Liberia - Demographic and Health Survey - 2014

Publication date: 2014

Liberia Demographic and Health Survey 2013 Liberia 2013 D em ographic and H ealth Survey Liberia Demographic and Health Survey 2013 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 ICF International Inc. Rockville, Maryland, USA August 2014 The Global Fund To Fight AIDS, Tuberculosis and Malaria The 2013 Liberia Demographic and Health Survey (LDHS) was implemented by the Liberia Institute of Statistics and Geo-Information Services (LISGIS) from March 10 to July 19, 2013. The Ministry of Health and Social Welfare (MOHSW) authorized the survey. Funding for the survey was provided by the United States Agency for International Development (USAID), the Global Fund, the United Nations Children’s Fund (UNICEF), the United Nations Population Fund (UNFPA), and the Government of Liberia. ICF International supported the project through the MEASURE DHS project, a USAID-funded program providing support, technical assistance, and funding for population and health surveys in countries worldwide. Additional information about the survey may be obtained from from the Liberia Institute of Statistics and Geo-Information Services (LISGIS), Statistics House, Capitol Hill, P.O. Box 629, Monrovia, Liberia (Telephone +231-886-518885/886-583839; Web: www.lisgis.net). Information about The DHS Program may be obtained from ICF International, 530 Gaither Road, Suite 500, Rockville, MD 20850, USA; Telephone: +1.301-407-6500, Fax: +1.301-407-6501, E-mail: reports@dhsprogram.com, Internet: http://www.dhsprogram.com. Cover photo of a detail of the Unification Monument in Voinjama City, Lofa County, is provided courtesy of Joseph K. Bryant, Director, LISGIS County Statistical and Information Office, Voinjama City, Lofa County, Liberia. Flag images are provided by Fry1989 (http://commons.wikimedia. org/wiki/User:Fry1989). Suggested citation: Liberia Institute of Statistics and Geo-Information Services (LISGIS), Ministry of Health and Social Welfare [Liberia], National AIDS Control Program [Liberia], and ICF International. 2014. Liberia Demographic and Health Survey 2013. Monrovia, Liberia: Liberia Institute of Statistics and Geo- Information Services (LISGIS) and ICF International. Table of Contents • iii TABLE OF CONTENTS LIST OF TABLES AND FIGURES . ix FOREWORD . xvii ACKNOWLEDGMENTS . xxi MILLENIUM DEVELOPMENT GOAL INDICATORS . xxiii MAP OF LIBERIA . xxiv 1 INTRODUCTION . 1 1.1 HISTORY, GEOGRAPHY, AND ECONOMY. 1 1.2 OBJECTIVES OF THE SURVEY . 2 1.3 ORGANIZATION OF THE SURVEY . 2 1.4 SURVEY IMPLEMENTATION . 2 1.4.1 Sample Design . 2 1.4.2 Questionnaires . 3 1.4.3 HIV Testing . 4 1.4.4 Training of Field Staff . 5 1.4.5 Fieldwork . 6 1.4.6 Data Processing . 6 1.5 RESPONSE RATES . 7 2 HOUSING CHARACTERISTICS AND HOUSEHOLD POPULATION . 9 2.1 HOUSEHOLD CHARACTERISTICS . 9 2.1.1 Drinking Water . 10 2.1.2 Sanitation Facilities and Waste Disposal . 11 2.1.3 Housing Characteristics . 12 2.1.4 Household Possessions . 14 2.1.5 Distance to a Health Facility . 15 2.2 HOUSEHOLD WEALTH . 16 2.3 HAND WASHING . 17 2.4 HOUSEHOLD POPULATION BY AGE, SEX, AND RESIDENCE . 18 2.5 HOUSEHOLD COMPOSITION . 19 2.6 BIRTH REGISTRATION . 20 2.7 CHILDREN’S LIVING ARRANGEMENTS AND PARENTAL SURVIVAL . 21 2.8 EDUCATION OF THE HOUSEHOLD POPULATION . 23 2.8.1 Educational Attainment . 23 2.8.2 School Attendance Ratios . 25 2.9 UTILIZATION OF HEALTH SERVICES AND OUT-OF-POCKET EXPENDITURES FOR HEALTH CARE . 29 3 CHARACTERISTICS OF RESPONDENTS . 33 3.1 CHARACTERISTICS OF SURVEY RESPONDENTS . 33 3.2 EDUCATIONAL ATTAINMENT BY BACKGROUND CHARACTERISTICS . 35 3.3 LITERACY . 37 3.4 EXPOSURE TO MASS MEDIA . 40 3.5 EMPLOYMENT STATUS . 42 iv • Table of Contents 3.6 OCCUPATION . 45 3.7 TYPE OF EMPLOYMENT . 48 3.8 HEALTH INSURANCE COVERAGE . 48 3.9 USE OF TOBACCO . 50 3.10 USE OF ALCOHOL . 53 4 MARRIAGE AND SEXUAL ACTIVITY . 57 4.1 MARITAL STATUS . 57 4.2 POLYGYNY . 58 4.3 AGE AT FIRST MARRIAGE . 60 4.4 AGE AT FIRST SEXUAL INTERCOURSE . 62 4.5 RECENT SEXUAL ACTIVITY . 64 5 FERTILITY . 69 5.1 CURRENT FERTILITY . 69 5.2 FERTILITY BY BACKGROUND CHARACTERISTICS . 70 5.3 FERTILITY TRENDS . 71 5.4 CHILDREN EVER BORN AND LIVING . 72 5.5 BIRTH INTERVALS . 73 5.6 POSTPARTUM AMENORRHEA, ABSTINENCE, AND INSUSCEPTIBILITY . 75 5.7 MEDIAN DURATION OF POSTPARTUM INSUSCEPTIBILITY BY BACKGROUND CHARACTERISTICS . 75 5.8 MENOPAUSE . 77 5.9 AGE AT FIRST BIRTH . 77 5.10 MEDIAN AGE AT FIRST BIRTH BY BACKGROUND CHARACTERISTICS . 78 5.11 TEENAGE PREGNANCY AND MOTHERHOOD . 79 6 FERTILITY PREFERENCES . 81 6.1 FERTILITY PREFERENCES BY NUMBER OF LIVING CHILDREN . 81 6.2 DESIRE TO LIMIT CHILDBEARING BY BACKGROUND CHARACTERISTICS . 82 6.3 IDEAL NUMBER OF CHILDREN . 84 6.4 MEAN IDEAL NUMBER OF CHILDREN BY BACKGROUND CHARACTERISTICS . 86 6.5 FERTILITY PLANNING STATUS . 86 6.6 WANTED FERTILITY RATES . 87 7 FAMILY PLANNING . 89 7.1 KNOWLEDGE OF CONTRACEPTIVE METHODS . 89 7.2 CURRENT USE OF CONTRACEPTION . 91 7.3 CURRENT USE OF CONTRACEPTION BY BACKGROUND CHARACTERISTICS . 92 7.4 SOURCE OF MODERN CONTRACEPTIVE METHODS . 95 7.5 USE OF SOCIAL MARKETING BRAND PILLS . 96 7.6 INFORMED CHOICE . 97 7.7 RATES OF DISCONTINUING CONTRACEPTIVE METHODS . 98 7.8 REASONS FOR DISCONTINUING CONTRACEPTIVE METHODS . 98 7.9 KNOWLEDGE OF THE FERTILE PERIOD . 99 7.10 NEED AND DEMAND FOR FAMILY PLANNING . 100 7.11 FUTURE USE OF CONTRACEPTION . 104 7.12 EXPOSURE TO FAMILY PLANNING MESSAGES IN THE MEDIA . 105 7.13 CONTACT OF NONUSERS WITH FAMILY PLANNING PROVIDERS . 106 Table of Contents • v 8 INFANT AND CHILD MORTALITY . 109 8.1 BACKGROUND AND ASSESSMENT OF DATA QUALITY . 109 8.2 INFANT AND CHILD MORTALITY LEVELS AND TRENDS . 111 8.3 SOCIOECONOMIC DIFFERENTIALS IN EARLY CHILDHOOD MORTALITY . 112 8.4 DEMOGRAPHIC DIFFERENTIALS IN EARLY CHILDHOOD MORTALITY . 113 8.5 PERINATAL MORTALITY . 114 8.6 HIGH-RISK FERTILITY BEHAVIOR . 115 9 MATERNAL HEALTH CARE . 117 9.1 PRENATAL CARE . 117 9.2 NUMBER AND TIMING OF PRENATAL VISITS . 120 9.3 COMPONENTS OF PRENATAL CARE . 120 9.4 TETANUS TOXOID . 122 9.5 PLACE OF DELIVERY . 124 9.6 ASSISTANCE DURING DELIVERY . 125 9.7 POSTNATAL CARE FOR THE MOTHER . 128 9.8 POSTNATAL CARE FOR THE NEWBORN . 131 9.9 PROBLEMS IN ACCESSING HEALTH CARE . 135 10 CHILD HEALTH . 137 10.1 CHILD’S WEIGHT AND SIZE AT BIRTH . 137 10.2 VACCINATION OF CHILDREN . 139 10.3 PREVALENCE AND TREATMENT OF ACUTE RESPIRATORY INFECTION . 143 10.4 PREVALENCE AND TREATMENT OF FEVER . 145 10.5 DIARRHEAL DISEASE . 147 10.5.1 Prevalence of Diarrhea . 147 10.5.2 Treatment of Diarrhea . 149 10.5.3 Feeding Practices during Diarrhea . 151 10.6 KNOWLEDGE OF ORS PACKETS . 153 10.7 DISPOSAL OF CHILDREN’S STOOLS . 154 11 NUTRITION OF CHILDREN AND ADULTS . 157 11.1 NUTRITIONAL STATUS OF CHILDREN . 157 11.1.1 Measurement of Nutritional Status among Young Children . 158 11.1.2 Data Collection . 159 11.1.3 Levels of Child Malnutrition . 159 11.1.4 Trends in Child Malnutrition . 161 11.2 BREASTFEEDING . 162 11.2.1 Initiation of Breastfeeding . 162 11.2.2 Breastfeeding Status by Age . 164 11.2.3 Median Duration of Breastfeeding . 166 11.3 DIETARY DIVERSITY AMONG YOUNG CHILDREN . 167 11.3.1 Foods and Liquids Consumed by Infants and Young Children . 168 11.3.2 Infant and Young Child Feeding (IYCF) Practices . 169 11.4 MICRONUTRIENT INTAKE AND SUPPLEMENTATION AMONG CHILDREN . 171 vi • Table of Contents 11.5 PRESENCE OF IODIZED SALT IN HOUSEHOLDS . 174 11.6 ADULT NUTRITIONAL STATUS . 175 11.6.1 Nutritional Status of Women . 175 11.6.2 Nutritional Status of Men . 177 11.7 MICRONUTRIENT INTAKE AMONG MOTHERS . 178 12 MALARIA . 181 12.1 OWNERSHIP OF MOSQUITO NETS . 182 12.2 INDOOR RESIDUAL SPRAYING . 183 12.3 ACCESS TO MOSQUITO NETS . 185 12.4 USE OF MOSQUITO NETS . 186 12.4.1 Use of Mosquito Nets by Persons in the Household . 186 12.4.2 Use of Existing Mosquito Nets . 188 12.4.3 Use of Mosquito Nets by Children Under 5. 189 12.4.4 Use of Mosquito Nets by Pregnant Women . 192 12.5 INTERMITTENT PREVENTIVE TREATMENT OF MALARIA IN PREGNANCY . 193 12.6 PREVALENCE, DIAGNOSIS, AND PROMPT TREATMENT OF FEVER AMONG CHILDREN . 195 13 HIV/AIDS-RELATED KNOWLEDGE, ATTITUDES, AND BEHAVIOR . 201 13.1 HIV/AIDS KNOWLEDGE, TRANSMISSION, AND PREVENTION METHODS . 202 13.2 KNOWLEDGE ABOUT MOTHER-TO-CHILD TRANSMISSION . 208 13.3 ATTITUDES TOWARD PEOPLE LIVING WITH HIV/AIDS . 210 13.4 ATTITUDES TOWARD NEGOTIATING FOR SAFER SEXUAL RELATIONS WITH HUSBANDS . 213 13.5 ATTITUDES TOWARDS CONDOM EDUCATION FOR YOUNG PEOPLE . 214 13.6 MULTIPLE SEXUAL PARTNERS . 215 13.7 PAID SEX . 220 13.8 COVERAGE OF HIV TESTING SERVICES . 222 13.9 MALE CIRCUMCISION . 227 13.10 SELF-REPORTING OF SEXUALLY TRANSMITTED INFECTIONS . 227 13.11 INJECTIONS . 229 13.12 HIV/AIDS-RELATED KNOWLEDGE AND BEHAVIOR AMONG YOUNG PEOPLE . 231 13.12.1 Knowledge about HIV/AIDS and Source for Condoms . 231 13.12.2 First Sex . 232 13.12.3 Premarital Sex . 234 13.12.4 Multiple Sexual Partners . 236 13.12.5 Age-mixing in Sexual Relationships . 237 13.12.6 Coverage of HIV Testing Services . 238 14 HIV PREVALENCE . 241 14.1 COVERAGE RATES FOR HIV TESTING . 242 14.2 HIV PREVALENCE . 245 14.2.1 HIV Prevalence by Age and Sex . 245 14.2.2 HIV Prevalence by Socioeconomic Characteristics . 246 14.2.3 HIV Prevalence by Other Sociodemographic and Health Characteristics . 247 14.2.4 HIV Prevalence by Sexual Risk Behavior . 249 14.3 HIV PREVALENCE AMONG YOUNG PEOPLE . 251 14.4 HIV PREVALENCE BY OTHER CHARACTERISTICS RELATED TO HIV RISK . 253 14.5 HIV PREVALENCE AMONG COUPLES . 254 Table of Contents • vii 15 WOMEN’S EMPOWERMENT AND DEMOGRAPHIC AND HEALTH OUTCOMES . 257 15.1 WOMEN’S AND MEN’S EMPLOYMENT . 257 15.2 WOMEN’S CONTROL OVER THEIR OWN EARNINGS AND RELATIVE MAGNITUDE OF WOMEN’S EARNINGS . 258 15.3 WOMEN’S OWNERSHIP OF ASSETS . 262 15.4 WOMEN’S AND MEN’S PARTICIPATION IN DECISION MAKING . 265 15.5 ATTITUDES TOWARD WIFE BEATING . 269 15.6 WOMEN’S EMPOWERMENT INDICATORS . 272 15.7 CURRENT USE OF CONTRACEPTION BY WOMEN’S EMPOWERMENT . 272 15.8 IDEAL FAMILY SIZE AND UNMET NEED BY WOMEN’S EMPOWERMENT . 273 15.9 WOMEN’S EMPOWERMENT AND REPRODUCTIVE HEALTH CARE . 274 15.10 DIFFERENTIALS IN INFANT AND CHILD MORTALITY BY WOMEN’S EMPOWERMENT . 275 15.11 FEMALE GENITAL CUTTING . 275 15.12 ATTITUDES TOWARD CHILD BEATING . 277 16 ADULT AND MATERNAL MORTALITY . 281 16.1 ASSESSMENT OF DATA QUALITY . 281 16.2 ESTIMATES OF ADULT MORTALITY . 282 16.3 ESTIMATES OF MATERNAL MORTALITY. 283 REFERENCES . 287 APPENDIX A SAMPLE DESIGN . 291 APPENDIX B ESTIMATES OF SAMPLING ERRORS . 303 APPENDIX C DATA QUALITY TABLES . 333 APPENDIX D PARTICIPANTS IN THE 2013 LIBERIA DEMOGRAPHIC AND HEALTH SURVEY . 339 APPENDIX E QUESTIONNAIRES . 345 List of Tables and Figures • ix LIST OF TABLES AND FIGURES 1 INTRODUCTION . 1 Table 1.1 Basic demographic indicators . 1 Table 1.2 Results of the household and individual interviews . 7 2 HOUSING CHARACTERISTICS AND HOUSEHOLD POPULATION . 9 Table 2.1 Household drinking water . 11 Table 2.2 Household sanitation facilities . 12 Table 2.3 Household characteristics . 13 Table 2.4 Household possessions . 14 Table 2.5 Method of travel and travel time to nearest health facility . 15 Table 2.6 Travel time to health facility by walking . 16 Table 2.7 Wealth quintiles . 17 Table 2.8 Household population by age, sex, and residence . 18 Table 2.9 Household composition . 20 Table 2.10 Birth registration of children under 5 . 21 Table 2.11 Children's living arrangements and orphanhood . 22 Table 2.12.1 Educational attainment of the female household population . 24 Table 2.12.2 Educational attainment of the male household population . 25 Table 2.13 School attendance ratios . 27 Table 2.14 Annual outpatient visits and inpatient admissions . 30 Table 2.15 Annual per capita expenditure (in Liberian dollars) on outpatient visits and inpatient admissions . 31 Table 2.16 Annual total health expenditures (in Liberian dollars) per household . 32 Figure 2.1 Population pyramid . 19 Figure 2.2 Age-specific attendance rates of the de-facto population 5 to 24 years . 29 3 CHARACTERISTICS OF RESPONDENTS . 33 Table 3.1 Background characteristics of respondents . 34 Table 3.2.1 Educational attainment: Women . 36 Table 3.2.2 Educational attainment: Men . 37 Table 3.3.1 Literacy: Women . 38 Table 3.3.2 Literacy: Men . 39 Table 3.4.1 Exposure to mass media: Women . 40 Table 3.4.2 Exposure to mass media: Men . 41 Table 3.5.1 Employment status: Women . 43 Table 3.5.2 Employment status: Men . 44 Table 3.6.1 Occupation: Women . 46 Table 3.6.2 Occupation: Men . 47 Table 3.7 Type of employment: Women . 48 Table 3.8.1 Health insurance coverage: Women . 49 Table 3.8.2 Health insurance coverage: Men . 50 Table 3.9.1 Use of tobacco: Women . 51 x • List of Tables and Figures Table 3.9.2 Use of tobacco: Men . 52 Table 3.10.1 Use of alcohol: Women . 53 Table 3.10.2 Use of alcohol: Men . 54 Figure 3.1 Women’s employment status in the past 12 months . 42 4 MARRIAGE AND SEXUAL ACTIVITY . 57 Table 4.1 Current marital status . 58 Table 4.2.1 Number of women's co-wives . 59 Table 4.2.2 Number of men's wives . 60 Table 4.3 Age at first marriage . 61 Table 4.4 Median age at first marriage by background characteristics: Women . 62 Table 4.5 Age at first sexual intercourse . 63 Table 4.6 Median age at first sexual intercourse by background characteristics . 64 Table 4.7.1 Recent sexual activity: Women . 65 Table 4.7.2 Recent sexual activity: Men . 67 5 FERTILITY . 69 Table 5.1 Current fertility . 70 Table 5.2 Fertility by background characteristics . 70 Table 5.3.1 Trends in age-specific fertility rates . 71 Table 5.3.2 Trends in age-specific and total fertility rates . 72 Table 5.4 Children ever born and living . 73 Table 5.5 Birth intervals . 74 Table 5.6 Postpartum amenorrhea, abstinence, and insusceptibility . 75 Table 5.7 Median duration of amenorrhea, postpartum abstinence, and postpartum insusceptibility . 76 Table 5.8 Menopause . 77 Table 5.9 Age at first birth . 77 Table 5.10 Median age at first birth . 78 Table 5.11 Teenage pregnancy and motherhood . 79 Figure 5.1 Trends in fertility . 72 6 FERTILITY PREFERENCES . 81 Table 6.1 Fertility preferences by number of living children . 82 Table 6.2.1 Desire to limit childbearing: Women . 83 Table 6.2.2 Desire to limit childbearing: Men . 84 Table 6.3 Ideal number of children by number of living children . 85 Table 6.4 Mean ideal number of children by background characteristics . 86 Table 6.5 Fertility planning status . 87 Table 6.6 Wanted fertility rates . 88 7 FAMILY PLANNING . 89 Table 7.1 Knowledge of contraceptive methods . 90 Table 7.2 Current use of contraception by age . 92 Table 7.3.1 Current use of contraception by background characteristics . 93 Table 7.3.2 Trends in the current use of contraception . 94 Table 7.4 Source of modern contraception methods . 95 List of Tables and Figures • xi Table 7.5 Use of social marketing brand pills . 96 Table 7.6 Informed choice . 97 Table 7.7 Twelve-month contraceptive discontinuation rates . 98 Table 7.8 Reasons for discontinuation . 99 Table 7.9 Knowledge of fertile period . 99 Table 7.10.1 Need and demand for family planning among currently married women . 101 Table 7.10.2 Need and demand for family planning for all women and for sexually active unmarried women . 103 Table 7.11 Future use of contraception . 105 Table 7.12 Exposure to family planning messages . 106 Table 7.13 Contact of nonusers with family planning providers . 107 Figure 7.1 Trends in contraceptive use among currently married women . 94 Figure 7.2 Trends in unmet need for family planning . 102 8 INFANT AND CHILD MORTALITY . 109 Table 8.1 Early childhood mortality rates . 111 Table 8.2 Early childhood mortality rates by socioeconomic characteristics . 113 Table 8.3 Early childhood mortality rates by demographic characteristics . 114 Table 8.4 Perinatal mortality . 115 Table 8.5 High-risk fertility behavior . 116 Figure 8.1 Trends in childhood mortality 1981-2012 . 112 9 MATERNAL HEALTH CARE . 117 Table 9.1 Prenatal care . 119 Table 9.2 Number of prenatal care visits and timing of first visit. 120 Table 9.3 Components of prenatal care . 121 Table 9.4 Tetanus toxoid injections . 123 Table 9.5 Place of delivery . 124 Table 9.6 Assistance during delivery . 126 Table 9.7 Timing of first postnatal checkup . 129 Table 9.8 Type of provider of first postnatal checkup for the mother . 130 Table 9.9 Timing of first postnatal checkup for the newborn . 132 Table 9.10 Type of provider of first postnatal checkup for the newborn . 134 Table 9.11 Problems in accessing health care . 136 Figure 9.1 Mother’s duration of stay in the health facility after giving birth . 128 10 CHILD HEALTH . 137 Table 10.1 Child's size and weight at birth . 138 Table 10.2 Vaccinations by source of information . 140 Table 10.3 Vaccinations by background characteristics . 141 Table 10.4 Vaccinations in first year of life . 142 Table 10.5 Prevalence and treatment of symptoms of ARI . 144 Table 10.6 Prevalence and treatment of fever . 146 Table 10.7 Prevalence of diarrhea . 148 Table 10.8 Diarrhea treatment . 150 Table 10.9 Feeding practices during diarrhea . 152 Table 10.10 Knowledge of ORS packets . 153 Table 10.11 Disposal of children's stools . 155 xii • List of Tables and Figures Figure 10.1 Trends in vaccination coverage during the first year of life among children 12-23 months . 142 11 NUTRITION OF CHILDREN AND ADULTS . 157 Table 11.1 Nutritional status of children . 159 Table 11.2 Initial breastfeeding . 163 Table 11.3 Breastfeeding status by age . 164 Table 11.4 Median duration of breastfeeding . 167 Table 11.5 Foods and liquids consumed by children in the day or night preceding the interview . 168 Table 11.6 Infant and young child feeding (IYCF) practices . 170 Table 11.7 Micronutrient intake among children . 173 Table 11.8 Presence of iodized salt in household . 174 Table 11.9.1 Nutritional status of women . 176 Table 11.9.2 Nutritional status of men . 178 Table 11.10 Micronutrient intake among mothers . 179 Figure 11.1 Nutritional status of children by age . 161 Figure 11.2 Trends in nutritional status of children under 5 . 162 Figure 11.3 Infant feeding practices by age . 165 Figure 11.4 IYCF Indicators on breastfeeding status . 166 Figure 11.5 IYCF Indicators on minimum acceptable diet . 171 Figure 11.6 Trends in nutritional status of women age 15-49 . 177 12 MALARIA . 181 Table 12.1 Household possession of mosquito nets . 182 Table 12.2 Indoor residual spraying against mosquitoes . 184 Table 12.3 Access to an insecticide-treated net (ITN) . 185 Table 12.4 Use of mosquito nets by persons in the household . 187 Table 12.5 Use of existing ITNs . 189 Table 12.6 Use of mosquito nets by children . 191 Table 12.7 Use of mosquito nets by pregnant women . 193 Table 12.8 Use of intermittent preventive treatment (IPTp) by women during pregnancy . 195 Table 12.9 Prevalence, diagnosis, and prompt treatment of children with fever . 197 Table 12.10 Source of advice or treatment for children with fever . 198 Table 12.11 Type of antimalarial drugs used . 199 Figure 12.1 Trends in ITN ownership . 183 Figure 12.2 Percentage of the de facto population with access to an ITN in the household . 186 Figure 12.3 Ownership of, access to, and use of ITNs . 188 13 HIV/AIDS-RELATED KNOWLEDGE, ATTITUDES, AND BEHAVIOR . 201 Table 13.1 Knowledge of AIDS . 203 Table 13.2 Knowledge of HIV prevention methods . 204 Table 13.3.1 Comprehensive knowledge about AIDS: Women . 206 Table 13.3.2 Comprehensive knowledge about AIDS: Men . 207 Table 13.4 Knowledge of prevention of mother-to-child transmission of HIV . 209 Table 13.5.1 Accepting attitudes toward those living with HIV/AIDS: Women . 211 Table 13.5.2 Accepting attitudes toward those living with HIV/AIDS: Men . 212 Table 13.6 Attitudes toward negotiating safer sexual relations with husband . 213 List of Tables and Figures • xiii Table 13.7 Adult support of education about condom use to prevent AIDS . 215 Table 13.8.1 Multiple sexual partners: Women . 217 Table 13.8.2 Multiple sexual partners: Men . 218 Table 13.9 Point prevalence and cumulative prevalence of concurrent sexual partners . 220 Table 13.10 Payment for sexual intercourse and condom use at last paid sexual intercourse . 221 Table 13.11.1 Coverage of prior HIV testing: Women . 223 Table 13.11.2 Coverage of prior HIV testing: Men . 224 Table 13.12 Pregnant women counseled and tested for HIV . 226 Table 13.13 Male circumcision . 227 Table 13.14 Self-reported prevalence of sexually-transmitted infections (STIs) and STI symptoms . 228 Table 13.15 Prevalence of medical injections . 230 Table 13.16 Comprehensive knowledge about AIDS and of a source of condoms among youth . 232 Table 13.17 Age at first sexual intercourse among young people . 233 Table 13.18 Premarital sexual intercourse and condom use during premarital sexual intercourse among youth . 235 Table 13.19.1 Multiple sexual partners in the past 12 months among young people: Women . 236 Table 13.19.2 Multiple sexual partners in the past 12 months among young people: Men . 237 Table 13.20 Age-mixing in sexual relationships among women and men age 15-19 . 238 Table 13.21 Recent HIV tests among youth . 239 Figure 13.1 Women and men seeking treatment for STIs . 229 Figure 13.2 Trends in age of first sexual intercourse . 234 14 HIV PREVALENCE . 241 Table 14.1 Coverage of HIV testing by residence and region . 243 Table 14.2 Coverage of HIV testing by selected background characteristics . 244 Table 14.3 HIV prevalence by age . 245 Table 14.4 HIV prevalence by socioeconomic characteristics . 247 Table 14.5 HIV prevalence by demographic characteristics . 248 Table 14.6 HIV prevalence by sexual behavior . 250 Table 14.7 HIV prevalence among young people by background characteristics . 252 Table 14.8 HIV prevalence among young people by sexual behavior . 253 Table 14.9 HIV prevalence by other characteristics . 253 Table 14.10 Prior HIV testing by current HIV status . 254 Table 14.11 HIV prevalence among couples . 254 Figure 14.1 HIV prevalence among all adults age 15-49, and by sex, Liberia 2007 and 2013 . 246 15 WOMEN’S EMPOWERMENT AND DEMOGRAPHIC AND HEALTH OUTCOMES . 257 Table 15.1 Employment and cash earnings of currently married women and men . 258 Table 15.2.1 Control over women's cash earnings and relative magnitude of women's cash earnings . 259 Table 15.2.2 Control over men's cash earnings . 261 Table 15.3 Women's control over their own earnings and over those of their husbands . 262 Table 15.4.1 Ownership of assets: Women . 263 Table 15.4.2 Ownership of assets: Men . 264 Table 15.5 Participation in decision making . 265 xiv • List of Tables and Figures Table 15.6.1 Women's participation in decision making by background characteristics . 266 Table 15.6.2 Men's participation in decision making by background characteristics . 268 Table 15.7.1 Attitude toward wife beating: Women . 270 Table 15.7.2 Attitude toward wife beating: Men . 271 Table 15.8 Indicators of women's empowerment . 272 Table 15.9 Current use of contraception by women's empowerment . 273 Table 15.10 Ideal number of children and unmet need for family planning by women's empowerment . 274 Table 15.11 Reproductive health care by women's empowerment . 274 Table 15.12 Early childhood mortality rates by women's status . 275 Table 15.13 Female genital cutting . 276 Table 15.14.1 Attitude toward child beating: Women . 278 Table 15.14.2 Attitude toward child beating: Men . 279 Figure 15.1 Number of decisions in which currently married women participate . 267 16 ADULT AND MATERNAL MORTALITY . 281 Table 16.1 Adult mortality rates . 282 Table 16.2 Adult mortality probabilities . 283 Table 16.3 Maternal mortality . 284 Figure 16.1 Age specific mortality rates by sex . 283 Figure 16.2 Maternal mortality ratio (MMR) with confidence intervals for the seven years preceding the 2007 Liberia DHS and the 2013 Liberia DHS . 285 APPENDIX A SAMPLE DESIGN . 291 Table A.1 Households and population . 292 Table A.2 Enumeration areas and households . 292 Table A.3 Sample allocation of clusters and households . 293 Table A.4 Sample allocation of completed interviews with women and men . 294 Table A.5 Sample implementation: Women . 296 Table A.6 Sample implementation: Men . 297 Table A.7 Coverage of HIV testing by social and demographic characteristics: Women . 298 Table A.8 Coverage of HIV testing by social and demographic characteristics: Men . 299 Table A.9 Coverage of HIV testing by sexual behavior characteristics: Women . 300 Table A.10 Coverage of HIV testing by sexual behavior characteristics: Men . 301 APPENDIX B ESTIMATES OF SAMPLING ERRORS . 303 Table B.1 List of selected variables for sampling errors, Liberia 2013 . 306 Table B.2 Sampling errors for national sample, Liberia 2013 . 307 Table B.3 Sampling errors: Urban sample, Liberia 2013 . 308 Table B.4 Sampling errors: Greater Monrovia sample, Liberia 2013 . 309 Table B.5 Sampling errors: Other urban sample, Liberia 2013 . 310 Table B.6 Sampling errors: Rural sample, Liberia 2013 . 311 Table B.7 Sampling errors: North Western sample, Liberia 2013. 312 Table B.8 Sampling errors: South Central sample, Liberia 2013 . 313 Table B.9 Sampling errors: South Eastern A sample, Liberia 2013 . 314 Table B.10 Sampling errors: South Eastern B sample, Liberia 2013 . 315 Table B.11 Sampling errors: North Central sample, Liberia 2013 . 316 List of Tables and Figures • xv Table B.12 Sampling errors: Bomi sample, Liberia 2013 . 317 Table B.13 Sampling errors: Bong sample, Liberia 2013 . 318 Table B.14 Sampling errors: Gbarpolu sample, Liberia 2013 . 319 Table B.15 Sampling errors: Grand Bassa sample, Liberia 2013 . 320 Table B.16 Sampling errors: Grand Cape Mount sample, Liberia 2013 . 321 Table B.17 Sampling errors: Grand Gedeh sample, Liberia 2013 . 322 Table B.18 Sampling errors: Grand Kru sample, Liberia 2013 . 323 Table B.19 Sampling errors: Lofa sample, Liberia 2013 . 324 Table B.20 Sampling errors: Margibi sample, Liberia 2013 . 325 Table B.21 Sampling errors: Maryland sample, Liberia 2013 . 326 Table B.22 Sampling errors: Montserrado sample, Liberia 2013 . 327 Table B.23 Sampling errors: Nimba sample, Liberia 2013 . 328 Table B.24 Sampling errors: River Cess sample, Liberia 2013 . 329 Table B.25 Sampling errors: River Gee sample, Liberia 2013 . 330 Table B.26 Sampling errors: Sinoe sample, Liberia 2013 . 331 Table B.27 Sampling errors for adult and maternal mortality rates, Liberia 2013 . 332 APPENDIX C DATA QUALITY TABLES . 333 Table C.1 Household age distribution . 333 Table C.2.1 Age distribution of eligible and interviewed women . 334 Table C.2.2 Age distribution of eligible and interviewed men . 334 Table C.3 Completeness of reporting . 335 Table C.4 Births by calendar years . 335 Table C.5 Reporting of age at death in days . 336 Table C.6 Reporting of age at death in months . 337 Table C.7 Completeness of information on siblings . 337 Table C.8 Sibship size and sex ratio of siblings . 338 APPENDIX D PARTICIPANTS IN THE 2013 LIBERIA DEMOGRAPHIC AND HEALTH SURVEY . 339 APPENDIX E QUESTIONNAIRES . 345 Foreword • xvii FOREWORD Prior to the civil crisis, the Government of Liberia conducted three censuses and several demographic surveys. The censuses were the 1962 Population Census and the 1974 and 1984 Population and Housing Censuses, and the surveys were the 1978 National Demographic Survey (NDS) and the 1986 Liberia Demographic and Health Survey (1986 LDHS). With the exception of a few hard copies of the 1984 Population and Housing Census summary results, most other census and survey results stored on computer tapes and diskettes or printed as reports were extensively damaged or looted during the civil crisis. The economic and demographic situation of Liberia was adversely affected by the civil crisis to an extent still to be determined. This state of affairs affected policy decision-making and program development because the precise order of magnitude of population structures and processes was unknown. It was difficult to assess the extent of the large-scale displacement of rural and urban populations. There was a massive loss of lives caused by the civil crisis and destruction of social and physical infrastructure. The only recourse was secondary analysis of defective data collected by non-statistical professionals during the crisis. Information on the demographic processes of mortality and fertility and the associated aspects of reproductive health and primary health care were based on projections that used unreliable data and relied on dubious manipulation of those data. There has been therefore a dire need for accurate socio-demographic statistics to help others understand the dynamics of the Liberian population within the context of the recommendations of international conferences, such as the Africa Population Conference in Dakar, Senegal, in 1992, the International Conference on Population and Development in Cairo, Egypt, in 1994, and the Fourth World Conference on Women in Beijing, China, in 1995. Within this context, the Government of Liberia, in collaboration with its development partners, decided to separate the Department of Statistics (DOS) from the Ministry of Planning and Economic Affairs to create an autonomous statistical agency. The Liberia Institute of Statistics and Geo-Information Services (LISGIS) was established by an act of the National Transitional Legislative Assembly (NTLA) and approved by the chairman of the National Transitional Government of Liberia (NTGL) on July 22, 2004. The full title of the act is “The Liberian Code of Laws Revised, As Amended, By Adding Thereto A New Chapter 50A.” As indicated in Section 50A.1, its short title is known and cited as the “National Statistics and Geo-Information Act.” The goals and objectives are as follows: Goals: 1. Establish, develop, and maintain a holistic National Statistical and Spatial Data System (NSSDS) and an integrated National Statistical and Spatial Database (NSSD) 2. Coordinate, monitor, and supervise the NSSDS and NSSD to allow for the provision of holistic gender and geographically sensitive analysis for timely, relevant, and acceptable standards of information to institutions of government, business, and national and international communities xviii • Foreword Objectives: 1. Serve as the prime, authoritative agency of government responsible for collecting, managing, coordinating, supervising, evaluating, analyzing, disseminating, and setting quality standards for statistical and associated geo-information for overall national socio-economic reconstruction and development 2. More specifically, formulate and implement national strategies, programs, and policies for the development and management of a National Statistical and Geo-Information System and an integrated gender-sensitive and environmentally sensitive National Statistical and Spatial Database in Liberia The agency did not open its doors to the public immediately because it lacked budgetary support until 2006 when Her Excellency Ellen Johnson-Sirleaf, President of the Republic of Liberia, instructed the director of the Bureau of the Budget to include LISGIS in the national budget for Fiscal Year 2006/2007. Hence, for the first time an amount of US$450,000 was appropriated in the national budget for LISGIS to open its doors and commence its activities. Since 2006, LISGIS, with the support of the Government of Liberia and its development partners, and in collaboration with other ministries and agencies, has produced the following: • Comprehensive Food Security and Nutrition Survey (CFSNS) - 2006, 2008, 2010, 2012, and 2014 • 2007 Liberia Demographic and Health Survey (LDHS) for the provision of demographic, education, and health indicators for the monitoring of the Poverty Reduction Strategy I, (PRS-I), the County Development Agenda (CDA), and the Millennium Development Goals (MDGs) Programmes/Projects • 2007 Core Welfare Indicators Questionnaire Survey (CWIQ) and the 2007 Poverty Participatory Perception Survey (PPPS) to produce poverty line and indicators for the preparation and development of the Poverty Reduction Strategy I • 2008 PRS I Monitoring and Evaluation Framework • 2008 National Strategy for the Development of Statistics (NSDS) • 2008 National Population and Housing Census (NPHS) • The Agriculture Crops Survey (ACS) - 2008, 2009, 2010, 2011, 2012, and 2013 • 2010 Core Welfare Indicators Questionnaire Survey (CWIQ) • 2010 Labor Force Survey (LFS) • 2010 Human Right Survey (HRS) • National Accounts Annual Survey (NAAS) - 2008 and 2012 • National Establishment Census (NEC) - 2011 and 2013 • 2011 Social Cash Transfer Survey (SCTS) Foreword • xix • 2012 School-to-Work Transitional Survey (SWTS) • 2012 Most-at-Risk Youth and Adolescent Survey (MRYAS) • Liberia Malaria Indicator Survey (LMIS) –2009 and 2011 • Monrovia Consumer Price Index 2006, 2007, 2008, 2009, 2010, 2011, 2012 and 2013 • External/Foreign Trade – 2007, 2008, 2009, 2010, 2011, 2012, and 2013 The 2013 Liberia Demographic and Health Survey (2013 LDHS) constitutes the second post-war, and fourth overall, 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 and with no outside technical assistance. Liberia undertook a third LDHS in 2007, this time as part of the MEASURE DHS program. The 2013 LDHS covered the entire country. The main objectives of the 2013 LDHS were to provide reliable and detailed information on socio-demographic characteristics of the general population, the health and nutritional status of children, maternal and reproductive health, and HIV prevalence among adults. The information will enable the government of Liberia and the international community to develop, monitor, and evaluate policies and programs related to population, reproductive health, child health, and HIV/AIDS. The survey will also provide data for assessing progress in the achievements of a number of targets set for the Poverty Reduction Strategy (PRS) and the Millennium Development Goals (MDGs). Finally, the data will contribute to construction of a population database on reproductive health, gender, and attitudes towards violence against women, and will also provide institutional capacity-building at LISGIS. The four main survey outcomes will be: 1. Availability and accessibility of accurate, timely, and reliable indicators of socio- demographic characteristics of the population for use in policy formulation, national development planning, monitoring, and evaluation 2. Enhanced capacity in government, especially within LISGIS, to plan and conduct sample surveys 3. Increased knowledge of stakeholders at all levels on survey findings 4. Increased utilization of data for designing, monitoring, and evaluating development programs The planning of the LDHS began in 2012 with the establishment of the management team comprised of personnel from the Liberia Institute of Statistics and Geo-Information Services (LISGIS). The secretariat of the management team, which sits in the LISGIS, managed the day-to-day affairs of the project. The Project Steering Committee (PSC) and the Project Technical Committee (PTC) were established to assist LISGIS in mobilizing resources and managing the project. The PSC consisted of representatives from government ministries/agencies, the University of Liberia, UN agencies, and bilateral and multilateral donors. 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 in reviewing the sampling coverage, xx • Foreword questionnaire development, and tabulation plan. MEASURE DHS via ICF International provided technical backstopping during the project’s implementation. The activities of the 2013 LDHS commenced in September 2012 with the identification of selected enumeration areas (EAs) and the household listing, which lasted about one month. The preparation and finalization of the household and individual questionnaires and supervisor’s and interviewer’s manuals were completed with the assistance of MEASURE DHS, a program of ICF International. Following the recruitment of field staff candidates from across Liberia, the training of prospective field staff was carried out by ICF and LISGIS staff from February 11 to March 8, 2013, at the Catholic Retreat Center in the city of Gbarnga, Bong County. Upon selection of field teams, the survey was launched on March 9, 2013, starting with a parade in the main streets of Gbarnga, Bong County, and ending with an indoor program in the City Hall of Gbarnga. The field interview exercise started on March 10, 2013, and lasted four months. Sixteen teams of seven members each (one supervisor, one field editor, four interviewers, and a driver) deployed to collect the data from the field. The data were electronically processed and edited from April 2013 to August 2013. It is our hope that this report will be useful for advocacy, research, policy formulation and decision- making, program development, service delivery, and socio-economic development planning. There is more information available in the dataset, which is available from both LISGIS and the DHS Program. T. Edward Liberty (PhD) Director General/LISGIS Acknowledgments • xxi ACKNOWLEDGMENTS The Government of Liberia conducted the 2013 Liberia Demographic and Health Survey (LDHS) to measure the extent of health-related changes in Liberian society, especially changes in the basic profile of the population by age, sex, and education. Assessments were made of fertility rates and preferences, maternal and child mortality rates, maternal and child health indicators, knowledge and attitudes of women and men about HIV/AIDS and other sexually transmitted diseases, patterns of recent behavior regarding the use of condoms and other contraceptive methods, and the prevalence of HIV infection. The 2013 LDHS was undertaken by the Liberia Institute of Statistics and Geo-Information Services (LISGIS), the Ministry of Health and Social Welfare, and the National AIDS Control Program (NACP). ICF International provided technical support. The impetus to conduct the 2013 LDHS derived from the need to update data collected in the 2007 LDHS and to monitor progress made on a number of key indicators related to Poverty Reduction Strategy I (PRS-I) and the Millennium Development Goals (MDGs). The success of the 2013 LDHS is due to the many institutions and individuals who contributed immeasurably to project activities. I wish to extend my sincere thanks and appreciation for their tireless contributions. I would like to recognize the President of the Republic of Liberia, Her Excellency Ellen Johnson- Sirleaf, and the Government and the People of Liberia, not only for their support of the 2013 LDHS but also for their support of the development of national health care statistics. Also, I wish to extend gratitude to the LISGIS management and staff, the chairman and members of the Board of Directors, and all other individuals and institutions, including those listed in Appendix D of this report. They contributed immensely to the success of the 2013 LDHS. Finally, I wish to extend my sincere thanks and appreciation to the survey respondents who took time from their busy schedules to complete the survey questionnaires as well as others whose names have not been mentioned but who contributed to the successful completion of the 2013 LDHS project. T. Edward Liberty (PhD) Director General/LISGIS Millennium Development Goal Indicators • xxiii MILLENNIUM DEVELOPMENT GOAL INDICATORS Millennium Development Goal Indicators Liberia 2013 Indicator Sex Total Female Male 1. Eradicate extreme poverty and hunger 1.8 Prevalence of underweight children under age 5 13.2 16.6 15.0 2. Achieve universal primary education 2.1 Net attendance ratio in primary education1 40.0 37.7 38.8 2.3 Literacy rate of 15-24 year-olds2 64.2 79.0a 71.6b 3. Promote gender equality and empower women 3.1 Ratio of girls to boys in primary, secondary, and tertiary education 3.1a Ratio of girls to boys in primary education3 na na 1.1 3.1b Ratio of girls to boys in secondary education3 na na 0.9 3.1c Ratio of girls to boys in tertiary education3 na na 1.0 4. Reduce child mortality 4.1 Under 5 mortality rate4 111 115 94 4.2 Infant mortality rate4 67 72 54 4.3 Proportion of 1 year-old children immunized against measles 74.6 73.8 74.2 5. Improve maternal health 5.1 Maternal mortality ratio5 na na 1,072 5.2 Percentage of births attended by skilled health personnel6 na na 61.1 5.3 Contraceptive prevalence rate7 20.2 na na 5.4 Adolescent birth rate8 149.3 na na 5.5 Antenatal care coverage 5.5a Antenatal care coverage: at least one visit9 95.9 na na 5.5b Antenatal care coverage: four or more visits10 78.1 na na 5.6 Unmet need for family planning 31.1 na na 6. Combat HIV/AIDS, malaria and other diseases 6.1 HIV prevalence among the population age 15-24 1.4 0.5 1.0 6.2 Condom use at last high-risk sex11 22.1 45.1 33.6 6.3 Percentage of the population age 15-24 years with comprehensive correct knowledge of HIV/AIDS12 35.7 28.5 32.1 6.4 Ratio of school attendance of orphans to school attendance of non-orphans age 10-14 years * * * 6.7 Percentage of children under 5 sleeping under insecticide-treated bednets 37.4 38.7 38.1 6.8 Percentage of children under 5 with fever who are treated with appropriate antimalarial drugs13 54.3 56.9 55.7 Urban Rural Total 7. Ensure environmental sustainability 7.8 Percentage of population using an improved drinking water source14 85.8 56.6 73.0 7.9 Percentage of population with access to improved sanitation15 26.1 5.0 16.9 na = Not applicable * There are too few cases of orphans age 10-14 to present the data for this indicator. 1 The ratio is based on reported attendance, not enrollment, in primary education among primary school age children (6-11 year-olds). The rate also includes children of primary school age enrolled in secondary education. This is a proxy for MDG indicator 2.1, Net enrollment ratio. 2 Refers to respondents who attended secondary school or higher or who could read a whole sentence or part of a sentence 3 Based on reported net attendance, not gross enrollment, among 6-11 year-olds for primary, 12-17 year-olds for secondary and 18-22 year-olds for tertiary education 4 Expressed in terms of deaths per 1,000 live births. Mortality by sex refers to a 10-year reference period preceding the survey. Mortality rates for males and females combined refer to the 5-year period preceding the survey. 5 Expressed in terms of maternal deaths per 100,000 live births in the 7-year period preceding the survey 6 Among births in the five years preceding the survey 7 Percentage of currently married women age 15-49 using any method of contraception 8 Equivalent to the age-specific fertility rate for women age 15-19 for the 3-year preceding the survey, expressed in terms of births per 1,000 women age 15-19 9 With a skill provider 10 With any healthcare provider 11 Higher-risk sex refers to sexual intercourse with a non-marital, non-cohabitating partner. Expressed as a percentage of men and women age 15-24 who had higher-risk sex in the past 12 months. 12 Comprehensive knowledge means knowing that consistent use of a condom during sexual intercourse and having just one uninfected faithful partner can reduce the chance of getting HIV, knowing a healthy-looking person can have HIV, and rejecting the two most common local misconceptions about transmission or prevention of HIV. 13 Measured as the percentage of children age 0-59 months who were ill with a fever in the two weeks preceding the interview and received any anti-malarial drug 14 Percentage of de jure population whose main source of drinking water is a household connection (piped), public tap or standpipe, tubewell or borehole, protected dug well/hand pump, protected spring, rainwater collection, or bottled water. 15 Percentage of de jure population whose household has a flush toilet, ventilated improved pit latrine, pit latrine with a slab, or composting toilet and does not share this facility with other households a Restricted to men in sub-sample of households selected for the male interview b The total is calculated as the simple arithmetic mean of the percentages in the columns for male and females xxiv • Map of Liberia Introduction • 1 INTRODUCTION 1 1.1 HISTORY, GEOGRAPHY, AND ECONOMY iberia is located on the west coast of Africa, with a land area of 110,080 sq km and a coastline of 560 km that stretches along the Atlantic Ocean. The country is bordered by Sierra Leone to the west, Guinea to the northwest, and Côte d’Ivoire to the northeast and the east (see map). The country is divided into 15 counties that are further subdivided into districts and clans, with a population of approximately 3.5 million people (LISGIS, 2009; Table 1.1). Most of the country lies below 500 m in altitude, and rain forest and swamp are common geographic features. During the main rainy season—July through September—temperatures average 24.5°C and rise to 26.5°C in December and January when it is predominantly dry. Rainfall in the coastal areas where the capital of Monrovia lies, is over 5,000 mm a year; however, this decreases as one moves inland to as little as 2,000 mm. Average humidity is about 72 percent (MOH, 2001). Driven by iron-ore and rubber exports, construction, and the service sector, Liberia’s economy grew an estimated 8.9 percent in 2012, and is projected to expand by 7.7 percent in 2013 and 5.4 percent in 2014 (African Economic Outlook, 2014). Despite the economic growth of the country, more than half of the population (56 percent) lives below the poverty line on less than US$1.25 per day (World Bank, 2012). Liberia’s 2012 Human Development Index (HDI), a composite score of the population’s general well-being as measured by the United Nations Development Program (UNDP), is 0.388 (UNDP, 2013). The HDI compiles indicators that measure life expectancy, health, education, and standard of living to generate a composite score ranging from a low of zero to a high of 1.0. The HDI score for Liberia ranks the country 174 out of 187 countries with comparable data. The HDI of Sub-Saharan Africa, as a region, has increased from 0.365 in 1980 to 0.475 in 2012, which places Liberia’s score below the regional average. Liberia, which means land of the free, was founded by the American Colonization Society (ACS) in 1820 in a drive to resettle free slaves from America back to Africa. The capital, Monrovia, was named after the U. S. President, James Monroe. Liberia became an independent state in 1847, and Joseph Jenkins Roberts, one of the freed African-Americans, was its first elected president. Until 1904, the indigenous Africans resisted the settlers. As a result, they were refused citizenship in the new republic. To this day, descendants of the American freed slaves are referred to as Americo-Liberians, highlighting Liberia’s longstanding connection with the United States of America (Guannu, 2010). Table 1.1 Basic demographic indicators Demographic indicators from selected sources, Liberia Indicators Census 1984 Census 2008 Population (millions) 2.1 3.5 Intercensal growth rate (percent) 3.4 2.1 Density (population/km2) 145.0 240.9 Percent urban 47.0 Life expectancy (years) Male 51.6 Female 53.9 Source: LISGIS, Population and Housing Census 2008 L 2 • Introduction 1.2 OBJECTIVES OF THE SURVEY The primary objective of the 2013 Liberia Demographic and Health Survey (2013 LDHS) is to provide up-to-date estimates of basic demographic and health indicators. Specifically, the 2013 LDHS collected information on fertility levels, marriage, sexual activity, fertility preferences, family planning methods, breastfeeding practices, nutrition, childhood and maternal mortality, maternal and child health, and HIV/AIDS and other sexually transmitted infections (STIs). In addition, the 2013 LDHS provides estimates on HIV prevalence among adult Liberians. The 2013 LDHS is a follow-up to the 2007 LDHS, the 1999/2000 LDHS1, and the 1986 LDHS. A subset of the indicators presented in the 2013 LDHS overlap with indicators produced as part of the 2009 and 2011 Liberia Malaria Indicator Surveys (LMIS). 1.3 ORGANIZATION OF THE SURVEY The 2013 LDHS was implemented by the Liberia Institute of Statistics and Geo-Information Services (LISGIS). Data collection took place from 10 March to 19 July 2013. The survey was conducted under the aegis of the country’s Ministry of Health and Social Welfare (MOHSW). ICF International provided technical assistance through the United States Agency for International Development (USAID)-funded MEASURE DHS project, which provides support and technical assistance for population and health surveys in countries worldwide. USAID also provided material support directly to Government of Liberia for the survey. Other agencies and organizations that facilitated the successful implementation of the survey through technical or financial support were the National AIDS Control Program (NACP), the National Malaria Control Program (NMCP), the Global Fund, the United Nations Children’s Fund (UNICEF), the United Nations Population Fund (UNFPA), the United Nations Development Fund (UNDP), the World Health Organization (WHO), the Montserrado Regional Blood Bank, the National Reference Laboratory, and the Government of Liberia. 1.4 SURVEY IMPLEMENTATION 1.4.1 Sample Design The sampling frame for the 2013 LDHS was developed by the Liberia Institute of Statistics and Geo- Information Services (LISGIS) after the 2008 National Population and Housing Census (NPHC). The sampling frame is similar to that used for the 2009 and 2011 Liberia Malaria Indicator Surveys (LMIS), except that the classification of localities as urban or rural was updated through the application of standardized definitions. The sampling frame excluded nomadic and institutional populations such as residents of hotels, barracks, and prisons. Notably, the sampling frame for the 2013 LDHS differs markedly from that used for the 2007 LDHS, which was based on the 1984 NPHC. Taken together, these differences may complicate data comparisons between surveys. The 2013 LDHS followed a two-stage sample design that allowed estimates of key indicators for the country as a whole, for urban and rural areas separately, for Greater Monrovia and other urban areas separately, and for each of 15 counties. To facilitate estimates of geographical differentials for certain demographic indicators, the 15 counties were collapsed into five regions as follows: 1 The 1999/2000 LDHS was undertaken by the Ministry of Planning and Economic Affairs (MPEA) and the University of Liberia outside the purview of MEASURE DHS. Introduction • 3 North Western: Bomi, Grand Cape Mount, and Gbarpolu South Central: Montserrado, Margibi, and Grand Bassa South Eastern A: River Cess, Sinoe, and Grand Gedeh South Eastern B: River Gee, Grand Kru, and Maryland North Central: Bong, Nimba, and Lofa Regional data were presented in the 2007 LDHS, the 2009 LMIS, and the 2011 LMIS. However, in contrast with these past surveys, the South Central region now includes Monrovia. Thus, data presented for the South Central region in this report is not directly comparable to that presented in the 2007 LDHS, the 2009 LMIS, or the 2011 LMIS. The first stage of sample selection involved selecting sample points (clusters) consisting of enumeration areas (EAs) delineated for the 2008 NPHC. Overall, the sample included 322 sample points, 119 in urban areas and 203 in rural areas. To allow for separate estimates of Greater Monrovia and Montserrado as a whole, 44 sample points were selected in Montserrado; 16 to 26 sample points were selected in each of the other 14 counties. The second stage of selection involved the systemic sampling of households. A household listing operation was undertaken in all the selected EAs from mid-September to mid-October 2012. From these lists, households to be included in the survey were selected. Approximately 30 households were selected from each sample point for a total sample size of 9,677 households. During the listing, geographic coordinates (latitude and longitude) were taken in the center of the populated area of each EA using global positioning system (GPS) units. Because of the approximately equal sample sizes in each region, the sample is not self-weighting at the national level, and weighting factors have been added to the data file so that the results will be proportional at the national level. All women age 15-49 who were either permanent residents of the selected households or visitors who stayed in the household the night before the survey were eligible to be interviewed. In half of the households, all men age 15-49 who were either permanent residents of the selected households or visitors who stayed in the household the night before the survey were eligible to be interviewed. In the subsample of households selected for the male survey, blood samples were collected for laboratory testing to detect HIV from eligible women and men who consented; in this same subsample of households, height and weight information was collected from eligible women, men, and children 0-59 months. 1.4.2 Questionnaires Three questionnaires were used for the 2013 LDHS: the Household Questionnaire, the Woman’s Questionnaire, and the Man’s Questionnaire. These questionnaires are based on MEASURE DHS standard survey questionnaires and were adapted to reflect the population and health issues relevant to Liberia. Input was solicited from various stakeholders representing government ministries and agencies, nongovernmental organizations, and international donors. 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. 4 • Introduction The Household Questionnaire was used to list all the usual members of and visitors to selected households. Some basic demographic information was collected on the characteristics of each person listed, including his or her age, sex, education, and relationship to the head of the household. For children under age 18, survival status of the parents was determined. The data on age and sex of household members obtained in the Household Questionnaire were used to identify women and men who were eligible for individual interview and HIV testing. The Household Questionnaire also collected information on characteristics of the household’s dwelling unit, such as the source of water, type of toilet facility, materials used for the floor of the house, ownership of various durable goods, ownership and use of mosquito nets, and information on household out- of-pocket health-related expenditures. The Household Questionnaire was also used to record height and weight measurements of children 0-59 months and eligible adults. Also recorded was whether or not eligible adults consented to HIV testing. The Woman’s Questionnaire was used to collect information from all eligible women age 15-49. Eligible women who consented to being interviewed were asked questions on the following topics: • Background characteristics (age, education, religion, etc.) • Birth history and child mortality • Knowledge and use of family planning methods • Fertility preferences • Prenatal, delivery, and postnatal care • Breastfeeding and infant feeding practices • Vaccinations and childhood illnesses • Marriage and sexual activity • Women’s work and husband’s background characteristics • Malaria prevention and treatment • Knowledge, awareness, and behavior regarding AIDS and other sexually transmitted infections (STIs) • Adult mortality, including maternal mortality The Man’s Questionnaire was administered to all men age 15-49 in the subsample of households selected for the male survey in the 2013 LDHS sample. The Man’s Questionnaire collected much of the same information as the Woman’s Questionnaire, but was shorter because it did not contain a detailed reproductive history or questions on maternal and child health. 1.4.3 HIV Testing The 2013 LDHS incorporated HIV testing, which required taking finger prick blood from adults age 15-49. Blood specimens were collected in the field and tested in the laboratory. Verbal consent for blood collection for HIV testing for adults was requested from each respondent following completion of the individual interview. The protocol for HIV testing was approved by the Liberia Institute for Biomedical Research, the Institutional Review Board of ICF International, and the U.S. Centers for Disease Control and Prevention in Atlanta, Georgia. Interviewers collected blood specimens from all women and men who consented. The protocol for the blood specimen collection and analysis was based on the anonymous linked protocol developed by MEASURE DHS. This protocol allows for the merging of the HIV test results with the socio-demographic data collected in the individual questionnaires after all information that could potentially identify an individual is destroyed. Introduction • 5 Interviewers explained the procedure, the confidentiality of the data, and the fact that the test results would not be made available to the respondent. If a respondent consented to HIV testing, three to five blood spots from a finger prick were collected on a filter paper card to which a barcode label unique to the respondent was affixed. Respondents were asked for consent to having the laboratory store their blood sample for future unspecified testing. If the respondent did not consent to additional testing using their sample, it was indicated on the Household Questionnaire that the respondent refused additional tests using their specimen, and the words ‘No additional testing’ were written on the filter paper card. Each respondent, whether consenting or not, was given an informational brochure on HIV/AIDS and a list of nearby sites providing voluntary counselling and testing (VCT) services. A barcode label identical to that placed on the filter paper card was attached to the Household Questionnaire. A third copy of the same barcode was affixed to the Dried Blood Spot (DBS) Transmittal Form to track the blood samples from the field to the laboratory. Blood samples were dried overnight and packaged for storage the following morning. Samples were periodically collected from the field, along with the completed questionnaires, and transported to LISGIS in Monrovia to be logged in and checked; blood samples were then transported to the Montserrado Regional Blood Bank in Monrovia. At the Montserrado Regional Blood Bank, each blood sample was logged into the CSPro HIV Test Tracking System (CHTTS) database, given a laboratory number, and stored at -20˚C. The Blood Bank served as a convenient, but temporary, repository for the blood samples. Prior to the start of HIV testing, all samples were transferred to a -80˚C freezer at the National Reference Laboratory (NRL). The NRL is housed at the Liberia Institute for Biomedical Research (LIBR), and is where HIV testing took place. The HIV testing protocol stipulates that testing of blood can only be conducted after the questionnaire data entry is completed, verified, and cleaned, all paper questionnaires are destroyed, and all unique identifiers are removed from the questionnaire data file except the anonymous barcode number. The testing algorithm called for testing all samples with the first assay test, an ELISA, the Vironostika® HIV Ag/Ab (Biomérieux). A negative result was recorded as negative. All positives and 10 percent of the negatives were subjected to a second ELISA, the Enzygnost® HIV Integral II assay (Siemens). Positive samples on both tests were recorded as positive. If the first and second tests were discordant, the two ELISAs were repeated. If the results remained discordant, a third confirmatory test, the Inno-Lia HIV I/II line immunoassay (Innogenetics), was administered. The final result was recorded as positive if the line immunoassay confirmed the result to be positive and negative if the line immunoassay confirmed it to be negative. If the line immunoassay results were indeterminate, the sample was rendered indeterminate. The line immunoassay was also used to determine the HIV type of all positive samples. Upon finishing HIV testing, the HIV test results were entered into a spreadsheet with a barcode as the unique identifier to the result. The barcode linked the HIV test results with the individual interview data. 1.4.4 Training of Field Staff Six women and nine men participated in a training to pretest the LDHS survey protocol from 20 August to 7 September 2012. Most participants had worked on various LDHS survey activities previously, including the 2007 LDHS, or were employed by LISGIS. Trainers were staff from LISGIS and MEASURE DHS. Ten days of classroom instruction were provided. Additionally, pretest field practice took place over four days in both rural and urban locations. Following field practice, a debriefing session was held with the pretest field staff, and modifications to the questionnaires were made based on lessons drawn from the exercise. The recruitment of the LDHS field staff began in October 2012. The positions were advertised via announcements on bulletin boards in LISGIS headquarters and all LISGIS county offices. Minimum 6 • Introduction requirements of applicants included a high school diploma, fluency in English, and familiarity with one or more local dialects. A total of 3,662 applications were received from all counties. Vetting of all applications was done over a two-week period; 1,339 candidates were short-listed to sit for aptitude testing. Two aptitude tests were arranged. The first occurred in November 2013; those who passed were eligible for a second aptitude test, which was administered in January 2013. One thousand and sixty-four candidates sat for the first test, and 564 candidates sat for the second test. Based on the outcome of the second test combined with prior survey experience and other intangibles, a total of 128 persons (82 females and 46 males) were invited to the main training. The field staff main training took place over four weeks (11 February to 8 March 2013). The training was conducted following MEASURE DHS training procedures, which included class presentations, mock interviews, tests, and field practice. Trainers included LISGIS staff who participated in the LDHS pretest; staff from MOHSW, WHO, and Planned Parenthood Association of Liberia; and staff from ICF International. Out of those persons who were recruited and attended the main training, 65 women and 31 men were selected to carry out field work. Among this group, 16 persons were selected as team supervisors and 16 persons were selected as field editors; all others served as interviewers. Team supervisors and field editors were provided with additional training in methods of field editing, data quality control procedures, and fieldwork coordination. 1.4.5 Fieldwork Data collection was carried out by 16 field teams, each consisting of one team supervisor, one field editor, three female interviewers, one male interviewer, and one driver. On each team, one of the female interviewers and the male interviewer were also tasked with biomarker collection (conducting height and weight measurements and blood collection for HIV testing from eligible respondents). Five senior staff members from LISGIS and a senior staff member from NACP coordinated and supervised the fieldwork activities. Participants in fieldwork monitoring also included a resident advisor, a survey technical specialist, and a senior data processing specialist, all of whom worked directly for the MEASURE DHS project. Data collection took place over a four-month period from 10 March to 19 July 2013. For logistical reasons, including the difficulty in reaching the clusters located in the Southeast during the rainy season, fieldwork was divided into three phases: • Phase I: Maryland, Grand Kru, Sinoe, River Gee, Grand Gedeh • Phase II: Lofa, Bong, Nimba, Grand Bassa, River Cess • Phase III: Margibi, Montserrado, Greater Monrovia, Bomi, Gbarpolu, Grand Cape Mount At least three teams were assigned to each county. 1.4.6 Data Processing All questionnaires were returned to the LISGIS central office in Monrovia for data processing, which consisted of office editing, coding of open-ended questions, data entry, and editing computer-identified errors. The data were processed by a team of 12 data entry clerks, two data editors, one data entry supervisor, and two administrators of questionnaires; the latter checked that the clusters were completed according to the sample selection and that all members of the household eligible for individual interview were identified. Secondary editing was led by an LDHS coordinator. Several LISGIS staff took on the responsibility of receiving the blood samples from the field and checking them before sending them to the Montserrado Regional Blood Bank Introduction • 7 for storage. Data entry and editing using CSPro software was initiated in April 2013 and completed in late- August 2013. 1.5 RESPONSE RATES Table 1.2 shows response rates for the 2013 LDHS. A total of 9,677 households were selected for the sample, of which 9,386 were occupied. Of the occupied households, 9,333 were successfully interviewed, yielding a response rate of 99 percent. In the interviewed households, 9,462 eligible women were identified for individual interview; of these, complete interviews were conducted with 9,239 women, yielding a response rate of 98 percent. In the subsample of households selected for the male survey, 4,318 eligible men were identified and 4,118 were successfully interviewed, yielding a response rate of 95 percent. The lower response rate for men was likely due to their more frequent and longer absences from the household. Table 1.2 Results of the household and individual interviews Number of households, number of interviews, and response rates, according to residence (unweighted), Liberia 2013 Result Residence Total Urban Rural Household interviews Households selected 3,576 6,101 9,677 Households occupied 3,468 5,918 9,386 Households interviewed 3,450 5,883 9,333 Household response rate1 99.5 99.4 99.4 Interviews with women age 15-49 Number of eligible women 3,808 5,654 9,462 Number of eligible women interviewed 3,723 5,516 9,239 Eligible women response rate2 97.8 97.6 97.6 Interviews with men age 15-49 Number of eligible men 1,680 2,638 4,318 Number of eligible men interviewed 1,591 2,527 4,118 Eligible men response rate2 94.7 95.8 95.4 1 Households interviewed/households occupied 2 Respondents interviewed/eligible respondents Housing Characteristics and Household Population • 9 HOUSING CHARACTERISTICS AND HOUSEHOLD POPULATION 2 his chapter presents information on demographic and socioeconomic characteristics of the household population such as age, sex, education, and place of residence. The environmental profile of households in the 2013 LDHS sample is also examined. Taken together, these descriptive data provide context for the interpretation of demographic and health indices and can furnish an approximate indication of the representativeness of the survey. In the 2013 LDHS, a household was defined as a person or group of related and unrelated persons who lived together in the same dwelling unit(s), who acknowledged one adult male or female as the head of the household, who shared the same housekeeping arrangements, and who were considered a single unit. Information was collected from all the usual residents of each selected household and visitors who had stayed in the selected household the night before the interview. Those persons who stayed in the selected household the night before the interview (whether usual residents or visitors) represent the de facto population; usual residents alone constitute the de jure population. To maintain comparability with other surveys, all tables in this report refer to the de facto population unless otherwise specified. 2.1 HOUSEHOLD CHARACTERISTICS The physical characteristics of households and the availability and accessibility of basic household facilities are important in assessing the general welfare and socioeconomic condition of the population. The 2013 LDHS collected information on a range of housing characteristics, including source of drinking water, time taken to fetch water, type of sanitation facility, access to electricity, type of flooring, and number of rooms used for sleeping. Questions asked about sources of energy for cooking fuel and lighting and the distance to the nearest health facility. These data are presented for households and are further disaggregated by residence. T Key Findings • Seventy-three percent of Liberian households use an improved source of drinking water. • Only 14 percent of households in Liberia use improved toilet facilities that are not shared with other households; 45 percent of households have no toilet facility at all. • Ten percent of households have access to electricity. • Ninety-eight percent of households use solid fuel for cooking. • Ownership of mobile phones has risen dramatically. Although 29 percent of households owned a mobile phone in 2007, 65 percent of households reported owning a mobile phone in the current survey. • One in four children under 5 has a birth certificate. • Approximately 7 percent of children under age 18 are orphaned (that is, one or both parents are not living). • Forty-seven percent of females and 33 percent of males age 6 and older have never attended school. 10 • Housing Characteristics and Household Population 2.1.1 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, 2002). Table 2.1 includes a number of indicators that are useful in monitoring household access to improved drinking water (WHO and UNICEF, 2012a). The source of the drinking water is an indicator of suitability for drinking. Sources that are more likely to provide water suitable for drinking are identified in Table 2.1 as improved sources. These include a piped source within the dwelling, yard, or plot; a public tap, tube well, or borehole; a hand pump/protected well or protected spring; and rainwater or bottled water.1 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, if it is fetched from a source that is not immediately accessible to the household, it may be contaminated during transport or storage. Finally, home water treatment can be effective in improving the quality of household drinking water. The source of drinking water is important because waterborne diseases, including diarrhea and dysentery, are prevalent in Liberia. Sources of water expected to be relatively free of the agents responsible for these diseases are piped water, hand pumps/protected wells, and protected springs. Other sources such as unprotected wells, rivers or streams, and ponds, lakes, or dams are more likely to carry disease-causing agents. Table 2.1 indicates that a majority of Liberian households (73 percent) have access to improved water sources: 3 percent from piped water (including public tap or standpipe), 1 percent from tube well or borehole, 64 percent from a hand pump or protected dug well, 1 percent from a protected spring, 4 percent from bottled water, and less than 1 percent from rainwater. Households in urban areas (86 percent) are more likely than those in rural areas (56 percent) to have access to an improved source of water. According to the 2007 LDHS, 82 percent of urban households and 56 percent of rural households used improved sources of water. Thus, there has been little change in access to improved sources of drinking water since 2007. For 8 percent of households in Liberia, the source of drinking water is on their premises; 10 percent of urban households and 5 percent of rural households have water on their premises. Eighty-nine percent of Liberian households obtain water from a source not on the premises; 71 percent of households take less than 30 minutes to obtain drinking water, and 18 percent take 30 minutes or longer to obtain drinking water. Fourteen percent of households appropriately treat their drinking water. Ten percent use bleach or chlorine, 4 percent use WaterGuardTM, and less than one percent uses other methods of treatment. The findings are comparable to those reported in the 2007 LDHS, in which 16 percent of households used an appropriate method to treat their drinking water. 1 The categorization into improved and non-improved categories follows that proposed by the WHO/UNICEF Joint Monitoring Programme for Water Supply and Sanitation (WHO and UNICEF, 2012b). Housing Characteristics and Household Population • 11 Table 2.1 Household drinking water Percent distribution of households and de jure population by source of drinking water, time to obtain drinking water, and treatment of drinking water, according to residence, Liberia 2013 Characteristic Households Population Urban Rural Total Urban Rural Total Source of drinking water Improved source 85.8 55.5 72.6 85.8 56.6 73.0 Piped water into dwelling/yard/ plot 1.9 0.0 1.1 1.9 0.0 1.1 Public tap/standpipe 3.2 0.0 1.8 3.0 0.0 1.7 Tube well/borehole 1.5 0.8 1.2 1.8 0.8 1.4 Hand pump/protected dug well 71.5 53.7 63.8 72.9 54.8 65.0 Protected spring 1.2 0.7 1.0 1.1 0.8 1.0 Rain water 0.2 0.1 0.1 0.1 0.1 0.1 Bottled/sack water 6.3 0.1 3.6 4.8 0.1 2.8 Non-improved source 14.1 44.4 27.3 14.1 43.2 26.9 Unprotected dug well 6.2 9.2 7.5 6.5 9.4 7.8 Unprotected spring 0.5 2.8 1.5 0.5 2.7 1.5 Tanker truck/cart with small tank 4.8 0.3 2.8 4.4 0.3 2.6 Surface water 2.6 32.1 15.4 2.7 30.8 15.0 Total1 100.0 100.0 100.0 100.0 100.0 100.0 Time to obtain drinking water (round trip) Water on premises 9.7 4.8 7.6 10.6 5.6 8.4 Less than 30 minutes 66.6 76.7 71.0 64.4 75.5 69.3 30 minutes or longer 19.0 16.7 18.0 20.4 17.1 19.0 Don't know/missing 4.6 1.8 3.4 4.6 1.8 3.4 Total 100.0 100.0 100.0 100.0 100.0 100.0 Water treatment prior to drinking2 Boiled 0.2 0.2 0.2 0.4 0.2 0.3 Bleach/chlorine added 12.9 7.0 10.4 13.7 7.5 11.0 PURTM 0.2 0.1 0.2 0.2 0.1 0.2 WaterGuardTM 5.4 1.9 3.9 5.9 2.1 4.2 Strained through cloth 0.0 0.2 0.1 0.0 0.2 0.1 Ceramic, sand or other filter 0.1 0.1 0.1 0.0 0.1 0.1 Let stand and settle 0.1 0.2 0.1 0.0 0.2 0.1 Other 0.2 0.2 0.2 0.3 0.2 0.3 No treatment 80.5 90.2 84.7 79.4 89.4 83.8 Percentage using an appropriate treatment method3 18.0 9.0 14.1 19.3 9.6 15.0 Number 5,289 4,044 9,333 25,982 20,234 46,216 1 Total includes 8 households for which information on source of drinking water is missing. 2 Respondents may report multiple treatment methods, so the sum of treatment may exceed 100 percent. 3 Appropriate water treatment methods include boiling, bleaching, PURTM, WaterGuardTM, filtering, and solar disinfecting. 2.1.2 Sanitation Facilities and Waste Disposal Ensuring adequate sanitation facilities is another Millennium Development Goal 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 and UNICEF, 2012a). The types of facilities considered improved are toilets that flush or pour flush into a piped sewer system, septic tank, or pit latrine; ventilated improved pit (VIP) latrines; and pit latrines with a slab. Table 2.2 shows that only 14 percent of households in Liberia use improved toilet facilities that are not shared with other households, and 28 percent of households use facilities that would be considered improved if they were not shared. Twenty-two percent of households in urban areas have improved toilet facilities that are not shared compared with 4 percent in rural areas. 12 • Housing Characteristics and Household Population A majority of Liberian households (58 percent) have non-improved toilet facilities. Six percent of households use pit latrines without slabs or open pits, and another 6 percent use hanging toilets. Forty-five percent of households have no toilet facility at all, a lower proportion than that reported in the 2007 LDHS (55 percent). Still, 24 percent of households in urban areas and 73 percent of households in rural areas lack any toilet facility. Table 2.2 Household sanitation facilities Percent distribution of households and de jure population by type of toilet/latrine facilities, according to residence, Liberia 2013 Type of toilet/latrine facility Households Population Urban Rural Total Urban Rural Total Improved, not shared facility 21.9 4.1 14.2 26.1 5.0 16.9 Flush/pour flush to piped sewer system 1.0 0.0 0.6 1.2 0.0 0.7 Flush/pour flush to septic tank 16.4 0.9 9.7 19.1 1.2 11.3 Flush/pour flush to pit latrine 0.6 0.2 0.4 0.7 0.2 0.5 Ventilated improved pit (VIP) latrine 3.4 2.1 2.8 4.6 2.5 3.7 Pit latrine with a slab 0.5 0.9 0.7 0.6 1.0 0.8 Shared facility1 36.2 16.2 27.5 32.0 16.5 25.2 Flush/pour flush to piped sewer system 0.8 0.0 0.4 0.6 0.0 0.3 Flush/pour flush to septic tank 8.2 0.6 4.9 6.3 0.7 3.8 Flush/pour flush to a pit latrine 2.0 0.1 1.2 1.7 0.1 1.0 Ventilated improved pit (VIP) latrine 19.2 12.3 16.2 17.1 12.4 15.0 Pit latrine with a slab 6.0 3.1 4.7 6.3 3.2 5.0 Non-improved facility 41.9 79.7 58.3 41.8 78.5 57.9 Flush/pour flush not to sewer/septic tank/pit latrine 1.0 0.1 0.6 0.9 0.1 0.5 Pit latrine without slab/open pit 6.2 5.3 5.8 6.6 5.8 6.3 Bucket 0.4 0.0 0.2 0.4 0.0 0.2 Hanging toilet/hanging latrine 9.7 1.7 6.2 8.4 1.7 5.5 No facility/bush/field 24.2 72.6 45.2 24.8 70.9 45.0 Other 0.5 0.0 0.3 0.6 0.0 0.3 Total 100.0 100.0 100.0 99.9 100.0 99.9 Number 5,289 4,044 9,333 25,982 20,234 46,216 Note: Total includes 2 households using composting toilets that are shared, and 3 households for which information on the type of toilet facility is missing. 1 Facilities that would be considered improved if they were not shared by two or more households. 2.1.3 Housing Characteristics Table 2.3 presents information on characteristics of the dwelling in which households live. In addition to reflecting the household’s socioeconomic situation, these characteristics show environmental conditions in which the household lives. For example, use of biomass fuels exposes the household members to indoor pollution, which has a direct bearing on their health and welfare. Use of electricity usually goes hand in hand with improved housing structures and a better standard of living. In Liberia, only 10 percent of households have electricity that is connected. There is a large difference in access to electricity between urban and rural households (16 percent in urban areas compared with 1 percent in rural areas). The percentage of households with electricity has risen since 2007, when only 3 percent of households had electricity. This gain, however, has been in urban households, in which those having electricity rose from 7 percent to 16 percent; the percentage of rural households with electricity is unchanged since 2007. The type of material used for flooring is also an indicator of socioeconomic status and to some extent determines the household’s vulnerability to disease-causing agents. Forty-seven percent of Liberian households have earthen floors (made of earth, sand, or mud), and 45 percent have concrete or cement floors. Housing Characteristics and Household Population • 13 Large differences exist between rural and urban households; earth flooring is most common in rural areas (80 percent of households), while concrete or cement is most common in urban areas (64 percent of households). The number of rooms used for sleeping indicates the extent of crowding. Overcrowding increases the risk of contracting diseases. Overall, 40 percent of Liberian households use one room for sleeping, 27 percent use two rooms, and 33 percent use three or more rooms for sleeping. Cooking and heating with solid fuels can lead to high levels of indoor smoke, a complex mix of health-damaging pollutants that could increase the risk of contracting diseases (WHO, 2011a). Solid fuels include fire coal/charcoal and wood. In the 2013 LDHS, households were asked about their primary source of fuel for cooking. The results show that 98 percent of households use solid fuel for cooking, with wood being the top source of solid fuel (54 percent of households). There are large differentials in cooking fuel between urban and rural areas. Although 90 percent of households in the rural areas use wood for cooking, the main source of cooking fuel in the urban areas is fire coal/charcoal (70 percent). In addition to having health effects on the household population, both fuels have a negative impact on the environment because they involve cutting down trees. The potential for exposure to harmful effects of smoke from using solid fuels for cooking increases if cooking occurs within the home itself rather than outdoors or in a separate building. Seventeen percent of households in Liberia cook in the house, 27 percent cook in a separate building, 17 percent cook on a porch, and 37 percent cook outdoors. Twenty-two percent of urban households cook in the house, compared with 11 percent of rural households. Nearly half of Liberian households use plastic, battery-powered Chinese lamps as their major source of lighting. Other common lighting energy sources were battery (16 percent), flashlight/torch (15 percent), electricity (10 percent), and oil lamp/jack- o’-lantern (6 percent). Table 2.3 Household characteristics Percent distribution of households by housing characteristics, percentage using solid fuel for cooking, and percent distribution by frequency of smoking in the home, according to residence, Liberia 2013 Housing characteristic Residence Total Urban Rural Electricity Yes 16.4 1.2 9.8 No 83.6 98.7 90.1 Total 100.0 100.0 100.0 Flooring material Earth/sand/mud 21.4 79.6 46.6 Wood planks 0.6 0.1 0.4 Parquet or polished wood 0.2 0.0 0.1 Floormat/linoleum/vinyl 6.6 0.6 4.0 Ceramic tiles/terrazzo 6.6 0.6 4.0 Concrete/cement 64.3 19.1 44.7 Carpet 0.4 0.1 0.3 Total 100.0 100.0 100.0 Rooms used for sleeping One 44.1 34.7 40.0 Two 25.1 29.2 26.9 Three or more 30.5 36.0 32.9 Total 100.0 100.0 100.0 Cooking fuel Electricity 0.1 0.0 0.0 Gas cylinder 0.0 0.0 0.0 Kerosene stove 0.3 0.0 0.2 Fire coal/charcoal 70.3 9.1 43.8 Wood 26.5 90.2 54.1 No food cooked in household 2.7 0.7 1.8 Total 100.0 100.0 100.0 Percentage using solid fuel for cooking1 96.8 99.3 97.9 Place for cooking In the house 22.2 10.9 17.3 In a separate building 14.9 42.9 27.1 On a porch 23.0 8.9 16.9 Outdoors 37.2 36.6 36.9 No food cooked in household 2.7 0.7 1.8 Total 100.0 100.0 100.0 Lighting energy Electricity 16.3 0.9 9.6 Battery 11.2 22.7 16.2 Solar 0.1 0.1 0.1 Kerosene 0.3 0.3 0.3 Oil lamp/Jack-o’-lantern 2.5 9.4 5.5 Chinese lamp 53.1 43.7 49.0 Gas 1.5 0.3 1.0 Candles 4.1 1.6 3.1 Firewood 0.0 0.5 0.2 Flashlight/Torch 10.6 20.3 14.8 No lighting in household 0.1 0.3 0.2 Other 0.1 0.1 0.1 Total 100.0 100.0 100.0 Frequency of smoking in the home Daily 8.8 17.8 12.7 Weekly 0.5 1.4 0.9 Monthly 0.0 0.1 0.1 Less than monthly 0.1 0.1 0.1 Never 90.6 80.6 86.2 Total 100.0 100.0 100.0 Number 5,289 4,044 9,333 Note: Totals include 5 households for which information on electricity is missing, 1 case for which information on flooring material is "other," 24 households for which information on rooms used for sleeping is missing, 2 households for which information on cooking fuel is missing, 1 household for which place for cooking is "other," and 3 households for which information on frequency of smoking in the home is missing. 1 Includes fire coal, charcoal, and wood. 14 • Housing Characteristics and Household Population Information on frequency of smoking inside the home was obtained to assess the percentage of households in which there is exposure to second-hand smoke, which causes health risks in children and adults who do not smoke. Pregnant women who are exposed to secondhand smoke have a higher risk of delivering a low birth weight baby (Windham et al., 1999), and children exposed to second-hand smoke are at increased risk for respiratory and ear infections and poor lung development (U.S. Department of Health and Human Services, 2006). Thirteen percent of Liberian households report that someone smokes at the home daily, one percent report that someone smokes at least once a week, and less than one percent report that someone smokes monthly or less frequently than once a month. In 86 percent of households, smoking never occurs in the home. Overall, smoking inside the home is less frequent in urban areas than in rural areas; smoking never occurs in 91 percent of urban households, compared with 81 percent of rural households. 2.1.4 Household Possessions The availability of durable goods is an indicator of a household’s socioeconomic status. Moreover, each particular item has specific benefits. For instance, having access to a radio or a television exposes household members to innovative ideas; a refrigerator prolongs the wholesomeness of foods; and a means of transport allows greater access to services away from the local area. Table 2.4 shows the ownership of selected household possessions by residence. The most commonly owned items by households are a mattress (81 percent of households), table (72 percent), chairs (67 percent), a mobile telephone (65 percent), and a radio (59 percent). Additionally, 34 percent of households own a watch, 20 percent own a cupboard, 14 percent own a television, 13 percent own a generator, 5 percent own a computer, and 4 percent own a refrigerator. All of these figures except for a watch are higher than those recorded in the 2007 LDHS. Most notably, household ownership of mobile phones has risen from 29 percent to 65 percent. Urban households are more likely than rural households to own each of the items. With regard to means of transportation, 8 percent of households own a motorcycle or scooter, 4 percent own a car or truck, 4 percent own a bicycle, and 1 percent owns a boat or canoe. Ownership of each of these items has either increased or remained unchanged since 2007. Farming of agricultural land and ownership of farm animals are common in Liberia, with about 4 in 10 households farming land and 35 percent of households owning farm animals. Not surprisingly, the proportion of households in rural areas that farm agricultural land (63 percent) and own farm animals (50 percent) is higher than the proportion of households in urban areas that farm agricultural land (19 percent) and own farm animals (23 percent). Table 2.4 Household possessions Percentage of households possessing various household effects, means of transportation, agricultural land and livestock/farm animals, by residence, Liberia 2013 Possession Residence Total Urban Rural Household effects Generator 20.4 4.1 13.4 Solar panel 0.8 0.4 0.6 Radio 66.7 48.8 58.9 Television 23.2 2.3 14.1 Mobile telephone 81.7 42.4 64.6 Refrigerator (ice box) 6.5 1.1 4.1 Computer 8.5 0.6 5.1 Table 82.0 57.9 71.6 Chairs 77.9 52.3 66.8 Cupboard 31.6 4.3 19.7 Mattress 92.0 66.3 80.9 Sewing machine 3.5 1.1 2.5 Watch 42.8 23.0 34.2 Means of transport Bicycle 5.5 1.3 3.7 Motorcycle/scooter 10.0 5.7 8.1 Car/truck 6.7 0.5 4.0 Boat or canoe 0.8 1.4 1.0 Farming of agricultural land1 19.3 63.1 38.3 Ownership of farm animals2 23.3 49.7 34.7 Ownership of a bank account 28.5 4.3 18.0 Number 5,289 4,044 9,333 1Households were asked if any member of the household farmed agricultural land. Such land need not be owned by the household. 2 Cows, pigs, goats, sheep, or chickens/ducks/guinea fowl. Housing Characteristics and Household Population • 15 Only 18 percent of households in Liberia have at least one member who has a bank account. Possession of a bank account is much more common in urban areas (29 percent) than in rural areas (4 percent). 2.1.5 Distance to a Health Facility In the 2013 LDHS, households were asked how far they lived from the nearest health facility. They were also asked the means of transportation they would use to get to the nearest health facility and how long it would take to get there by this means of transportation. Few respondents knew the actual distance in miles to the health facility, but nearly all knew the time it would take by a given means of transportation. The results have therefore been tabulated by transport type and by time. As shown in Table 2.5, walking is the major means of transport to health facilities (cited by 65 percent of household respondents), followed by public transport (30 percent) and cars or motorcycles (4 percent). Rural households are more likely than urban households to walk (75 percent versus 56 percent), whereas urban households are more likely to use public transport than rural households (37 percent versus 21 percent). One third of all Liberian households are within 20 minutes of the nearest health facility, regardless of means of transportation. Table 2.5 Method of travel and travel time to nearest health facility Percent distribution of households by transportation method to nearest health facility, and time required to get to nearest health facility by usual means of transportation, according to residence, Liberia 2013 Characteristic Residence Total Urban Rural Transportation method to nearest health facility Car/motorcycle 5.6 2.4 4.2 Public transport 36.9 20.6 29.8 Walking 56.4 75.3 64.6 Bicycle 0.8 0.7 0.8 Wheelbarrow 0.0 0.1 0.0 Other 0.1 0.3 0.2 Total 100.0 100.0 100.0 Time to get to nearest health facility by usual means of transportation <20 min 45.0 15.8 32.4 20-40 min 32.1 16.5 25.3 41-60 min 11.0 15.4 12.9 61-120 min 5.0 24.1 13.3 >120 min 3.9 25.8 13.4 Don't know 2.9 2.3 2.6 Total 100.0 100.0 100.0 Number of households 5,289 4,044 9,333 Note: Totals include 33 households for which the transportation method to the nearest health facility is missing, and 2 households for which the time to get to the nearest health facility is missing. As shown in Table 2.6, among households that travel to health facilities by walking, 30 percent require less than 20 minutes to get to the nearest health facility. As expected, urban households are much more likely to be located within a 20-minute walking distance to a health facility than rural households (45 percent and 15 percent, respectively). In contrast, the percentage of rural households that require greater than 120 minutes to walk to a health facility is far larger than the percentage of urban households (31 percent and 7 percent, respectively). 16 • Housing Characteristics and Household Population Table 2.6 Travel time to health facility by walking Among households that travel to the nearest health facility by walking, the percent distribution of the time required to walk to the nearest health facility, according to residence, Liberia 2013 Characteristic Residence Total Urban Rural Time to get to nearest health facility by walking <20 min 45.2 14.8 29.8 20-40 min 27.4 10.8 19.0 41-60 min 11.0 14.2 12.6 61-120 min 7.5 26.9 17.3 >120 min 6.5 31.3 19.0 Don't know 2.4 2.2 2.3 Total 100.0 100.0 100.0 Number of households that travel to health facility by walking 2,982 3,046 6,028 2.2 HOUSEHOLD WEALTH Information on household assets was used to create an index that is used throughout this report to represent the wealth of the households interviewed in the 2013 LDHS. This method for calculating a country- specific wealth index was developed and tested in a large number of countries in relation to inequalities in household income, use of health services, and health outcomes (Rutstein and Johnson, 2004). It has been shown to be consistent with expenditure and income measures. The wealth index is constructed using household asset data, including ownership of consumer items ranging from a television to a bicycle or car, as well as dwelling characteristics, such as source of drinking water, sanitation facilities, and type of flooring material. In its current form, which takes account of urban-rural differences in these items and characteristics, the wealth index is created in three steps. In the first step, a subset of indicators common to urban and rural areas is used to create wealth scores for households in both areas. For purposes of creating scores, categorical variables are transformed into separate dichotomous (0-1) indicators. These indicators and those that are continuous are then examined using principal components analysis to produce a common factor score for each household. In the second step, separate factor scores are produced for households in urban and rural areas using area-specific indicators (Rutstein, 2008). The third step combines the separate area-specific factor scores to produce a nationally applicable combined wealth index by adjusting area-specific scores through a regression on the common factor scores. The resulting combined wealth index has a mean of zero and a standard deviation of one. Once the index is computed, national-level wealth quintiles (from lowest to highest) are formed by assigning the household score to each de jure household member, ranking each person in the population by that score, and then dividing the ranking into five equal categories, each comprising 20 percent of the population. Thus, throughout this report, wealth quintiles are expressed in terms of quintiles of individuals in the overall population rather than quintiles of individuals at risk for any one health or population indicator. For example, quintile rates for infant mortality refer to infant mortality rates per 1,000 live births among all people in the population quintile concerned, as distinct from quintiles of live births or newly born infants, who constitute the only members of the population at risk of mortality during infancy. Table 2.7 presents wealth quintiles by residence, region, and county. Also included in the table is the Gini Coefficient, which indicates the level of concentration of wealth, with 0 being an equal distribution and 1 a totally unequal distribution. Housing Characteristics and Household Population • 17 Table 2.7 Wealth quintiles Percent distribution of the de jure population by wealth quintiles, and the Gini Coefficient, according to residence and region, Liberia 2013 Residence/region Wealth quintile Total Number of persons Gini coefficient Lowest Second Middle Fourth Highest Residence Urban 4.6 8.7 21.1 31.6 34.0 100.0 25,982 0.20 Greater Monrovia 0.0 0.1 8.4 37.9 53.6 100.0 14,159 0.06 Other urban 10.1 19.0 36.3 24.0 10.6 100.0 11,823 0.24 Rural 39.8 34.5 18.6 5.2 2.0 100.0 20,234 0.31 Region North Western 30.9 31.8 24.8 9.2 3.4 100.0 4,505 0.32 South Central 8.4 6.9 13.6 31.7 39.4 100.0 21,857 0.20 South Eastern A 47.3 29.2 14.8 6.1 2.7 100.0 2,940 0.38 South Eastern B 36.9 31.7 20.2 8.6 2.6 100.0 3,291 0.29 North Central 25.1 32.3 29.8 10.6 2.3 100.0 13,622 0.24 County Bomi 27.8 23.6 28.4 15.6 4.6 100.0 1,335 0.33 Bong 34.1 35.6 21.8 7.2 1.3 100.0 4,974 0.27 Gbarpolu 41.1 37.1 16.0 3.7 2.1 100.0 992 0.33 Grand Bassa 43.0 17.5 14.9 15.2 9.5 100.0 2,453 0.41 Grand Cape Mount 28.1 34.4 26.5 7.7 3.2 100.0 2,179 0.31 Grand Gedeh 35.7 28.7 24.4 7.7 3.6 100.0 999 0.31 Grand Kru 53.3 32.0 11.3 2.6 0.7 100.0 1,260 0.22 Lofa 33.3 39.4 19.9 6.4 1.0 100.0 2,493 0.36 Margibi 13.6 17.9 25.2 26.2 17.1 100.0 3,627 0.28 Maryland 21.6 30.7 28.6 15.0 4.1 100.0 1,439 0.32 Montserrado 1.8 2.7 10.7 35.6 49.2 100.0 15,777 0.13 Nimba 14.5 26.8 40.2 14.9 3.6 100.0 6,154 0.27 River Cess 71.3 20.8 3.5 3.3 1.1 100.0 769 0.40 River Gee 39.3 33.4 18.7 5.6 3.0 100.0 592 0.37 Sinoe 41.3 35.1 14.0 6.5 3.0 100.0 1,171 0.39 Total 20.0 20.0 20.0 20.0 20.0 100.0 46,216 0.32 Two-thirds of the urban population is represented in the fourth and highest quintiles (66 percent), while nearly three-quarters of the population (74 percent) in rural areas is in the lowest and second wealth quintiles. The distribution of the population by wealth quintile among counties shows large variations. As expected, Montserrado has the largest proportion in the highest wealth quintile (49 percent). Grand Kru has the largest proportion in the lowest wealth quintile (53 percent). 2.3 HAND WASHING Hand washing with soap and water is ideal. However, hand washing with a non-soap cleansing agent such as ash or sand is an improvement over not using any cleansing agent. To obtain hand-washing information, interviewers asked to see the place where members of the household most often washed their hands; information on the availability of water, cleansing agents, or both was recorded only for households where the hand washing place was observed. Interviewers observed the place most often used for hand washing in only 2 percent of households (data not shown). The most common reason interviewers were not able to observe the place where members of the household washed their hands was that there was no specific place designated for hand washing (data not shown). Among those few households where the hand washing place was observed, 47 percent had soap and water, 2 percent had water and a cleansing agent other than soap, 19 percent had only water, 5 percent had soap but no water, and 27 percent had no water, soap, or any other cleansing agent at the hand washing place (data not shown). 18 • Housing Characteristics and Household Population 2.4 HOUSEHOLD POPULATION BY AGE, SEX, AND RESIDENCE Age and sex are important demographic variables that are the primary basis for demographic classification in vital statistics, censuses, and surveys. They are also very important variables in the study of mortality, fertility, and marriage. The distribution of the de facto household population in the 2013 LDHS is shown in Table 2.8 by five-year age groups, according to sex and residence. A total of 45,042 individuals resided in the 9,333 households successfully interviewed; the population was nearly evenly distributed between females (22,725) and males (22,317). Table 2.8 Household population by age, sex, and residence Percent distribution of the de facto household population by five-year age groups, according to sex and residence, Liberia 2013 Age Residence Total Urban Rural Male Female Total Male Female Total Male Female Total <5 15.2 13.3 14.2 18.9 18.1 18.5 16.8 15.3 16.1 5-9 16.6 15.0 15.8 18.4 16.9 17.7 17.4 15.8 16.6 10-14 12.9 14.6 13.8 13.7 10.8 12.3 13.3 13.0 13.1 15-19 11.5 11.8 11.7 7.4 7.6 7.5 9.7 10.0 9.8 20-24 8.7 8.9 8.8 5.5 6.7 6.1 7.2 8.0 7.6 25-29 7.5 8.3 7.9 6.0 6.9 6.4 6.8 7.7 7.3 30-34 5.8 5.7 5.8 5.5 5.8 5.7 5.7 5.7 5.7 35-39 4.9 5.9 5.4 5.3 5.4 5.3 5.1 5.7 5.4 40-44 4.4 3.7 4.0 4.5 4.2 4.3 4.4 3.9 4.2 45-49 3.7 2.5 3.1 3.7 3.8 3.8 3.7 3.1 3.4 50-54 2.6 3.2 2.9 3.1 4.5 3.8 2.8 3.8 3.3 55-59 2.1 2.2 2.2 2.3 2.4 2.4 2.2 2.3 2.2 60-64 1.4 1.7 1.5 1.8 2.1 2.0 1.6 1.9 1.7 65-69 1.1 1.1 1.1 1.5 1.7 1.6 1.3 1.4 1.3 70-74 0.7 0.7 0.7 1.0 1.3 1.1 0.8 0.9 0.9 75-79 0.5 0.5 0.5 0.8 0.8 0.8 0.6 0.6 0.6 80 + 0.4 0.8 0.6 0.8 1.0 0.9 0.6 0.9 0.7 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Number 12,395 13,042 25,438 9,922 9,683 19,604 22,317 22,725 45,042 Note: Total includes 6 cases for which age is unknown or missing. The age-sex structure of the population is shown in the population pyramid in Figure 2.1. The broad base of the pyramid indicates that Liberia’s population is young, a scenario typical of countries with high fertility rates. The proportion of persons under age 15 was about 46 percent in 2013, while the proportion of individuals age 65 and older was about 4 percent. This pattern is similar to the ones observed in the 2011 LMIS, the 2009 LMIS, and the 2007 LDHS. Nevertheless, the observation that the population of those age 5-9 (17 percent) is greater than those less than age 5 (16 percent) is unlikely, and is indicative of either age displacement or omission of children under 5 from households. Presumably this was done to reduce interviewers’ workloads since women were asked questions about their children under age 5, and in half of the households, children under 5 were eligible for height and weight measurements. In addition, there appears to be age displacement between women age 50-54 and age 45-49. Interviewers may have intentionally overestimated the respondents’ ages as older than the age cut-off of 49 so as to make them ineligible for the individual interview. Housing Characteristics and Household Population • 19 Figure 2.1 Population pyramid 10 8 6 4 2 0 2 4 6 8 10 <5 5-9 10-14 15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59 60-64 65-69 70-74 75-79 80 + Percent Age Male Female LDHS 2013 2.5 HOUSEHOLD COMPOSITION Information on the composition of households, including the sex of the head of the household and the size of the household, is presented in Table 2.9. These characteristics are important because they are associated with the welfare of the household. Female-headed households are, for example, typically poorer than male- headed households. In larger households, economic resources are often more limited. Moreover, where the household size is large, crowding can lead to health problems. Table 2.9 shows that 65 percent of the households in Liberia are headed by men. This proportion is slightly lower than that found in the 2007 LDHS (69 percent). Households with one member or two members constitute 10 and 11 percent of all households, respectively. The four-person households account for the largest proportion (15 percent) of all households. The overall average household size of 5.0 is identical to that reported in the 2007 LDHS. Variation in household size by residence is small. The mean size of households in urban areas is 4.9, which compares with 5.0 in rural areas. Information was also collected on the living arrangements of all children under age 18 residing in households and on the survival status of their parents. These data can be used to assess the extent to which households face a need to care for orphaned or foster children. Orphans include children whose mother or father has died (single orphans) as well as children who have lost both parents (double orphans). In the case of foster children, both parents are alive but the children are living in a household where neither their natural mother nor their natural father resides. Overall, 37 percent of households in Liberia are caring for foster or orphaned children, or both. 20 • Housing Characteristics and Household Population Table 2.9 Household composition Percent distribution of households by sex of head of household and by household size; mean size of household, and percentage of households with orphans and foster children under age 18, according to residence, Liberia 2013 Characteristic Residence Total Urban Rural Household headship Male 61.5 69.2 64.8 Female 38.5 30.8 35.2 Total 100.0 100.0 100.0 Number of usual members 0 0.0 0.1 0.0 1 11.5 8.2 10.0 2 10.7 10.7 10.7 3 14.0 12.4 13.3 4 14.7 16.0 15.3 5 12.9 15.2 13.9 6 11.8 11.9 11.9 7 8.1 9.0 8.5 8 5.4 6.0 5.6 9+ 10.9 10.5 10.7 Total 100.0 100.0 100.0 Mean size of households 4.9 5.0 5.0 Percentage of households with orphans and foster children under age 18 Foster children1 36.3 30.6 33.8 Double orphans 0.8 1.2 1.0 Single orphans2 11.6 10.1 10.9 Foster and/or orphan children 39.2 33.9 36.9 Number of households 5,289 4,044 9,333 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. 2 Includes children with one dead parent and an unknown survival status of the other parent. 2.6 BIRTH REGISTRATION The registration of births is the inscription of the facts of each 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, thus, basic rights and services (UNICEF, 2006; United Nations General Assembly, 2002). Information on the registration of births was collected in the household interview. Respondents were asked whether children under 5 residing in the household had a birth certificate. Table 2.10 shows the percentage of de jure children under 5 who had a birth certificate at the time of the survey. The proportion of de jure children who have a birth certificate is 25 percent. There is little variation by age or sex in the proportion of children registered. Children in urban households are more likely to have a birth certificate than children in rural households (29 percent and 20 percent, respectively). By county, the proportion of children with birth certificates was highest in Bomi (42 percent) and lowest in Grand Bassa (9 percent). The percentage of children with birth certificates correlated positively with wealth, ranging from 16 percent of children in the lowest wealth quintile to 31 percent of children in the highest wealth quintile. A comparison of the 2013 LDHS with the 2007 LDHS reveals that the percentage of children under 5 with birth certificates has increased (25 percent versus 4 percent). Housing Characteristics and Household Population • 21 It is noteworthy that in the process of collecting data on birth registration, interviewers were not instructed to observe the birth certificates of those children under 5 who were reported to have them. Nevertheless, some interviewers took it upon themselves to request to see the birth certificate for those children who were reported to have them, and there were anecdotal reports from such interviewers that some respondents confused birth certificates with health cards. These respondents indicated that certain children under 5 had birth certificates when in reality they had only health cards. If this problem was widespread, it is possible that the data presented in Table 2.10 do not portray an accurate picture of birth registration in Liberia. Table 2.10 Birth registration of children under 5 Percentage of de jure children under 5 who have a birth certificate, according to background characteristics, Liberia 2013 Background characteristic Percentage who have a birth certificate Number of children Age <2 24.0 2,885 2-4 25.0 4,458 Sex Male 24.8 3,801 Female 24.4 3,542 Residence Urban 29.2 3,666 Greater Monrovia 29.1 1,785 Other urban 29.2 1,881 Rural 20.1 3,677 Region North Western 29.7 813 South Central 22.6 2,990 South Eastern A 17.4 526 South Eastern B 14.3 548 North Central 29.2 2,466 County Bomi 41.9 210 Bong 20.6 894 Gbarpolu 31.2 177 Grand Bassa 9.2 407 Grand Cape Mount 23.1 427 Grand Gedeh 21.9 171 Grand Kru 11.0 220 Lofa 32.7 390 Margibi 11.7 558 Maryland 14.0 222 Montserrado 28.3 2,025 Nimba 34.6 1,182 River Cess 13.1 154 River Gee 21.9 106 Sinoe 17.0 201 Wealth quintile Lowest 16.2 1,776 Second 23.7 1,636 Middle 27.3 1,552 Fourth 28.8 1,354 Highest 31.1 1,025 Total 24.6 7,343 2.7 CHILDREN’S LIVING ARRANGEMENTS AND PARENTAL SURVIVAL Information was collected on the living arrangements and survival status of parents of all children under age 18 residing in the LDHS sample households to assess the potential burden on households of the need to provide for orphaned or foster children. These data were also used to assess the situation from the 22 • Housing Characteristics and Household Population perspective of the children themselves. Table 2.11 presents the proportion of children under age 18 who are not living with one or both parents, either because the parent(s) died or for other reasons. Over half of Liberian children under 18 are not living with both parents (56 percent). One-quarter of children are not living with either parent. Twenty-two percent of children are not living with either parent although both are alive. Seven percent of children under age 18 are orphaned, that is, one or both parents are dead. Table 2.11 Children's living arrangements and orphanhood Percent distribution of de jure children under age 18 by living arrangements and survival status of parents, the percentage of children not living with a biological parent, and the percentage of children with one or both parents dead, according to background characteristics, Liberia 2013 Background characteristic Living with both parents Living with mother but not with father Living with father but not with mother Not living with either parent Total Percent- age not living with a bio- logical parent Percent- age with one or both parents dead1 Number of children Father alive Father dead Mother alive Mother dead Both alive Only father alive Only mother alive Both dead Missing infor- mation on father/ mother Age 0-4 54.4 27.2 1.5 3.8 0.2 11.9 0.3 0.5 0.1 0.1 100.0 12.8 2.6 7,343 <2 58.7 34.6 1.0 1.0 0.0 4.2 0.1 0.1 0.0 0.2 100.0 4.4 1.2 2,885 2-4 51.5 22.4 1.9 5.6 0.2 16.9 0.5 0.7 0.2 0.1 100.0 18.2 3.5 4,458 5-9 45.2 18.4 2.6 7.7 0.4 22.4 0.8 1.7 0.5 0.2 100.0 25.4 6.1 7,580 10-14 36.1 15.5 4.8 9.2 0.8 28.2 1.3 3.0 0.8 0.3 100.0 33.3 10.7 6,011 15-17 28.3 15.0 6.1 10.3 1.2 29.9 2.1 4.7 0.9 1.5 100.0 37.6 15.1 2,796 Sex Male 44.6 20.4 3.4 8.1 0.6 19.4 1.0 1.9 0.4 0.3 100.0 22.6 7.2 12,146 Female 42.8 19.6 3.1 6.2 0.5 23.7 0.9 2.1 0.6 0.4 100.0 27.4 7.3 11,583 Residence Urban 38.9 21.5 3.3 7.2 0.5 24.6 0.9 2.3 0.4 0.4 100.0 28.2 7.5 13,109 Greater Monrovia 35.6 23.0 3.2 7.5 0.3 26.3 0.8 2.5 0.4 0.4 100.0 30.0 7.2 6,898 Other Urban 42.5 19.9 3.5 6.9 0.7 22.6 1.0 2.1 0.5 0.4 100.0 26.3 7.8 6,210 Rural 49.7 18.1 3.2 7.2 0.6 17.7 1.0 1.6 0.6 0.4 100.0 20.9 6.9 10,620 Region North Western 44.0 18.6 3.9 8.3 0.4 20.5 1.0 2.5 0.6 0.2 100.0 24.5 8.4 2,434 South Central 38.7 21.4 3.3 8.0 0.4 24.1 1.0 2.2 0.4 0.5 100.0 27.7 7.4 10,988 South Eastern A 52.1 16.0 2.2 8.2 0.3 17.6 0.7 1.8 0.4 0.6 100.0 20.4 5.5 1,531 South Eastern B 47.5 17.4 3.8 7.9 0.8 17.0 1.2 2.3 1.4 0.6 100.0 21.9 9.6 1,733 North Central 48.8 19.7 3.0 5.1 0.7 19.8 0.8 1.5 0.3 0.2 100.0 22.5 6.4 7,042 County Bomi 35.3 20.6 5.9 9.9 0.2 22.3 0.8 3.8 0.9 0.5 100.0 27.7 11.6 736 Bong 50.8 20.4 2.0 4.4 0.5 19.3 0.9 1.2 0.4 0.1 100.0 21.8 5.0 2,557 Gbarpolu 44.1 21.0 4.1 8.6 0.0 16.9 1.6 2.8 0.6 0.1 100.0 22.0 9.2 519 Grand Bassa 54.1 17.2 2.6 7.8 0.1 16.2 1.1 0.6 0.2 0.2 100.0 18.0 4.5 1,239 Grand Cape Mount 49.3 16.4 2.6 7.2 0.8 20.9 0.9 1.5 0.3 0.1 100.0 23.7 6.1 1,180 Grand Gedeh 47.0 18.0 2.9 7.0 0.3 20.3 0.5 2.8 0.5 0.9 100.0 24.0 7.4 501 Grand Kru 49.4 18.7 3.2 9.4 0.2 15.4 0.5 1.5 0.5 1.0 100.0 18.0 6.0 656 Lofa 44.0 20.1 3.6 7.3 0.5 19.7 1.3 1.9 1.0 0.5 100.0 23.9 8.3 1,266 Margibi 41.1 19.1 3.7 9.4 1.1 21.8 1.0 1.8 0.3 0.6 100.0 24.9 8.1 1,951 Maryland 44.7 16.0 4.2 6.8 1.4 19.3 1.9 2.9 2.6 0.2 100.0 26.7 13.0 783 Montserrado 35.6 22.7 3.4 7.7 0.3 25.9 1.0 2.6 0.5 0.5 100.0 30.0 7.7 7,798 Nimba 49.1 19.0 3.5 4.8 1.0 20.2 0.6 1.6 0.1 0.1 100.0 22.4 6.8 3,220 River Cess 56.0 16.4 1.7 8.3 0.1 15.0 0.7 1.1 0.4 0.4 100.0 17.2 3.9 419 River Gee 50.6 18.3 4.1 7.5 0.8 14.6 1.0 2.2 0.2 0.7 100.0 18.1 8.5 294 Sinoe 53.7 14.2 2.0 9.0 0.6 17.3 0.8 1.3 0.3 0.6 100.0 19.8 5.1 612 Wealth quintile Lowest 51.9 18.9 3.7 6.3 0.4 15.6 0.8 1.4 0.6 0.3 100.0 18.3 6.9 4,774 Second 49.7 18.6 3.2 6.3 0.8 17.9 1.1 1.5 0.5 0.4 100.0 20.9 7.1 4,822 Middle 44.0 20.1 3.7 6.3 0.6 21.7 0.9 1.9 0.4 0.4 100.0 25.0 7.7 4,970 Fourth 38.9 23.1 2.4 8.4 0.3 22.9 0.7 2.6 0.4 0.3 100.0 26.6 6.4 4,649 Highest 33.3 19.3 3.0 8.8 0.5 29.9 1.3 2.7 0.5 0.5 100.0 34.5 8.1 4,513 Total <15 45.8 20.7 2.9 6.8 0.4 20.4 0.8 1.6 0.4 0.2 100.0 23.2 6.2 20,934 Total <18 43.7 20.0 3.2 7.2 0.5 21.5 0.9 2.0 0.5 0.4 100.0 24.9 7.2 23,729 Note: Table is based on de jure members, i.e., usual residents. 1Includes children with father dead, mother dead, both dead, and one parent dead but missing information on survival status of the other parent. Housing Characteristics and Household Population • 23 The percentage of orphaned children increases rapidly with age, from 3 percent of children under 5 to 15 percent of children age 15-17. Urban children are about as likely to be orphaned as rural children (8 percent and 7 percent, respectively). River Cess (4 percent) had the lowest proportion of children orphaned, and Maryland had the highest (13 percent). The percentage of children with one or both parents dead varies little by wealth. In contrast, the percentage of children not living with a biological parent increases rapidly by wealth; whereas 18 percent of children living in households in the lowest wealth quintile are not living with a biological parent, 35 percent of children in households in the highest wealth quintile are not living with a biological parent. 2.8 EDUCATION OF THE HOUSEHOLD POPULATION The educational level of household members is among the most important characteristics of the household because it is associated with many factors that have a significant impact on health-seeking behavior, reproductive behavior, use of contraception, and the health of children. Liberia’s education system has been unstable for more than 20 years because of the civil crisis; however, a major restructuring of the infrastructure and expansion of the program is being undertaken by the government. At present, the government of Liberia has adopted a free primary education policy in all government schools, with a special program for female education. For the analysis presented below, age 6 is used as the age for entry into the primary level of schooling. Because of the war, however, many children did not start school when they reached school-going age. Officially, primary school consists of six years of education, and junior high school and senior high school each consist of three years. 2.8.1 Educational Attainment Tables 2.12.1 and 2.12.2 show the distribution of female and male household members age 6 and above by the highest level of schooling ever attended (even if they did not complete that level) and the median number of years of education completed according to age, residence, region, county, and wealth quintile. A comparison of the two tables reveals that there is a substantial gap in educational attainment between females and males. Although the majority of the household population age 6 and older has some education, 47 percent of females have never attended school; this compares with 33 percent of males. The median number of years of schooling for females is 0.0 years, which is 2.5 years less than that for males (2.5 years). Educational attainment also differs markedly among counties. For example, the largest proportion of the household population over age 6 that has never been to school is found in Bong (68 percent) and Grand Bassa (66 percent) for females, and Bong (50 percent), and Grand Cape Mount (48 percent) for males. The county with the lowest proportion of household members who have never attended school is Montserrado (30 percent for females and 21 percent for males). The percentage of males and females who have at least some secondary education rises with wealth quintile, peaking in the highest wealth quintile for both sexes. Comparison of data from the 2013 LDHS with the 2007 LDHS shows some improvement in educational attainment. For example, between 2007 and 2013 the proportion of those ages 15-19 that completed primary school increased from 31 to 41 percent for females and from 36 to 46 percent for males. Among those ages 20-24, the proportions that completed primary school increased from 40 to 53 percent among women and from 64 to 76 percent among men. 24 • Housing Characteristics and Household Population Table 2.12.1 Educational attainment of the female household population Percent distribution of the de facto female household population age six and over by highest level of schooling attended or completed and median years completed, according to background characteristics, Liberia 2013 Background characteristic No education Some primary Completed primary1 Some secondary Completed secondary2 More than secondary Total Number Median years completed Age 6-9 78.4 21.4 0.0 0.0 0.0 0.0 100.0 2,911 0.0 10-14 28.1 66.7 0.3 4.8 0.0 0.1 100.0 2,952 0.6 15-19 8.2 51.2 2.2 37.4 0.5 0.5 100.0 2,279 4.3 20-24 22.7 24.8 4.0 38.1 5.2 5.2 100.0 1,810 5.3 25-29 33.9 19.7 3.7 22.7 11.2 8.7 100.0 1,747 4.3 30-34 49.0 18.8 2.7 15.3 10.7 3.6 100.0 1,305 0.1 35-39 50.9 18.4 3.6 17.0 5.2 5.0 100.0 1,293 0.0 40-44 53.6 18.8 3.0 14.2 6.5 3.9 100.0 889 0.0 45-49 64.5 14.1 1.6 11.2 5.0 3.5 100.0 696 0.0 50-54 74.7 7.6 1.5 7.2 6.3 2.6 100.0 854 0.0 55-59 75.1 8.6 0.7 7.6 7.3 0.6 100.0 523 0.0 60-64 87.9 4.9 0.0 3.3 3.0 0.8 100.0 430 0.0 65+ 93.4 2.1 0.4 2.5 1.3 0.0 100.0 865 0.0 Residence Urban 36.1 30.9 2.0 21.0 5.9 4.0 100.0 10,935 1.9 Greater Monrovia 28.1 30.3 2.0 24.9 8.4 6.3 100.0 6,248 3.5 Other urban 46.7 31.7 2.0 15.8 2.7 1.1 100.0 4,687 0.0 Rural 63.0 27.1 1.5 7.1 0.9 0.2 100.0 7,626 0.0 Region North Western 60.8 27.6 1.6 8.7 1.0 0.1 100.0 1,702 0.0 South Central 37.6 29.4 1.8 20.2 6.3 4.7 100.0 9,338 1.6 South Eastern A 55.7 31.8 1.1 9.7 1.3 0.2 100.0 1,083 0.0 South Eastern B 50.3 33.3 2.1 11.7 1.7 0.6 100.0 1,211 0.0 North Central 57.2 28.5 1.9 10.8 1.4 0.1 100.0 5,225 0.0 County Bomi 56.6 24.2 2.7 14.6 1.8 0.0 100.0 535 0.0 Bong 68.1 23.4 0.9 6.6 0.7 0.3 100.0 1,883 0.0 Gbarpolu 59.6 32.2 1.0 5.6 1.0 0.6 100.0 370 0.0 Grand Bassa 66.2 22.5 1.2 8.1 1.5 0.5 100.0 932 0.0 Grand Cape Mount 64.1 27.7 1.2 6.2 0.4 0.0 100.0 797 0.0 Grand Gedeh 49.5 32.5 1.6 13.7 2.1 0.5 100.0 375 0.0 Grand Kru 56.4 32.1 2.0 7.7 1.1 0.1 100.0 461 0.0 Lofa 65.3 24.1 1.7 7.6 1.1 0.1 100.0 1,026 0.0 Margibi 53.4 29.5 1.5 10.5 2.9 2.1 100.0 1,503 0.0 Maryland 43.7 34.3 2.1 16.0 2.5 1.3 100.0 536 0.3 Montserrado 30.3 30.3 2.0 23.9 7.7 5.9 100.0 6,903 3.0 Nimba 44.7 34.5 2.9 15.6 2.2 0.1 100.0 2,316 0.3 River Cess 61.1 32.3 0.3 5.7 0.0 0.1 100.0 275 0.0 River Gee 53.7 33.1 2.3 9.4 1.3 0.1 100.0 215 0.0 Sinoe 57.7 31.0 1.1 8.7 1.3 0.0 100.0 433 0.0 Wealth quintile Lowest 70.8 23.6 1.0 4.2 0.3 0.0 100.0 3,412 0.0 Second 61.9 27.8 1.9 7.6 0.5 0.1 100.0 3,488 0.0 Middle 51.1 31.3 2.1 13.5 1.6 0.3 100.0 3,676 0.0 Fourth 36.3 33.0 2.1 21.4 5.3 1.9 100.0 3,878 1.6 Highest 21.5 30.2 2.0 27.0 10.3 9.0 100.0 4,108 4.7 Total 47.1 29.3 1.8 15.3 3.9 2.5 100.0 18,561 0.0 Note: Total includes 5 cases for which age is missing and 22 cases for which education level is missing. 1 Completed grade 6 at the primary level 2 Completed grade 12 at the secondary level Housing Characteristics and Household Population • 25 Table 2.12.2 Educational attainment of the male household population Percent distribution of the de facto male household population age six and over by highest level of schooling attended or completed and median years completed, according to background characteristics, Liberia 2013 Background characteristic No education Some primary Completed primary1 Some secondary Completed secondary2 More than secondary Total Number Median years completed Age 6-9 79.9 19.8 0.0 0.0 0.0 0.0 100.0 3,193 0.0 10-14 29.1 66.4 0.7 3.7 0.0 0.0 100.0 2,961 0.3 15-19 6.9 47.1 1.6 43.1 0.7 0.5 100.0 2,155 4.7 20-24 9.3 15.1 1.7 53.3 14.0 6.7 100.0 1,616 8.0 25-29 14.7 16.1 2.9 31.9 21.4 13.1 100.0 1,526 8.3 30-34 22.6 17.0 4.0 26.1 17.7 12.6 100.0 1,273 7.1 35-39 20.9 19.4 3.8 21.5 23.0 11.4 100.0 1,129 7.1 40-44 24.5 15.0 4.7 23.0 23.5 9.2 100.0 986 7.1 45-49 23.1 13.3 3.3 23.6 22.1 14.6 100.0 829 7.8 50-54 27.9 9.3 2.3 23.5 25.3 11.5 100.0 624 7.9 55-59 34.5 10.6 3.7 16.4 22.5 12.1 100.0 487 5.9 60-64 43.5 8.2 3.2 16.6 18.5 9.9 100.0 348 4.5 65+ 61.7 11.3 2.3 10.3 9.8 4.7 100.0 732 0.0 Residence Urban 24.9 26.6 1.9 23.6 13.6 9.3 100.0 10,160 4.7 Greater Monrovia 19.2 23.6 2.2 24.3 16.7 13.9 100.0 5,573 6.5 Other urban 31.7 30.3 1.6 22.7 9.9 3.8 100.0 4,587 2.5 Rural 43.0 30.0 2.1 17.5 6.3 0.9 100.0 7,701 0.3 Region North Western 43.4 29.5 1.8 17.5 6.6 1.1 100.0 1,721 0.4 South Central 25.9 25.2 2.0 22.6 13.7 10.4 100.0 8,593 4.7 South Eastern A 32.6 34.5 2.1 22.7 6.5 1.4 100.0 1,131 2.1 South Eastern B 30.5 32.4 2.2 23.5 9.4 1.7 100.0 1,296 2.5 North Central 41.1 29.9 1.9 18.4 7.5 1.3 100.0 5,120 0.6 County Bomi 38.7 29.8 1.7 19.8 8.3 1.6 100.0 527 1.4 Bong 49.9 25.6 1.8 14.9 6.6 1.1 100.0 1,894 0.0 Gbarpolu 39.9 33.1 1.2 18.0 5.6 2.0 100.0 385 0.8 Grand Bassa 46.3 27.0 1.7 16.6 6.1 2.0 100.0 979 0.0 Grand Cape Mount 48.1 27.6 2.2 15.7 5.9 0.3 100.0 809 0.0 Grand Gedeh 28.3 33.3 2.5 25.7 7.0 3.1 100.0 376 2.7 Grand Kru 33.2 31.6 1.2 21.7 11.1 0.3 100.0 495 2.0 Lofa 41.2 29.0 2.4 18.8 7.4 1.1 100.0 939 0.9 Margibi 32.6 29.2 1.2 21.3 10.0 5.5 100.0 1,405 2.2 Maryland 28.0 32.5 2.3 25.3 8.8 3.1 100.0 580 2.9 Montserrado 21.2 24.0 2.3 23.8 15.8 12.9 100.0 6,209 5.9 Nimba 33.7 33.9 1.7 21.0 8.2 1.5 100.0 2,287 1.7 River Cess 39.6 37.5 1.3 16.1 4.9 0.6 100.0 297 0.9 River Gee 31.0 33.8 4.0 23.0 6.9 1.3 100.0 222 2.7 Sinoe 31.6 33.6 2.2 24.5 7.2 0.7 100.0 458 2.2 Wealth quintile Lowest 50.1 29.4 2.3 14.5 3.3 0.3 100.0 3,437 0.0 Second 42.5 30.7 2.2 18.3 5.6 0.6 100.0 3,507 0.4 Middle 33.9 31.2 1.7 21.3 9.9 1.9 100.0 3,495 1.7 Fourth 24.7 25.7 1.4 24.6 16.4 7.2 100.0 3,664 4.9 Highest 14.3 23.8 2.4 25.6 16.4 17.5 100.0 3,759 7.6 Total 32.7 28.1 2.0 21.0 10.5 5.7 100.0 17,862 2.5 Note: Total includes 1 case for which age is missing and 29 cases for which education level is missing. 1 Completed grade 6 at the primary level 2 Completed grade 12 at the secondary level 2.8.2 School Attendance Ratios In Table 2.13, school attendance ratios for the 2012-13 academic year are presented by level of schooling and sex, residence, region, county, and wealth quintile. The net attendance ratio (NAR) is an 26 • Housing Characteristics and Household Population indicator of participation in schooling among children of official school age—age 6-11 for primary school and age 12-17 for secondary school—and the gross attendance ratio (GAR) indicates participation at each level of schooling among those of any age between 5 and 24. The GAR is nearly always higher than the NAR for the same level because the GAR includes participation by those who may be older or younger than the official age range for that level.2 Finally, the Gender Parity Index (GPI), which is the ratio of female to male attendance rates at the primary and secondary levels, indicates the magnitude of the gender gap in school attendance. A GPI less than one indicates that a smaller proportion of females than males attends school. Individuals are considered to be attending school currently if they attended formal academic school at any point during the given school year. The results in Table 2.13 show that 38 percent of children age 6 to 11 attend primary school and 23 percent of youth age 12 to 17 attend secondary school. There are only small differences in the NARs for males and females at either the primary or secondary level. At both levels, however, the NAR in urban areas is much higher than in rural areas (48 percent and 26 percent, respectively, at the primary school level and 31 percent and 9 percent, respectively, at the secondary school level). By county, large differences in NAR are also observed at both primary and secondary school levels. For example, at the primary level, Montserrado has the highest NAR (54 percent) and Bong has the lowest (19 percent). At the secondary level, Montserrado again has the highest NAR (37 percent), but River Cess and Grand Kru have the lowest (4 percent each). School attendance as measured by the NAR is higher among children of wealthy households than children of poorer households at both the primary and secondary levels. For example, 21 percent of children age 6 to 11 in the lowest wealth quintile attend primary school, compared with 61 percent in the highest wealth quintile. The primary school level GAR is 82 percent. This figure exceeds the primary school NAR (38 percent) by 44 percentage points, indicating that a large number of children outside the official school age population are attending primary school. At the secondary level, the GAR (49 percent) is somewhat closer to the NAR (23 percent), indicating that fewer youth outside of the official school age population are attending secondary school than is the case for primary school. The GPIs for both the NAR and GAR are just over 1 at the primary school levels, but are only 0.88 and 0.78, respectively, at the secondary school level. This means that there is gender parity in primary school but gender disparity in favor of males at the secondary school level. This disparity is especially pronounced in rural areas. The GPI associated with the NAR for secondary school for rural areas is 0.67 compared with 0.84 in urban areas; the GPI associated with the GAR for secondary school is 0.65 and 0.74 in rural areas and urban areas, respectively. Large differences in GPI are also observed by county. Age-specific attendance rates (ASARs) for the population age 5 to 24—i.e., the percentage of a given age cohort that attends school, regardless of the level attended (primary, secondary, or higher)—are shown in Figure 2.2. From age 5 through 12, trends are similar for males and females. Attendance rates peak at 83 percent for girls age 14 and at 88 percent for boys age 15. Whereas the percentage of girls in school is modestly higher than boys at ages 13 and 14, from ages 15 upward, the percentage of boys in school exceeds girls at every age. 2 Students who are overage for a given level of schooling may have started school overage, may have repeated one or more grades, or may have dropped out of school and later returned. Housing Characteristics and Household Population • 27 Table 2.13 School attendance ratios Net attendance ratios (NAR) and gross attendance ratios (GAR) for the de facto household population by sex and level of schooling; and the Gender Parity Index (GPI), according to background characteristics, Liberia 2013 Background characteristic Net attendance ratio1 Gross attendance ratio2 Male Female Total Gender Parity Index3 Male Female Total Gender Parity Index3 PRIMARY SCHOOL Residence Urban 46.9 48.6 47.8 1.04 93.5 97.5 95.6 1.04 Greater Monrovia 56.4 57.6 57.0 1.02 98.6 106.9 103.2 1.08 Other urban 37.9 37.3 37.6 0.98 88.7 85.4 87.1 0.96 Rural 26.0 26.8 26.4 1.03 67.2 63.5 65.5 0.94 Region North Western 29.0 31.8 30.3 1.10 66.7 65.3 66.0 0.98 South Central 46.0 47.4 46.7 1.03 89.8 93.3 91.7 1.04 South Eastern A 34.5 32.1 33.3 0.93 83.8 71.1 77.5 0.85 South Eastern B 36.2 35.6 35.9 0.98 85.6 92.0 88.4 1.07 North Central 28.8 29.5 29.1 1.02 73.0 71.0 72.1 0.97 County Bomi 32.7 30.0 31.4 0.92 73.9 61.6 68.0 0.83 Bong 17.0 22.2 19.3 1.30 52.3 52.6 52.4 1.01 Gbarpolu 27.3 25.2 26.3 0.92 70.5 71.4 70.9 1.01 Grand Bassa 24.7 22.7 23.8 0.92 62.6 55.7 59.5 0.89 Grand Cape Mount 27.3 36.1 31.3 1.32 60.4 65.2 62.6 1.08 Grand Gedeh 46.3 34.5 40.4 0.74 97.4 81.9 89.7 0.84 Grand Kru 29.4 32.8 30.8 1.12 81.8 90.7 85.6 1.11 Lofa 38.6 33.6 36.2 0.87 91.4 77.6 84.8 0.85 Margibi 35.8 33.7 34.6 0.94 86.8 75.8 80.6 0.87 Maryland 41.5 36.9 39.5 0.89 87.8 98.2 92.3 1.12 Montserrado 52.6 54.4 53.5 1.03 95.7 103.0 99.6 1.08 Nimba 34.8 33.8 34.4 0.97 83.3 83.7 83.5 1.00 River Cess 23.7 25.1 24.4 1.06 72.2 56.2 64.7 0.78 River Gee 37.8 38.0 37.9 1.00 89.0 77.7 83.7 0.87 Sinoe 32.7 34.4 33.6 1.05 81.2 71.6 76.4 0.88 Wealth quintile Lowest 20.8 21.1 21.0 1.01 60.0 50.9 55.8 0.85 Second 27.1 27.0 27.1 0.99 67.4 66.8 67.2 0.99 Middle 36.3 32.5 34.5 0.90 83.6 76.8 80.3 0.92 Fourth 47.8 50.5 49.2 1.06 96.5 93.5 94.9 0.97 Highest 58.9 62.4 60.7 1.06 104.7 122.0 113.9 1.16 Total 37.2 39.5 38.3 1.06 81.2 83.2 82.2 1.02 Continued… 28 • Housing Characteristics and Household Population Table 2.13 School attendance ratios—Continued Background characteristic Net attendance ratio1 Gross attendance ratio2 Male Female Total Gender Parity Index3 Male Female Total Gender Parity Index3 SECONDARY SCHOOL Residence Urban 33.5 28.2 30.7 0.84 73.7 54.6 63.5 0.74 Greater Monrovia 44.4 35.4 39.2 0.80 90.3 63.9 75.3 0.71 Other urban 20.7 16.2 18.6 0.78 54.1 38.9 46.8 0.72 Rural 10.3 6.9 8.8 0.67 26.5 17.2 22.3 0.65 Region North Western 17.7 12.9 15.5 0.73 34.4 27.4 31.2 0.80 South Central 35.0 29.3 31.9 0.84 73.5 54.1 63.0 0.74 South Eastern A 10.2 8.5 9.4 0.83 31.0 21.4 26.8 0.69 South Eastern B 16.0 8.5 12.5 0.53 46.0 25.9 36.5 0.56 North Central 12.0 10.1 11.1 0.84 35.2 27.0 31.4 0.77 County Bomi 28.4 25.5 27.1 0.90 49.4 55.1 51.9 1.12 Bong 11.6 9.0 10.5 0.77 27.3 16.6 22.7 0.61 Gbarpolu 12.1 5.3 8.8 0.43 31.4 9.1 20.4 0.29 Grand Bassa 14.3 12.4 13.4 0.86 32.2 25.1 29.0 0.78 Grand Cape Mount 12.0 7.1 9.8 0.60 24.0 15.6 20.2 0.65 Grand Gedeh 14.5 8.4 11.9 0.58 44.0 32.8 39.1 0.74 Grand Kru 5.5 2.8 4.3 0.51 29.5 15.1 23.3 0.51 Lofa 18.2 15.2 16.8 0.84 50.7 27.2 39.5 0.54 Margibi 19.6 13.9 16.7 0.71 54.6 27.4 40.4 0.50 Maryland 26.2 12.8 19.5 0.49 64.7 35.9 50.3 0.56 Montserrado 41.1 33.6 36.9 0.82 83.1 61.7 71.2 0.74 Nimba 9.6 8.5 9.1 0.88 34.8 34.1 34.4 0.98 River Cess 3.4 5.3 4.2 1.56 12.4 11.3 11.9 0.92 River Gee 7.2 3.7 5.6 0.52 22.8 9.0 16.4 0.39 Sinoe 11.2 10.4 10.8 0.93 32.7 18.3 26.1 0.56 Wealth quintile Lowest 5.3 4.5 5.0 0.86 16.8 9.5 13.6 0.57 Second 10.8 6.0 8.6 0.56 30.4 16.1 23.9 0.53 Middle 15.9 11.8 13.9 0.74 44.5 29.5 37.1 0.66 Fourth 26.7 24.8 25.7 0.93 70.1 60.9 65.4 0.87 Highest 51.9 38.5 44.2 0.74 94.3 63.2 76.6 0.67 Total 24.3 21.4 22.8 0.88 55.0 42.7 48.7 0.78 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 overage and underage students at a given level of schooling, the GAR can exceed 100 percent. 3 The Gender Parity Index for primary school is the ratio of the primary school NAR(GAR) for females to the NAR(GAR) for males. The Gender Parity Index for secondary school is the ratio of the secondary school NAR(GAR) for females to the NAR(GAR) for males. Housing Characteristics and Household Population • 29 Figure 2.2 Age-specific attendance rates of the de-facto population 5 to 24 years 0 10 20 30 40 50 60 70 80 90 100 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 Percent Age (years) Male Female LDHS 2013 2.9 UTILIZATION OF HEALTH SERVICES AND OUT-OF-POCKET EXPENDITURES FOR HEALTH CARE The 2013 LDHS collected data on the utilization of health services by household members. Information on outpatient visits by each household member to a health care facility, provider, pharmacy, or traditional healer in the four weeks preceding the interview and information on inpatient admissions in the 6 months preceding the interview was collected. The survey also collected out-of-pocket expenditures for visits and admissions during those reference periods. For inpatient admissions, expenditures were collected for all household members who had had an admission in the reference time period. For outpatient visits, expenditures were collected for a single, randomly selected household member who paid money the last time they received care; findings were then extrapolated to other members of the household. Utilization of health services was assessed in the Household Questionnaire, and questions were asked of all households in the sample. An analysis was carried out to estimate the number of annual outpatient visits (per capita) and inpatient admissions (per 1,000 population), with separate data for women and men. Table 2.14 shows that in Liberia the number of annual outpatient visits in 2013 is 2.0 visits per capita for women and 1.8 visits per capita for men. Among women, the number of visits is highest among children under 5 (5.0 visits) and among the elderly age 65 and older (2.4 visits). Among men, the number of outpatient visits is highest for children under 5 (4.8 annual visits). In both populations, the number of visits is higher in Greater Monrovia than other urban areas or in rural areas. 30 • Housing Characteristics and Household Population Table 2.14 Annual outpatient visits and inpatient admissions Average number of annual outpatient visits and inpatient admissions to health facilities for women and men by background characteristics, Liberia 2013 Background characteristic Women Men Outpatient visits (per capita) Inpatient admissions (per 1,000 population) Total population Outpatient visits (per capita) Inpatient admissions (per 1,000 population) Total population Age <5 5.0 245 3,760 4.8 236 3,488 5-14 1.6 85 6,850 1.9 98 6,539 15-24 1.6 80 3,772 1.1 55 4,090 25-34 1.4 109 2,799 0.6 18 3,052 35-44 0.8 49 2,115 0.3 20 2,182 45-54 0.6 51 1,454 0.6 22 1,550 55-64 0.8 32 836 1.3 70 954 65+ 2.4 62 732 1.6 122 865 Residence Urban 2.1 110 12,395 1.8 90 13,042 Greater Monrovia 2.6 99 6,666 2.2 94 7,294 Other urban 1.5 123 5,729 1.5 85 5,749 Rural 1.9 100 9,922 1.6 85 9,683 Region North Western 1.7 77 2,213 1.4 75 2,176 South Central 2.1 102 10,434 2.0 95 11,053 South Eastern A 2.5 119 1,433 2.1 102 1,387 South Eastern B 2.5 142 1,623 1.6 116 1,520 North Central 1.7 109 6,614 1.4 71 6,589 County Bomi 1.6 84 660 1.5 86 650 Bong 2.0 119 2,445 1.2 79 2,393 Gbarpolu 2.9 121 488 3.3 98 475 Grand Bassa 1.5 102 1,209 1.6 115 1,171 Grand Cape Mount 1.1 53 1,064 0.5 57 1,051 Grand Gedeh 2.8 118 467 2.3 127 476 Grand Kru 3.9 174 632 2.4 176 575 Lofa 1.1 87 1,189 1.4 73 1,237 Margibi 1.2 110 1,764 1.6 86 1,803 Maryland 1.5 114 706 1.2 85 668 Montserrado 2.4 100 7,461 2.2 94 8,080 Nimba 1.8 110 2,980 1.6 64 2,958 River Cess 2.4 74 392 1.3 72 359 River Gee 2.1 144 286 1.2 65 277 Sinoe 2.3 150 574 2.4 100 552 Wealth quintile Lowest 2.2 89 4,509 1.7 82 4,400 Second 1.8 113 4,514 1.5 82 4,409 Middle 1.8 113 4,387 1.6 89 4,575 Fourth 2.0 107 4,492 1.8 82 4,623 Highest 2.3 107 4,416 2.1 102 4,717 Total 2.0 106 22,317 1.8 88 22,725 Note: Total includes 6 cases for which age is unknown or missing. On average, the annual number of inpatient admissions is 106 admissions (per 1,000 population) for women and 88 admissions (per 1,000 population) for men. Among women, the number of annual admissions peaks among two age groups: those under 5 and those age 25-34 with 245 admissions and 109 admissions, respectively, per 1,000 population. For men, the number of annual admissions is highest among the youngest and oldest age groups: those under 5 have 236 admissions per 1,000 population and those over age 65 have 122 admissions per 1,000 population. Small differences in annual outpatient and inpatient visits are observed by region, county, and wealth quintile. Housing Characteristics and Household Population • 31 Table 2.15 indicates that the total annual out-of-pocket expenditure for the female population is LD$2,227 per capita; that includes LD$2,003 in outpatient expenditure and LD$225 in inpatient expenditure. For the male population, the total annual out-of-pocket expenditure is LD$1,891 per capita; that includes LD$1,719 in outpatient expenditure and LD$172 in inpatient expenditure. Table 2.15 Annual per capita expenditure (in Liberian dollars) on outpatient visits and inpatient admissions Average annual per capita expenditure for outpatient visits and inpatient admissions for women and men, by background characteristics, Liberia 2013 Background characteristic Women Men Per capita expenditure for outpatient Per capita expenditure for inpatient Total per capita expenditure Total population Per capita expenditure for outpatient Per capita expenditure for inpatient Total per capita expenditure Total population Age <5 4,735 403 5,138 3,760 5,195 358 5,552 3,488 5-14 2,054 169 2,223 6,850 1,707 228 1,935 6,539 15-24 1,438 148 1,586 3,772 842 133 975 4,090 25-34 1,344 456 1,800 2,799 648 45 693 3,052 35-44 683 80 763 2,115 273 38 311 2,182 45-54 600 111 711 1,454 658 36 694 1,550 55-64 461 17 478 836 1,836 80 1,916 954 65+ 1,279 221 1,500 732 1,143 314 1,457 865 Residence Urban 2,081 268 2,349 12,395 1,891 194 2,085 13,042 Greater Monrovia 3,085 239 3,324 6,666 2,191 246 2,437 7,294 Other urban 913 300 1,213 5,729 1,510 128 1,638 5,749 Rural 1,905 171 2,076 9,922 1,487 142 1,629 9,683 Region North Western 1,211 73 1,284 2,213 850 68 918 2,176 South Central 2,307 237 2,544 10,434 2,139 226 2,364 11,053 South Eastern A 1,764 173 1,936 1,433 1,786 133 1,919 1,387 South Eastern B 3,949 154 4,103 1,623 1,580 143 1,723 1,520 North Central 1,361 285 1,646 6,614 1,319 131 1,450 6,589 County Bomi 828 106 934 660 631 60 691 650 Bong 1,787 252 2,039 2,445 858 119 977 2,393 Gbarpolu 2,023 64 2,086 488 2,176 95 2,271 475 Grand Bassa 1,024 138 1,161 1,209 1,044 169 1,212 1,171 Grand Cape Mount 1,077 57 1,134 1,064 387 61 448 1,051 Grand Gedeh 2,366 94 2,460 467 2,209 159 2,367 476 Grand Kru 8,335 260 8,595 632 2,622 239 2,862 575 Lofa 900 100 999 1,189 1,362 127 1,489 1,237 Margibi 706 313 1,019 1,764 2,745 157 2,902 1,803 Maryland 1,032 71 1,103 706 1,116 88 1,204 668 Montserrado 2,894 235 3,129 7,461 2,162 249 2,411 8,080 Nimba 1,195 386 1,581 2,980 1,674 142 1,816 2,958 River Cess 892 178 1,070 392 628 121 749 359 River Gee 1,459 122 1,581 286 536 77 612 277 Sinoe 1,869 234 2,102 574 2,175 119 2,294 552 Wealth quintile Lowest 2,309 166 2,474 4,509 1,134 124 1,258 4,400 Second 1,294 229 1,522 4,514 1,262 126 1,387 4,409 Middle 1,404 159 1,563 4,387 1,221 153 1,375 4,575 Fourth 2,098 238 2,336 4,492 2,634 153 2,787 4,623 Highest 2,913 333 3,246 4,416 2,276 297 2,573 4,717 Total 2,003 225 2,227 22,317 1,719 172 1,891 22,725 Note: Total includes 6 cases for which age is unknown or missing. In the female population, annual expenditure is highest among children under 5 at LD$5,138. Annual expenditure decreases with age reaching a low of LD$478 among women age 55-64 before increasing to LD$1,500 among women over age 65. In the male population, annual expenditure is also highest among children under 5 at LD$5,552. Annual expenditure decreases with age reaching a low of LD$311among those in the 35-44 age group before increasing to LD$1,916 among those age 55-64 and LD$1,457 among those over age 65. 32 • Housing Characteristics and Household Population The total per capita out-of-pocket expenditure is higher in Greater Monrovia than in other urban areas or rural areas. Large differences are observed by region, county, and wealth quintile. Among women, the total annual out-of-pocket expenditure is highest for those in the lowest wealth quintile (LD$2,474) and highest wealth quintile (LD$3,246). Among men, total annual out-of-pocket expenditure is greatest for those in the fourth wealth quintile (LD$2,787). In addition to the information collected on outpatient and inpatient expenditures, all households were asked about any expenses on health related items they incurred during the four weeks preceding the interview (for example, purchases of vitamins, bandages, etc.). These data were annualized and then combined with the annual inpatient and outpatient expenditures for each household to produce an annual total health expenditure estimate. As shown in Table 2.16, the total annual health-related expenditure per household was LD$13,094. The total annual health-related expenditure was higher for households in Greater Monrovia (LD$15,750) than either other urban areas (LD$10,739) or rural areas (LD$12,382). Sizeable differences are also observed by region, county, and wealth quintile. Table 2.16 Annual total health expenditures (in Liberian dollars) per household Annual total expenditures on any health-related items for members of the household, by background characteristics, Liberia 2013 Background characteristic Total health-related expenditures Total households Residence Urban 13,638 5,289 Greater Monrovia 15,750 3,060 Other urban 10,739 2,229 Rural 12,382 4,044 Region North Western 8,705 909 South Central 14,099 4,645 South Eastern A 12,710 573 South Eastern B 20,387 571 North Central 11,337 2,634 County Bomi 6,753 280 Bong 9,765 1,118 Gbarpolu 14,361 212 Grand Bassa 7,151 588 Grand Cape Mount 7,140 417 Grand Gedeh 15,158 196 Grand Kru 39,818 206 Lofa 7,895 498 Margibi 13,693 694 Maryland 10,311 249 Montserrado 15,398 3,363 Nimba 14,750 1,018 River Cess 6,080 152 River Gee 7,546 116 Sinoe 15,061 225 Wealth quintile Lowest 11,672 2,008 Second 11,032 1,785 Middle 10,718 1,738 Fourth 14,208 2,024 Highest 17,826 1,777 Total 13,094 9,333 Characteristics of Respondents • 33 CHARACTERISTICS OF RESPONDENTS 3 his chapter presents information on demographic and socioeconomic characteristics of the survey respondents such as age, education, place of residence, marital status, employment, and wealth status. This information is useful for understanding the factors that affect use of reproductive health services, contraceptive use, and other health behaviors, as they provide a context for the interpretation of demographic and health indices. 3.1 CHARACTERISTICS OF SURVEY RESPONDENTS Background characteristics of the 9,239 women and 4,118 men age 15-49 interviewed in the 2013 LDHS are presented in Table 3.1. The distribution of respondents according to age shows a similar pattern for men and women. The proportion of respondents in each age group declines with increasing age for both sexes. Forty percent of women and 39 percent of men are in the 15-24 age groups, and 30 percent of both sexes are in the 25-34 age group. T Key Findings • A total of 9,239 women and 4,118 men age 15-49 were interviewed as part of the 2013 LDHS. • Thirty-three percent of women and 13 percent of men age 15-49 have no education. • Thirty-six percent of women and 58 percent of men have at least some secondary school education. • Literacy rates are low in Liberia: 48 percent of women and 71 percent of men are literate. • Only 6 percent of women and 13 percent of men access three media (read a newspaper, watch television, and listen to the radio) at least once a week. • Fifty-three percent of women and 74 percent of men age 15-49 are currently employed. • Among women who were employed in the past 12 months, 49 percent worked in sales and services and 42 percent in agriculture. Among men who were employed in the past 12 months, 40 percent worked in agriculture, 15 percent in unskilled manual labor, 14 percent in skilled manual labor, 14 percent in sales and services, and 10 percent in professional, technical, or managerial occupations. • Ninety-six percent of women and 93 percent of men age 15-49 lack health Insurance coverage. • Ten percent of men report that they smoke cigarettes, while less than 1 percent of women report using any form of tobacco. • Twenty-seven percent of women and 50 percent of men drank alcohol in the month before the survey. 34 • Characteristics of Respondents Table 3.1 Background characteristics of respondents Percent distribution of women and men age 15-49, by selected background characteristics, Liberia 2013 Background characteristic Women Men Weighted percent Weighted number Unweighted number Weighted percent Weighted number Unweighted number Age 15-19 22.5 2,080 1,915 21.6 890 847 20-24 17.8 1,642 1,584 16.9 696 645 25-29 17.4 1,611 1,585 16.3 673 640 30-34 13.0 1,199 1,244 14.0 575 603 35-39 12.8 1,179 1,203 11.4 469 544 40-44 8.8 812 901 11.7 482 490 45-49 7.7 716 807 8.1 332 349 Religion Christian 86.0 7,945 7,851 82.3 3,387 3,359 Muslim 10.8 1,001 1,095 12.9 529 545 Traditional religion 0.5 42 36 1.3 54 71 No religion 2.5 227 238 3.2 130 127 Other 0.0 1 1 0.0 0 0 Missing 0.3 23 18 0.4 16 15 Marital status Never married 31.0 2,867 2,405 42.5 1,749 1,591 Married 27.9 2,579 3,062 30.2 1,245 1,428 Living together 30.4 2,806 2,813 23.6 973 934 Divorced/separated 7.9 734 719 3.1 126 148 Widowed 2.7 253 240 0.6 25 17 Residence Urban 61.0 5,633 3,723 58.6 2,413 1,591 Greater Monrovia 36.4 3,361 1,154 34.8 1,433 463 Other urban 24.6 2,272 2,569 23.8 980 1,128 Rural 39.0 3,606 5,516 41.4 1,705 2,527 Region North Western 9.1 837 1,553 8.9 367 667 South Central 52.5 4,854 2,759 52.2 2,149 1,193 South Eastern A 5.2 483 1,367 6.2 254 697 South Eastern B 6.2 577 1,432 7.0 288 663 North Central 26.9 2,488 2,128 25.7 1,060 898 County Bomi 2.6 244 456 2.4 97 163 Bong 9.7 894 630 9.5 389 271 Gbarpolu 2.0 182 482 2.3 94 240 Grand Bassa 4.7 434 505 4.9 204 227 Grand Cape Mount 4.5 412 615 4.3 176 264 Grand Gedeh 1.8 167 448 2.0 82 214 Grand Kru 2.3 217 450 2.7 110 227 Lofa 4.8 447 629 5.3 219 294 Margibi 8.1 744 720 8.8 364 338 Maryland 2.8 257 559 3.0 123 251 Montserrado 39.8 3,675 1,534 38.4 1,582 628 Nimba 12.4 1,147 869 11.0 451 333 River Cess 1.5 135 459 1.6 64 214 River Gee 1.1 103 423 1.3 55 185 Sinoe 2.0 182 460 2.6 108 269 Education No education 33.2 3,066 3,679 12.9 533 599 Primary 31.1 2,875 3,195 29.2 1,202 1,404 Secondary and higher 35.7 3,298 2,365 57.9 2,383 2,115 Wealth quintile Lowest 17.1 1,581 2,589 18.2 749 1,172 Second 17.6 1,624 2,279 18.3 753 1,049 Middle 19.3 1,779 1,998 17.7 728 803 Fourth 22.2 2,047 1,305 21.0 864 568 Highest 23.9 2,207 1,068 24.9 1,024 526 Total 100.0 9,239 9,239 100.0 4,118 4,118 Note: Education categories refer to the highest level of education attended, whether or not that level was completed. Characteristics of Respondents • 35 The overwhelming majority of the respondents (86 percent of women and 82 percent of men) are Christian. Eleven percent of women and 13 percent of men are Muslim, and one percent of women and men practice traditional religion. Three percent of women and men report no religious affiliation. Twenty-eight percent of women and 30 percent of men are married, while 30 percent of women and 24 percent of men are living together in informal unions. Male respondents are much more likely than female respondents to have never married (43 percent versus 31 percent). Three percent of female respondents and 1 percent of male respondents are widowed. Men are less likely to be divorced or separated than women (3 percent versus 8 percent). The majority of respondents live in urban areas (61 percent of female respondents and 59 percent of male respondents). By contrast, according to the 2007 LDHS, only 42 percent of female respondents and 40 percent of male respondents resided in urban areas. Thus, there has been an apparent shift in population from rural areas to urban areas between the 2007 and 2013 LDHS. This change likely reflects a true shift in residence between the two surveys, as well as differences in the sampling frames used in the 2007 LDHS and 2013 LDHS (see Section 1.4.1 of Chapter 1). The largest proportions of both female and male respondents live in the South Central region (composed of Montserrado, Margibi, and Grand Bassa counties); the smallest proportions live in South Eastern A region (River Cess, Sinoe, and Grand Gedeh). In agreement with the regional distribution of respondents, by county, the largest proportion of respondents lives in Montserrado (40 percent of female respondents and 38 percent of male respondents), while the smallest proportion of respondents lives in River Gee (1 percent of both female and male respondents). Education influences an individual’s attitude and outlook on life. Generally, educational attainment in Liberia is low; only 36 percent of women and 58 percent of men have attended at least some secondary school. Thirty-one percent of women and 29 percent of men have attended only primary school. Thirty-three percent of women and 13 percent of men have no education. 3.2 EDUCATIONAL ATTAINMENT BY BACKGROUND CHARACTERISTICS Tables 3.2.1 and 3.2.2 present an overview of female and male respondents’ educational attainment, according to background demographic characteristics. Overall, the results show a low level of education in Liberia among both female and male respondents. Nevertheless, men have a huge advantage in average educational attainment, having completed a median of 6.5 years of schooling compared with 3.4 years among women. The difference in median years of schooling is partially explained by the huge differential observed in the total proportion of females with no education compared with males (33 percent and 13 percent, respectively). The proportions of women who have completed primary or secondary school, or who have attained schooling beyond secondary school, lags behind men. For example, only 39 percent of women have completed primary school compared with 62 percent of men; likewise, 10 percent of women have completed secondary school compared with 23 percent of men. Rural respondents generally have attained less education than their urban counterparts. For example, 50 percent of rural women have no education compared with 23 percent of urban women. Among men, 19 percent of rural men have no education compared with 9 percent of rural men. Of the 15 counties in Liberia, attainment of more than secondary education is concentrated in two counties: Montserrado, where Monrovia, the nation’s capital, is located, and Margibi, just to the east of Montserrado. In Montserrado, 10 percent of women and 20 percent of men have attained more than a 36 • Characteristics of Respondents secondary school education. In Margibi, 9 percent of men have more than secondary education; the proportion of women in Margibi with more than secondary education, however, is only 3 percent. Table 3.2.1 Educational attainment: Women Percent distribution of women age 15-49 by highest level of schooling attended or completed, and median years completed, according to background characteristics, Liberia 2013 Background characteristic Highest level of schooling Total Median years completed Number of women No education Some primary Completed primary1 Some secondary Completed secondary2 More than secondary Age 15-24 13.3 39.9 4.2 37.0 3.0 2.7 100.0 4.7 3,722 15-19 6.9 51.6 3.9 36.3 0.7 0.6 100.0 4.4 2,080 20-24 21.4 25.0 4.6 37.9 5.9 5.3 100.0 5.4 1,642 25-29 32.4 20.4 4.0 23.2 11.2 8.9 100.0 4.5 1,611 30-34 47.0 20.5 2.6 15.7 10.5 3.7 100.0 0.3 1,199 35-39 50.8 18.7 2.5 17.5 5.4 5.1 100.0 0.0 1,179 40-44 53.5 20.1 3.2 14.7 5.0 3.4 100.0 0.0 812 45-49 63.1 16.1 1.4 10.9 4.9 3.6 100.0 0.0 716 Residence Urban 22.5 24.5 3.7 33.4 9.0 6.8 100.0 5.4 5,633 Greater Monrovia 17.2 19.5 3.1 37.5 12.5 10.2 100.0 6.8 3,361 Other urban 30.5 31.9 4.6 27.3 3.9 1.8 100.0 3.5 2,272 Rural 49.8 32.7 3.0 12.8 1.3 0.4 100.0 0.0 3,606 Region North Western 49.3 30.7 3.4 14.8 1.6 0.2 100.0 0.0 837 South Central 25.2 22.6 3.0 31.7 9.7 7.9 100.0 5.3 4,854 South Eastern A 40.7 36.2 2.8 17.6 2.0 0.6 100.0 1.2 483 South Eastern B 38.8 32.5 4.1 20.9 2.6 1.1 100.0 2.2 577 North Central 40.7 33.8 4.3 19.1 2.0 0.2 100.0 1.8 2,488 County Bomi 42.0 22.3 7.1 26.1 2.6 0.0 100.0 2.4 244 Bong 55.3 30.0 1.4 11.9 1.0 0.3 100.0 0.0 894 Gbarpolu 43.2 41.6 2.0 10.1 1.9 1.2 100.0 0.1 182 Grand Bassa 53.3 25.6 2.1 15.5 2.2 1.3 100.0 0.0 434 Grand Cape Mount 56.2 30.9 1.9 10.1 0.8 0.0 100.0 0.0 412 Grand Gedeh 33.3 33.0 3.5 25.7 2.9 1.6 100.0 3.1 167 Grand Kru 47.3 33.0 4.3 13.5 1.8 0.1 100.0 0.7 217 Lofa 56.5 23.4 4.2 14.2 1.6 0.2 100.0 0.0 447 Margibi 40.7 30.6 3.6 17.8 4.3 3.1 100.0 1.4 744 Maryland 30.7 31.1 3.9 28.5 3.4 2.4 100.0 3.6 257 Montserrado 18.7 20.6 3.0 36.4 11.6 9.6 100.0 6.5 3,675 Nimba 23.0 40.7 6.6 26.5 2.9 0.2 100.0 3.6 1,147 River Cess 47.9 41.0 1.3 9.5 0.2 0.2 100.0 0.0 135 River Gee 41.1 35.1 4.0 17.5 2.2 0.2 100.0 1.5 103 Sinoe 42.3 35.6 3.2 16.2 2.6 0.1 100.0 0.6 182 Wealth quintile Lowest 59.2 30.8 1.9 7.5 0.5 0.1 100.0 0.0 1,581 Second 47.6 34.0 3.8 13.4 0.8 0.2 100.0 0.0 1,624 Middle 34.5 34.1 4.5 24.2 2.4 0.4 100.0 2.6 1,779 Fourth 24.7 26.6 3.5 34.2 7.4 3.6 100.0 4.8 2,047 Highest 10.7 16.6 3.4 39.7 15.5 14.2 100.0 8.0 2,207 Total 33.2 27.7 3.4 25.4 6.0 4.3 100.0 3.4 9,239 1 Completed grade 6 at the primary level 2 Completed grade 12 at the secondary level Wealth status is associated with educational attainment. The proportion of women in the lowest wealth quintile with no education is over five times higher than those in the highest wealth quintile (59 percent and 11 percent, respectively), and the proportion of women who have attended more than secondary school varies from less than 1 percent in the lowest three wealth quintiles to 14 percent in the highest quintile. Similar patterns are observed for men. Characteristics of Respondents • 37 Table 3.2.2 Educational attainment: Men Percent distribution of men age 15-49 by highest level of schooling attended or completed, and median years completed, according to background characteristics, Liberia 2013 Background characteristic Highest level of schooling Total Median years completed Number of men No education Some primary Completed primary1 Some secondary Completed secondary2 More than secondary Age 15-24 5.4 33.3 3.5 48.5 5.5 3.8 100.0 6.1 1,587 15-19 4.8 46.8 4.0 43.2 1.0 0.2 100.0 4.9 890 20-24 6.2 16.0 3.0 55.2 11.2 8.4 100.0 8.1 696 25-29 12.6 17.4 3.2 29.2 22.9 14.7 100.0 8.4 673 30-34 21.1 24.8 2.5 24.4 16.4 10.9 100.0 5.8 575 35-39 20.3 23.2 4.4 22.6 15.2 14.2 100.0 6.1 469 40-44 17.3 22.0 5.5 27.5 18.3 9.3 100.0 6.8 482 45-49 18.9 13.1 4.5 24.6 24.1 14.7 100.0 8.5 332 Residence Urban 8.7 17.8 3.6 37.9 17.0 15.1 100.0 8.2 2,413 Greater Monrovia 7.1 11.4 3.3 38.2 18.4 21.6 100.0 9.1 1,433 Other urban 10.9 27.1 4.1 37.5 14.8 5.5 100.0 6.3 980 Rural 19.0 36.3 4.0 30.0 9.7 1.1 100.0 4.4 1,705 Region North Western 21.6 33.1 2.8 28.0 13.1 1.3 100.0 4.5 367 South Central 9.6 18.7 3.1 36.0 16.2 16.5 100.0 8.0 2,149 South Eastern A 9.7 37.0 3.1 39.2 9.5 1.6 100.0 5.4 254 South Eastern B 8.8 28.8 4.5 42.3 14.1 1.5 100.0 6.3 288 North Central 18.7 32.8 5.3 31.1 10.7 1.4 100.0 4.8 1,060 County Bomi 15.0 25.9 5.3 35.6 16.5 1.7 100.0 6.2 97 Bong 24.3 33.2 4.4 25.8 10.6 1.7 100.0 3.7 389 Gbarpolu 17.1 42.1 1.5 24.8 12.3 2.1 100.0 4.0 94 Grand Bassa 20.4 37.0 2.9 29.1 9.3 1.3 100.0 3.8 204 Grand Cape Mount 27.7 32.2 2.2 25.5 11.6 0.7 100.0 4.2 176 Grand Gedeh 7.1 26.9 3.2 48.5 10.2 4.1 100.0 6.4 82 Grand Kru 6.1 28.1 4.3 42.0 18.4 1.1 100.0 6.6 110 Lofa 24.8 22.3 9.5 31.3 10.3 1.8 100.0 5.3 219 Margibi 10.5 32.5 2.7 32.1 13.6 8.5 100.0 5.8 364 Maryland 9.0 28.3 3.9 44.0 12.9 1.9 100.0 6.4 123 Montserrado 8.0 13.1 3.2 37.7 17.7 20.2 100.0 8.8 1,582 Nimba 10.8 37.6 4.1 35.5 10.9 1.0 100.0 5.1 451 River Cess 7.3 50.5 2.3 32.5 7.5 0.0 100.0 4.4 64 River Gee 13.8 31.5 6.6 39.0 8.0 1.1 100.0 5.5 55 Sinoe 13.1 36.6 3.6 36.0 10.2 0.6 100.0 5.1 108 Wealth quintile Lowest 25.8 38.5 4.3 26.1 4.8 0.5 100.0 3.1 749 Second 17.0 37.0 4.8 32.2 8.6 0.5 100.0 4.6 753 Middle 13.7 29.2 3.4 35.6 16.8 1.4 100.0 5.9 728 Fourth 8.8 18.0 3.0 38.9 19.8 11.5 100.0 8.0 864 Highest 3.5 11.1 3.5 38.5 17.6 25.9 100.0 9.8 1,024 Total 12.9 25.4 3.7 34.6 14.0 9.3 100.0 6.5 4,118 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. In the 2013 LDHS, the literacy status of respondents who had not attended school or had attended only primary school was determined by their ability to read all or part of a sentence. Those with secondary education or higher were assumed to be literate. 38 • Characteristics of Respondents Tables 3.3.1 and 3.3.2 show the percent distributions of women and men by level of schooling attended and level of literacy, along with the percentage of respondents who are literate, according to background characteristics. Literacy rates in Liberia are low; overall, 48 percent of women and 71 percent of men are literate. Among women, literacy correlates inversely with age; 69 percent of women age 15-19 are literate compared with only 23 percent of women age 45-49. For men, in contrast, a clear correlation between age and literacy is not observed. Rather, younger men age 15-29 (74-85 percent) and older men age 40-49 (67- 71 percent) have higher rates of literacy than men age 30-39 (60-61 percent). 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 2013 Background characteristic Secondary school or higher No schooling or primary school Total Percentage literate1 Number of women Can read a whole sentence Can read part of a sentence Cannot read at all No card with required language Blind/ visually impaired Age 15-24 42.6 7.6 14.0 35.5 0.2 0.0 100.0 64.2 3,722 15-19 37.6 12.0 19.0 31.2 0.2 0.0 100.0 68.5 2,080 20-24 49.0 2.1 7.7 41.0 0.1 0.0 100.0 58.9 1,642 25-29 43.2 1.0 5.7 49.5 0.3 0.0 100.0 49.9 1,611 30-34 29.9 0.8 5.7 63.5 0.0 0.0 100.0 36.4 1,199 35-39 28.0 2.0 3.9 66.1 0.0 0.0 100.0 33.8 1,179 40-44 23.1 1.4 4.0 71.3 0.0 0.0 100.0 28.6 812 45-49 19.4 0.3 2.9 77.1 0.1 0.1 100.0 22.5 716 Residence Urban 49.2 4.6 8.2 37.7 0.2 0.0 100.0 62.1 5,633 Greater Monrovia 60.2 5.3 8.4 25.8 0.2 0.0 100.0 73.9 3,361 Other urban 33.0 3.6 8.0 55.2 0.1 0.0 100.0 44.6 2,272 Rural 14.6 2.4 8.8 74.0 0.1 0.0 100.0 25.8 3,606 Region North Western 16.6 2.5 10.6 69.9 0.0 0.0 100.0 29.7 837 South Central 49.3 4.9 8.6 37.0 0.2 0.0 100.0 62.7 4,854 South Eastern A 20.3 2.1 9.9 67.1 0.5 0.0 100.0 32.3 483 South Eastern B 24.6 3.0 11.6 60.4 0.2 0.1 100.0 39.2 577 North Central 21.3 2.4 6.4 69.8 0.1 0.0 100.0 30.1 2,488 County Bomi 28.7 2.0 11.7 57.6 0.0 0.0 100.0 42.4 244 Bong 13.2 2.1 4.7 80.0 0.0 0.0 100.0 20.0 894 Gbarpolu 13.2 2.2 12.8 71.5 0.0 0.0 100.0 28.1 182 Grand Bassa 19.0 1.2 9.5 69.8 0.2 0.0 100.0 29.7 434 Grand Cape Mount 10.9 3.0 8.9 76.6 0.0 0.0 100.0 22.8 412 Grand Gedeh 30.2 2.2 12.0 54.4 1.0 0.0 100.0 44.5 167 Grand Kru 15.3 2.1 15.9 66.7 0.0 0.0 100.0 33.3 217 Lofa 15.9 0.5 9.1 74.5 0.0 0.0 100.0 25.5 447 Margibi 25.2 4.7 10.1 59.9 0.0 0.0 100.0 40.0 744 Maryland 34.4 3.7 8.7 52.4 0.5 0.3 100.0 46.8 257 Montserrado 57.7 5.4 8.2 28.5 0.2 0.0 100.0 71.3 3,675 Nimba 29.6 3.4 6.7 60.0 0.2 0.0 100.0 39.7 1,147 River Cess 9.9 2.0 11.6 76.4 0.0 0.0 100.0 23.6 135 River Gee 19.9 3.1 9.9 66.9 0.0 0.0 100.0 32.8 103 Sinoe 18.9 1.9 6.7 71.8 0.4 0.1 100.0 27.6 182 Wealth quintile Lowest 8.0 1.3 6.7 83.8 0.1 0.0 100.0 16.0 1,581 Second 14.5 1.9 8.6 74.7 0.2 0.0 100.0 24.9 1,624 Middle 27.0 3.7 10.0 59.1 0.2 0.0 100.0 40.7 1,779 Fourth 45.2 4.3 10.2 40.2 0.1 0.0 100.0 59.6 2,047 Highest 69.4 6.4 6.7 17.2 0.2 0.0 100.0 82.5 2,207 Total 35.7 3.7 8.4 51.8 0.1 0.0 100.0 47.9 9,239 Note: Total includes 10 cases for which information on literacy is missing. 1 Refers to women who attended secondary school or higher and women who can read a whole sentence or part of a sentence Characteristics of Respondents • 39 Women and men in urban areas have much higher literacy rates (62 percent and 81 percent, respectively) than their rural counterparts (26 percent and 58 percent, respectively). For women, Montserrado and Maryland have the highest literacy rates (71 percent and 47 percent). For men, Montserrado and Grand Kru have the highest literacy rates (84 percent and 77 percent, respectively). Bong has the lowest literacy rate for both women and men (20 percent and 53 percent). Literacy closely correlates with increasing wealth quintile for both women and men. 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 2013 Background characteristic Secondary school or higher No schooling or primary school Total Percentage literate1 Number of men Can read a whole sentence Can read part of a sentence Cannot read at all No card with required language Age 15-24 57.7 9.9 11.4 20.8 0.0 100.0 79.0 1,587 15-19 44.4 14.2 16.1 25.1 0.1 100.0 74.6 890 20-24 74.8 4.5 5.4 15.3 0.0 100.0 84.6 696 25-29 66.8 1.5 5.8 25.6 0.2 100.0 74.2 673 30-34 51.7 2.5 6.0 39.6 0.2 100.0 60.2 575 35-39 52.1 2.7 5.8 39.5 0.0 100.0 60.5 469 40-44 55.1 4.4 7.8 31.5 0.3 100.0 67.3 482 45-49 63.4 1.4 5.8 29.1 0.0 100.0 70.7 332 Residence Urban 70.0 5.4 5.4 18.8 0.1 100.0 80.9 2,413 Greater Monrovia 78.3 5.2 2.7 13.5 0.0 100.0 86.2 1,433 Other urban 57.9 5.8 9.4 26.6 0.3 100.0 73.1 980 Rural 40.7 5.2 12.1 41.7 0.1 100.0 58.1 1,705 Region North Western 42.4 6.7 11.5 38.6 0.3 100.0 60.6 367 South Central 68.7 5.6 5.5 19.9 0.1 100.0 79.8 2,149 South Eastern A 50.2 7.1 11.8 30.0 0.5 100.0 69.1 254 South Eastern B 57.8 3.5 12.7 25.6 0.2 100.0 74.1 288 North Central 43.2 4.4 10.6 41.9 0.0 100.0 58.1 1,060 County Bomi 53.8 2.8 12.9 28.8 1.1 100.0 69.5 97 Bong 38.1 4.8 10.5 46.6 0.0 100.0 53.4 389 Gbarpolu 39.3 4.7 11.7 44.0 0.0 100.0 55.8 94 Grand Bassa 39.7 6.8 10.9 42.1 0.5 100.0 57.4 204 Grand Cape Mount 37.8 9.9 10.5 41.0 0.0 100.0 58.3 176 Grand Gedeh 62.8 3.1 7.2 25.0 1.7 100.0 73.1 82 Grand Kru 61.5 2.4 13.4 22.5 0.0 100.0 77.3 110 Lofa 43.4 0.6 10.5 45.5 0.0 100.0 54.5 219 Margibi 54.2 6.5 12.2 27.0 0.0 100.0 73.0 364 Maryland 58.9 5.2 10.7 24.7 0.5 100.0 74.8 123 Montserrado 75.7 5.3 3.2 15.5 0.0 100.0 84.2 1,582 Nimba 47.4 5.8 10.7 36.1 0.0 100.0 63.9 451 River Cess 39.9 12.9 13.1 34.0 0.0 100.0 66.0 64 River Gee 48.1 2.1 15.9 34.0 0.0 100.0 66.0 55 Sinoe 46.8 6.6 14.6 31.4 0.0 100.0 68.0 108 Wealth quintile Lowest 31.4 4.9 11.1 52.3 0.2 100.0 47.4 749 Second 41.2 6.5 11.7 40.4 0.0 100.0 59.4 753 Middle 53.8 4.7 9.8 31.6 0.0 100.0 68.3 728 Fourth 70.2 6.6 6.0 16.9 0.2 100.0 82.8 864 Highest 82.0 4.2 4.2 9.0 0.1 100.0 90.4 1,024 Total 57.9 5.4 8.2 28.3 0.1 100.0 71.4 4,118 Note: Total includes 8 cases for which information on literacy is missing. 1 Refers to men who attended secondary school or higher and men who can read a whole sentence or part of a sentence 40 • Characteristics of Respondents 3.4 EXPOSURE TO MASS MEDIA The 2013 LDHS collected information on respondents’ exposure to common print and electronic media. Respondents were asked how often they read a newspaper, listened to the radio, or watched television. This information indicates the extent to which Liberians are regularly exposed to mass media, often used to convey messages on family planning, malaria, HIV/AIDS awareness, and other health topics. Tables 3.4.1 and 3.4.2 show the percentages of female and male respondents who were exposed to different types of mass media by age, residence, region, county, level of education, and wealth quintile. Nine percent of women and 30 percent of men read newspapers at least once a week, 19 percent of women and 24 percent of men watch television at least once a week, and 39 percent of women and 60 percent of men listen to the radio at least once a week. Overall, only 6 percent of women and 13 percent of men are exposed to all three media at least once per week. More than half of women (56 percent) and a third of men (33 percent) are not exposed to any of the three media on a regular basis. 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 2013 Background characteristic Reads a newspaper at least once a week Watches television at least once a week Listens to the radio at least once a week Accesses all three media at least once a week Accesses none of the three media at least once a week Number of women Age 15-19 10.2 24.3 39.6 6.3 52.7 2,080 20-24 11.1 20.8 40.7 6.4 53.7 1,642 25-29 11.7 20.9 41.5 7.8 52.9 1,611 30-34 8.6 16.8 39.8 5.9 56.6 1,199 35-39 5.4 17.0 40.2 3.5 55.5 1,179 40-44 6.7 11.7 35.4 3.2 62.7 812 45-49 5.5 10.9 33.8 3.1 63.8 716 Residence Urban 13.3 27.6 45.6 8.8 47.6 5,633 Greater Monrovia 17.7 39.7 52.1 13.0 39.5 3,361 Other urban 6.9 9.8 36.1 2.5 59.4 2,272 Rural 2.6 5.6 29.6 0.8 68.0 3,606 Region North Western 1.3 5.5 30.0 0.2 68.0 837 South Central 15.3 31.3 47.5 10.3 45.1 4,854 South Eastern A 2.7 8.0 29.7 0.7 67.1 483 South Eastern B 4.2 10.4 38.2 1.3 57.5 577 North Central 2.2 3.7 28.7 0.5 69.0 2,488 County Bomi 2.4 7.6 30.5 0.3 66.8 244 Bong 1.8 3.0 28.8 0.4 70.0 894 Gbarpolu 1.6 3.3 26.5 0.4 71.3 182 Grand Bassa 10.7 13.0 36.5 6.3 60.3 434 Grand Cape Mount 0.4 5.2 31.4 0.0 67.2 412 Grand Gedeh 4.0 7.5 29.9 1.0 66.7 167 Grand Kru 3.0 9.4 33.6 1.1 62.4 217 Lofa 4.1 6.7 20.2 1.3 76.3 447 Margibi 7.5 10.7 28.2 1.5 64.6 744 Maryland 5.2 8.5 40.6 1.4 56.5 257 Montserrado 17.4 37.7 52.8 12.5 39.3 3,675 Nimba 1.7 3.2 32.0 0.3 65.4 1,147 River Cess 0.7 1.6 30.1 0.0 69.0 135 River Gee 4.1 17.2 42.2 1.4 49.6 103 Sinoe 3.1 13.2 29.3 0.9 66.1 182 Education No education 0.0 7.9 27.2 0.0 70.2 3,066 Primary 3.0 14.0 33.3 1.5 61.7 2,875 Secondary and higher 22.9 33.8 56.0 14.6 36.5 3,298 Wealth quintile Lowest 1.2 3.1 21.6 0.3 76.9 1,581 Second 2.3 4.6 29.8 0.6 68.1 1,624 Middle 3.3 7.6 33.4 1.0 63.0 1,779 Fourth 10.7 20.3 45.1 6.5 50.4 2,047 Highest 23.1 49.1 58.7 16.3 29.7 2,207 Total 9.1 19.0 39.4 5.7 55.5 9,239 Characteristics of Respondents • 41 The proportions of respondents who are not exposed to any media on at least a weekly basis are highest among women age 45-49 and among men age 15-19 (64 percent and 41 percent, respectively). Urban residents are more likely to be exposed to all forms of mass media than rural residents. Overall, 68 percent of rural women and 47 percent of rural men reported having no exposure to any form of mass media at least once a week, compared with 48 percent of urban women and 24 percent of urban men. Montserrado residents generally are more likely to read newspapers, watch television, and listen to the radio than people living in other counties. Women in Lofa and men in Bong are most likely to report having no exposure to any of the three media (76 percent and 74 percent, respectively). 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 2013 Background characteristic Reads a newspaper at least once a week Watches television at least once a week Listens to the radio at least once a week Accesses all three media at least once a week Accesses none of the three media at least once a week Number of men Age 15-19 22.3 30.7 48.0 12.7 41.4 890 20-24 41.2 29.6 62.2 17.9 29.5 696 25-29 35.3 25.3 62.7 15.0 30.1 673 30-34 25.8 15.6 60.2 8.7 35.3 575 35-39 27.1 16.6 65.8 11.2 31.6 469 40-44 29.5 22.5 68.4 13.8 26.9 482 45-49 28.8 14.7 61.3 10.2 33.8 332 Residence Urban 41.8 35.3 67.5 20.3 23.5 2,413 Greater Monrovia 53.7 44.6 71.9 28.3 18.0 1,433 Other urban 24.3 21.9 61.2 8.8 31.5 980 Rural 13.4 7.1 49.3 2.9 47.1 1,705 Region North Western 21.5 9.0 61.7 4.0 34.8 367 South Central 41.3 34.9 68.0 20.7 23.7 2,149 South Eastern A 19.1 9.4 46.4 2.6 44.3 254 South Eastern B 20.0 20.2 62.2 9.1 32.8 288 North Central 15.4 10.3 45.8 4.7 49.6 1,060 County Bomi 30.0 4.0 50.1 2.2 44.0 97 Bong 5.8 2.4 20.7 0.0 74.0 389 Gbarpolu 12.4 0.9 50.6 0.0 48.6 94 Grand Bassa 10.5 9.3 53.4 1.3 41.8 204 Grand Cape Mount 21.7 16.1 74.1 7.2 22.3 176 Grand Gedeh 20.0 10.3 64.3 2.0 29.4 82 Grand Kru 36.5 30.4 61.1 19.0 31.9 110 Lofa 24.3 5.3 48.5 1.5 46.7 219 Margibi 21.3 19.6 62.6 8.4 32.6 364 Maryland 7.9 11.1 68.2 0.9 29.1 123 Montserrado 49.9 41.7 71.1 26.0 19.4 1,582 Nimba 19.4 19.5 66.0 10.2 29.9 451 River Cess 25.8 1.2 46.3 0.4 42.0 64 River Gee 14.1 20.1 50.9 7.7 43.1 55 Sinoe 14.5 13.6 32.9 4.4 56.9 108 Education No education 0.0 4.7 39.1 0.0 59.7 533 Primary 5.6 13.6 46.8 2.7 48.3 1,202 Secondary and higher 49.0 33.0 71.3 21.3 19.8 2,383 Wealth quintile Lowest 12.2 4.9 41.9 3.2 54.7 749 Second 13.9 6.7 49.3 1.9 46.2 753 Middle 19.5 13.3 58.6 6.5 37.9 728 Fourth 35.8 24.5 65.4 12.3 25.9 864 Highest 57.5 56.5 77.5 34.1 11.0 1,024 Total 30.0 23.7 60.0 13.1 33.3 4,118 42 • Characteristics of Respondents Not surprisingly, media exposure is related to education among both women and men. For example, 70 percent of women with no education report that they are not exposed to any media on at least a weekly basis, compared with 37 percent of women with at least some secondary education. Similarly, 60 percent of men who never attended school have no exposure to any media at least once a week, as compared with 20 percent of men with at least some secondary education. Media exposure among women and men also relates to wealth status. For example, 23 percent of women in the highest wealth quintile read a newspaper at least once a week, compared with 1 percent of women in the lowest wealth quintile. Among men, 58 percent in the highest wealth quintile and 12 percent in the lowest quintile read a newspaper at least once a week. Forty-nine percent of women and 57 percent of men in the highest wealth quintile watch television at least once a week, in contrast with 3 percent of women and 5 percent of men in the lowest wealth quintile. Fifty-nine percent of women and 78 percent of men in the highest wealth quintile listen to the radio at least once a week, compared with 22 percent of women and 42 percent of men in the lowest wealth quintile. 3.5 EMPLOYMENT STATUS The 2013 LDHS asked respondents several questions about their current employment status and continuity of employment in the 12 months prior to the survey. Figure 3.1 and Table 3.5.1 present the proportion of women who were currently employed (i.e., who were working in the seven days preceding the survey), the proportion who were not currently employed but had been employed at some time during the 12 months before the survey, and the proportion who had not been employed at any time during the 12-month period. Table 3.5.2 presents employment status data for men. Overall, 53 percent of women reported that they were currently employed. An additional 2 percent of women were not currently employed but had worked in the 12 months preceding the survey. Seventy-four percent of men were currently employed, and an additional 2 percent had worked in the year prior to the survey. Figure 3.1 Women’s employment status in the past 12 months Currently employed 53% Not currently employed, but worked in last 12 months 2% Did not work in last 12 months 44% LDHS 2013 Characteristics of Respondents • 43 Table 3.5.1 Employment status: Women Percent distribution of women age 15-49 by employment status, according to background characteristics, Liberia 2013 Background characteristic Employed in the 12 months preceding the survey Not employed in the 12 months preceding the survey Total Number of women Currently employed1 Not currently employed Age 15-19 25.2 1.1 73.8 100.0 2,080 20-24 42.9 2.3 54.7 100.0 1,642 25-29 57.8 2.8 39.4 100.0 1,611 30-34 64.7 2.5 32.8 100.0 1,199 35-39 71.4 3.0 25.6 100.0 1,179 40-44 75.8 2.4 21.8 100.0 812 45-49 74.4 3.0 22.6 100.0 716 Marital status Never married 29.9 1.3 68.8 100.0 2,867 Married or living together 63.3 2.5 34.2 100.0 5,386 Divorced/separated /widowed 67.0 4.0 29.0 100.0 987 Number of living children 0 27.5 1.6 71.0 100.0 2,185 1-2 53.3 2.0 44.7 100.0 3,294 3-4 66.4 3.5 30.1 100.0 2,084 5+ 70.7 2.3 27.0 100.0 1,676 Residence Urban 49.9 2.5 47.6 100.0 5,633 Greater Monrovia 48.9 2.9 48.2 100.0 3,361 Other urban 51.5 1.8 46.7 100.0 2,272 Rural 58.6 2.0 39.4 100.0 3,606 Region North Western 58.8 1.2 40.0 100.0 837 South Central 48.6 2.9 48.5 100.0 4,854 South Eastern A 46.5 2.2 51.3 100.0 483 South Eastern B 48.8 3.1 48.1 100.0 577 North Central 63.1 1.3 35.6 100.0 2,488 County Bomi 41.8 0.8 57.4 100.0 244 Bong 71.9 1.3 26.8 100.0 894 Gbarpolu 78.1 0.9 21.0 100.0 182 Grand Bassa 50.8 6.8 42.4 100.0 434 Grand Cape Mount 60.3 1.5 38.1 100.0 412 Grand Gedeh 48.2 0.7 51.2 100.0 167 Grand Kru 47.0 3.9 49.1 100.0 217 Lofa 53.6 2.6 43.8 100.0 447 Margibi 41.1 0.6 58.3 100.0 744 Maryland 46.6 2.7 50.7 100.0 257 Montserrado 49.8 2.9 47.3 100.0 3,675 Nimba 59.9 0.8 39.3 100.0 1,147 River Cess 52.9 2.4 44.7 100.0 135 River Gee 57.8 2.7 39.5 100.0 103 Sinoe 40.2 3.5 56.3 100.0 182 Education No education 64.9 2.9 32.2 100.0 3,066 Primary 49.6 1.4 49.0 100.0 2,875 Secondary and higher 45.8 2.5 51.7 100.0 3,298 Wealth quintile Lowest 63.1 2.4 34.5 100.0 1,581 Second 60.8 1.4 37.8 100.0 1,624 Middle 53.6 1.5 45.0 100.0 1,779 Fourth 47.9 4.1 48.0 100.0 2,047 Highest 45.6 1.9 52.5 100.0 2,207 Total 53.3 2.3 44.4 100.0 9,239 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. 44 • Characteristics of Respondents Table 3.5.2 Employment status: Men Percent distribution of men age 15-49 by employment status, according to background characteristics, Liberia 2013 Background characteristic Employed in the 12 months preceding the survey Not employed in the 12 months preceding the survey Total Number of men Currently employed1 Not currently employed Age 15-19 32.3 2.3 65.3 100.0 890 20-24 63.2 4.1 32.6 100.0 696 25-29 82.6 2.8 14.6 100.0 673 30-34 93.2 1.4 5.4 100.0 575 35-39 96.3 1.9 1.8 100.0 469 40-44 92.1 2.1 5.8 100.0 482 45-49 95.5 1.3 3.3 100.0 332 Marital status Never married 48.6 3.2 48.2 100.0 1,749 Married or living together 91.9 1.8 6.3 100.0 2,218 Divorced/separated/widowed 95.9 2.3 1.8 100.0 151 Number of living children 0 47.5 3.3 49.1 100.0 1,634 1-2 86.1 2.2 11.7 100.0 1,083 3-4 95.7 1.3 3.0 100.0 728 5+ 93.0 1.8 5.2 100.0 673 Residence Urban 67.9 2.3 29.7 100.0 2,413 Greater Monrovia 66.8 2.0 31.2 100.0 1,433 Other urban 69.6 2.8 27.6 100.0 980 Rural 81.7 2.5 15.7 100.0 1,705 Region North Western 87.3 1.1 11.4 100.0 367 South Central 69.7 2.0 28.3 100.0 2,149 South Eastern A 84.6 3.4 12.0 100.0 254 South Eastern B 71.7 3.2 25.0 100.0 288 North Central 74.9 3.1 22.0 100.0 1,060 County Bomi 71.2 0.6 27.7 100.0 97 Bong 87.2 0.8 11.9 100.0 389 Gbarpolu 93.7 0.9 5.4 100.0 94 Grand Bassa 83.1 3.7 13.2 100.0 204 Grand Cape Mount 92.8 1.5 5.7 100.0 176 Grand Gedeh 77.8 4.5 17.7 100.0 82 Grand Kru 80.0 4.6 15.5 100.0 110 Lofa 58.8 3.9 37.3 100.0 219 Margibi 69.1 2.0 29.0 100.0 364 Maryland 57.6 1.8 40.7 100.0 123 Montserrado 68.1 1.8 30.1 100.0 1,582 Nimba 72.1 4.8 23.2 100.0 451 River Cess 93.6 2.9 3.4 100.0 64 River Gee 87.2 4.0 8.8 100.0 55 Sinoe 84.3 2.9 12.7 100.0 108 Education No education 91.2 1.6 7.1 100.0 533 Primary 67.5 1.7 30.8 100.0 1,202 Secondary and higher 72.8 2.9 24.3 100.0 2,383 Wealth quintile Lowest 85.8 2.2 11.9 100.0 749 Second 79.3 2.2 18.5 100.0 753 Middle 76.7 2.4 21.0 100.0 728 Fourth 65.0 2.7 32.3 100.0 864 Highest 65.7 2.5 31.8 100.0 1,024 Total 73.6 2.4 23.9 100.0 4,118 Note: Total includes 1 case for which information on employment is 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 • 45 The proportion of women and men in the 15-19 age groups who are currently employed is lower than those in older age groups, a finding that is partially due to the fact that many in this age cohort are students. Women and men who are divorced, separated, or widowed are more likely to be currently employed (67 percent and 96 percent, respectively) than other women and men, especially those who have never been married. Women and men with no children are less likely to be currently employed than those who have children. This finding may be linked to the fact that the former are typically younger than those with children. A higher percentage of rural women and men (59 percent and 82 percent, respectively) are currently employed than their urban counterparts (50 percent and 68 percent, respectively). By county, there are substantial differentials in women’s and men’s employment status. Women in Gbarpolu and Bong (78 and 72 percent, respectively) are more likely to be currently employed than women in other counties (40-60 percent); men in Gbarpolu, River Cess, and Grand Cape Mount (94 percent, 94 percent, and 93 percent, respectively) are more likely than men in other counties to be currently employed (58-87 percent). Women and men with no education were more likely to be currently employed (65 percent and 91 percent, respectively) than women and men who have attended school (46-50 percent and 68-73 percent, respectively). The proportion of women who were currently employed decreased with increasing wealth quintile. Among men, a similar trend was observed. Sixty-three percent of women in the lowest wealth quintile were currently employed compared with 46 percent in the highest wealth quintile. For men, the proportion currently employed ranged from 86 percent in the lowest wealth quintile to 65-66 percent in the highest two wealth quintiles. 3.6 OCCUPATION Respondents who were currently employed or who had worked in the 12 months preceding the survey were asked to specify their occupation. Information on the current occupation of employed women and men is shown in Tables 3.6.1 and 3.6.2. Women are most likely to be employed in sales and services (49 percent), followed by agriculture (42 percent). Men are most commonly employed in agriculture (40 percent), unskilled manual labour (15 percent), sales and services (14 percent), and skilled manual labor (14 percent). Four percent of women and 10 percent of men had professional, technical, or managerial occupations. Urban women are most often employed in sales and services (66 percent). Among urban men, the most common occupations are agriculture and sales and services (22 percent each). In rural areas, the majority of women (69 percent) and men (62 percent) are employed in agriculture. By county, Lofa has the highest percentage of women in agricultural occupations (84 percent), while Bong has the highest percentage of men working in agriculture (74 percent). Montserrado has the highest percentage of both women and men in sales and services (80 percent and 25 percent, respectively). Additionally, Montserrado has the highest percentages of women and men employed in skilled manual labor (5 percent and 24 percent, respectively). Montserrado, Maryland, and Margibi have the highest proportion of women in professional, technical, and managerial occupations (6 percent); Montserrado has the highest proportion of men in those occupations (18 percent). Occupation also varies with level of education. Eleven percent of women and 17 percent of men with at least some secondary education are employed in the professional, technical, and managerial sector. Women and men with no education or only a primary education most commonly work in the agricultural sector. Employed women and men in the lowest wealth quintile are concentrated in agricultural occupations (80 percent and 74 percent, respectively). Sales and services are the most common occupations among women in the highest two wealth quintiles (76 to 85 percent). Men in the highest wealth quintile are most commonly employed in professional, technical, or managerial positions (26 percent). 46 • Characteristics of Respondents 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 2013 Background characteristic Profes- sional/ technical/ managerial Clerical Sales and services Skilled manual Unskilled manual Domestic service Agriculture Other Total Number of women Age 15-19 1.4 0.6 45.7 3.4 1.7 0.6 45.7 0.9 100.0 546 20-24 1.4 1.4 52.6 1.8 2.1 1.2 39.4 0.2 100.0 743 25-29 2.8 1.3 56.4 2.7 0.7 0.2 35.9 0.0 100.0 975 30-34 4.8 0.3 49.5 2.7 2.4 0.4 39.9 0.0 100.0 806 35-39 3.3 1.4 53.2 1.8 1.7 0.7 37.7 0.2 100.0 877 40-44 4.8 1.2 42.6 2.1 2.1 0.4 46.7 0.1 100.0 635 45-49 8.5 0.0 34.6 0.6 1.2 0.2 54.5 0.1 100.0 554 Marital status Never married 4.3 2.4 55.6 3.5 2.0 1.1 30.6 0.5 100.0 895 Married or living together 3.4 0.4 46.0 1.8 1.5 0.5 46.3 0.1 100.0 3,542 Divorced/separated/ widowed 4.6 1.9 55.7 2.4 2.0 0.3 32.9 0.2 100.0 701 Number of living children 0 4.4 1.5 52.3 6.0 1.8 0.2 33.2 0.6 100.0 634 1-2 4.6 1.6 56.8 2.1 1.6 0.7 32.5 0.2 100.0 1,823 3-4 3.7 0.6 49.9 1.4 1.9 0.3 42.0 0.1 100.0 1,456 5+ 2.0 0.1 34.7 1.3 1.4 0.8 59.6 0.0 100.0 1,223 Residence Urban 5.6 1.5 66.1 3.4 1.0 0.8 21.4 0.2 100.0 2,952 Greater Monrovia 6.9 2.1 83.0 5.0 0.4 0.6 1.8 0.1 100.0 1,742 Other urban 3.7 0.5 41.8 1.0 1.9 1.2 49.6 0.3 100.0 1,210 Rural 1.1 0.2 25.9 0.6 2.6 0.2 69.2 0.2 100.0 2,185 Region North Western 1.4 0.1 38.2 0.9 3.0 0.2 55.9 0.2 100.0 502 South Central 5.7 1.8 70.4 3.9 1.7 0.6 15.8 0.1 100.0 2,499 South Eastern A 2.6 0.6 43.7 1.5 1.3 0.7 48.9 0.7 100.0 235 South Eastern B 2.9 0.8 40.3 0.6 2.5 0.7 51.5 0.8 100.0 299 North Central 1.6 0.0 21.5 0.4 1.1 0.6 74.8 0.1 100.0 1,602 County Bomi 0.8 0.4 47.9 2.8 4.9 0.6 42.2 0.0 100.0 104 Bong 0.7 0.0 18.4 0.3 1.1 0.3 79.3 0.0 100.0 654 Gbarpolu 2.7 0.0 23.5 0.5 1.3 0.3 70.9 0.8 100.0 143 Grand Bassa 1.1 0.4 32.7 1.3 2.4 1.4 60.6 0.0 100.0 250 Grand Cape Mount 0.9 0.0 42.5 0.4 3.2 0.0 53.0 0.0 100.0 255 Grand Gedeh 5.0 0.4 42.6 3.3 1.4 0.4 46.4 0.6 100.0 81 Grand Kru 0.1 0.0 49.7 0.0 0.1 0.0 50.1 0.0 100.0 110 Lofa 0.9 0.0 12.9 0.3 0.9 0.0 84.3 0.4 100.0 251 Margibi 6.0 1.5 42.8 1.5 8.5 0.0 39.5 0.2 100.0 311 Maryland 6.0 1.8 37.0 0.8 4.4 1.4 46.9 1.6 100.0 126 Montserrado 6.3 2.0 79.7 4.6 0.5 0.5 6.3 0.1 100.0 1,938 Nimba 2.7 0.0 27.5 0.4 1.1 1.1 67.2 0.0 100.0 696 River Cess 0.8 0.0 33.1 0.4 0.8 0.1 64.8 0.0 100.0 74 River Gee 1.3 0.0 30.3 1.3 2.6 0.4 63.5 0.7 100.0 62 Sinoe 1.9 1.5 54.9 0.5 1.8 1.5 36.6 1.3 100.0 79 Education No education 0.3 0.0 35.3 1.0 2.1 0.4 60.6 0.1 100.0 2,079 Primary 1.1 0.1 47.0 1.6 1.6 0.7 47.7 0.2 100.0 1,466 Secondary and higher 10.6 2.9 68.8 4.2 1.1 0.5 11.6 0.3 100.0 1,592 Wealth quintile Lowest 0.7 0.1 16.7 0.7 1.8 0.1 79.9 0.0 100.0 1,036 Second 1.1 0.1 23.9 0.3 1.6 0.2 72.6 0.3 100.0 1,010 Middle 2.7 0.0 41.1 0.6 3.0 0.7 51.5 0.3 100.0 979 Fourth 3.8 0.4 84.5 3.5 1.5 0.3 5.9 0.1 100.0 1,064 Highest 10.1 4.0 76.4 5.7 0.5 1.4 1.6 0.3 100.0 1,048 Total 3.7 0.9 49.0 2.2 1.7 0.5 41.7 0.2 100.0 5,137 Note: Total includes 2 women for whom information on occupation is missing. Characteristics of Respondents • 47 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 2013 Background characteristic Profes- sional/ technical/ managerial Clerical Sales and services Skilled manual Unskilled manual Domestic service Agriculture Other Missing Total Number of men Age 15-19 1.7 2.2 8.5 14.2 17.2 2.5 39.6 0.1 14.0 100.0 308 20-24 10.3 2.6 16.5 14.4 13.6 2.1 35.1 0.9 4.7 100.0 469 25-29 9.4 1.2 16.3 16.2 17.4 0.5 37.1 0.8 1.2 100.0 575 30-34 8.2 1.3 14.3 13.1 17.5 0.5 44.7 0.5 0.0 100.0 544 35-39 9.9 4.8 13.2 11.4 16.1 0.6 43.6 0.3 0.1 100.0 461 40-44 16.6 0.8 15.1 11.7 13.9 0.9 40.3 0.6 0.1 100.0 454 45-49 16.3 2.9 11.5 13.7 10.8 0.1 43.4 1.4 0.0 100.0 321 Marital status Never married 9.5 2.8 13.8 14.7 15.7 2.8 33.0 0.4 7.2 100.0 906 Married or living together 10.6 2.0 14.1 13.0 14.8 0.2 44.1 0.8 0.3 100.0 2,077 Divorced/ separated/ widowed 12.7 0.2 15.4 14.8 22.0 0.1 34.1 0.0 0.6 100.0 149 Number of living children 0 7.7 3.1 13.6 14.5 16.3 2.4 34.0 0.5 7.8 100.0 830 1-2 12.7 2.1 17.3 15.7 17.2 0.6 33.4 0.4 0.8 100.0 957 3-4 9.8 1.0 13.8 13.5 13.6 0.1 46.5 1.7 0.0 100.0 706 5+ 11.1 2.4 10.0 9.3 13.6 0.7 52.7 0.2 0.0 100.0 638 Residence Urban 14.8 3.6 22.3 19.8 12.8 1.5 21.8 0.9 2.4 100.0 1,696 Greater Monrovia 19.8 5.1 26.2 25.5 11.7 1.7 6.0 0.8 3.1 100.0 986 Other uUrban 7.8 1.6 17.0 11.9 14.3 1.3 43.7 1.1 1.4 100.0 709 Rural 5.2 0.5 4.3 6.2 18.5 0.3 62.4 0.3 2.2 100.0 1,436 Region North Western 7.2 0.7 7.1 11.2 22.6 0.4 46.6 0.4 3.8 100.0 325 South Central 15.4 3.9 21.2 20.5 13.8 1.2 20.1 0.9 3.1 100.0 1,541 South Eastern A 6.6 0.9 7.9 7.7 26.6 0.6 46.4 0.1 3.3 100.0 223 South Eastern B 6.2 0.9 7.6 6.5 26.3 1.2 49.6 0.5 1.2 100.0 216 North Central 4.4 0.2 6.8 5.1 9.7 0.7 71.9 0.5 0.4 100.0 827 County Bomi 13.7 0.7 11.2 15.6 22.7 0.5 33.1 0.0 2.6 100.0 69 Bong 3.2 0.5 7.4 5.4 9.2 0.0 73.7 0.5 0.0 100.0 343 Gbarpolu 7.3 0.9 8.8 9.8 14.2 0.0 58.7 0.0 0.2 100.0 89 Grand Bassa 1.3 1.3 10.6 12.6 23.0 0.0 50.2 1.0 0.0 100.0 177 Grand Cape Mount 4.5 0.7 4.5 10.0 27.0 0.6 45.7 0.8 6.2 100.0 166 Grand Gedeh 9.0 1.4 7.3 8.6 28.5 0.9 41.3 0.3 2.6 100.0 67 Grand Kru 7.6 1.5 5.0 4.7 32.0 2.8 45.4 0.0 0.9 100.0 93 Lofa 12.6 0.0 3.6 6.7 2.7 0.0 71.1 1.9 1.5 100.0 137 Margibi 13.4 2.6 13.5 11.2 11.5 0.7 39.2 1.6 6.3 100.0 258 Maryland 7.1 0.8 10.2 7.5 13.9 0.0 58.3 1.6 0.5 100.0 73 Montserrado 18.1 4.6 24.7 23.9 12.9 1.5 10.8 0.7 2.8 100.0 1,106 Nimba 2.4 0.0 7.5 4.3 13.0 1.8 70.5 0.0 0.5 100.0 347 River Cess 4.4 0.4 4.4 6.9 20.7 0.0 56.4 0.0 6.9 100.0 62 River Gee 2.2 0.0 8.4 8.4 33.9 0.0 44.5 0.0 2.7 100.0 50 Sinoe 6.4 0.9 10.5 7.6 29.1 0.7 43.4 0.0 1.4 100.0 94 Education No education 0.7 0.0 7.2 13.8 14.5 0.4 63.0 0.4 0.0 100.0 495 Primary 1.5 0.2 9.1 9.4 15.9 0.2 59.4 0.6 3.7 100.0 832 Secondary and higher 17.2 3.7 18.2 15.5 15.5 1.5 25.5 0.7 2.3 100.0 1,805 Wealth quintile Lowest 2.0 0.0 1.8 2.8 17.4 0.1 73.8 0.3 1.6 100.0 659 Second 4.5 0.4 3.6 5.9 16.7 0.6 65.6 0.4 2.2 100.0 613 Middle 6.3 1.1 16.0 14.6 15.0 0.7 42.8 1.5 2.0 100.0 575 Fourth 11.9 1.9 27.1 23.9 13.6 2.2 15.4 0.9 3.2 100.0 585 Highest 25.6 6.8 22.3 20.9 14.3 1.3 5.8 0.3 2.6 100.0 699 Total 10.4 2.2 14.1 13.6 15.4 1.0 40.4 0.7 2.3 100.0 3,132 48 • Characteristics of Respondents 3.7 TYPE OF EMPLOYMENT Table 3.7 shows the percent distribution of women employed in the 12 months preceding the survey by type of earnings, type of employer, and continuity of employment, according to type of employment (agricultural or nonagricultural). Thirty percent of women engaged in agricultural work and 78 percent of women engaged in nonagricultural work are paid in cash only. Most of the remaining women in these occupational categories are not paid (46 percent for agriculture workers and 15 percent for nonagricultural workers). However, 19 percent of women working in agriculture and 5 percent of women in nonagricultural occupations received cash and in-kind earnings. Eighty percent of women engaged in agricultural work and 75 percent of women engaged in nonagricultural work are self-employed. Women in agricultural work are more likely than those employed in nonagricultural work to be employed by a family member (17 percent and 10 percent, respectively). Fifty-seven percent of women engaged in agricultural work are employed all year, compared with 81 percent of women engaged in nonagricultural work. Forty percent of women engaged in agricultural activities work seasonally, while 11 percent of those who are nonagricultural workers are seasonally employed. 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 2013 Employment characteristic Agricultural work Nonagricultural work Total Type of earnings Cash only 30.3 78.3 58.3 Cash and in-kind 18.9 5.4 11.0 In-kind only 4.3 1.0 2.3 Not paid 46.4 15.2 28.2 Missing 0.2 0.1 0.1 Total 100.0 100.0 100.0 Type of employer Employed by family member 16.7 10.3 13.0 Employed by nonfamily member 3.6 14.7 10.0 Self-employed 79.6 74.7 76.8 Missing 0.1 0.3 0.2 Total 100.0 100.0 100.0 Continuity of employment All year 56.5 81.4 71.0 Seasonal 39.8 11.2 23.1 Occasional 3.7 7.4 5.8 Total 100.0 100.0 100.0 Number of women employed during the last 12 months 2,144 2,992 5,137 Note: Total includes 2 women with missing information on type of employment who are not shown separately. 3.8 HEALTH INSURANCE COVERAGE The 2013 LDHS collected data on respondents’ health insurance coverage (Tables 3.8.1 and 3.8.2). The majority of women (96 percent) and men (93 percent) report that they do not have health insurance. Four percent of women have employer-based insurance, and less than 1 percent is covered by other mechanisms. Six percent of men have employer-based insurance, 1 percent through social security, and less than 1 percent by other mechanisms. For both women and men, differences in insurance coverage by background characteristics are Characteristics of Respondents • 49 minimal, with the exception that 20 percent of women and 26 percent of men in Margibi, and 23 percent of men in Bomi, have health insurance through employer-based plans. Table 3.8.1 Health insurance coverage: Women Percentage of women age 15-49 with specific types of health insurance coverage, according to background characteristics, Liberia 2013 Background characteristic Social security Employer- based insurance Mutual health organization/ community- based insurance Privately purchased commercial insurance Other None Number of women Age 15-19 0.6 4.6 0.0 0.2 0.0 94.6 2,080 20-24 0.1 2.0 0.0 0.2 0.0 97.7 1,642 25-29 0.0 1.8 0.0 0.0 0.0 98.2 1,611 30-34 0.2 4.0 0.0 0.1 0.0 95.8 1,199 35-39 1.3 5.1 0.2 0.1 0.0 93.4 1,179 40-44 0.4 3.9 0.0 0.4 0.0 95.3 812 45-49 0.6 5.2 0.8 0.4 0.0 93.1 716 Residence Urban 0.7 3.9 0.2 0.2 0.0 95.1 5,633 Greater Monrovia 0.3 3.1 0.2 0.2 0.0 96.2 3,361 Other urban 1.2 5.3 0.1 0.2 0.0 93.4 2,272 Rural 0.1 3.1 0.0 0.1 0.0 96.7 3,606 Region North Western 0.1 2.1 0.0 0.2 0.0 97.6 837 South Central 0.4 6.0 0.2 0.2 0.0 93.3 4,854 South Eastern A 0.0 1.6 0.1 0.4 0.1 97.9 483 South Eastern B 0.4 2.4 0.0 0.0 0.0 97.2 577 North Central 0.7 0.0 0.0 0.1 0.0 99.1 2,488 County Bomi 0.0 6.0 0.0 0.2 0.0 93.8 244 Bong 0.0 0.0 0.0 0.2 0.0 99.8 894 Gbarpolu 0.0 0.8 0.0 0.4 0.0 98.8 182 Grand Bassa 0.0 7.2 0.0 0.0 0.0 92.8 434 Grand Cape Mount 0.2 0.5 0.0 0.0 0.0 99.3 412 Grand Gedeh 0.0 1.1 0.0 0.0 0.0 98.9 167 Grand Kru 0.5 3.2 0.0 0.1 0.0 96.3 217 Lofa 0.0 0.2 0.0 0.0 0.0 99.8 447 Margibi 0.9 19.8 0.1 0.0 0.0 79.3 744 Maryland 0.5 2.6 0.0 0.0 0.0 96.9 257 Montserrado 0.3 3.1 0.2 0.2 0.0 96.2 3,675 Nimba 1.6 0.0 0.0 0.1 0.0 98.2 1,147 River Cess 0.0 0.3 0.0 0.0 0.2 99.5 135 River Gee 0.0 0.2 0.0 0.0 0.0 99.8 103 Sinoe 0.0 3.1 0.2 1.0 0.0 95.7 182 Education No education 0.1 2.1 0.0 0.1 0.0 97.7 3,066 Primary 0.5 3.4 0.0 0.0 0.0 96.0 2,875 Secondary and higher 0.7 5.2 0.2 0.3 0.0 93.6 3,298 Wealth quintile Lowest 0.0 0.3 0.0 0.0 0.0 99.7 1,581 Second 0.1 0.9 0.0 0.1 0.0 98.8 1,624 Middle 0.0 4.2 0.0 0.1 0.0 95.6 1,779 Fourth 0.7 4.5 0.0 0.1 0.0 94.8 2,047 Highest 1.0 6.7 0.4 0.4 0.0 91.6 2,207 Total 0.4 3.6 0.1 0.2 0.0 95.7 9,239 50 • Characteristics of Respondents Table 3.8.2 Health insurance coverage: Men Percentage of men age 15-49 with specific types of health insurance coverage, according to background characteristics, Liberia 2013 Background characteristic Social security Employer based insurance Mutual health organization/ community based insurance Privately purchased commercial insurance Other None Number of men Age 15-19 0.4 5.5 0.0 0.0 0.0 94.1 890 20-24 1.1 4.1 0.0 0.6 0.3 94.6 696 25-29 0.7 6.1 0.9 0.1 0.2 92.7 673 30-34 0.3 4.5 0.0 0.7 0.0 94.5 575 35-39 0.6 7.3 0.0 0.0 0.0 92.2 469 40-44 0.5 9.5 0.2 1.1 0.0 88.9 482 45-49 3.1 7.9 0.0 1.0 0.0 88.3 332 Residence Urban 0.9 6.7 0.3 0.7 0.1 91.6 2,413 Greater Monrovia 0.9 5.6 0.4 1.1 0.1 92.4 1,433 Other urban 0.9 8.4 0.1 0.0 0.2 90.6 980 Rural 0.7 5.2 0.0 0.1 0.0 94.3 1,705 Region North Western 1.1 7.7 0.0 0.0 0.0 92.1 367 South Central 0.9 9.3 0.3 0.7 0.2 89.0 2,149 South Eastern A 0.6 3.7 0.0 0.3 0.0 95.4 254 South Eastern B 0.6 2.7 0.0 0.2 0.0 96.5 288 North Central 0.5 0.6 0.0 0.0 0.0 98.8 1,060 County Bomi 0.0 23.4 0.0 0.0 0.0 76.6 97 Bong 1.0 1.4 0.0 0.0 0.0 97.7 389 Gbarpolu 0.8 0.2 0.0 0.0 0.0 98.9 94 Grand Bassa 0.9 9.7 0.0 0.0 0.0 89.7 204 Grand Cape Mount 1.9 3.0 0.0 0.0 0.0 97.0 176 Grand Gedeh 0.8 1.5 0.0 0.7 0.0 97.0 82 Grand Kru 1.0 0.3 0.0 0.4 0.0 98.3 110 Lofa 0.0 0.6 0.0 0.0 0.0 99.4 219 Margibi 1.1 26.3 0.3 0.0 0.6 72.0 364 Maryland 0.6 5.3 0.0 0.2 0.0 94.0 123 Montserrado 0.9 5.3 0.4 1.0 0.1 92.8 1,582 Nimba 0.4 0.0 0.0 0.1 0.0 99.5 451 River Cess 0.4 1.7 0.0 0.2 0.0 97.7 64 River Gee 0.0 1.5 0.0 0.0 0.0 98.5 55 Sinoe 0.7 6.5 0.0 0.0 0.0 92.8 108 Education No education 0.0 1.1 0.0 0.0 0.0 98.9 533 Primary 0.7 4.7 0.0 0.0 0.2 94.9 1,202 Secondary and higher 1.0 7.9 0.3 0.7 0.1 90.3 2,383 Wealth quintile Lowest 0.1 0.8 0.0 0.0 0.0 99.1 749 Second 0.1 1.3 0.0 0.1 0.0 98.5 753 Middle 1.4 6.6 0.0 0.0 0.0 92.5 728 Fourth 1.6 9.6 0.3 0.1 0.0 89.4 864 Highest 0.8 10.2 0.4 1.5 0.3 86.8 1,024 Total 0.8 6.1 0.2 0.4 0.1 92.7 4,118 3.9 USE OF TOBACCO The 2013 LDHS collected information on women’s and men’s tobacco use. Tobacco use has been shown to adversely affect both the health of users and those around them and is considered by the World Health Organization to be the primary cause of preventable deaths worldwide (WHO, 2011b). Characteristics of Respondents • 51 Tables 3.9.1 and 3.9.2 present the percentages of women and men who smoke cigarettes or a pipe or use other tobacco products (e.g., snuff). Table 3.9.2 also includes information obtained from male cigarette smokers on number of cigarettes smoked in the 24 hours before the interview. Almost all women (99 percent) and a large majority of men (90 percent) age 15-49 reported that they do not use tobacco. Given the small number of women who report using tobacco, it is not informative to examine the pattern of tobacco use among women by background characteristics. Table 3.9.1 Use of tobacco: Women Percentage of women age 15-49 who smoke cigarettes or a pipe or use other tobacco products, according to background characteristics and maternity status, Liberia 2013 Background characteristic Uses tobacco Does not use tobacco Number of women Cigarettes Other tobacco Age 15-19 0.2 0.0 99.8 2,080 20-24 0.2 0.1 99.8 1,642 25-29 0.0 0.1 99.9 1,611 30-34 0.5 0.2 99.3 1,199 35-39 0.1 0.6 99.3 1,179 40-44 0.3 1.6 98.1 812 45-49 2.2 2.6 95.3 716 Maternity status Pregnant 0.1 0.1 99.8 765 Breastfeeding (not pregnant) 0.1 0.3 99.6 2,170 Neither 0.4 0.6 99.0 6,303 Residence Urban 0.3 0.2 99.5 5,633 Greater Monrovia 0.5 0.1 99.5 3,361 Other urban 0.0 0.3 99.7 2,272 Rural 0.4 0.9 98.6 3,606 Region North Western 0.4 1.3 98.3 837 South Central 0.4 0.2 99.4 4,854 South Eastern A 0.6 0.6 98.9 483 South Eastern B 0.5 1.7 97.8 577 North Central 0.2 0.4 99.5 2,488 Education No education 0.5 1.2 98.3 3,066 Primary 0.3 0.2 99.5 2,875 Secondary and higher 0.2 0.1 99.7 3,298 Wealth quintile Lowest 0.7 1.2 98.1 1,581 Second 0.2 0.8 99.1 1,624 Middle 0.2 0.4 99.4 1,779 Fourth 0.7 0.1 99.2 2,047 Highest 0.0 0.1 99.9 2,207 Total 0.3 0.5 99.2 9,239 Among men, cigarettes are the most common form of tobacco use. Tobacco use generally increases with age and is more common among men living in rural areas than urban areas. Tobacco use among men decreases with increasing education and wealth quintile. T ab le 3 .9 .2 U se o f t ob ac co : M en P er ce nt ag e of m en a ge 1 5- 49 w ho s m ok e ci ga re tte s or a p ip e or u se o th er to ba cc o pr od uc ts a nd th e pe rc en t d is tr ib ut io n of c ig ar et te s m ok er s by n um be r of c ig ar et te s sm ok ed in p re ce di ng 2 4 ho ur s, a cc or di ng to b ac kg ro un d ch ar ac te ris tic s, L ib er ia 2 01 3 B ac kg ro un d ch ar ac te ris tic U se s to ba cc o D oe s no t us e to ba cc o N um be r of m en P er ce nt d is tri bu tio n of m en w ho s m ok e ci ga re tte s by n um be r o f ci ga re tte s sm ok ed in th e pa st 2 4 ho ur s T ot al N um be r of ci ga re tte sm ok er s C ig ar et te s P ip e C he w in g to ba cc o S nu ff C ig ar O th er to ba cc o 0 1- 2 3- 5 6- 9 10 + D on 't kn ow / m is si ng A ge 15 -1 9 0. 6 0. 0 0. 1 0. 0 0. 0 0. 0 99 .4 89 0 * * * * * * 10 0. 0 5 20 -2 4 1. 6 0. 3 0. 1 0. 0 0. 1 0. 5 97 .7 69 6 * * * * * * 10 0. 0 11 25 -2 9 6. 1 0. 0 0. 4 0. 1 0. 2 0. 3 93 .6 67 3 0. 0 33 .4 44 .8 10 .8 11 .1 0. 0 10 0. 0 41 30 -3 4 13 .4 0. 0 0. 8 1. 0 0. 4 1. 6 85 .0 57 5 0. 0 17 .1 33 .3 10 .4 38 .0 1. 2 10 0. 0 77 35 -3 9 20 .8 0. 0 0. 5 0. 5 0. 4 0. 7 78 .6 46 9 0. 0 14 .9 44 .9 18 .9 19 .5 1. 8 10 0. 0 98 40 -4 4 18 .2 0. 0 0. 4 0. 5 0. 3 0. 7 80 .9 48 2 0. 0 17 .1 34 .1 25 .5 22 .6 0. 6 10 0. 0 88 45 -4 9 22 .8 0. 0 1. 5 0. 0 0. 3 0. 7 77 .0 33 2 0. 0 9. 4 49 .3 18 .4 22 .9 0. 0 10 0. 0 76 R es id en ce U rb an 5. 9 0. 1 0. 1 0. 3 0. 1 0. 3 93 .3 2, 41 3 0. 0 20 .6 41 .9 18 .2 18 .9 0. 4 10 0. 0 14 3 G re at er M on ro vi a 4. 5 0. 0 0. 0 0. 5 0. 0 0. 4 94 .5 1, 43 3 * * * * * * 10 0. 0 65 O th er u rb an 7. 9 0. 2 0. 2 0. 0 0. 3 0. 3 91 .6 98 0 0. 0 21 .4 43 .3 15 .4 19 .2 0. 7 10 0. 0 78 R ur al 14 .8 0. 0 0. 9 0. 2 0. 3 0. 9 84 .8 1, 70 5 0. 4 16 .3 39 .1 17 .3 25 .5 1. 4 10 0. 0 25 3 R eg io n N or th W es te rn 15 .7 0. 0 1. 7 0. 2 0. 3 0. 4 83 .9 36 7 0. 0 12 .7 30 .1 19 .2 33 .4 4. 6 10 0. 0 58 S ou th C en tr al 6. 6 0. 0 0. 1 0. 4 0. 0 0. 5 92 .6 2, 14 9 0. 8 19 .9 39 .4 18 .3 20 .5 1. 1 10 0. 0 14 3 S ou th E as te rn A 16 .2 0. 0 0. 8 0. 2 1. 7 2. 3 82 .4 25 4 0. 0 16 .3 41 .7 15 .1 27 .0 0. 0 10 0. 0 41 S ou th E as te rn B 15 .8 0. 0 0. 5 0. 1 0. 3 1. 3 83 .9 28 8 0. 0 17 .3 45 .0 13 .1 24 .6 0. 0 10 0. 0 45 N or th C en tr al 10 .2 0. 2 0. 5 0. 2 0. 1 0. 2 89 .5 1, 06 0 0. 0 18 .7 43 .5 18 .7 19 .1 0. 0 10 0. 0 10 9 Ed uc at io n N o ed uc at io n 20 .0 0. 0 0. 6 1. 2 0. 0 1. 3 78 .5 53 3 1. 1 15 .5 45 .0 17 .4 19 .3 1. 6 10 0. 0 10 6 P rim ar y 12 .6 0. 0 0. 6 0. 0 0. 4 0. 5 87 .1 1, 20 2 0. 0 18 .8 38 .5 20 .3 21 .2 1. 2 10 0. 0 15 2 S ec on da ry a nd hi gh er 5. 8 0. 1 0. 3 0. 2 0. 2 0. 4 93 .7 2, 38 3 0. 0 18 .6 38 .0 14 .8 28 .2 0. 4 10 0. 0 13 7 W ea lth q ui nt ile Lo w es t 16 .6 0. 0 0. 8 0. 2 0. 3 1. 1 83 .0 74 9 0. 0 14 .7 43 .6 17 .5 24 .2 0. 0 10 0. 0 12 4 S ec on d 14 .2 0. 0 1. 1 0. 0 0. 3 0. 8 85 .4 75 3 1. 0 18 .9 33 .4 18 .0 25 .9 2. 8 10 0. 0 10 7 M id dl e 13 .0 0. 0 0. 5 0. 1 0. 5 0. 1 86 .7 72 8 0. 0 19 .4 44 .4 12 .3 23 .3 0. 6 10 0. 0 95 Fo ur th 3. 7 0. 2 0. 0 0. 7 0. 0 0. 8 94 .9 86 4 (0 .0 ) (2 6. 2) (4 6. 2) (1 6. 5) (9 .4 ) (1 .7 ) 10 0. 0 32 H ig he st 3. 6 0. 0 0. 0 0. 3 0. 0 0. 2 96 .0 1, 02 4 * * * * * * 10 0. 0 37 T ot al 9. 6 0. 0 0. 4 0. 3 0. 2 0. 6 89 .8 4, 11 8 0. 3 17 .9 40 .1 17 .6 23 .1 1. 0 10 0. 0 39 5 N ot e: F ig ur es in p ar en th es es a re b as ed o n 25 -4 9 un w ei gh te d ca se s. A n as te ris k in di ca te s th at a fi gu re is b as ed o n fe w er th an 2 5 un w ei gh te d ca se s an d ha s be en s up pr es se d. 52 • Characteristics of Respondents Characteristics of Respondents • 53 3.10 USE OF ALCOHOL The 2013 LDHS collected information on women’s and men’s alcohol use. Tables 3.10.1 and 3.10.2 p

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