboring and other countries and to death as a result of the civil crisis. In view of the foregoing, the Government of Liberia through DOS, requested its development partners—the U.S. Agency for International Development (USAID), the United Nations Population Fund (UNFPA), the United Nations Development Programme (UNDP), and the United Nations Children’s Fund (UNICEF)—for financial, technical and logistical assistance to conduct the 2007 LDHS. The UNFPA responded positively and quickly to assist LISGIS to prepare the project document for signature by the government and its development partners. LISGIS successfully completed the 2007 LDHS because of the substantial inputs of the government and the four partners mentioned above. The sound management and cooperation of the implementers and the technical support provided by Macro and the UNFPA CST also contributed to the successful completion of the survey. In addition, the successful conclusion of the 2007 LDHS is owed to many institutions and individuals that contributed immensely at all levels of the implementation of the project activities, and I wish to extend my sincere thanks and appreciation to them for their tireless contributions. I would like to recognize the President of the Republic of Liberia, Her Excellency Ellen Johnson-Sirleaf, the government and people of Liberia, not only for their support for the 2007 LDHS, but for their support for the development of national official statistics. xx | Acknowledgments Also, I wish to extend my special gratitude to the Chairman and members of the LISGIS Board of Directors and to all the individuals and institutions that contributed immensely to the success of the 2007 LDHS project and those that are listed in Appendix D of this report. Finally, I wish to extend my sincere thanks and appreciation to the survey respondents who took off time from their busy schedule to complete the survey questionnaires as well as others whose names have not been mentioned, but contributed to the successful completion of the 2007 LDHS project. T. Edward Liberty (Ph.D.) Director General/LISGIS Summary of Findings | xxi SUMMARY OF FINDINGS The 2007 Liberia Demographic and Health Survey (LDHS) is the third in a series of DHS surveys to be held in Liberia—the first two hav- ing been implemented in 1986 and 1999-2000— and is the first to include HIV testing on a na- tionally representative sample of adults. Teams visited 298 sample points across Liberia and col- lected data from a nationally representative sam- ple of more than 7,000 women and 6,000 men age 15-49. The primary purpose of the 2007 LDHS is to provide policymakers and planners with detailed information on fertility, family planning, childhood mortality, maternal and child health, domestic violence, maternal mortality, nutrition, knowledge of HIV/AIDS and other sexually transmitted infections, and HIV preva- lence rates. FERTILITY Survey results indicate that there has been a steady decline in the total fertility rate over the past two decades, from 6.6 children per woman in 1981-85 to 5.2 children for the three years be- fore the 2007 LDHS (approximately 2004-06). Fertility continues to be far lower in urban areas than in rural areas (3.8 and 6.2 children per woman, respectively). Regional variations in fer- tility are marked, ranging from a high of almost seven births per woman in South Eastern A to a low of 3.4 births in Monrovia. Women with no education give birth to almost twice as many children as women who have been to secondary school (6.0 vs. 3.3 births). Fertility is also closely associated with wealth, decreasing from 6.5 births among women in the lowest wealth quin- tile to 2.8 births among women in the highest wealth quintile, a difference of almost four births. Research has demonstrated that children born too close to a previous birth are at increased risk of dying. In Liberia, 18 percent of births oc- cur less than 24 months after a previous birth. The interval between births is relatively long; the median interval is 36 months. Childbearing begins early in Liberia. The median age at first birth is 19.1, which is almost unchanged from 19.2 in 1986 and 19.4 in 1999- 2000. Over one-quarter of girls age 15-19 have already had a child. Marriage and sexual initiation patterns are important determinants of fertility levels. Almost two-thirds of women 15-49 are currently mar- ried—42 percent are formally married and 22 percent are living together with a man. The pro- portion of men age 15-49 who are married is lower than for women—57 percent, most proba- bly because men tend to marry later than women. Sixteen percent of married women in Liberia are in polygynous unions. The median age at first marriage is 18.4 years for women age 25-49 compared with 23.9 for men the same age. Women who are currently in their 20s have a slightly higher median age at first marriage than older women, indicating that younger women may be marrying at later ages than women did in the past. Women and men generally do not wait until marriage to initiate sexual activity. The median age at first intercourse is 16.2 years among wom- en and 18.2 years among men age 25-49. Al- though urban and better educated women and men tend to wait longer to get married, the me- dian age at first sexual intercourse is very similar across groups. There is a considerable desire among Libe- rian women to control the number and timing of their births. Thirty-one percent of married women do not want any more children or are sterilized and another 34 percent would like to wait at least two years before their next child. On average, Liberian women would like to have 5.0 children, slightly less than the current fertility rate of 5.2 children per woman. One-quarter of recent births were mistimed (wanted later) and 4 percent were not wanted at all. These results in- dicate that there is a strong need for family plan- ning services, especially for child spacing. xxii � Summary of Findings FAMILY PLANNING Almost all Liberian women and men know of at least one method of contraception. Contra- ceptive pills, condoms, and injectables are known to more than 74 percent of currently mar- ried women and more than 60 percent of married men. A higher proportion of respondents report knowing a modern method than a traditional me- thod. There has been an increase in awareness of family planning methods among women over the last two decades. The proportion of all women age 15-49 who have heard of at least one method of family planning has increased from 72 percent in 1986 to 87 percent in 2007. Knowledge of specific methods shows even more dramatic in- creases since 1986. For example, the proportion of women 15-49 who have heard of the pill in- creased from 64 to 82 percent since 1986, while the proportion who have heard about the male condom increased from 31 percent to 79 percent. More than one-third of currently married women have ever used a contraceptive method; 31 percent have used a modern method and 11 percent have used a traditional method. How- ever, only about one in nine currently married women (11 percent) is currently using some me- thod of contraception. Modern methods of con- traception account for almost all the use, with 10 percent of married women reporting use of a modern method versus only 1 percent using a traditional method. Injectables and pills are the most widely used methods (used by 4 percent of married women each), followed by condoms (2 percent). Contraceptive use has increased from 6 percent of married women in 1986 to 11 percent in 2007. Current use of contraceptives is slightly higher among all women than among those who are currently married. However, use is far higher among unmarried women who are sexually ac- tive (27 percent) than among married women (11 percent) or all women (13 percent). Married women in urban areas are consider- ably more likely to use contraception (19 per- cent) than those in rural areas (8 percent). Use increases with educational attainment, from 8 percent of married women with no education to 21 percent among those who have attended sec- ondary school. Use of contraception also rises as wealth increases, from 4 percent among married women in the lowest wealth category to 20 per- cent among those in the richest. About half of women using modern contra- ceptives (51 percent) obtain their methods from the public sector, mostly from government hos- pitals (21 percent), government health clinics (19 percent), and government health centers (11 per- cent). About one-third (31 percent) of women use the private medical sector to get their contra- ceptives, with the Family Planning Association of Liberia accounting for 10 percent of users and pharmacies for another 10 percent. Eight percent of women using a modern method obtain their method from private hospitals and clinics and 12 percent get their method from other sources, mostly from friends or relatives. Thirty-four percent of currently married women who are not using contraception say they intend to use family planning in the future, 48 percent do not intend to use, and 17 percent are unsure. The most commonly cited reasons for not intending to use are fear of side effects (men- tioned by 27 percent), desire for more children (16 percent), and lack of knowledge of methods (11 percent). There continues to be considerable scope for increased use of family planning in Liberia. Overall, 36 percent of married women in Liberia have an unmet need for family planning services, most of which is due to a need for spacing births (25 percent) rather than a need for limiting births (11 percent). CHILD HEALTH The study of infant and child mortality is critical for assessment of population and health policies and programs. Infant and child mortality rates are also regarded as indices reflecting the degree of poverty and deprivation of a popula- tion. Survey data show that over the past 20 years the under-five mortality has been cut in half, from 220 deaths per 1,000 births measured in the 1986 LDHS to 110 in the 2007 LDHS. Still, one in every nine Liberian children dies before reaching age five. For the most recent five-year period before the 2007 survey (ap- proximately calendar years 2002-06), the infant mortality rate is 71 deaths per 1,000 live births Summary of Findings | xxiii and under-five mortality is 110 deaths per 1,000 live births. The neonatal mortality rate is 32 deaths per 1,000 live births and the postneonatal mortality rate is 39 deaths per 1,000 live births. The child mortality rate is 41 deaths per 1,000 children surviving to age one year. Mortality rates at all ages of childhood show a strong relationship with length of the preceding birth interval. Under-five mortality is more than twice as high among children born less than two years after a preceding sibling than for those born four or more years after a previous child (208 vs. 91 per 1,000 births). Survey results show that only 39 percent of Liberian children age 12-23 months are fully vac- cinated with BCG, measles, and three doses of DPT and polio. Looking at coverage for specific vaccines, 77 percent of children have received the BCG vaccination, 75 percent the first DPT dose, and 83 percent the first polio dose (Polio 1). Cov- erage declines for subsequent doses, with only 50 percent of children receiving the recommended three doses of DPT and 49 percent receiving all three doses of polio. Only 63 percent of children receive the measles vaccine. Twelve percent of children have received no vaccinations at all. Nine percent of children under age five years were reported to have had a cough with short rapid breathing in the two weeks before the survey that was not just due to a blocked or runny nose. About six in ten children with these symptoms were taken to a health facility or provider for treatment. Less likely to be taken for treatment are younger children, rural children, and children whose mothers have less education. Fever is a symptom of malaria and other acute infections in children. Almost six in ten children with fever are taken to a health facility or provider for treatment, and the same propor- tion are given antimalarial drugs. The data indicate that half of the children who were ill with diarrhea in the two weeks before the survey were taken to a health facility or provider. Mothers reported that almost three in four (72 percent) of the children with diarrhea were treated with some form of oral rehydration ther- apy or increased fluids, and over half were given a solution prepared using a packet of oral rehy- dration salts. MATERNAL HEALTH The survey shows that almost eight in ten mothers (79 percent) in Liberia receive prenatal care from a health professional (doctor, nurse, midwife, or physician’s assistant). Sixteen per- cent of mothers receive prenatal care from a tra- ditional midwife and 4 percent of mothers do not receive any prenatal care. In Liberia, two-thirds of mothers have four or more prenatal care visits, almost 20 percent have one to three prenatal care visits, and only 4 percent have no prenatal care at all. The survey also shows that women in Liberia receive prenat- al care services early during pregnancy. Over half of mothers (59 percent) obtain prenatal care in the first three months of pregnancy, and 24 percent make their first visit in the fourth or fifth month. Only 2 percent of women have their first prenatal care visit in their eighth month of preg- nancy or later. Survey results show that more than three- quarters (76 percent) of women age 15-49 with a live birth in the two years preceding the survey took some kind of antimalarial medicine for pre- vention of malaria during the last pregnancy. However, in the vast majority of cases, the prac- tice was not in accordance with the national poli- cy, i.e., only 12 percent of women said they took SP/Fansidar—the recommended drug for inter- mittent preventive treatment of malaria during pregnancy in Liberia—at least once during the pregnancy. This is exactly the same level that was measured in the 2005 Malaria Indicator Sur- vey. Increasing the proportion of babies delivered in health facilities is an important factor in reduc- ing the health risks to both the mother and the baby. LDHS data show that the majority of births in Liberia (61 percent) are delivered at home and 37 percent are delivered in health facilities, most- ly public sector facilities. Just under half (46 per- cent) of births in Liberia are delivered with the help of a health professional (i.e., doctor, nurse/midwife, or physician’s assistant), and 48 percent are delivered by a traditional midwife. Very few births are attended by relatives (4 per- cent) and less than 1 percent of all births are de- livered without any type of assistance at all. xxiv � Summary of Findings Postnatal care coverage is low in Liberia. According to the survey, only 44 percent of mothers receive postnatal care within 4 hours of delivering and almost one-third of mothers (30 percent) do not get any postnatal care. The maternal mortality ratio as measured in the survey is 994 maternal deaths per 100,000 births for the seven-year period before the sur- vey. BREASTFEEDING AND NUTRITION Poor nutritional status is one of the most im- portant health and welfare problems facing Libe- ria today and particularly afflicts women and children. The data show that 39 percent of chil- dren under five are stunted or short for their age and 8 percent of children under five are wasted or too thin for their height. Overall, 19 percent of children are underweight, which may reflect stunting, wasting, or both. As for women, at the national level 10 percent of women are consid- ered to be thin (with a body mass index <18.5); however, only 2 percent of women are consid- ered to be severely thin. Poor breastfeeding and infant feeding prac- tices can have adverse consequences for the health and nutritional status of children. Fortu- nately, breastfeeding in Liberia is almost univer- sal and generally of fairly long duration; 87 per- cent of newborns are breastfed within one day after delivery. However, only 29 percent of in- fants under 6 months are exclusively breastfed, far lower than the recommended 100 percent ex- clusive breastfeeding for children under 6 months. The median duration of any breastfeed- ing is 20 months in Liberia, although the median duration of exclusive breastfeeding is extremely short—less than one month. Infant and young child feeding (IYCF) prac- tices include timely initiation of feeding solid/ semisolid foods from age 6 months and increas- ing the amount and variety of foods and fre- quency of feeding as the child gets older while still maintaining frequent breastfeeding. Guide- lines have been established with respect to IYCF practices for children age 6-23 months. Overall, only one in four Liberian children is fed in ac- cordance with IYCF practices. Ensuring that children between 6 and 59 months receive enough vitamin A may be the single most effective child survival intervention. Survey results show that 43 percent of children age 6-59 months received a vitamin A supple- ment in the six months preceding the survey. Moreover, 79 percent of children age 6-35 months living with the mother consumed foods rich in vitamin A in the 24 hours preceding the survey and 65 percent consumed foods rich in iron. With regard to iron supplements, only 17 percent of children age 6-59 months received an iron supplement in the seven days preceding the survey. HIV/AIDS The HIV/AIDS pandemic is one of the most serious health concerns in the world today be- cause of its high case fatality rate and the lack of a cure. Awareness of AIDS is almost universal among Liberian adults, with 89 percent of wom- en and 93 percent of men saying that they have heard about AIDS. Nevertheless, only 19 percent of women and 32 percent of men are classified as having “comprehensive knowledge” about AIDS, i.e., knowing that consistent use of condoms and having just one faithful partner can reduce the chance of getting infected, knowing that a healthy-looking person can be infected, and knowing that AIDS cannot be transmitted by sharing food or by mosquito bites. Such a low level of knowledge about AIDS implies that a concerted effort is needed to address misconcep- tions about HIV transmission. Programs might be focused in rural areas and especially in North Western, South Eastern A, and South Eastern B regions where comprehensive knowledge is low- est. Moreover, a composite indicator on stigma towards HIV-infected people shows that only 13 percent of women and 22 percent of men ex- pressed accepting attitudes toward persons living with HIV/AIDS. With regard to condom use, only 14 percent of women who had more than one partner in the 12 months before the survey said they used a condom during the most recent sexual inter- course, far lower than the 22 percent reported by men. Among women who reported having had higher-risk intercourse in the past 12 months, only 14 percent used a condom at the last higher- risk sex. For men, the comparable figure is again higher—26 percent. Summary of Findings | xxv Overall, only about one-quarter of women age 15-49 years and one-third of men know where to get an HIV test. Even fewer have ever been tested; only 4 percent of women and 6 per- cent of men have ever had an HIV test and only 2 percent of women and 2 percent of men have been tested and received their test results in the 12 months before the survey. Several recent studies have shown that male circumcision may have a protective effect against HIV infection. The 2007 LDHS shows that male circumcision is widespread in Liberia, with al- most all men being circumcised (98 percent). This is also true for all ages, residence status, and by level of educational achievement. One of the most important elements in the 2007 LDHS was the inclusion of HIV testing among adults who were interviewed. Overall, HIV tests were conducted for 87 percent of the 7,448 eligible women and 80 percent of the 6,476 eligible men age 15-49. Results indicate that 1.5 percent of Liberian adults are infected with HIV. HIV prevalence in women age 15-49 is 1.8 percent and for men age 15-49 it is 1.2 percent. There are very few differ- ences in HIV infection levels according to so- cioeconomic, demographic, and sexual behavior characteristics. DOMESTIC VIOLENCE The 2007 LDHS included a module on do- mestic violence in the Women’s Questionnaire. To protect respondents, only one woman per household was selected to respond to these ques- tions and interviewers were instructed to only ask the questions in strict privacy. The data show that 44 percent of women age 15-49 say they have experienced physical violence since the age of 15. The main perpetrators of violence against women are current or former husbands or part- ners, followed by mothers or stepmothers and fathers or stepfathers. Among ever-married women who have ever been abused, almost 80 percent report that a current or former husband or partner was the perpetrator. Among never- married women, the most common abusers are mothers or stepmothers and fathers or stepfa- thers. Eighteen percent of women age 15-49 re- ported having experienced some form of sexual violence. Sexual violence perpetrated by intimate partners is far more common than sexual vi- olence perpetrated by those who are not intimate partners. Marital violence refers to violence perpe- trated by partners in a marital union. The data show that 35 percent of ever-married women have experienced physical violence by a current or most recent husband or partner, 11 percent have experienced sexual violence, and 36 percent have experienced emotional violence. Overall, just under half (49 percent) of ever-married women have experienced some kind of violence (physical, sexual, or emotional) by a husband or other intimate partner. xxvi | Map of Liberia Atlantic Ocean GUINEA CÔTE D’IVOIRE SIERRA LEONE NORTH CENTRAL SOUTH EASTERN A NORTH WESTERN SOUTH CENTRAL SOUTH EASTERN B MONROVIA /RID 1LPED 6LQRH %RQJ *EDUSROX *UDQG�*HGHK 5LYHU�*HH *UDQG�%DVVD 5LYHU�&HVV %RPL 0DUJLEL *UDQG�.UX *UDQG�&DSH 0RXQW 0DU\ODQG 0RQWVHUUDGR ± LIBERIA 0 100 20050 Kilometers Introduction | 1 INTRODUCTION 1 1.1 OBJECTIVES AND ORGANIZATION OF THE SURVEY The 2007 Liberia Demographic and Health Survey (LDHS) was carried out from late December 2006 to April 2007, using a nationally representative sample of over 7,000 households. All women and men age 15-49 years in these households were eligible to be individually interviewed and were asked to provide a blood sample for HIV testing. The blood samples were dried and carried to the National Laboratory of the Ministry of Health and Social Welfare (MOHSW) on the JFK Hospital compound in Monrovia where they were tested for the human immunodeficiency virus (HIV). The 2007 LDHS was designed to provide data to monitor the population and health situation in Liberia. Specifically, the LDHS collected information on fertility levels, marriage, sexual activity, fertility preferences, awareness and use of family planning methods, breastfeeding practices, nutritional status of women and young children, childhood and maternal mortality, maternal and child health, domestic violence, and awareness and behavior regarding HIV/AIDS and other sexually transmitted infections (STIs). 1.2 SURVEY ORGANIZATION The 2007 LDHS was implemented by the Liberia Institute for Statistics and Geo-Information Services (LISGIS), the MOHSW, and the National AIDS Control Program (NACP). Technical assistance was provided through the MEASURE DHS program, a project sponsored by the United States Agency for International Development (USAID) to carry out population and health surveys in developing countries. Financial support for the survey was provided by the Government of Liberia and a consortium of donors: namely USAID/Liberia, the United Nations Population Fund (UNFPA), the United Nations Development Program (UNDP), and the United Nations Children’s Fund (UNICEF). 1.3 SAMPLE DESIGN The LDHS sample was designed to produce most of the key indicators for the country as a whole, for urban and rural areas separately, and for Monrovia and each of five regions that were formed by grouping the 15 counties. The regional groups are as follows: 1. Greater Monrovia 2. North Western: Bomi, Grand Cape Mount, and Gbarpolu 3. South Central: Montserrado (outside Monrovia), Margibi, and Grand Bassa 4. South Eastern A: River Cess, Sinoe, and Grand Gedeh 5. South Eastern B: Rivergee, Grand Kru, and Maryland 6. North Central: Bong, Nimba, and Lofa Thus, the sample was not spread geographically in proportion to the population, but rather more or less equally across the regions. As a result, the LDHS sample is not self-weighting at the national level, and sample weighting factors have been applied to the survey records in order to bring them into proportion. The survey utilized a two-stage sample design. The first stage involved selecting 300 sample points or clusters from the list of 4,602 enumeration areas (EAs) covered in the 1984 Population Census. This sampling “frame” is more than 20 years old and in the intervening years Liberia has 2 | Introduction experienced a civil war and considerable population change. Many people left the country altogether, others lost their lives, and others moved within the country. For example, some households in rural areas relocated into larger villages in order to be better protected. New communities were established and existing communities expanded, contracted, or even disappeared. Furthermore, as urban areas— especially Monrovia—expanded, some EAs that were previously considered rural may have become urban, but this will not be reflected in the sample frame. Taking all these factors into account, it is obvious that the 1984 census frame is not ideal to be used as the sampling frame; however, it is still the only national frame which covers the whole country. LISGIS conducted a fresh listing of the households residing in the selected sample points and recorded the geographic coordinates (latitude and longitude) of the centre of each cluster (GPS coding). The listing was conducted from March to May 2006. The second stage of selection involved the systematic sampling of 25 of the households listed in each cluster. It later turned out that there was a problem with the sample frame for Monrovia that resulted in two areas being erroneously oversampled. To correct this error, two clusters were dropped altogether, while five others were replaced in order to provide more balance in the selection. Thus, the survey covered a total of 298 clusters—114 urban and 184 rural. All women and men age 15-49 years who were either permanent residents of the households in the sample or visitors present in the household on the night before the survey were eligible to be interviewed in the survey and to give a few drops of blood for HIV testing. 1.4 QUESTIONNAIRES Three questionnaires—a Household Questionnaire, a Women’s Questionnaire, and a Men’s Questionnaire—were used in the survey. The contents of these questionnaires were based on model questionnaires developed by the MEASURE DHS program. In consultation with a group of stakeholders, LISGIS and Macro staff modified the DHS model questionnaires to reflect relevant issues in population, family planning, HIV/AIDS, and other health issues in Liberia. Given that there are dozens of local languages in Liberia, most of which have no accepted written script and are not taught in the schools, and given that English is widely spoken, it was decided not to attempt to translate the questionnaires into vernaculars. However, many of the questions were broken down into a simpler form of Liberian English that interviewers could use with respondents. The Household Questionnaire was used to list all the usual members and visitors in the selected households. Some basic information was collected on the characteristics of each person listed, including age, sex, education, and relationship to the head of the household. The main purpose of the Household Questionnaire was to identify women and men who were eligible for the individual interview. The Household Questionnaire also collected information on characteristics of the household’s dwelling unit, such as the source of water, type of toilet facilities, materials used for the floor and roof of the house, ownership of various durable goods, and ownership and use of mosquito nets. In addition, this questionnaire was also used to record height and weight measurements of women age 15-49 years and of children under the age of 5 years and women’s and men’s consent to volunteer to give blood samples. The HIV testing procedures are described in detail in the next section. The Women’s Questionnaire was used to collect information from all women age 15-49 years and covered the following topics: • Background characteristics (education, residential history, media exposure, etc.) • Reproductive history and child mortality • Knowledge and use of family planning methods • Fertility preferences Introduction | 3 • Prenatal and delivery care • Breastfeeding and infant feeding practices • Vaccinations and childhood illnesses • Marriage and sexual activity • Woman’s work and husband’s background characteristics • Infant and child feeding practices • Awareness and behavior about HIV/AIDS and other STIs • Adult mortality including maternal mortality. The Women’s Questionnaire also included a series of questions to obtain information on women’s experience of domestic violence. These questions were administered to one woman per household. In households with two or more eligible women, special procedures were followed in order to ensure that there was random selection of the woman to be interviewed and that these questions were administered in privacy. The Men’s Questionnaire collected similar information contained in the Woman’s Question- naire, but was shorter because it did not contain questions on reproductive history, maternal and child health, nutrition, maternal mortality, or domestic violence. All aspects of the LDHS data collection were pretested in July 2006. For the pretest, LISGIS recruited 19 people to attend the training, most of whom were LISGIS staff with a few from other organizations involved in the survey, e.g., the NACP. Training was held at the Liberia Bible Society for 11 days from June 20 through July 1. Twelve of the 19 participants were selected to implement the pretest interviewing. Two teams were formed for the pretest, each with one supervisor, three female interviewers. and two male interviewers. Each team covered one rural and one urban EA. Because the work was being done during the period of heavy rainfall, the rural areas selected were off a main paved road, about 1-2 hours’ drive from Monrovia, and the urban areas were both in Monrovia itself. Pretest interviewing took six days, from July 4 through July 9. In total, the teams completed inter- views with 95 households, 82 women and 60 men, and collected 118 blood samples. The pretest resulted in deleting some questions and making modifications in others. 1.5 HIV TESTING All eligible women and men age 15-49 who were interviewed were asked to voluntarily provide some drops of blood for HIV testing. The protocol for the blood specimen collection and analysis was based on the anonymous linked protocol developed by DHS and approved by Macro International’s Institutional Review Board. The protocol for the LDHS was also reviewed and approved by the Liberian National Ethics Committee on Bio-Medical Research. The protocol allows for merging the HIV results with the sociodemographic data collected in the individual question- naires, provided that the information that could potentially identify an individual is destroyed before the linking is effected. This requires that identification codes be deleted from the data file and that the back page of the Household Questionnaire that contains the bar code labels and names of respondents be destroyed before merging the HIV results with the individual data file. To obtain informed consent for collection of a blood sample for HIV testing, interviewers explained the procedures, the confidentiality of the data, and the fact that test results could not be linked or made available to the subject, and informed respondents how they could establish their HIV status through voluntary counseling and testing (VCT) services. Interviewers then collected a dried blood spot sample on a filter paper card using blood from a finger prick with a single-use, spring- loaded, sterile lancet. Each blood sample was given a bar code label, with a duplicate label attached to the Household Questionnaire on the line showing consent for that respondent. A third copy of the same bar code label was affixed to a Blood Sample Transmittal Form in order to track the blood samples from the field to the laboratory. Filter papers were dried overnight in a plastic drying box, after which they were packed in individual airtight bags with desiccants and a humidity indicator card and placed in a larger airtight bag for each sample point. Blood samples were periodically collected in 4 | Introduction the field. along with the completed questionnaires, and transported to LISGIS headquarters in Monrovia to be logged in, after which they were taken to the National Laboratory of the MOHSW at the JFK Hospital compound for HIV testing. At the laboratory, the bar code labels on the dried blood spot samples were scanned into the computer using a program developed by Macro that preassigns to each sample a sequential number for ease in tracking. The blood spots were kept refrigerated or frozen depending on how long it would be until they could be tested. After the samples were allowed to attain room temperature, a circle (a completely filled and well saturated spot without blood clot) of at least 6.3 mm in diameter was taken from each filter paper using a hole punch. Each blot was placed into its preassigned well in the elution plate that contained 200 μl of phosphate buffered saline (PBS, pH 7.3-7.4) and left in the refrigerator overnight at 2-8° C. These eluates were then diluted and tested with Vironostika HIV Uniform II Plus O (BioMerieux). All positive samples and 10% of negatives were then tested with the Enzygnost Anti-HIV 1/2 Plus enzyme-linked immunosorbent assay (ELISA) test kit (Dade-Behring). Finally, any discordant samples were tested on Western Blot 2.2 (Abbott) to resolve the discrepancies. Positive samples were also tested with Pepti-Lav 1/2 (BioRad) to differentiate HIV-1 and HIV-2. Before the survey, the laboratory had some experience using its ELISA machine for measles and yellow fever testing, but no experience with ELISA testing for HIV. Macro laboratory specialists and a consultant worked with the lab staff to purchase and install a new refrigerator and a new freezer, as well as other equipment and supplies, and trained six laboratory technicians in how to run the various tests. In part as a means of training and for checking the validity of the HIV testing protocol, the Macro laboratory specialist also worked with lab staff to conduct a validation study. For this study, after obtaining informed consent, they collected both venous and capillary blood samples from 40 known HIV-positive and 40 known HIV-negative individuals from various sites in Monrovia, including the VCT centre at JFK Hospital, the Catholic Hospital, and an association for HIV-positive individuals (LIGHT). The comparison of the venous and dried blood spot samples showed a very high correlation. The HIV test results were merged with the individual questionnaire records after the ques- tionnaires were destroyed and the cluster numbers scrambled. 1.6 TRAINING LISGIS recruited 122 field staff candidates from Monrovia, mostly by word of mouth. Many of the candidates had participated in either the LDHS pretest or a prior survey. LISGIS then organized a four-week training course from November 14 through December 9 at the LISGIS Headquarters in Monrovia. Trainers included four staff who participated in the LDHS pretest and two Macro staff. Training consisted mainly of lectures followed by mock interviews between trainees. Three quizzes were administered, graded, and reviewed. The third week of training consisted largely of instructions on how to take anthropometric measurements and procedures for HIV testing (how to administer informed consent, how to take blood spot samples, how to dry the filter papers, and how to pack them the next morning). During the final week of training, participants had two field practice sessions in which they were divided into teams and conducted interviews with households located in Monrovia. After several meetings, senior LDHS staff and the trainers decided on the final assignment of participants to teams. Unfortunately, the pool of candidates did not include a sufficient number of speakers of all the local dialects spoken in the sampled areas. Although English is widely spoken, it is preferable to be able to conduct the interviews in respondents’ dialects, given the sensitivity and complexity of some of the questions. Also, because the vehicles could only hold six people, it was decided not to have a field editor on each team and instead ask one of the interviewers to help the supervisor in checking questionnaires when the workload was heavy. The final day of training Introduction | 5 consisted of a session with the team supervisors to train them on how to supervise fieldwork and edit completed questionnaires. 1.7 FIELDWORK A total of 19 teams—each comprising one supervisor, two female interviewers, two male interviewers, and one driver—were organized for the data collection. Two senior staff from LISGIS and one from the NACP were designated as field coordinators and were each assigned a number of teams to monitor. Data collection started on December 25, 2006. Several weeks later, a review of completed questionnaires showed considerable errors, low response rates, and lack of attention to details. Consequently, all teams were recalled to Monrovia for two days of additional training and three teams were relieved of their duties altogether. The remaining 16 teams continued with data collection until April 2007. A number of challenges were faced by the field teams. There were several road accidents, including one in which the vehicle turned over on Christmas Eve, thankfully causing no serious injuries. In several clusters, many selected households had moved or could not be found. 1.8 DATA PROCESSING The processing of the LDHS data began a few weeks after the fieldwork commenced. Completed questionnaires were returned periodically from the field to the LISGIS office in Monrovia, where they were coded by data processing personnel recruited and trained for this task. The data processing staff consisted of two supervisors from LISGIS, four questionnaire administrators/coding clerks, and 14 data entry operators, all of whom were trained by Macro staff. Data were entered using the CSPro computer package. All data were entered twice (100 percent verification). The concurrent processing of the data was a distinct advantage for data quality, because LISGIS was able to advise field teams of errors detected during data entry. The data entry and editing phase of the survey was completed in early July 2007. 1.9 RESPONSE RATES Table 1.1 shows response rates for the 2007 LDHS. A total of 7,471 households were selected in the sample, of which 7,021 were found occupied at the time of the fieldwork. The shortfall is largely due to households that were away for an extended period of time and structures that were found to be vacant or destroyed. Of the existing households, 6,824 were successfully inter- viewed, yielding a household response rate of 97 percent. In the households interviewed in the survey, a total of 7,448 eligible women were identified, of whom 7,092 were successfully interviewed, yielding a response rate of 95 percent. With regard to the male survey results, 6,476 eligible men were identified, of whom 6,009 were successfully interviewed, yielding a response rate of 93 percent. The response rates are lower in the urban than rural sample, especially for men. Table 1.1 Results of the household and individual interviews Number of households, number of interviews, and response rates, according to residence (unweighted), Liberia 2007 Residence Result Urban Rural Total Household interviews Households selected 2,868 4,603 7,471 Households occupied 2,720 4,301 7,021 Households interviewed 2,606 4,218 6,824 Household response rate1 95.8 98.1 97.2 Interviews with women age 15-49 Number of eligible women 3,376 4,072 7,448 Number of eligible women interviewed 3,194 3,898 7,092 Eligible women response rate2 94.6 95.7 95.2 Interviews with men age 15-49 Number of eligible men 2,801 3,675 6,476 Number of eligible men interviewed 2,531 3,478 6,009 Eligible men response rate2 90.4 94.6 92.8 1 Households interviewed/households occupied 2 Respondents interviewed/eligible respondents 6 | Introduction The principal reason for nonresponse among eligible men and women was the failure to find individuals at home despite repeated visits to the household, followed by refusal to be interviewed. The substantially lower response rate for men reflects the more frequent and longer absence of men from the households. Household Population and Housing Characteristics | 7 HOUSEHOLD POPULATION AND HOUSING CHARACTERISTICS 2 The purpose of this chapter is to provide a descriptive summary of some demographic and socioeconomic characteristics of the population in the households sampled in the 2007 Liberia Demographic and Health Survey (LDHS), as well as characteristics of the dwelling units themselves. For the purpose of the 2007 LDHS, a household was defined as a person or a group of persons, related or unrelated, who live together and share a common source of food. The Household Questionnaire (see Appendix E) included a schedule collecting basic demographic and socioeconomic information (e.g., age, sex, educational attainment, and current school attendance) for all usual residents and visitors who spent the night preceding the interview. This method of data collection allows the analysis of the results for either the de jure (usual residents) or de facto (those who are there at the time of the survey) populations. The Household Questionnaire also obtained information on housing facilities (e.g., sources of water supply, sanitation facilities) and household possessions. These latter items are used to create an index of relative wealth, which is described later in this chapter. The information presented in this chapter is intended to facilitate interpretation of the key demographic, socioeconomic, and health indicators presented later in the report. It is also intended to assist in the assessment of the representativeness of the survey sample. 2.1 POPULATION BY AGE AND SEX Age and sex are important demographic variables and are the primary basis of demographic classification. The distribution of the de facto household population in the 2007 LDHS is shown in Table 2.1 by five-year age groups, according to sex and residence. 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, Liberia 2007 Urban Rural Total Age Male Female Total Male Female Total Male Female Total <5 15.7 13.3 14.4 20.6 18.7 19.6 18.8 16.6 17.7 5-9 14.7 15.0 14.9 17.4 16.6 17.0 16.4 16.0 16.2 10-14 16.3 15.3 15.8 12.9 10.8 11.9 14.1 12.6 13.3 15-19 9.1 11.2 10.2 7.0 6.4 6.7 7.8 8.2 8.0 20-24 9.0 10.3 9.7 5.8 7.7 6.8 6.9 8.7 7.9 25-29 6.6 8.1 7.4 5.6 7.0 6.3 6.0 7.4 6.7 30-34 5.4 6.4 6.0 4.7 5.8 5.3 5.0 6.1 5.5 35-39 5.2 5.7 5.4 5.6 5.9 5.8 5.5 5.8 5.6 40-44 4.5 3.9 4.2 4.3 4.2 4.2 4.3 4.1 4.2 45-49 3.7 2.9 3.3 4.2 4.7 4.4 4.0 4.0 4.0 50-54 3.9 3.2 3.5 3.5 4.0 3.7 3.6 3.7 3.6 55-59 2.2 1.6 1.9 2.6 2.4 2.5 2.5 2.1 2.3 60-64 1.4 1.0 1.2 1.9 1.8 1.8 1.7 1.5 1.6 65-69 1.0 1.0 1.0 1.8 1.5 1.6 1.5 1.3 1.4 70-74 0.6 0.4 0.5 0.7 0.8 0.8 0.7 0.7 0.7 75-79 0.4 0.4 0.4 0.7 0.9 0.8 0.6 0.7 0.7 80 + 0.3 0.3 0.3 0.8 0.6 0.7 0.6 0.5 0.6 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Number 5,942 6,632 12,575 10,365 10,516 20,881 16,307 17,149 33,456 8 | Household Population and Housing Characteristics The 2007 LDHS enumerated a population of 33,456 persons. Just under half of the population (49 percent) is male and 51 percent is female. The results indicate an overall sex ratio of 95 males per 100 females. The sex ratio is higher in rural areas (99 males per 100 females) than urban areas (90 males per 100 females). The population age structure shows a substantially larger proportion of persons in younger age groups than in the older age groups for each sex (Figure 2.1). This is a reflection of the young age structure of the population of Liberia and indicates a population with high fertility. Forty-seven percent of the population are below 15 years of age, 49 percent are in the age group 15-64, and 3 percent are age 65 or older. However, there is an implausibly large drop-off between ages 10-14 and 15-19. Examination of the distribution of the household population by single year of age (Table �.1 and Figure 2.2) shows evidence that interviewers may have intentionally underestimated respondents’ ages to be younger than the age cut-off of 15 so as to make them ineligible for the individual interview. 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 LDHS 2007 Male Percent Female Age Household Population and Housing Characteristics | 9 2.2 HOUSEHOLD COMPOSITION Information on key aspects of the composition of households, including the sex of the head of the household and the size of the household, is presented in Table 2.2. These characteristics are important because they are associated with the welfare of the household. The sex of the head of the house- hold is sometimes related to socio-economic status of the household. Economic resources are often more limited in larger households. Moreover, where the size of the household is large, crowding also can lead to health problems. Households in Liberia are predomi- nantly male-headed (69 percent), a common feature in African countries. Nevertheless, more than three in ten households are headed by women, and the proportion of female- headed households is higher in urban than rural areas. Liberian households most commonly consist of four or five members, with the average household size being five persons. Overall, 11 percent of households have nine or more members. Urban households are slightly larger than rural households. Table 2.2 Household composition Percent distribution of households by sex of head of household and by household size, mean size of household, and percentage of households with orphans and foster children under 18, according to residence, Liberia 2007 Residence Characteristic Urban Rural Total Household headship Male 64.9 71.2 68.9 Female 35.1 28.8 31.1 Total 100.0 100.0 100.0 Number of usual members 1 8.2 6.8 7.3 2 8.9 8.5 8.7 3 13.4 14.8 14.3 4 17.1 18.3 17.9 5 15.1 16.6 16.0 6 11.3 11.6 11.5 7 8.0 7.6 7.7 8 5.5 6.1 5.9 9+ 12.4 9.5 10.6 Total 100.0 100.0 100.0 Mean size of households 5.2 5.0 5.0 Percentage of households with orphans and foster children under 18 Foster children1 37.7 26.7 30.7 Double orphans 1.7 1.4 1.5 Single orphans 9.6 10.5 10.2 Foster and/or orphan children 40.0 31.4 34.5 Number of households 2,486 4,338 6,824 Note: Table is based on de jure household members, i.e., usual residents. 1 Foster children are those under age 18 living in households with neither their mother nor their father present. Figure 2.2 Distribution of the Household Population by Single Year of Age � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 0 5 10 15 20 25 30 35 40 45 50 0 1 2 3 4 5 Percent Male Female� � LDHS 2007 10 | Household Population and Housing Characteristics In Liberia, 31 percent of households have at least one foster child, i.e., a child under 18 years who is not living with either of their natural parents. The proportion is much higher (38 percent) in urban areas than rural areas (27 percent). Ten percent of households have a single orphan and 2 percent have double orphans. Thirty-five percent of households in Liberia have either foster or orphan children. The percentage is much higher (40 percent) in urban areas than in rural areas (31 percent). Detailed information on households with orphans and foster children less than 18 years is presented in Table 2.3. Just under half (48 percent) of children under 18 live with both of their biological parents, 21 percent live with only their mother, 9 percent live with only their father, and 21 percent live with neither parent. Eighteen percent of children live with only their mothers even though their fathers are alive, 8 percent live with only their fathers even though their mothers are alive, and 18 percent live with neither parent even though both parents are alive. Five percent of children under 18 do not have a father alive and 3 percent do not have a mother alive. Seven percent of children under 18 have either a mother, father, or both dead. Table 2.3 Children's living arrangements and orphanhood Percent distribution of de jure children under age 18 by living arrangements and survival status of parents, the percentage of children not living with a biological parent, and the percentage of children with one or both parents dead, according to background characteristics, Liberia 2007 Living with mother but not with father Living with father but not with mother Missing informa- tion on father/ mother Total Percentage not living with a biological parent Percentage with one or both parents dead Number of children Living with both parents Not living with either parent Only father alive Only mother alive Background characteristic Father alive Father dead Mother alive Mother dead Both alive Both dead Age 0-4 56.2 25.4 1.9 4.1 0.4 9.1 0.3 0.6 0.2 1.7 100.0 10.2 3.4 6,028 <2 58.9 32.0 0.8 1.5 0.3 4.4 0.2 0.2 0.1 1.6 100.0 5.0 1.6 2,300 2-4 54.6 21.3 2.5 5.8 0.5 12.0 0.3 0.9 0.2 1.8 100.0 13.5 4.6 3,727 5-9 48.0 15.8 2.2 9.2 1.1 19.1 0.9 1.8 0.8 1.2 100.0 22.5 6.8 5,533 10-14 40.5 12.8 3.5 10.9 1.4 24.3 1.6 2.6 1.2 1.1 100.0 29.8 10.4 4,535 15-17 34.7 12.9 4.6 11.0 1.8 24.9 1.0 4.7 1.4 3.0 100.0 32.0 13.7 1,629 Sex Male 48.1 17.8 2.5 9.0 1.1 16.4 0.9 1.9 0.7 1.7 100.0 19.9 7.1 8,988 Female 47.2 18.3 2.8 7.1 1.0 18.7 0.8 1.9 0.8 1.4 100.0 22.3 7.3 8,736 Residence Urban 38.5 22.1 1.9 8.3 0.5 23.4 1.1 2.0 0.8 1.4 100.0 27.3 6.3 6,512 Rural 52.9 15.6 3.1 7.9 1.3 14.2 0.8 1.8 0.7 1.6 100.0 17.4 7.7 11,212 Region Monrovia 36.7 23.0 1.4 8.2 0.5 24.9 1.2 2.0 0.8 1.4 100.0 28.8 5.9 4,755 North Western 43.1 19.6 6.0 5.3 0.6 15.9 1.0 3.9 1.3 3.2 100.0 22.1 12.8 1,399 South Central 51.3 15.8 2.4 9.5 1.3 14.9 0.9 1.5 1.1 1.4 100.0 18.3 7.2 2,541 South Eastern A 56.3 13.9 1.7 9.4 0.6 12.8 1.1 1.3 0.8 2.0 100.0 16.0 5.5 1,188 South Eastern B 52.4 16.5 3.4 6.5 1.0 15.3 1.3 2.0 1.0 0.6 100.0 19.6 8.7 1,312 North Central 52.6 16.0 2.9 8.1 1.5 15.0 0.5 1.6 0.4 1.5 100.0 17.5 6.9 6,529 Wealth quintile Lowest 53.6 15.8 3.7 7.3 1.9 13.9 0.7 1.2 0.7 1.3 100.0 16.5 8.2 3,505 Second 57.6 14.7 3.2 7.2 0.9 11.9 0.8 1.5 0.8 1.5 100.0 14.9 7.1 3,560 Middle 49.3 17.9 2.8 7.1 1.0 15.4 1.0 2.0 0.9 2.5 100.0 19.4 7.7 3,605 Fourth 40.2 23.1 2.6 8.0 0.9 20.0 0.8 2.6 0.5 1.3 100.0 23.9 7.5 3,646 Highest 37.3 18.5 1.0 10.8 0.4 27.0 1.1 2.0 0.9 1.1 100.0 31.0 5.4 3,408 Total <15 48.9 18.5 2.4 7.8 0.9 16.8 0.9 1.6 0.7 1.4 100.0 20.0 6.5 16,095 Total <18 47.6 18.0 2.6 8.1 1.0 17.6 0.9 1.9 0.7 1.5 100.0 21.1 7.2 17,724 Note: Table is based on de jure members, i.e., usual residents. Household Population and Housing Characteristics | 11 The percentage of children living with both of their biological parents decreases with increasing age of the child. Rural children are more likely to live with both parents than urban children. The highest proportion of children living with both parents is in the South Eastern A region (56 percent) and the lowest proportion is in Monrovia (37 percent). Interestingly, the proportion of children under 18 who are living with both parents generally decreases with increasing wealth.1 Among children in the highest wealth quintile, more than one-quarter are not living with either of their biological parents even though both are alive. 2.3 EDUCATION OF THE HOUSEHOLD POPULATION Education is a key determinant of the lifestyle and status an individual enjoys in a society. Studies have consistently shown that educational attainment has a strong effect on health behaviors and attitudes. In general, the higher the level of education a woman has attained, the more knowledgeable she is about the use of health facilities, family planning methods, and the health of her children. Results from the 2007 LDHS can be used to look at educational attainment and current school attendance among household members. Liberia’s education system has been unstable for a little more than 15 years because of the civil crisis; however, a major restructuring of the infrastructure and program is being undertaken by the government. Presently, the government of Liberia has adopted a free primary education policy in all government schools with a special program for female education. The government is undertaking massive renovation of infrastructure damaged during the war and is also restructuring and expanding programs in the educational system. For the purposes of the analysis presented below, age 6 is used as the age for entry into the primary level. Because of the war, however, many children who should have started school when they reached school-going age never got to start school at all. Officially, primary school consists of six years of education, and junior high school and senior high school each consist of three years. 2.3.1 Educational Attainment Tables 2.4.1 and 2.4.2 show the percent distribution of the de facto female and male household population age six and over by highest level of education attended, according to background characteristics. The LDHS results show that the majority of Liberians have little education, with females much less educated than males. Fifty-six percent of females and 39 percent of males have never attended any school, and 25 percent of females and 26 percent males have only some primary education. Only 5 percent of females and 13 percent of males have completed secondary or higher education. However, with the introduction of compulsory free primary education in all government schools and renovation and rebuilding of schools that were damaged during the civil war, there will be an improvement in educational attainment as well as a reduction in the gap between male and female educational attainment in the country. The proportion of the population with no education is high among the youngest children, many of whom may not have yet started school. The proportion decreases with age up to those in their teens and early 20s, after which it increases among the older population. Urban residents tend to be considerably more educated than their rural counterparts. For example, the proportion of women who have attended some secondary school is five times higher in urban than rural areas (29 percent vs. 6 percent, respectively). On a regional basis, the highest proportions of the population with no education are found in North Western region for both females and males, while the lowest proportions are observed for Monrovia. For example, 70 percent of females in North Western have no education, compared with only 34 percent of those in Monrovia. As expected, educational attainment is highly correlated with household wealth. The proportion of women with no education decreases from 77 percent among those in the lowest wealth quintile to 28 percent among those in the highest quintile. 1 See Section 2.9 for a description of how the wealth index was calculated. 12 | Household Population and Housing Characteristics Table 2.4.1 Educational attainment of the female household population Percent distribution of the de facto female household population age six and over by highest level of schooling attended or completed and median grade completed, according to background characteristics, Liberia 2007 Background characteristic No education Some primary Completed primary1 Some secondary Completed secondary or higher2 Don't know/ missing Total Number Median years completed Age 6-9 86.5 13.1 0.1 0.0 0.0 0.3 100.0 2,242 0.0 10-14 43.8 50.3 3.3 2.3 0.0 0.3 100.0 2,153 0.3 15-19 19.4 48.8 7.7 22.6 1.0 0.4 100.0 1,414 3.3 20-24 30.1 29.4 6.0 27.3 7.0 0.2 100.0 1,497 3.7 25-29 43.4 25.7 3.7 15.5 11.4 0.3 100.0 1,277 1.4 30-34 50.3 21.2 4.5 11.8 11.6 0.6 100.0 1,039 0.0 35-39 55.1 15.6 4.3 13.3 11.1 0.7 100.0 1,001 0.0 40-44 60.7 13.8 3.5 13.6 7.9 0.5 100.0 697 0.0 45-49 74.6 10.7 1.0 5.8 6.9 1.0 100.0 688 0.0 50-54 78.8 5.9 1.4 4.8 6.3 2.7 100.0 629 0.0 55-59 86.0 5.5 0.4 2.3 5.4 0.3 100.0 365 0.0 60-64 89.5 2.8 0.4 0.2 3.4 3.7 100.0 255 0.0 65+ 89.2 1.5 0.4 1.0 1.6 6.4 100.0 540 0.0 Residence Urban 37.5 28.1 4.8 18.3 10.6 0.7 100.0 5,597 2.1 Rural 68.2 23.0 2.3 4.7 1.0 0.9 100.0 8,208 0.0 Region Monrovia 34.0 27.8 4.9 20.0 12.9 0.4 100.0 4,275 2.9 North Western 70.3 19.5 2.8 5.0 0.9 1.6 100.0 1,077 0.0 South Central 64.3 22.8 2.5 7.7 2.3 0.4 100.0 1,945 0.0 South Eastern A 63.7 25.4 3.6 4.3 0.7 2.2 100.0 776 0.0 South Eastern B 55.2 33.0 3.4 6.9 0.9 0.5 100.0 909 0.0 North Central 67.2 23.1 2.2 5.3 1.1 1.0 100.0 4,824 0.0 Wealth quintile Lowest 76.7 18.4 1.6 2.3 0.2 0.8 100.0 2,607 0.0 Second 72.2 20.8 2.1 3.5 0.3 1.1 100.0 2,551 0.0 Middle 58.3 28.2 3.9 7.1 1.3 1.3 100.0 2,664 0.0 Fourth 49.2 27.0 4.0 14.8 4.4 0.7 100.0 2,934 0.0 Highest 28.2 29.7 4.5 20.9 16.4 0.3 100.0 3,049 3.6 Total 55.8 25.0 3.3 10.2 4.9 0.8 100.0 13,805 0.0 1 Completed grade 6 at the primary level 2 Completed grade 12 at the secondary level Comparison of data from 2007 with the 1999-2000 LDHS shows that there has been some improvement in educational attainment.2 For example, between 1999-2000 and 2007, the proportion of those age 15-19 years who completed primary school increased from 23 to 31 percent for females and from 31 to 36 percent for males. Among those age 20-24, the proportions who completed primary school increased from 34 to 40 percent among women and from 56 to 64 percent among men. 2 Data for the 1999-2000 LDHS were tabulated for the population age five and over and in terms of the level of education completed; the differences in tabulations make comparisons more difficult. Household Population and Housing Characteristics | 13 Table 2.4.2 Educational attainment of the male household population Percent distribution of the de facto male household population age six and over by highest level of schooling attended or completed and median grade completed, according to background characteristics, Liberia 2007 Background characteristic No education Some primary Completed primary1 Some secondary Completed secondary or higher2 Don't know/ missing Total Number Median years completed Age 6-9 86.5 12.8 0.1 0.0 0.0 0.7 100.0 2,220 0.0 10-14 42.2 52.2 2.7 2.6 0.0 0.3 100.0 2,304 0.3 15-19 11.4 52.3 8.6 26.5 0.9 0.2 100.0 1,265 3.9 20-24 11.0 25.0 7.3 45.5 11.1 0.1 100.0 1,133 6.5 25-29 22.7 19.0 5.1 33.1 19.6 0.5 100.0 975 6.3 30-34 20.4 20.1 4.6 27.6 27.1 0.1 100.0 811 6.8 35-39 24.2 18.7 6.5 26.1 24.3 0.2 100.0 889 6.0 40-44 22.4 9.8 4.2 26.5 36.2 0.8 100.0 708 8.6 45-49 29.1 16.8 2.3 19.3 31.6 0.9 100.0 655 6.4 50-54 32.6 13.8 4.4 16.3 31.6 1.4 100.0 591 5.6 55-59 45.2 12.2 2.3 15.3 22.8 2.1 100.0 400 1.7 60-64 53.3 13.8 3.7 10.9 14.7 3.6 100.0 277 0.0 65+ 68.0 10.0 2.3 9.1 8.2 2.5 100.0 554 0.0 Residence Urban 24.7 25.9 4.2 22.0 22.6 0.5 100.0 4,871 4.8 Rural 48.1 26.4 3.8 14.8 6.2 0.7 100.0 7,912 0.0 Region Monrovia 21.8 25.8 4.4 22.1 25.4 0.4 100.0 3,679 5.4 North Western 56.8 19.3 3.9 12.5 6.9 0.6 100.0 952 0.0 South Central 43.2 28.7 1.9 16.4 9.3 0.4 100.0 1,814 0.7 South Eastern A 43.3 29.0 3.3 17.5 6.1 0.8 100.0 796 0.7 South Eastern B 35.0 31.7 6.1 18.8 8.1 0.4 100.0 888 2.2 North Central 47.8 25.4 4.1 15.1 6.5 1.0 100.0 4,654 0.1 Wealth quintile Lowest 56.5 25.7 3.2 10.9 2.7 1.0 100.0 2,417 0.0 Second 49.4 26.1 5.2 14.5 4.4 0.4 100.0 2,486 0.0 Middle 42.5 27.0 3.6 18.2 7.7 0.9 100.0 2,602 1.0 Fourth 32.8 25.4 3.3 20.7 17.3 0.6 100.0 2,464 3.2 Highest 17.9 26.6 4.3 22.5 28.2 0.4 100.0 2,814 6.0 Total 39.2 26.2 3.9 17.5 12.5 0.7 100.0 12,784 1.7 1 Completed grade 6 at the primary level 2 Completed grade 12 at the secondary level 2.3.2 School Attendance Rates Table 2.5 presents primary school and secondary school net and gross attendance ratios (NAR and GAR) for the school year that started in 2006, by household residence, region, and wealth quintile. The NAR for primary school is the percentage of the primary-school-age (6-11 years) population that is attending primary school. The NAR for secondary school is the percentage of the secondary-school-age (12-17 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 a percentage of the official primary-school-age population. The GAR for secondary school is the total number of secondary school students, of any age, expressed as a percentage of the official secondary-school-age population. If there are significant numbers of over- age and under-age students at a given level of schooling, the GAR can exceed 100 percent. Youth are considered to be attending school currently if they attended formal academic school at any point during the given school year. 14 | Household Population and Housing Characteristics Table 2.5 School attendance ratios Net attendance ratios (NAR) and gross attendance ratios (GAR) for the de facto household population by sex and level of schooling, and the gender parity index (GPI), according to background characteristics, Liberia 2007 Net attendance ratio1 Gross attendance ratio2 Background characteristic Male Female Total Gender Parity Index3 Male Female Total Gender Parity Index3 PRIMARY SCHOOL Residence Urban 60.8 54.6 57.5 0.90 109.0 102.7 105.7 0.94 Rural 30.5 27.1 28.9 0.89 73.6 62.0 68.2 0.84 Region Monrovia 65.3 56.5 60.6 0.87 110.8 103.7 107.0 0.94 North Western 33.5 30.6 32.0 0.91 70.1 64.3 67.1 0.92 South Central 32.5 30.0 31.2 0.92 74.8 59.0 66.7 0.79 South Eastern A 31.9 28.9 30.6 0.91 78.2 79.3 78.7 1.01 South Eastern B 46.8 41.7 44.3 0.89 110.8 87.9 99.5 0.79 North Central 29.9 28.2 29.1 0.94 73.0 65.9 69.7 0.90 Wealth quintile Lowest 25.2 19.8 22.6 0.79 58.3 47.9 53.3 0.82 Second 27.6 24.9 26.4 0.90 72.1 57.7 65.6 0.80 Middle 36.4 38.0 37.1 1.04 82.8 84.0 83.4 1.01 Fourth 47.4 36.8 41.8 0.78 97.3 80.7 88.5 0.83 Highest 69.1 64.1 66.4 0.93 119.2 111.4 115.0 0.93 Total 41.4 38.6 40.0 0.93 86.3 79.1 82.7 0.92 SECONDARY SCHOOL Residence Urban 32.2 29.0 30.4 0.90 76.1 57.9 66.0 0.76 Rural 13.1 5.9 9.7 0.45 35.0 18.0 27.0 0.51 Region Monrovia 35.9 32.8 34.2 0.91 80.2 62.2 70.1 0.78 North Western 26.6 10.1 19.1 0.38 42.9 15.1 30.3 0.35 South Central 17.2 17.7 17.5 1.02 42.9 39.2 41.1 0.91 South Eastern A 11.2 6.6 8.9 0.59 42.3 19.8 31.2 0.47 South Eastern B 11.4 10.2 10.9 0.90 45.0 22.8 34.6 0.51 North Central 12.1 3.9 8.1 0.32 36.0 19.2 27.9 0.53 Wealth quintile Lowest 7.3 1.4 4.5 0.19 25.4 7.8 16.9 0.31 Second 10.7 3.0 7.3 0.28 30.0 14.9 23.3 0.50 Middle 15.3 8.7 12.0 0.57 41.6 21.3 31.5 0.51 Fourth 22.2 19.1 20.5 0.86 56.8 45.6 50.7 0.80 Highest 40.0 36.7 38.2 0.92 88.3 68.3 77.4 0.77 Total 21.3 17.9 19.6 0.84 52.7 38.7 45.5 0.73 1 The NAR for primary school is the percentage of the primary-school-age (6-11 years) population that is attending primary school. The NAR for secondary school is the percentage of the secondary-school-age (12-17 years) population that is attending secondary school. By definition the NAR cannot exceed 100 percent. 2 The GAR for primary school is the total number of primary school students, expressed as a percentage of the official primary-school-age population. The GAR for secondary school is the total number of secondary school students, expressed as a percentage of the official secondary-school-age population. If there are significant numbers of over-age and under-age students at a given level of schooling, the GAR can exceed 100 percent. 3 The Gender Parity Index for primary school is the ratio of the primary school NAR(GAR) for females to the NAR(GAR) for males. The Gender Parity Index for secondary school is the ratio of the secondary school NAR(GAR) for females to the NAR(GAR) for males. Table 2.5 shows that only 40 percent of primary-school-age children in Liberia are attending primary school; however, the GAR is considerably higher (83 percent), indicating that there are many primary school students who are not in the official primary school age group. The NAR is higher in urban areas than in rural areas (58 and 29 percent, respectively), as is the GAR (106 and 68 percent, respectively). There is significant variation by region: the NARs in North Western, South Central, South Eastern A, and North Central regions are half of the NAR in Monrovia. Household Population and Housing Characteristics | 15 The data in Table 2.5 show that there is a high correlation between economic status of the household and school attendance. For example, the NAR at the primary school level is 23 percent for the poorest households and 66 percent for the wealthiest households. The data indicate that unless the free education policy is effectively implemented by the government, many young Liberians will continue to be denied educational opportunities. At the secondary school level, the NAR is 20 percent and the GAR is 46 percent. Regional disparities at the secondary school level are even more pronounced than the primary school level; for example, the NAR ranges from a low of 8 percent in North Central region to a high of 34 percent in Monrovia. The gender parity index (GPI) assesses sex-related differences in school attendance rates and is calculated by dividing the NAR or GAR for females by the NAR or GAR for males. A GPI of less than one indicates a gender disparity in favor of males, i.e., a higher proportion of males than females attends that level of schooling. A GPI greater than one indicates a gender disparity in favor of females. A GPI of one indicates parity or equality between the rates of participation for males and females. The GPI for the NAR for primary school is 0.93 and for the GAR is 0.92. For secondary school, the GPIs are 0.84 and 0.73, respectively. This means that there is a gender disparity in favor of males in Liberia and that it is stronger at the secondary school level than at the primary level. Girls tend to be more educationally disadvantaged in rural than in urban areas, especially at the secondary level. Once again, regional differentials exist, especially for secondary school; the data indicate that girls residing in North Central and North Western regions are particularly disadvantaged at the secondary school level. Gender disparities in school attendance by age—i.e., the percentage of a given age cohort who attend school, regardless of the level attended (primary, secondary, or higher)—are shown in Figure 2.3. Another way to measure school attendance is to ask if school-aged children actually attended school in the previous week. In the LDHS, for all children age 5-14 listed in the household, a question was first asked as to whether the child was “going to school these days.” If yes, the respondent was asked how many days the child was absent from school in the last week. For children who were either not going to school these days or who had missed one or more days in the previous week, the Figure 2.3 Age-Specific School Attendance Rates 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 Age 0 10 20 30 40 50 60 70 80 90 100 Percent Female Male LDHS 2007Note: Figure shows percentage of the de jure household population age 5-24 years attending school. 16 | Household Population and Housing Characteristics respondent was asked why the child was absent from school. Data are tabulated for children age 6-14, because age 6 is a more common age for starting primary school. As shown in Table 2.6, more than one-quarter of children age 6-14 were reported as “not going to school these days,” and an additional 14 percent were going to school but were absent for one or more days in the preceding week. Slightly more than half of school-aged children were reported to have not been absent from school the previous week. This proportion is far higher than average among urban children and children whose mothers are better educated and who are in the wealthier quintiles. Table 2.6 School absenteeism Percent distribution of children age 6-14 years by school attendance in the week preceding the interview, according to background characteristics, Liberia 2007 Background characteristic School attendance in week preceding survey (%) Total Number of children age 6-14 Present all days Absent 1+ days Absent all days Missing Sex Male 55.7 14.4 25.9 3.9 100.0 4,636 Female 54.3 13.3 28.7 3.6 100.0 4,491 Age 6-11 years 52.9 13.7 29.7 3.7 100.0 6,444 12-14 years 60.3 14.4 21.4 3.9 100.0 2,683 Residence Urban 66.0 14.9 16.0 3.1 100.0 3,619 Rural 47.8 13.2 34.7 4.2 100.0 5,508 Region Monrovia 66.9 14.9 15.5 2.7 100.0 2,689 North Western 60.2 12.2 23.0 4.7 100.0 690 South Central 49.8 18.1 26.8 5.3 100.0 1,227 South Eastern A 54.6 14.0 24.8 6.6 100.0 541 South Eastern B 58.9 10.6 26.0 4.5 100.0 672 North Central 45.6 12.6 38.7 3.2 100.0 3,309 Mother's education None 48.5 12.8 35.1 3.6 100.0 2,996 Primary 57.0 16.6 23.5 3.0 100.0 1,214 Secondary or higher 72.6 15.6 8.5 3.3 100.0 1,049 Mother’s survival status Mother dead/don’t know 44.8 14.7 36.3 3.7 100.0 382 Mother not in household 56.8 13.1 35.9 4.2 100.0 3,172 Mother in household, not interviewed 46/0 15/1 33/1 5.8 100.0 311 Wealth quintile Lowest 41.6 12.1 42.2 4.1 100.0 1,699 Second 45.0 13.9 35.4 5.7 100.0 1,617 Middle 53.1 16.4 27.3 3.3 100.0 1,832 Fourth 59.2 12.8 25.2 2.8 100.0 1,933 Highest 72.0 14.1 10.5 3.4 100.0 2,046 Total 55.0 13.9 27.3 3.8 100.0 9,127 Table 2.7 shows that important reasons for absence from school are school holidays or vacations, especially for those who are going to school but were absent one or more days the previous week. Among children who are not going to school, by far the main reason is lack of funds for school fees. Clearly, making primary school free and compulsory could increase enrolment. Household Population and Housing Characteristics | 17 Table 2.7 Reasons for school absenteeism Percent distribution of children age 6-14 years who were not going to school or who were absent one or more days in the week preceding the interview, by reason for absence, Liberia 2007 Reason for child's absence from school School absence in week preceding survey (%) Did not attend school Attended school 1+ days Work 0.0 0.9 Did not want to go 3.0 4.7 Mistreated at school 0.1 0.1 Child was sick 2.0 19.5 Had to care for sick relative 0.3 0.5 School is too far 5.2 0.1 Security concerns 0.6 0.8 Vacation, holiday 20.7 35.9 School not open 1.5 2.5 School too far 4.9 0.8 No money for fees 50.2 18.5 Other 8.8 13.1 Missing 2.7 2.7 Total 100.0 100.0 Number of children 2,491 1,267 2.4 CHILD LABOR Interestingly, having to work is not a significant reason for children’s absence from school. Nevertheless, child labor can affect the amount of time available to do homework, play, and sleep. In the 2007 LDHS, respondents to the Household Questionnaire were asked a series of questions about all children age 5-14 in the household, namely, whether the child did any kind of work for someone outside the household in the past week or the past year, whether the child helped with household chores in the past week, and whether the child did any other family work on the farm or in a family business. If the answer to any of these questions was “yes,” the respondent was asked whether the work was for pay or unpaid and how many hours the child did that kind of work in the past week. Table 2.8 shows data on child labor in Liberia. Different criteria were used depending on the age of the child. A child age 5-11 was considered to be working if he/she worked at all, while a child age 12-14 was considered to be working only if he/she worked for 14 hours or more in the previous week. The data show that one-fifth of children age 5-14 are considered to be engaged in labor (see definition in footnote 2 in Table 2.8). The main contributor to child labor consists of children age 5-11 working in a family business or on the farm. Although older children (age 12-14) also work in the family business or farm, only 3 percent do so for 14 hours a week or more. Nine percent of children age 5-14 work outside the household, mostly in unpaid jobs. Because of the definition of child labor, it is more common among younger children than older children. Child labor is also more common among rural than urban children and among those in the poorer wealth quintiles. 18 | Household Population and Housing Characteristics Table 2.8 Child labor Percentage of children age 5-14 years who were involved in child labor activities in the past week, by type of work, Liberia 2007 Background characteristic Working outside the household in past week1 Household chores for 28+ hours/ week Working for family business in past week1 Total child labor2 Number of children age 5-14 years Paid work Unpaid work Sex Male 1.2 7.6 0.3 15.9 21.1 5,105 Female 0.6 8.5 0.5 15.4 20.5 5,002 Age 5-11 years 1.2 10.5 0.4 20.2 27.5 7,424 12-14 years 0.2 1.2 0.6 3.1 2.2 2,683 School participation Yes 0.9 8.7 0.5 16.3 21.8 6,976 No 1.0 6.9 0.3 15.0 19.5 2,954 Residence Urban 1.2 9.1 0.6 8.6 15.7 3,920 Rural 0.7 7.4 0.3 20.1 24.0 6,186 Region Monrovia 1.3 9.9 0.2 7.6 15.6 2,898 North Western 1.2 13.2 0.0 13.0 22.3 784 South Central 0.4 7.1 0.6 13.4 17.4 1,397 South Eastern A 1.4 10.3 1.1 26.9 31.7 612 South Eastern B 0.1 13.4 0.1 20.6 27.2 754 North Central 0.7 4.4 0.5 20.4 22.7 3,662 Mother's education None 0.8 7.1 0.3 18.5 22.3 3,392 Primary 0.9 9.0 0.2 18.5 23.7 1,387 Secondary and higher 0.8 8.5 0.9 9.0 16.4 1,147 Mother’s survival status Mother dead/don’t know 0.5 9.6 0.9 8.2 24.4 415 Mother not in household 0.9 8.2 0.5 13.8 19.2 3,426 Mother in household, not interviewed 2.5 8.9 0.0 13.1 19.8 337 Wealth quintile Lowest 1.3 8.4 0.5 22.8 26.9 1,922 Second 1.1 8.8 0.2 20.5 25.3 1,851 Middle 0.4 6.9 0.4 16.9 21.2 2,049 Fourth 0.8 8.0 0.7 12.3 18.4 2,113 Highest 1.0 8.3 0.4 7.2 13.5 2,171 Total 0.9 8.1 0.4 15.6 20.8 10,107 Note: Total includes some cases with missing data for school participation 1 Defined as any such work for children age 5-11 and 14 hours or more of such work for those age 12-14 2 The numerator to estimate child labor percentage includes: (a) children 5-11 years of age that during the week preceding the survey did at least one hour of economic activity or at least 28 hours of domestic chores and (b) children 12-14 years of age that during the week preceding the survey did at least 14 hours of economic activity or at least 28 hours of domestic chores. 2.5 CHILD DISCIPLINE The manner in which parents and caretakers discipline children can have long-term consequences on their physical and psychological development and well-being. In an effort to identify the types of child discipline methods used in Liberia, the 2007 LDHS included questions on this topic. The questions were aimed at only one randomly selected child age 2-14 in the household. Interviewers were instructed how to use the “Kish” grid at the back of the Household Questionnaire to randomly select one child in households with two or more eligible children. Interviewers then posed questions to the household respondent about whether the respondent or anyone else in the household used any of a list of methods to discipline the child in the previous month. The methods asked about ranged from “Gave him/her something else to do” to “Beat him/her with an implement over and over as hard as one could.” Household Population and Housing Characteristics | 19 Data in Table 2.9 show that the vast majority of children receive psychological punishment such as yelling and name calling (83 percent) or minor physical punishment such as shaking, spanking, hitting with a hard object, or slapping on the face, head, arm, or leg (76 percent). Fifteen percent of children age 2-14 received severe physical punishment in the previous month, namely severe beating with an implement. Almost all children (94 percent) were punished with some type of psychological or physical method. One in 20 children was not disciplined or punished at all in the previous month or received only nonviolent discipline such as taking away privileges, explaining why something the child did was wrong, or giving him/her something else to do. Differences in the use of the various methods of child discipline by background characteristics are notably minor. One exception is age of the child, with the youngest children (2-4 years) slightly more likely than older children to not be disciplined at all. Table 2.9 Child discipline Percentage of children age 2-14 years who experience various methods of discipline, according to background characteristics, Liberia 2007 Background characteristic Only non- violent discipline Psycho- logical punish- ment Minor physical punish- ment1 Severe physical punish- ment1 Any psycho- logical or physical punish- ment No discipline or punish- ment Respondent believes the child needs to be physically punished Number of children age 2-14 years Sex Male 4.3 83.5 76.3 16.2 94.0 4.8 60.7 2,731 Female 4.8 81.6 74.7 14.2 94.0 4.6 61.8 2,660 Age 2-4 years 4.1 78.7 73.4 11.2 89.2 8.3 57.6 1,604 5-9 years 3.9 85.5 79.0 16.5 97.2 2.4 63.3 2,137 10-14 years 5.8 82.6 73.1 17.5 94.7 4.2 62.0 1,650 Residence Urban 3.4 86.4 79.9 18.2 94.6 4.3 65.4 1,946 Rural 5.2 80.4 73.0 13.5 93.7 4.9 58.9 3,444 Region Monrovia 2.4 88.5 81.3 19.2 94.2 4.8 65.1 1,473 North Western 5.4 87.6 63.6 12.5 97.0 1.5 50.0 460 South Central 4.6 84.2 78.8 11.2 97.2 2.4 71.1 800 South Eastern A 7.7 81.6 69.9 16.1 94.6 4.1 59.7 349 South Eastern B 4.1 82.4 69.5 12.6 89.3 9.7 70.4 362 North Central 5.5 76.5 74.8 14.8 92.6 5.6 55.5 1,947 Mother's education None 4.0 82.3 76.3 16.8 94.4 4.1 61.9 1,885 Primary 4.2 80.5 74.7 12.5 90.6 7.5 58.8 908 Secondary and higher 2.3 89.0 81.5 16.2 95.9 3.1 70.3 621 Mother’s survival status Mother dead/don’t know 4.0 82.5 72.8 13.7 94.3 5.6 57.3 203 Mother not in household 6.3 82.1 73.0 15.5 94.6 4.5 59.5 1,567 Mother in household, not interviewed 5.1 77.9 75.0 9.2 94.8 3.7 56.8 205 Wealth quintile Lowest 6.1 76.1 69.9 12.2 90.8 7.5 56.9 1,162 Second 5.1 80.9 74.8 14.8 94.7 4.4 59.2 1,101 Middle 4.8 84.4 75.3 14.2 95.4 3.2 60.0 1,049 Fourth 2.8 87.4 80.9 19.4 95.7 2.8 68.4 1,065 Highest 3.8 84.9 77.4 15.8 93.6 5.4 62.2 1,014 Total 4.5 82.6 75.5 15.2 94.0 4.7 61.2 5,391 Note: In households with more than one child aged 2-14, one child was randomly selected as the subject for the questions. 1 The DHS definition of minor and severe physical punishment varies slightly with the UNICEF definition due to question wording. The UNICEF Multiple Indicator Cluster Survey questionnaire includes two questions: “Hit or slapped him/her on the face, head or ears” and “Hit or slapped him/her on the hand, arm or leg”, with the former considered to be severe physical punishment and the latter to be minor physical punishment. The two questions were combined in the LDHS into: “Slapped him/her on the face, head, arm or leg”. In this table, this method is included in the minor physical punishment category. 20 | Household Population and Housing Characteristics Table 2.9 also shows that six in ten household respondents believe that the child needs to be physically punished in order to be brought up properly. Belief in physical punishment is more prevalent among respondents in urban areas, in South Central and South Eastern B regions, and among those with at least some secondary education. 2.6 BIRTH REGISTRATION The registration of births is the inscription of the facts of the birth into an official log kept at the registrar’s office. A birth certificate is issued at the time of registration or later as proof of the registration of the birth. Birth registration is basic to ensuring a child’s legal status and, therefore, their basic rights and services (UNICEF, 2006; United Nations General Assembly, 2002). Table 2.10 gives the percentage of children under age five whose births were officially registered and the percentage who had a birth certificate at the time of the survey. Not all children who are registered may have a birth certificate because some certificates may have been lost or were never issued. However, all children with a certificate have been registered. The results show that only 4 percent of Liberian children under age five have birth certifi- cates. Birth certificates are more common among children in South Central region and among those in the higher wealth quintiles. Table 2.10 Birth registration of children under age five Percent distribution of de jure children under five years of age by whether they have a birth certificate, according to background characteristics, Liberia 2007 Percent distribution of children who have a birth certificate Background characteristic Has a birth certificate Does not have a birth certificate Missing Total Number of children Age <2 3.7 89.4 6.9 100.0 2,300 2-4 3.5 86.1 10.4 100.0 3,727 Sex Male 3.2 87.4 9.4 100.0 3,128 Female 4.0 87.3 8.7 100.0 2,900 Residence Urban 5.3 83.5 11.2 100.0 1,834 Rural 2.8 89.0 8.1 100.0 4,194 Region Monrovia 3.9 83.9 12.2 100.0 1,291 North Western 1.7 91.5 6.8 100.0 536 South Central 6.8 88.5 4.7 100.0 946 South Eastern A 1.6 91.4 7.0 100.0 487 South Eastern B 1.0 89.9 9.2 100.0 435 North Central 3.4 86.5 10.1 100.0 2,333 Wealth quintile Lowest 1.2 89.0 9.8 100.0 1,378 Second 2.4 90.0 7.6 100.0 1,445 Middle 4.6 88.2 7.2 100.0 1,238 Fourth 4.2 84.8 10.9 100.0 1,182 Highest 7.3 81.9 10.8 100.0 784 Total 3.6 87.3 9.1 100.0 6,028 2.7 HOUSEHOLD ENVIRONMENT The physical characteristics of the dwelling in which a household lives are important determinants of the health status of household members, especially children. They can also be used as indicators of the socioeconomic status of households. LDHS respondents were asked a number of questions about their household environment, including questions on the source of drinking water; Household Population and Housing Characteristics | 21 type of sanitation facility; type of flooring, walls, and roof; and number of rooms in the dwelling. The results are presented both in terms of households and of the de jure population. 2.7.1 Drinking Water Increasing access to improved drinking water is one of the Millennium Development Goals that Liberia, along with other nations worldwide, has adopted (United Nations General Assembly, 2001). Table 2.11 includes a number of indicators that are useful in monitoring household access to improved drinking water (WHO and UNICEF, 2005). The source of drinking water is an indicator of whether it is suitable for consumption. Sources that are likely to provide water suitable for drinking are identified as improved sources in Table 2.11. They include a piped source within the dwelling or plot, public tap, tube well or borehole, protected well or spring, and rainwater.3 Lack of ready access to a water source may limit the quantity of suitable drinking water that is available to a household. Even if the water is obtained from an improved source, water that must be fetched from a source that is not immediately accessible to the household may be contaminated during transport or storage. Another factor in considering the accessibility of water sources is the fact that the burden of going for water often falls disproportionately on female members of the household. Finally, home water treatment can be effective in improving the quality of household drinking water. The 2007 LDHS shows that only two-thirds (65 percent) of Liberian households have an improved source of drinking water. By far, the most common single source of water is protected dug wells (54 percent of households). Urban households are much more likely than rural households to use an improved source of drinking water (82 vs. 56 percent, respectively). One-fifth of rural households get their drinking water from lakes and ponds (surface water). Eleven percent of Liberian households have water in their households or on the premises, and 80 percent take less than 30 minutes to go to their source of drinking water, get water, and come home. Interestingly, urban households are slightly more likely than rural households to take more than 30 minutes to get their drinking water. Table 2.11 also shows that women are disproportionately more likely than men to collect the drinking water. In half of the households, adult women usually get the drinking water, compared with 11 percent of households in which adult men usually get it. Survey results indicate that very few Liberian households take any measures to treat their water before drinking it. Eighty-two percent of households do not treat their water, and only 16 percent treat their water with bleach or chlorine. Comparisons with the 1999-2000 LDHS are difficult because of variations in the classifications of water sources. Nevertheless, it appears that there has been some improvement in sources of water. Although the proportion of households using piped water has decreased slightly from 11 to 7 percent since 1999-2000 and the proportion getting drinking water from a tube well or borehole has also decreased from 16 to 3 percent, the proportion getting water from a protected dug well or spring has increased from 28 to 56 percent and the proportion getting water from unprotected dug wells, unprotected springs, and surface water has decreased from 38 to 30 percent. 3 The classification of improved and nonimproved sources of drinking water follows that proposed by the WHO/UNICEF Joint Monitoring Programme for Water Supply and Sanitation (WHO and UNICEF, 2004). 22 | Household Population and Housing Characteristics Table 2.11 Household drinking water Percent distribution of households and de jure population by source, time to collect, and person who usually collects drinking water; and percentage of households and the de jure population by treatment of drinking water, according to residence, Liberia 2007 Households Population Characteristic Urban Rural Total Urban Rural Total Source of drinking water Improved source 81.5 55.9 65.2 83.5 55.8 66.1 Piped water into dwelling/yard/plot 7.1 0.1 2.6 7.5 0.1 2.9 Public tap/standpipe 11.0 0.2 4.1 11.8 0.3 4.6 Tube well or borehole 3.7 2.3 2.8 4.0 2.5 3.0 Protected dug well 59.6 51.2 54.3 60.1 50.8 54.3 Protected spring 0.1 2.0 1.3 0.1 2.1 1.4 Nonimproved source 14.0 43.9 33.0 12.7 44.0 32.3 Unprotected dug well 6.4 13.1 10.6 6.8 14.1 11.4 Unprotected spring 0.4 9.7 6.3 0.3 9.5 6.1 Tanker truck/cart with small tank 6.7 0.1 2.5 5.1 0.1 2.0 Surface water 0.5 20.9 13.5 0.5 20.3 12.9 Bottled water, improved source for cooking/washing1 0.3 0.0 0.1 0.2 0.0 0.1 Bottled water, nonimproved source for cooking/washing1 0.1 0.0 0.0 0.1 0.0 0.0 Other 4.1 0.1 1.6 3.6 0.1 1.4 Missing 0.0 0.1 0.1 0.0 0.1 0.1 Total 100.0 100.0 100.0 100.0 100.0 100.0 Percentage using any improved source of drinking water 81.8 55.9 65.3 83.7 55.8 66.2 Time to get drinking water (round trip) Water on premises 15.2 8.0 10.6 16.1 8.2 11.2 Less than 30 minutes 72.5 84.1 79.9 71.1 83.7 79.0 30 minutes or longer 10.4 6.5 7.9 11.2 6.9 8.5 Don't know/missing 2.0 1.4 1.6 1.6 1.3 1.4 Total 100.0 100.0 100.0 100.0 100.0 100.0 Person who usually gets drinking water Adult female 15+ 34.5 58.2 49.5 31.6 58.0 48.2 Adult male 15+ 15.8 8.7 11.3 12.0 5.3 7.8 Female child under age 15 11.1 7.1 8.5 13.0 7.5 9.6 Male child under age 15 7.2 4.6 5.6 7.6 4.9 5.9 Female and male children equally 12.5 9.9 10.9 16.6 13.2 14.5 Other 3.1 2.0 2.4 2.3 1.2 1.6 Water on premises 15.2 8.0 10.6 16.1 8.2 11.2 Missing 0.7 1.5 1.2 0.7 1.6 1.3 Total 100.0 100.0 100.0 100.0 100.0 100.0 Water treatment2 Boiled 0.3 0.0 0.1 0.3 0.0 0.1 Bleach/chlorine 23.3 11.0 15.5 25.7 11.2 16.6 Strained through cloth 0.4 0.6 0.5 0.4 0.7 0.6 Other 0.8 0.6 0.6 0.7 0.8 0.7 No treatment 74.1 85.9 81.6 71.9 85.8 80.6 Percentage using an appropriate treatment method3 23.8 11.6 16.1 26.0 12.0 17.2 Number 2,486 4,338 6,824 12,814 21,512 34,326 1 Because the quality of bottled water is not known, households using bottled water for drinking are classified as using an improved or nonimproved source according to their water source for cooking and washing. 2 Respondents may report multiple treatment methods so the sum of treatment may exceed 100 percent. 3 Appropriate water treatment methods include boiling, bleaching, straining, filtering, and solar disinfecting. 2.7.2 Household Sanitation Facilities Ensuring adequate sanitation facilities is another one of the Millennium Development Goals that Liberia shares with other countries. A household is classified as having an improved toilet if the toilet is used only by members of one household (i.e., it is not shared) and if the facility used by the household separates the waste from human contact (WHO/UNICEF Joint Monitoring Program for Water Supply and Sanitation, 2004). Household Population and Housing Characteristics | 23 Table 2.12 shows that only 10 percent of Liberian households use an improved, unshared toilet facility, and 90 percent have access to a nonimproved facility. Over half (55 percent) of the households do not use any toilet facility. These results indicate that considerable resources, dedication, and effort are needed to improve toilet facilities in Liberia. There has been no improvement in toilet facilities since 1999-2000, when 11 percent of households had access to flush toilets. Table 2.12 Household sanitation facilities Percent distribution of households and de jure population by type of toilet/latrine facilities, according to residence, Liberia 2007 Households Population Type of toilet/latrine facility Urban Rural Total Urban Rural Total Improved, not shared facility Flush/pour flush to piped sewer system 4.6 0.4 1.9 4.4 0.5 2.0 Flush/pour flush to septic tank 14.3 1.2 6.0 15.7 1.3 6.7 Flush/pour flush to pit latrine 0.4 0.0 0.2 0.6 0.0 0.2 Ventilated improved pit (VIP) latrine 1.1 0.8 0.9 1.3 0.9 1.1 Pit latrine with slab 0.9 1.0 1.0 1.0 1.3 1.2 Nonimproved facility Any facility shared with other households 24.6 13.6 17.6 23.4 12.4 16.5 Flush/pour flush not to sewer/septic tank/ pit latrine 1.3 0.4 0.8 1.1 0.4 0.7 Pit latrine without slab/open pit 12.6 8.6 10.1 12.9 8.8 10.3 Bucket 0.6 0.2 0.3 0.7 0.1 0.3 Hanging toilet/hanging latrine 8.4 3.3 5.1 7.8 3.0 4.8 No facility/bush/field 27.7 69.8 54.5 28.2 70.5 54.7 Other 2.6 0.3 1.1 2.1 0.3 1.0 Missing 0.7 0.4 0.5 0.8 0.4 0.5 Total 100.0 100.0 100.0 100.0 100.0 100.0 Number 2,486 4,338 6,824 12,814 21,512 34,326 2.7.3 Housing Characteristics Table 2.13 presents information on a number of characteristics of the dwelling in which LDHS households live. These characteristics reflect the household’s socioeconomic situation. They also may influence environmental conditions—for example, exposure to indoor pollution with the use of biomass fuels—that have a direct bearing on the health and welfare of household members. Ninety-seven percent of Liberian households do not have electricity. The 3 percent that have electricity are mostly located in the urban areas. The reason for the low level of access to electricity is that the entire electric grid of the country was destroyed during the civil crisis and only a tiny fraction of Monrovia has been restored to the electric grid that is being developed. The type of material used for flooring is an indicator of the economic situation of households and the potential exposure of household members to disease-causing agents. Fifty-five percent of households in Liberia live in dwellings with earth, sand, or mud floors, and 40 percent live in dwellings with concrete or cement floors. Three-quarters of urban households have concrete or cement floors, and just over three-quarters of rural households have earthen floors. With regard to the type of walls in the dwelling, 54 percent of households live in structures with mud walls, and 28 percent live in structures with cement or stone blocks for walls. As is the case for flooring materials, the materials of the walls are more likely to be cement or stone blocks in urban areas and mud and sticks in rural areas. 24 | Household Population and Housing Characteristics Table 2.13 Household characteristics Percent distribution of households and de jure population by housing characteristics and percentage using solid fuel for cooking, according to residence, Liberia 2007 Households Population Housing characteristic Urban Rural Total Urban Rural Total Electricity Yes 6.9 0.8 3.0 7.0 1.0 3.3 No 92.9 99.2 96.9 92.8 98.9 96.6 Missing 0.2 0.1 0.1 0.2 0.1 0.1 Total 100.0 100.0 100.0 100.0 100.0 100.0 Flooring material Earth, sand, mud 14.8 78.1 55.0 15.1 77.0 53.9 Wood planks 0.9 0.2 0.5 1.0 0.3 0.5 Parquet, polished wood 0.2 0.1 0.1 0.2 0.1 0.2 Floor mat, linoleum, vinyl 2.1 0.2 0.9 1.9 0.2 0.8 Ceramic tiles 5.5 1.0 2.6 6.1 0.9 2.8 Concrete, cement 75.3 20.2 40.3 74.3 21.2 41.0 Carpet 0.3 0.0 0.1 0.2 0.0 0.1 Other 0.4 0.0 0.1 0.5 0.0 0.2 Missing 0.6 0.2 0.4 0.7 0.3 0.4 Total 100.0 100.0 100.0 100.0 100.0 100.0 Wall material Mud and sticks 11.7 77.5 53.5 11.6 76.2 52.1 Cane/palm/trunks 0.6 0.2 0.4 0.6 0.2 0.3 Straw, thatch mats 3.3 0.3 1.4 3.0 0.2 1.3 Mud bricks 7.3 9.9 9.0 8.5 10.7 9.9 Plywood, reused wood 0.3 0.0 0.1 0.3 0.0 0.1 Cardboard, plastic 0.0 0.0 0.0 0.0 0.0 0.0 Zinc, metal 9.8 0.2 3.7 9.8 0.2 3.8 Cement or stone blocks 60.1 9.0 27.6 60.0 8.8 27.9 Bricks 4.5 2.4 3.2 4.3 3.2 3.6 Wood planks/shingles 0.8 0.2 0.4 0.7 0.3 0.4 Other 1.1 0.0 0.4 1.0 0.0 0.4 Missing 0.4 0.2 0.3 0.4 0.3 0.3 Total 100.0 100.0 100.0 100.0 100.0 100.0 Roofing material Thatch/palm leaf 3.4 43.4 28.8 3.6 41.8 27.6 Palm/bamboo/mats 0.3 1.7 1.2 0.2 1.9 1.3 Wood planks 0.0 0.0 0.0 0.1 0.1 0.1 Tarpaulin, plastic 4.9 1.6 2.8 4.5 1.6 2.7 Zinc, metal 83.3 49.7 62.0 84.2 50.5 63.1 Wood 0.2 0.1 0.1 0.2 0.1 0.2 Ceramic tiles 0.4 0.1 0.2 0.4 0.1 0.2 Concrete, cement 4.7 0.3 1.9 3.8 0.3 1.6 Asbestos sheets, shingles 2.0 2.6 2.4 2.2 3.1 2.8 Other 0.3 0.2 0.2 0.4 0.1 0.2 Missing 0.4 0.2 0.3 0.3 0.4 0.4 Total 100.0 100.0 100.0 100.0 100.0 100.0 Rooms used for sleeping One 42.6 35.2 37.9 30.0 25.2 27.0 Two 24.7 28.6 27.2 27.4 29.5 28.7 Three or more 31.3 33.5 32.7 41.2 42.3 41.9 Missing 1.4 2.7 2.2 1.3 3.1 2.4 Total 100.0 100.0 100.0 100.0 100.0 100.0 Continued… Household Population and Housing Characteristics | 25 Table 2.13—Continued Households Population Housing characteristic Urban Rural Total Urban Rural Total Place for cooking In the house 27.7 13.7 18.8 27.7 13.9 19.1 In separate kitchen 17.5 8.5 11.8 18.1 8.6 12.1 Not in separate kitchen 10.2 5.2 7.0 9.7 5.3 6.9 Porch 16.9 4.2 8.8 17.0 4.0 8.9 In a separate building 5.7 18.2 13.6 6.9 18.3 14.1 Outdoors 47.5 62.2 56.9 47.2 62.5 56.8 Other 0.1 0.1 0.1 0.1 0.1 0.1 Missing 2.2 1.5 1.8 1.1 1.1 1.1 Total 100.0 100.0 100.0 100.0 100.0 100.0 Cooking fuel Electricity 0.0 0.0 0.0 0.0 0.0 0.0 Gas cylinder 0.2 0.0 0.1 0.1 0.0 0.0 Kerosene stove 0.1 0.0 0.0 0.0 0.0 0.0 Fire coal/coal/charcoal 85.3 13.1 39.4 85.6 13.6 40.5 Wood 12.6 86.1 59.4 13.6 86.0 58.9 No food cooked in household 1.6 0.7 1.0 0.4 0.3 0.4 Missing 0.2 0.1 0.1 0.2 0.1 0.2 Total 100.0 100.0 100.0 100.0 100.0 100.0 Percentage using solid fuel for cooking1 97.9 99.2 98.7 99.2 99.5 99.4 Number of households 2,486 4,338 6,824 12,814 21,512 34,326 1 Includes coal, charcoal, and wood More than three in five households in Liberia live in dwellings with zinc or metal roofs. Most of the remainder live in dwellings with roofs made of thatch or palm leaf (29 percent). Although thatched roofs are more common among rural than urban households, the most common type of roof in both rural and urban areas is metal. The number of rooms a household uses for sleeping is an indicator of socioeconomic level, but also can be used to assess crowding that can facilitate the spread of disease. In the 2007 LDHS, household respondents were asked how many rooms were used for sleeping, regardless of whether they were bedrooms or not. In Liberia, 38 percent of households have only one room for sleeping, 27 percent have two rooms, and 33 percent have three or more rooms. Urban households have more crowded sleeping arrangements than rural households; not only are urban households slightly larger in terms of the average number of members (see Table 2.2), but they are also more likely than rural households to have only one room for sleeping. Table 2.13 also shows the distribution of households by the type of place for cooking and the type of fuel used for cooking. Over half of Liberian households (57 percent) cook outdoors, and three in five households (59 percent) use wood for fuel. Sizeable proportions of urban households cook in their dwellings (28 percent) or on a porch (17 percent); however, almost half (48 percent) cook outdoors. The majority of rural households (62 percent) cook outdoors, though 18 percent have a separate building for cooking. Almost all urban households use charcoal for cooking, and almost all rural households use wood. 2.8 HOUSEHOLD POSSESSIONS The availability of durable consumer goods is a good indicator of a household’s socioeco- nomic status. Moreover, particular goods have specific benefits. For instance, having access to a radio or a television exposes household members to innovative ideas, a refrigerator prolongs the whole- someness of foods, and a means of transport allows greater access to many services away from the local area. Table 2.14 shows the availability of selected consumer goods by residence. 26 | Household Population and Housing Characteristics Table 2.14 Household durable goods Percentage of households and de jure population possessing various household effects, means of transportation, and livestock/farm animals, by residence, Liberia 2007 Households Population Possession Urban Rural Total Urban Rural Total Radio 72.7 39.3 51.5 74.3 42.6 54.5 Television 17.4 1.0 7.0 18.9 1.3 7.9 Mobile telephone 63.0 9.0 28.7 65.9 10.5 31.2 Refrigerator (ice box) 4.1 0.6 1.8 4.3 0.9 2.1 Generator 22.9 1.5 9.3 23.8 1.7 10.0 Table 79.9 47.2 59.1 81.1 50.0 61.6 Chairs 75.4 50.7 59.7 77.0 53.3 62.2 Cupboard 30.7 3.6 13.5 30.6 3.8 13.8 Mattress 86.9 41.8 58.2 87.0 44.5 60.4 Sewing machine 4.1 0.7 2.0 5.0 0.9 2.4 Computer 2.0 0.1 0.8 2.5 0.1 1.0 Watch 59.2 27.5 39.1 62.9 30.5 42.6 Bicycle 7.0 2.4 4.1 8.2 2.6 4.7 Motorcycle/scooter 3.0 1.0 1.7 2.8 1.0 1.7 Car/truck 5.2 0.3 2.1 5.6 0.3 2.3 Boat or canoe 0.4 1.0 0.8 0.4 1.0 0.8 Ownership of farm animals1 21.1 41.8 34.3 25.4 46.2 38.4 Number 2,486 4,338 6,824 12,814 21,512 34,326 1 Cows, pigs, goats, sheep, or chickens Of the 17 selected household durable goods, chairs, tables, mattresses, and radios stand out as the most commonly owned by households; all four items are owned by more than half of Liberian households. Almost four in ten households have a watch, and just over one-third own farm animals. It is interesting to note that more than one-quarter of households (29 percent) have a mobile phone. Ownership of the remaining items is rarer; only 14 percent of households own a cupboard, 9 percent have a generator, and 7 percent have televisions. Two percent of households have sewing machines or refrigerators, and less than 1 percent own a computer. With regard to means of transport, 4 percent of households have a bicycle; 2 percent have either a car, truck, or motorcycle; and less than 1 percent have a boat or canoe. There is noticeable urban-rural variation in the proportion of households owning durable goods. The largest discrepancies between urban and rural households are in ownership of mobile phones and generators. It is worth noting that several interviewers remarked that they thought some respondents might be reluctant to report all of the household’s possessions. One reason for this might be that they hoped that the survey teams might provide them with some items like chairs or mosquito bednets. 2.9 WEALTH INDEX � The wealth index is a background characteristic that is used throughout the report as a proxy for long-term standard of living of the household. It is based on the data on the household’s ownership of consumer goods, dwelling characteristics, source of drinking water, toilet facilities, and other characteristics that are related to a household’s socioeconomic status. To construct the index, each of these assets was assigned a weight (factor score) generated through principal component analysis, and the resulting asset scores were standardized in relation to a standard normal distribution with a mean of zero and standard deviation of one (Gwatkin et al., 2000). Each household was then assigned a score for each asset, and the scores were summed for each household. Individuals were ranked according to the total score of the household in which they resided. The sample was then divided into quintiles from one (lowest) to five (highest). A single asset index was developed on the basis of data from the entire country sample and this index is used in all the tabulations presented. Household Population and Housing Characteristics | 27 Table 2.15 shows the distribution of the de jure household population into five wealth levels (quintiles) based on the wealth index by residence. These distributions indicate the degree to which wealth is evenly (or unevenly) distributed by geographic areas. The table shows that, according to the wealth index, urban respondents and those in Monrovia are much more likely to fall in the higher wealth quintiles. Only 1 percent of the urban population falls in the lowest wealth quintile, compared with 31 percent of the rural population. Residents of South Eastern A region are more than twice as likely as average to fall into the poorest wealth quintile. Table 2.15 Wealth quintiles Percent distribution of the de jure population by wealth quintiles, according to residence and region, Liberia 2007 Wealth quintile Number Residence/region Lowest Second Middle Fourth Highest Total Residence Urban 1.0 3.6 14.2 34.3 46.8 100.0 12,814 Rural 31.3 29.8 23.4 11.5 4.0 100.0 21,512 Region Monrovia 0.1 0.9 8.0 34.6 56.4 100.0 9,552 North Western 21.9 33.1 31.4 12.6 1.0 100.0 2,716 South Central 25.0 19.4 20.3 21.1 14.2 100.0 5,025 South Eastern A 47.3 27.4 16.4 6.9 2.0 100.0 2,294 South Eastern B 32.0 27.1 24.8 12.4 3.8 100.0 2,362 North Central 25.6 29.4 26.3 13.9 4.8 100.0 12,377 Total 20.0 20.0 20.0 20.0 20.0 100.0 34,326 Characteristics of Respondents | 29 CHARACTERISTICS OF RESPONDENTS 3 This chapter provides a profile of the respondents who were interviewed in the 2007 Liberia Demographic and Health Survey (LDHS), i.e., women and men age 15-49. First, information is presented on a number of basic characteristics including age at the time of the survey, religion, marital status, residence, education, literacy, and media access. Then, the chapter explores adults’ employment status, occupation, and earnings. An analysis of these variables provides the socioeconomic context within which demographic and reproductive health issues are examined in the subsequent chapters. 3.1 CHARACTERISTICS OF SURVEY RESPONDENTS Table 3.1 presents the distribution of women and men age 15-49 by age, religion, marital status, urban-rural residence, region, education level, and wealth quintile. The proportion of respondents in each age group generally decreases as age increases, reflecting the comparatively young age structure of the population (see Chapter 2). The slightly lower proportion of women age 15-19 than age 20-24 could be evidence of a decline in fertility; however, a more plausible explanation is deliberate age misreporting on the part of interviewers. As shown in Appendix Table C.1, there were almost 50 percent more girls listed on the Household Questionnaire as being age 14 than age 15 (408 vs. 274). The problem is even more severe among boys. This pattern is almost certainly due to interviewers deliberately displacing the ages of these adolescents in order to avoid having to do an individual interview. To the extent that this displacement affects only those in the 15-19 age group, it might not have a large impact on the major survey indicators like fertility and family planning. However, it reflects a disturbing lack of commitment on the part of interviewers that may affect other aspects of data quality. The overwhelming majority of Liberian adults (more than 80 percent) are Christian and 10-12 percent are Muslim. Almost two-thirds of women (64 percent) are either currently married or living with a man, compared with 57 percent of men. The difference is mainly because men tend to marry later than women. This is reflected in the fact that only 26 percent of women have never married, compared with 38 percent of men. Women are also more likely than men to be divorced, separated, or widowed, which is probably due to the fact that men are more likely than women to remarry when a relationship ends. In terms of urban-rural residence, about 40 percent of women and men are urban and 58 to 60 percent are rural. The distribution of respondents by region shows that about one-third of respondents live in Monrovia and another one-third live in the North Central region (Bong, Nimba, and Lofa counties). Regions with the smallest proportion of respondents are South Eastern A (River Cess, Sinoe, and Grand Gedeh counties), South Eastern B (Rivergee, Grand Kru, and Maryland counties), and North Western (Bomi, Grand Cape Mount, and Gbarpolu counties). Men are considerably more likely than women to be educated. For example, 42 percent of women age 15-49 have never been to school, compared with only 18 percent of men. At the other end of the spectrum, men are twice as likely as women to have been to secondary school (51 percent of men vs. 25 percent of women). By definition, roughly one-fifth of respondents fall into each wealth quintile. 30 | Characteristics of Respondents Table 3.1 Background characteristics of respondents Percent distribution of women and men age 15-49 by selected background characteristics, Liberia 2007 Women Men Background characteristic Weighted percent Weighted Unweighted Weighted percent Weighted Unweighted Age 15-19 18.5 1,312 1,340 19.2 1,156 1,178 20-24 19.2 1,363 1,386 17.3 1,039 1,065 25-29 16.4 1,166 1,161 15.3 917 897 30-34 13.5 956 1,003 12.8 766 768 35-39 13.5 956 927 13.8 830 819 40-44 9.4 665 671 11.4 687 657 45-49 9.5 674 604 10.2 613 625 Religion Christian 84.7 6,005 6,116 81.9 4,919 5,023 Muslim 10.4 734 694 11.8 711 685 Traditional religion 0.6 44 28 2.4 147 88 No religion 3.4 239 184 3.3 199 182 Other/missing 1.0 69 70 0.6 34 31 Marital status Never married 26.1 1,853 1,906 37.8 2,274 2,368 Married 41.6 2,953 2,913 32.6 1,960 2,004 Living together 22.4 1,587 1,595 24.2 1,452 1,325 Divorced/separated 7.3 514 511 4.6 279 279 Widowed 2.6 185 167 0.7 40 31 Residence Urban 42.3 2,998 3,194 40.4 2,426 2,531 Rural 57.7 4,094 3,898 59.6 3,583 3,478 Region Monrovia 32.8 2,329 1,858 31.0 1,862 1,428 North Western 7.2 509 765 6.7 405 654 South Central 14.3 1,011 1,071 14.9 894 934 South Eastern A 5.3 375 803 5.9 357 724 South Eastern B 6.4 451 1,244 6.8 407 1,120 North Central 34.1 2,417 1,351 34.7 2,084 1,149 Education No education 42.4 3,005 2,961 17.6 1,056 943 Primary 32.2 2,280 2,425 31.5 1,895 2,025 Secondary and higher 25.4 1,799 1,700 50.9 3,056 3,037 Wealth quintile Lowest 17.6 1,251 1,346 17.7 1,062 1,187 Second 18.8 1,332 1,383 19.6 1,181 1,215 Middle 19.2 1,359 1,396 19.5 1,170 1,195 Fourth 22.3 1,580 1,564 19.3 1,160 1,152 Highest 22.1 1,569 1,403 23.9 1,437 1,260 Total 15-49 100.0 7,092 7,092 100.0 6,009 6,009 Note: Education categories refer to the highest level of education attended, whether or not that level was completed. Total includes a small number of cases with missing values. 3.2 EDUCATIONAL ATTAINMENT BY BACKGROUND CHARACTERISTICS Tables 3.2.1 and 3.2.2 present an overview of the relationship between the respondent’s level of education and other background characteristics. The results show large differences between women and men age 15-49. As mentioned above, the proportion who have never been to school is twice as high among women than men (42 percent vs. 18 percent). Another measure of the differences by gender is that the median years of education is 1.6 for women and 5.8 for men. Characteristics of Respondents | 31 Table 3.2.1 Educational attainment: Women Percent distribution of women age 15-49 by highest level of schooling attended or completed, and median grade completed, according to background characteristics, Liberia 2007 Highest level of schooling Background characteristic No education Some primary Completed primary1 Some secondary Completed secondary2 More than secondary Missing Total Median years completed Number of women Age 15-24 22.9 39.2 7.6 25.9 3.3 1.0 0.0 100.0 3.7 2,675 15-19 16.9 49.3 8.5 23.8 1.0 0.5 0.0 100.0 3.5 1,312 20-24 28.8 29.5 6.7 28.0 5.4 1.5 0.1 100.0 4.0 1,363 25-29 43.0 26.5 4.3 14.9 8.9 2.3 0.0 100.0 1.4 1,166 30-34 47.4 24.0 4.5 12.7 7.3 3.9 0.2 100.0 0.5 956 35-39 54.5 16.6 4.2 13.5 8.6 2.3 0.3 100.0 0.0 956 40-44 61.5 14.2 3.7 13.1 5.0 2.3 0.3 100.0 0.0 665 45-49 75.2 10.6 0.9 6.9 4.0 2.3 0.0 100.0 0.0 674 Residence Urban 24.3 22.9 6.8 29.3 11.9 4.5 0.1 100.0 5.3 2,998 Rural 55.6 29.9 4.0 9.1 1.1 0.2 0.1 100.0 0.0 4,094 Region Monrovia 20.8 21.5 6.8 31.3 14.3 5.2 0.1 100.0 5.9 2,329 North Western 60.3 23.7 4.8 9.6 1.6 0.0 0.0 100.0 0.0 509 South Central 51.7 28.8 2.4 13.6 2.4 0.9 0.2 100.0 0.0 1,011 South Eastern A 47.3 35.6 7.3 8.5 1.0 0.3 0.1 100.0 0.1 375 South Eastern B 41.3 38.6 7.1 11.3 1.3 0.4 0.0 100.0 1.6 451 North Central 54.9 28.6 4.2 10.5 1.2 0.4 0.1 100.0 0.0 2,417 Wealth quintile Lowest 65.3 26.1 2.9 5.1 0.3 0.0 0.2 100.0 0.0 1,251 Second 60.8 28.9 3.4 6.6 0.3 0.0 0.0 100.0 0.0 1,332 Middle 44.4 33.8 6.3 13.3 1.7 0.3 0.1 100.0 1.0 1,359 Fourth 34.0 26.5 6.4 25.8 6.1 1.0 0.0 100.0 3.5 1,580 Highest 15.0 20.5 6.3 32.5 17.6 7.9 0.1 100.0 6.9 1,569 Total 42.4 27.0 5.2 17.6 5.7 2.0 0.1 100.0 1.6 7,092 Note: Total includes a small fraction of information missing on educational attainment. 1 Completed 6 grade at the primary level 2 Completed 12 grade at the secondary level Among women, younger persons have generally reached higher levels of school than older people; however, among men, the median years of education show little change across age groups. For both women and men, urban residents are better educated than rural residents. For example, the median number of years of school is 5.3 for urban women and 0 for rural women. Among the regions, Monrovia has by far the largest proportion of women and men who have attended secondary school and above. The educational level of both women and men in North Western region is particularly low, with 60 percent of women and 39 percent of men having no schooling at all. As expected, the level of education increases with the wealth index. For example, among the poorest quintile of women, only 5 percent have at least some secondary education, compared with 58 percent of those in the richest category. 32 | Characteristics of Respondents Table 3.2.2 Educational attainment: Men Percent distribution of men age 15-49 by highest level of schooling attended or completed, and median grade completed, according to background characteristics, Liberia 2007 Highest level of schooling Background characteristic No education Some primary Completed primary1 Some secondary Completed secondary2 More than secondary Missing Total Median years completed Number of men Age 15-24 8.0 41.7 6.7 37.2 4.5 1.9 0.0 100.0 4.9 2,195 15-19 6.8 56.0 7.2 29.1 0.8 0.2 0.0 100.0 3.9 1,156 20-24 9.4 25.7 6.1 46.2 8.6 3.8 0.1 100.0 6.7 1,039 25-29 21.5 19.6 5.0 34.2 13.2 6.5 0.1 100.0 6.3 917 30-34 20.7 21.4 3.5 28.4 16.7 9.4 0.0 100.0 6.4 766 35-39 23.8 19.3 5.1 30.0 13.4 8.4 0.0 100.0 6.1 830 40-44 22.4 11.4 3.0 27.0 22.1 14.0 0.0 100.0 8.3 687 45-49 28.2 16.7 2.1 22.0 20.4 10.4 0.2 100.0 6.7 613 Residence Urban 8.4 16.1 4.7 37.7 19.5 13.5 0.1 100.0 8.4 2,426 Rural 23.8 33.7 5.1 28.0 7.3 2.1 0.0 100.0 4.0 3,583 Region Monrovia 7.7 14.6 4.7 36.4 20.5 16.0 0.1 100.0 8.8 1,862 North Western 39.1 21.3 4.8 25.8 7.7 1.3 0.0 100.0 2.7 405 South Central 23.3 32.9 2.2 28.8 10.3 2.6 0.0 100.0 4.1 894 South Eastern A 11.4 37.5 5.9 34.9 8.0 2.1 0.2 100.0 5.0 357 South Eastern B 8.9 34.7 8.1 36.5 10.1 1.6 0.0 100.0 5.5 407 North Central 22.5 32.2 5.5 29.0 7.7 3.1 0.0 100.0 4.3 2,084 Wealth quintile Lowest 31.6 37.7 4.5 22.5 3.3 0.4 0.0 100.0 2.4 1,062 Second 25.1 34.8 6.7 27.0 5.4 1.0 0.0 100.0 3.7 1,181 Middle 18.3 29.9 4.2 35.6 9.6 2.2 0.1 100.0 5.2 1,170 Fourth 11.7 20.5 5.0 36.6 19.6 6.5 0.1 100.0 7.3 1,160 Highest 5.1 13.9 4.2 36.1 20.7 19.9 0.1 100.0 9.5 1,437 Total 15-49 17.6 26.6 4.9 31.9 12.2 6.7 0.0 100.0 5.8 6,009 1 Completed grade 6 at the primary level 2 Completed grade 12 at the secondary level 3.3 LITERACY The ability to read and write is an important personal asset, allowing individuals increased opportunities in life. Knowing the distribution of the literate population can help program managers, especially for health and family planning, know how to reach women and men with their messages. Unlike previous surveys, in which respondents were asked if they could read, the 2007 LDHS assessed the ability to read among women and men who had never been to school or who had attended only the primary level by asking respondents to read a simple, short sentence.1 Tables 3.3.1 and 3.3.2 show the percent distribution of female and male respondents, respectively, by level of literacy and percent literate according to background characteristics. The data show that literacy among adult women is far lower (41 percent) than for men (70 percent). The difference is much larger at older ages; only 17 percent of women age 45-49 are literate, compared with 62 percent of men. Although the discrepancies in literacy by sex have declined among the younger generation, there are still large gaps; only 58 percent of women age 15-19 are literate, compared with 73 percent of men age 15-19. 1 . These sentences include the following: 1. The child is reading a book; 2. Farming is hard work; 3. Parents should care for their children; 4. The rains were heavy this year. Characteristics of Respondents | 33 For both sexes, there is a strong urban-rural differential in literacy, with far more urban than rural residents being literate. Monrovia has the highest proportion of women and men who are literate, while North Western region has the lowest. Literacy increases as wealth increases. For example, the proportion of women age 15-49 who can read increases from 18 percent among those in the lowest wealth quintile to 73 percent of those in the highest quintile. This pattern also holds for men. Table 3.3.1 Literacy: Women Percent distribution of women age 15-49 by level of schooling attended and level of literacy, and percentage literate, according to background characteristics, Liberia 2007 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 No card with required language Blind/ visually impaired Missing Total Percent- age literate1 Number of women Age 15-19 25.3 10.9 22.2 40.8 0.0 0.0 0.7 100.0 58.4 1,312 20-24 34.9 5.3 11.6 47.4 0.1 0.0 0.7 100.0 51.9 1,363 25-29 26.2 2.8 10.0 60.2 0.2 0.1 0.6 100.0 39.0 1,166 30-34 23.9 3.9 8.2 62.0 0.4 0.1 1.4 100.0 36.1 956 35-39 24.4 2.4 7.4 64.4 0.1 0.0 1.1 100.0 34.3 956 40-44 20.4 1.6 4.4 73.1 0.1 0.0 0.4 100.0 26.3 665 45-49 13.2 1.6 2.4 80.9 0.5 0.3 1.0 100.0 17.2 674 Residence Urban 45.8 5.6 9.7 38.1 0.2 0.0 0.6 100.0 61.2 2,998 Rural 10.4 4.0 11.5 72.8 0.2 0.1 1.0 100.0 25.9 4,094 Region Monrovia 50.8 4.7 9.7 34.1 0.1 0.0 0.6 100.0 65.2 2,329 North Western 11.2 2.1 9.2 77.0 0.0 0.2 0.2 100.0 22.6 509 South Central 17.0 3.0 6.5 73.0 0.4 0.0 0.1 100.0 26.5 1,011 South Eastern A 9.8 6.0 11.3 71.6 0.0 0.8 0.5 100.0 27.1 375 South Eastern B 13.0 7.1 12.5 67.0 0.1 0.2 0.2 100.0 32.5 451 North Central 12.1 5.2 13.5 67.3 0.3 0.0 1.6 100.0 30.8 2,417 Wealth quintile Lowest 5.4 4.0 8.7 81.0 0.1 0.2 0.6 100.0 18.1 1,251 Second 6.9 3.2 11.7 76.8 0.2 0.1 1.2 100.0 21.8 1,332 Middle 15.3 5.1 14.3 64.0 0.2 0.1 1.0 100.0 34.7 1,359 Fourth 33.0 5.1 9.7 51.2 0.3 0.0 0.7 100.0 47.8 1,580 Highest 58.0 5.7 9.5 26.0 0.2 0.0 0.6 100.0 73.2 1,569 Total 25.4 4.7 10.7 58.1 0.2 0.1 0.8 100.0 40.8 7,092 1 Refers to women who attended secondary school or higher and women who can read a whole sentence or part of a sentence 34 | Characteristics of Respondents Table 3.3.2 Literacy: Men Percent distribution of men age 15-49 by level of schooling attended and level of literacy, and percentage literate, according to background characteristics, Liberia 2007 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 No card with required language Blind/ visually impaired Missing Total Percent- age literate1 Number of men Age 15-19 30.0 17.1 25.6 26.7 0.2 0.0 0.4 100.0 72.7 1,156 20-24 58.6 7.0 13.5 19.0 0.5 0.0 1.4 100.0 79.1 1,039 25-29 53.9 5.6 8.1 31.6 0.2 0.0 0.6 100.0 67.6 917 30-34 54.5 4.5 8.7 31.9 0.0 0.0 0.4 100.0 67.7 766 35-39 51.8 5.2 7.7 34.0 0.8 0.1 0.4 100.0 64.8 830 40-44 63.1 3.9 6.5 25.9 0.1 0.1 0.4 100.0 73.5 687 45-49 52.9 3.9 4.9 37.2 0.4 0.4 0.5 100.0 61.7 613 Residence Urban 70.7 6.7 8.2 13.4 0.4 0.1 0.5 100.0 85.6 2,426 Rural 37.4 8.1 14.4 39.2 0.3 0.1 0.6 100.0 59.9 3,583 Region Monrovia 72.9 6.4 7.6 12.1 0.3 0.1 0.6 100.0 86.9 1,862 North Western 34.8 6.7 11.7 45.7 0.9 0.0 0.1 100.0 53.3 405 South Central 41.7 6.3 12.1 39.1 0.3 0.1 0.3 100.0 60.1 894 South Eastern A 44.9 8.1 16.4 30.0 0.1 0.2 0.3 100.0 69.4 357 South Eastern B 48.3 8.3 13.2 29.6 0.2 0.2 0.4 100.0 69.7 407 North Central 39.7 8.8 14.7 35.5 0.3 0.0 0.9 100.0 63.3 2,084 Wealth quintile Lowest 26.2 7.8 14.0 51.5 0.3 0.0 0.2 100.0 48.0 1,062 Second 33.4 8.0 16.0 42.2 0.1 0.0 0.3 100.0 57.4 1,181 Middle 47.4 7.4 13.8 29.3 0.6 0.1 1.4 100.0 68.6 1,170 Fourth 62.7 8.3 8.7 19.2 0.5 0.1 0.5 100.0 79.7 1,160 Highest 76.6 6.4 8.0 8.2 0.2 0.0 0.6 100.0 91.0 1,437 Total 15-49 50.9 7.5 11.9 28.8 0.3 0.1 0.6 100.0 70.3 6,009 1 Refers to men who attended secondary school or higher and men who can read a whole sentence or part of a sentence 3.4 ACCESS TO MASS MEDIA Access to information is essential in increasing people’s knowledge and awareness of what is taking place around them, which may eventually affect their perceptions and behavior. It is important to know the types of persons who are more or less likely to be reached by the media for purposes of planning programs intended to spread information about health and family planning. In the survey, exposure to the media was assessed by asking how often a respondent reads a newspaper, watches television, or listens to a radio. Tables 3.4.1 and 3.4.2 show the percentage of women and men who were exposed to different types of media by age, urban-rural residence, region, level of education, and wealth quintile. Characteristics of Respondents | 35 Table 3.4.1 Exposure to mass media: Women Percentage of women age 15-49 who are exposed to specific media on a weekly basis, by background characteristics, Liberia 2007 At least once a week Number of women Background characteristic Reads a newspaper Watches television Listens to the radio All three media No media Age 15-19 17.3 42.7 49.0 12.0 37.0 1,312 20-24 19.8 36.2 51.9 13.6 40.0 1,363 25-29 14.9 30.0 51.6 10.0 42.3 1,166 30-34 14.5 25.7 50.5 9.3 44.2 956 35-39 15.3 23.5 49.2 10.9 46.4 956 40-44 11.3 17.8 43.8 7.6 53.7 665 45-49 8.3 11.7 35.9 4.7 60.8 674 Residence Urban 29.2 51.4 70.6 21.8 21.0 2,998 Rural 5.2 13.0 32.3 2.0 61.8 4,094 Region Monrovia 33.5 57.7 72.6 26.1 18.6 2,329 North Western 4.5 22.4 32.3 3.2 61.1 509 South Central 10.5 23.3 47.6 6.4 45.9 1,011 South Eastern A 5.1 18.2 42.7 2.4 51.8 375 South Eastern B 9.7 13.3 34.8 2.8 60.2 451 North Central 4.8 10.4 32.5 1.1 61.4 2,417 Education No education 0.0 12.7 32.8 0.0 63.0 3,005 Primary 6.9 29.0 45.6 3.5 44.3 2,280 Secondary and higher 51.6 57.2 78.4 36.5 14.0 1,799 Wealth quintile Lowest 2.6 4.8 20.7 0.3 75.9 1,251 Second 2.8 12.3 34.1 0.6 60.9 1,332 Middle 8.4 18.3 43.6 3.0 47.9 1,359 Fourth 17.5 36.1 56.6 11.2 34.4 1,580 Highest 39.9 65.7 78.9 32.2 12.9 1,569 Total 15.3 29.2 48.5 10.4 44.5 7,092 In general, women are less likely than men to have access to mass media; this is true for all types of media (Figure 3.1). Only 15 percent of women and 32 percent of men read newspapers at least once a week, while 29 percent of women and 38 percent of men watch television at least once a week, and 49 percent of women and 73 percent of men listen to the radio once a week. Only 10 percent of women and 20 percent of men are exposed to all three of these media sources. Almost half of women (45 percent) and 23 percent of men have no access to mass media. Urban residents are far more likely to have access to mass media than rural residents. For example, 22 percent of urban women are exposed to all three media at least once a week, compared with only 2 percent of rural women. Similarly, Monrovia has the highest proportion of women and men who have access to all three media. Exposure to media is positively associated with educational attainment; the proportion exposed to all three media outlets increases with increasing education level of respondents. Similarly, access to all three media outlets increases as wealth increases for both sexes. 36 | Characteristics of Respondents Table 3.4.2 Exposure to mass media: Men Percentage of men age 15-49 who are exposed to specific media on a weekly basis, by background characteristics, Liberia 2007 At least once a week Number of men Background characteristic Reads a newspaper Watches television Listens to the radio All three media No media Age 15-19 21.8 48.6 63.2 15.1 27.4 1,156 20-24 38.9 50.9 74.5 27.3 18.2 1,039 25-29 32.1 38.1 71.7 21.5 23.9 917 30-34 34.2 36.4 76.3 21.1 21.2 766 35-39 29.9 28.0 74.0 16.8 23.4 830 40-44 40.3 30.5 80.2 22.7 18.3 687 45-49 29.7 23.0 72.6 14.6 25.1 613 Residence Urban 55.4 64.3 89.3 40.5 5.8 2,426 Rural 16.1 20.7 61.2 6.1 34.0 3,583 Region Monrovia 60.7 70.1 91.6 46.5 3.7 1,862 North Western 18.5 22.6 68.5 8.6 27.3 405 South Central 23.1 34.0 64.9 14.2 30.4 894 South Eastern A 19.8 24.0 65.2 7.6 28.9 357 South Eastern B 23.1 25.6 56.5 7.0 35.1 407 North Central 16.4 19.6 63.9 5.7 31.9 2,084 Education No education 0.8 17.8 53.8 0.7 43.8 1,056 Primary 9.4 31.4 59.7 5.9 33.7 1,895 Secondary and higher 56.6 49.7 86.9 35.4 8.5 3,056 Wealth quintile Lowest 9.4 10.0 47.0 2.0 49.3 1,062 Second 13.0 18.0 62.0 4.5 34.3 1,181 Middle 25.1 31.7 71.8 11.1 22.6 1,170 Fourth 41.6 48.9 83.4 25.0 9.6 1,160 Highest 61.9 72.7 91.8 49.2 3.9 1,437 Total 15-49 31.9 38.3 72.5 20.0 22.6 6,009 15 29 49 32 38 73 Reads newspaper Watches TV Listens to radio 0 20 40 60 80 Percent Women Men Figure 3.1 Exposure to Mass Media at Least Once a Week among Women and Men LDHS 2007 Characteristics of Respondents | 37 3.5 EMPLOYMENT Male and female respondents age 15 and older were asked whether they were employed at the time of the survey and, if not, whether they were employed in the 12 months that preceded the survey. The measurement of employment, however, is difficult because some work, especially work on family farms, family businesses, or in the informal sector, is often not perceived as employment, and hence not reported as such. To avoid underestimating respondent’s employment, the DHS asks respondents several questions to probe for their employment status and to ensure complete coverage of employment in both the formal and informal sectors. Respondents are asked a number of questions to elicit their current employment status and continuity of employment in the 12 months before the survey. Employed individuals are those who say that they are currently working (i.e., worked in the past seven days) and those who worked at any time during the 12 months before the survey. Tables 3.5.1 and 3.5.2 show the percent distribution of adult women and men according to current and recent employment. The data show that 59 percent of women and 78 percent of men were currently employed, and 6 percent of women and 4 percent of men were not employed at the time of the survey but had been employed within the previous year (Figure 3.2). The proportion currently employed generally increases with age and number of living children. As expected, women and men who have never married are less likely to be currently employed than those who are currently married or divorced, separated, or widowed. Rural women and men are more likely to be currently employed than urban residents. There are notable regional variations in the proportion employed. Women in North Central region and men in South Eastern B and South Eastern A are the most likely to have been employed in the previous 12 months, and women in Monrovia and men in North Western and Monrovia are the least likely to be employed. Current employment generally declines with increasing education. The proportion currently employed generally decreases as wealth status of the respondent increases. LDHS 2007 Figure 3.2 Women’s Employment Status in the Past 12 Months Currently employed 59% Not employed in past 12 months 34% Not currently employed, but was in past 12 months 6% 38 | Characteristics of Respondents Table 3.5.1 Employment status: Women Percent distribution of women age 15-49 by employment status, according to background characteristics, Liberia 2007 Employed in the 12 months preceding the survey Not employed in the 12 months preceding the survey Background characteristic Currently employed1 Not currently employed Missing/ don't know Total Number of women Age 15-19 33.7 1.9 64.3 0.0 100.0 1,312 20-24 47.8 5.8 46.3 0.1 100.0 1,363 25-29 61.9 7.4 30.3 0.4 100.0 1,166 30-34 71.8 8.0 20.1 0.1 100.0 956 35-39 72.8 6.8 19.3 1.1 100.0 956 40-44 71.1 11.0 17.9 0.0 100.0 665 45-49 77.9 7.1 14.6 0.3 100.0 674 Marital status Never married 34.6 2.7 62.6 0.1 100.0 1,853 Married or living together 67.7 8.0 23.9 0.4 100.0 4,540 Divorced/separated/widowed 68.7 5.8 25.4 0.1 100.0 699 Number of living children 0 34.5 2.5 62.8 0.3 100.0 1,514 1-2 58.3 6.3 35.3 0.1 100.0 2,496 3-4 70.7 8.5 20.6 0.3 100.0 1,746 5+ 73.7 8.1 17.5 0.7 100.0 1,336 Residence Urban 44.4 5.4 50.1 0.1 100.0 2,998 Rural 70.0 7.1 22.5 0.4 100.0 4,094 Region Monrovia 44.5 5.0 50.4 0.0 100.0 2,329 North Western 44.1 22.2 33.6 0.0 100.0 509 South Central 60.6 2.4 36.5 0.5 100.0 1,011 South Eastern A 62.8 6.2 30.1 0.9 100.0 375 South Eastern B 60.3 8.3 31.0 0.4 100.0 451 North Central 75.1 5.7 18.9 0.4 100.0 2,417 Education No education 71.6 7.2 20.7 0.4 100.0 3,005 Primary 53.5 6.4 39.8 0.3 100.0 2,280 Secondary and higher 45.7 4.8 49.3 0.1 100.0 1,799 Wealth quintile Lowest 75.5 8.3 15.5 0.7 100.0 1,251 Second 71.6 7.9 20.3 0.3 100.0 1,332 Middle 59.6 7.5 32.9 0.1 100.0 1,359 Fourth 51.0 4.5 44.2 0.2 100.0 1,580 Highest 43.5 4.5 51.8 0.2 100.0 1,569 Total 59.2 6.4 34.2 0.3 100.0 7,092 Note: Total row includes a few cases with information missing. 1 "Currently employed" is defined as having done work in the past seven days. Includes persons who did not work in the past seven days but who are regularly employed and were absent from work for leave, illness, vacation, or any other such reason. Characteristics of Respondents | 39 Table 3.5.2 Employment status: Men Percent distribution of men age 15-49 by employment status, according to background characteristics, Liberia 2007 Employed in the 12 months preceding the survey Not employed in the 12 months preceding the survey Background characteristic Currently employed1 Not currently employed Missing/ don't know Total Number of men Age 15-19 47.0 5.1 47.8 0.0 100.0 1,156 20-24 65.6 4.1 30.1 0.2 100.0 1,039 25-29 82.6 3.2 14.2 0.0 100.0 917 30-34 89.4 3.3 7.2 0.0 100.0 766 35-39 94.6 2.1 3.2 0.1 100.0 830 40-44 92.0 3.3 4.7 0.0 100.0 687 45-49 93.4 3.0 3.6 0.0 100.0 613 Marital status Never married 54.3 4.6 41.0 0.1 100.0 2,274 Married or living together 92.4 2.9 4.6 0.1 100.0 3,413 Divorced/separated/widowed 83.4 3.6 12.9 0.0 100.0 319 Number of living children 0 55.9 4.6 39.4 0.1 100.0 2,275 1-2 85.9 3.6 10.4 0.1 100.0 1,493 3-4 93.6 2.2 4.2 0.0 100.0 1,153 5+ 94.1 2.8 2.9 0.1 100.0 1,088 Residence Urban 66.3 4.1 29.5 0.1 100.0 2,426 Rural 85.1 3.2 11.6 0.1 100.0 3,583 Region Monrovia 66.7 2.9 30.4 0.1 100.0 1,862 North Western 82.4 6.4 11.2 0.0 100.0 405 South Central 77.1 3.6 19.2 0.1 100.0 894 South Eastern A 84.8 7.6 7.6 0.1 100.0 357 South Eastern B 89.7 2.7 7.4 0.2 100.0 407 North Central 82.8 3.1 14.0 0.1 100.0 2,084 Education No education 91.3 2.7 6.0 0.0 100.0 1,056 Primary 73.0 3.5 23.4 0.1 100.0 1,895 Secondary and higher 75.6 3.9 20.5 0.1 100.0 3,056 Wealth quintile Lowest 89.6 3.3 7.0 0.0 100.0 1,062 Second 89.1 2.5 8.2 0.2 100.0 1,181 Middle 79.6 4.6 15.8 0.0 100.0 1,170 Fourth 69.9 4.1 25.9 0.1 100.0 1,160 Highest 63.5 3.3 33.2 0.0 100.0 1,437 Total 15-49 77.5 3.6 18.8 0.1 100.0 6,009 Note: Total row includes a few cases with missing information. 1 "Currently employed" is defined as having done work in the past seven days. Includes persons who did not work in the past seven days but who are regularly employed and were absent from work for leave, illness, vacation, or any other such reason. 40 | Characteristics of Respondents 3.6 OCCUPATION Respondents who are currently employed were asked to state their occupation, and the results are presented in Tables 3.6.1 and 3.6.2. Over half of working women (55 percent) and men (53 percent) are engaged in agricultural occupations. The next most common category of occupation is the sales and service sector (37 percent of women and 21 percent of men). For men, skilled manual jobs is the third major occupation category, employing 11 percent of all working men. Only 3 percent of employed Liberian women work in professional, technical, or managerial fields, compared with 8 percent of employed men. Table 3.6.1 Occupation: Women Percent distribution of women age 15-49 employed in the 12 months preceding the survey, by occupation, according to background characteristics, Liberia 2007 Background characteristic Profes- sional/ technical/ managerial Clerical Sales and services Skilled manual Unskilled manual Domestic service Agricul- ture Missing Total Number of women Age 15-19 0.4 0.0 39.7 1.3 0.9 0.1 54.3 3.2 100.0 468 20-24 1.3 0.0 37.4 0.5 0.6 0.5 55.9 3.7 100.0 730 25-29 3.5 0.1 37.7 1.5 0.7 0.9 52.8 2.7 100.0 808 30-34 2.9 0.3 42.1 2.1 0.1 0.6 49.7 2.1 100.0 763 35-39 3.3 0.0 41.0 0.7 0.3 0.9 51.6 2.1 100.0 761 40-44 3.3 0.0 34.0 1.2 0.1 0.4 59.0 2.0 100.0 546 45-49 3.4 0.0 27.3 0.1 0.0 0.0 67.9 1.1 100.0 573 Marital status Never married 3.4 0.1 48.3 1.4 0.5 0.1 41.2 4.9 100.0 692 Married or living together 2.5 0.1 34.0 0.7 0.3 0.4 60.0 2.0 100.0 3,436 Divorced/separated/ widowed 3.2 0.0 45.3 3.5 0.7 2.0 43.0 2.2 100.0 521 Number of living children 0 3.0 0.3 42.1 1.1 0.3 0.5 48.6 4.2 100.0 559 1-2 3.1 0.0 43.4 1.0 0.8 0.8 48.4 2.6 100.0 1,614 3-4 2.6 0.1 34.5 1.6 0.2 0.2 58.8 2.0 100.0 1,382 5+ 2.1 0.0 29.8 0.7 0.2 0.6 64.6 2.0 100.0 1,093 Residence Urban 5.7 0.2 81.2 1.8 0.2 1.5 5.1 4.2 100.0 1,492 Rural 1.3 0.0 16.7 0.8 0.5 0.1 79.1 1.6 100.0 3,156 Region Monrovia 6.7 0.1 85.6 1.5 0.3 1.7 1.0 3.2 100.0 1,154 North Western 0.8 0.0 35.3 3.7 0.0 0.0 58.1 2.2 100.0 338 South Central 1.7 0.1 37.7 0.7 1.9 0.4 54.8 2.8 100.0 637 South Eastern A 1.5 0.0 29.3 0.7 0.0 0.8 64.1 3.8 100.0 259 South Eastern B 2.7 0.1 9.8 0.1 0.1 0.0 85.9 1.4 100.0 309 North Central 1.2 0.1 14.6 0.7 0.1 0.1 81.2 1.9 100.0 1,951 Education No education 0.4 0.0 26.3 0.6 0.5 0.3 70.7 1.1 100.0 2,369 Primary 0.2 0.0 38.8 1.3 0.1 0.9 56.0 2.7 100.0 1,366 Secondary and higher 12.4 0.4 63.9 1.9 0.6 0.6 14.5 5.6 100.0 910 Wealth quintile Lowest 0.7 0.0 6.9 0.7 0.1 0.1 91.0 0.5 100.0 1,048 Second 0.9 0.0 13.2 0.2 0.2 0.1 83.4 2.0 100.0 1,058 Middle 1.6 0.0 33.7 1.3 0.9 0.3 59.8 2.3 100.0 911 Fourth 2.1 0.0 70.5 2.5 0.4 1.3 20.0 3.2 100.0 877 Highest 9.9 0.4 79.7 1.0 0.5 1.2 2.1 5.1 100.0 754 Total 2.7 0.1 37.4 1.1 0.4 0.5 55.3 2.5 100.0 4,648 Characteristics of Respondents | 41 Differences by background characteristics show that, as expected, rural women and men are more likely than urban residents to be employed in agricultural jobs. Similarly, those living in Monrovia are less likely to have agricultural occupations. Better educated and wealthier respondents are more likely than others to be employed in sales and service or in professional, technical, or managerial jobs. Table 3.6.2 Occupation: Men Percent distribution of men age 15-49 employed in the 12 months preceding the survey, by occupation, according to background characteristics, Liberia 2007 Background characteristic Profes- sional/ technical/ managerial Clerical Sales and services Skilled manual Unskilled manual Domestic service Agricul- ture Missing Total Number of men Age 15-19 1.1 0.1 16.4 10.6 5.9 0.1 54.7 11.2 100.0 603 20-24 3.5 0.3 25.3 12.5 3.6 0.4 48.1 6.4 100.0 724 25-29 4.5 2.0 20.0 12.1 2.9 0.3 54.4 3.9 100.0 786 30-34 7.4 2.1 24.2 12.3 1.0 0.2 51.0 1.7 100.0 711 35-39 11.1 1.7 20.5 11.1 1.8 0.1 53.1 0.6 100.0 803 40-44 13.9 1.0 20.0 8.9 2.1 0.4 52.0 1.5 100.0 655 45-49 15.2 2.2 15.7 10.0 0.6 0.0 55.5 0.8 100.0 591 Marital status Never married 4.7 0.9 23.0 13.2 4.5 0.3 44.4 9.0 100.0 1,340 Married or living together 9.3 1.4 19.9 9.8 1.6 0.2 56.4 1.4 100.0 3,251 Divorced/separated/ widowed 9.3 3.0 15.7 17.0 3.9 0.0 48.4 2.6 100.0 277 Number of living children 0 4.2 0.4 20.7 13.1 4.7 0.3 48.1 8.5 100.0 1,377 1-2 7.3 1.9 24.1 12.2 2.1 0.2 49.2 3.1 100.0 1,335 3-4 9.5 1.8 19.9 9.9 2.1 0.3 55.2 1.2 100.0 1,105 5+ 12.3 1.5 16.4 8.6 0.7 0.0 60.1 0.4 100.0 1,056 Residence Urban 14.4 2.8 45.2 19.0 3.7 0.5 7.6 6.8 100.0 1,709 Rural 4.6 0.6 7.2 6.9 1.9 0.0 76.9 1.9 100.0 3,163 Region Monrovia 15.6 2.4 50.9 17.8 3.5 0.4 2.0 7.4 100.0 1,296 North Western 2.1 1.3 7.1 16.9 2.3 0.2 62.2 7.8 100.0 360 South Central 5.5 1.6 14.1 11.3 3.2 0.2 61.5 2.6 100.0 721 South Eastern A 6.9 0.8 11.0 10.3 5.1 0.1 62.9 2.9 100.0 330 South Eastern B 7.3 1.4 9.1 6.6 2.1 0.3 71.4 1.9 100.0 376 North Central 5.1 0.6 7.9 6.2 1.3 0.0 77.9 0.9 100.0 1,791 Education No education 0.8 0.0 11.7 14.0 0.7 0.0 72.3 0.5 100.0 993 Primary 0.6 0.1 14.2 8.2 3.9 0.1 70.4 2.5 100.0 1,450 Secondary and higher 15.4 2.7 27.9 11.7 2.5 0.3 34.0 5.5 100.0 2,428 Wealth quintile Lowest 3.1 0.2 3.1 5.3 1.6 0.0 85.6 1.1 100.0 987 Second 2.3 0.3 5.9 6.3 1.6 0.1 82.1 1.5 100.0 1,081 Middle 6.2 1.1 13.9 13.1 2.9 0.2 58.3 4.2 100.0 985 Fourth 8.6 2.1 36.7 18.7 3.9 0.5 24.0 5.4 100.0 858 Highest 20.7 3.3 47.2 13.8 3.1 0.3 5.2 6.4 100.0 961 Total 15-49 8.0 1.4 20.5 11.1 2.5 0.2 52.6 3.6 100.0 4,873 3.7 EARNINGS AND TYPE OF EMPLOYMENT Table 3.7 presents the percent distribution of employed women age 15-49, by type of earnings and employer characteristics, according to type of employment (agricultural or nonagricultural). Sixty-two percent of women receive cash for their work, and one in three is not paid. Women are more likely to be paid in cash and kind or not paid at all if they are employed in agricultural activities. The vast majority (86 percent) of working women are self-employed, with only 5 percent employed by a non-family member and 9 percent employed within the family. Women are more 42 | Characteristics of Respondents likely to be employed by a non-family member if they are doing nonagricultural work than if they are engaged in agricultural work. Just over two-thirds of working women are employed throughout the year, and 28 percent have seasonal jobs. Women are more prone to seasonal work if they are employed in agricultural activities than if they are in nonagricultural occupations and, conversely, continuity of employment is more assured for women who are engaged in nonagricultural work. Table 3.7 Type of employment: Women Percent distribution of women age 15-49 employed in the 12 months preceding the survey by type of earnings, type of employer, and continuity of employment, according to type of employment (agricultural or nonagricultural), Liberia 2007 Employment characteristic Agricultural work Nonagricultural work Total Type of earnings Cash only 6.6 59.0 29.4 Cash and in-kind 41.9 20.2 32.1 In-kind only 4.7 1.7 3.4 Not paid 46.4 17.4 34.0 Missing 0.4 1.6 1.1 Total 100.0 100.0 100.0 Type of employer Employed by family member 8.6 8.1 8.6 Employed by non-family member 2.2 8.1 5.0 Self-employed 89.1 83.0 85.9 Missing 0.1 0.8 0.6 Total 100.0 100.0 100.0 Continuity of employment All year 54.2 84.2 67.0 Seasonal 43.1 9.3 28.3 Occasional 1.9 5.5 3.7 Missing 0.8 1.0 1.1 Total 100.0 100.0 100.0 Number of women employed during the last 12 months 2,572 1,963 4,648 Note: Total includes women with missing information on type of employment who are not shown separately. 3.8 KNOWLEDGE AND ATTITUDES CONCERNING TUBERCULOSIS The 2007 LDHS collected data on women’s and men’s knowledge and attitudes concerning tuberculosis (TB). Tables 3.8.1 and 3.8.2 show the percentage of women and men who have heard of TB, and among those who have heard of TB, the percentage who know that TB is spread through air by coughing, the percentage who believe that TB can be cured, and the percentage who would want a family member’s TB to be kept a secret. Characteristics of Respondents | 43 Table 3.8.1 Knowledge and attitudes concerning tuberculosis: Women Percentage of women age 15-49 who have heard of tuberculosis (TB), and among women who have heard of TB, the percentage who know that TB is spread through the air by coughing, the percentage who believe that TB can be cured, and the percentage who would want to keep secret that a family member has TB, by background characteristics, Liberia 2007 Among respondents who have heard of TB: Percentage who report that TB is spread through the air by coughing Percentage who believe that TB can be cured Percentage who would want a family member's TB kept secret Among all respondents Background characteristic Percentage who have heard of TB Number Number Age 15-19 86.5 1,312 58.2 69.9 15.1 1,135 20-24 91.6 1,363 61.2 73.4 19.3 1,249 25-29 89.5 1,166 61.0 76.6 14.2 1,044 30-34 92.6 956 59.6 76.6 12.8 886 35-39 91.8 956 59.5 81.3 18.0 877 40-44 92.2 665 60.2 77.2 12.9 613 45-49 88.5 674 51.4 75.5 14.2 596 Residence Urban 97.3 2,998 67.0 83.3 15.3 2,918 Rural 85.1 4,094 52.6 68.7 15.8 3,483 Region Monrovia 99.1 2,329 68.1 84.2 14.6 2,309 North Western 90.5 509 57.9 66.2 15.1 461 South Central 92.4 1,011 56.7 70.3 23.0 934 South Eastern A 89.9 375 63.9 64.3 17.1 338 South Eastern B 86.5 451 61.5 71.8 8.5 390 North Central 81.5 2,417 48.9 72.3 14.4 1,970 Education No education 85.8 3,005 50.6 67.5 14.4 2,579 Primary 90.2 2,280 57.2 73.0 14.6 2,058 Secondary and higher 97.7 1,799 74.0 89.7 18.4 1,757 Wealth quintile Lowest 79.5 1,251 46.8 61.5 16.1 994 Second 85.4 1,332 54.9 68.8 18.4 1,138 Middle 88.9 1,359 57.1 74.5 14.6 1,209 Fourth 96.2 1,580 60.2 79.7 11.4 1,521 Highest 98.1 1,569 70.8 85.7 18.0 1,539 Total 90.3 7,092 59.2 75.4 15.6 6,401 More than nine in ten women and men in Liberia have heard of TB. The youngest respondents, those in rural areas, and those in North Central region are somewhat less likely than others to have heard of TB. Similarly, respondents with less education and less wealth are also less likely to know about TB, though the differences are not large. Among women and men who have heard of TB, a majority know that TB is spread through the air by coughing (59 percent of women and 69 percent of men). About three-quarters of respondents know that TB can be cured. As with knowledge of TB in general, knowledge that TB is spread through the air by coughing and knowledge that it can be cured is generally lower among the youngest respondents, those with less education, and those in the lower wealth quintiles. Fortunately, there is apparently little stigma related to TB. Only 16 percent of women and 11 percent of men said that if a family member had TB, they would want it to remain a secret. 44 | Characteristics of Respondents Table 3.8.2 Knowledge and attitudes concerning tuberculosis: Men Percentage of men age 15-49 who have heard of tuberculosis (TB), and among men who have heard of TB, the percentage who know that TB is spread through the air by coughing, the percentage who believe that TB can be cured, and the percentage who would want to keep secret that a family member has TB, by background characteristics, Liberia 2007 Among respondents who have heard of TB: Background characteristic Percentage who report that TB is spread through the air by coughing Percentage who believe that TB can be cured Percentage who would want a family member's TB kept secret Number Among all respondents Percentage who have heard of TB Number Age 15-19 78.3 1,156 59.8 67.4 16.1 905 20-24 90.9 1,039 68.7 71.1 13.4 945 25-29 94.1 917 67.9 70.4 10.2 863 30-34 96.4 766 67.4 73.0 9.3 739 35-39 96.0 830 70.9 73.0 7.8 798 40-44 97.8 687 75.3 79.2 9.3 672 45-49 97.6 613 74.2 76.3 11.5 598 Residence Urban 95.7 2,426 75.9 82.0 12.8 2,323 Rural 89.2 3,583 63.4 65.5 10.2 3,196 Region Monrovia 96.3 1,862 77.7 82.8 12.5 1,794 North Western 93.5 405 66.5 77.6 3.8 379 South Central 97.1 894 64.5 69.0 11.8 868 South Eastern A 88.4 357 63.7 66.5 10.9 315 South Eastern B 87.3 407 74.9 69.2 6.7 355 North Central 86.8 2,084 61.8 64.4 12.4 1,808 Education No education 89.4 1,056 61.9 59.4 9.0 943 Primary 85.4 1,895 57.8 60.9 12.4 1,617 Secondary and higher 96.7 3,056 76.7 82.9 11.4 2,955 Wealth quintile Lowest 88.6 1,062 62.7 56.4 8.7 941 Second 88.5 1,181 60.9 63.7 9.8 1,045 Middle 90.2 1,170 66.6 70.8 11.7 1,055 Fourth 94.8 1,160 74.6 82.3 12.6 1,099 Highest 96.0 1,437 75.4 83.5 12.8 1,379 Total 15-49 91.8 6,009 68.7 72.5 11.3 5,519 3.9 SMOKING In order to measure the extent of smoking among Liberian adults, women and men who were interviewed in the 2007 LDHS were asked if they currently smoked cigarettes or used tobacco. Only 2 percent of women said they used tobacco of any kind and only 1 percent said they smoked cigarettes (data not shown). Twenty percent of men use tobacco products, with 15 percent saying that they smoke cigarettes. Although the proportion of women who smoke is too small to show details, Table 3.9 shows differentials in smoking among men. Characteristics of Respondents | 45 Younger men are far less likely to smoke than men in their 30s and 40s. Similarly, urban men, men in Monrovia, men with more education, and men in the higher wealth quintiles are less likely than other men to smoke. Among men who smoke cigarettes, one-fifth say they smoke 10 or more cigarettes per day, one-quarter say they smoke 6-9 cigarettes per day, and one-third say they smoke only 3-5 cigarettes per day. Table 3.9 Use of tobacco: Men Percentage of men age 15-49 who smoke cigarettes or a pipe or use other tobacco products, and the percent distribution of cigarette smokers by number of cigarettes smoked in the preceding 24 hours, according to background characteristics, Liberia 2007 Number of cigarettes in the past 24 hours Background characteristic Cigarettes Pipe Other tobacco Does not use tobacco Number of men 0 1-2 3-5 6-9 10+ Don't know/ missing Total Number of cigarette smokers Age 15-19 0.8 0.0 0.3 98.9 1,156 * * * * * * 100.0 10 20-24 4.2 0.5 1.9 94.8 1,039 (0.0) (20.3) (36.3) (22.6) (18.2) (2.6) 100.0 43 25-29 15.8 1.0 5.0 82.5 917 3.1 20.2 20.4 31.2 20.8 4.4 100.0 145 30-34 21.2 1.2 7.4 77.5 766 3.0 22.9 29.7 28.1 16.3 0.1 100.0 162 35-39 24.8 1.1 5.5 74.2 830 0.4 15.2 35.2 25.1 20.2 3.8 100.0 206 40-44 28.1 0.9 5.3 71.3 687 1.2 11.3 39.6 21.6 25.8 0.5 100.0 193 45-49 24.6 1.3 5.6 72.9 613 1.3 11.8 31.7 32.6 22.2 0.3 100.0 151 Residence Urban 11.3 0.8 2.3 87.9 2,426 1.4 8.8 26.9 34.2 26.8 1.9 100.0 274 Rural 17.8 0.8 5.2 81.0 3,583 1.7 19.2 35.1 23.5 18.6 1.9 100.0 636 Region Monrovia 11.6 1.0 2.2 87.6 1,862 1.6 6.2 22.2 39.9 28.6 1.4 100.0 216 North Western 25.7 1.1 2.5 73.5 405 2.2 13.6 45.1 20.9 16.5 1.7 100.0 104 South Central 16.9 0.9 5.8 82.3 894 1.4 12.7 37.9 28.6 17.8 1.6 100.0 151 South Eastern A 21.0 0.2 8.2 77.5 357 2.1 13.5 30.7 23.2 29.2 1.3 100.0 75 South Eastern B 15.1 1.2 4.0 83.0 407 0.6 22.6 40.2 17.0 16.2 3.4 100.0 61 North Central 14.5 0.5 4.4 84.1 2,084 1.6 24.9 32.1 21.3 17.9 2.3 100.0 303 Education No education 29.4 1.0 7.5 68.2 1,056 1.9 15.1 31.9 23.1 25.4 2.6 100.0 311 Primary 14.1 0.4 4.5 85.2 1,895 0.6 20.2 35.8 27.4 15.3 0.7 100.0 267 Secondary and higher 10.9 0.9 2.5 88.3 3,056 2.1 13.7 30.8 29.7 21.5 2.1 100.0 332 Wealth quintile Lowest 20.4 0.9 7.4 78.6 1,062 0.7 26.1 35.9 20.6 15.7 1.0 100.0 217 Second 20.9 0.8 5.7 77.7 1,181 1.8 18.0 31.7 24.8 22.3 1.4 100.0 247 Middle 14.8 0.7 4.0 83.3 1,170 2.2 10.9 41.7 23.5 19.9 1.7 100.0 173 Fourth 11.6 0.8 2.6 87.7 1,160 0.3 15.5 32.2 29.8 19.4 2.8 100.0 134 Highest 9.8 0.8 1.3 89.8 1,437 3.1 4.0 18.6 40.6 30.2 3.5 100.0 140 Total 15-49 15.2 0.8 4.0 83.8 6,009 1.6 16.1 32.6 26.7 21.1 1.9 100.0 911 Note: Numbers in parentheses are based on 25-49 unweighted men; an asterisk denotes a figure based on fewer than 25 unweighted men that has been suppressed. Fertility Levels, Trends, and Differentials | 47 FERTILITY LEVELS, TRENDS, AND DIFFERENTIALS 4 This chapter looks at a number of fertility indicators including levels, patterns, and trends in both current and cumulative fertility; the length of birth intervals; and the age at which women initiate childbearing. Information on current and cumulative fertility is essential in monitoring population growth. The data on birth intervals are important because short intervals are strongly associated with childhood mortality. The age at which childbearing begins can also have a major impact on the health and well-being of both the mother and the child. Data on fertility were collected in several ways. Each woman interviewed was asked about all of the births she had had in her lifetime. To ensure completeness of the responses, the duration, the month and year of termination, and the result of the pregnancy were recorded for each pregnancy. In addition, questions were asked separately about sons and daughters who live with the mother, those who live elsewhere, and those who have died. Subsequently, a list of all births was recorded along with name, age if still alive, and age at death if dead. Finally, information was collected on whether women were pregnant at the time of the survey. 4.1 CURRENT FERTILITY The level of current fertility is one of the most important topics in this report because of its direct relevance to population policies and programs. Current fertility can be measured using the age-specific fertility rate (ASFR), the total fertility rate (TFR), the general fertility rate, and the crude birth rate. The ASFR provides the age pattern of fertility, and the TFR refers to the number of live births that a woman would have had if she were subject to the current ASFRs throughout the reproductive ages (15-49 years). The general fertility rate is expressed as the number of live births per 1,000 women of reproductive age, and the crude birth rate is expressed as the number of live births per 1,000 population. The measures of fertility presented in this chapter refer to the period three years before the survey. This generates a sufficient number of births to provide robust and current estimates. Current estimates of fertility levels are presented in Table 4.1 by urban-rural residence. Table 4.1 shows a TFR of 5.2 children per woman for the three-year period preceding the survey (roughly 2004 through 2006). A TFR of 5.2 means that a Liberian woman who is at the beginning of her childbearing years would give birth to an average of just over five children by the end of her reproductive period if fertility levels remained constant at the levels observed in the three-year period before the 2007 Liberia Demographic and Health Survey (LDHS). The TFR of 6.2 for women in rural areas is more than two births higher than the rate of 3.8 for women in urban areas. The peak childbearing years are 20-24, followed by 25-29. Women age 20-24 and 25-29 years contribute 23 and 22 percent, respectively, to the TFR. In the rural areas, fertility peaks at ages 20-24, 25-29, and 30-34 years, and then sharply declines at ages 40-44 and 45-49 years. In the urban area, fertility follows a similar pattern. Fertility at each age is higher in rural than in urban areas (Figure Table 4.1 Current fertility Age-specific and total fertility rate (TFR), the general fertility rate (GBR), and the crude birth rate (CBR) for the three years preceding the survey, by residence, Liberia 2007 Residence Age group Urban Rural Total 15-19 101 182 141 20-24 193 281 243 25-29 168 269 226 30-34 135 222 187 35-39 104 165 142 40-44 45 87 72 45-49 17 33 29 TFR 3.8 6.2 5.2 GFR 134 214 180 CBR 32.5 40.4 37.6 Notes: Age-specific fertility rates are per 1,000 women. Rates for age group 45-49 may be slightly biased due to truncation. Rates are for the period 1-36 months before the interview. TFR: Total fertility rate, expressed per woman GFR: General fertility rate, expressed per 1,000 women CBR: Crude birth rate, expressed per 1,000 population 48 | Fertility Levels, Trends, and Differentials 4.1). Adolescent fertility is very high, with teenage girls contributing about 14 percent of the TFR in Liberia. The general fertility rate is 180. This means that there were 180 births for every 1,000 women during the three-year period preceding the survey. There is a clear differential in this rate by residence: 214 births per 1,000 women age 15-44 years in the rural areas versus 134 births per 1,000 women age 15-44 years in the urban areas. The crude birth rate for Liberia is 38 births per 1,000 population. As with the general fertility rate, there is also a clear differential by residence: 40 births per 1,000 population in the urban areas versus 33 births per 1,000 population in the urban areas. The survey results also point to the extreme youthfulness of childbearing in Liberia. Indeed, women under 25 years of age contribute about two-fifths of the TFR in Liberia. 4.2 FERTILITY DIFFERENTIALS BY BACKGROUND CHARACTERISTICS Fertility is known to vary by residence, educational background, and other background char- acteristics of a woman. Table 4.2 shows several different indicators of fertility—the TFR, the mean number of births to women age 40-49, and the percentage currently pregnant—by residence, region, education, and wealth quintile. The mean number of births to women age 40-49 is an indicator of cumulative fertility; it reflects the fertility performance of older women who are nearing the end of their reproductive period. If fertility remains stable over time, the two fertility measures, TFR, and children ever born tend to be very similar. The percentage pregnant provides a useful additional measure of current fertility, although it is recognized that it may not capture all pregnancies in an early stage. As mentioned above, the data in Table 4.2 show a strong urban-rural differential in fertility. Regional variations in fertility are marked, ranging from a high of almost seven births per woman in South Eastern A to a low of three in Monrovia. The TFR is inversely related to the level of education. Women with no education give birth to almost twice as many children as women who have been to � � � � � � � � � � � � � � 15-19 20-24 25-29 30-34 35-39 40-44 45-49 Age group 0 50 100 150 200 250 300 Births per 1,000 women Urban Rural� � LDHS 2007 Figure 4.1 Age-Specific Fertility Rates by Urban-Rural Residence Fertility Levels, Trends, and Differentials | 49 secondary school (6.0 vs. 3.3 births). Fertility is also closely associated with wealth, decreasing with increasing wealth. Table 4.2 shows that the TFR decreases from 6.5 births among women in the lowest wealth quintile to 2.8 births among women in the highest wealth quintile, a difference of almost four births. Just under 11 percent of the women interviewed at the time of the survey said they were pregnant. Rural women are much more likely to be pregnant (13 percent) than urban women (8 percent). Current pregnancy is highest in South Eastern B (15 percent) and lowest in Monrovia (8 percent). The percentage of women currently pregnant is lower among women with at least some secondary school (7 percent) than among those with either no education or only primary education (both 12 percent). Also, the percentage of currently pregnant women is highest (15 percent) among the poorest segment of women and is lowest (8 percent) among the richest. Table 4.2 also shows the mean number of children ever born by women age 40-49 years. Overall, women age 40-49 years have given birth to an average of 6.2 children. Differences in the mean number of children ever born generally follow a similar pattern to that for the TFR and the percentage currently pregnant. 4.3 FERTILITY TRENDS Table 4.3 examines trends in fertility in Liberia by comparing the results of the 2007 LDHS with the two earlier LDHS surveys (1986 and 1999-2000). This comparison is appropriate because all three surveys used similar methods of data collection, although the current fertility rates for the 1986 LDHS are based on births in the five years preceding the survey and those for the 1999- 2000 LDHS and the 2007 LDHS are based on births in the three years preceding the survey. Table 4.3 Trends in fertility from various surveys Age-specific fertility rates from various surveys, Liberia 1981-85 to 2004-06 Mother’s age at birth/ approximate calendar period Survey 1986 LDHS 1981-1985 1999-2000 LDHS 1997-1999 2007 LDHS 2004-2006 15-19 184 135 141 20-24 285 279 243 25-29 272 241 226 30-34 223 211 187 35-39 181 171 142 40-44 114 112 72 45-49 63 83 29 Total fertility rate 6.6 6.2 5.2 Note: Age-specific fertility rates are per 1,000 women. Source: Chieh-Johnson et al., 1988; MPEA et al., 2000 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, Liberia 2007 Background characteristic Total fertility rate Percentage of women age 15-49 currently pregnant Mean number of children ever born to women age 40-49 Residence Urban 3.8 7.7 5.6 Rural 6.2 12.9 6.5 Region Monrovia 3.4 8.0 5.3 North Western (6.5) 13.3 6.0 South Central 5.8 9.9 6.9 South Eastern A (6.9) 11.6 7.1 South Eastern B 6.0 15.3 6.6 North Central 6.0 12.2 6.4 Education No education 6.0 11.9 6.4 Primary 5.9 11.9 6.4 Secondary and higher 3.3 7.3 5.3 Wealth quintile Lowest 6.5 15.1 6.3 Second 6.5 12.2 6.4 Middle 6.0 11.3 6.8 Fourth 4.7 8.1 6.2 Highest 2.8 8.2 5.1 Total 5.2 10.7 6.2 Note: Total fertility rates are for the period 1-36 months before the interview. Total fertility rates in parentheses are based on 500-999 unweighted women. 50 | Fertility Levels, Trends, and Differentials The data show a steady decrease in the fertility rates across all three surveys and for all age groups. The TFR decreased from 6.6 in the five years preceding the 1986 LDHS (roughly equivalent to 1981-85) to 5.2 for the three years before the 2007 LDHS (approximately 2004-06), a decrease of more than 20 percent (Figure 4.2). Surprisingly, the rate of decline has been greater in the more recent period than for the much longer period between the first two surveys. Another way to examine trends in fertility is based on the birth histories from the 2007 survey. Table 4.4 uses information from the retrospective birth histories obtained from LDHS respondents to examine trends in ASFRs for successive five-year periods before the survey. To calculate these rates, births were classified according to the period of time in which the birth occurred and the mother’s age at the time of birth. Because birth histories were not collected for women over age 50, the rates for older age groups become progressively more truncated for periods more distant from the survey date. For example, rates cannot be calculated for women age 45- 49 for five to nine years or more before the survey because women in that age group would have been 50 years or over at the time of the survey. Table 4.4 also shows evidence of decreasing fertility, although the decreases are not large. 4.4 CHILDREN EVER BORN AND LIVING Table 4.5 presents the distribution of all women and currently married women by number of children ever born, according to five-year age groups. The table also shows the mean number of children ever born. Data on the number of children ever born reflect the accumulation of births to women over their entire reproductive years and therefore have limited reference to current fertility levels, particularly when a country has experienced a decrease in fertility. Table 4.4 Trends in age-specific fertility rates Age-specific fertility rates for five-year periods preceding the survey, by mother's age at the time of the birth, Liberia 2007 Mother's age at birth Number of years preceding survey 0-4 5-9 10-14 15-19 15-19 137 152 161 163 20-24 241 249 257 239 25-29 230 245 250 267 30-34 199 220 241 [227] 35-39 151 185 [202] 40-44 81 [123] 45-49 [40] Note: Age-specific fertility rates are per 1,000 women. Estimates in brackets are truncated. Rates exclude the month of interview. 6.6 6.2 5.2 1981-85 1997-99 2004-06 0 2 4 6 8 Births per woman Figure 4.2 Trends in Total Fertility Rates Source: Chieh-Johnson et al. 1988 and MPEA et al., 2000 Fertility Levels, Trends, and Differentials | 51 However, the information on children ever born is useful for observing how average family size varies across age groups and for observing the level of primary infertility. The data show that early childbearing is common in Liberia. Over one-quarter of girls age 15-19 have already given birth; by age 20-24, almost 8 in 10 have had a baby. Only 1 percent of women at the end of their reproductive age remain childless, indicating that childbearing among Liberian women is almost universal. Because deliberate childlessness is rare in Liberia, the 1 percent of women who have never had a child can be interpreted as a rough measure of the level of primary infertility or the inability to bear children. Table 4.5 Children ever born and living Percent distribution of all women and currently married women by number of children ever born, mean number of children ever born, and mean number of living children, according to age group, Liberia 2007 Mean number of children ever born Mean number of living children Number of women Number of children ever born Age 0 1 2 3 4 5 6 7 8 9 10+ Total ALL WOMEN 15-19 74.0 22.2 3.5 0.3 0.0 0.0 0.0 0.0 0.0 0.0 0.0 100.0 1,312 0.30 0.28 20-24 21.8 38.3 26.6 10.0 2.4 0.6 0.2 0.0 0.0 0.0 0.0 100.0 1,363 1.36 1.19 25-29 5.5 17.0 26.2 24.6 14.8 7.6 2.6 1.3 0.2 0.2 0.0 100.0 1,166 2.68 2.29 30-34 2.0 9.8 12.8 23.3 20.3 14.3 9.2 5.3 1.8 0.8 0.3 100.0 956 3.76 3.13 35-39 2.5 3.4 9.3 13.1 14.6 18.5 12.9 12.9 6.6 3.3 2.8 100.0 956 4.92 3.92 40-44 1.1 2.8 6.2 11.7 10.9 15.0 10.9 13.2 11.3 6.5 10.4 100.0 665 5.86 4.61 45-49 1.1 1.4 4.6 8.5 10.4 11.6 13.8 12.3 9.8 9.7 16.9 100.0 674 6.56 4.93 Total 19.6 16.4 14.1 12.8 9.6 8.3 5.8 5.1 3.2 2.1 3.0 100.0 7,092 3.10 2.51 CURRENTLY MARRIED WOMEN 15-19 31.3 53.8 13.2 1.6 0.0 0.0 0.0 0.0 0.0 0.0 0.0 100.0 251 0.85 0.79 20-24 10.4 34.7 34.7 15.1 3.7 1.2 0.1 0.0 0.0 0.0 0.0 100.0 739 1.71 1.50 25-29 3.1 13.1 24.3 26.2 18.4 9.3 3.6 1.6 0.2 0.2 0.0 100.0 847 2.97 2.54 30-34 1.7 7.6 12.5 22.1 21.0 16.1 10.1 6.1 1.7 1.0 0.1 100.0 805 3.90 3.26 35-39 2.4 2.5 8.0 13.1 14.9 17.7 12.7 14.5 7.3 3.8 3.1 100.0 812 5.09 4.05 40-44 1.3 2.4 5.9 11.6 10.4 13.7 10.5 14.8 11.4 7.5 10.4 100.0 545 5.96 4.65 45-49 1.4 1.7 3.9 7.8 9.7 11.2 13.7 11.9 11.3 10.2 17.2 100.0 541 6.67 4.98 Total 5.1 13.4 15.7 16.0 12.8 10.9 7.6 7.2 4.4 3.0 3.9 100.0 4,540 3.99 3.22 On average, Liberian women attain a parity of 6.6 children per woman at the end of their childbearing. This number is considerably higher than the TFR of 5.2 per woman, a discrepancy that is attributable to the decrease in fertility. The same pattern is replicated for currently married women, except that young married women are much more likely than all young women to have had at least one child. This difference in the tempo of childbearing can be explained by the presence in the all-women category of many young and unmarried women who are known to exhibit extremely low fertility. Consonant with expectations, the mean number of children ever born rises monotonically with increasing age of women, thus presupposing minimal or no recall lapse, which heightens confidence in the birth history reports. Women in their early twenties have given birth to more than one child on average, women in their late 30s have had five births, and those age 45-49 have borne 6.6 children each. As expected, women above 40 years have much higher parities, with substantial proportions having 10 or more births by the end of their childbearing years. 52 | Fertility Levels, Trends, and Differentials 4.5 BIRTH INTERVALS A birth interval is defined as the length of time between two live births. The study of birth intervals is important in understanding the health status of young children. Research has shown that short birth intervals are closely associated with poor health of children, especially during infancy. Children born too close to a previous birth, especially if the interval between the births is less than two years, are at increased risk of health problems and dying at an early age. Longer birth intervals, on the other hand, contribute to the improved health status of both mother and child. The study of birth intervals is done using two measures: median birth interval and proportion of non-first births that occur 24 months or more after the previous birth. Table 4.6 presents the distribution of second and higher-order births in the five years preceding the survey by the number of months since the previous birth, according to background characteristics. The table also presents the median number of months since the preceding birth. Table 4.6 Birth intervals Percent distribution of non-first births in the five years preceding the survey by number of months since preceding birth, and median number of months since preceding birth, according to background characteristics, Liberia 2007 Number of non-first births Median number of months since preceding birth Background characteristic Months since preceding birth 7-17 18-23 24-35 36-47 48-59 60+ Total Age 15-19 11.8 35.0 35.3 14.8 1.0 2.1 100.0 53 26.6 20-29 7.6 12.3 35.9 20.9 10.7 12.7 100.0 1,879 33.8 30-39 6.5 8.0 29.4 19.4 13.3 23.5 100.0 1,798 39.1 40-49 8.5 9.3 22.3 18.0 14.8 27.2 100.0 588 41.4 Birth order 2-3 6.3 10.8 29.3 21.3 11.6 20.7 100.0 1,908 37.3 4-6 7.5 9.5 32.2 19.8 12.1 18.9 100.0 1,637 36.3 7+ 9.1 11.2 34.4 16.2 13.6 15.4 100.0 773 34.4 Sex of preceding birth Male 8.2 10.8 30.1 19.5 12.0 19.4 100.0 2,186 36.3 Female 6.4 9.9 32.5 20.2 12.4 18.7 100.0 2,132 36.5 Survival of preceding birth Living 6.5 10.1 31.5 20.1 12.4 19.4 100.0 3,711 36.7 Dead 11.9 12.1 30.5 17.8 11.0 16.7 100.0 607 33.7 Residence Urban 5.2 7.8 25.2 21.9 11.7 28.2 100.0 1,199 42.1 Rural 8.1 11.3 33.7 19.0 12.4 15.5 100.0 3,119 34.8 Region Monrovia 3.6 6.7 24.5 21.7 12.0 31.4 100.0 803 44.1 North Western 9.6 13.7 33.9 16.5 9.9 16.5 100.0 423 34.3 South Central 9.7 13.9 29.6 19.0 12.2 15.4 100.0 704 34.4 South Eastern A 10.8 10.8 31.6 20.6 12.5 13.7 100.0 330 34.6 South Eastern B 9.0 12.4 35.8 20.1 10.8 11.8 100.0 333 32.6 North Central 6.4 9.3 33.6 19.8 13.0 17.8 100.0 1,725 36.2 Education No education 8.7 11.8 31.5 18.7 11.6 17.7 100.0 2,328 35.2 Primary 6.3 10.5 34.0 22.1 12.2 14.9 100.0 1,381 35.7 Secondary and higher 3.9 4.5 24.4 19.2 14.5 33.5 100.0 602 46.3 Wealth quintile Lowest 10.3 10.2 33.7 18.2 12.9 14.7 100.0 992 34.4 Second

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